The 2015 U.S. Soccer Federation header ban and its effect on emergency room concussion rates in soccer players aged 10-13.
Bibliographic record
Abstract
BACKGROUND: In 2015, the U.S. Soccer Federation banned heading for players aged 10-13. PURPOSE/QUESTION: To assess the change in proportion of children aged 10-13 playing soccer in the US presenting to an Emergency Department (ED) with a concussion in relation to any other injury before and after the ban. METHODS: Analysis was restricted to soccer athletes between 10-13 years that reported to a National Electronic Injury Surveillance System (NEISS) participating hospital ED following injury in 2013-2014 and 2016-2017. Multivariable logistic regression was performed to assess the association between year of injury and concussion diagnosis in relation to other injury diagnosis after adjusting for age, sex, and ethnicity. RESULTS: Concussion in relation to other injuries showed a significant increase in 2016-2017 when compared to 2013-2014 after adjustment (OR= 1.286, 95%CI = 1.090-1.517). CONCLUSIONS: These results suggest that banning heading may not reduce concussion within this population. However, significant confounders, including increased reporting, were not controlled for.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".