Read the following three research articles and complete written response to the readings. Write a page and a half synthesis of the three articles plus 1 discussion question per article.
The following factors will be considered in grading: relevance, accuracy, synthetization of the reading materials, degree to which the responses show understanding/comprehension of the material, and quality of writing.
· Questions must be original, thoughtful and not easily found in the readings.
· Quality of Synthesis
· Follows APA Rules
· Use proper citations
· Use past tense when discussing the studies (the research was already conducted).
· Avoid the use of the following words: me, you, I, we, prove, proof
· Refer to the articles by their authors (year of publication) (not by the title of the article or the words first, second, or third)
· Do not just summarize the articles. Dig deeper!
***FOLLOW THE ATTACHED SAMPLE
Two Factor Model of ASD Symptoms
One of the key factors in determining whether an individual has Autism Spectrum Disorder (ASD) is in their social and communication skills. Individuals who are diagnosed with ASD have delayed joint attention, eye gazing, and other social interactions such as pointing (Swain et al., 2014).
Joint attention is an important social skill to master because it is a building block for developing theory of mind which, helps us to understand other’s perspectives. Korhonen et al. (2014) found that individuals with autism have impaired joint attention. However, some did not show impairment in joint attention, which lead to evidence that suggests there are different trajectories for joint attention. One suggestion as to why Korhonen et al. (2014) found mixed results, is that there is evidence that joint attention may not be directly linked to individuals with ASD since they were unable to find a difference in joint attention between ASD and developmentally delayed (DD) individuals. Another suggestion for the mixed results, is individual interest in the task vary. Research has found that while individualized studies are beneficial in detecting personal potential and abilities, it would be difficult to generalize the study in order to further research to ASD as a whole (Korhonen et al., 2014). In addition to joint attention, atypical gaze shifts is a distinguishing factor in individuals with ASD. Swain et al. (2014) found the main difference between typically developing (TD) and ASD individuals in the first 12 months of life is in gaze shifts. Individuals that were diagnosed with ASD earlier had lower scores on positive affect, joint attention, and gaze shifts, however those diagnosed later differed from typically developing (TD) only in gaze shifts. It is not until 24 months that later onset ASD individuals significantly differ from their TD peers, by displaying lower positive affect and gestures (Swain et al., 2014). These findings may lead to other ASD trajectories.
Another defining characteristic of ASD is the excess of restrictive patterns of interest and repetitive motor movements. These patterns and movements often impaired the individual from completing daily tasks. Like joint attention and gaze shifts, these repetitive movements and patterns of interest have different trajectories (Joseph et al., 2013). Joseph et al. (2013) found that individuals with high cognitive functioning ASD engage in more distinct and specific interests and less in repetitive motor movements than individuals with lower cognitive functioning ASD. Another finding showed that at the age of two, repetitive motor and play patterns were more common than compulsion. By the age of four all these behaviors increased however, repetitive use of specific objects was found to be less frequent in older children than younger children. This finding suggests that the ritualistic behaviors and motor movements may present themselves differently based on the age of the individual (Joseph et al., 2013).
Joseph et al. (2013), Korhornen et al. (2014), and Swain et al. (2014) all defined key characteristics of an ASD individual and explains the different trajectories of each characteristic. The difficulty with the trajectories is that it is specific to each individual, some symptoms may worsen while others remain stable. It is also difficult to generalize finding with small sample sizes (Joseph et al., 2013).
Discussion Questions:
1. Korhonen et al. (2014) did not use preference-based stimuli to look for joint attention and did not separate high- from low-functioning ASD individuals. Do you think that there could be a difference in level of motivation from each group? If so, how do you think this could change the results?
2. Swain et al. (2014) found that early and late onset of ASD did not differ in their social skills scores at the age of 12 months. If we know that their social skills do not differ then, is there another factor that would allow diagnosis of late onset ASD to be diagnosed at an earlier point in development?
3. Joseph et al. (2013) explains that it is difficult to assess the trajectories of ASD with a small sample size however, how do you think that their findings still help advance the research on ASD?
REVIEW
CURRENTOPINION Autism spectrum disorder in infancy: developmental
considerations in treatment targets
Copyrig
1350-7540 Copyright � 2015 Wolte
a b c
Jessica A. Brian , Susan E. Bryson , and Lonnie Zwaigenbaum
Purpose of review
This review explores recent literature to prioritize aspects of development to be targeted by intervention for
infants and toddlers with autism spectrum disorder (ASD).
Recent findings
Recent investigation of early development in ASD, including prospective studies of infants at increased risk
(i.e., those with an affected older sibling) identifies impairments in four key developmental domains that are
predictive of ASD. These domains are early attentional control, emotion regulation, social orienting/
approach, and communication development. Reciprocal relationships exist among these domains, both in
ASD and in typical development. Thus, these domains represent key intervention targets, informing
treatment models under investigation in recent clinical trials.
Summary
By targeting the earliest and foundational manifestations of atypical development, we can capitalize on
neural plasticity and build skills that are most likely to have scaffolding effects on development. The optimal
timing and procedures of intervention remain empirical questions, but as the field moves toward earlier
identification of risk, we are now poised to evaluate the impact of tailored approaches before the
developmental cascade that leads to ASD is fully manifested. Consideration regarding community
translation of ASD-specific interventions for infants and toddlers is also needed, with a focus on feasibility,
cost-effectiveness, and sustainability.
Keywords
attention, autism, communication, early intervention, emotion regulation
aBloorview Research Institute, University of Toronto, Ontario,
bDepartments of Pediatrics and Psychology, Dalhousie University, Halifax
and cDepartment of Pediatrics, University of Alberta, Edmonton, Canada
Correspondence to Dr Jessica A. Brian, Bloorview Research Institute,
150 Kilgour Rd, Toronto, Ontaio M4G 1R8, Canada. Tel: +1 416 425
6220 x3716; fax: +1 416 422 7045; e-mail: jbrian@hollandbloorview.ca
Curr Opin Neurol 2015, 28:117–123
DOI:10.1097/WCO.0000000000000182
INTRODUCTION
Remarkable progress has been made in early detec-
tion and diagnosis of autism spectrum disorder
(ASD), particularly in high-risk samples (e.g.,
younger siblings of children with ASD; see [1
&
&
]
for a recent review). This, in turn, has highlighted
the need for developmentally appropriate interven-
tion for infants and toddlers with suspected or diag-
nosed ASD. Information on the nature and efficacy
of such interventions is beginning to emerge [2–4].
However, to date there has been little discussion of
what should constitute the main targets of inter-
vention, and why. Knowing that resources are
limited and time is precious, it is critical to focus
on targets that yield the greatest benefits. Such
endeavors are limited by current knowledge about
early development of ASD, and therefore should be
considered ‘moving targets’ to be refined as knowl-
edge accumulates. Nonetheless, we argue that a
focus on empirically and theoretically relevant
targets (and associated outcomes) is warranted. This
approach differs from that traditionally adopted in
ht © 2015 Wolters Kluwe
rs Kluwer Health, Inc. All rights rese
intervention for preschoolers with ASD, wherein the
focus has been on the model or techniques adopted
(i.e., applied behavior analysis, naturalistic and/or
developmental), and on the intensity of interven-
tion. Although our choice of key targets depends
heavily on normative development, our operating
assumption is that all of these approaches have
merits, and thus an integrated model of interven-
tion is warranted.
We begin by identifying early signs of ASD that
might serve as intervention targets. Then, upon
considering the relative precedence and putative
benefits of each to overall development, we argue
r
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mailto:jbrian@hollandbloorview.ca
KEY POINTS
� Prospective, longitudinal studies of high-risk infants
indicate early impairments in four broad domains of
development that are predictive of ASD: sensory-motor,
attentional, social-emotional, and communication.
� We argue for reciprocal relationships among early
attentional control, emotion regulation, social
orienting/approach, and early communication
development in the emergence of ASD.
� With the goal of optimizing development as efficiently
as possible, we propose that very early intervention
should target attentional control, positive effect, social
orienting/engagement, and communication.
� By targeting the earliest and foundational
manifestations of atypical development, we can
capitalize on neural plasticity and build skills that are
most likely to have scaffolding effects on development.
� As the field moves toward earlier identification of risk,
we are now poised to evaluate the impact of tailored
interventions before the developmental cascade that
leads to ASD is fully manifested.
Developmental disorders
for the importance of some over others (i.e., ‘key
targets’). This analysis considers potential ramifica-
tions of very early intervention for both psychologi-
cal and neurological development in ASD. Finally,
we conclude by discussing approaches and tech-
niques that might be most effective in enhancing
key target skills. With an eye to community trans-
lation of ASD-specific interventions, we end by
discussing practical issues related to feasibility,
cost-effectiveness, and sustainability.
EARLY SIGNS OF AUTISM SPETRUM
DISORDER AND ASSOCIATED
INTERVENTION TARGETS
Prospective, longitudinal studies of high-risk infants
indicate that early impairments in four broad
domains of development – sensory-motor, atten-
tion, social-emotional, and communication – are
predictive of later ASD diagnoses. Atypical develop-
ment in each of these domains has the potential to
disrupt early interactions with the social and non-
social world, with cascading effects as development
unfolds. As the field moves toward ever earlier
detection of ASD risk, we are afforded the opportu-
nity for earlier intervention, possibly before the full-
blown syndrome has emerged and associated dys-
functional neural pathways become engrained.
Sensory-motor development
Although relatively little is known about sensory-
motor development in infants with ASD, early
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118 www.co-neurology.com
differences have been reported based on retrospec-
tive video review in the first year of life [5,6]. Pro-
spective findings from high-risk infants include
reduced motor activity [7], delayed motor mile-
stones or atypical developmental trajectories
[8–10], unusual mannerisms/repetitive behaviors,
and various sensory sensitivities or interests
[11 –14]. Atypical visual exploration of toys (and
spinning and rotating) has been demonstrated as
young as 12 months in infants later diagnosed with
ASD [15]. In a study of grasping behavior, the com-
ponent process, starting at 12 months, that distin-
guished high-risk infants later diagnosed with ASD,
was difficulty in disengaging visual attention from
the object to be grasped [16]. Subtle motor delays
and sensory issues have been reported as early as
6 months in babies later diagnosed with ASD (e.g.,
reduced motor control [11,15], protracted head lag
[17]).
