Comparing Attention to Socially-Relevant Stimuli in Autism Spectrum Disorder and Developmental Coordination Disorder

Abstract

Difficulties with social interaction have been reported in both children with an autism spectrum disorder (ASD) and children with developmental coordination disorder (DCD), although these disorders have very different diagnostic characteristics. To date, assessment of social skills in a DCD population has been limited to paper-based assessment or parent report. The present study employed eye tracking methodology to examine how children attend to socially-relevant stimuli, comparing 28 children with DCD, 28 children with ASD and 26 typically-developing (TD) age-matched controls (aged 7–10). Eye movements were recorded while children viewed 30 images, half of which were classed as ‘Individual’ (one person in the scene, direct gaze) and the other half were ‘Social’ (more naturalistic scenes showing an interaction). Children with ASD spent significantly less time looking at the face/eye regions in the images than TD children, but children with DCD performed between the ASD and TD groups in this respect. Children with DCD demonstrated a reduced tendency to follow gaze, in comparison to the ASD group. Our findings confirm that social atypicalities are present in both ASD and to a lesser extent DCD, but follow a different pattern. Future research would benefit from considering the developmental nature of the observed findings and their implications for support.

Full text

Comparing Attention to Socially-Relevant Stimuli in Autism
Spectrum Disorder and Developmental Coordination Disorder
Emma Sumner
1
&Hayley C. Leonard
2
&Elisabeth L. Hill
3
#The Author(s) 2018. This article is an open access publication
Abstract
Difficulties with social interaction have been reported in both children with an autism spectrum disorder (ASD) and children with
developmental coordination disorder (DCD), although these disorders have very different diagnostic characteristics. To date,
assessment of social skills in a DCD population has been limited to paper-based assessment or parent report. The present study
employed eye tracking methodology to examine how children attend to socially-relevant stimuli, comparing 28 children with DCD,
28 children with ASD and 26 typically-developing (TD) age-matched controls (aged 7–10). Eye movements were recorded while
children viewed 30 images, half of which were classed as ‘Individual’(one person in the scene, direct gaze) and the other half were
‘Social’(more naturalistic scenes showing an interaction). Children with ASD spent significantly less time looking at the face/eye
regions in the images than TD children, but children with DCD performed between the ASD and TD groups in this respect.
Children with DCD demonstrated a reduced tendency to follow gaze, in comparison to the ASD group. Our findings confirm that
social atypicalities are present in both ASD and to a lesser extent DCD, but follow a different pattern. Future research would benefit
from considering the developmental nature of the observed findings and their implications for support.
Keywords Autism spectrum disorder .Developmental coordination disorder .Eye tracking .Face processing .Social .Attention
The development of social skills, including socio-
cognitive abilities and being able to establish and main-
tain friendships, plays a major role throughout develop-
ment. Interacting with others requires interpreting a range
of behaviours, both verbal and non-verbal. For example,
the ability to interpret gaze can provide subtle clues as to
what another person is thinking or attending to (Thorup
et al. 2016), and developing selective attention to socially-
relevant information, such as facial expressions, is crucial
to understanding others and their intentions (Shepherd
2010). However, the task of processing these non-verbal
cues is difficult; the information changes quickly and of-
ten, and thus may be more challenging than processing
facial identity. Indeed, the complexity of face processing
has been acknowledged in neuropsychological and neural
models (Bruce and Young 1986; Haxby et al. 2000).
Notably, processing this changeable information (i.e., ex-
pression, gaze) relies on attending to the relevant parts of
thefaceattherighttime,andafailuretodosoislikelyto
result in problems in social interaction.
Difficulties with social interaction are not uncommon. In
particular, individuals with autism spectrum disorder (ASD)
are diagnosed based on marked impairments in social com-
munication and interaction, along with restricted interests and
repetitive behaviours (American Psychiatric Association
[APA], 2013). In addition, although diagnosed on the basis
of motor coordination difficulties (APA, 2013), research has
indicated that children with developmental coordination dis-
order (DCD) also experience a range of social problems
(Leonard 2016). The aim of the current study is to explore
how children with ASD and children with DCD view
socially-relevant information to understand whether the social
*Emma Sumner
e.sumner@ucl.ac.uk
1
Department of Psychology and Human Development, UCL Institute
of Education, University College London, 25 Woburn Square,
London WC1H 0AA, UK
2
School of Psychology, University of Surrey, Guildford, UK
3
Department of Psychology, Goldsmiths, University of London,
London, UK
Journal of Abnormal Child Psychology
https://doi.org/10.1007/s10802-017-0393-3

problems evident in the two disorders rely on similar cognitive
processing of social information. Increasing our understand-
ing of the processes underlying similar behavioural outcomes
in neurodevelopmental disorders is a vital step in improving
diagnosis and treatment, allowing more focused interventions.
Research on Social Attention and Face
Processing in ASD
Research has highlighted difficulties with face recognition (see
Chawarska et al. 2003) and problems with accurately process-
ing emotions and gaze behaviour (Corbett et al. 2014;Dawson
et al. 2005) as prominent characteristics of ASD. Further, dur-
ing the last decade, the increased accessibility and accuracy of
eye tracking technology has enabled more detailed exploration
of how individuals with ASD view socially-relevant informa-
tion (see Falck-Ytter et al. 2013; Guillon et al. 2014,fora
review). Fixations and eye gaze patterns (i.e., scanpaths) pro-
vide a proxy for attention, as eye movements indicate overt
orientation of visual attention. A number of studies have report-
ed reduced attention to social stimuli. In particular, limited gaze
to people and faces has been reported early in development, in
toddlers and infants who are later diagnosed with ASD
(Chawarska et al. 2013; Chawarska and Shic 2009; Sasson
et al. 2011;vonHofstenetal.2009; although see Elsabbagah
et al. 2012). Reduced attention to another person’s face or eyes
is believed to have repercussions for recognising subtle social
cues, such as expressions and gaze (Falck-Ytter et al. 2013)
and, therefore, could be argued to be an explanation for diffi-
culties with social interaction in ASD.
