Best practices for the dissemination and implementation of neuromuscular training injury prevention warm-ups in youth team sport: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To evaluate best practices for neuromuscular training (NMT) injury prevention warm-up programme dissemination and implementation (D&I) in youth team sports, including characteristics, contextual predictors and D&I strategy effectiveness. DESIGN: Systematic review. DATA SOURCES: Seven databases were searched. ELIGIBILITY: The literature search followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. INCLUSION CRITERIA: participation in a team sport, ≥70% youth participants (<19 years), D&I outcomes with/without NMT-related D&I strategies. The risk of bias was assessed using the Downs & Black checklist. RESULTS: Of 8334 identified papers, 68 were included. Sport participants included boys, girls and coaches. Top sports were soccer, basketball and rugby. Study designs included randomised controlled trials (RCTs) (29.4%), cross-sectional (23.5%) and quasi-experimental studies (13.2%). The median Downs & Black score was 14/33. Injury prevention effectiveness (vs efficacy) was rarely (8.3%) prioritised across the RCTs evaluating NMT programmes. Two RCTs (2.9%) used Type 2/3 hybrid approaches to investigate D&I strategies. 19 studies (31.6%) used D&I frameworks/models. Top barriers were time restrictions, lack of buy-in/support and limited benefit awareness. Top facilitators were comprehensive workshops and resource accessibility. Common D&I strategies included Workshops with supplementary Resources (WR; n=24) and Workshops with Resources plus in-season Personnel support (WRP; n=14). WR (70%) and WRP (64%) were similar in potential D&I effect. WR and WRP had similar injury reduction (36-72%) with higher adherence showing greater effectiveness. CONCLUSIONS: Workshops including supplementary resources supported the success of NMT programme implementation, however, few studies examined effectiveness. High-quality D&I studies are needed to optimise the translation of NMT programmes into routine practice in youth sport.
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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 | 0.060 | 0.173 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.016 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".