To date, the sensory-motor domain has not been
addressed specifically in infant and toddler interven-
tions for ASD, although its potential importance is
underscored by theoretical links between sensory-
motor and cognitive development [18,19]. Based
on recent findings [16], interventions aimed at
improving coordination of movement with atten-
tion (e.g., reaching/grasping with coordinated eye
gaze to an object) may be beneficial, although the
impact of such strategies in infancy has yet to be
systematically evaluated.
Attention
Deficits in attentional control, and related influences
on emotion regulation, may play a central role in the
emergence of ASD. The ability to disengage attention,
which typically develops by 4–6 months, allows
infants to move attention away from arousing events,
and thereby to regulate their state [20]. Attention is
largely reflexive (or involuntary) early in life, but
toward the end of the first year, voluntary, or exec-
utive, control over visual attention emerges, at which
point emotion regulation also improves [21,22]. A
selective deficit in attentional disengagement is
well documented in ASD [23,24
&&
,25] and has been
demonstrated by age 12 months in high-risk infants
later diagnosed with ASD [26
&
,27]. The relative
absence of attentional control might explain the
intense, prolonged negative emotional states and
reduced social approach reported in infants later
diagnosed with ASD [28] (S.E. Bryson, N. Garon, T.
McMullen, et al., unpublished observation). Dimin-
ished attentional control and difficulty regulating
emotional state may together negatively impact
social approach and reduce infants’ opportunities
to experience positive associations from interactions
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Autism spectrum disorder in infancy Brian et al.
with caregivers. Impaired attentional disengagement
may also impact the development of other important
functions, including joint attention and early recep-
tive language (S.E. Bryson, N. Garon, T. McMullen,
et al., unpublished observation). Schietecatte et al.
[29] have demonstrated a relationship between atten-
tional disengagement and initiating joint attention
in 3-year olds with ASD; disengagement from an
object of interest is arguably necessary to move atten-
tion to a person. As well, early language acquisition
requires flexible attention to objects or events to
which others are referring when using linguistic
terms. We thus argue for reciprocal relationships
among early attentional control, emotion regulation,
social orienting/approach, and early communication
development in the emergence of ASD (cf, [30]).
Deficits in attentional control have yet to be
targeted systematically in any known infant/toddler
interventions for ASD, although recent work with
symptomatic high-risk infants as young as 9 months
has begun to encompass attention and engagement
[2]. Fostering attentional control will likely be best
addressed via both structured and naturalistic inter-
vention methods. Wass et al. [31] have successfully
used a series of computerized gaze-contingent
orienting tasks with typically developing 11-month
olds, with evidence of enhanced cognitive control,
sustained attention, and attentional disengage-
ment. Attention-training programs such as this
clearly hold promise for use with high-risk infants.
However, given documented challenges generaliz-
ing from contrived to real-world situations in ASD
[32], the inclusion of training in a naturalistic con-
text may be a critical addition. Gains in attentional
control could lead to downstream effects on
emotion regulation, social engagement, and joint
attention, which in turn might further foster com-
munication development.
Social-emotional development
Early social-emotional deficits in ASD include
reduced positive affect and reciprocal social smiling,
reduced social orienting, and atypical face process-
ing.
Positive facial affect (i.e., smiling) is thought to
have innate hedonic value that serves to motivate
the development of very early social-communi-
cation skills such as eye gaze and reciprocal social
smiling [33 –35]. These very early interactions are
also essential to the development of the emotional
connectedness (or inter-subjectivity) required for
understanding others, which is impaired in ASD
[36 –38]. The putative significance of shared positive
emotion to subsequent communicative and social
development, together with converging evidence of
its early impairment in ASD, argues for targeted
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interventions. Reduced facial expressiveness,
particularly smiling, is well documented in pre-
schoolers with ASD [39,40], and reduced smiling
has been reported by 12–18 months in infants sub-
sequently diagnosed with ASD [7,10,12,41], but not
earlier (e.g., [42]). The possibility remains that
diminished social smiling is a consequence of earlier
deficits in orienting to others.
Early home videos of infants later diagnosed
with ASD initially revealed reduced social orienting
toward the end of the first year of life [5,43]. Evi-
dence of even earlier deficits in attention to faces
comes from high-risk samples, although discrepan-
cies exist as to the timing of its emergence, the
specific facial regions involved, and even specificity
to ASD. Some studies fail to find group differences
until 12 or 18 months [10,44], whereas others
have reported differences as early as 6 months [45].
Chawarska et al. [45] reported reduced attention to a
video-displayed static face in 6-month-old infants
later diagnosed with ASD; however, diminished
attention to the video screen also distinguished
this group, suggesting that attentional control may
be the more primary issue. Selective deficits in
orienting to faces have not been replicated consist-
ently in experimental paradigms. For example,
Elsabbagh et al. [46] did not report a difference in
looking time toward eyes of static faces between
low-risk controls and high-risk infants (including
those later diagnosed with ASD) at 6–10 months,
although there were differences in evoked responses
related to ASD outcome. In a related study, high-risk
infants (aged 6�10 and 12�15 months) were shown
displays containing faces and nonsocial stimuli. This
task also failed to distinguish infants who went on to
have ASD [44]. Instead, a nonspecific effect emerged,
whereby high-risk infants (regardless of ASD out-
come) spent marginally more time looking at faces
and less time sampling other items in the visual
display. Based on infants’ eye gaze while watching
videos of actors looking directly into the camera and
making age-appropriate social overtures, Jones
and Klin [47] reported a declining trajectory of
eye-looking time in high-risk infants later diagnosed
with ASD relative to high-risk and low-risk controls
beginning at 2 months of age, although cross-
sectional differences were not detectable until
9 months of age. This body of work highlights the
importance of controlling carefully for stimulus
characteristics such as face region assessed and the
nature of the display (dynamic vs. static). It also
remains possible that other features can account
for differences in looking time. For example, one
possibility is that motion is the critical variable in
observed differences between response to eyes and
mouths in dynamic displays.
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Developmental disorders
Thus, despite early evidence of reduced social
orienting in ASD, findings remain somewhat incon-
sistent when examined experimentally in very
young babies. Further research is needed to more
fully understand the nature, timing, and specificity
of this phenomenon. Moreover, competing views
remain as to the primacy of a basic attentional vs.
social interpretation of atypical social orienting in
ASD. Elsabbagh et al. [44] interpret their findings as
evidence of deficient attentional control, conclud-
ing that ‘cortical mechanisms mediating efficient
selection and distribution of attention appear to
modulate infants’ early responses to faces’
(p. 153). Nonetheless, both basic attention and
social orienting deficits appear to index early-
developing challenges in brain and behavioral func-
tioning, which may, at a minimum, interact in a
cascading manner to contribute to ASD outcomes.
As such, both can be argued to be critical targets for
intervention in infants and young toddlers with
emerging ASD.
Interventions aimed at fostering early social-
emotional development in ASD may need to focus
first on increasing child orienting to a social partner
and parent responsiveness [4,48]. Some existing
parent- or teacher-mediated approaches with tod-
dlers have yielded gains related to social orienting
or engagement [49 –51]. Through increased social
orienting, opportunities arise to foster positive
affect sharing through approaches that capitalize
on the child’s motivation and interests, and on
building positive, reciprocal interactions with social
partners. Moreover, given the relationship between
positive affect and both learning in general [52], and
social engagement specifically [35,53], learning may
be enhanced by targeting positive affect directly.
Whether this is accomplished best by directly
targeting child and/or caregiver smiling (e.g., via
parent-mediated interventions) remains an empiri-
cal question, but evidence suggests that this is best
accomplished through the use of naturalistic behav-
ioral procedures that capitalize on the child’s motiv-
ation, such as those of Pivotal Response Training
[2,54].
Communication
Early communication differences in ASD include
reduced nonverbal and verbal communication such
as lack of eye gaze and pointing to share interest (i.e.,
joint attention), diminished use of gestures, reduced
babbling and reduplication, delayed receptive
word learning, and few if any words used mean-
ingfully [1
&&
,55
&
]. Most communication deficits are
not clearly apparent until the end of the first
year and usually manifest as the absence of typical
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120 www.co-neurology.com
development (vs. deviance, which tends to emerge
later; e.g., idiosyncratic or repetitive language in the
second year).
Impairments in joint attention are well docu-
mented in ASD [29,56,57]. Because joint attention
typically develops within the first year, this has been
an area of considerable interest in early ASD detec-
tion research [58 –61]. However, despite the widely
held view that joint attention deficits are universal
in ASD, variances in task demands can yield differ-
ent effects. An intriguing phenomenon highlighted
by Jones et al. in their review [1
&&
] is that orienting to
a proximal target may be relatively less impaired in
ASD than orienting to a more distal target. They
posit that joint attention to near objects may occur
via reflexive orienting mechanisms, whereas distal
orienting may require greater motivation and
understanding of the referential nature of the
orienting cue. Selective deficits in distal orienting
are consistent with an attentional interpretation
whereby executive, or voluntary, control of atten-
tion is needed for distal, but not more proximal (i.e.,
reflexive), orienting.
Some of the earliest communication impair-
ments in ASD may emerge in response to deficits
in attentional control and its impact on skills like
joint attention. However, regardless of whether
communication deficits are primary or at least par-
tially secondary to more basic deficits in attention,
communication development (including within the
context of overall intelligence [62]) has taken pre-
cedence as a target in ASD-specific interventions for
toddlers, for several reasons. First, communication
deficits remain among the most easily detected first
signs in clinical contexts, leading to the bulk of
referrals for assessment. Moreover, communication
may be viewed as a key target because it lays the
foundation for meaningful interactions with care-
givers and others, prevents or reduces behavioral
agitation, and remains the best predictor of positive
outcomes in ASD [63].
