Systematic review with meta-analysis of childhood and adolescent risk and prognostic factors for musculoskeletal pain
Bibliographic record
Abstract
A variety of factors may be involved in the development and course of musculoskeletal (MSK) pain. We undertook a systematic review with meta-analysis to synthesize and evaluate the quality of evidence about childhood and adolescent factors associated with onset and persistence of MSK pain, and its related disability. Studies were identified from searches of electronic databases (PubMed, EMBASE, PsycINFO, CINAHL, and Web of Science), references of included studies, and the Pediatric Pain mail list. Two independent reviewers assessed study inclusion, completed data extraction, and evaluated the quality of evidence using a modified Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. Thirty-six studies reporting on 21 cohorts were included. These studies examined 65 potential risk factors for onset of MSK pain and 43 potential prognosis factors for persistence of MSK pain. No study was identified that examined prognostic factors for MSK pain-related disability. High-quality evidence suggests that low socioeconomic status is a risk factor for onset of MSK pain in studies exploring long-term follow-up. Moderate-quality evidence suggests that negative emotional symptoms and regularly smoking in childhood or adolescence may be associated with later MSK pain. However, moderate-quality evidence also suggests that high body mass index, taller height, and having joint hypermobility are not risk factors for onset of MSK pain. We found other risk and prognostic factors explored were associated with low or very low quality of evidence. Additional well-conducted primary studies are needed to increase confidence in the available evidence, and to explore new childhood risk and prognostic factors for MSK pain.
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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 | 0.031 | 0.082 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.049 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".