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1 page critique Journal of Autism and Developmental Disorders https://doi.org/10.1007/s10803-021-05377-y
Defining in Detail and Evaluating Reliability of DSM-5 Criteria for Autism Spectrum Disorder (ASD) Among Children
C. E. Rice1,2 · L. A. Carpenter3 · M. J. Morrier1 · C. Lord4 · M. DiRienzo2 · A. Boan3 · C. Skowyra5 · A. Fusco6 · J. Baio2 ·
A. Esler7 · W. Zahorodny6 · N. Hobson8 · A. Mars9 · A. Thurm10 · S. Bishop11 · L. D. Wiggins2
Accepted: 13 November 2021
This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2021
Abstract
This paper describes a process to define a comprehensive list of exemplars for seven core Diagnostic and Statistical Manual (DSM) diagnostic criteria for autism spectrum disorder (ASD), and report on interrater reliability in applying these exem- plars to determine ASD case classification. Clinicians completed an iterative process to map specific exemplars from the CDC Autism and Developmental Disabilities Monitoring (ADDM) Network criteria for ASD surveillance, DSM-5 text, and diagnostic assessments to each of the core DSM-5 ASD criteria. Clinicians applied the diagnostic exemplars to child behavioral descriptions in existing evaluation records to establish initial reliability standards and then for blinded clinician review in one site (phase 1) and for two ADDM Network surveillance years (phase 2). Interrater reliability for each of the DSM-5 diagnostic categories and overall ASD classification was high (defined as very good .60?.79 to excellent = .80 Kappa values) across sex, race/ethnicity, and cognitive levels for both phases. Classification of DSM-5 ASD by mapping specific exemplars from evaluation records by a diverse group of clinician raters is feasible and reliable. This framework provides confidence in the consistency of prevalence classifications of ASD and may be further applied to improve consistency of ASD diagnoses in clinical settings.
Keywords Autism · Autism spectrum disorder · Diagnosis · DSM-5 · Classification · Clinician reliability
? C. E. Rice [email protected]
1 Emory University, Atlanta, GA, USA
2 Centers for Disease Control and Prevention, Atlanta, GA, USA
3 Medical University of South Carolina, Charleston, SC, USA
4 University of California Los Angeles, Los Angeles, CA, USA
5 Washington University in St. Louis, St. Louis, MO, USA
6 Rutgers New Jersey Medical School, Newark, NJ, USA
7 University of Minnesota, Minneapolis, MN, USA
8 Independent Consultant, Keller, TX, USA
9 Hunterdon Healthcare System, Flemington, NJ, USA
10 National Institute of Mental Health, Bethesda, MD, USA
11 University of California San Francisco, San Francisco, CA, USA
Introduction
Autism spectrum disorder (ASD) is a neurodevelopmen- tal disorder defined by a profile of persistent challenges in social communication and interaction and the presence of restrictive, repetitive patterns of behavior, interests, or activities that are present early in childhood and cause clini- cally significant functional impairments (APA, 2013). At the individual level, being diagnosed with ASD can inform intervention, supports, and understanding of a person?s strengths and challenges. At a community or population- level, diagnoses of autism spectrum conditions can inform policies, services, and supports available and may impact ultimate functioning. Understanding why and how people are diagnosed with behavioral conditions such as ASD can provide insight into the meaning of ascribing such labels for individuals and communities. This paper describes an itera- tive process of specifying and reliably applying exemplars to endorse the presence/absence of each of the core ASD DSM-5 criteria and to, ultimately, classify children as meet- ing an ASD diagnostic classification. This goal is to increase
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conceptual and practical consistency in the way clinicians consider behavioral criteria for diagnosis ASD.
Autism was first described as a condition by Kanner (1943) and ?Infantile Autism? was first included in the Diag- nostic and Statistical Manual (DSM) in 1980 as one subtype of several ?Pervasive Developmental Disorders? (PDDs) (APA, 1980). ASD is now considered in the DSM-5 as a single categorical spectrum of behaviors with heterogenous core and co-occurring features (APA, 2013). Across taxo- nomic changes, diagnosis has relied on behaviorally-defined diagnostic criteria to meet a categorial diagnosis (Volkmar & McPartland, 2014). Guided by current diagnostic crite- ria, professionals with appropriate training, credentials, and experience (Shulman et al., 2020a) assess a person?s profile of behavior to determine if the evidence supports endors- ing persistent deficits in the domains of Social Communi- cation and Interaction (SCI) and Restricted and Repetitive Behaviors or Interests (RRBI) that are present early, cause impairment, and are not better explained by other conditions, specifically intellectual disability or global developmental delay (APA, 2013).