As the next generation of infant intervention
programs are developed, the challenge will be to
design strategies that address the earliest manifes-
tations of communicative deficits in ASD. These will
ideally include methods for fostering nonverbal
communicative acts such as eye-to-eye gaze, gesture
use, and functional vocal output, prior to the devel-
opment of verbal language. Such skills will be most
appropriately taught in naturalistic contexts,
capitalizing on highly motivating interactions
and social routines (thereby optimizing positive
effective states), with tight, but developmentally
appropriate contingencies between the babies’
communicative acts and responses from communi-
cation partners (e.g., primary caregiver, therapist).
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Volume 28 � Number 2 � April 2015
Autism spectrum disorder in infancy Brian et al.
Evidence is beginning to emerge regarding the effi-
cacy of such strategies used with infants in the first
year of life [2], revealing that such interventions
have the potential to positively affect outcomes in
a meaningful way.
SUMMARY OF KEY INTERVENTION
TARGETS
Although several systems have been implicated,
findings on early development in ASD most consist-
ently point to poor attentional control, reduced
positive emotion, and delayed nonverbal and verbal
communication skills, atypical development in any
of which has the potential to disrupt early inter-
actions with the world, contributing to cascading
effects as development unfolds. Findings on social
orienting and attention to faces are less consistent,
especially with respect to timing, but important,
given the nature of the social challenges in ASD.
With the goal of optimizing development as effi-
ciently as possible, we thus suggest that very early
intervention should target attentional control,
social orienting/engagement, positive affect, and
communication. By targeting the earliest and
foundational manifestations of atypical develop-
ment, we can capitalize on neural plasticity
[64,65] and build skills that are most likely to have
scaffolding effects on development. Evidence dis-
cussed above also implicates complex interactions
between the earliest-developing deficits in ASD,
highlighting the potential for wide-reaching,
collateral effects of intervening in key domains.
The optimal timing and procedures of intervention
in these domains remain empirical questions,
but as the field moves toward earlier identification
of risk, we are now poised to evaluate the impact of
tailored interventions before the developmental
cascade that leads to ASD has the opportunity to
take hold.
PRACTICAL CONSIDERATIONS
Given current prevalence [66], future intervention
efforts must focus on community translation of
ASD-specific interventions, with a focus on feasible,
cost-effective, and sustainable programs. Current
evidence supports the efficacy of resource-intensive
(i.e., 1 : 1), comprehensive, behaviorally based
approaches for use with preschoolers [67]. As we
move to earlier, publicly funded models, creative
approaches are needed to maintain efficacy with
more children in need and fewer resources.
Parent-mediated approaches that capitalize on the
principles of applied behavior analysis as well as
those of naturalistic learning are gaining traction
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with infants and toddlers [3], often with a focus on
child-directed and highly motivating activities.
These are appealing because they are a natural fit
for this age group, and because they afford the
opportunity for intensive intervention by teaching
parents skills that can be integrated into everyday
caregiving interactions. By identifying key targets
that are likely to have collateral effects on multiple
domains and by capitalizing on evidence-based
intervention methods, we will be poised to deliver
efficient and effective intervention very early in
development in a sustainable way.
CONCLUSION
Evidence from high-risk longitudinal cohorts
indicates that atypical development may first appear
in the sensory-motor system, with deficits in atten-
tional control by the latter part of the first year. Such
deficits are associated with concomitant impair-
ments in emotion regulation, possibly affecting
social approach and joint attention, and negatively
impacting the development of positive associations
required to fuel the social reward system [68].
Moreover, basic deficits in attentional control
may result in reduced social orienting, also nega-
tively affecting infants’ opportunities to learn from
and about social partners. Deficits in attentional
control may also impact important foundational
social communicative interactions such as joint
attention and affect sharing. Mounting evidence
points to a cascading effect of these differences over
the first year of life and into the second year. By
carefully considering the nature by which these
differences unfold, we have the opportunity to
develop very early interventions targeted to key
processes that have the potential to have a scaffold-
ing influence on development. Intervention at
the earliest possible time points, if appropriately
targeted, has the potential for significant down-
stream effects including secondary prevention of
suboptimal outcomes.
Acknowledgements
None.
Financial support and sponsorship
Our research is supported by the Canadian Institutes of
Health Research, Autism Speaks Canada, the Simons
Foundation, the Sinneave Family Foundation and
NeuroDevNet. L.Z. is supported by the Stollery Child-
ren’s Hospital Foundation Chair in Autism.
Conflicts of interest
There are no conflicts of interest.
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rved. www.co-neurology.com 121
Developmental disorders
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rved. www.co-neurology.com 123
REVIEW
CURRENTOPINION Motor development and delay: advances
in assessment of motor skills in autism
spectrum disorders
Copyright
www.co-neurology.com
a b b
Rujuta B. Wilson , Peter G. Enticott , and Nicole J. Rinehart
Purpose of review
Motor impairments in neurodevelopmental disorders, specifically autism spectrum disorder (ASD), are
prevalent and pervasive. Moreover, motor impairments may be the first sign of atypical development in
ASD and likely contribute to abnormalities in social communication. However, measurement of motor
function in ASD has lagged behind other behavioral phenotyping. Quantitative and neurodiagnostic
measures of motor function can help identify specific motor impairments in ASD and the underlying neural
mechanisms that might be implicated. These findings can serve as markers of early diagnosis, clinical
stratification, and treatment targets.
Recent findings
Here, we briefly review recent studies on the importance of motor function to other developmental domains
in ASD. We then highlight studies that have applied quantitative and neurodiagnostic measures to better
measure motor impairments in ASD and the neural mechanisms that may contribute to these abnormalities.
Summary
Information from advanced quantitative and neurodiagnostic methods of motor function contribute to a
better understanding of the specific and subtle motor impairments in ASD, and the relationship of motor
function to language and social development. Greater utilization of these methods can assist with early
diagnosis and development of targeted interventions. However, there remains a need to utilize these
approaches in children with neurodevelopmental disorders across a developmental trajectory and with
varying levels of cognitive function.
Keywords
autism spectrum disorder, motor control, motor function
&&
aUCLA Semel Institute of Neuroscience and Human Behavior, David
Geffen School of Medicine, UCLA Division of Pediatric Neurology, Los
Angeles, California, USA and bDeakin Child Study Centre, School of
Psychology, Faculty of Health, Deakin University, Geelong, Victoria,
Australia
Correspondence to Rujuta B. Wilson, MD, 760 Westwood Plaza, Room
A7-420, Los Angeles, CA 90095, USA. Tel: +1 310 825 1746;
fax: +1 310 206 4245; e-mail: rbhatt@mednet.ucla.edu
Curr Opin Neurol 2018, 31:134–139
DOI:10.1097/WCO.0000000000000541
INTRODUCTION
The development of the motor system is critical for an
individual to engage with the environment. As a
child gains the ability to crawl, point, and ambulate,
new opportunities arise for social interactions with
caregivers and peers [1
]
.
Neurodevelopmental disor-
ders (NDDs) are a heterogeneous group of conditions
that are characterized by delays or abnormalities in a
variety of developmental domains, including delays
in motor skills [Diagnostic and Statistical Manual of
Mental Disorders Fifth Edition (DSM-5)]. Within the
group of NDDs, autism spectrum disorder (ASD) is
diagnosed based on core impairments in social com-
munication skills. However, motor impairments are
particularly prevalent in ASD, and they can be the
first sign of atypical development [2,3]. With advan-
ces in genetic testing, there has also been an increased
identification of copy number variants and single
gene disorders that confer elevated risk for ASD
© 2018 Wolters Kluwer
[4,5 ]. Motor impairments are often the first sign
of abnormal development in these genetic variants
and may be more common in children with syn-
dromic forms of ASD [5
&
&
,6]. Thus, the identification
of early motor delays might be indicative of an indi-
vidual at higher risk for a genetic disorder. Despite
their clinical relevance, quantification of motor skills
in ASD has been hampered by the use of standardized
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mailto:rbhatt@mednet.ucla.edu
KEY POINTS
� Motor impairments are prevalent in autism spectrum
disorder and are related to overall development.
� Quantitative measures of motor function can aid in
identifying specific and subtle motor impairments
in ASD.
� Neurodiagnostic measures of motor function can better
elucidate aberrant underlying neural mechanisms
contributing to motor impairments in ASD.
� Early identification of motor impairments in ASD can
aid in early intervention and improved long term
functioning.
Autism spectrum disorders Wilson et al.
assessments that mostly capture developmental mile-
stones and rely on an individual’s ability to under-
stand complex tasks [7,8]. These assessments often
lead to results that do not adequately capture a child’s
motor abilities or impairments. This has led research-
ers to develop and utilize quantitative measures of
motor function to better identify motor impairments
in ASD to aid in earlier diagnosis and development of
individualized interventions. In this review, we
briefly discuss new findings on the relationship
between motor skills, core ASD features, and cogni-
tive function, and then review recent advances in
quantitative and measures of motor function in ASD.
RELATIONSHIP OF MOTOR FUNCTION TO
OTHER DEVELOPMENTAL DOMAINS
The development of motor function is linked to a
child’s capacity for language, cognitive, and social
development, and may serve as an indication of emer-
gent developmental psychopathology [1,9]. Retro-
spective studies of infants at high risk for ASD or
with a confirmed diagnosis of ASD report the emer-
gence of motor impairments before the more salient
social-communicative impairment has been formally
diagnosed. It is well accepted that early emergence of
motor impairments has a downstream impact on key
aspects of social and communicative development, for
example, impairing a child’s ability to gesture, and
interact with other children in play [1,2,10].
Longitudinal studies reveal that the connection
between motor, language, and higher-level cogni-
tive impairment continues into childhood. In the
school-age period, when children may experience
higher developmental demands, studies have
shown a relationship between motor impairments
and disturbances in emotional and behavioral func-
tioning, as measured on the Developmental Behav-
ior Checklist. One explanation for this association is
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that children who experience greater motor prob-
lems may experience more adverse life events, for
example, being excluded from school yard games
and more trouble with academic tasks such as hand-
writing, thus leading to the higher levels of psycho-
pathology [11].
