Accepted for/Published in: JMIR Human Factors
Date Submitted: Dec 22, 2023
Date Accepted: Apr 26, 2024
An artificial intelligence-based app for self-management of low back and neck pain in specialist care: a process evaluation from a randomised clinical trial
ABSTRACT
Background:
Self-management is endorsed in clinical practice guidelines for the care of musculoskeletal pain. In a randomised clinical trial, we tested the effectiveness of an artificial intelligence-based self-management app (SELFBACK) as an adjunct to usual care for patients with low back and neck pain referred to specialist care.
Objective:
This study is a process evaluation aiming to explore patients’ engagement and experiences with the SELFBACK app, and specialist health care practitioners’ views on adopting digital self-management tools in their clinical practice.
Methods:
App usage analytics in the first 12 weeks were used to explore patients' engagement with the SELFBACK app. A purposive sample of eleven patients was selected for semi-structured individual interviews based on app usage. Two focus group interviews were conducted with specialist health care practitioners (n=9). Interviews were analysed using thematic analysis.
Results:
Nearly one-third of patients never accessed the app and one-third were low users. Three themes were identified from interviews with patients and health care practitioners: 1) overall impression of the app, where patients discussed the interface and content of the app, reported on usability issues, and described their app usage; 2) perceived value of the app, where patients and health care practitioners described the primary value of the app and its potential to supplement usual care; and 3) suggestions for future use, where patients and health care practitioners addressed aspects they believed would determine acceptance.
Conclusions:
Although the app uptake was relatively low, both patients and health care practitioners had a positive opinion about adopting an app-based self-management intervention for low back and neck pain as add-on to usual care. Both described that the app could reassure patients through the provision of trustworthy information, thus empowering them to take actions on their own. Factors influencing app acceptance and engagement were identified such as content relevance, tailoring, trust, and usability properties.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.