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Journal of Autism and Developmental Disorders

Gepubliceerd in:

06-09-2022 | Original Paper

Network Structure of Autism Spectrum Disorder Behaviors and Its Evolution in Preschool Children: Insights from a New Longitudinal Network Analysis Method

Auteurs: Farhad Montazeri, Jan K. Buitelaar, Iris J. Oosterling, Annelies de Bildt, George M. Anderson

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 11/2023

Abstract

Network modeling of the social, communication and restrictive/repetitive behaviors (RRBs) included in the definition of Autism Spectrum Disorder was performed. The Autism Diagnostic Interview-Revised (ADI-R) assessed behaviors in 139 pre-school cases at two cross-sections that averaged 34.8 months apart. Cross-sectional networks were based on the correlation matrix of the ADI-R behavioral items and the “bootCross” method was developed and enabled the estimation of a longitudinal network. At both stages, RRB items/nodes formed a consistent peripheral cluster, while social and communication nodes formed a core cluster that diverged with time. These differences in the nature and evolution of the RRB and socio-communicative dimensions indicate that their inter-behavior dynamics are very different. The most central behaviors across stages are proposed as prime targets for efficient therapeutic intervention.

vorige artikel Atypical Semantic Fluency and Recall in Children and Adolescents with Autism Spectrum Disorders Associated with Autism Symptoms and Adaptive Functioning

volgende artikel Adaptation and pilot implementation of the Psychosocial Assessment Tool for Autism Spectrum Disorders (PAT-ASD)

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Titel: Network Structure of Autism Spectrum Disorder Behaviors and Its Evolution in Preschool Children: Insights from a New Longitudinal Network Analysis Method
Auteurs: Farhad Montazeri
Jan K. Buitelaar
Iris J. Oosterling
Annelies de Bildt
George M. Anderson
Publicatiedatum: 06-09-2022
Uitgeverij: Springer US
Gepubliceerd in: Journal of Autism and Developmental Disorders / Uitgave 11/2023
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI: https://doi.org/10.1007/s10803-022-05723-8

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