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Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review
Journal of Medical Internet Research ( IF 7.4 ) Pub Date : 2021-09-28 , DOI: 10.2196/29412
Gisbert W Teepe 1 , Ashish Da Fonseca 2 , Birgit Kleim 3, 4 , Nicholas C Jacobson 5 , Alicia Salamanca Sanabria 6 , Lorainne Tudor Car 7, 8 , Elgar Fleisch 1, 2 , Tobias Kowatsch 1, 2, 6
Affiliation  

Background: 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. Objective: The aim of this study is to systematically assess the use of JITAI mechanisms in popular apps for individuals with depression. Methods: 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. Results: 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. Conclusions: 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.

This is the abstract only. Read the full article on the JMIR site. JMIR is the leading open access journal for eHealth and healthcare in the Internet age.


中文翻译:

流行移动应用程序针对抑郁症患者的即时适应机制:系统应用程序搜索和文献综述

背景: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。提高应用程序有效性同时减轻个人负担的一种有前途的方法是使用及时自适应干预(JITAI)机制。JITAI 旨在通过在正确的时间提供正确类型的支持来提高干预措施的有效性并减轻干预措施使用者的负担。正确的支持类型和正确的时间是通过分别测量脆弱性状态和接受性状态来确定的。目的:本研究的目的是系统评估 JITAI 机制在针对抑郁症患者的流行应用程序中的使用情况。方法:我们于 2020 年 8 月在 Apple App Store 和 Google Play Store 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学会的精选列表中系统地搜索了解决抑郁症的应用程序。相关应用程序根据评论数量(Apple App Store)或下载数量(Google Play Store)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 Register of Controlled Trials、PsycINFO、Google Scholar、IEEE Xplore、Web of Science、ACM Portal 和 Science Direct)中找到的与该应用程序相关的所有出版物,以及在应用程序的网站、应用程序网站上的信息以及应用程序本身。应用程序中发现的所有类型的测量(例如,开放式问题、封闭式问题和设备分析)都被记录和审查。结果:所审查的 28 个应用程序中没有一个使用 JITAI 机制来根据情况、状态或个人定制内容。在 28 个应用程序中,3 个(11%)没有使用任何测量,20 个(71%)专门使用自我报告,不足以充分发挥 JITAI 的全部潜力,5 个(18%)应用程序使用自我报告被动测量仅将它们用作进度或任务指标。尽管 34% (23/68) 的受审查出版物调查了应用程序的有效性,21% (14/68) 调查了其功效,但没有出版物提及或评估 JITAI 机制。结论:有前景的 JITAI 机制尚未转化为主流抑郁症应用程序。尽管智能手机提供的各种被动测量很少被使用,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,测量的结果都没有用于根据脆弱性或接受性状态定制内容和时间安排。由于缺乏针对个人、州或情况的定制,我们认为这些应用程序不能被视为 JITAI。由于缺乏出版物调查 JITAI 机制是否会提高应用程序的有效性或功效,这凸显了进一步研究的必要性,尤其是在现实世界的应用程序中。

这只是摘要。在 JMIR 网站上阅读全文。JMIR 是互联网时代电子健康和医疗保健领域领先的开放获取期刊。
更新日期:2021-09-28
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