A recent study on high-risk infant siblings
(defined by having a sibling with ASD) examined
whether advances in sitting, and also prone loco-
motion, are related to communicative development
[12
&&
]. This longitudinal study included 37 high-risk
infants, with gross motor skills assessed at monthly
intervals from 5 to 14 months using the Alberta
Infant Motor Scale (AIMS), which is a standardized
observational measure of prone postures utilized in
sitting and locomotion [13]. The age of onset of
verbal and nonverbal communication was also
recorded. Motor delays were observed across all
observations, with the majority of participants
exhibiting delays by 5 and 6 months of age. Motor
development recorded monthly on the AIMS was
related to emergence of both verbal and nonverbal
communicative milestones. As the authors hypoth-
esized, the ability to sit unsupported relates to both
verbal (reduplicative babbling) and nonverbal com-
munication (show gesture onset), whereas prone
locomotion related to nonverbal communication
milestones (show and point gesture). The authors
state that acquiring independent sitting increases
the use of manual movements to engage with people
and also allows an infant to coordinate behaviors,
such as eye contact with multiple individuals [12
&&
].
Therefore, in addition to the relationship of motor
skills with other domains (such as language and
communication), developments in gross motor
skills can serve as the building blocks for more
complex social and behavioral interactions. More-
over, there can be lifelong implications if motor
development is disrupted.
Another study that evaluated high-risk infant
siblings (defined as having a sibling with ASD)
examined the relationship between motor skills
and executive functioning, which is a set of
higher-level cognitive functions including atten-
tion, working memory, and planning. This study
compared the relationship of motor skills and exec-
utive functioning in high-risk infants (both those
who went on to receive an ASD diagnosis and those
who did not) and low-risk infants (defined as a child
without a sibling or family history of ASD) at 12 and
24 months of age. Motor function was assessed using
the Mullen Scales of Early Learning (MSEL) – a
standardized measure of cognitive development
for children from birth to 68 months [14]. Although
no group differences were seen at 12 months, at 24
months, all high-risk infants demonstrated worse
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Developmental disorders
working memory and response inhibition compared
to low-risk infants. In addition, in all groups, worse
gross motor skills were associated with worse
response inhibition [15
&&
].
The mounting research evidence connecting
early motor impairment to poorer global develop-
mental outcomes for children at high risk for ASD
supports the importance of better understanding
motor impairments that might be specific to ASD
and when these impairments emerge. Given the
heterogeneity of ASD and the discovery of genetic
syndromes highly penetrant for ASD, quantitative
and neurodiagnostic measures of motor may shed
light on the individual variability of motor function
in these disorders.
QUANTITATIVE MEASURES OF MOTOR
FUNCTION IN AUTISM SPECTRUM
DISORDER
Quantitative tools of motor function often use
kinetic and kinematic analysis to capture specific
spatiotemporal variables of motor function (e.g. gait
analysis, three-dimensional motion capture analy-
sis, digitized tablets). ‘Kinetics’ refers to the study of
forces that cause motion such as torque, gravity, and
friction. ‘Kinematics’ is the study of movement such
as displacement in time and velocity. These tools
have identified gross and fine motor impairments
that differentiate individuals with ASD from other
groups [16,17,18
&
]
Motor impairments in ASD are often present
beyond early childhood and can affect both gross
and fine motor domains such as balance and manual
dexterity [3]. These persistent deficits can affect
school-based activities, which can influence cogni-
tive and academic performance. For example, mea-
sures of handwriting ability can shed light on
multiple motor domains, such as grip strength
and manual dexterity, and they provide useful infor-
mation on a frequently employed school-based
activity. A recent study utilized an advanced quan-
titative digitized tablet to evaluate kinematic varia-
bles of handwriting (tortuosity, speed, size) and its
relationship to attention and ASD core symptomol-
ogy in school-aged children with ASD. The task was
designed to minimize additional cognitive and lin-
guistic processes, which can confound studies of
ASD [19
&&
]. Participants were also evaluated using
the Movement Assessment Battery for Children-2
(MABC-2), a standardized measure of motor func-
tion examining three domains – manual dexterity,
balance, and aiming and catching [20]. Three main
findings were highlighted in the study: caregiver
report indicated greater handwriting difficulties in
children with ASD compared to typically developing
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136 www.co-neurology.com
age-matched peers; handwriting performance in the
ASD group was characterized by significantly poorer
writing quality and speed; and greater severity of
ASD, attention, and motor symptoms were corre-
lated with reduced handwriting performance and
greater difficulties in functional handwriting perfor-
mance [19
&&
]. However, one of the most salient
points of the study was the value and feasibility of
a reliable, easy, and quantitative (rather than quali-
tative) assessment of handwriting performance.
Similar to the evaluation of handwriting skills,
there has been use of kinematic analysis for evaluate
of gait. Studies utilizing gait analysis have identified
differences in stride width, velocity, and stride
length in children with ASD compared to typically
developing children [21,22,23
&
]. These findings pro-
vide more clarity to previous qualitative descrip-
tions of gait in ASD such as ‘clumsy, rigid, and
wide-based’ [24,25]. A recent study using three-
dimensional motion capture to evaluate gait func-
tion in ASD has shown asymmetry of gait, which is
thought to be a marker of pathologic motor devel-
opment. Kinetic and kinematic gait data were
obtained from children 5–12 years of age with
ASD using a Vicon three-dimensional motion cap-
ture system. Unlike previous studies, the authors
used point-to-point analysis to evaluate data across
a gait cycle rather than in discrete time points. The
results showed significant asymmetry in joint posi-
tions (kinematic data) and nearing significance in
right and leg joint force (kinetic data). Additionally,
the analysis allowed evaluation at different points
during the gait cycle, which can indicate greater
dysfunction in positioning of the hips, knees, or
ankles. The authors noted that although asymmetry
might not always be detrimental, persistent asym-
metry in gait starting from childhood could be
problematic. When asymmetry is present, the con-
tralateral leg is required to compensate in position
and force, and this can place an individual at greater
risk for injury [26
&
]. Abnormalities in gait symmetry
can also lead to difficulties in social play-based
activities and sports, creating a barrier for children
with ASD to participate in such activities with their
peers. This work also provides clearer targets for
motor intervention.
These quantitative measures of motor function
have increased our knowledge of more specific
motor impairments in ASD and have even led
researchers to use these findings to hypothesize that
impairments in motor could be secondary to dis-
ruptions in cerebellar or fronto-striatal networks
[16,27]. The more recent utilization of neurodiag-
nostic measures, such as electroencephalography
(EEG), MRI, and transcranial magnetic stimulation
(TMS), has provided early insights into more specific
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Autism spectrum disorders Wilson et al.
abnormal neural networks leading to motor impair-
ments in ASD [28
&
,29
&
,30
&&
,31
&&
].
NEURODIAGNOSTIC MEASURES OF
MOTOR FUNCTION
Studies of neural mechanisms used in conjunction
with standardized and quantitative motor measures
are essential to parse out the heterogeneity of ASD
and identify targets for behavioral and pharmaco-
logic interventions for motor impairments.
Electroencephalography offers an economical
and noninvasive method for investigating motor-
related neural activity, including neural connectiv-
ity [32]. Oscillatory electrical activity, as captured by
EEG, reflects aspects of neural excitation and inhi-
bition, with the latter primarily modulated by
GABAergic processes. Altered brain oscillatory activ-
ity has been implicated in ASD (for review, see [33]).
In motor output areas, the modulation (suppres-
sion) of beta band oscillations (typically defined
as 13–30 Hz) has emerged as a prominent signal,
particularly elicited during motor specific actions.
Beta oscillations might indicate ongoing sensorimo-
tor integration, coordination, and motor prepara-
tion, as attenuation of beta oscillations are linked to
faster onset of movement [34]. Quantifying modu-
lations of beta oscillations during task-dependent
motor activities in individuals with ASD can provide
valuable information regarding potential aberrant
cortical networks that might be contributing to the
motor dysfunction.
In a recent study, EEG was used to evaluate the
role of oscillatory changes during a praxis motor
control task in children with ASD from 8 to 13 years
of age [31
&&
]. The study chose to evaluate praxis,
because this motor domain represents the perfor-
mance of complex, skilled gestures that are used in
functional skills and communication. EEG was
recorded while the patients performed a praxis par-
adigm made up of pantomiming 10 common tools.
Individuals with ASD displayed reduced task-related
EEG power modulation during performance on the
praxis task, which suggests that dyspraxia in ASD
might be associated with decreased activity in the
frontal-parietal praxis network. The authors also
found a correlation between decreased left central
beta band desynchronization and autism severity
(defined from Autism Diagnostic Observation Scale
severity scores). These findings indicate aberrant
neural physiology associated with motor impair-
ments in ASD, and offers a potential brain-based
marker that can be measured with introduction of
interventions [31
&&
].
Imaging studies using MRI, functional MRI
(fcMRI), and diffusion-tensor imaging (DTI)/
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diffusion tractography/diffusion-weighted images
have identified atypical patterns of structural brain
growth in ASD [35]. The use of imaging studies in
conjunction with behavioral measures of motor
function can allow evaluation of the neurobiology
underlying motor development.
As noted earlier in this review, studies of infants
at risk for ASD have primarily utilized behavioral
measures to identify differences in motor develop-
ment. A recent study used resting state fcMRI to
identify functional brain networks associated with
walking and gross motor skills in infants at low and
high risk for ASD. In all, 187 infants at 12 and
24 months of age underwent gross motor assess-
ments through the Mullen Scales of Early Learning
(MSEL) and brain MRI. Scores for walking and gross
motor function were analyzed in relation to network
level functional connectivity based on fcMRI data
acquired from infants and toddlers during natural
sleep. The authors adapted a statistical method
termed enrichment analysis to use a brain-wide
approach to identify networks with a significantly
increased density of connections strongly related to
the studies of walking and gross motor behaviors.
The findings indicated that subsets of infant/toddler
brain networks show strong relationships of func-
tional connectivity to walking and gross motor
function, and the profile of these brain networks
differs at 12 and 24 months. Additionally, these
network profiles involve both positive and negative
brain–behavior relationships, which implies that
increases and decreases in network level connectiv-
ity may underlie the developmental progression of
walking and gross motor function during this age
range. The description of these brain networks of
early gross motor development can aid in informing
neural systems contributing to typical and atypical
motor outcomes and also potentially aid in differ-
entiating neurodevelopmental disorders associated
with motor abnormalities [36
&&
].
