11.16 The 2015 U.S soccer federation header ban and its effect on emergency room concussion rates in adolescent soccer players
Bibliographic record
Abstract
Objective In 2015, due to ongoing litigation the U.S Soccer Federation banned heading for players 10–13 years of age. The purpose of this study was to assess the change in proportion of children aged 10–13 playing soccer in the United States presenting to an Emergency Department (ED) with a concussion in relation to any other injury before and after the 2015 header ban. Design Descriptive Epidemiological Study. Setting Over 100 U.S. Hospital ED’s participating in the National Electronic Injury Surveillance System (NEISS). Participants 7496 soccer athletes (2920 female, 4576 male) between the ages of 10–13 that reported to a US hospital ED following injury in 2013–2014 and in 2016–2017. Interventions (or Assessment of Risk Factors) Multivariable logistic regression was performed to assess the association between year of injury and concussion diagnosis in relation to any other injury diagnosis after controlling for age, gender, and ethnicity. Outcome Measures Physician diagnosis of concussion or any other injury in ED. Main Results Concussion in relation to all other injuries showed a statistically significant increase in 2016–2017 when compared to 2013–2014 after controlling for all covariates (OR= 1.286, 95%CI = 1.090–1.517). Conclusions These results suggest that banning heading in soccer may not reduce concussion. The increase concussion may reflect increased reporting due to policy and educational measures by the U.S. Soccer Federation after the ban.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.012 | 0.001 |
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".