Rethinking Personalization in Adolescent Digital Mental Health: Toward Adaptive Behavioral Systems

Digital mental health technologies are increasingly used to support adolescent wellbeing, yet many interventions continue to struggle with long-term engagement and sustainable behavioral impact. A major limitation is that personalization in existing systems often relies on static user profiles, isolated mood reports, or short-term engagement metrics, while adolescent emotional and behavioral needs change continuously across developmental and social contexts.Current digital mental health interventions remain constrained not simply by limited personalization, but by their inability to adapt to evolving behavioral patterns over time. In response, it proposes Adaptive Behavioral Systems (ABS) as a conceptual framework for digital mental health support that adapts to evolving behavioral trajectories rather than isolated behavioral events.The framework is organized around six interconnected dimensions: trajectory-based behavioral understanding, iterative adaptation, interpretable behavioral intelligence, integration of behavioral theory, context sensitivity, and autonomy-supportive design. Rather than optimizing engagement alone, Adaptive Behavioral Systems aim to support sustainable self-regulation, coping stability, and behavioral resilience over time.The paper further examines implications for research, intervention design, ethics, equity, and public policy, particularly in relation to vulnerable adolescent populations affected by social inequality, migration-related stress, and unstable support environments. Ultimately, the paper argues that adolescent digital mental health systems must become not only more technologically advanced, but also more behaviorally meaningful, developmentally responsive, and socially aware.