Dissemination and implementation of injury prevention interventions: a scoping review for the Female, woman and/or girl Athlete Injury pRevention (FAIR) consensus
Bibliographic record
Abstract
OBJECTIVE: To synthesise evidence related to the dissemination and implementation (D&I) of injury prevention interventions for female, woman and/or girl (female/woman/girl) athletes. DESIGN: Scoping review. DATA SOURCES: MEDLINE, APA PsycInfo, Cochrane Databases for Systematic Review, Cochrane Central Register for Controlled Trials Registry, EMBASE, CINAHL, SPORTDiscus, ERIC, ProQuest Dissertation and Theses Global. ELIGIBILITY: Primary research including ≥25% female/woman/girl athletes of any age or people working with them (eg, coaches), participating in sports competition and/or performance, were eligible. Papers reporting D&I outcomes (eg, coach knowledge, adoption and maintenance) related to an injury prevention intervention and/or a factor (eg, coach beliefs) associated with D&I outcomes were included. RESULTS: 220 papers with 419 494 participants (96 790 athletes (49% female/woman/girl), 277 923 coaches (59% working with females/women/girls) and 44 781 others) across 81 sports were included. 89% of the papers were from Europe, Oceania and North America. Papers included amateur (n=175), sub-elite (n=10), elite (n=63) and Para sport (n=2) athletes. Interventions were training strategies (n=113), personal protective equipment (PPE, n=41), policy/rules/laws (n=5) or other (n=61, eg, multimodal). There were >650 D&I outcomes; adoption was the most common, followed by athlete and coach perceptions and attitudes about injury prevention. Key facilitators of D&I were previous injury experience, higher competition levels and positive perceptions and attitudes. CONCLUSION: Most studies on D&I of injury prevention interventions for female/woman/girl athletes were descriptive and related to athletes and coaches. Engaging people across the socio-ecological system (eg, parents, health professionals and administrators) and prioritising under-represented regions, populations and D&I-focused trials may enhance D&I outcomes and ultimately reduce injury risk in female/woman/girl athletes.
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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 | 0.184 | 0.419 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.026 | 0.022 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".