The effect of protective headgear on head injuries and concussions in adolescent football (soccer) players
Bibliographic record
Abstract
OBJECTIVE: To examine the effects of protective headgear in adolescent football (soccer) players. DESIGN: Cross-sectional study. SETTING: Oakville Soccer Club, Oakville, Canada. PARTICIPANTS: Football players aged 12-17 years. INTERVENTION: A questionnaire examining the 2006 football season using self-reported symptoms. MAIN OUTCOME MEASURES: The number of concussions experienced during the current football season, the duration of symptoms, injuries to the head and face and any associated risk factors for these injuries. RESULTS: In the population studied, 47.8% had experienced symptoms of a concussion during the current football year. 26.9% of athletes who wore headgear (HG) and 52.8% of those who did not wear headgear (No-HG) had concussions. Approximately 4 out of 5 athletes in each group did not realize they had suffered a concussion. More than one concussion was experienced by 50.0% of the concussed HG athletes and 69.3% of the concussed No-HG group. 23.9% of all concussed players experienced symptoms for at least 1 day or longer. Variables that increased the risk of suffering a concussion during the 2006 football year included being female and not wearing headgear. Being female and not wearing football headgear increased the risk of suffering an abrasion, laceration or contusion on areas of the head covered by football headgear. CONCLUSION: Adolescent football players experience a significant number of concussions. Being female may increase the risk of suffering a concussion and injuries on the head and face, while the use of football headgear may decrease the risk of sustaining these injuries.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".