Studies of neuroimaging to better identify neu-
ral mechanisms of motor dysfunction in adults with
ASD has been more frequently utilized compared to
younger populations. A recent study of adults with
high functioning ASD combined the use of diffusion
tractography and a behavioral measure of fine
motor skill performance [37
&&
]. It was found that
participants with ASD had slower performance on
the Purdue Pegboard test compared to typically
developing adults. Additionally, diffusion tractog-
raphy investigating primary motor cortex (M1) and
somatosensory cortex (S1) connections showed
decreased fractional anisotropy and increased per-
pendicular diffusivity, which has been seen in asso-
ciation with abnormalities of white matter tract
structure, reduced tract coherence and organization,
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Developmental disorders
and reduced myelination. It is thought that these
white matter abnormalities might underpin slower
and worse performance on the Purdue Pegboard
test. This study provides direct support of the
role of the connections between S1, M1, and fine
motor skill performance, and supports the potential
development of therapeutic approaches due to the
relationship of S1 input to M1 in long term potenti-
ation [37
&&
]
FUTURE DIRECTIONS AND CONCLUSION
As we move forward in the assessment of motor
function in ASD it is imperative the field continue
to employ these quantitative (both behavioral
and neurodiagnostic) measures. This study has
highlighted the advances in assessment of motor
function in ASD and the contribution these assess-
ments have made in better understanding more
specific and subtle motor impairments in ASD and
the underlying pathophysiology leading to these
impairments.
Despite evidence for definitive motor dysfunc-
tion in ASD, studies of motor function in ASD, how-
ever, face some significant limitations, which include
lack of large samples of children with ASD and varying
levels of behavioral and cognitive functioning; few
studies evaluating children with ASD across develop-
ment to examine emergence of motor impairment
and changes over time; few studies that evaluate the
impact of genetic cause, ASD severity, and prevalent
behavioral comorbidities (attention deficit hyperac-
tivity disorder, intellectual disability, irritability) on
the manifestation of motor impairments. Quantita-
tive measures of motor function can alleviate the
cognitive and behavioral requirements of most stan-
dardized motor assessments and assess individuals
with ASD across a lifespan. These qualities allow
the study of a more heterogeneous sample of individ-
uals with ASD. Additionally, future studies should
utilize these measures to compare motor impairments
in other NDDs to ASD, to establish the degree of
specificity of certain motor impairments in ASD.
Recently, the literature has recognized how
motor impairments in ASD not only affect other
developmental domains but can also lead to reduced
participation in physical activity and subsequent
predisposition to poorer health outcomes [38
&
]. Evi-
dence-based early intervention programs that target
social and behavioral difficulties in children with
ASD have shown to facilitate long-term improve-
ments in these areas [39]. A recent systematic review
highlighted the benefits of various physical activity
interventions for children with ASD below 16 years
of age. The study found that jogging, horseback
riding, martial arts, swimming, and yoga/dance can
Copyright © 2018 Wolters Kluwer
138 www.co-neurology.com
result in improvements to numerous behavioral out-
comes. These outcomes include stereotyped behav-
iors, social–emotional functioning, cognition, and
attention [40]. Another study evaluated the benefits
of an Australian Football League program adapted for
children with ASD. Children enrolled in the program
for 1.5 h a week over a total of 11 weeks. Although
there was not significant change on the objective
motor assessment, standardized parent question-
naire indicated significant improvement in child
object control skills. Parents also noted improve-
ments in coordination and social skills [41]. The
positive results of these studies highlight the critical
need to develop evidence-based motor and physical
activity interventions for individuals with ASD.
As we begin to identify specific motor impair-
ments in ASD and the timing of emergence of these
impairments, we can begin to develop timely, indi-
vidualized interventions and community-based ser-
vices that support these individuals and improve
overall neurodevelopmental outcomes and long-
term functioning.
Acknowledgements
None.
Financial support and sponsorship
Dr Wilson is funded by the National Institutes of Health.
Professor Enticott is funded by a Future Fellowship
from the Australian Research Council (FT160100077).
He also receives funding from the Brain and Behavior
Research Foundation and Fererro.
The work was supported by the Department of Psy-
chiatry at UCLA and the Centre for Social and Early
Emotional Development (SEED), Deakin University.
Conflicts of interest
Dr Wilson has no conflicts of interest to disclose.
Prof. Enticott and Professor Rinehart receive funding
from the Ferrero Group, Australia as part of its Kinder
þ Sport pillar of Corporate Social Responsibility initia-
tives to promote active lifestyles among young people.
Ferrero Group Australia had no role in this research
including the collection, analysis, and interpretation of
data; in writing of the manuscript; and in the decision to
submit the article for publication.
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BRIEF REPORT
Brief Report: DSM-5 Sensory Behaviours in Children With
and Without an Autism Spectrum Disorder
Dido Green1 • Susie Chandler2 • Tony Charman3 • Emily Simonoff2,5 •
Gillian Baird4
Published online: 30 July 2016
� Springer Science+Business Media New York 2016
Abstract Atypical responses to sensory stimuli are a new
criterion in DSM-5 for the diagnosis of an autism spectrum
disorder (ASD) but are also reported in other develop-
mental disorders. Using the Short Sensory profile (SSP)
and Autism Diagnostic Interview-Revised we compared
atypical sensory behaviour (hyper- or hypo-reactivity to
sensory input or unusual sensory interests) in children aged
10–14 years with (N = 116) or without an ASD but with
special educational needs (SEN; N = 72). Atypical sensory
behaviour was reported in 92 % of ASD and 67 % of
SEN
children. Greater sensory dysfunction was associated with
increased autism severity (specifically restricted and
repetitive behaviours) and behaviour problems (specifically
emotional subscore) on teacher and parent Strengths and
Difficulties Questionnaires but not with IQ.
Keywords Autism spectrum disorder � Sensory reactivity �
Sensory interests � DSM-5 � Diagnostic criteria � Behaviour
Introduction
Kanner’s (1943) original description of autism referred to
negative reactions to sensory stimuli, ‘‘loud noises or
moving objects, which are therefore reacted to with horror
or panic’’ (p. 245) while noting that the child ‘‘can happily
make as great a noise as any that he dreads and move
objects to his heart’s desire’’ (p. 245). Asperger (1944) also
described children as demonstrating hypersensitivity in
some circumstances but in other situations either ignoring
(appearing hyposensitive) or seeking out particular stimuli.
The Third Diagnostic and Statistical Manual of Mental
Disorders (DSM-III) (American Psychiatric Association
(APA) 1980) included atypical sensory responsiveness as
an associated feature of infantile autism under diagnostic
criterion E: ‘‘Bizarre responses to various aspects of the
environment’’ (APA 1980, p. 90). However, the subsequent
two editions of the DSM did not include specific reference
to sensory responsiveness in the diagnostic criteria (DSM-
IV, APA 1994; DSM-IV-TR, APA 1987). Since then,
atypical responses to sensory stimuli have been reported as
occurring in 65–95 % of individuals with ASD (Lane et al.
2014; Leekam et al. 2007; Tomchek and Dunn 2007;
Zachor and Ben-Itzchak 2014). Different types of response
to the sensory environment in ASD have been described;
hyper-responsivity, hypo-responsivity and over focussed
sensory interests (described in the literature as sensory
seeking) (Ausderau et al. 2014). Single or mixed sensory
modality responsivity and association with core features of
ASD and comorbidities have also been explored. A meta-
analysis of sensory behaviours in individuals with
ASD
showed significant variation between studies with three
important moderators identified; chronological age, sever-
ity of autism and type of control group (whether compar-
ison groups were matched for chronological or mental age
& Dido Green
dido.green@brookes.ac.uk
1
Centre for Rehabilitation, Oxford Brookes University,
Marston Road Campus, Jack Straw’s Lane, Oxford OX3 3FL,
UK
2
Department of Child and Adolescent Psychiatry, Institute of
Psychiatry, Psychology and Neuroscience, King’s College
London,
London, UK
3
Department of Psychology, Institute of Psychiatry,
Psychology and Neuroscience, King’s College London,
London, UK
4
Guy’s and St Thomas’ NHS Foundation Trust, King’s Health
Partners, London, UK
5
NIHR Biomedical Research Centre for Mental Health,
Institute of Psychiatry, Psychology and Neuroscience, King’s
College London, London, UK
123
J Autism Dev Disord (2016) 46:3597–3606
DOI 10.1007/s10803-016-2881-7
http://orcid.org/0000-0002-1129-8071
http://crossmark.crossref.org/dialog/?doi=10.1007/s10803-016-2881-7&domain=pdf
http://crossmark.crossref.org/dialog/?doi=10.1007/s10803-016-2881-7&domain=pdf
or other developmental disorder) (Ben-Sasson et al. 2009).
Altered sensory responsivity is reported as being associated
with restricted repetitive behaviours (Chen et al. 2009;
Foss-Feig et al. 2012) and need for sameness (Wigham
et al. 2015). Foss-Feig et al. (2012) considered sensory
subtypes in a study of 5–8 year olds with ASD (without a
comparison group) using both parent questionnaire and
direct observation of sensory behaviour. They found that
tactile hypo-responsiveness and sensory seeking correlated
strongly with increased social and communication impair-
ment on the Autism Diagnostic Interview-Revised (ADI-R)
(LeCouteur et al. 2003) and Autism Diagnostic Observa-
tion Schedule-Generic (ADOS-G) (Lord et al. 2000), and to
a lesser degree, repetitive behaviours. Tactile hyper-re-
sponsiveness did not significantly correlate with any of the
core features of ASD (Foss-Feig et al. 2012). Lane et al.
