Description
Each class, students will be responsible for reading three research articles and completing written responses to thereadings for that day. These responses are meant to facilitate class discussion of the assigned material. For eachresponse, students will be required to write a one-page paper synthesizing the three articles and include at least 1discussion question per article that they are prepared to bring up in class that day. Article Response assignmentsmust be turned in online via Canvas by 12:00 PM (noon) on the day of class (Thursday). Only assignmentssubmitted ON TIME via the designated link on Canvas will be graded. NO EXCEPTIONS.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.Times New Roman 12Remember citations and intext citationsPlease find the 3 articles attached
bs_bs_banner
ORIGINAL ARTICLE
Towards the DSM-5 Criteria for Autism: Clinical, Cultural, and
Research Implications
Giacomo Vivanti, Kristelle Hudry, David Trembath, Josephine Barbaro, Amanda Richdale and
Cheryl Dissanayake
Olga Tennison Autism Research Centre, School of Psychological Science, La Trobe University
The new edition of the DSM is proposing significant changes to current diagnostic definitions of autism and related conditions. In this article, we
will discuss the clinical, research, and cultural implications of these changes. We conclude that the new criteria appear to better reflect current
understanding of the autism spectrum disorder than the current DSM-IV criteria. As expected with any major change in classification systems,
there are also significant risks, which will have to be carefully monitored and addressed by both policy makers and the scientific community to
ensure that best clinical practice and research are facilitated and advanced.
Key words:
Asperger’s disorder, autism, DSM-5, ICD, social communication disorder.
What is already known on this topic
What this paper adds
1 Autism and related conditions cannot be diagnosed using
medical tests. Therefore, diagnosis of these complex disorders
still relies on behavioural features defined by classification
systems such as the DSM (American Psychiatric Association)
and the International Classification of Diseases (ICD; World
Health Organization).
2 Since the publication of the current diagnostic definition of
autism and related conditions in the DSM-IV (1994), an unprecedented amount of research has been undertaken to investigate
the nature and developmental course of these disorders.
3 The knowledge generated by this research has led the DSM
committee to propose significant changes in the diagnostic definition of autism and related conditions in the next edition of the
DSM, scheduled to be published in March 2013.
1 Analysis of the potential implications of the new diagnostic definition suggests that the DSM-5 diagnostic criteria have the
potential to simplify the diagnostic process and increase diagnostic reliability.
2 However, it is possible that some individuals who currently meet
criteria for autism or related conditions will no longer meet criteria under the new DSM-5 diagnostic definition.
3 Another risk is that the next edition of the ICD will not conform to
the new DSM-5 criteria, thus jeopardising the international consensus about diagnostic criteria.
Almost two decades after the publication of the DSM-IV criteria,
the new edition of the DSM, scheduled to be published in 2013,
is proposing significant changes to current diagnostic definitions
of autism and related conditions. Some of these changes are of
a controversial nature and concerns have been raised by the
scientific community (McPartland, Reichow, & Volkmar, 2012;
Rutter, 2011; Wing, Gould, & Gillberg, 2011) and by major
advocacy groups (e.g., Autism Speaks, Asperger Services Australia, UK National Autistic Society). In particular, with the
introduction of the new diagnostic criteria, some of the diagCorrespondence: Giacomo Vivanti, Olga Tennison Autism Research
Centre, School of Psychological Science, La Trobe University, Bundoora
Campus, Melbourne, VIC 3086, Australia. Fax: +61 3 9479 1956; email:
g.vivanti@latrobe.edu.au
Accepted for publication 19 December 2012
doi:10.1111/ap.12008
258
nostic concepts that have crucially influenced clinical practice,
research studies, and cultural perceptions of autism will no
longer be used, most notably the concepts of “Asperger’s disorder,” “pervasive developmental disorders,” and the “triad of
symptoms.” The purpose of this position article is to summarise
the proposed changes and to consider their possible clinical,
research, and cultural implications.
Main Differences between DSM-IV
and DSM-5
The proposed criteria for the DSM-5 involve one central
diagnosis—autism spectrum disorder (ASD)—that will replace
the different subtypes defined by the DSM-IV (autistic disorder,
Asperger’s disorder, childhood disintegrative disorder, and pervasive developmental disorder—not otherwise specified (PDDNOS)). The diagnosis of Rett syndrome will no longer be
included in the DSM. The ASD diagnosis will be accompanied by
Australian Psychologist 48 (2013) 258–261
© 2013 The Australian Psychological Society
G Vivanti et al.
the indication of the level of symptom severity (on a 3-point
scale ranging from “requiring support” to “requiring very substantial support”) as well as relevant clinical “specifiers,” including language and cognitive ability levels.
Social and communication problems will be melded into one
category, “social/communication deficits,” which, together with
“fixated interests and repetitive behaviours,” will replace the
traditional triad of symptoms (impaired social reciprocity,
impaired language/communication, and restricted and repetitive pattern of interests/activities) that has been in use since
autism (childhood autism) first found a home in DSM-III. Language impairment/delay is not listed as a relevant feature for the
diagnosis of ASD.
Unusual sensitivity to sensory stimuli, a clinical feature of
autism that was not listed in the previous criteria, will now be
included as a specification of the behaviours that can be coded
in the “fixated interests and repetitive behaviours” domain.
The diagnostic criterion of onset before 36 months is replaced
with a more “open” definition, stating that “Symptoms must be
present in early childhood, but may not become fully manifest
until social demands exceed limited capacities.”
