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Quantitative Analysis of Heterogeneity in Academic Achievement of Children With Autism

Abstract : Autism spectrum disorders (ASD) represent a quintessential example of a clinical population with diverse symptom presentations and marked variation in cognitive abilities. However, the extensive literature lacks rigorous quantitative procedures for characterizing heterogeneity of cognitive abilities in these individuals. Here we employ novel clustering and cross-validation procedures to investigate the stability of heterogeneous patterns of cognitive abilities in reading and math in a relatively large sample (N = 114) of children with ASD and matched controls (N = 96). Our analysis revealed a unique profile of heterogeneity in ASD, consisting of a low-achieving subgroup with poor math skills compared with reading and a high-achieving subgroup who showed superior math skills compared with reading. Verbal and central executive working memory skills further differentiated these subgroups. Findings provide insights into distinct profiles of academic achievement in children with ASD, with implications for educational practice and intervention, and provide a novel framework for quantifying heterogeneity in the disorder.
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Contributor : Teresa Iuculano <>
Submitted on : Wednesday, October 7, 2020 - 5:20:02 PM
Last modification on : Friday, February 26, 2021 - 5:58:02 PM

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Lang Chen, Daniel Abrams, Miriam Rosenberg-Lee, Teresa Iuculano, Holly Wakeman, et al.. Quantitative Analysis of Heterogeneity in Academic Achievement of Children With Autism. Clinical Psychological Science, 2018, 7 (2), pp.362-380. ⟨10.1177/2167702618809353⟩. ⟨halshs-02960484⟩



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