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Accepted for/Published in: JMIR mHealth and uHealth

Date Submitted: Oct 4, 2023
Date Accepted: Dec 21, 2023

The final, peer-reviewed published version of this preprint can be found here:

mHealth Apps for the Self-Management of Low Back Pain: Systematic Search in App Stores and Content Analysis

Zhou T, Salman D, McGregor A

mHealth Apps for the Self-Management of Low Back Pain: Systematic Search in App Stores and Content Analysis

JMIR Mhealth Uhealth 2024;12:e53262

DOI: 10.2196/53262

PMID: 38300700

PMCID: 10870204

mHealth apps for the self-management of low back pain: an analysis of content, quality and approaches used

  • Tianyu Zhou; 
  • David Salman; 
  • Alison McGregor

ABSTRACT

Background:

With the rapid development of mobile health (mHealth) technology, many health apps have been introduced to the commercial market for people with back pain conditions. However, little is known about their content, quality, and LBP care approaches, and their associated risks.

Objective:

The aims of this research were to (1) identify apps for the self-management of low back pain (LBP) currently on the market, and (2) assess their quality, intervention content, theoretical approaches, and risk-related approaches.

Methods:

The UK iTunes and Google Play stores were initially searched for apps related to the self-management of LBP in May 2022. A repeat search in June 2023 was conducted to ensure that any relevant new apps developed in the last year were incorporated into the review. Three keywords recommended by the Cochrane Back and Neck Group were used to search apps: “low back pain,” “back pain,” and “lumbago”. The quality of apps were assessed by using the 5-point Mobile App Rating Scale (MARS).

Results:

A total of 69 apps (25 iOS, 44 Android) met the inclusion criteria. These LBP self-management apps mainly provide recommendations on muscle stretching (n=51, 73.9%), muscle strengthening (n=42, 60.9%), core stability exercises (n=32, 46.4%), yoga (n=19, 27.5%), and information about LBP mechanisms (n=17, 24.6%). Most (n=14, 78%) are consistent with the recommendations in the National Institute for Health and Care Excellence (NICE) guidelines. The mean (SD) MARS overall score of included apps was 2.4 (0.44), with 5 being the best. The functionality dimension was associated with the highest score (3.0), whereas the engagement and information dimension resulted in the lowest score (2.1). Regarding theoretical and risk-related approaches, eighteen of the 69 apps reported the rate of intervention progression, 11 reported safety checks, only one reported personalisation of care, and none reported the theoretical care model or the age group targeted.

Conclusions:

mHealth apps are potentially promising alternatives to help people manage their LBP; however, most of the LBP self-management apps were of poor quality, and did not report the theoretical approaches to care and their associated risks. Although nearly all apps reviewed included a component of care listed in the NICE guidelines, the model of care delivery or embracement of care principles such as the application of a biopsychosocial care model was unclear. This study highlighted the need for a comprehensive tool to evaluate LBP self-management apps.Smartphone, mHealth, Low back pain, Self-management, Treatment interventions


 Citation

Please cite as:

Zhou T, Salman D, McGregor A

mHealth Apps for the Self-Management of Low Back Pain: Systematic Search in App Stores and Content Analysis

JMIR Mhealth Uhealth 2024;12:e53262

DOI: 10.2196/53262

PMID: 38300700

PMCID: 10870204

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