However, inconsistencies exist in the adolescent and adult
ASD literature on social attention and social processing (i.e.,
making sense of social cues, such as gaze). Some studies
report a preference for fixating on non-social parts of a scene
(i.e., the background and not the faces in the scene) when
viewing social scenes in video clips (Klin et al. 2002; Speer
et al. 2007), photographs of human faces (Dalton et al. 2005;
Riby and Hancock 2009;Sassonetal.2007)andnaturalistic
photographs of social scenes (Riby and Hancock 2008). There
have been reports of reduced time looking at the eyes (Dalton
et al. 2005; Riby and Hancock 2008,2009; Sasson et al. 2007)
and Freeth et al. (2010,2011) found individuals with ASD
were slower to initially fixate the face in a photograph.
Slower fixations to the face region were considered to provide
some indication of a reduced interest in social aspects of the
scene. In addition, difficulties with processing social cues
have been reported, as it has been found that adolescents with
ASD rarely spontaneously follow an actor’s gaze in a photo-
graph (Riby et al. 2013; Ristic et al. 2005) and preschoolers
with ASD did not respond to gaze cues to an object shown in
video clips (Vivanti et al. 2014). Others, however, report no
avoidance of the face region, nor problems with gaze follow-
ing in high-functioning young adults with ASD (Fletcher-
Watson et al. 2009; Freeth et al. 2010,2011). A possible ex-
planation for mixed findings may be due to differing method-
ologies, the heterogeneous nature of an ASD population, or
possibly the development of compensatory strategies in some
individuals, in response to social experiences in early life. Of
note, very little is known about the viewing patterns of
primary-aged children with ASD, and knowledge of how this
age group process social information would contribute to the
current body of work seeking to understand the development
of such skills.
Research on Social Skills and Cognition
in DCD
A number of studies have flagged poor social skills in chil-
dren with DCD. Although primarily a motor disorder, re-
search indicates that children with DCD experience addition-
al problems with peer relations (Chen et al. 2009; Dewey
et al. 2002; Poulsen et al. 2007; Smyth and Anderson 2000;
Wagner et al. 2012) and difficulty processing emotions from
the face (Cummins et al. 2005). A recent study by Sumner
and colleagues (Sumner et al. 2016b) directly comparing
children with ASD and those with DCD highlighted that
the two groups were comparable on paper- and laptop-
based face processing tasks in their ability to identify facial
expressions, speech sounds, and gaze; with both groups
performing worse than a control group. In addition, parents
reported lower social functioning (i.e., building friendships,
engaging in play activities) in the DCD and ASD groups
compared to typically-developing children, with ASD chil-
dren the most compromised. The authors were able to dem-
onstrate that motor ability predicted social functioning in
these two clinical groups, providing a possible explanation
for why social difficulties are found in DCD. This is in line
with Campos et al. (2000), who have argued that the devel-
opment of early gross motor skill (sitting, crawling, walking)
provides increasing opportunities for infants to interact with
the world and others. As infants become independent ex-
plorers, through crawling and walking, they develop skills
for social referencing and interaction (Clearfield et al. 2008).
Considering the development of children with DCD, it has
been shown that these children are significantly delayed in
achieving early gross motor milestones (Sumner et al.
2016b) and, therefore, they may well be missing out on vital
opportunities to develop socially. Thus, although social in-
teraction difficulties may appear similar in DCD and ASD,
they may differ in the causal pathways and subsequent de-
velopmental trajectory of social skill development.
The social abilities of children with DCD should be ex-
plored further. To date, no study has used eye tracking
J Abnorm Child Psychol

methodology to examine how children with DCD attend to
socially-relevant stimuli. Although similarities have been
identified between children with DCD and ASD in terms of
the number of correct responses they make when identifying
socially-relevant information, such as expressions and gaze,
(Sumner et al. 2016b), it is possible that this behavioural sim-
ilarity relies on different attention and processing in the two
groups. Given that social difficulties may persist through to
adolescence and adulthood in DCD, there is a need to better
understand the social problems experienced by this popula-
tion, which should increase recognition and inform appropri-
ate intervention.
The Present Study
Direct comparisons of neurodevelopmental disorders can help
to ascertain whether behavioural and cognitive phenotypesare
specific or general to a disorder. The overall aim of the present
study was to employ eye tracking methodology to examine
how children with ASD, those with DCD, and typically-
developing (TD) children view socially-relevant information.
In doing so, we contribute to the existing eye tracking litera-
ture on ASD, which is currently lacking with regards to
knowledge of primary-aged children. We also further our un-
derstanding of DCD by using this methodology, which has not
yet been used to analyse social behaviour within this
population.
In the present study, spontaneous gaze was recorded and
later analysed while participants viewed images classified as
‘Individual’(one person in the scene) and ‘Social’(two or
more people, depicting an interaction). For the ‘Individual’
images, a standard approach from previous research was used,
in which faces are presented in a frontal view, with direct gaze
towards the participants (e.g., Pelphrey et al. 2005; Speer et al.
2007). This allowed a direct comparison of individuals in the
current ASD group to those in previous research in terms of
the relative time spent looking at the eyes or face compared to
other parts of the scene. It also allowed the exploration of the
allocation of attention to these regions of interest in the DCD
group. However, this is not the most naturalistic task, and
therefore the social scenes were included to assess attention
to socially-relevant elements of more ecologically-valid stim-
uli and address the limitations of these more controlled im-
ages. Social scenes used in previous studies (e.g. Riby and
Hancock 2008;Ribyetal.2013)haveusednaturalisticpho-
tographs of people during an interaction, in which gaze is
often averted from the participant and appears more naturalis-
tic between people presented in the scene. The current study
adopted this approach for the ‘Social’stimuli, presenting nat-
uralistic interactions between children. In addition to identify-
ing the regions of interest in social scenes, these stimuli also
allowed for consideration of gaze following behaviour. The
analyses therefore aimed to address a number of research
questions:
1. Do children with ASD, children with DCD, and TD chil-
dren differ in the amount of time they fixate on the face
and eye regions in a social scene?
