Digital Technologies and Pediatric Mental Health in Urban Asian Populations: A Narrative Review of Passive Sensing, AI-Enabled Interventions, and Ethical Barriers

Background: The rapid digitization of daily life across Asia's urban centres has positioned smartphones as ubiquitous companions in the lives of children and adolescents. Passive sensing technologies embedded in these devices-including accelerometers, GPS receivers, screen state monitors, and communication logs-are increasingly studied as potential tools for monitoring pediatric mental health at scale. Concurrently, artificial intelligence (AI)-enabled interventions delivered through mobile applications and chatbots are being explored as accessible, scalable alternatives to traditional mental healthcare for youth. Despite growing enthusiasm, significant methodological, ethical, and implementation challenges temper the clinical promise of these approaches. Objectives: This narrative review synthesizes evidence from three thematic domains: (1) correlations between passive smartphone sensing and pediatric mental health outcomes in urban Asian populations; (2) clinical outcomes of AI-enabled early interventions for adolescent anxiety in China, Singapore, and Hong Kong; and (3) ethical barriers to the responsible adoption of passive digital phenotyping in Asian pediatric care. Methods: A structured narrative synthesis was conducted drawing on three systematic literature searches covering research published between 2019 and 2024. Across the three thematic domains, a combined initial pool of 3,010 papers was identified; following deduplication, abstract screening, and semantic relevance assessment, 60 papers formed the basis of this review. Results: Higher screen time is consistently associated with depressive symptoms, attention deficits, and sleep disturbances across Singapore, India, and China, though effect sizes are modest and socioeconomic status remains a stronger predictor. Machine learning models employing multimodal passive sensor data demonstrate moderate accuracy in predicting negative affect but require personalization. AI-enabled interventions — primarily app-based cognitive behavioural therapy (CBT) and chatbots — show small but statistically significant reductions in anxiety and stress among adolescents in China and Hong Kong; however, sustained effects beyond three months remain unproven. Significant ethical barriers persist, including unresolved consent and assent frameworks for minors, algorithmic bias risk, regulatory inadequacy, and digital inequity. Conclusions: Passive smartphone sensing and AI-enabled interventions hold genuine promise for scalable pediatric mental health monitoring and support in urban Asia, but require longitudinal validation, cultural adaptation, and robust ethical governance to realize their potential. Future research should prioritize mechanistic studies, high-risk populations, Singapore-specific evidence, and the co-design of culturally appropriate regulatory frameworks.