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


Journal

Journal of the American Academy of Child and Adolescent Psychiatry
ISSN: 1527-5418
Titre abrégé: J Am Acad Child Adolesc Psychiatry
Pays: United States
ID NLM: 8704565

Informations de publication

Date de publication:
09 2019
Historique:
received: 16 02 2018
revised: 22 09 2018
accepted: 18 10 2018
pubmed: 16 2 2019
medline: 24 7 2020
entrez: 16 2 2019
Statut: ppublish

Résumé

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, a 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. 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. Based on comparison of 44 different models, results indicated that the ASD symptom phenotype is best conceptualized as multidimensional 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. Findings reveal an optimal structure with which to characterize the ASD phenotype using a single, parent-report measure, supporting the 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.

Identifiants

pubmed: 30768420
pii: S0890-8567(18)31894-X
doi: 10.1016/j.jaac.2018.09.431
pmc: PMC6488452
mid: NIHMS1511033
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

876-886.e2

Subventions

Organisme : NIMH NIH HHS
ID : R01 MH077997
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH110585
Pays : United States

Commentaires et corrections

Type : CommentIn
Type : CommentIn

Informations de copyright

Copyright © 2018 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

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Auteurs

Hyunsik Kim (H)

Stony Brook University, NY. Electronic address: hyunsik.kim2@gmail.com.

Cara Keifer (C)

Stony Brook University, NY.

Craig Rodriguez-Seijas (C)

Stony Brook University, NY.

Nicholas Eaton (N)

Stony Brook University, NY.

Matthew Lerner (M)

Stony Brook University, NY.

Kenneth Gadow (K)

Stony Brook University, NY.

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