2. Does symptom severity (i.e., ASD symptomology, and
motor skill in DCD) relate to the amount of time children
fixate the face?
3. Do children with ASD and those with DCD take longer to
first fixate the face region, in comparison to TD children?
4. Do the three groups show evidence of spontaneously fol-
lowing a person’sgaze?
Based on previous research, a number of hypotheses were
proposed. We predicted that children with ASD would fixate
for less time on faces, and the eye region, and be slower to first
fixate the face region than their TD counterparts. It was also
hypothesized that children with ASD would be poorer at fol-
lowing gaze to an object than TD children. Children with
DCD were expected to demonstrate a similar profile to chil-
dren with ASD, although to a lesser extent, and thus perform
below that of the TD group.
Method
Participants
Participants aged 7–10 years formed three groups: children
with ASD, children with DCD, and TD children. Groups were
matched on chronological age (p= 0.15). Importantly, chil-
dren in the two clinical groups (ASD and DCD) had an
existing diagnosis from relevant clinicians external to the re-
search team. Diagnoses were corroborated - and ruled out in
the TD group - using various background measures and the
following inclusion/exclusion criteria applied (see Table 1for
group characteristics):
1. All participants had a Full Scale IQ (FSIQ) ≥80 on the
Wechsler Intelligence Scales for Children (WISC-IV;
Wech sler 2003).
2. Parents completed the lifetime version of the Social
Communication Questionnaire (SCQ, Rutter et al.
2003). The SCQ contains 40 questions, half of which
focus on the behaviour of the child at their present age
and the other half of questions relate to their child’sbe-
haviour during the period of time between their 4th and
5th birthday. A score of 15 and above is suggestive of
ASD symptomology. All children in the ASD group were
required to score ≥15, while all TD children had to score
below the cut-off 15 (i.e., ruling out ASD characteristics
in this group). In fact, all TD children scored below 9 on
JAbnormChildPsychol

the SCQ (note: 72% of the TD group scored <5). The
SCQ was an exploratory measure for the DCD group
and, therefore, no cut-off was applied.
3. Motor competency was assessed using the Movement
Assessment Battery for Children, second edition
(MABC-2; Henderson et al. 2007), a standardised assess-
ment of fine and gross motor skill. Overall test perfor-
mance was converted to a percentile rank (UK norms).
As all children in the DCD group had an existing diagno-
sis, the MABC-2 inclusion criterion for this group was a
score ≤16th percentile. Children in the TD group scored
≥25th percentile. The MABC-2 was an exploratory mea-
sure for the ASD group and thus no exclusion criteria
were applied.
4. Prior to testing, parents completed a screening question-
naire. Parents of children in the ASD and DCD groups
reported no additional diagnoses, such as ADHD, ASD,
or dyslexia, no form of visual or neurological impairment,
nor a general medical condition; parents of children in the
TD groups did not identify diagnoses of any kind.
Thirty-one children with ASD were recruited through spe-
cialist schools and special educational needs units attached to
mainstream schools in South London, and also by advertise-
ments through a charitable organisation, the National Autistic
Society. One child was excluded due to a low FSIQ, two
children were excluded because they had difficulty complet-
ing the eye tracker calibration procedure (following four at-
tempts). The final sample comprised 28 children (24 male)
with ASD. As well as considering information from the
SCQ, children in this group scored ≥7 on Module 3 of the
Autism Diagnostic Observation Schedule (ADOS-2; Lord
et al. 2012), demonstrating a group mean score of 8.67 (stan-
dard deviation, 1.11). ADOS data were not collected for 3
children in the sample because they had undergone their diag-
nostic assessment, which required completing the ADOS,
close to the time of the study. Fourteen children with ASD
(50%) had moderate to significant motor difficulties (≤16th
percentile) as assessed by the MABC-2.
The DCD group initially comprised 34 children, recruited via
an advertisement placed with a charitable foundation, the
Dyspraxia Foundation, and primary schools in South London.
One child was excluded due to a FSIQ below cut-off, and a
further 5 participants were removed from the sample due to
difficulties with eye tracking calibration requirements (again fol-
lowing four attempts to calibrate). Therefore, the final sample
comprised 28 children (21 male) that met the DSM-5 criteria
(APA, 2013) for DCD: motor ability below the level expected
given the child’s age and measured-IQ, motor difficulties were
not explained by medical or neurological condition and were
present in the early developmental period. Of note, 5 children
with DCD (18%) scored above the SCQ cut-off.
1
Thirty-one TD children were recruited from mainstream
primary schools in the South London area. Adhering to the
inclusion/exclusion criteria, six children were excluded from
further study due to scoring below the motor difficulty cut-off
Table 1 Participant characteristics
Characteristics TD (n=25) ASD (n=28) DCD(n=28) F(df) p n
2
p
Post hoc
Gender (m;f) 22;3 24;4 21;7 ––––
Age (in years)
Mean (SD) 9.10 (1.07) 8.58 (1.18) 8.53 (1.16) 1.97 0.15 0.05 All ns
Range 7.70–10.74 7.01–10.91 7.04–10.99 (2, 78)
FSIQ standard score
Mean (SD) 110.64 (10.07) 101.32 (14.32) 95.93 (12.47) 9.30 0.001 0.19 (DCD = ASD) < TD
Range 89–127 80–136 80–126 (2, 78)
MABC2%ile
Mean (SD) 63.20 (22.20) 31.87 (32.42) 3.23 (4.87) 47.03†0.001 0.58 DCD < ASD < TD
Range 25–98 0.01–95 0.01–16
SCQ
Mean (SD) 2.84 (2.67) 22.82 (6.13)
a
9.85 (6.43)
a
92.05 0.001 0.71 TD < DCD < ASD
Range 0–915–38 1–27 (2, 76)
FSIQ = Full Scale IQ from the WISC, M=100, SD = 15. MABC-2 = Movement Assessment Battery for Children, percentile scores; SCQ = Social
Communication Questionnaire.
a
1 missing data point because parents did not return the questionnaire. ns = non-significant. †Nonparametric analyses
conducted due to unequal variances (Kruskal-Wallis Hand post hoc Mann-Whitney reported)
1
The eye tracking analyses were also conducted excluding the 5 children with
DCD that presented with high SCQ scores and the pattern of results remained
the same. Therefore, the full sample is presented in subsequent analyses.
