Association between Musculoskeletal Injuries and Depressive Symptoms among Athletes: A Systematic Review
Bibliographic record
Abstract
Musculoskeletal (MSK) injuries have a significant physical and psychological influence on an athlete's life. A systematic review of prospective cohort, cross-sectional, and case-control studies was undertaken in this study to analyze the association between MSK injuries with depressive symptoms in athletes. We searched on PubMed, Web of Science, and Scopus, with data inception to 15 February 2023. The methodological quality was assessed using the Newcastle-Ottawa Scale (NOS). Of the 3677 potential studies only nine were included. These studies showed a bidirectional association between MSK injuries and depressive symptoms. Athletes with MSK injuries had higher levels of depressive symptoms, which raises the likelihood of experiencing depression in the future. Women athletes had higher levels of depressive symptoms compared with men. The presence of depressive symptoms is a significant predictor of disability in athletes. Our findings suggest that coaches should be more aware of depressive symptoms, in order to prevent MSK injuries, and to monitor athletes following an MSK injury.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".