The DSM-5 will also introduce a new diagnostic label within
the category of Language Impairments; “Social Communication
Disorder.” This diagnosis appears to be quite similar to that
of ASD, as individuals diagnosed with social communication
disorder should have an “impairment of pragmatics” and
impairment in the “social uses of verbal and nonverbal communication.” However, there are two key factors that will differentiate children diagnosed with ASD and those diagnosed
with social communication disorder. First, children with social
communication disorder must have “persistent difficulties in
pragmatics and or the social use of verbal and non-verbal communication in natural contexts, which affect the development
of social reciprocity and social relationships” that cannot be
explained by children having difficulties with their language
skills (e.g., word structure and grammar) or intellectual disability. Therefore, a child presenting with broad language difficulties
(not just in the area of pragmatics) or cognitive delay is unlikely
to meet the first criteria for social communication disorder.
Second, the presence of fixated interests and repetitive behaviours is an exclusionary criterion for social communication disorder. Therefore, the presence of repetitive behaviours will be
crucial for the differential diagnosis of ASD.
Finally, with the new diagnostic procedures, if the child
presents with additional symptoms that are sufficient to meet
criteria for other disorders, then he or she will be diagnosed as
having two or more disorders (e.g., ASD + ADHD). This was not
possible under DSM-IV.
Clinical Implications
Twenty years after the introduction of the DSM-IV criteria, there
are still questions regarding the validity of the non-autism
DSM-IV subtypes (Asperger’s disorder, childhood disintegrative
disorder, and PDD-NOS) as separate and distinct from autistic
disorder. Longitudinal research has documented that distinctions among these subtypes is inconsistent over time (e.g., a
child might meet criteria for autistic disorder at age 3 and
PDD-NOS at age 5; Daniels et al., 2011). Moreover, reliability in
Australian Psychologist 48 (2013) 258–261
© 2013 The Australian Psychological Society
DSM-5 criteria for autism
the application of diagnostic subtypes was documented to be
poor across sites (e.g., the same child could be diagnosed as
having Asperger’s disorder at one site and autistic disorder at
another site; Lord et al., 2012), and numerous studies reported
little or no qualitative differences between these groups (see
Macintosh & Dissanayake, 2004, for a review). These findings,
together with data suggesting common genetic risk factors for
the different subtypes, have led to the decision to combine these
diagnostic categories. Therefore, it is possible that the diagnostic
process using DSM-5 will be “simplified,” as clinicians will no
longer need to spend resources to determine what specific
subtype of autism a child has. This change might help with a
more timely diagnosis, thereby getting children into treatment
more quickly.
Nevertheless, concerns have been raised as to whether the
diversity and heterogeneity of ASD can be adequately captured
if subtypes no longer exist. For example, with the introduction
of the proposed DSM-5 criteria, a child with Asperger’s disorder
who has an above-average IQ and a circumscribed interest in
the French Revolution would receive the same diagnosis as a
non-verbal child who spends his days spinning objects and
flapping his hands. However, the DSM-5 guidelines address this
issue by employing a more descriptive approach that involves
accompanying the ASD diagnosis with the indication of relevant
clinical features such as the level of symptom severity and
associated verbal and cognitive abilities. Therefore, instead of a
diagnosis of Asperger’s disorder, the child may receive one of
“ASD with good language skills and high intelligence, requiring
support for his social communication and requiring very substantial support for his repetitive behaviour.”
There are also concerns about the fact that the new definition
will narrow the criteria for ASD, so that people who currently
meet the criteria for a DSM-IV subtype may no longer meet
criteria for an ASD according to DSM-5. This might be especially
relevant for individuals with milder characteristics of autism
(e.g., individuals with Asperger’s disorder, PDD-NOS), as highlighted in a recent study by McPartland et al. (2012). However,
results from the first DSM-5 field trial suggest that only 5–10% of
people currently captured within the pervasive developmental
disorders spectrum will no longer meet criteria for ASD. Many
of them (possibly those who do not present with obvious repetitive behaviour) might now be classified in the new category of
“Social Communication Disorder” (Swedo, 2012).
By bringing social and communication skills together under
one category and eliminating any reference to verbal communication, the proposed criteria focus less on when, and to what
extent, a child has developed language, and more on how he or
she communicates to initiate and maintain social interactions.
This change might lead to earlier diagnoses for those children
who do not show delays in language development, as is the case
for many people who currently meet criteria for Asperger’s
disorder. These individuals are typically identified later than
those presenting with delays in language development (as is the
case for many who meet criteria for autistic disorder).
In terms of treatment, in the 20 years that have passed since
the introduction of the DSM-IV criteria, there is no evidence
that the type of intervention advocated should be based on an
ASD “subtype.” Therefore, there is no reason to anticipate problems with treatment following a move to DSM-5. Clinical
259
DSM-5 criteria for autism
research indicates that treatment goals and strategies should be
planned on the basis of the individual’s profile of strength and
weakness rather than on his or her particular diagnostic label,
and this will not be affected by the proposed changes (National
Research Council, 2001). Nevertheless, the elimination of
DSM-IV subtypes has the potential to impact access to services.
For example, in the USA, some state legislations (e.g., California) and insurance policies allow access to services only to
children diagnosed with autistic disorder. It is not known how
such policies will change in response to the new criteria. One
possibility is that funding will be tied to the severity ratings
proposed in DSM-5, whereby individuals “requiring very substantial support” would have greater access to support services.