J Abnorm Child Psychol

on the MABC-2. The final TD sample group thus consisted of
25 children (22 male).
Procedure
Ethical approval was obtained from Goldsmiths, University of
London. All schools and parents of the participating children
were provided with detailed information relating to the study
aims, planned tasks and the procedures relating to maintaining
anonymity for each participant. Informed consent was then
obtained by asking head teachers of the schools and the indi-
vidual parents to provide written consent confirming that they
were happy for the children to take part in the study. Further,
all children gave verbal assent after the tasks were explained
in full.
Materials and Apparatus
The stimuli consisted of 30 colour images. They were stock
images selected and purchased for the purpose of the experi-
ment through Fotolia. Each image was landscape orientation
and was presented at 800 × 600 pixels. The stimuli depicted a
range of social activities and included children of a similar age
to the participants in the study.
Stimuli were randomly divided into two sets of images: 15
images showing an ‘Individual’character with their attention
directed towards the viewer; and 15 images showing ‘Social’
interactions between two or more characters (maximum, 4,
following a similar procedure to Riby and Hancock 2008).
In the latter, the characters’attention (gaze) was directed to
others or objects in the scene. All images contained either one
character (child) presented close to an everyday object
(‘Individual’), or two or more characters interacting with the
object (i.e., with gaze directed towards it; ‘Social’). The object
was considered a non-social aspect of the scene, along with
the background of the scene, while the head and body of the
character(s) were considered to be social elements. Example
‘Individual’scenes included a child sitting with a book open
but looking directly at the camera (see Fig. 1a), a child on a
scooter, etc.; and ‘Social’scenes included children playing on
atablet(seeFig.1b), throwing a ball to each other, reading
together. Images were presented in a random order and divid-
ed into 2 blocks of 15 (mixed Individual/Social).
Eye movements were recorded using the Eyelink 1000
(SR-research; 1000 Hz sampling rate), and children viewed
the stimuli presented on a computer monitor from a viewing
distance of approximately 70 cm (1024 × 786 screen resolu-
tion). Each image was presented for 3000 ms. The stimuli
subtended a visual angle of approximately 29 × 18°. At the
beginning of the session, children completed a 9-point cali-
bration, requiring fixations to be made within 1° of each fix-
ation point, followed by a validation phase. This procedure
was also repeated after the break that followed the first block
of images. The camera was set up in the desktop mount and
was non-invasive. A combined forehead/chin rest was used to
keep the head stable and the eye movements within range. All
children were given the option to not use this rest, but all opted
to do so. A height-adjustable chair was used and the forehead/
chin rest could also be adjusted for height and size to accom-
modate the participant. The experiment was implemented
using Experiment Builder and analysed using Data Viewer
(both SR Research software). Data Viewer automatically iden-
tifies fixations and saccades using predetermined criteria.
Saccades are operationalised by velocity/acceleration criteria
(30° per second; acceleration > 8000° per second squared);
fixations are determined as when velocity drops back below
30° per second.
Eye Tracking Data Analyses
Areas of Interest (AOIs) Data Viewer (SR-research) enabled
the construction of AOIs over the viewed images. The first
step of analysis identified four AOIs: the background in the
image, the object, the face, and the body. Figure 1c and d
provides an example of how AOIs were drawn in the first
instance. This was then followed up to consider the eye and
mouth regions/AOIs. Analyses were conducted to investigate
fixations to specific AOIs. Following a similar procedure to
Riby and Hancock (2008), fixations to the ‘background’were
calculated by drawing an AOI around the outline of the image
and calculating all fixations to the image minus those directed
to the other AOIs (face, body, object). Therefore, ‘back-
ground’does not include the white border of the screen sur-
rounding the image (i.e., the image did not fill the whole
screen). A recent meta-analysis identified that percentage of
time spent in specific regions is the most widely and uniformly
reported measure in eye tracking studies that focus on ASD
population (Chita-Tegmark 2016). Therefore, overall time
spent fixating the AOIs was calculated as a percentage of the
time that the image was shown on screen.
Time to Fixate the Face This was calculated from the start time
at which the image was presented on the screen in relation to
when a fixation was first made to any part of the face AOI (in
seconds). First fixations were recorded as those that occurred
after the first saccade from the stimulus onset. This prevented
scoring fixations that occurred in the face region simply because
the eye position was there when the image was first shown.
Gaze Following The Social images contained 2 or more chil-
dren and their gaze was naturally directed either to another
child or the object in the scene. For ease of analysis, tendency
to follow gaze was investigated only during the images that
showed all children in the scene directing their gaze to the
same object. Six images met this criteria (the remaining im-
ages had mixed content - where children in the scene were
JAbnormChildPsychol

looking at different things, either the object or another child).
Figure 1b is an example of two children both looking at a
tablet device. Other examples include children reading a book
together, passing a ball, and completing a puzzle. Gaze fol-
lowing was confirmed if children fixated on the eye AOI of
the children in the photographs and then executed a saccade
immediately to the object AOI. Additional analyses were con-
ducted on scan paths where children fixated on the head AOI
followed by the object AOI. Number of valid gaze shifts were
recorded for each participant, as well as the time spent fixating
the object.
