Evidence map›Paper›PMID 41282198›Full record

ArticleResearch square2025

A meta-model of low back pain to examine collective expert knowledge of the effects of treatments and their mechanisms.

Jacek Cholewicki, Paul W Hodges, John M Popovich, Payam Aminpour, Steven A Gray, Angela S Lee, Alan Breen, Simon Brumagne, Jaap H van Dieën, Linda R Van Dillen and 22 more

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In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

32 authors.

Jacek CholewickiMichigan State University.
Paul W HodgesUniversity of Queensland.
John M PopovichMichigan State University.
Payam AminpourThermo Fisher Scientific (United States).
Steven A GrayMichigan State University.
Angela S LeeMichigan State University.
Alan BreenBournemouth University.
Simon BrumagneKU Leuven.
Jaap H van DieënVrije Universiteit Amsterdam.
Linda R Van DillenWashington University School of Medicine in St. Louis.
Thomas E DreisingerTherapy Advisors.
Manuela L FerreiraThe University of Sydney.
Steven Z GeorgeDuke University.
Christine M GoertzDuke University.
Jan HartvigsenUniversity of Southern Denmark.
Julie A HidesGriffith University.
Damian HoyThe University of Sydney.
Gregory N KawchukUniversity of Alberta.
Bart W KoesErasmus MC.
Ralph KotheSchön Klinik Hamburg Eilbek.
Helene M LangevinNational Institutes of Health.
Diane LeeDiane Lee & Associates.
Jeffrey C LotzUniversity of California, San Francisco.
G Lorimer MoseleyUniversity of South Australia.
Heidi PratherHospital for Special Surgery.
N Peter ReevesSumaq Life LLC.
Shirley SahrmannWashington University School of Medicine in St. Louis.
Rob J SmeetsMaastricht University.
Laura S StoneUniversity of Minnesota.
Johan W S VlaeyenKU Leuven.
Jeffrey C WangUniversity of Southern California.
Sherri WeiserNew York University Langone Medical Center.

Funding

Spinal Control during Functional Activities to Improve Low Back Pain OutcomesR01HD047709 · NICHD · WASHINGTON UNIVERSITY · PI VANDILLEN, LINDA R · 2006 to 2017
$3.7M
NICHD NIH HHS R01 HD047709
6 · The paper itself

Abstract

Purpose: Low back pain (LBP) is a complex, multifactorial condition with diverse contributors across biopsychosocial domains. Although personalized treatment is advocated, clear guidance on tailoring interventions is lacking. To help address this gap, we synthesized expert knowledge on treatment effectiveness and underlying mechanisms using a systems-based, collaborative modeling approach. Methods: Twenty-nine experts from diverse disciplines created individual fuzzy cognitive maps (FCMs) to represent their understanding of factors affecting pain, disability, and quality of life (QoL), along with treatment mechanisms. These maps were aggregated into a meta-model comprising 142 Components and 1,161 weighted Connections. Centrality was used to identify the most central domains of the meta-model. Simulations with the meta-model based on expert knowledge 1) estimated the relative effectiveness of treatments on pain, disability, and QoL and 2) identified key Mediators and mediating Domains based on their relative contribution to mediating treatment effects. Results: Psychological, biomechanical, and social/contextual Domains were central to expert conceptualizations of LBP. Simulation indicated cognitive behavioral therapy was considered the most effective among all interventions. Most interventions were mediated by Components across multiple Domains, with psychological factors frequently serving as mediators. The conceptual meta-model underscored the complexity of LBP, reflecting both its multifactorial nature and the diversity of expert perspectives on factors related to treatment effectiveness. Conclusion: The developed meta-model provides a novel, systems-based representation of expert knowledge about LBP, enabling quantitative exploration of treatment effects and underlying mechanisms. This conceptual framework also offers a foundation for advancing research on multi-modal, personalized care.

Identifiers

PMID41282198
PMCPMC12636709

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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.