Overuse injuries are prevalent in children’s competitive football: a prospective study using the OSTRC Overuse Injury Questionnaire
Bibliographic record
Abstract
OBJECTIVES: To investigate the prevalence and burden of overuse injuries in children's football as well as player characteristics and their association with overuse injury risk. METHODS: This investigation is based on the control arm (10 clubs) of a randomised controlled trial investigating prevention of injuries in youth football. We conducted a prospective 20-week follow-up study on overuse injuries among Finnish football players (n=733, aged 9-14 years). Each week, we sent a text message to players' parents to ask if the player had sustained any injury during the past week. Players with overuse problem were interviewed over the phone using an overuse injury questionnaire. The main outcome measures were prevalence of all overuse injuries and substantial overuse injuries (those leading to moderate or severe reductions in participation or performance) and injury severity. RESULTS: The average response rate was 95%. In total, 343 players (46.8%) reported an overuse problem while in the study. The average weekly prevalence of all overuse problems and substantial overuse problems was 12.8% and 6.0%, respectively. Injuries affecting the knee had the highest weekly prevalence (5.7% and 2.4% for all and substantial knee problems, respectively). Girls had a higher likelihood of knee problems (OR 2.70; 95% CI 1.69 to 4.17), whereas boys had a higher likelihood of heel problems (OR 2.82; 95% CI 1.07 to 7.44). The likelihood of reporting an overuse problem increased with age (OR 1.21; 95% CI 1.00 to 1.47). CONCLUSION: Overuse injuries are prevalent in children's competitive football. Knee overuse injuries represent the greatest burden on participation and performance. TRIAL REGISTRATION NUMBER: ISRCTN14046021.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".