Computational Approaches to Cyber-Syndrome: A Scoping Review with Considerations for Adolescent Mental Health

Cyber-Syndrome denotes the physical, social, and thinking disorders arising from problematic cyberspace interactions, with its thinking dimension encompassing cognitive deficits (e.g., attentional impairment, executive dysfunction) and affective disturbances (e.g., mood disorders, emotional dysregulation). Conventional assessment approaches, relying primarily on self-report questionnaires and laboratory-based tasks, are unable to capture the rapid, context-dependent fluctuations of mental states in real-world digital environments. Leveraging advances in computational psychiatry, affective computing, and machine learning, this paper presents a scoping review of computational approaches for inferring cognitive and affective states of Cyber-Syndrome from digital behavior. It situates Cyber-Syndrome within the Cyber-Physical-Social-Thinking (CPST) space framework, reviews the principal data sources, and covers the computational methods used to analyze them. It then synthesizes evidence from adolescent studies and examines the research institutions and open-source platforms that have driven methodological progress in the field. Finally, it discusses key challenges and outlines future directions essential for clinical translation and real-world deployment, particularly in adolescent mental health.