Abstract
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 that maps, rather than validates, the computational approaches available for inferring the cognitive and affective states of Cyber-Syndrome from digital behavior. Because the construct still lacks established diagnostic instruments, the review is positioned as an assembly of the evidence base that its future operationalization will require rather than as a validation of it. 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.