Comparative Effectiveness of Multi-Component, Exercise-Based Interventions for Preventing Soccer-Related Musculoskeletal Injuries: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Soccer is a high-intensity sport characterized by a considerable incidence of injuries, particularly among professional male players, with injury rates ranging from 5.9 to 9.6 per 1000 player-hours. Lower limb injuries, including those affecting the knee, ankle, hip/groin, and hamstring muscles, are particularly prevalent. Additionally, a history of prior injuries may exacerbate the risk of recurrence. In response to these concerns, various injury prevention programs have been developed and implemented, targeting different genders and age groups. Methods: This systematic review and meta-analysis, conducted with the PRISMA guidelines, critically evaluated randomized RCTs across diverse genders and age groups to assess the efficacy of multi-component exercise-based injury prevention programs in reducing musculoskeletal injuries among soccer players. Comprehensive searches were conducted in ClinicalTrials.gov, CENTRAL, EMBASE, PubMed, Scopus, and Web of Science, with no language restrictions applied. Results: A total of 15 RCTs met the predefined inclusion criteria. The intervention programs were found to be significantly effective in reducing lower limb injuries, with a pooled RR of 0.73 (95% CI: 0.63 to 0.84, p = 0.035). Subgroup analyses further revealed a significant reduction in the incidence of hamstring, knee, and ankle injuries following the implementation of these programs. Conclusions: Multi-component exercise-based injury prevention programs demonstrate considerable efficacy in reducing musculoskeletal injuries in soccer players, spanning various age groups and genders. These findings underscore the potential of such programs in professional soccer injury management and highlight their importance in the development of comprehensive injury prevention strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".