Categorical versus dimensional structure of autism spectrum disorder: A multi-method investigation

Thomas W Frazier; Lacey Chetcuti; Fouad A Al-Shaban; Nick Haslam; Iman Ghazal; Eric W Klingemier; Mohammed Aldosari; Andrew J O Whitehouse; Eric A Youngstrom; Antonio Y Hardan; Mirko Uljarević

doi:10.1002/jcv2.12142

Categorical versus dimensional structure of autism spectrum disorder: A multi-method investigation

JCPP Adv. 2023 Feb 21;3(2):e12142. doi: 10.1002/jcv2.12142. eCollection 2023 Jun.

Authors

Affiliations

¹ Department of Psychology John Carroll University University Heights Ohio USA.
² Olga Tennison Autism Research Centre School of Psychology and Public Health La Trobe University Melbourne Victoria Australia.
³ Neurological Disorders Research Center Qatar Biomedical Research Institute Hamad Bin Khalifa University Doha Qatar.
⁴ Melbourne School of Psychological Sciences University of Melbourne Melbourne Victoria Australia.
⁵ Caregiver Experience Cleveland Clinic Cleveland Ohio USA.
⁶ Neurological Institute Cleveland Clinic Cleveland Ohio USA.
⁷ Telethon Kids Institute University of Western Australia Perth Western Australia Australia.
⁸ Department of Psychology and Neuroscience University of North Carolina at Chapel Hill Chapel Hill North Carolina USA.
⁹ Department of Psychiatry and Behavioral Sciences Stanford University Stanford California USA.

Abstract

Background: A key question for any psychopathological diagnosis is whether the condition is continuous or discontinuous with typical variation. The primary objective of this study was to use a multi-method approach to examine the broad latent categorical versus dimensional structure of autism spectrum disorder (ASD).

Method: Data were aggregated across seven independent samples of participants with ASD, other neurodevelopmental disorders (NDD), and non-ASD/NDD controls (aggregate Ns = 512-16,755; ages 1.5-22). Scores from four distinct phenotype measures formed composite "indicators" of the latent ASD construct. The primary indicator set included eye gaze metrics from seven distinct social stimulus paradigms. Logistic regressions were used to combine gaze metrics within/across paradigms, and derived predicted probabilities served as indicator values. Secondary indicator sets were constructed from clinical observation and parent-report measures of ASD symptoms. Indicator sets were submitted to taxometric- and latent class analyses.

Results: Across all indicator sets and analytic methods, there was strong support for categorical structure corresponding closely to ASD diagnosis. Consistent with notions of substantial phenotypic heterogeneity, the ASD category had a wide range of symptom severity. Despite the examination of a large sample with a wide range of IQs in both genders, males and children with lower IQ were over-represented in the ASD category, similar to observations in diagnosed cases.

Conclusions: Our findings provide strong support for categorical structure corresponding closely to ASD diagnosis. The present results bolster the use of well-diagnosed and representative ASD groups within etiologic and clinical research, motivating the ongoing search for major drivers of the ASD phenotype. Despite the categorical structure of ASD, quantitative symptom measurements appear more useful for examining relationships with other factors.

Keywords: autism; categorical; dimensional; latent; taxometric.

Abstract

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