While not foreshadowed, such a change will have the potential
to place additional pressure on clinicians responsible for diagnosing ASD to lean towards more severe ratings in the interests
of ensuring access to those in need of services. Nevertheless, this
pressure exists already under the DSM-IV criteria, reflecting
health economics issues rather than the validity of the diagnostic criteria. Irrespective of the approach taken, it is very unlikely
that access to services will be simply extended to anyone with
an ASD diagnosis and, of more concern, to those who meet
criteria for social communication disorder.
In Australia, it has been the case that support has been variously tied to the diagnostic label of autistic disorder versus
Asperger’s disorder with differences across states and across
services despite funding mechanisms (e.g., funding for teachers’
aids, carer payments) needing to be tied to an individual’s level
of disability/functioning regardless of their diagnosis. Therefore,
it is possible, although again not foreshadowed, that such criteria could be expanded to include the proposed severity ratings.
Irrespective of the approach governments take in accommodating the proposed changes, it is imperative that they ensure that
the introduction of the new criteria will not result in changes in
coverage policies that will exclude people with ASD from access
to services (Lord & Jones, 2012).
Research Implications
Through its characterisation of ASD as a heterogeneous group of
conditions, the DSM-IV has stimulated tremendous research into
the different types of ASD. The new criteria, which will replace
five diagnostic labels with a single label, fail to emphasise the
notion of “multiple conditions” within the spectrum. This can be
viewed as a significant limitation for research, as future studies
may necessarily focus on one “entity” (i.e., ASD) rather than
multiple. However, research in the last decade has raised many
questions about subtype boundaries, showing that the symptoms of autistic disorder, Asperger’s disorder, and PDD-NOS are
more similar than different, while the severity and relevance of
the symptoms varies between but also within diagnostic subtypes (e.g., Fernell et al., 2010). The dimensional model proposed by the DSM-5 appears to reflect this combination of
homogeneity in the core symptoms and heterogeneity in the
severity levels, giving up on the idea that such heterogeneity
can be best captured by a discreet number of mutually exclusive
categories. Therefore, it is important that the “simplification”
imposed in adopting a single diagnostic category should not
limit the search for endophenotypes (i.e., subgroups). On the
260
G Vivanti et al.
contrary, it should stimulate more fine-grained investigations
on individual differences within the spectrum, something that is
sorely needed in the field.
Unfortunately, new changes to the diagnostic criteria will
make the comparability of results across old and new studies
difficult. For example, studies using samples diagnosed on the
DSM-IV criteria (i.e., from 1994 to 2013) might include some
individuals who would now fall into “Social Communication
Disorder.” However, information regarding the symptom severity (e.g., scores in diagnostic instruments such as the Autism
Diagnostic Interview, Lord, Rutter, & Le Couteur, 1994; and the
Autism Diagnostic Observation Schedule, Lord, Rutter, DiLavore, & Risi, 1999), language level, and cognitive abilities, typically provided in the most rigorous studies, will hopefully assist
in making relevant comparisons across studies.
A major concern is that changes in the diagnostic definitions
will affect our ability to monitor changes in the prevalence rates
over time. The new classification, in excluding children who
may have formerly received a diagnosis of PDD-NOS (and who
may now be captured under Social Communication Disorder)
may result in an “artificial” inversion of the increasing prevalence trend documented over the last decade (Fombonne,
Quirke, & Hagen, 2011). However, as reasons for the increase in
prevalence are still debated, the introduction of more stringent
criteria may allow for a more rigorous test of prevalence
changes.
The main reason of concern, from a research (and also clinical) point of view, however, lies in the possibility that the
European classification system (i.e., the ICD-10); World Health
Organization, 1992) will retain the current diagnostic definitions of PDD, thereby resulting in substantial differences in the
way these conditions are conceptualised and defined in different
parts of the world. In fact, one of the major achievements of the
DSM-IV working group was to obtain convergence across the
diagnostic criteria used in the two classification systems, thus
creating shared clinical conceptualisation and terminology
across countries. Having a cross-national definition has allowed
comparison across studies conducted in different parts of the
world, thus stimulating research (as reflected in the dramatic
increase of autism research since the publication of the DSM-IV
and ICD-10). It is unknown whether the World Health Organization will adopt the changes proposed for DSM-5 in the next
edition of the ICD (ICD-11). If not, the lack of international
consistency will certainly be detrimental to research efforts
undertaken to understand the nature, causes, and best-practice
treatments for ASDs.
Cultural Implications
The decision to eliminate the distinction between autistic disorder and Asperger’s disorder has begun to raise a cultural storm.
Many people currently diagnosed with the latter condition do
not see themselves as having autism, but rather identify themselves as a specific cultural minority (i.e., the “Aspie” culture;
see websites such as aspieweb.net, wrongplanet.net, or aspieworld.net). This perspective, which has emerged in the last
decade, considers Asperger’s disorder as “a way of being” rather
than a “disability,” let alone a psychiatric condition. Similar to
other cultural minorities, this “community” considers their
Australian Psychologist 48 (2013) 258–261
© 2013 The Australian Psychological Society
G Vivanti et al.
difference from the “mainstream” way of being as a value rather
than a problem; a culture that should be supported and appreciated rather than treated. This position of “I don’t need
treatment, just acceptance” implies a clear separation between
persons with Asperger’s disorder and those with autism whose
need for intervention is universally acknowledged. The lack of
distinction between these conditions as proposed by the DSM-5
criteria places proponents of the “Aspie culture” in a difficult
position. However, it is important to separate the notions of
“medical diagnosis” from those of “cultural” or “personal identity.” Systems of classification are created in order to communicate and share knowledge among clinicians and investigators,
and to facilitate the implementation of legislations and guidelines to address the needs of individuals who have similar characteristics. Medical diagnoses are never intended to define a
person and cannot capture the complexity of one’s personal and
cultural identity, which includes a unique way of being in the
world and relating to others, and a unique personal history.
