Ryan Shíofra, Ní Chasaide Noirín, O' Hanrahan Shane, Corcoran Darragh, Caulfield Brian, Argent Rob
School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.
Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland.
JMIR Rehabil Assist Technol. 2022 Aug 1;9(3):e34355. doi: 10.2196/34355.
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.
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.
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.
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%).
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.
近年来，随着对数字健康干预措施的深入探索和研究，用于肌肉骨骼（MSK）损伤治疗及通过家庭锻炼计划（HEP）进行自我管理的移动健康（mHealth）应用程序数量迅速增加。随着此类应用数量的增长，用户在市场中进行筛选并为其特定需求选择最合适的应用程序变得越来越困难。此外，目前尚不清楚这些应用程序的开发者利用了哪些功能来支持患者自我管理，以及它们如何融入临床护理路径。
本研究旨在梳理用于MSK康复的mHealth应用程序的当前市场情况，并报告其功能、宣称、证据基础及实用功能。
在iTunes应用商店和谷歌Play商店中对用于MSK康复的应用程序开展了一项横断面研究。使用了四个搜索词，即物理治疗康复、物理疗法康复、康复锻炼和治疗性锻炼来识别应用程序，然后由4名评审员根据既定的选择标准进行交叉核对。每位评审员在可能的情况下下载应用程序，并查阅产品上提供的补充文献以协助数据提取。
共识别出1322个应用程序。在应用纳入和排除标准并去除重复项后，144个应用程序被纳入研究。超过半数（n = 81，56.3%）的纳入应用程序是在过去3年内发布的。四分之三（n = 107，74.3%）的应用程序未提及支持该应用程序设计或功效的证据，只有11.1%（n = 16）提供了对研究的直接引用。大多数应用程序确实使用了锻炼图片（n = 138，95.8%）或视频（n = 97，67.4%）；然而，相对较少的应用程序利用其他功能来促进参与和支持自我管理，如依从性记录（n = 66，45.8%）、沟通门户（n = 32，22.2%）、患者报告结局采集（n = 36，25%）或直接反馈（n = 57，39.6%）。值得注意且令人担忧的是，许多此类应用程序在未向用户提供个性化输入的情况下规定了通用锻炼（n = 93，64.6%），很少提供特定的患者教育（n = 43，34%）以及安全建议或免责声明（n = 38，26.4%）。
本研究纳入的应用程序群组在功能方面存在很大的异质性，因此用户很难识别最合适或最有效的应用程序。许多应用程序错失了提供关键功能的机会，这些功能本可促进MSK康复中的锻炼依从性并鼓励自我管理。此外，目前在市场上提供产品的开发者中，很少有人提供证据来支持其技术的设计和功效。
