High adherence to a neuromuscular injury prevention programme (FIFA 11+) improves functional balance and reduces injury risk in Canadian youth female football players: a cluster randomised trial
Bibliographic record
Abstract
BACKGROUND: A protective effect on injury risk in youth sports through neuromuscular warm-up training routines has consistently been demonstrated. However, there is a paucity of information regarding the quantity and quality of coach-led injury prevention programmes and its impact on the physical performance of players. OBJECTIVE: The aim of this cluster-randomised controlled trial was to assess whether different delivery methods of an injury prevention programme (FIFA 11+) to coaches could improve player performance, and to examine the effect of player adherence on performance and injury risk. METHOD: During the 2011 football season (May-August), coaches of 31 tiers 1-3 level teams were introduced to the 11+ through either an unsupervised website or a coach-focused workshop with and without additional on-field supervisions. Playing exposure, adherence to the 11+, and injuries were recorded for female 13-year-old to 18-year-old players. Performance testing included the Star Excursion Balance Test (SEBT), single-leg balance, triple hop and jumping-over-a-bar tests. RESULTS: Complete preseason and postseason performance tests were available for 226 players (66.5%). Compared to the unsupervised group, single-leg balance (OR=2.8; 95% CI 1.1 to 4.6) and the anterior direction of the SEBT improved significantly in the onfield supervised group of players (OR=4.7; 95% CI 2.2 to 7.1), while 2-leg jumping performance decreased (OR=-5.1; 95% CI -9.9 to -0.2). However, significant improvements in 5 of 6 reach distances in the SEBT were found, favouring players who highly adhered to the 11+. Also, injury risk was lower for those players (injury rate ratio, IRR=0.28, 95% CI 0.10 to 0.79). CONCLUSIONS: Different delivery methods of the FIFA 11+ to coaches influenced players' physical performance minimally. However, high player adherence to the 11+ resulted in significant improvements in functional balance and reduced injury risk.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".