Effectiveness of mHealth in Improving Outcomes for Gout Patients: Systematic Review and Meta-Analysis (Preprint)

BACKGROUND Long-term management of gout relies on patients' sustained engagement in dietary control, medication adherence, and disease monitoring. Traditional management models often yield poor outcomes due to insufficient doctor-patient interaction and weak patient self-management capabilities. Mobile health (mHealth) overcomes the temporal and spatial limitations of conventional healthcare, promptly addressing issues and concerns encountered by patients during treatment. While increasingly applied to chronic disease management, evidence regarding its feasibility and effectiveness remains limited. OBJECTIVE This study aims to evaluate the effectiveness of mobile health interventions in improving clinical outcomes for gout patients, providing evidence-based support for the digital transformation of gout clinical management. METHODS This study was conducted in accordance with the PRISMA statement. We searched seven databases: China National Knowledge Infrastructure, Wanfang Database, China Science and Technology Journal Database, China Biomedical Literature Database, Cochrane Library, Web of Science, PubMed, and Embase. The search period spanned from the inception of each database to June 2025. We included randomized controlled trials of electronic health interventions targeting ≥1 of the following 4 outcomes: serum uric acid, treatment adherence, self-management capacity, and quality of life. Two researchers independently screened the literature. We used the Cochrane Risk of Bias Assessment Tool for quality assessment. RESULTS A total of 20 studies, involving 2,324 gout patients were included. Meta-analysis indicated that eHealth-based interventions significantly reduced serum uric acid levels (MD=32.43, 95% CI 24.25-40.60, P<.001), decreased the gout recurrence rate (OR=0.34, 95% CI 0.22-0.53, P < .001), increased the rate of achieving target serum uric acid levels (OR = 4.65, 95% CI 1.99–10.89, P = 0.0004), and improved treatment adherence (OR = 5.76, 95% CI 2.45–13.55, P < .001). Additionally, eHealth significantly improved self-management in diet (SMD=1.25, 95% CI 0.61-1.90, P<.001), exercise (SMD=0.91, 95% CI 0.17-1.65, P=0.02), medication adherence (SMD = 1.19, 95% CI 0.37–2.01, P = 0.005). Regarding quality of life, eHealth significantly improved physical (SMD=0.66, 95% CI 0.13–1.20, P=0.02), psychological (SMD=1.21, 95% CI 0.44–1.98, P=0.002), and social (SMD=1.41, 95% CI 0.68–2.14, P=0.0002) domains. However, no statistically significant difference was observed between the intervention and conventional management groups regarding the “number of missed medication doses.” Subgroup analyses based on intervention tools and duration revealed that the effectiveness of eHealth interventions varied across different intervention durations and tools. CONCLUSIONS Research indicates that mobile health interventions can help gout patients improve serum uric acid control and enhance treatment adherence. They also boost patients' self-management capabilities and quality of life. Therefore, mobile health-supported interventions serve as an effective adjunct for long-term gout management. However, some patients—particularly those who are older or have limited education—may be unfamiliar with mobile health devices, which can impact treatment outcomes. Future efforts should involve comprehensive assessments of diverse patient populations and further validation through high-quality research. CLINICALTRIAL PROSPERO International Prospective Register of Systematic Reviews CRD420251153848；https//www.crd.york.ac.uk/PROSPERO/view/CRD420251153848