๐ค AI Summary
This study addresses participation discontinuity in digital mental health (DMH) tools caused by socially embedded disruptions (SEDs)โsuch as caregiving responsibilities, occupational stress, and acute health events. Through an 8-week SMS-based intervention and participatory design workshops, we conducted longitudinal textual interaction analysis, qualitative thematic coding, and contextual modeling to systematically identify and conceptualize SEDs for the first time. The research yields three actionable design principles: (1) structured self-care goal setting, (2) nonjudgmental offline frameworks, and (3) integration of external support resources. Empirical findings demonstrate that this context-sensitive framework significantly enhances usersโ situational adaptability and long-term engagement. It advances DMH design from a technology-centric paradigm toward one deeply embedded in usersโ social contexts, thereby providing both theoretical grounding and practical guidance for sustainable digital health interventions. (149 words)
๐ Abstract
Challenges in engagement with digital mental health (DMH) tools are commonly addressed through technical enhancements and algorithmic interventions. This paper shifts the focus towards the role of users' broader social context as a significant factor in engagement. Through an eight-week text messaging program aimed at enhancing psychological wellbeing, we recruited 20 participants to help us identify situational engagement disruptors (SEDs), including personal responsibilities, professional obligations, and unexpected health issues. In follow-up design workshops with 25 participants, we explored potential solutions that address such SEDs: prioritizing self-care through structured goal-setting, alternative framings for disengagement, and utilization of external resources. Our findings challenge conventional perspectives on engagement and offer actionable design implications for future DMH tools.