Autism Spectrum Disorder Decision Tree Subgroups Predict Adaptive Behavior and Autism Severity Trajectories in...

Area of Science:

• Neurodevelopmental Disorders
• Behavioral Psychology
• Pediatric Medicine

Background:

• Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition.
• Identifying distinct ASD subgroups is crucial for understanding varied developmental trajectories.
• Previous research indicates heterogeneity in ASD severity and adaptive functioning.

Purpose of the Study:

• To retrospectively analyze the adaptive skills and autism severity trajectories in behaviorally distinct ASD subgroups.
• To evaluate the prognostic value of the Autism Spectrum Disorder-Decision Tree (ASD-DT) in predicting these trajectories.
• To determine if the ASD-DT can aid in clinical and research applications for ASD.

Main Methods:

• Utilized classification and regression tree algorithm on PDD Behavior Inventory (PDDBI) data to create the ASD-DT.
• Identified three ASD subgroups: minimally verbal, verbal, and atypical, based on the ASD-DT.
• Retrospectively analyzed adaptive skills and autism severity trajectories within these identified subgroups.

Main Results:

• The ASD-DT successfully identified three behaviorally distinct ASD subgroups.
• Each subgroup exhibited unique trajectories in adaptive skills and autism severity.
• These trajectories varied based on the type of adaptive behavior assessed, supporting the ASD-DT's prognostic value.

Conclusions:

• The ASD-DT demonstrates prognostic value for identifying distinct developmental trajectories in ASD.
• The identified ASD subgroups (minimally verbal, verbal, atypical) have differential adaptive behavior outcomes.
• The ASD-DT can be a valuable tool for both clinical practice and research in autism spectrum disorder.