Therefore, we believe, and hope, that changes in medical/
psychiatric classification systems will not affect the cultural
appreciation of each individual’s unique way of being in the
world, which is richer and more complex than any conceptualisation of diagnostic labelling, past, present, or future.
Conclusions
The bold changes proposed by the DSM-5 committee regarding
PDDs will undoubtedly impact upon the lives of people with
ASD and their families in both direct and indirect ways. Overall,
we believe that the impact will be a positive one. Importantly,
the changes appear to be based on science rather than on lobbying and political negotiations. The relevance of the role of
repetitive behaviours for differential diagnosis, the dimensional
conceptualisation (as opposed to categorical approach), and the
two-factor model of symptom clustering (as opposed to the
symptom triad) all reflect advances in our understanding of ASD
that have occurred in the past two decades (Kim & Lord, 2010;
Lord & Jones, 2012; Mandy, Charman, & Skuse, 2012). The
main reasons for concern include (a) the possibility that some
individuals currently included within DSM-IV classification will
now be classified under a new category (Social Communication
Disorder) for which there are no treatment guidelines or legislation; (b) the possibility that the next edition of the ICD will not
conform to the DSM-5 criteria, thus jeopardising international
consensus that has supported research advancement over previous decades; and (c) the possibility that the notion of multiple
conditions within the spectrum is not clearly reflected in the
new criteria. Of course, other changes might take place before
the publication of the DSM-5 (May 2013) with possible additional implications at different levels. It is likely that future
advancements will lead to further changes in the way we conceptualise these complex disorders until, ultimately, diagnostic
validation will be possible on a pathophysiological basis.
Australian Psychologist 48 (2013) 258–261
© 2013 The Australian Psychological Society
DSM-5 criteria for autism
References
Daniels, A. M., Rosenberg, R. E., Law, J. K., Lord, C., Kaufmann, W. E., &
Law, P. A. (2011). Stability of initial autism spectrum disorder
diagnoses in community settings. Journal of Autism and
Developmental Disorders, 4(1), 110–121.
Fernell, E., Hedvall, Å., Norrelgen, F., Eriksson, M., Höglund-Carlsson, L.,
Barnevik-Olsson, M., & Gillberg, C. (2010). Developmental profiles in
preschool children with autism spectrum disorders referred for
intervention. Research in Developmental Disabilities, 31, 790–799.
Fombonne, E., Quirke, S., & Hagen, A. (2011). Epidemiology of pervasive
developmental disorders. In D. G. Amaral, G. Dawson, & D. H.
Geschwind (Eds.), Autism spectrum disorders (pp. 90–111). New York,
NY: Oxford University Press.
Kim, S. H., & Lord, C. (2010). Restricted and repetitive behaviors in
toddlers and preschoolers with autism spectrum disorders based on
the Autism Diagnostic Observation Schedule (ADOS). Autism
Research, 3(4), 162–173.
Lord, C., & Jones, R. M. (2012). Annual research review: Re-thinking the
classification of autism spectrum disorders. The Journal of Child
Psychology and Psychiatry, 53(5), 490–509.
Lord, C., Petkova, E., Hus, V., Gan, W., Lu, F., Martin, D. M., . . . Risi, S.
(2012). A multisite study of the clinical diagnosis of different autism
spectrum disorders. Archives of General Psychiatry, 69(3), 306–313.
Lord, C., Rutter, M., DiLavore, P., & Risi, S. (1999). Autism Diagnostic
Observation Schedule – WPS (ADOS-WPS). Los Angeles, CA: Western
Psychological Services.
Lord, C., Rutter, M., & Le Couteur, A. (1994). Autism Diagnostic
Interview-Revised: A revised version of a diagnostic interview for
caregivers of individuals with possible pervasive developmental
disorders. Journal of Autism and Developmental Disorders, 24(5),
659–685.
Macintosh, K., & Dissanayake, C. (2004). Annotation: The similarities and
differences between autistic disorder and Asperger’s disorder: A
review of the empirical evidence. Journal of Child Psychology and
Psychiatry, 45, 421–434.
Mandy, W. P., Charman, T., & Skuse, D. H. (2012). Testing the construct
validity of proposed criteria for DSM-5 autism spectrum disorder.
Journal of the American Academy of Child and Adolescent Psychiatry,
51(1), 41–50.
McPartland, J. C., Reichow, B., & Volkmar, F. R. (2012). Sensitivity and
specificity of proposed DSM-5 diagnostic criteria for autism spectrum
disorder. Journal of the American Academy of Child and Adolescent
Psychiatry, 51(4), 368–383.
National Research Council (2001). Educating children with autism.
Committee on Educational Interventions for children with autism.
Division of Behavioral and Social Sciences and Education. Washington,
DC: National Academy Press.
