Mobile Application-Based Interventions for Clinical Insomnia: A Systematic Review and Meta-Analysis (Preprint)

BACKGROUND Insomnia is a highly prevalent and disabling condition with substantial personal and societal burden. Although cognitive behavioral therapy for insomnia (CBT I) is the recommended first line treatment, access to face to face therapy remains limited. Mobile health (mHealth) applications offer a scalable and accessible alternative; however, existing reviews have often included heterogeneous or non clinical populations, limiting their relevance to individuals with clinically significant insomnia. OBJECTIVE The primary objective is to evaluate the efficacy of mobile app-based treatment for individuals with clinical insomnia, as measured by symptom reduction. Factors contributing to heterogeneities in treatment outcomes will be examined. The secondary objective is to assess the impact of app-based interventions on both subjective and objective sleep parameters, including sleep onset latency (SOL), wake after sleep onset (WASO), total sleep time (TST), and sleep efficiency (SE). METHODS This systematic review and meta-analysis was conducted in accordance with PRISMA guidelines and registered on PROSPERO (CRD42023494699). We searched seven electronic databases and grey literature sources for randomized controlled trials published up to March 2025. Eligible studies included adults (≥18 years) with clinical insomnia, defined by formal diagnostic criteria (DSM, ICD, or ICSD) or validated scale cutoffs (ISI ≥15 or AIS ≥10), who received mobile app–based interventions. Risk of bias was assessed using Cochrane RoB 2, and pooled effects were estimated using random-effects models, with sensitivity, subgroup, and meta-regression analyses. RESULTS Thirteen randomized controlled trials involving 2,573 participants were included. Mobile app–based interventions produced a large and statistically significant reduction in insomnia severity compared with control conditions (SMD = –0.81, 95% CI: –0.99 to –0.63). Structured, scheduled content delivery was associated with greater efficacy than self paced formats. Improvements were also observed in subjective sleep onset latency, wake after sleep onset, and sleep efficiency. These findings provide robust evidence supporting mobile apps as effective mHealth interventions for clinical insomnia and offer practical insights into app design features relevant to digital sleep therapeutics. CONCLUSIONS Mobile app–based interventions are effective in reducing insomnia severity among adults with clinical insomnia, offering a convenient and accessible alternative to face-to-face therapy. Interventions with structured, scheduled delivery appear more effective than self-paced, free-navigation formats. Future research should include more diverse populations, examine how delivery approaches influence outcomes, identify app features that drive therapeutic benefit, incorporate objective sleep measures, and evaluate both long-term and real-world effectiveness. CLINICALTRIAL PROSPERO (ID: CRD42023494699)