Losos Wojciech, Shao Carrie, Wang Biqi, Kitsiou Spyros, Gerber Ben S, McManus David D
Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States of America.
Program in Digital Medicine, UMass Memorial Medical Center, Worcester, MA, United States of America.
medRxiv. 2025 Jul 10:2025.07.09.25331174. doi: 10.1101/2025.07.09.25331174.
Atrial fibrillation (AF) is the most common cardiac arrhythmia, increasing the risk of stroke, heart failure, and healthcare costs. Although patient self-management can improve outcomes, sustaining long-term engagement is often difficult. Mobile health applications may help address this gap, but their quality and clinical alignment have not been systematically assessed using a validated framework. A structured search of the Apple App Store and Google Play Store identified free, English-language apps supporting AF self-management. Eligible apps included features such as symptom tracking, medication reminders, or educational content. App quality was assessed using the Mobile Application Rating Scale (MARS), which evaluates engagement, functionality, aesthetics, and information quality. Of 455 apps identified, five met all inclusion criteria. Common features included symptom tracking and medication logging, but coverage of evidence-based care domains varied. Mean MARS scores ranged from 4.07 to 4.53 out of 5. Higher-performing apps excelled in functionality and information quality but often lacked comprehensive integration of guideline-recommended care, such as stroke risk assessment or personalized feedback. These findings highlight a gap in high-quality, clinically grounded digital tools for AF self-care. Improved co-design processes and clearer frameworks for app evaluation may help guide the development and selection of effective tools to support AF self-management.
心房颤动（AF）是最常见的心律失常，会增加中风、心力衰竭的风险以及医疗成本。尽管患者自我管理可以改善治疗效果，但保持长期参与往往很困难。移动健康应用程序可能有助于弥补这一差距，但其质量和与临床的一致性尚未使用经过验证的框架进行系统评估。对苹果应用商店和谷歌应用商店进行结构化搜索，识别出支持房颤自我管理的免费英文应用程序。符合条件的应用程序包括症状跟踪、用药提醒或教育内容等功能。使用移动应用程序评分量表（MARS）评估应用程序质量，该量表评估参与度、功能、美观性和信息质量。在识别出的455个应用程序中，有5个符合所有纳入标准。常见功能包括症状跟踪和用药记录，但基于证据的护理领域的覆盖范围各不相同。MARS平均得分在5分制中从4.07到4.53不等。表现较好的应用程序在功能和信息质量方面表现出色，但往往缺乏指南推荐护理的全面整合，如中风风险评估或个性化反馈。这些发现凸显了用于房颤自我护理的高质量、基于临床的数字工具的差距。改进的协同设计流程和更清晰的应用程序评估框架可能有助于指导有效支持房颤自我管理工具的开发和选择。