Swedo, S. (2012). An update on the ASD DSM 5 recommendations. Paper
presented at the International Meeting for Autism Research, Toronto,
May 20.
Rutter, M. (2011). Research review: Child psychiatric diagnosis. Journal of
Child Psychology and Psychiatry, 52, 647–660.
Wing, L., Gould, J., & Gillberg, C. (2011). Autism spectrum disorders in the
DSM-V: Better or worse than the DSM-IV? Research in Developmental
Disabilities, 32(2), 768–773.
World Health Organization (1992). ICD-10 classifications of mental and
behavioural disorder: Clinical descriptions and diagnostic guidelines.
Geneva: World Health Organization.
261
Copyright of Australian Psychologist is the property of Wiley-Blackwell and its content may
not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s
express written permission. However, users may print, download, or email articles for
individual use.
Journal of Child Psychology and Psychiatry 57:1 (2016), pp 93–102
doi:10.1111/jcpp.12448
Examining the phenotypic heterogeneity of early
autism spectrum disorder: subtypes and short-term
outcomes
So Hyun Kim,1 Suzanne Macari,1 Judah Koller,2 and Katarzyna Chawarska1
1
Child Study Center, Yale University School of Medicine, New Haven, CT, USA; 2School of Education, Hebrew
University of Jerusalem, Jerusalem, Israel
Background: Phenotypic heterogeneity among toddlers presenting with ASD symptoms complicates diagnostic
considerations and limits our ability to predict long-term outcomes. To address this concern, we sought to identify
more homogeneous subgroups within ASD based on toddlers’ clinical profiles in the second year of life, evaluating
diagnostic stability and clinical outcomes within the subgroups 1–2 years later. Methods: One hundred toddlers
referred for suspected ASD underwent comprehensive assessments at 22 months (SD = 3) and 37 months (SD = 4).
At 22 months, they were clustered based on symptom severity, developmental skills, and adaptive functioning.
Diagnostic stability and clinical outcomes were evaluated within the clusters. Results: Four clusters characterized
by distinct clinical profiles at the time of the first diagnosis were identified. Diagnostic stability was excellent in 3 out
of 4 clusters (93%–100%) and was lowest in the initially least affected cluster (85%). Autism symptom severity was
stable, except for one group where it increased over time (16% of the sample). A large proportion of toddlers showed
significant improvements in verbal and communication skills. Only a small group (17%) exhibited very low levels of
functioning and limited gains over time. Conclusions: Diagnostic stability and developmental progression from the
second to third year of life in toddlers with ASD vary depending on their initial early profiles of relative strengths and
deficits. Although a small minority of toddlers with more complex clinical presentations may not retain their
diagnoses by the age of three, most children continue to exhibit symptoms of autism. Despite limited improvements
in symptom severity, many children show significant gains in verbal functioning. Only a small proportion of children
(17%) exhibit very limited gains despite intensive intervention. These findings support continued efforts to examine
determinants of developmental trajectories including factors mediating and moderating response to treatment.
Keywords: ASD; toddlers; diagnosis; clinical outcomes.
Introduction
Autism Spectrum Disorder (ASD) is an early emerging and highly heterogeneous neurodevelopmental
disorder (APA, 2013). Symptoms of ASD begin to
manifest by the second year of life and include
deficits in verbal and nonverbal communication and
social reciprocity as well as repetitive behaviors,
atypical sensory interests (Chawarska, Klin, Paul,
Macari, & Volkmar, 2009; Guthrie, Swineford, Nottke, & Wetherby, 2013; Kim & Lord, 2010), and
impairments in adaptive functioning (Ray-Subramanian, Huai, & Weismer, 2011). One of the paradigmatic features of ASD is its genotypic and
phenotypic heterogeneity. On the phenotypic level,
heterogeneity is expressed with regard to symptom
severity (Georgiades et al., 2013; Wiggins, Robins,
Adamson, Bakeman, & Henrich, 2011), verbal and
nonverbal IQ (Munson et al., 2008), social attention
(Campbell, Shic, Macari, & Chawarska, 2014), and
response to treatment (Sherer & Schreibman, 2005).
Such heterogeneity hinders attempts to predict clinical outcomes, develop individualized treatment targets and strategies, and identify etiological factors
associated with ASD.
Conflicts of interest statement: No conflicts declared.
One strategy for improving the understanding of
heterogeneity of early syndrome expression involves
investigating the presence of more homogeneous
subtypes among affected toddlers. Only a few studies
have focused on identifying phenotypically less variable subgroups in toddlers with ASD. Wiggins et al.
(2011) clustered a group of 2-year olds (N = 186)
with ASD based on items from the Childhood Autism
Rating Scale (Schopler & Reichler, 1980) and found
three clusters varying in overall symptom levels (i.e.,
‘mild,’ ‘moderate,’ and ‘severe’ impairment). Georgiades et al. (2013) also found three clusters in
3-year olds (N = 391) varying in levels of impairments across symptom domains based on parent
report (Autism Diagnostic Interview Revised; Rutter,
Le Couteur, & Lord, 2003). These studies focused
their clustering analyses on autism symptoms only.
To our best knowledge there have been no studies
examining subgroups of toddlers with ASD based on
multiple features. However, a study by Stevens et al.
(2000) followed 138 preschoolers with ASD to school
age and identified clusters based on measures of
language, nonverbal intelligence, and normal and
abnormal social behavior. In this study, high- and
low-functioning subgroups were identified who continued to show distinct social, adaptive, and developmental outcomes at school age. Therefore,
© 2015 Association for Child and Adolescent Mental Health.