Statistical Analyses
Tests of normality and homogeneity were checked prior to
statistical test selection. Parametric tests were conducted un-
less otherwise indicated. To answer research questions 1 and
3, repeated measures ANOVAs were conducted to investigate
group differences and to compare Individual and Social im-
ages. Significant main effects and interactions were analysed
further using post-hoc comparisons and simple main effects.
Bonferroni-corrected values are indicated in the relevant sec-
tions of the results. To answer research question 2, bivariate
correlations were conducted. Sensitivity analyses revealed
that N=81 would be sufficient to detect a small to medium
effect size for both types of analyses (Faul et al. 2007).
Tab le 1revealed that children in the TD group had a sig-
nificantly higher FSIQ than children in the ASD and DCD
groups, while the clinical groups were comparable. In line
with existing ASD eye tracking studies (Fletcher-Watson
et al. 2009), correlations between FSIQ and the dependent
variables were considered. However, no significant correla-
tions were found between FSIQ and the eye tracking measures
(i.e., total fixation time, time to fixate an AOI, etc). Similarly,
correlations between age and gender and the eye tracking
measures were considered, but revealed non-significant re-
sults (ps > 0.12). Therefore, FSIQ, age, and gender were not
included as covariates in the subsequent analyses.
Results
Following the same criteria applied by Fletcher-Watson et al.
(2009), trials with less than 500 ms of eye tracking data recorded
were excluded from the analysis. Using this criterion, only 1.3%
of the trials were removed and these were roughly split across the
three groups. A univariate ANOVA revealed that participants in
each group were engaged with the task (as measured by total
fixation durations per image) for comparable amounts of time in
the Individual (F(2, 78) = 1.68, p= 0.10, n
2
p
= 0.04: TD group
M= 2.56 s per image, SD = 1.97; ASD group M=2.34 s per
image, SD = 0.46; DCD group M= 2.60s per image, SD =
0.36) and Social images (F(2, 78) = 0.82, p=0.44, n
2
p
=0.02:
TD group M= 2.71 s per image, SD = 0.23; ASD group M=
2.33 s per image, SD = 0.43; DCD group M=2.63sperimage,
SD = 0.27). When participants were not engaged in the task (i.e.,
fixating on the screen), they were making saccades, blinking, or
looking away from the screen.
A 2 × 3 (Image Type x Group) ANOVA was conducted on
the number of saccades made per trial (Individual images: TD
group M= 11.16, SD = 1.36, ASD group, M= 10.45, SD =
1.87, DCD group, M= 9.97, SD = 1.73; Social images: TD
group M= 12.25, SD = 1.38, ASD group, M= 11.37, SD =
2.05, DCD group, M= 10.99, SD = 1.72). Significantly more
eye movements (saccades) were made in the Social images,
F(1, 78) = 144.56, p<0.001,n
2
p
= 0.65, presumably because
the images contained more information (characters) to look at.
A significant effect of group was seen, F(2, 78) = 3.77, p=
Fig. 1 Stimuli examples of (a)an
‘Individual’image (a: ©
contrastwerkstatt/Fotolia), and (b)
a‘Social’image. (b: ©julaszka/
Fotolia). AOI examples (cand d)
are also shown. Yellow shading
indicates the background of the
image, red represents the object
AOI, the green is the face AOI,
and blue represents the body AOI
J Abnorm Child Psychol

0.03, n
2
p
= 0.08, with post hoc analyses revealing no differ-
ences for the TD vs ASD and DCD vs ASD comparisons
(ps > 0.24), but children with DCD made significantly fewer
saccades than the TD group (p= 0.02). No interaction was
found, F(2, 78) = 0.36, p= 0.69, n
2
p
= 0.01. Given that the
number of saccades made was different only for the DCD
and TD comparison, the correlation between the number of
saccades and the variables tested in subsequent analyses was
taken into consideration. However, no significant correlations
were found between number of saccades per trial and any of
the experimental eye tracking measures (viewing time to the
AOIs, time to first fixate the face). For this reason, the number
of saccades made was not included as a covariate in the sub-
sequent analyses.
Viewing Times to Areas of Interest
Figure 2illustrates how visual attention was distributed across
the Individual and Social scenes, considering percentage of
total viewing time per trial to the following AOIs: back-
ground, object, face, body.
A 2 × 4 × 3 (Image Type x AOI x Group) ANOVA was
conducted. Significance levels were Bonferroni-corrected to
p= 0.01. There was no main effect of Image Type, F(1, 78) =
5.70, p=0.02,n
2
p
= 0.07, but there was a main effect of AOI,
F(3, 234) = 272.53, p<0.001, n
2
p
= 0.78, revealing a larger
proportion of time spent fixating the face region in compari-
son to the other AOIs (p< 0.001). A significant interaction
between Image Type and AOI, F(2, 234) = 58.72, p<0.001,
n
2
p
= 0.43, was found, which showed longer viewing time to
the face in the Individual images than the Social images, and
more time spent on the background in the Social images than
in the Individual images.
There was a main effect of Group, F(2, 78) = 7.49, p=
0.001, n
2
p
= 0.16, and a significant interaction between AOI
and Group, F(6, 234) = 4.49, p<0.001,n
2
p
= 0.10, but not for
Image Type and Group (p= 0.02). Children with ASD did not
differ from the TD group in viewing time to the background,
object, or body AOIs in both image types (all ps > 0.14), but
they did fixate on the face significantly less than TD children in
the Individual, t(51) = 3.04, p= 0.003, d=0.84,andSocialim-
ages, t(51) = 4.68, p< 0.001, d= 1.28. Compared to TD chil-
dren, children with DCD were comparable in their viewing
times to all AOIs (all ps > 0.03) in the Individual images and
all in the Social images, except that children with DCD spent
significantly longer looking at the body AOI than TD children
t(51) = 2.88, p= 0.005, d= 0.80. The DCD and ASD groups
did not differ in attention to any of the AOIs (all ps > 0.07).
