Evidence map›Paper›PMID 37368401›Full record

Trial reportJAMA network open2023

Effect of an Artificial Intelligence-Based Self-Management App on Musculoskeletal Health in Patients With Neck and/or Low Back Pain Referred to Specialist Care: A Randomized Clinical Trial.

Anna Marcuzzi, Anne Lovise Nordstoga, Kerstin Bach, Lene Aasdahl, Tom Ivar Lund Nilsen, Ellen Marie Bardal, Nora Østbø Boldermo, Gro Falkener Bertheussen, Gunn Hege Marchand, Sigmund Gismervik and 1 more

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04463043 (The Effectiveness of an App-based), which is not on this map. Cited by 44 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 11 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.

NCT04463043 nacompletednot on this map

The Effectiveness of an App-based (selfBACK) Versus a Web-based (e-Help) Self-management Intervention or Usual Care in People With Low Back and/or Neck Pain on a Waiting List for Hospital-based Outpatient Rehabilitation: a Three Arm Randomised Controlled Trial

TypeinterventionalSponsorNorwegian University of Science and TechnologyRan2020 to 2021Enrolled294ConditionsBack Pain, Neck PainArmsSelfBACK app, e-Help webpage, Usual care
3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 11 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Telerehabilitation for neck pain.The Cochrane database of systematic reviews · 2025
    Pooled it
  5. Models of care for managing non-specific low back pain.The Cochrane database of systematic reviews · 2025
    Pooled it
  6. Moving towards the use of artificial intelligence in pain management.European journal of pain (London, England) · 2025
    Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. Pooled it
  11. Pooled it
  12. Trial
  13. Trial
  14. Trial
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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

11 authors.

Anna MarcuzziDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Anne Lovise NordstogaDepartment of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway.
Kerstin BachDepartment of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway.
Lene AasdahlDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Tom Ivar Lund NilsenDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Ellen Marie BardalDepartment of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway.
Nora Østbø BoldermoDepartment of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway.
Gro Falkener BertheussenDepartment of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway.
Gunn Hege MarchandDepartment of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim, Norway.
Sigmund GismervikDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.
Paul Jarle MorkDepartment of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Self-management is a key element in the care of persistent neck and low back pain. Individually tailored self-management support delivered via a smartphone app in a specialist care setting has not been tested. Objective: To determine the effect of individually tailored self-management support delivered via an artificial intelligence-based app (SELFBACK) adjunct to usual care vs usual care alone or nontailored web-based self-management support (e-Help) on musculoskeletal health. Design, Setting, and Participants: This randomized clinical trial recruited adults 18 years or older with neck and/or low back pain who had been referred to and accepted on a waiting list for specialist care at a multidisciplinary hospital outpatient clinic for back, neck, and shoulder rehabilitation. Participants were enrolled from July 9, 2020, to April 29, 2021. Of 377 patients assessed for eligibility, 76 did not complete the baseline questionnaire, and 7 did not meet the eligibility criteria (ie, did not own a smartphone, were unable to take part in exercise, or had language barriers); the remaining 294 patients were included in the study and randomized to 3 parallel groups, with follow-up of 6 months. Interventions: Participants were randomly assigned to receive app-based individually tailored self-management support in addition to usual care (app group), web-based nontailored self-management support in addition to usual care (e-Help group), or usual care alone (usual care group). Main Outcomes and Measures: The primary outcome was change in musculoskeletal health measured by the Musculoskeletal Health Questionnaire (MSK-HQ) at 3 months. Secondary outcomes included change in musculoskeletal health measured by the MSK-HQ at 6 weeks and 6 months and pain-related disability, pain intensity, pain-related cognition, and health-related quality of life at 6 weeks, 3 months, and 6 months. Results: Among 294 participants (mean [SD] age, 50.6 [14.9] years; 173 women [58.8%]), 99 were randomized to the app group, 98 to the e-Help group, and 97 to the usual care group. At 3 months, 243 participants (82.7%) had complete data on the primary outcome. In the intention-to-treat analysis at 3 months, the adjusted mean difference in MSK-HQ score between the app and usual care groups was 0.62 points (95% CI, -1.66 to 2.90 points; P = .60). The adjusted mean difference between the app and e-Help groups was 1.08 points (95% CI, -1.24 to 3.41 points; P = .36). Conclusions and Relevance: In this randomized clinical trial, individually tailored self-management support delivered via an artificial intelligence-based app adjunct to usual care was not significantly more effective in improving musculoskeletal health than usual care alone or web-based nontailored self-management support in patients with neck and/or low back pain referred to specialist care. Further research is needed to investigate the utility of implementing digitally supported self-management interventions in the specialist care setting and to identify instruments that capture changes in self-management behavior. Trial Registration: ClinicalTrials.gov Identifier: NCT04463043.

Indexed as

Low Back PainMobile ApplicationsSelf-ManagementAdultArtificial IntelligenceFemaleHumansMiddle AgedQuality of Life

Identifiers

PMID37368401
PMCPMC10300712

What OpenQuestion holds

Textmetadata
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.