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Quantifying the Optimal Structure of the Autism Phenotype: A Comprehensive Comparison of Dimensional, Categorical, and Hybrid Models.

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OBJECTIVE The two primary - seemingly contradictory - strategies for classifying child psychiatric syndromes are categorical and dimensional; conceptual ambiguities appear to be greatest for polythetic syndromes such as autism… Click to show full abstract

OBJECTIVE The two primary - seemingly contradictory - strategies for classifying child psychiatric syndromes are categorical and dimensional; conceptual ambiguities appear to be greatest for polythetic syndromes such as autism spectrum disorder (ASD). Recently, a compelling alternative has emerged that integrates both categorical and dimensional approaches (ie, hybrid model) thanks to the increasing sophistication of analytic procedures. This study aimed to quantify the optimal phenotypic structure of ASD by comprehensively comparing categorical, dimensional, and hybrid models. METHOD The sample comprised 3,825 youth, who were consecutive referrals to a university developmental disabilities or child psychiatric outpatient clinic. Caregivers completed the Child and Adolescent Symptom Inventory-4R (CASI-4R), which includes an ASD symptom rating scale. A series of latent class analyses, exploratory and confirmatory factor analyses, and factor mixture analyses was conducted. Replication analyses were conducted in an independent sample (N=2,503) of children referred for outpatient evaluation. RESULTS Based on comparison of 44 different models, results indicated that the ASD symptom phenotype is best conceptualized as multi-dimensional versus a categorical or categorical-dimensional hybrid construct. ASD symptoms were best characterized as falling along three dimensions (ie, social interaction, communication, and repetitive behavior) on the CASI-4R. CONCLUSION Findings reveal an optimal structure with which to characterize the ASD phenotype using a single, parent-report measure, supporting presence of multiple correlated symptom dimensions that traverse formal diagnostic boundaries and quantify the heterogeneity of ASD. These findings inform understanding of how neurodevelopmental disorders can extend beyond discrete categories of development and represent continuously-distributed traits across the range of human behaviors.

Keywords: quantifying optimal; optimal structure; hybrid models; categorical dimensional; structure autism; structure

Journal Title: Journal of the American Academy of Child and Adolescent Psychiatry
Year Published: 2018

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