THE EFFECT OF EXPOSURE TO THE FIFA 11+ WARM-UP PROGRAM ON INJURY RISK KNOWLEDGE AND PREVENTION BELIEFS IN ELITE FEMALE YOUTH SOCCER
Bibliographic record
Abstract
Background Injury knowledge and beliefs influence uptake of injury prevention programs. The effect of exposure to prevention programs on knowledge and beliefs is not well understood. Objective To explore the effect of exposure to the FIFA 11+ program on the injury knowledge and beliefs of female youth soccer coaches and players. Design A sub-cohort analysis from a cluster-randomized controlled trial. Setting Youth soccer league venues in Alberta, Canada. Participants 31 female teams [coaches n=29, players (ages 13–18) n=258]. Risk factor assessment Teams recorded FIFA 11+ adherence during the season. Main outcome measurements Coaches and players completed pre-season and post-season questionnaires to assess changes in injury knowledge and prevention beliefs after FIFA 11+ exposure. Results At baseline, 62.8% (95% CI: 48.4–77.3) of coaches and 75.8% (95% CI: 71.5–80.1) of players considered "inadequate warm-up" a risk factor for injury. There was no effect of 11+ adherence on this belief (odds ratio=1.0; 95% CI: 0.9–1.1), although more players (78.7%; 95% CI: 73.77–83.7) than coaches (51.7%; 95% CI: 33.55–69.9) considered "inadequate warm-up" a risk factor at post-season. At baseline, 13.8% (95% CI: 1.3–26.4) of coaches believed a warm-up could prevent muscle injuries, but none believed it could prevent knee and ankle injuries. For players, 9.7% (95% CI: 6.1–13.3), 4.7% (95% CI: 2.1–7.3), and 4.7% (95% CI: 2.1–7.3) believed a warm-up would prevent muscle, knee, and ankle injuies, respectively. There was no effect of adherence on post-season beliefs that a warm-up could prevent an injury, for coaches or players. Conclusions Exposure to the FIFA 11+ appears insufficient for changing injury risk or prevention beliefs over a single season. This could have implications for program delivery strategies and may influence sustained program use.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".