Evidence map›Paper›PMID 37656023›Full record

Trial reportJMIR mHealth and uHealth2023

The Role of Pain Duration and Pain Intensity on the Effectiveness of App-Delivered Self-Management for Low Back Pain (selfBACK): Secondary Analysis of a Randomized Controlled Trial.

Anne Lovise Nordstoga, Lene Aasdahl, Louise Fleng Sandal, Tina Dalager, Atle Kongsvold, Paul Jarle Mork, Tom Ivar Lund Nilsen

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06896812 (A Pilot Study on App-based Treatment Combining Physical Exercise, Graded Activity, and Pain Journaling for Patients with Spinal Complaints), which is not on this map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
2.9field-weighted citation impact, top 10% of its field
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.

NCT06896812 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

A Pilot Study on App-based Treatment Combining Physical Exercise, Graded Activity, and Pain Journaling for Patients with Spinal Complaints

TypeinterventionalSponsorZuyderland Medisch CentrumRan2025 to 2025Enrolled30ConditionsBack Pain, Spinal Disease, Spinal ConditionArmsThe app-based treatment consists of a combination of physical exercise, graded activity, and pain journaling.
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Moving towards the use of artificial intelligence in pain management.European journal of pain (London, England) · 2025
    Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Review
  7. Review
  8. Review
  9. Article
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

7 authors at 3 institutions in 4 countries.

Anne Lovise Nordstoga *Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0001-6675-169X
Lene Aasdahl *Unicare Helsefort Rehabilitation Center, Rissa, Norway.ORCID 0000-0003-4276-1345
Louise Fleng SandalDepartment of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.ORCID 0000-0001-8436-1046
Tina DalagerDepartment of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.ORCID 0000-0002-6632-7001
Atle KongsvoldDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0003-4887-8288
Paul Jarle MorkDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0003-3355-2680
Tom Ivar Lund NilsenDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.ORCID 0000-0001-8251-3544
Norwegian University of Science and Technology · NOUniversity of Southern Denmark · DKUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Clinical guidelines for nonspecific low back pain (LBP) recommend self-management tailored to individual needs and capabilities as a first-line treatment. Mobile health solutions are a promising method for delivering tailored self-management interventions to patients with nonspecific LBP. However, it is not clear if the effectiveness of such self-management interventions depends on patients' initial pain characteristics. High pain intensity and long-term symptoms of LBP have been associated with an unfavorable prognosis, and current best evidence indicates that long-term LBP (lasting more than 3 months) requires a more extensive treatment approach compared to more acute LBP. The artificial intelligence-based selfBACK app supports tailored and evidence-based self-management of nonspecific LBP. In a recent randomized controlled trial, we showed that individuals who received the selfBACK app in addition to usual care had lower LBP-related disability at the 3-month follow-up compared to those who received usual care only. This effect was sustained at 6 and 9 months. Objective: This study aims to explore if the baseline duration and intensity of LBP influence the effectiveness of the selfBACK intervention in a secondary analysis of the selfBACK randomized controlled trial. Methods: In the selfBACK trial, 461 adults (18 years or older) who sought care for nonspecific LBP in primary care or at an outpatient spine clinic were randomized to receive the selfBACK intervention adjunct to usual care (n=232) or usual care alone (n=229). In this secondary analysis, the participants were stratified according to the duration of the current LBP episode at baseline (≤12 weeks vs >12 weeks) or baseline LBP intensity (≤5 points vs >5 points) measured by a 0-10 numeric rating scale. The outcomes were LBP-related disability measured by the Roland-Morris Disability Questionnaire (0- to 24-point scale), average LBP intensity, pain self-efficacy, and global perceived effect. To assess whether the duration and intensity of LBP influenced the effect of selfBACK, we estimated the difference in treatment effect between the strata at the 3- and 9-month follow-ups with a 95% CI. Results: Overall, there was no difference in effect for patients with different durations or intensities of LBP at either the 3- or 9-month follow-ups. However, there was suggestive evidence that the effect of the selfBACK intervention on LBP-related disability at the 3-month follow-up was largely confined to people with the highest versus the lowest LBP intensity (mean difference between the intervention and control group -1.8, 95% CI -3.0 to -0.7 vs 0.2, 95% CI -1.1 to 0.7), but this was not sustained at the 9-month follow-up. Conclusions: The results suggest that the intensity and duration of LBP have negligible influence on the effectiveness of the selfBACK intervention on LBP-related disability, average LBP intensity, pain self-efficacy, and global perceived effect.

Indexed as

Low Back PainMobile ApplicationsSelf-ManagementAdultArtificial IntelligenceHumansPain Measurementbackdigital interventioneffectivenesshealth applow back painmHealthmobile appmobile healthpainrandomized controlled trialRCTsecondary analysessecondary analysisself-managementspine

Identifiers

PMID37656023
PMCPMC10501500
OpenAlexW4379980065

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.