Trial reportBMC medicine2022
Multimorbidity and co-occurring musculoskeletal pain do not modify the effect of the SELFBACK app on low back pain-related disability.
Trial report in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03798288 (A Decision Support System for Self-management of Low Back Pain - a Randomized Controlled Trial for the selfBACK Project), which is not on this map. Cited by 14 papers, 3 of them syntheses that pooled it.
What it found
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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.
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.
A Decision Support System for Self-management of Low Back Pain - a Randomized Controlled Trial for the selfBACK Project
Who cites it
14 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Moving towards the use of artificial intelligence in pain management.European journal of pain (London, England) · 2025Pooled it
- The multiple uses of artificial intelligence in exercise programs: a narrative review.Frontiers in public health · 2025Pooled it
- Impact of 25 Years of Mobile Health Tools for Pain Management in Patients With Chronic Musculoskeletal Pain: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Efficacy of a Blended Low-Intensity Internet-Delivered Psychological Program in Patients With Multimorbidity in Primary Care: Randomized Controlled Trial.Journal of medical Internet research · 2025Trial
- The Physical and Psychological Effects of Telerehabilitation-Based Exercise for Patients With Nonspecific Low Back Pain: Prospective Randomized Controlled Trial.JMIR mHealth and uHealth · 2024Trial
- Trial
- An Artificial Intelligence-Based App for Self-Management of Low Back and Neck Pain in Specialist Care: Process Evaluation From a Randomized Clinical Trial.JMIR human factors · 2024Trial
- Artificial intelligence in spine care: A scoping review of treatment applications.North American Spine Society journal · 2026Review
- Community-based management strategies for adults with multimorbidity: a systematic review of clinical and patient-centred outcomes.BMJ public health · 2026Article
- Musculoskeletal Diseases as the Most Prevalent Component of Multimorbidity: A Population-Based Study.Journal of clinical medicine · 2024Article
- Interest in mHealth Among Patients With Low Back Pain: Cross-Sectional Study.JMIR human factors · 2024Article
- Do age, gender, and education modify the effectiveness of app-delivered and tailored self-management support among adults with low back pain?-Secondary analysis of the selfBACK randomised controlled trial.PLOS digital health · 2023Article
- Prevalence, Patterns, and Associated Factors for Musculoskeletal Disorders Among the Healthcare Workers of Northern Saudi Arabia: A Multicenter Cross-Sectional Study.Journal of pain research · 2023Article
- Digitally Delivered Exercise and Education Treatment Program for Low Back Pain: Longitudinal Observational Cohort Study.JMIR rehabilitation and assistive technologies · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSELFBACK, an artificial intelligence (AI)-based app delivering evidence-based tailored self-management support to people with low back pain (LBP), has been shown to reduce LBP-related disability when added to usual care. LBP commonly co-occurs with multimorbidity (≥ 2 long-term conditions) or pain at other musculoskeletal sites, so this study explores if these factors modify the effect of the SELFBACK app or influence outcome trajectories over time.
methodsSecondary analysis of a randomized controlled trial with 9-month follow-up. Primary outcome is as follows: LBP-related disability (Roland Morris Disability Questionnaire, RMDQ). Secondary outcomes are as follows: stress/depression/illness perception/self-efficacy/general health/quality of life/physical activity/global perceived effect. We used linear mixed models for continuous outcomes and logistic generalized estimating equation for binary outcomes. Analyses were stratified to assess effect modification, whereas control (n = 229) and intervention (n = 232) groups were pooled in analyses of outcome trajectories.
resultsBaseline multimorbidity and co-occurring musculoskeletal pain sites did not modify the effect of the SELFBACK app. The effect was somewhat stronger in people with multimorbidity than among those with LBP only (difference in RMDQ due to interaction, - 0.9[95 % CI - 2.5 to 0.6]). Participants with a greater number of long-term conditions and more co-occurring musculoskeletal pain had higher levels of baseline disability (RMDQ 11.3 for ≥ 2 long-term conditions vs 9.5 for LBP only; 11.3 for ≥ 4 musculoskeletal pain sites vs 10.2 for ≤ 1 additional musculoskeletal pain site); along with higher baseline scores for stress/depression/illness perception and poorer pain self-efficacy/general health ratings. In the pooled sample, LBP-related disability improved slightly less over time for people with ≥ 2 long-term conditions additional to LBP compared to no multimorbidity and for those with ≥4 co-occurring musculoskeletal pain sites compared to ≤ 1 additional musculoskeletal pain site (difference in mean change at 9 months = 1.5 and 2.2, respectively). All groups reported little improvement in secondary outcomes over time.
conclusionsMultimorbidity or co-occurring musculoskeletal pain does not modify the effect of the selfBACK app on LBP-related disability or other secondary outcomes. Although people with these health problems have worse scores both at baseline and 9 months, the AI-based selfBACK app appears to be helpful for those with multimorbidity or co-occurring musculoskeletal pain.
trial registrationNCT03798288 . Date of registration: 9 January 2019.
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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.