How Effective Are Nonsurgical Interventions for Work-Related Shoulder Pain? A Systematic Review With Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of nonsurgical interventions for work-related shoulder pain. DESIGN: Intervention systematic review with meta-analysis of randomized controlled trials. DATA SOURCES: Six databases and 2 clinical trial registries were searched, supplemented by manual searches and citation tracking. Eligible trials compared nonsurgical interventions for work-related shoulder pain. DATA SYNTHESIS: Outcomes of interest were pain intensity, physical functioning, return to work, and productivity loss. Risk of bias was assessed using the Cochrane Risk of Bias tool 2.0; certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework. A random-effects meta-analysis and narrative synthesis were performed. RESULTS: Of 8608 records identified, 24 randomized controlled trials met the inclusion criteria. Four trials were included in meta-analysis. No trials were at low risk of bias. The evidence was very uncertain (GRADE) regarding the effect of exercises interventions (eg, strengthening, stretching, and endurance exercises) compared to no intervention on short-term pain intensity (standardized mean difference, –0.60; 95% confidence interval: –1.22, 0.03; 95% prediction interval: –1.83, 0.64; k = 4; n = 172). Reanalyzing using 3 alternative meta-analysis approaches for small-study meta-analyses yielded different results. The narrative synthesis provided no additional insights. CONCLUSION: The evidence was very uncertain about whether exercise interventions (strengthening, stretching, and endurance) provided a moderate short-term (<3 months) benefit for reducing pain compared with no intervention. These results should be interpreted cautiously due to the limited number of trials included in the meta-analysis and the inconsistent terminology for work-related shoulder pain. J Orthop Sports Phys Ther 2025;55(11):705-718. Epub 3 October 2025. doi:10.2519/jospt.2025.13360
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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 | 0.064 | 0.175 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.034 | 0.045 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 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".