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. 2021 Sep 28;23(9):e29412. doi: 10.2196/29412.
The number of smartphone apps that focus on the prevention, diagnosis, and treatment of depression is increasing. A promising approach to increase the effectiveness of the apps while reducing the individual's burden is the use of just-in-time adaptive intervention (JITAI) mechanisms. JITAIs are designed to improve the effectiveness of the intervention and reduce the burden on the person using the intervention by providing the right type of support at the right time. The right type of support and the right time are determined by measuring the state of vulnerability and the state of receptivity, respectively.
The aim of this study is to systematically assess the use of JITAI mechanisms in popular apps for individuals with depression.
We systematically searched for apps addressing depression in the Apple App Store and Google Play Store, as well as in curated lists from the Anxiety and Depression Association of America, the United Kingdom National Health Service, and the American Psychological Association in August 2020. The relevant apps were ranked according to the number of reviews (Apple App Store) or downloads (Google Play Store). For each app, 2 authors separately reviewed all publications concerning the app found within scientific databases (PubMed, Cochrane Register of Controlled Trials, PsycINFO, Google Scholar, IEEE Xplore, Web of Science, ACM Portal, and Science Direct), publications cited on the app's website, information on the app's website, and the app itself. All types of measurements (eg, open questions, closed questions, and device analytics) found in the apps were recorded and reviewed.
None of the 28 reviewed apps used JITAI mechanisms to tailor content to situations, states, or individuals. Of the 28 apps, 3 (11%) did not use any measurements, 20 (71%) exclusively used self-reports that were insufficient to leverage the full potential of the JITAIs, and the 5 (18%) apps using self-reports and passive measurements used them as progress or task indicators only. Although 34% (23/68) of the reviewed publications investigated the effectiveness of the apps and 21% (14/68) investigated their efficacy, no publication mentioned or evaluated JITAI mechanisms.
Promising JITAI mechanisms have not yet been translated into mainstream depression apps. Although the wide range of passive measurements available from smartphones were rarely used, self-reported outcomes were used by 71% (20/28) of the apps. However, in both cases, the measured outcomes were not used to tailor content and timing along a state of vulnerability or receptivity. Owing to this lack of tailoring to individual, state, or situation, we argue that the apps cannot be considered JITAIs. The lack of publications investigating whether JITAI mechanisms lead to an increase in the effectiveness or efficacy of the apps highlights the need for further research, especially in real-world apps.
专注于预防、诊断和治疗抑郁症的智能手机应用程序数量正在增加。一种提高应用程序效果同时减轻个人负担的有前途的方法是使用即时自适应干预(JITAI)机制。JITAIs 的设计目的是通过在正确的时间提供正确类型的支持来提高干预的效果并减少对使用干预的人的负担。正确的支持类型和正确的时间是通过分别测量脆弱状态和接受状态来确定的。
本研究旨在系统评估在针对抑郁症的流行应用程序中使用 JITAI 机制的情况。
我们于 2020 年 8 月在 Apple App Store 和 Google Play Store 中以及美国焦虑和抑郁协会、英国国家卫生服务中心和美国心理协会的精选列表中系统地搜索了针对抑郁症的应用程序。根据评论数量(Apple App Store)或下载量(Google Play Store)对相关应用程序进行排名。对于每个应用程序,两位作者分别审查了在科学数据库(PubMed、Cochrane 对照试验注册处、PsycINFO、Google Scholar、IEEE Xplore、Web of Science、ACM 门户和 Science Direct)中找到的有关该应用程序的所有出版物、该应用程序网站上引用的出版物、该应用程序网站上的信息以及该应用程序本身。记录并审查了应用程序中发现的所有类型的测量(例如,开放问题、封闭问题和设备分析)。
在 28 个被审查的应用程序中,没有一个应用程序使用 JITAI 机制根据情况、状态或个人来调整内容。在 28 个应用程序中,有 3 个(11%)未使用任何测量方法,20 个(71%)仅使用自我报告,这些报告不足以充分利用 JITAIs 的潜力,而使用自我报告和被动测量的 5 个(18%)应用程序仅将其用作进度或任务指标。尽管 34%(23/68)的已审查出版物调查了应用程序的有效性,21%(14/68)调查了它们的疗效,但没有出版物提及或评估 JITAI 机制。
有前途的 JITAI 机制尚未转化为主流的抑郁症应用程序。尽管智能手机提供的各种被动测量方法很少使用,但 71%(20/28)的应用程序使用了自我报告的结果。然而,在这两种情况下,测量结果都没有用于根据脆弱性或接受性状态调整内容和时间。由于缺乏针对个人、状态或情况的定制,我们认为这些应用程序不能被视为 JITAIs。缺乏研究 JITAI 机制是否会提高应用程序的效果或疗效的出版物强调了进一步研究的必要性,特别是在现实世界的应用程序中。