Tinschert Peter, Jakob Robert, Barata Filipe, Kramer Jan-Niklas, Kowatsch Tobias
Center for Digital Health Interventions, Institute of Technology Management (ITEM-HSG), University of St. Gallen, St. Gallen, Switzerland.
Operations & Supply Chain Management, School of Management, Technical University of Munich, Munich, Germany.
JMIR Mhealth Uhealth. 2017 Aug 2;5(8):e113. doi: 10.2196/mhealth.7177.
Effective disease self-management lowers asthma's burden of disease for both individual patients and health care systems. In principle, mobile health (mHealth) apps could enable effective asthma self-management interventions that improve a patient's quality of life while simultaneously reducing the overall treatment costs for health care systems. However, prior reviews in this field have found that mHealth apps for asthma lack clinical evaluation and are often not based on medical guidelines. Yet, beyond the missing evidence for clinical efficacy, little is known about the potential apps might have for improving asthma self-management.
The aim of this study was to assess the potential of publicly available and well-adopted mHealth apps for improving asthma self-management.
The Apple App store and Google Play store were systematically searched for asthma apps. In total, 523 apps were identified, of which 38 apps matched the selection criteria to be included in the review. Four requirements of app potential were investigated: app functions, potential to change behavior (by means of a behavior change technique taxonomy), potential to promote app use (by means of a gamification components taxonomy), and app quality (by means of the Mobile Application Rating Scale [MARS]).
The most commonly implemented functions in the 38 reviewed asthma apps were tracking (30/38, 79%) and information (26/38, 68%) functions, followed by assessment (20/38, 53%) and notification (18/38, 47%) functions. On average, the reviewed apps applied 7.12 of 26 available behavior change techniques (standard deviation [SD]=4.46) and 4.89 of 31 available gamification components (SD=4.21). Average app quality was acceptable (mean=3.17/5, SD=0.58), whereas subjective app quality lied between poor and acceptable (mean=2.65/5, SD=0.87). Additionally, the sum scores of all review frameworks were significantly correlated (lowest correlation: r=.33, P=.04 between number of functions and gamification components; highest correlation: r=.80, P<.001 between number of behavior change techniques and gamification components), which suggests that an app's potential tends to be consistent across review frameworks.
Several apps were identified that performed consistently well across all applied review frameworks, thus indicating the potential mHealth apps offer for improving asthma self-management. However, many apps suffer from low quality. Therefore, app reviews should be considered as a decision support tool before deciding which app to integrate into a patient's asthma self-management. Furthermore, several research-practice gaps were identified that app developers should consider addressing in future asthma apps.
有效的疾病自我管理可减轻哮喘对个体患者和医疗保健系统的疾病负担。原则上,移动健康(mHealth)应用程序可以实现有效的哮喘自我管理干预措施,既能提高患者的生活质量,又能同时降低医疗保健系统的总体治疗成本。然而,该领域之前的综述发现,用于哮喘的mHealth应用程序缺乏临床评估,且往往未基于医学指南。此外,除了缺乏临床疗效证据外,对于这些应用程序在改善哮喘自我管理方面的潜力知之甚少。
本研究旨在评估公开可用且广泛应用的mHealth应用程序在改善哮喘自我管理方面的潜力。
对苹果应用商店和谷歌应用商店进行系统搜索以查找哮喘应用程序。总共识别出523个应用程序,其中38个应用程序符合纳入综述的选择标准。研究了应用程序潜力的四个要求:应用程序功能、改变行为的潜力(通过行为改变技术分类法)、促进应用程序使用的潜力(通过游戏化组件分类法)以及应用程序质量(通过移动应用程序评分量表[MARS])。
在38个经审查的哮喘应用程序中,最常实现的功能是跟踪(30/38,79%)和信息(26/38,68%)功能,其次是评估(20/38,53%)和通知(18/38,47%)功能。平均而言,经审查的应用程序使用了26种可用行为改变技术中的7.12种(标准差[SD]=4.46)和31种可用游戏化组件中的4.89种(SD=4.21)。应用程序的平均质量可以接受(均值=3.17/5,SD=0.58),而主观应用程序质量介于较差和可接受之间(均值=2.65/5,SD=0.87)。此外,所有综述框架的总分之间存在显著相关性(最低相关性:功能数量与游戏化组件之间r=.33,P=.04;最高相关性:行为改变技术数量与游戏化组件之间r=.80,P<.001),这表明应用程序的潜力在各个综述框架中往往是一致的。
识别出了几款在所有应用的综述框架中表现始终良好的应用程序,这表明mHealth应用程序在改善哮喘自我管理方面具有潜力。然而,许多应用程序质量较低。因此,在决定将哪个应用程序整合到患者的哮喘自我管理中之前,应将应用程序审查视为一种决策支持工具。此外,还发现了几个研究与实践之间的差距,应用程序开发者在未来的哮喘应用程序中应考虑解决这些问题。