The biopsychosocial factors associated with development of chronic musculoskeletal pain. An umbrella review and meta-analysis of observational systematic reviews
Bibliographic record
Abstract
AIM: The aim of this umbrella review was to establish which biopsychosocial factors are associated with development of chronic musculoskeletal pain. METHODS: Ovid Medline, Embase, Web of Science Core Collection, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, PsycINFO, CINAHL, PEDro, PROSPERO, Google Scholar and grey literature were searched from database inception to 4th April 2023. Systematic reviews of observational prospective longitudinal studies, including populations with <3 months (not chronic) musculoskeletal pain, investigating biopsychosocial factors that contribute to development of chronic (>3 months) musculoskeletal pain. Two reviewers searched the literature, assessed risk of bias (Assessing the Methodological Quality of Systematic Reviews-2), and evaluated quality (Grading of Recommendations, Assessment, Development and Evaluation) to provide an overall statement on the certainty of evidence for each biopsychosocial factor. Data analysis was performed through random effects meta-analysis (including meta-analysis of meta-analyses where possible) and descriptive synthesis. RESULTS: 13 systematic reviews were included comprising 185 original research studies (n = 489,644 participants). Thirty-four biopsychosocial factors are associated with development of chronic musculoskeletal pain. Meta-analyses of odds and/or likelihood ratios were possible for 25 biopsychosocial factors. There is moderate certainty evidence that smoking (OR 1.24 [95%CI, 1.14-1.34), fear avoidance (LR+ 2.11 [95%CI, 1.59-2.8]; LR- 0.5 [95%CI, 0.35-0.71]) poorer support networks (OR 1.21 [95%CI, 1.14-1.29]), lower socioeconomic status (OR 2.0 [95%CI, 1.64-2.42]), and high levels of pain (OR 5.61 [95%CI, 3.74-8.43]) are associated with development of chronic musculoskeletal pain (all P<0.001). Remaining factors are of low or very low certainty evidence. CONCLUSIONS AND RELEVANCE: There is moderate certainty evidence that smoking, fear avoidance, poorer support networks, lower socioeconomic status, and high levels of pain are associated with development of chronic musculoskeletal pain. High risk of bias was evident in most included reviews; this highlights the need for higher quality systematic reviews.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.099 | 0.208 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".