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Autism Spectrum Disorder Decision Tree Subgroups Predict Adaptive Behavior and Autism Severity Trajectories in Children with ASD

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A recent cross-sectional analysis of PDD Behavior Inventory (PDDBI) data, analyzed with a classification and regression tree algorithm, yielded a decision tree (the Autism Spectrum Disorder-Decision Tree or ASD-DT) that… Click to show full abstract

A recent cross-sectional analysis of PDD Behavior Inventory (PDDBI) data, analyzed with a classification and regression tree algorithm, yielded a decision tree (the Autism Spectrum Disorder-Decision Tree or ASD-DT) that detected three behaviorally distinct ASD subgroups: minimally verbal, verbal, and atypical. These subgroups differed in PDDBI profiles and in factors previously reported to be predictors of autism severity and adaptive behavior trajectories. We retrospectively analyzed trajectories of adaptive skills and autism severity in these subgroups, defined by ASD-DTs calculated from initial evaluation PDDBIs. Results confirmed predictions that each subgroup had distinct trajectories that varied with the type of adaptive behavior assessed suggesting that the ASD-DT has prognostic value that could be helpful for both clinical and research applications.

Keywords: adaptive behavior; autism; tree; autism severity; decision tree

Journal Title: Journal of Autism and Developmental Disorders
Year Published: 2019

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