Published by John Wiley & Sons Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main St, Malden, MA 02148, USA
94
So Hyun Kim et al.
considering that levels of social, adaptive, and
developmental functioning are often interdependent,
another highly informative approach to examining
heterogeneity in ASD is to identify subtypes based on
a broader constellation of behavioral characteristics.
The stability of an ASD diagnosis is typically high,
ranging from 84% to 100% in 2–3-year olds (e.g.,
Chawarska, Klin, Paul, & Volkmar, 2007; Chawarska et al., 2009; Guthrie et al., 2013) and from
85% to 89% in children aged 5 years or older (see
Woolfenden, Sarkozy, Ridley, & Williams, 2012 for a
review). There is evidence that, for some children
with ASD, symptoms lessen over time such that the
children may cease to meet diagnostic criteria for
ASD by school-age (Fein et al., 2013). Given recent
advances in early detection and improvements in
early intervention strategies, it is not clear whether
the proportion of children who no longer meet ASD
criteria later during school-age has increased in
recent years. Assuming that clinically meaningful
subtypes exist among toddlers with ASD, it is
possible that diagnostic stability may vary depending on the clinical presentation of affected children in
the second year of life. However, there have been no
direct investigations into the diagnostic stability
among different subtypes within ASD.
In sum, several questions regarding heterogeneity
in diagnostic and clinical outcomes in toddlers with
ASD remain to be investigated. First, considering
that studies have mainly focused on identifying
subgroups based on a single domain (i.e., autism
symptoms), we expand our investigation by considering not only symptom severity but also levels of
cognitive and adaptive functioning. Moreover, toddlers in the most recent studies examining diagnostic and clinical outcomes were either born between
1997 and 2006 (Guthrie et al., 2013) or referred
between 2001 and 2006 (Chawarska et al., 2009).
Here, we focus our inquiry on the cohort of toddlers
diagnosed with ASD more recently, between 2006
and 2012, a period that has been marked by
significant increases in the awareness of early diagnosis, as well as major improvements in early
intervention policies in our capture area (Connecticut, New York, New Jersey, and Massachusetts). By
focusing on this particular cohort, we address the
question of phenotypic variability and developmental
dynamics in toddlers who were diagnosed with ASD
in the very early stages of the disorder and who had
access to early intensive treatment. Toward these
ends, we examine patterns of phenotypic variability
among 100 toddlers presenting with ASD symptoms
between 14 and 27 months who were followed
prospectively to the age of 3 years for a confirmatory
diagnostic assessment. The main objectives of the
study are to: (1) evaluate diagnostic stability in the
whole sample (N = 100); (2) identify more homogeneous subgroups within ASD among a subset of
toddlers who received an initial diagnosis of ASD
(n = 95) based on a constellation of key clinical
J Child Psychol Psychiatr 2016; 57(1): 93–102
features in the second year of life; (3) examine
cluster characteristics with regard to demographic
characteristics and intervention history; and (4)
examine stability of the diagnostic and clinical
presentation in the identified clusters.
Methods
This study was approved by the Human Investigations Committee of Yale University School of Medicine, New Haven,
Connecticut; written informed consent was obtained from all
parents. Assessments were conducted at the Toddler Developmental Disabilities Clinic at the Yale Child Study Center.
Participants
One hundred toddlers (84 males) were referred by parents or
professionals to a university-based clinic or research study in
an urban setting between 2006 and 2012, due to concerns
regarding their cognitive, language, or social development. All
toddlers were first evaluated between 14 and 27 months (Time
1), and were re-evaluated between 30 and 49 months (Time 2).
There was notable heterogeneity in early clinical presentations
in our sample (Table 1). To be included in the present study, a
toddler had to receive an ASD diagnosis either at Time 1 or 2,
or at both times. Participants were primarily drawn from the
northeastern states of the United States: Connecticut, New
Jersey, New York, and Massachusetts. In 79% of cases,
parents reported Caucasian racial background, 5% Asian,
5% African American, and 7% mixed racial heritage; 4% did not
provide race information. Children of Hispanic origin constituted 6% of the sample. Mothers were, on average, 36 years of
age (SD = 5.6) and fathers 38 years (SD = 6.1). Around 80%
and 71% of mothers and fathers, respectively, had a 4-year
college degree.
Procedures
All children underwent a comprehensive assessment conducted by a multidisciplinary team specializing in autism
and other developmental disorders, consisting of measures of
autism symptoms along with language, cognitive, and adaptive
skills.
Table 1 Sample characterization at Time 1 and Time 2
Time 1
N (male:female)
Age
ADOS Comparison Scores
Verbal DQ
% with VDQ > 70
Nonverbal DQ
% with NVDQ > 70
Vineland: Communication
Vineland: Daily Living
Vineland: Socialization
Intensity of Total
Intervention (hr/week)
Educational
Speech/Language
Occupational/Physical
100
21.72
6.92
51.25
39%
80.04
74%
76.09
80.62
78.63
(84:16)
(2.83)
(2.14)
(27.21)
(18.71)
(14.17)
(11.94)
(7.58)
Time 2
100
37.14
7.20
77.56
63%
80.27
68%
85.71
82.38
79.08
(84:16)
(3.72)
(2.09)
(36.09)
(23.22)
(18.18)
(14.07)
(11.56)
N
Range
M (SD)
99
0.9–44
17.44 (9.22)
97
95
92
0.3–40
0.3–12
0.3–15
14.08 (8.40)
2.07 (1.50)
1.79 (1.73)
ADOS, Autism Diagnostic Observation Schedule.
