An App-Delivered Self-Management Program for People With Low Back Pain: Protocol for the selfBACK Randomized
Louise Fleng Sandal1, Mette Jensen Stochkendahl1,2, Malene Jagd Svendsen1,3
1Department of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
JMIR Research Protocols
|December 4, 2019
Summary
This study evaluated the selfBACK app for low back pain (LBP) self-management. The app, using artificial intelligence, provides tailored plans, aiming to improve outcomes for LBP patients.
Area of Science:
- Digital health interventions
- Artificial intelligence in healthcare
- Musculoskeletal health
Background:
- Low back pain (LBP) is a leading cause of disability globally.
- Self-management is a key treatment strategy for LBP.
- Mobile applications offer a promising platform for supporting LBP self-management.
Purpose of the Study:
- To evaluate the effectiveness of the selfBACK app for LBP self-management.
- To compare outcomes of app-supported self-management versus usual care.
- To assess the app's role in providing tailored, person-centered LBP care.
Main Methods:
- A single-blinded, randomized controlled trial (RCT) with two parallel arms.
- The selfBACK app utilizes case-based reasoning (CBR) for tailored self-management plans.
- Participants with LBP were randomized to the intervention (app + usual care) or control (usual care only) group.
Main Results:
- The trial opened for recruitment in February 2019.
- Data collection was expected to conclude in fall 2020.
- Primary outcome results were anticipated in fall 2020.
Conclusions:
- The RCT will provide insights into app-based tailored self-management for LBP.
- The selfBACK intervention could serve as a model for managing LBP and other musculoskeletal conditions.
- Successful outcomes may inform future digital health interventions for chronic pain.
