Mechanisms of Injury for Concussions in University Football, Ice Hockey, and Soccer
Bibliographic record
Abstract
OBJECTIVE: To examine the mechanisms of injury for concussions in university football, ice hockey, and soccer. DESIGN: Prospective cohort design. SETTING: McGill University Sport Medicine Clinic. PARTICIPANTS: Male and female athletes participating in varsity football, ice hockey, and soccer. MAIN OUTCOME MEASURES: Athletes were followed prospectively over a 10-year period to determine the mechanisms of injury for concussions and whether contact with certain areas of the body or individual variables predisposed to longer recovery from concussions. For soccer, data were collected on whether concussions occurred while attempting to head the ball. RESULTS: There were 226 concussions in 170 athletes over the study period. The side/temporal area of the head or helmet was the most common area to be struck resulting in concussion in all 3 sports. Contact from another player's head or helmet was the most probable mechanism in football and soccer. In hockey, concussion impacts were more likely to occur from contact with another body part or object rather than another head/helmet. Differences in mechanisms of injuries were found between males and females in soccer and ice hockey. Athletes with multiple concussions took longer to return to play with each subsequent concussion. Half of the concussions in soccer were related to attempting to head the soccer ball. CONCLUSIONS: The side of the head or helmet was the most common area to be struck resulting in concussion in all 3 sports. In ice hockey and soccer, there are differences in the mechanisms of injury for males and females within the same sport.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".