Poster Presentation 50th International Society for the Study of the Lumbar Spine Annual Meeting 2024

mHealth apps for the self-management of low back pain: an analysis of content, quality and approaches used   (#249)

Tianyu Zhou 1 , David Salman 2 , Alison McGregor 1
  1. Department of Surgery & Cancer, Imperial College London, London, United Kingdom
  2. School of Public Health, Imperial College London, London, United Kingdom

INTRODUCTION

Clinical practice guidelines (CPGs) for managing low back pain (LBP) suggest that self-management strategies offer a potential solution to its management. Our recent narrative review on self-management needs revealed a consensus with respect to the critical components of self-management interventions. With the rapid development of mobile health (mHealth) technology, smartphone apps are an innovative way to support LBP self-management. This study aims to identify current apps for the self-management of LBP, assessing them for their quality, intervention content, theoretical approaches, and risk management approaches.

 

METHODS

A systematic app search was performed on the UK iTunes and Google Play stores in June 2023. The predefined terms guided by the Cochrane Back and Neck Group were used to search apps: “low back pain,” “back pain,” and “lumbago”. Apps were considered eligible when they met the following criteria: (1) Apps offered at least one active treatment option for LBP, (2) Apps released or updated within the last five years, (3) Apps designed for people with LBP, (4) Apps developed in English. The 5-point Mobile App Rating Scale (MARS) assessed the quality of apps. A theoretical framework that considers the theoretical care model of the intervention, the personalisation of care, and the rate of intervention progression, as well as a risk management framework that includes the age group targeted and the provision of appropriate safety checks, were used to evaluate delivery approaches.

 

RESULTS

We identified 69 LBP self-management apps, of which 25 were from Apple iOS and 44 from Android. The most recommended interventions are muscle stretching (n=51, 73.9%), muscle strengthening (n=42, 60.9%), and core stability exercises (n=32, 46.4%), which are consistent with the recommendations in the National Institute for Health and Care Excellence (NICE) guidelines. The average MARS overall score for the included apps was 2.4 out of 5, with the functionality dimension scoring the highest at 3.0 and the engagement and information dimension scoring the lowest at 2.1. In terms of theoretical and risk management approaches, no apps offered a theoretical care model and all failed to specify the age group targeted; only one provided a tailored care approach; 18 included intervention progression; and 11 reported management safety checks.

 

DISCUSSION

This study shows that app developers generally select interventions endorsed by guidelines. However, the application of a biopsychosocial care model is not being considered. Although many apps are available for LBP self-management, most of them are of low quality with regards engagement and information, and the absence of theoretical models of care. It is essential to involve clinicians and patients in developing LBP self-management apps to improve the quality and related approach. Future research also needs to develop an evaluation tool to assess LBP self-management apps holistically.