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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9379789/ https://www.ncbi.nlm.nih.gov/pubmed/35916688 http://dx.doi.org/10.2196/34355 |
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author | Ryan, Shíofra Ní Chasaide, Noirín O' Hanrahan, Shane Corcoran, Darragh Caulfield, Brian Argent, Rob |
author_facet | Ryan, Shíofra Ní Chasaide, Noirín O' Hanrahan, Shane Corcoran, Darragh Caulfield, Brian Argent, Rob |
author_sort | Ryan, Shíofra |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9379789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-93797892022-08-17 mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis Ryan, Shíofra Ní Chasaide, Noirín O' Hanrahan, Shane Corcoran, Darragh Caulfield, Brian Argent, Rob JMIR Rehabil Assist Technol Original Paper 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. JMIR Publications 2022-08-01 /pmc/articles/PMC9379789/ /pubmed/35916688 http://dx.doi.org/10.2196/34355 Text en ©Shíofra Ryan, Noirín Ní Chasaide, Shane O' Hanrahan, Darragh Corcoran, Brian Caulfield, Rob Argent. Originally published in JMIR Rehabilitation and Assistive Technology (https://rehab.jmir.org), 01.08.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Rehabilitation and Assistive Technology, is properly cited. The complete bibliographic information, a link to the original publication on https://rehab.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Ryan, Shíofra Ní Chasaide, Noirín O' Hanrahan, Shane Corcoran, Darragh Caulfield, Brian Argent, Rob mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis |
title | mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis |
title_full | mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis |
title_fullStr | mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis |
title_full_unstemmed | mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis |
title_short | mHealth Apps for Musculoskeletal Rehabilitation: Systematic Search in App Stores and Content Analysis |
title_sort | mhealth apps for musculoskeletal rehabilitation: systematic search in app stores and content analysis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9379789/ https://www.ncbi.nlm.nih.gov/pubmed/35916688 http://dx.doi.org/10.2196/34355 |
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