Examining Concussion Rates and Return to Play in High School Football Players Wearing Newer Helmet Technology: A Three-Year Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to compare concussion rates and recovery times for athletes wearing newer helmet technology compared to traditional helmet design. METHODS: This was a three-year, prospective, naturalistic, cohort study. Participants were 2,141 high school athletes from Western Pennsylvania. Approximately half of the sample wore the Revolution helmet manufactured by Riddell, Inc. (n = 1,173) and the remainder of the sample used standard helmets (n = 968). Athletes underwent computerized neurocognitive testing through the use of ImPACT at the beginning of the study. Following a concussion, players were reevaluated at various time intervals until recovery was complete. RESULTS: In the total sample, the concussion rate in athletes wearing the Revolution was 5.3% and in athletes wearing standard helmets was 7.6% [chi (1, 2, 141) = 4.96, P < 0.027]. The relative risk estimate was 0.69 (95% confidence interval = 0.499- 0.958). Wearing the Revolution helmet was associated with approximately a 31% decreased relative risk and 2.3% decreased absolute risk for sustaining a concussion in this cohort study. The athletes wearing the Revolution did not differ from athletes wearing standard helmets on the mechanism of injury (e.g., head-to-head strike), on-field concussion markers (e.g., amnesia or loss of consciousness), or on-field presentation of symptoms (e.g., headaches, dizziness, or balance problems). CONCLUSION: Recent sophisticated laboratory research has better elucidated injury biomechanics associated with concussion in professional football players. This data has led to changes in helmet design and new helmet technology, which appears to have beneficial effects in reducing the incidence of cerebral concussion in high school football players.
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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 | 0.002 |
| 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) | 0.001 | 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".