The next stage of analysis considered precisely where par-
ticipants were looking when fixating on the face (see Fig. Fig.
3). Statistical comparisons were made only between the eyes
and mouth region (not the ‘other’/remaining part of the face).
A 2 × 2 × 3 (Image Type x AOI x Group) ANOVA was con-
ducted. Significance levels were Bonferroni-corrected to p=
0.01. There was a main effect of Image Type, F(1, 78) =
54.33, p<0.001, n
2
p
= 0.41, such that a greater proportion of
viewing time was spent in the identified AOIs in the
Individual images across all groups. There was also a main
effect of AOI, F(1, 78) = 48.69, p< 0.001, n
2
p
= 0.38,
0
10
20
30
40
50
60
Background Object Face Body
Proportion of viewing time (%)
TD
ASD
DCD
0
10
20
30
40
50
60
Background Object Face Body
Proportion of viewing time (%)
TD
ASD
DCD
b
a
Fig. 2 Gaze to areas of interest for (a) Individual and (b)Socialacrossthe
three groups. The proportions do not total 100% because of time spent
looking at areas outside of the interest areas
0%
20%
40%
60%
80%
100%
TD ASD DCD
Proportion of time split
across the face region (%)
Other
Mout
h
Eyes
0%
20%
40%
60%
80%
100%
TD ASD DCD
Proportion of time split
across the face region (%)
Other
Mout
h
Eyes
b
a
Fig. 3 Gaze time directed to the eyes, mouth, and other AOI in the face
region, as a proportion of time spent fixating the face as a whole, for (a)
Individual and (b) Social images across the three groups
JAbnormChildPsychol

revealing a larger proportion of time spent fixating the eye
region in comparison to the mouth; and a significant interac-
tion between Image Type and AOI, F(1, 78) = 14.67,
p<0.001, n
2
p
= 0.16, which showed a greater difference be-
tween fixating the eyes and mouth in the Individual images.
There was a main effect of Group, F(2, 78) = 5.89, p=0.004,
n
2
p
= 0.13, revealing children with ASD spent significantly
less time fixating on the eyes (p< 0.01) than the TD group;
but no significant interactions involving Group (ps > 0.08).
Correlations with Symptom Severity
Time spent fixating the face region was combined for both the
Individual and Social performance. A significant negative cor-
relation was found for the SCQ score (all groups combined for
a full range of scores) and overall time spent fixating the face
(r=−0.32, p= 0.006). Higher scores on the SCQ indicate
more ASD-like symptomology, thus those recognised by par-
ents as having more social difficulties spent less time fixating
the face region. However, when correlations were split by
group, no significant correlations remained for the SCQ and
overall time spent fixating the face (ps > 0.11). The MABC-2
total test score did not correlate with the overall time spent
fixating the face region (p= 0.13), suggesting no relationship
between motor ability and a preference to fixate the face. Of
note, the SCQ and MABC-2 performance were not signifi-
cantly correlated with the subsequent eye tracking measures:
time to fixate the face, or gaze following.
2
Time Taken to Fixate the Face
Tab le 2reports the time taken to first fixate the face region in
the images. The correlation between the number of saccades
made during the trials (reported at the beginning of the results)
and the time taken to fixate the face region was considered but
revealed a non-significant relationship (rs < 0.42 and ps>
0.93). Therefore, a link between more saccades and longer
times to fixate the face was not found.
A 2 × 3 (Image Type x Group) ANOVA revealed no effect
of group membership, F(2, 78) = 1.41, p= 0.25, n
2
p
= 0.04,
although a signficiant effect of image type was found, F(1,
78) = 125.47, p<0.001,n
2
p
= 0.62. All groups fixated the face
sooner in the Individual images. Further, a non-significant
interaction, F(2, 78) = 1.83, p=0.17,n
2
p
= 0.05, demonstrated
that this effect was similar across groups. Nevertheless, it was
noteworthy that, although not statistically significant, children
with DCD took longer to fixate the face than the TD and ASD
groups in the Individual images.
Gaze Following
Example scanpaths are shown in Fig. 4. As a reminder, this
analysis was focused on 6 Social images. Of note, 1 TD child
(3.8% of the group) did not make any valid gaze shifts (eye
AOI to object AOI) in any of the six images, neither did 6
children with ASD (21%) and 8 children with DCD (29%). Of
those children who did follow gaze at least once, the mean
number of valid gaze shifts from the eye to object AOI for the
TD group was M= 3.00, SD, 1.93 (range: 1–6), in the ASD
group, M= 2.26, SD, 1.37 (range: 1–6) and in the DCD group,
M= 2.56, SD, 1.15 (range: 1–5). No significant group differ-
ence was found for the mean number of eye to object gaze
shifts, F(2, 67) = 1.06, p=0.35, n
2
p
= 0.04. Time spent fixat-
ing the object was analysed as an indicator of interest in the
part of the scene to which the actors were directing attention,
and also revealed no significant group differences (F(2, 75) =
259, p= 0.06. n
2
p
= 0.06): TD, M= 0.60s per image, SD =
0.27; ASD, M= 0.46 s per image, SD = 0.26; DCD, M=
0.44 s per image, SD = 0.25).
Given that the direction/angle of the head can also provide
cues as to where attention is directed, we extended this anal-
ysis to look at gaze shifts from the face to object. Here we
found that all TD children made valid gaze shifts from the
headAOItotheobjectAOI,while2childrenwithASD
(7%) still did not and, interestingly, 5 children with DCD
(18%) failed to do so: suggesting that a proportion of children
were not receptive to following others’visual attention. When
the analysis was not constrained to the eye region, a higher
number of gaze shifts were found in all groups (TD, M=4.84,
SD, 2.05 (range: 1–8); ASD, M= 3.35, SD, 1.76 (range: 1–6);
DCD, M= 3.54, SD, 1.77 (range: 1–8). Here significant group
differences were found, F(2, 78) = 6.70, p=0.002,n
2
p
=0.12
and post hoc analyses revealed that children with DCD (p=
0.005) and children with ASD (p= 0.007) made significantly
fewer gaze shifts from the head to object AOI than the TD
group. However, the DCD and ASD groups made a compa-
rable number of gaze shifts (p=0.99).