© 2015 Association for Child and Adolescent Mental Health.
doi:10.1111/jcpp.12448
Assessment procedures. Autism symptom severity was
evaluated with the ADOS-G (Lord et al., 2000), using Module 1
(N = 100) at Time 1 and either Module 1 (n = 52) or Module 2
(n = 48) at Time 2, depending on language level. To facilitate
comparisons of symptom severity across modules, comparison
scores (CS) for both algorithm totals (Gotham, Pickles, & Lord,
2009) and domain scores under the algorithm (Social Affect
[SA] and Restricted and Repetitive Behaviors [RRBs]; Esler
et al., 2015; Hus, Gotham, & Lord, 2014) were computed
based on ADOS algorithm scores. Verbal and nonverbal
developmental skills were assessed using the Mullen Scales
of Early Learning (MSEL; Mullen, 1995), which captured Fine
Motor (FM), Visual Reception (VR), Receptive Language (RL),
and Expressive Language (EL) skills and age equivalents (AE).
Developmental quotient (DQ) scores were computed based on
age equivalents from FM and VR scales for nonverbal DQ and
from RL and EL scales for verbal DQ ([average AE scores from
the two scales/chronological age]*100). Levels of adaptive
functioning in the areas of Socialization, Communication, and
Daily Living were quantified with the Vineland Adaptive
Behavioral Scales, 2nd edition (VABS-II; Sparrow, Cicchetti,
& Balla, 2005) using standard scores (M = 100, SD = 15).
Clinical best estimate diagnosis. At both time points,
a clinical best estimate diagnosis was assigned by at least two
expert clinicians based on direct clinical assessment of autism
symptoms (ADOS-G), verbal and nonverbal skills (MSEL), and
adaptive functioning (VABS-II), as well as detailed information
regarding medical and developmental history. Clinicians made
independent diagnostic judgments, and a full consensus
among all clinicians was necessary for the diagnostic assignment (Chawarska et al., 2009). All examiners had previously
established reliability with the ADOS training site and with
each other.
Intervention. At Time 1, all toddlers who received a provisional diagnosis of ASD or other developmental disorders were
referred to their local early intervention agencies for treatment.
Information regarding the type (i.e., educational, speech and
language, occupational and physical therapies) and duration
of intervention received between Times 1 and 2 were gathered
at the follow-up visit via face-to-face parent interview by
clinical social workers. Speech and language as well as
educational therapies were typically delivered using either
behavioral (e.g., Applied Behavioral Analysis) or developmental
(e.g., Floor Time) approaches or both. The hours of each
intervention type were then divided by the weeks elapsed
between Times 1 and 2 to obtain the average intensity of
intervention (hr/week).
Statistical analysis
To identify subgroups among the 95 toddlers who received an
ASD diagnosis at Time 1, we applied Hierarchical Clustering
(HC) analysis to the Euclidean distances between each pair of
subjects with Ward’s method as linkage criterion to the
following set of variables from Time 1: ADOS Social Affect
and Restricted and Repetitive domain scores, Mullen VR, FM,
RL, and EL DQ scores, and Vineland Socialization, Communication, and Daily Living standard scores. All scores were
standardized into Z-scores. The optimal number of clusters
was chosen by the location of an ‘elbow’ in the cluster tree of
height differences on the y-axis versus cluster number on the
x-axis (Tibshirani, Walther, & Hastie, 2001). Cluster characteristics with regard to clinical presentations and demographic
information at Time 1 and intervention intensity between
Times 1 and 2 were evaluated using a series of ANOVAs with
Bonferroni correction for multiple comparisons. Subsequently,
we evaluated the stability of diagnosis over time within the
identified clusters, as well as changes in symptom severity,
© 2015 Association for Child and Adolescent Mental Health.
Examining the phenotypic heterogeneity of early ASD
95
verbal and nonverbal functioning, and adaptive functioning
using Generalized Linear Mixed Models with an unstructured
covariance matrix, while controlling for the intensity of intervention. Cohen’s ds were calculated to examine the magnitudes of changes in these domains using the raw means and
standard deviations. Data analysis was implemented in SPSS
19.
Results
Preliminary analyses
At Time 1, 95 toddlers referred for a differential
diagnosis were diagnosed with ASD. An additional
three toddlers were diagnosed with global developmental delay, one with language delay, and one with
reactive attachment disorder (Table 2); all five toddlers were diagnosed with ASD at Time 2. At Time 2,
6 (6.9%) of 95 toddlers initially diagnosed with ASD
no longer met diagnostic criteria for ASD. Five of
these six toddlers received another diagnosis (e.g.,
language delays or global developmental delays), and
one did not meet criteria for any disorder, although
clinicians noted continued subthreshold vulnerabilities in social communication. The overall stability of
the ASD diagnosis was 93%.
Cluster analysis
The HC analysis identified four clusters among the 95
toddlers who received the ASD diagnosis at Time 1
(Fig. 1, Table 3). There were no significant differences
in the distribution of gender (v2 (3) = .398, p = .94),
multiplex status (v2 (3) = 3.197, p = .36), gestational
age (F(3,89) = 2.00, p = .92), maternal (F(3,91) = .953,
p = .42) or paternal age (F(3,89) = 1.65, p = .18), or age
at the time of first diagnosis (F(3,91) = .179, p = .91)
(See Table S1).