(2010; 2014) described four distinct sensory subtypes
showing different associations with age and IQ (e.g., taste/
smell versus postural inattentiveness) but noted that the
sensory phenotypes were not explained by gender or autism
severity (Lane et al. 2014). Altered sensory responsiveness
has been linked to anxiety (e.g., Lane et al. 2012; Ben-
Sasson et al. 2008; Wigham et al. 2015) and depression
(Bitsika et al. 2016) and may also have a significant impact
on adaptive function (e.g. Ben-Sasson et al. 2009; Lane
et al. 2010; Tomchek and Dunn 2007; Zachor and Ben-
Itzchak 2014).
The latest version of the DSM has again included
atypical sensory responsiveness (hyper- or hypo- reactivity
to sensory input) or unusual interest in sensory aspects of
the environment as one of four possible elements of which
two must be met in Criterion B: Restricted, repetitive
patterns of behaviour, interests, or activities. Combined
with persistent deficits in social communication and social
interaction across multiple contexts, these two domains
define autism spectrum disorder (DSM-5; APA 2013).
However, atypical responses to sensory stimuli are also
reported in people with intellectual disability and other
neurodevelopmental disorders (Watling et al. 2001; Green
et al. 2003; Tomchek and Dunn 2007; Lane et al. 2012),
leading to the suggestion that sensory symptoms are a non-
specific indicator, along with abnormalities in motor skills
or self-regulation, of brain network vulnerability in
developmental psychopathology (Levit-Binnun et al.
2013). While sensory behaviours are reported as occurring
more frequently in ASD than in comparator groups
(Watling et al. 2001; Tomchek and Dunn 2007), it is not
clear what proportion of individuals with conditions other
than ASD have hyper- or hypo-reactivity or sensory
interests and whether these involve the same sensory
modalities, single or multiple. We therefore contrasted the
proportion of individuals with hyper-or hypo-reactivity or
sensory interest to environmental sensory input, consistent
with DSM-5 criteria, in two groups of children from the
Special Needs and Autism Project (SNAP; Baird et al.
2006). Children with ASD and children with other forms of
special educational needs (SEN) without ASD were com-
pared using relevant items from the ADI-R (Lord et al.
1994) and the Short Sensory Profile (SSP) (Dunn 1999).
We also explored whether atypical sensory behaviours in
ASD were associated with autism symptom severity, IQ or
co-occurring emotional and behavioural problems. We
hypothesised that children with ASD would show a high
frequency of atypical responses to the sensory environ-
ment. These atypical responses would be more frequent
and more severe than in children with other neurodevel-
opmental problems and associated with autism severity and
behaviour problems.
Methods
The study was approved by the South East Multicentre
Research Ethics Committee (REC) (00/01/50). Parents
gave informed consent for participation.
Participants
The sampling methodology of the SNAP study has been
described previously (Baird et al. 2006) and is illustrated in
Fig. 1. In brief, this was a study of the prevalence of ASD
within a total population cohort of 56,946 children born
between July 1st 1990 and December 31st 1991 who were
assessed when aged 9–14 years. All those with a current
clinical diagnosis of ASD (N = 255) or considered ‘at risk’
of ASD by virtue of having a Statement of SEN
1
(N = 1515) were screened using the Social Communica-
tion Questionnaire (SCQ) (Rutter et al. 2003). Based on
SCQ score, a subsample stratified by four levels of SCQ
score
2
representing low (\8), moderately low (8–14),
moderately high (15–21) and high ([21) scores (by coin-
cidence also N = 255), received a face to face compre-
hensive diagnostic assessment by trained researchers which
included the ADOS-G (Lord et al. 2000) and the ADI-R
(Lord et al. 1994), and measures of intellectual ability
(IQ).and behaviour. All information was used by the senior
authors to derive a clinical consensus diagnosis of ASD
(childhood autism and other ASDs; Baird et al. 2006) based
on ICD-10 (World Health Organization (WHO) 1993)
1
A Statement of Special Educational Needs is a legal document
issued by the local educational authority when children require
significant additional support in school due to any learning and/or
behavioural problems.
2
The cut-offs of 15 and 22 are recommended by Rutter et al. (2003),
and an additional cut-point of \8 was applied, based on the
distribution of SCQ scores within the sample.
3598 J Autism Dev Disord (2016) 46:3597–3606
123
research criteria. The total number of ICD-10 autism
symptoms was recorded. A panel of international experts
reviewed a proportion of cases and agreement on diagnosis
was high (see Baird et al. 2006 for details). Cases not
meeting criteria for a diagnosis of ASD were categorized as
SEN. These children had educational needs and a variety of
other developmental/medical diagnoses.
Measures
ADI-R the ADI-R has three items relevant to sensory
responsivity; ‘unusual sensory interests’, ‘undue sensitivity
to noise’, and ‘abnormal idiosyncratic response to specific
sensory stimuli’. Scored as current or having ever been
present; 0 (nil), 1 (present but with little or no impact, 2
(definite with impact), and 3 (for two items indicating
severe impact).
The Sensory Profile (SPr) (Dunn 1999). Parents com-
pleted the SSP (Dunn 1999), a commonly used question-
naire measure of abnormal responses to sensory stimuli,
reported to have good discriminate validity for children
(McIntosh et al. 1999a). The parent or carer rates the
child’s typical responses to sensory stimuli across 38 items
on a five point scale from ‘never = 5’ responds in this
ASD Autism Spectrum Disorder; SCQ Social Communication
Questionnaire; SEN Special Educational Needs; SSP Short Sensory Profile
56, 946 births in total population
(July 1, 1990 to Dec 31 1991)
1515 with SEN but no local ASD diagnosis
37 with local ASD diagnosis but no SEN
218 with local ASD diagnosis and SEN
1770 screened with the SCQ
1035 completed SCQ and opted in for further assessment
363 selected for in-depth assessment
Local diagnosis SCQ<8 SCQ 8-14 SCQ 15-21 SCQ>21 Total
No Selected 94 36 31 61 222
Participated 62 16 19 46 143
Yes Selected 9 14 29 89 141
Participated 3 9 26 74 112
255 seen for assessment
(Consensus diagnosis: 97 no ASD (SEN), 158 ASD)
66 opt-outs
30 uncontactable
12 did not attend
173 SSPs fully completed
15 SSPs pro-rated
188 SSPs for analysis
72 SEN 116 ASD
Fig. 1 SNAP sampling methodology
J Autism Dev Disord (2016) 46:3597–3606 3599
123
manner to ‘always = 1’. The time period is not specified
but the present tense phrasing implies current behaviour.
The total score indicates overall sensory dysfunction
(lower scores reflecting greater sensory dysfunction), and
seven subscales reflect dysfunction in the following
domains; tactile sensitivity, taste/smell sensitivity, move-
ment sensitivity, under-responsive/seeks sensation, audi-
tory filtering, low energy/weak, and visual/auditory
sensitivity. Missing values were prorated as an average for
the subscale if \10 % of items were missing for that
subscale and no more than 10 % of items missing across all
subscales. Cut-off scores for typical performance, probable
difference and definite difference can be calculated for the
total as well as each subscale. Construct validity and cut-
off scores have been derived from a North American
sample exploring the relationship of the SSP to physio-
logical responses in skin conductance in typical children
and a clinical sample of children identified with sensory
modulation difficulties (McIntosh et al. 1999a, b).
To conform to DSM-5 criteria, hyper-reactivity was
defined as scoring within the definite difference range on
SSP domains (tactile sensitivity, taste/smell sensitivity,
movement sensitivity or visual/auditory sensitivity) or a
score of 2 or 3 on the ADI-R items describing undue
sensitivity to noise or idiosyncratic negative responses to
sensory stimuli (using current codes). Hypo-reactivity was
defined as definite difference in the auditory filtering
domain of the SSP and an ‘always’ or ‘frequently’ response
to ‘Doesn’t seem to notice when face or hands are messy’,
or ‘Leaves clothing twisted on body’ items (both from the
under-responsive/seeks sensation domain) of the SSP.
Sensory interests were defined as a score of 1 or 2 on the
ADI-R item ‘unusual sensory interests’ (current code
used).
IQ was measured using the Wechsler Intelligence Scale
for Children (WISC-III, Wechsler 1991; the current version
at the time of the study) or Raven’s Standard (SPM) or
Coloured Progressive Matrices (CPM) (Raven et al.
1990a, b) depending on the child’s ability. Where WISC
full scale IQs were not available, imputed full-scale IQs
were obtained using the regression relationship of full scale
IQ to SPM/CPM IQ (N = 12). For the five cases where no
direct cognitive testing was possible, all had Vineland
Adaptive Behaviour composite scores (Sparrow et al.
1984) below 20 and these cases were assigned an IQ score
of 19 to reflect their profound level of intellectual
disability.
3
Severity of ASD was measured by ADI-R (4–5 and
current) and ADOS total scores, as well as an overall ICD-
10 symptom count based on all available information (with
symptom counts ranging 0–12). For each of these mea-
sures, total scores as well as domain scores for social
impairment, communication impairment, and restrictive,
repetitive and stereotyped behaviours (RRSB) were cal-
culated. Behaviour problems were measured by the parent
and teacher versions of the Strengths and Difficulties
Questionnaire (SDQ) (Goodman 1997), which asks par-
ents/teachers to rate 25 behaviours as not true (0), some-
what true (1) or certainly true (2). These ratings can be
used to generate a total difficulties score, as well as sub-
scales for emotional symptoms, conduct problem, hyper-
activity, peer problems, and prosocial behaviours. The
SDQ is widely used as a brief screening instrument for
psychiatric problems and its psychometric properties have
been established in several samples, including the UK (e.g.
Goodman et al. 2000).
Data Analysis
Chi squared analyses and Fisher’s exact tests were used to
compare the proportions of children, with and without
ASD, with a hypersensitivity or a hyposensitivity or a
sensory interest consistent with DSM-5 criteria. Within the
ASD group, linear regression was used to examine the
relationship between sensory dysfunction (indicated by
lower SSP total scores) and other child characteristics, IQ,
age, autism symptoms (domain scores from the ICD-10
symptom count, ADOS and ADI-R), and behaviour and
emotions (SDQ subscale scores). Analyses were carried out
using Stata 11 (StataCorp 2009).
