Remote monitoring of social behavior in children with autism: The role of digital phenotyping in public programs

Autism Spectrum Disorder (ASD) is characterized by social and behavioral challenges, making early identification and continuous monitoring crucial for effective intervention. Traditional methods of monitoring social behavior in children with ASD often face limitations, particularly in resource-limited settings. The advent of digital phenotyping—using data from smartphones, wearables, and other digital tools to track behaviors—presents new opportunities for remote monitoring. This review examines the role of digital phenotyping in ASD care, focusing on its integration into public health programs. It explores key technologies for remote monitoring, the advantages of digital phenotyping in tracking social interactions, and the challenges posed by privacy and data security concerns. Additionally, the review discusses the policy implications and potential for large-scale adoption in public programs. Finally, it highlights emerging trends, such as AI integration, which could enhance the effectiveness of digital phenotyping in diagnosing and treating children with ASD. The review underscores the potential of digital phenotyping to revolutionize ASD monitoring, enabling more personalized, data-driven approaches in public healthcare systems.