2
To further examine whether children with poor motor skill performed poorer
than those with age-appropriate motor skills, the mean scores on the eye
tracking measures for the subset of children with ASD performing below the
motor cut-off on the MABC-2 were also compared to children with DCD and
the remaining children with ASD who had age-appropriate motor skills. This
analysis revealed no differences in the time spent fixating the face region (p=
0.09)ortimetofixatetheface(p= 0.17) between the three groups.
Table 2 Mean time taken, in seconds, to fixate the face: all groups
Time to fixate TD (n=25) ASD (n=28) DCD(n=28)
Individual
Mean (SD) 0.53 (28) 0.59 (0.14) 0.75 (0.40)
Range 0.29–1.31 0.37–0.93 0.40–1.89
Social
Mean (SD) 1.17 (0.55) 1.13 (0.18) 1.15 (0.48)
Range 0.55–1.92 0.78–1.47 0.46–2.07
J Abnorm Child Psychol

Discussion
The main aim of the present study was to examine how chil-
dren with ASD, DCD and TD children view socially-relevant
information, and to determine whether groups differed in this
respect. Individual images showing direct gaze were used
alongside scenes that were more ecologically valid in showing
a natural interaction among two or more children. Confirming
our initial predictions, and in support of exisiting findings on
younger and older ASD populations (Klin et al. 2002;Riby
and Hancock 2008,2009; Sasson et al. 2007; von Hofsten
et al. 2009), primary-aged children with ASD were found to
fixate less on the face and eye regions than TD children. This
may, in part, contribute to the difficulties these children often
experience with recognising faces and processing facial ex-
pressions and gaze (Corbett et al. 2014; Dawson et al. 2005;
Sumner et al. 2016b). However, in comparison to TD chil-
dren, children with ASD were found to take a similar amount
of time to first make a fixation to the face region, conflicting
with exisiting data on adolescents with ASD (Freeth et al.
2010,2011) and suggesting that children with ASD do search
a scene for social information to some extent. Nevertheless, a
number of children with ASD (21%) did not spontaneously
follow the gaze (from the eye AOI to object) of the children in
the images. Thorup et al. (2016) found that infants at-risk of
ASD were less likely to follow gaze when information was
only provided from an adult’s eye and instead they were more
successful in doing so when a head shift was made alongside
gaze. In the present study, the eyes/head in the images were
always in the same direction, but we found that the percentage
of children with ASD who did not demonstrate a gaze shift to
the object decreased to 7% when looking at saccades made
from anywhere in the head AOI to the object, indicating that
some children may interpret clues from the angle of the head
rather than the eyes.
Using eye tracking methodology to better understand social
behaviour in a DCD population was a novel approach, and com-
parisons to ASD and TD children enabled the identification of
some atypicalities. In fact, this study provides the first experimen-
tal account of how children with DCD process socially-relevant
information. While the pattern of results were not as exaggerated
for children with DCD as they were for children with ASD (they
performed in between the TD and ASD groups on time fixating
the head and eye regions), some interesting patterns of behaviour
did emerge. Although not significantly different, overall children
with DCD were slower than the ASD and TD groups to first
fixate the face in the viewed images. Moreover, children with
DCD were the most impaired out of the three groups in the
examination of tendency to follow gaze. Nearly a third of the
DCD group did not follow the direction of gaze from the eyes to
the object on even one occasion. This decreased to 18% when the
head-to-object analysis was conducted, indicating that a signifi-
cant number of children with DCD did not utilise gaze cues when
passively viewing the social interactions. It is interesting that
although children with DCD, on average, spent longer looking
at the eye region than those with ASD, fewer children with DCD
interpreted these gaze cues. Gaze can reveal a person’sintentions
and research has shown that other people’s eyes naturally guide
our own visual attention (Macdonald and Tatler 2013). A lack of
awareness in this respect may indicate poor understanding of
social conventions and would understandably have repercussions
for social interaction. Thus, these exploratory findings of unusual
gaze behaviour potentially support the notion of social atypical-
ities in a DCD population (Cummins et al. 2005;Sumneretal.
Fig. 4 Examples of gaze scan
paths by (a)TDchild,(b)child
with DCD and (c)childwith
ASD. Photograph © Serhiy
Kobyakov/Fotolia
JAbnormChildPsychol

2016b), and this work could be usefully extended with more
specific gaze following tasks, discussed below.
In addition to the group comparisons discussed above, the
current study also assessed the influence of broader social
abilities on how children process socially-relevant information
across the three groups. As expected, a higher number of
atypical social characteristics, as measured by the parent re-
port SCQ, were shown to correlate with fewer fixations made
to the face region; although this correlation is likely driven by
group membership, given that when considered by individual
group the correlation diminished. The direction of a possible
relationship, however, remains unclear; thus, reduced atten-
tion to faces may influence how children act socially or social
experiences may influence how children with ASD and DCD
attend to faces. Future research might further explore this re-
lationship with more experimental measures of social skills,
rather than parent reports, in relation to eye-tracking perfor-
mance, over development, which will allow further interpre-
tations of cause and effect in these relationships.
