Self‐Management Technology of Medication Adherence in Patient Chronic Disease: A Systematic Review and Meta‐Analysis

BACKGROUND: Chronic diseases require sustained medication adherence, yet nonadherence remains common, leading to poor outcomes and increased healthcare costs. Digital self-management technologies such as mobile health (mHealth) apps, SMS reminders, and web-based platforms offer scalable ways to support adherence, but evidence on their overall effectiveness across diverse contexts is fragmented. AIM: To systematically review and meta-analyze the effectiveness of self-management technologies in improving medication adherence among adults with chronic diseases and to examine potential moderators of intervention impact. METHODS: ), subgroup analyses, and publication bias (Egger's, Begg's, trim-and-fill) were assessed. RESULTS: = 89%). Medium-duration (10.8-24 weeks) interventions had the largest effect (d = 0.50), and effects varied markedly by country (e.g., Iran d = 2.29; Taiwan d = -0.94). Begg's test suggested possible publication bias; trim-and-fill adjustment increased the pooled effect to d = 0.366. LINKING EVIDENCE TO ACTION: Digital self-management technologies yield a statistically significant, small-to-moderate improvement in medication adherence across chronic diseases, with potential underestimation due to selective reporting. Effectiveness is moderated by temporal trends, geography, intervention duration, and study design, underscoring the need for context-specific adaptation and methodological rigor. Future research should prioritize large, well-controlled trials, pre-registration, and exploration of cultural and systemic determinants to optimize intervention impact.