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Efficacy of mobile apps for urinary incontinence in women: a meta-analysis of randomized controlled trials

Aug 2026 · Frontiers in Public Health · 0 citations · 29 references

Abstract

Pelvic floor muscle training (PFMT) is recommended as a first-line treatment for urinary incontinence (UI); however, treatment adherence among women with UI remains suboptimal. The effectiveness of mobile applications in delivering PFMT for women with UI is not yet well established. This study aimed to evaluate the effects of app-based PFMT interventions on adherence, symptom severity, quality of life, and patient global impression of improvement (PGI-I). PubMed, Cochrane Library, Scopus, EMBASE, and Web of Science were systematically searched to identify relevant studies published up to February 11, 2026. Risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals (CIs) were calculated. A total of 12 randomized controlled trials (RCTs) including 1,647 participants (mobile app group: 823; usual care group: 824) were included. The meta-analysis demonstrated that, compared with usual care, mobile app–based interventions significantly reduced the severity of UI (MD = −1.93, 95% CI: −2.87, −0.98; P < 0.0001) and the frequency of incontinence episodes (MD = −2.28, 95% CI: −3.62, −0.94; P = 0.0008). In addition, these interventions improved adherence (RR = 1.42, 95% CI: 1.26, 1.59; P < 0.00001), PGI-I (RR = 3.79, 95% CI: 1.27, 11.29; P = 0.02), and quality of life (MD = −2.78, 95% CI: −4.43, −1.14; P = 0.0009). This meta-analysis suggests that mobile app-based PFMT interventions may serve as an adjunctive approach to improve adherence and patient-reported outcomes among women with UI. However, the magnitude of symptom improvement may be below the threshold of clinical importance, and the certainty of evidence remains low. Mobile applications should therefore complement rather than replace supervised PFMT, particularly for women requiring individualized rehabilitation and objective functional assessment. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261472595 , identifier CRD420261472595.

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