Results
From a sample of 255 children, a total of 210 SSPs were
returned. Of these, 173 were fully completed and prorated
scores were calculated for a further 15 resulting in a total of
188 SSPs available for analysis (see Fig. 1). Of the 188,
116 children received a consensus diagnosis of ASD. The
diagnoses of the remaining 72 children (categorised as
SEN) included: 39 intellectual disability, 11 hyperkinetic
or conduct disorder, 10 language impairment, 4 hearing
impairment, 5 physical disability or medical condition, 2
chromosome disorders and 1 with no current clinical
diagnosis. Sample characteristics, mean SSP total and
domain scores are presented in Table 1. The SEN group
was slightly older than the ASD group [t (186) = 8.85,
p \ .001] but the groups did not differ in terms of IQ
[t (186) = 0.92, p = 0.36].
3
As these children scored at floor (composite standard score \ 20)
on the Vineland Adaptive Behaviour Scale, these cases were assigned
a proxy IQ score of one point below this, consistent with previous
papers.
3600 J Autism Dev Disord (2016) 46:3597–3606
123
The proportions of SEN and ASD children reported to
have sensory behaviours on the ADI-R, and those scoring
within the definite difference range for each of the SSP
domains are shown in Table 2. Ninety-two percent (107) of
the ASD group compared with 67 % (48) of the SEN group
had either a hypersensitivity, hyposensitivity or a sensory
interest [v2 (1, N = 188) = 20.1, p \ .001].
Compared to the SEN group more children with ASD
scored within the definite difference range on at least one
hyper-reactive domain on the SSP [v2 (1, N = 188) =
29.7, p \ .001] and also for two hyper-reactive domains
[v2 (1, N = 188) = 27.1, p \ .001]. Hyper-reactivity to
the sensory environment was more common among the
ASD group compared to the SEN group for tactile, taste/
smell and visual/auditory sensitivity (all p \ .05); for
movement sensitivity, the difference in rates did not quite
reach significance [v2 (1, N = 188) = 3.84, p = .05].
Definite/marked oversensitivity to noise (ADI item, current
coding of 2 or 3) was also more common in the ASD group,
compared to the SEN group (Fisher’s exact: N = 188,
p \ .001). However rates of idiosyncratic negative
responses to specific sensory stimuli causing intrusion
(ADI item coding of 2 or 3) did not differ significantly
(Fisher’s exact: N = 188, p = .295).
Regarding hyposensitivity, a greater proportion of the
ASD group compared to the SEN group, scored within the
definite difference on the SSP auditory filtering subscale
[70 vs 49 %, v2 (1, N = 188) = 8.46, p \ .05]. The SEN
and ASD groups showed similar proportions of children
who always/frequently ‘[doesn’t] seem to notice when face
or hands are messy’ [v2 (1, N = 188) = .92, p = .34, see
Table 3]. However, the proportion of children who always/
frequently ‘leaves clothing twisted on body’ was signifi-
cantly higher in the ASD group [v2 (1, N = 188) = 13.3,
p \ .001].
More children in the ASD than SEN group were
reported to have unusual sensory interests both by current
[v2 (1, N = 188) = 23.2, p \ .001] and historical [v2 (1,
N = 188) = 36.4, p \ .001] ADI-R score (coding 1 or 2).
Within the ASD group, a lower SSP total (indicating
greater sensory dysfunction) was associated with higher
SDQ total score, accounted for by the emotional subscale
on parent report [b = -2.54, t (101) = -2.96, p = .004]
and with repetitive, restricted and stereotyped behaviour as
recorded on the ICD-10 symptom count [b = -5.49,
t (101) = -2.18, p = .03];but not with ICD-10 social or
communication impairment scores (p = .36 and p = .46,
respectively) (See Table 4). Sensory dysfunction was not
associated with IQ, age, or the remaining SDQ subscales
(all p [ .12). Repeated regressions using the different
measures of autism severity, ADI-R and ADOS scores,
yielded the same results, i.e. autism severity and SDQ total
were associated with sensory behaviours, while IQ was not.
A similar pattern was found when the regression analysis
was repeated using teacher SDQ totals in place of parent
SDQ totals.
Table 1 Sample characteristics and mean
SSP scores
SEN (N = 72) ASD (N = 116) T test/Chi square/
Fisher’s
exact
Sample characteristics
Age in years (SD, range) 12.7 (0.87, 10.1–14) 11.6 (0.87, 10–13.8) p \ .001
IQ (SD, range) 77.0 (20.5, 31–131) 73.9 (23.0, 19–136) p = .359
Ethnicity 94 % white 95 % white p = .909
Parental education 39 % with A-levels 47 % with A-levels p = .287
Gender 82 % male 87 % male p = .337
ADI-R 4–5 total (SD) 12.0 (8.87) 43.2 (11.0) p \ .001
ADOS-G total (SD) 3.99 (2.92) 12.5 (6.39) p \ .001
ICD-10 symptom count (SD) 1.38 (1.17) 7.97 (2.47) p \ .001
SSP scores
SSP total [mean (SD)] 153.7 (24.1) 131.0 (24.3) p \ .001
SSP domain scores [mean (SD)]: tactile sensitivity 30.4 (4.45) 26.4 (5.68) p \ .001
Taste sensitivity 16.8 (4.58) 13.5 (5.51) p \ .001
Movement sensitivity 13.0 (2.64) 11.89 (3.30) p \ .014
Underresponsive/seeks sensation 26.2 (7.54) 21.4 (6.20) p \ .001
Auditory filtering 20.2 (5.25) 16.8 (4.85) p \ .001
Low energy/weak 25.6 (5.98) 23.4 (7.12) p = .029
Visual/auditory 21.4 (3.71) 17.6 (5.22) p \ .001
A-Levels Advanced Level General Certificate of Education equivalent to Secondary or High School leaving qualification, ADI-R Autism
Diagnostic Interview-Revised, ADOS-G Autism Diagnostic Observation Scale-Generic, SSP Short Sensory Profile
J Autism Dev Disord (2016) 46:3597–3606 3601
123
Discussion
In this well characterised cohort, sensory interests or hyper
or hypo reactivity to sensory input were reported in the
majority (92 %) of children with ASD but were also
reported in 67 % with SEN but without ASD. A definite
difference in total SSP score was found in 66 % of the
ASD group and 32 % of the SEN group. Both
groups showed a higher frequency than in a group of
typically developing children without functional/clinical
Table 2 Frequency and percentage of definite sensory symptoms among the SEN and ASD groups
SEN
(N = 72)
ASD
(N = 116)
Chi-Sqaure/
Fisher’s exact
ADI-R items
Sensory interests (current) 1 or 2 shown regularly—score
1
[n
(%)]
11 (15 %) 49 (42 %) p \ .001
Marked with impact—score 2
[n (%)]
2 (3 %) 13 (11 %) p = .051
Any-score 1 or 2 [n (%)] 13 (18 %) 62 (53 %) p \ .001
Sensory interests (ever): 1 or 2 shown regularly score 1
[n (%)]
11 (15 %) 49 (42 %) p \ .001
Marked with impact—score 2
[n (%)]
3 (4 %) 26 (23 %) p = .001
Any—score 1 or 2 [n (%)] 14 (20 %) 75 (65 %) p \ .001
Sensitivity to noise (current): Slight—score 1 [n (%)] 9 (13 %) 31 (27 %) p = .027
Definite—score 2 [n (%)] 2 (3 %) 28 (24 %) p \ .001
Marked with impact—score 3
[n (%)]
1 (1 %) 6 (5 %) p = .254
Any—score 1–3 [n (%)] 12 (17 %) 65 (56 %) P \ .001
Sensitivity to noise (ever): Slight—score 1 [n (%)] 8 (11 %) 32 (28 %) p = .008
Definite—score 2 [n (%)] 7 (10 %) 40 (34 %) p \ .001
Marked with impact—score 3
[n (%)]
1 (1 %) 12 (10 %) p = .020
Any—score 1–3 [n (%)] 16 (23 %) 84 (72 %) p \ .001
Abnormal idiosyncratic negative response to specific
sensory stimuli (current):
Mild reaction—score 1 [n (%)] 5 (7 %) 23 (20 %) p = .020
Causes some intrusion—score
2 [n (%)]
4 (6 %) 11 (9 %) p = .415
Substantial intrusion—score 3
[n (%)]
0 (-) 2 (2 %) p = .525
Any—score 1–3 [n (%)] 9 (13 %) 36 (31 %) p = .005
Abnormal idiosyncratic negative response to specific
sensory stimuli (ever):
Mild reaction—Score 1 [n
(%)]
7 (10 %) 26 (22 %) p = .030
Causes some intrusion—score
2 [n (%)]
4 (6 %) 14 (12 %) p = .202
Substantial intrusion—score 3
[n (%)]
0 (-) 3 (3 %) p = .287
Any—score 1–3 [n (%)] 11 (15 %) 43 (37 %) p = .001
SSP domains
SSP total Definite difference [n (%)] 23 (32 %) 76 (66 %) p \ .001
Taste/smell sensitivity Definite difference [n (%)] 9 (13 %) 41 (35 %) p = .001
Movement sensitivity Definite difference [n (%)] 12 (17 %) 34 (29 %) p = .050
Under-responsive/seeks sensation Definite difference [n (%)] 23 (32 %) 72 (76 %) p \ .001
Auditory filtering Definite difference [n (%)] 35 (49 %) 81 (70 %) p = .004
Low energy/weak Definite difference [n (%)] 20 (28 %) 42 (36 %) p = .232
Visual/auditory sensitivity Definite difference [n (%)] 3 (4 %) 37 (32 %) p \ .001
3602 J Autism Dev Disord (2016) 46:3597–3606
123
Table 3 Frequency and percentage of children who always or frequently displayed behaviours on the Short Sensory Profile
SEN
(N = 72)
ASD
(N = 116)
Chi-sqaure/Fisher’s
exact
Tactile sensitivity
1. Expresses distress during grooming 5 (7 %) 39 (34 %) p \ .001
2. Prefers long-sleeved clothing even when it is warm or short sleeves when it is
cold
8 (11 %) 20 (17 %) p = .296
3. Avoids going barefoot, especially in grass or sand 4 (6 %) 18 (16 %) p = .060
4. Reacts emotionally or aggressively to touch 5 (7 %) 15 (13 %) p = .231
5. Withdraws from splashing water 4 (6 %) 18 (16 %) p = .060
6. Has difficulty standing in line or close to other people 7 (10 %) 41 (35 %) p \ .001
7. Rubs or scratches out a spot that has been touched 5 (7 %) 12 (10 %) p = .602
Taste/smell sensitivity
8. Avoids certain tastes or food smells that are typically part of children’s diets 7 (10 %) 40 (34 %) p \ .001
9. Will only eat certain tastes 9 (13 %) 37 (32 %) p = .003
10. Limits self to particular food textures/temperatures 7 (10 %) 34 (29 %) p = .002
11. Picky eater, especially regarding food textures 14 (19 %) 41 (35 %) p = .020
Movement sensitivity
