肌肉骨骼康复的移动健康应用程序:应用程序商店和内容分析的系统搜索。

Q2 Medicine
Shíofra Ryan, Noirín Ní Chasaide, Shane O' Hanrahan, Darragh Corcoran, Brian Caulfield, Rob Argent
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引用次数: 6

摘要

背景:近年来,随着数字健康干预措施的探索和研究越来越详细,用于肌肉骨骼(MSK)损伤治疗和家庭锻炼计划(HEPs)自我管理的移动健康(mHealth)应用程序的数量迅速增加。随着这个数字的增长,用户在市场上导航并选择最适合自己用例的应用变得越来越困难。目前还不清楚这些应用程序的开发者正在利用哪些功能来支持患者的自我管理,以及它们如何适应临床护理途径。目的:本研究的目的是确定MSK康复的移动健康应用程序的当前市场范围,并报告其特征、声明、证据基础和功能。方法:通过iTunes App Store和Google Play Store对MSK康复应用程序进行横断面研究。使用物理治疗康复、物理治疗康复、康复运动和治疗性运动四个搜索词来识别应用程序,然后由4名评论者根据设定的选择标准进行交叉引用。在可能的情况下,每个审稿人都下载了应用程序,并访问了产品上可用的补充文献,以协助数据提取。结果:共识别出1322个应用程序。在应用纳入和排除标准并删除重复后,144个应用程序被纳入研究。超过一半(n=81, 56.3%)的应用是在过去3年内发布的。四分之三(n=107, 74.3%)的应用程序没有引用支持应用程序设计或功效的证据,只有11.1% (n=16)的应用程序提供直接引用研究。大多数应用程序确实使用了运动图片(n=138, 95.8%)或视频(n=97, 67.4%);然而,相对而言,很少利用其他功能来鼓励参与和支持自我管理,例如依从性日志(n=66, 45.8%)、沟通门户(n=32, 22.2%)、患者报告的结果捕获(n=36, 25%)或直接反馈(n=57, 39.6%)。值得注意和关注的是,在缺乏个性化输入的情况下,许多应用程序规定了通用练习(n= 93,64.6%),很少提供具体的患者教育(n= 43,34%)和安全建议或免责声明(n= 38,26.4%)。结论:本研究中纳入的应用程序队列包含很大的功能异质性,因此用户很难识别最合适或最有效的应用程序。许多应用程序错过了提供可以促进运动坚持和鼓励MSK康复自我管理的关键功能的机会。此外,目前在市场上提供产品的开发人员很少提供证据来支持其技术的设计和功效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis.

mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis.

Background: The number of mobile health (mHealth) apps released for musculoskeletal (MSK) injury treatment and self-management with home exercise programs (HEPs) has risen rapidly in recent years as digital health interventions are explored and researched in more detail. As this number grows, it is becoming increasingly difficult for users to navigate the market and select the most appropriate app for their use case. It is also unclear what features the developers of these apps are harnessing to support patient self-management and how they fit into clinical care pathways.

Objective: The objective of this study was to scope the current market of mHealth apps for MSK rehabilitation and to report on their features, claims, evidence base, and functionalities.

Methods: A cross-sectional study of apps for MSK rehabilitation was performed across the iTunes App Store and Google Play Store. Four search terms were used, namely, physiotherapy rehabilitation, physical therapy rehabilitation, rehabilitation exercise, and therapeutic exercise to identify apps, which were then cross-referenced against set selection criteria by 4 reviewers. Each reviewer, where possible, downloaded the app and accessed supplementary literature available on the product to assist in data extraction.

Results: A total of 1322 apps were identified. After applying the inclusion and exclusion criteria and removing duplicates, 144 apps were included in the study. Over half (n=81, 56.3%) of the included apps had been released within the past 3 years. Three quarters (n=107, 74.3%) of the apps made no reference to evidence supporting the design or efficacy of the app, with only 11.1% (n=16) providing direct citations to research. Most of the apps did utilize exercise pictures (n=138, 95.8%) or videos (n=97, 67.4%); however, comparatively few harnessed additional features to encourage engagement and support self-management, such as an adherence log (n=66, 45.8%), communication portal (n=32, 22.2%), patient-reported outcome capture (n=36, 25%), or direct feedback (n=57, 39.6%). Of note and concern, many of these apps prescribed generic exercises (n=93, 64.6%) in the absence of individualized input to the user, with few providing specific patient education (n=43, 34%) and safety advice or disclaimers (n=38, 26.4%).

Conclusions: The cohort of apps included in this study contained a large heterogeneity of features, so it is difficult for users to identify the most appropriate or effective app. Many apps are missing the opportunity to offer key features that could promote exercise adherence and encourage self-management in MSK rehabilitation. Furthermore, very few developers currently offering products on the market are providing evidence to support the design and efficacy of their technologies.

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来源期刊
CiteScore
4.20
自引率
0.00%
发文量
31
审稿时长
12 weeks
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