As shown in Table 3, Clusters 1 (36% of the
sample) and 2 (16%) were similar in terms of verbal
and nonverbal skills. Their nonverbal skills were
largely in the average range, but their verbal skills
were significantly delayed at Time 1. Their levels of
restrictive and repetitive behaviors (RRB) were comparable. However, Cluster 2 had less severe Social
Affective (SA) symptoms and lower adaptive skills
than Cluster 1. Clusters 3 (31%) and 4 (17%) had SA
symptoms more severe than both Clusters 1 and 2,
but the differences in the RRB levels were less
Table 2 Stability of the provisional best estimate clinical
diagnosis from Time 1 to Time 2
Confirmatory diagnosis at
Time 2
Provisional diagnosis at Time 1
ASD
Non-ASD
Total
ASD
Non-ASD
Total
89
5
94
6
0
6
95
5
100
96
So Hyun Kim et al.
J Child Psychol Psychiatr 2016; 57(1): 93–102
Figure 1 Dendrogram for clustering analysis
Table 3 Descriptive statistics for the four clusters identified at Time 1
Cluster 1
N (%)
ADOS:SA
ADOS:RRB
Mullen: VRDQ
Mullen: FMDQ
Mullen: RLDQ
Mullen: ELDQ
Vineland: Communication
Vineland: Daily Living
Vineland: Socialization
Intensity of Intervention (hrs/week)
Educational
Speech/Language
Occupational/Physical
34
12.41
3.68
89.11
90.98
73.15
72.12
88.38
91.44
85.41
(36%)
(3.48)a
(16.43)a
(16.43)a
(11.84)a
(29.82)a
(22.89)a
(10.34)a
(10.31)a
(6.68)a
12.23 (7.78)a
1.85 (1.19)
2.01 (2.64)
Cluster 2
15
9.6
3.80
88.97
95.95
70.99
60.26
77.67
76.33
74.27
(16%)
(2.5)b
(1.74)a
(26.17)a
(22.05)a
(31.90)a
(21.86)a
(8.92)b
(4.14)b
(4.79)b
14.00 (7.41)ab
2.26 (1.06)
1.95 (1.31)
Cluster 3
30
16.97
5.27
72.69
81.60
27.49
38.73
66.13
77.50
76.17
(31%)
(1.8)c
(1.55)b
(12.60)b
(10.81)b
(13.93)b
(11.41)b
(11.41)c
(7.47)b
(5.1)b
14.06 (7.28)ab
1.73 (0.98)
1.35 (0.85)
Cluster 4
16
18.31
4.88
49.64
53.76
11.87
27.75
62.75
66.44
72.19
(17%)
(2.20)c
(1.78)a
(9.0)c
(8.18)c
(10.47)c
(10.61)b
(4.31)c
(7.55)c
(4.56)b
19.94 (10.37)b
2.93 (2.74)
1.98 (1.08)
SA, social affect, RRBs, restricted and repetitive behaviors; VR, visual reception; FM, fine motor; RL, receptive language; EL,
expressive language, Means with different superscripts within each row differ significantly; All comparisons with Bonferroni
correction for multiple comparisons.
consistent. Clusters 3 and 4 were also lower functioning with regard to verbal and nonverbal skills
than either Clusters 1 or 2. In comparison to Cluster
3, Cluster 4 had lower nonverbal skills and very
limited ability to understand and respond to language. Cluster 4 also had very delayed adaptive daily
living and socialization skills. Thus, Clusters 1 and 4
appeared to represent the classic extremes of the
‘autism spectrum,’ whereas Clusters 2 and 3 represented children with more intermediate skill levels,
distinguished largely by their levels of social impairment and verbal and nonverbal skills.
Clusters also differed significantly in the intensity
of the educational services (F(3,88) = 3.310, p on
ADOS Comparison scores
8
Cluster 4
Cluster 3
6
Cluster 1
Socializaon standard scores
ADOS Comparison scores
10
Cluster 2
4
2
0
Time 1
110
100
90
70
50
Time 1
Communicaon standard scores
DQ scores
20
Cluster 1
Cluster 2
Cluster 3
Cluster 4
0
Time 1
110
90
70
60
Cluster 4
50
Time 1
Time 2
Vineland daily living
110
Daily living standard scores
DQ scores
60
Cluster 3
80
Nonverbal DQ
80
Cluster 1
Cluster 2
100
Time 2
120
100
Time 2
Vineland communicaon
100
40
Cluster 4
60
Verbal DQ
60
Cluster 1
Cluster 2
Cluster 3
80
Time 2
120
80
97
Cluster 2
Cluster 1
Cluster 3
Cluster 4
40
20
100
90
Cluster 1
80
Cluster 2
Cluster 3
70
Cluster 4
60
50
0
Time 1
Time 2
Time 1
Time 2
Figure 2 Least square means (2 Standard Errors) for ADOS Comparison Scores, Mullen Verbal and Nonverbal DQ, and Vineland
Socialization, Communication, and Daily Living Scores at Time 1 and Time 2
showed a significant decrease in these skills. The
scores for the other clusters remained stable.
Verbal and communication skills. For VDQ and
adaptive communication, there were significant
effects of cluster (p
Purchase answer to see full
attachment