12. Becomes anxious or distressed when feet leave the ground 1 (1 %) 9 (8 %) p = .092
13. Fears falling or heights 4 (6 %) 22 (19 %) p = .009
14. Dislikes activities where head is upside down 12 (17 %) 24 (21 %) p = .496
Underresponsive/seeks sensation
15. Enjoys strange noises/seeks to make noise for noise’s sake 11 (15 %) 45 (39 %) p = .001
16. Seeks all kinds of movement and this interferes with daily routines 24 (33 %) 58 (50 %) p = .025
17. Becomes overly excitable during movement activity 13 (18 %) 39 (34 %) p = .020
18. Touches people and objects 15 (21 %) 46 (40 %) p = .007
19. Doesn’t seem to notice when face or hands are messy 20 (28 %) 40 (34 %) p = .338
20. Jumps from one activity to another so that it interferes with play 15 (21 %) 39 (34 %) p = .060
21. Leaves clothing twisted on body 10 (14 %) 46 (40 %) p \ .001
Auditory filtering
22. Is distracted or has trouble functioning if there is a lot of noise around 32 (44 %) 75 (67 %) p = .007
23. Appears to not hear what you say 21 (29 %) 63 (54 %) p = .001
24. Can’t work with background noise 6 (8 %) 25 (22 %) p = .025
25. Has trouble completing tasks when the radio is on 12 (17 %) 33 (28 %) p = .066
26. Doesn’t respond when name is called but you know the child’s hearing is ok 10 (14 %) 39 (34 %) p = .003
27. Has difficulty paying attention 30 (42 %) 70 (60 %) p = .013
Low energy/weak
28. Seems to have weak muscles 7 (10 %) 25 (22 %) p = .045
29. Tires easily, especially when standing or holding particular body position 12 (17 %) 25 (22 %) p = .413
30. Has weak grip 7 (10 %) 17 (15 %) p = .375
31. Can’t lift heavy objects 8 (11 %) 25 (22 %) p = .078
32. Props to support self 8 (11 %) 16 (14 %) p = .592
33. Poor endurance/tires easily 10 (14 %) 27 (24 %) p = .089
Visual auditory sensitivity
34. Responds negatively to unexpected or loud noises 3 (4 %) 43 (37 %) p \ .001
35. Holds hands over ears to protect ears from sound 7 (10 %) 47 (41 %) p \ .001
36. Is bothered by bright lights after others have adapted to the light 2 (3 %) 19 (16 %) p = .004
37. Watches everyone when they move around the room 16 (22 %) 24 (21 %) p = .803
38. Covers eyes or squints to protect eyes from light 3 (4 %) 21 (18 %) p = .006
J Autism Dev Disord (2016) 46:3597–3606 3603
123
impairments (albeit aged 3–6 years) who were reported as
having a probable (13 %) or definite (3 %) difference in
total SSP scores (Tomchek and Dunn 2007). Multiple
hyper-sensitivities (i.e. tactile, taste/smell, and noise) were
much more common in ASD than in the SEN group, as was
severity of hypersensitivity and impact particularly from
noise as shown on ADI score. Sensory interests were more
common in the ASD than SEN group.
Our findings support the inclusion of atypical sensory
responsivity to the environment in the DSM-5 diagnostic
criteria but emphasise that such behaviours are not unique
to ASD; one feature does not make a diagnosis, other
features remain essential. The findings are also supportive
of the hypothesis that sensory symptoms are a non-specific
indicator of brain functional network difference in devel-
opmental psychopathology (Levit-Binnun et al. 2013).
The association of atypical sensory behaviours with
restricted, repetitive and stereotyped behaviours, but not
IQ, are consistent with those of Boyd et al. (2010), Mandy
et al. (2012), Dar et al. (2012) and Wigham et al. (2015)
but inconsistent with Lane et al. (2014) who found hyper-
sensitivity and generalised reactivity to differ by age and
IQ but not ASD severity (as measured by the ADOS
whereas we included history from the ADI-R and ADOS).
We did not explore sensory subtypes but other studies have
found individual sensory subtypes e.g. tactile responsive-
ness patterns in ASD, to be only weakly (or not at all)
correlated with repetitive behaviours and extent of social
impairment (Foss-Feig et al. 2012). Some aspects of
atypical sensory behaviours, e.g. sensory interests, in ASD
may be an expression of positive absorption in a detail of
the environment similar to other restricted and repetitive
behaviours.
Our finding of an association between atypical sensory
behaviours and increased emotional symptoms in ASD is
consistent with the literature showing a potential link
between sensory symptoms and anxiety (Lane et al. 2012)
and depression (Bitsika et al. 2016) although the direction
of effect is not known. Further research is required for a
better understanding of the inter-relationship between aut-
ism, comorbidities and sensory symptoms and, how these
may change over time (Chen et al. 2009; McCormick et al.
2015). Anecdotally, many sensory symptoms persist into
adult life and continue to have a significant impact on
individuals.
Assessing sensory behaviours is limited by the current
methods available, usually through questionnaires com-
pleted by parent or carers or individuals themselves rather
than objective measures (Tavassoli et al. 2016). The SSP
has been widely used clinically and in research studies but
for some items the face validity as a ‘sensory’ behaviour is
unclear e.g. ‘Has a weak grasp’. Some clinically important
items are not recorded in the SSP, for example lack of
response to pain and lack of awareness of temperature,
which are hypo-responsivities frequently commented on by
parents. Thus, for this study we used complete SSP
domains for hypersensitivity but for hyposensitivity, one
domain and two items met face validity as representing
Table 4 Multiple regression
results for Short Sensory Profile
Total Scores and features of
Autism and behavioural factors
as report on the parent SDQ
Coefficient t 95 % CI p
Full scales
F(6108) = 6.50, p \ .001, R2 = .224
IQ .150 1.58 -.038, .337 .117
ADOS age years -.235 -0.10 -4.92, 4.45 .921
ICD 10 total -.066 -0.06 -2.34, 2.20 .954
ADI-R total -.709 -3.42 -1.12, -.298 .001
ADOS G total .370 0.90 -.448, 1.19 .372
SDQ total -1.58 -3.79 -2.40, -.752 \.001
Subscales
F(10,101) = 3.41, p \ .001, R2 = .253
ICD 10_social 2.20 0.91 -2.57, 6.96 .362
ICD 10 communication -1.87 -0.74 -6.83, 3.10 .458
ICD 10 repetitive -5.50 -2.18 -10.5, -.510 .031
SDQ emotional -2.54 -2.96 -4.24, -.834 .004
SDQ conduct -1.18 -1.21 -3/12, .750 .228
SDQ peer relations -1.70 -1.45 -4.03, .621 .149
SDQ hyperactivity -.038 -0.04 -2.09, 2.01 .971
SDQ pro-social -.043 -0.05 -1.87, 1.79 .963
CI confidence interval; Rfsiq Raven’s full scale IQ; ADOS Autistic Diagnostic Observation Scale-Generic;
ICD International Classification of Diseases; SDQ Strengths and Difficulties Questionnaire
3604 J Autism Dev Disord (2016) 46:3597–3606
123
under-responsiveness to sensory stimuli. This aspect of
behaviour may therefore have been underestimated.
Strengths of the study are a well characterised sample, the
use of a recognised sensory questionnaire and a comparison
group who have special educational needs and are a group
in which ASD is often considered as a differential
diagnosis.
In summary, the inclusion of hyper-or hypo respon-
sivity or sensory interests within the ASD diagnostic cri-
teria of DSM-5 is supported. However, comparison of
children with ASD to those with SEN affirms the finding
that young people with other developmental disorders may
also demonstrate altered sensory responsivity. In ASD
altered sensory function was associated with emotional
problems and restricted repetitive behaviours. It remains to
be seen if the profile of sensory responsivities differs
between neurodevelopmental disorders, how these may
differentially impact on function and participation and how
these may change over time.
Acknowledgments We are grateful to the children and families and
the clinical teams in South Thames, whose participation and collab-
oration made the study possible.
Funding This study was funded by the Wellcome Trust and the
Department of Health (Grant Number 039/0026).
Author Contributions All of the individuals listed as authors on this
manuscript contributed to the study design, data collection and or data
analysis along with manuscript preparation. All authors have read the
manuscript and agreed to its submission for publication. All authors
meet the appropriate authorship criteria, nobody who qualifies for
authorship has been omitted, all contributors and funding sources
have been properly acknowledged, and authors and contributors have
approved the acknowledgement of their contributions.
Compliance with Ethical Standards
Conflict of interest Dr Green declares that she has no conflict of
interest. Dr Chandler declares that she has no conflict of interest. Prof
Charman declares that he has no conflict of interest. Prof Simonoff
declares that she has no conflict of interest. Prof Baird declares that
she has no conflict of interest.
Ethical Approval All procedures performed in studies involving
human participants were in accordance with the ethical standards of
the institutional and/or national research committee and with the 1964
Helsinki declaration and its later amendments or comparable ethical
standards.
Informed Consent Informed consent was obtained from all parents
for their and their child’s participation in the study.
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Brief Report: DSM-5 Sensory Behaviours in Children With and Without an Autism Spectrum Disorder
Abstract
Introduction
Methods
Participants
Measures
Data Analysis
Results
Discussion
Acknowledgments
References