Evidence map›Paper›PMID 35130898›Full record

Trial reportBMC medicine2022

Multimorbidity and co-occurring musculoskeletal pain do not modify the effect of the SELFBACK app on low back pain-related disability.

Cecilie K Øverås, Tom I L Nilsen, Barbara I Nicholl, Guy Rughani, Karen Wood, Karen Søgaard, Frances S Mair, Jan Hartvigsen

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

NCT03798288 nacompletednot on this map

A Decision Support System for Self-management of Low Back Pain - a Randomized Controlled Trial for the selfBACK Project

TypeinterventionalSponsorUniversity of Southern DenmarkRan2019 to 2020Enrolled461ConditionsLow Back PainArmsselfBACK, Usual care
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Moving towards the use of artificial intelligence in pain management.European journal of pain (London, England) · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Cecilie K ØveråsDepartment of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway. ckoveraas@health.sdu.dk.ORCID 0000-0002-4395-8265
Tom I L NilsenDepartment of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
Barbara I NichollInstitute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Guy RughaniInstitute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Karen WoodInstitute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Karen SøgaardDepartment of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Frances S MairInstitute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Jan HartvigsenDepartment of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Low Back PainMobile ApplicationsMusculoskeletal PainArtificial IntelligenceHumansMultimorbidityPain MeasurementQuality of LifeTreatment OutcomeArtificial intelligenceComorbidityDigital technologyLow back painMobile applicationsMultimorbidityMusculoskeletal painRandomized controlled trialSelf-managementTelemedicine

Identifiers

PMID35130898
PMCPMC8822859

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Registered trials

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.