AI-SUPPORTED BEHAVIOR MANAGEMENT FOR CHILDREN WITH AUTISM SPECTRUM DISORDER

Abstract

Introduction: Autism spectrum disorder (ASD) is linked to the major difficulties in regulating behavior, such as emotional dysregulation, attention control, and social disabilities. The recent developments in artificial intelligence (AI) provided adaptive applications and wearable tools as the supplementary behavior management tools in children with ASD.

Aim: This study aimed to examine the effectiveness of AI-supported tools in improving behavior regulation and intervention outcomes among children with ASD in Pakistan.

Methodology: A quantitative cross-sectional design was used with a sample of 110 participants, including parents, therapists, and teachers. The data was gathered with the help of structured questionnaires which evaluated the usage and results of behavior of AI tools. Descriptive statistics, correlation and regression analysis were employed as the statistical analysis.

Results: Findings indicated that adaptive mobile applications were the most commonly used tools. Mean scores of the behavior indicators were observed to be positive, with emotional regulation among the most improved. Correlation and regression tests were used to determine an important positive correlation between behavior outcomes and AI usage. The participants who had both the app and wearable devices had relatively improved results.

Conclusion: AI-supported tools demonstrate strong potential to enhance behavior regulation in children with ASD. These technologies can be effectively used in regular and combined formats to enhance outcomes of interventions, which should be supplementary and not substitutive of classic interventions.