Unexpectedly, when considering the earlier argument that
motor skills enable opportunities for social interaction (Campos
et al. 2000;Clearfield2011), poorer motor skill did not correlate
with fixations to the face. The interaction between motor and
social development may be better studied in early development,
which can be difficult in a DCD population when diagnoses are
often made from the age of 5 (Blank et al. 2011). Indeed, children
with DCD are significantly delayed in achieving early gross
motor milestones (Sumner et al. 2016b), and may therefore dem-
onstrate clearer social differences earlier in life than was studied
here. The fact that children with DCD in the current study did not
differ significantly from the typically-developing group but per-
formed at a slightly lower level overall across eye-tracking mea-
sures may suggest that the close relationship between motor and
social difficulties in this group is mediated over time. The social
difficulties reported in DCD at school age (e.g., Chen et al. 2009;
Dewey et al. 2002) may thus be a consequence of poor motor
skill and its effect on interaction, rather than the primary difficulty
in social skills seen in ASD. Future research would benefit from
exploring whether social difficulties (including difficulties fol-
lowing gaze cues) are present from an early age or emerge as a
possible repercussion of motor problems in children with DCD,
but also in an ASD population where motor difficulties are in-
creasingly reported (Landa et al. 2013).
The present study was careful to select the sample groups so
that co-occurring diagnoses were not present and, therefore,
social atypicalities found in the DCD group cannot be attributed
to these children having a dual diagnosis. However some lim-
itations related to the methodology can be raised. One potential
problem might be that the Individual and Social images differed
in not only the the number of people in the image, but also in
the gaze direction of those presented (i.e., direct gaze in the
Individual images, and averted gaze in the Social images).
Direct gaze has been shown to influence ASD performance,
as atypical activation in theory-of-mind networks in adults with
ASD has been shown when viewing direct gaze (Hamilton
2015; von dem Hagen et al. 2014) and increased physiological
responses have been noted which may interfere with face pro-
cessing (Joseph et al. 2008; Kylliainen and Hietanen 2006).
However, this argument does not hold true in the present study
as all groups made a higher proportion of fixations to the face
(and eyes) region in the Individual images where the gaze was
directed to the observer, than in the Social images where gaze
was directed between the characters/objects in the images. In
fact, for all groups, more saccades were made and participants
were slower to first fixate the face region and directed fewer
fixations to the face region in the Social images, suggesting that
the content of the scene influences eye movements. Comparing
highly-controlled direct-gaze images and more naturalistic so-
cial scenes within one study was important because it could
help to explain the mixed findings from previous studies.
Future research could take this further by comparing a range
of different stimuli (e.g., individual and social images with both
averted and direct gaze) across groups or consider whether the
present findings translate to real-life scenarios. We live in a
multi-sensory environment and it may be expected that these
findings would be more pronounced in real life, where more
distractions may occur and the information provided by the face
changes rapidly.
Another point to consider is that we found that children with
DCD made fewer saccades per trial, which could be argued to
limit the conclusions if basic oculomotor function was
interferring with social scene processing. Poor oculomotor con-
trol has in fact been reported in both ASD (Johnson et al. 2016)
and DCD (Sumner et al. 2016a) populations when using para-
digms designed to examine the execution of saccades and fix-
ations. Such paradigms are notably different to a social scene
task, as the latter in the present case does not impose any in-
structions for oculomotor behaviour (i.e., the present task in-
volved passive viewing). Previous research using oculomotor
paradigms suggests that children with DCD have difficulty
inhibiting saccades and maintaining fixations when given spe-
cific instructions that test executive skills (Gonzales et al. 2016;
Sumner et al. 2016a), however we find fewer saccades made
during the social scene task than their peers (but not those with
ASD) and no group differences in average fixation duration,
which suggests that the children with DCD did not present with
poor control of saccadic eye movements when participants are
asked to freely view images. It was beyond the scope of this
paper, but future research may investigate how fundamental
oculomotor processes impact on spontaneous social processing
for both children with ASD and DCD.
A final point to consider for future research relates to the
gaze following analysis. The present study used images that
contained only one object, whereas in other gaze following
studies in adults with ASD the actor’s gaze is directed to one
of two competing objects (the ‘congruent’object; Freeth et al.
J Abnorm Child Psychol

2010). Now that we have established potentially reduced ten-
dency to follow gaze in DCD and ASD, future research using
the congruent vs incongruent gaze approach in children ASD
and DCD would be beneficial. It may be that individuals with
ASD and DCD are able to use gaze information if they are
directed to the eyes, but that this is not spontaneous.
Regarding ASD, it has been suggested that this lack of auto-
maticity of gaze following could be related to atypical function-
ing of the superior temporal sulcus, which is involved in the
processing of dynamic aspects of faces (Pelphrey et al. 2005).
Brain imaging studies in both ASD and DCD would be neces-
sary to support this claim in relation to the current results.
In summary, the present study identified subtle differences
between children with ASD and children with DCD. Those
with ASD directed their attention to social aspects of a scene
(the face, eyes) significantly less than their typically-
developing peers, while children with DCD demonstrated less
clear differences in their allocation of attention to these areas of
interest compared to TD children. Exploratory analysis re-
vealed that, in comparison to their TD peers, fewer children
with DCD had a reduced tenedency to follow gaze in the social
stimuli. Taken together, these findings hint at some atypicalities
in allocating attention to social stimuli in DCD, but suggest that
this may be linked to different causal mechanisms than in those
with ASD. This work extends exisiting findings from
standardised social measures to consider the allocation of visual
attention to social stimuli. While this goes some way to im-
proving our understanding of underlying processes affecting
social behaviour in DCD, further research is required to under-
stand the neural and cognitive underpinnings of social prob-
lems in the disorder. Future cross-syndrome comparisons are
also warranted to aid understanding of the overlap of ASD and
DCD and to determine effective avenues for intervention.
Acknowledgements This study was funded by The Leverhulme Trust
(RPG-2012-742). Special thanks go to all participating schools, parents
and children. Thanks are also due to our departmental technician, Maurice
Douglas, for technical assistance.
Compliance with Ethical Standards
Conflict of Interest The authors declare that they have no conflict of
interest.
Ethical Approval All procedures were approved by the Goldsmiths,
University of London, ethics committee and were in accordance with
the ethical standards laid down in the 1964 Helsinki declaration and its
later amendments.
Informed Consent Schools and parents of all participating children were
fully informed about the study and subsequently provided written consent;
while all children provided verbal assent to participate in the named tasks.
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give appro-
priate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
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