상세 보기
초록
This review investigates the clinical effectiveness of pelvic floor muscle training (PFMT) interventions delivered through digital healthmodalities for individuals experiencing urinary incontinence (UI). It also explores embedded system-level features that may shape adherencebehavior and health outcomes. Extensive searches were undertaken across global (PubMed, EMBASE, CINAHL, CENTRAL) and Korean(RISS, KISS) academic databases for relevant studies published from 2000 to 2023. Only randomized controlled trials (RCTs) evaluatingdigital PFMT programs delivered through mobile apps, telehealth systems, or wearable technologies were selected. Risk of bias was assessedusing the Cochrane RoB 2 tool. Meta-analytic synthesis with a random-effects model was used to calculate pooled effects. Additionally,a narrative synthesis examined digital functionalities including feedback mechanisms, adherence tracking, and user engagement tools. Ten eligible RCTs involving 1,342 participants were analyzed. Digital PFMT yielded statistically significant benefits in reducing symptomseverity (SMD = −0.46; 95% CI: −0.73, −0.19), alleviating urinary distress (SMD = −0.41; 95% CI: −0.68, −0.14), and enhancing qualityof life (SMD = 0.39; 95% CI: 0.11, 0.67). Platforms incorporating real-time feedback loops, gamified interfaces, and structured reminderswere associated with better adherence and sustained benefits. In contrast, few interventions integrated AI-based personalization or ensuredinteroperability with other digital systems. Digital PFMT approaches demonstrate clinical value in managing UI and improvingpatient-reported outcomes. Emphasizing real-time interactivity, tailored feedback, and user-centered system architecture could furtheroptimize intervention adherence and impact. The findings advocate for the continued evolution and integration of smart PFMT toolswithin comprehensive digital health strategies.
키워드
- 제목
- Effectiveness of Digital Health-Enabled Pelvic Floor Muscle Training for Urinary Incontinence: A Systematic Review and Meta-Analysis
- 저자
- 유인겸; 김가은
- 발행일
- 2025-06
- 유형
- Y
- 저널명
- 정보처리학회 논문지
- 권
- 14
- 호
- 6
- 페이지
- 386 ~ 396
- 언어
- ENG
- 출판사
- 한국정보처리학회
- 발행국가
- 대한민국
- 분량
- 11 페이지
- ISSN
- E 3022-7011