Abstract
<sec> <title>UNSTRUCTURED</title> <p>Mental health interventions delivered through digital platforms have expanded rapidly, yet questions remain regarding how patterns of user engagement influence clinical outcomes. This study examines the relationship between digital behavior, adherence, and symptom improvement within technology‑mediated mental health programs. Drawing on a mixed‑methods design, we analyzed user interaction logs, self‑reported mental health assessments, and qualitative feedback from adults enrolled in a 12‑week digital cognitive‑behavioral intervention. Quantitative models assessed associations between engagement frequency, session completion, and changes in depression and anxiety scores, while thematic analysis explored user perceptions of usability, barriers, and motivational factors. Findings indicate that higher engagement intensity—defined by consistent log‑ins, completion of structured therapeutic modules, and active participation in reflective exercises—was significantly associated with greater reductions in depressive symptoms. However, engagement quality, rather than quantity alone, emerged as a critical predictor: users who demonstrated sustained interaction with cognitive restructuring tasks and mood‑tracking tools showed the strongest clinical gains. Qualitative data revealed that personalization, perceived relevance, and ease of navigation shaped adherence, whereas digital fatigue and competing life demands were common barriers. These results underscore the importance of designing digital mental health interventions that promote meaningful, sustained engagement rather than simple platform usage. Integrating adaptive content, behavioral nudges, and real‑time feedback may enhance adherence and therapeutic impact. As digital mental health continues to evolve, understanding the mechanisms linking engagement to outcomes is essential for optimizing intervention design and improving population‑level access to effective care.</p> </sec>