Prevention strategies for lower extremity injury: a systematic review and meta-analyses for the Female, woman and/or girl Athlete Injury pRevention (FAIR) consensus
Bibliographic record
Abstract
OBJECTIVE: Examine the effectiveness and unintended consequences of prevention strategies for reducing female/woman/girl athletes' lower extremity (LE) injuries. DESIGN: Systematic review with meta-analyses and Grading of Recommendations, Assessment, Development and Evaluation. DATA SOURCES: Systematic search of eight data sources. ELIGIBILITY: Primary data studies with a comparison group(s) investigating injury prevention strategies for sport-related LE injuries with ≥1 female/woman/girl in each study group. RESULTS: Across 82 studies-including 48 randomised controlled trials (59%), 16 quasiexperimental studies (20%), 16 cohort studies (20%) and 1 cross-sectional study (1%)-a total of 154 561 participants were included, of whom 84 915 (55%) were females/women/girls. Neuromuscular training (NMT)-based programmes (n=60, 73%) were the most frequently studied intervention, followed by personal protective equipment (PPE) (n=9, 11%), policy/rule change (n=4, 5%) and education (n=6, 7%). The median Downs and Black score for all studies was 17 (range: 5-24). Point estimate from pooled results from nine studies revealed that NMT programmes, which include LE balance, strength, agility and change of direction exercises, with a minimum dose of 10 min two times per week, reduced female/woman/girl athletes' LE injuries by 19% (0.81, 95% CI 0.61% to 1.08%; low certainty evidence). Point estimate of pooled results from six studies uncovered that NMT reduced ankle sprains by 39% (0.61, 95% CI 0.36% to 1.03%; moderate certainty evidence). NMT significantly reduced anterior cruciate ligament (ACL) injuries by 61% (0.39, 95% CI 0.25% to 0.60%; high certainty evidence). CONCLUSION: NMT programmes can reduce female/woman/girl athletes' ACL injuries by up to 61% and ankle sprains by 39%, highlighting the need for widespread implementation of NMT programmes. Evidence informing PPE, policy/rule changes and education to prevent female/woman/girl athletes' LE injuries is needed. PROSPERO REGISTRATION NUMBER: CRD42024486715.
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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 | 0.021 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.035 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".