인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
Objectives: This study evaluated Korean mobile health (mHealth) applications, analyzing the extent to which they incorporated elements of health behavior theory. We aimed to classify application types and compare their structural characteristics and quality using cluster analysis. Methods: We evaluated 238 mHealth applications from Apple App Store and Google Play Store. Applications were assessed using the Health Care Smartphone Application Evaluation Tool, which considers content, design, and security as the criteria for quality evaluation. Elements from the Health Belief Model (HBM) and Theory of Planned Behavior (TPB), including perceived benefits/attitudes, cues to action, self-efficacy/perceived behavioral control, and subjective norms, were mapped onto application features. K-means clustering was performed using binary-coded theory elements, followed by validation and quality comparison. Results: Three clusters were identified: information-focused (36.6%), engagement-empowered (56.3%), and social influence-driven (7.1%) applications. Information-focused applications emphasized benefits but lacked interactivity. Engagement-empowered applications comprised diverse theory components, and social influence-driven applications emphasized peer influence. Application quality scores significantly differed across clusters ( p<.001), with information-focused apps scoring highest. Conclusion: mHealth applications can be meaningfully classified based on behavioral theory integration, which is associated with quality. Integrating structured theoretical frameworks may enhance both effectiveness and credibility of mHealth interventions.
본문·목차
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