Given the behaviorally-defined and heterogenous nature
of an ASD diagnosis, clinician judgment is an important factor to consider in arriving at an ASD diagnosis. Stud- ies comparing community-based diagnoses of ASD with an independent assessment battery and best-estimate diagno- sis found a lack of agreement on ASD diagnoses for 1/4 of the children (Hausman-Kedem et al., 2018; Wiggins et al., 2020). In another study, only 60% of differential diagnoses for ASD were made with high clinician certainty (McDon- nell et al., 2018). An analysis of clinical team diagnostic discussions indicated that subjective ?feelings of ASD? and professional evaluation of the quality of informant reports were prominent among clinicians when making the diag- nosis (Hayes et al, 2020). Given the identification of ASD by affirming the presence of a profile of relevant behaviors, understanding the way different professionals ascribe spe- cific behaviors as evidence of the diagnosis can add speci- ficity to clinical and research efforts to link symptoms with treatment or with risk factors or etiology in research.
Research has focused on developing and evaluating tools to increase the reliability of autism spectrum diagnoses (including ?autistic disorder? and other PDD historical sub- types) for both research and clinical purposes compared to ?best-estimate clinical judgment? of experienced research clinicians (Bishop et al., 2017; Hausman-Kedem et al., 2018; Kamp-Becker, 2018; Klin et al., 2000; Lord et al., 2012a, 2012b). Specific behaviors that constitute the way these cri- teria are identified, measured, and applied individually and together are often guided by the specific questions asked in diagnostic instruments (Aiello et al., 2017; Rutherford et al., 2016; Shulman et al., 2020b; Wiggins et al., 2015). Instru- ments, such as the Autism Diagnostic Observation Schedule
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Journal of Autism and Developmental Disorders
(ADOS-2) (Lord et al., 2000) and Autism Diagnostic Inter- view-Revised (ADI-R) (Lord et al., 1994), have organized specific autism-relevant behaviors rated from person obser- vation and caregiver interview and provide research-based algorithms that determine whether the person satisfies the instrument criteria for ASD with validation comparing to clinical diagnosis. However, meeting the threshold on a single instrument is not sufficient for diagnosis. Ultimately, ASD diagnosis depends on clinician confirmation of the DSM-5 criteria from multiple sources of information (Shul- man et al., 2020a; Volkmar & McPartland, 2014), and lit- tle attention has been given to how clinicians identify and endorse behavioral exemplars that constitute the evidence needed for an ASD diagnosis. Despite robust research on the overall diagnosis and supporting subdomains (Bishop et al., 2016; Frazier et al., 2012; Lord et al., 2012a, 2012b; McPartland et al., 2012; Thurm et al., 2019; Uljarevic et al., 2017; Zheng et al., 2020), research on behavioral exemplars that clinicians consider in endorsing the social and behav- ioral diagnostic criteria is lacking.
The DSM-5 ASD criteria were described broadly to
encompass a range of symptom presentations across age and developmental level. Beyond the initial categorical diagnosis (ASD/non-ASD), further indicators of function- ing such as language and cognitive levels, adaptive behav- ior, and co-occurring symptoms and features also must be specified (APA, 2013; Bolte & Diehl, 2013; DiRezze et al., 2016; Gardner et al., 2018). Moreover, some investigators recommend shifting from dependence on overall (categori- cal) diagnosis to recognition of specific phenotypic features, behaviors, and/or biologic pathways and to intervention research that cuts across behaviorally-defined psychiatric conditions (Constantino & Charman, 2016; Cuthbert & Insel, 2013). Clinical and research trends have emphasized a dimensional approach in overall symptom distribution across the population (Constantino & Todd, 2005; Riglin et al., 2020), subdimensions of primary social and behav- ioral domains of ASD (Bishop et al., 2016; Uljarevic et al., 2017), and stipulation of specifiers such as cognitive level, language capacities, and the presence of other co-occurring conditions (APA, 2013; Gardner et al., 2018). With the move to ?lump? the overall diagnostic category into a single ASD diagnosis without subtypes, and ?split? the dimensional aspects across the profile of symptoms and into domains and by co-occurring features, the challenge has become establishing valid and reliable categorical and dimensional ways of characterizing behaviors to inform etiologic and treatment research and meaningful supports (Gardner et al., 2018; Lord et al., 2012a, 2012b). Careful specification of the behaviors representing each of the ASD diagnostic criteria may be informative in clarifying a dimensional approach to the spectrum of presentation representing each criterion. For example, the diagnostic criterion A3 ?deficits in developing,
