Evidence map›Paper›PMID 35916688›Full record

ArticleJMIR rehabilitation and assistive technologies2022

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

Shíofra Ryan, Noirín Ní Chasaide, Shane O' Hanrahan, Darragh Corcoran, Brian Caulfield, Rob Argent

Open access · goldAbstract read
In one paragraph

Article in JMIR rehabilitation and assistive technologies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
8.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 31 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Shíofra RyanSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0002-2371-5311
Noirín Ní ChasaideSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0001-7569-5554
Shane O' HanrahanSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0003-3943-7624
Darragh CorcoranSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0001-9435-0164
Brian CaulfieldSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0003-0290-9587
Rob ArgentSchool of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland.ORCID https://orcid.org/0000-0002-3522-9409
University College Dublin · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

objectiveThe 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.

methodsA 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.

resultsA 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%).

conclusionsThe 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.

Indexed as

appconnected healthhome exercisehome exercise programmHealthmobile healthmusculoskeletal rehabilitationtelehealth

Identifiers

PMID35916688
PMCPMC9379789
OpenAlexW4285345127

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.