Centre for Digital Health Interventions, Department of Management, Technology and Economics, ETH Zurich, Zurich, Switzerland.
Centre for Digital Health Interventions, Institute of Technology Management, University of St. Gallen, St. Gallen, Switzerland.
J Med Internet Res. 2022 May 25;24(5):e35371. doi: 10.2196/35371.
Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions.
This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks.
A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings.
The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%).
This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app's intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.
移动健康 (mHealth) 应用在支持患者和医疗保健系统方面具有巨大的潜力,因为全球范围内非传染性疾病 (NCDs) 的发病率和经济成本不断上升。然而,尽管有基于证据的 mHealth 应用程序,很大一部分用户并没有按照预期使用它们,因此可能无法接受治疗。因此,了解影响依从性的障碍因素或促进因素是预防干预措施中断和提高数字健康干预措施效果的基本关注点。
本综述旨在通过确定影响 mHealth 应用程序针对 NCDs 的持续使用的因素,帮助利益相关者开发更有效的数字健康干预措施。我们进一步为各种健康领域得出了量化的依从性评分,以验证定性发现并探索依从性基准。
对 MEDLINE、Embase、Web of Science、Scopus 和 ACM Digital Library 进行了全面的系统文献检索 (2007 年 1 月至 2020 年 12 月)。提取了关于预期使用、实际使用和影响依从性的因素的数据。分别呈现与 NCD 自我管理、心理健康、物质使用、营养、身体活动、体重减轻、多成分生活方式干预、正念和其他 NCD 相关的干预措施和患者相关因素对依从性的积极或消极影响。为每项研究得出了量化的依从性衡量标准,即估计的预期使用与实际使用之间的比率,并将其与定性发现进行比较。
文献检索产生了 2862 篇潜在相关文章,其中 99 篇 (3.46%) 符合纳入标准。共有 4 个干预相关因素表明对所有健康领域的依从性有积极影响:根据用户的个人需求对 mHealth 应用程序的内容进行个性化或定制、以个性化推送通知的形式提供提醒、用户友好且技术稳定的应用程序设计以及数字干预的补充性个人支持。在多个健康领域中,社交和游戏化功能也被确定为应用程序依从性的驱动因素。用户特征或招募渠道等各种患者相关因素也进一步影响依从性。纳入的 mHealth 应用程序的依从性评分平均为 56.0% (SD 24.4%)。
本研究有助于填补关于影响 mHealth 应用程序依从性的积极或消极因素的科学证据空白,并且是第一个对各种健康领域的依从性与预期使用进行定量比较的研究。由于基础研究大多具有试点性质且研究持续时间较短,因此关于 mHealth 应用程序依从性的研究仍然有限。为了促进未来对 mHealth 应用程序依从性的研究,研究人员应明确概述和证明应用程序的预期用途;报告实际使用相对于预期使用的客观数据;并且,理想情况下,提供长期使用和保留数据。