Incidence, Awareness, and Reporting of Sport-Related Concussions in Manitoba High Schools
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Federal and provincial governments in Canada are promoting provincial legislation to prevent and manage sport-related concussions (SRCs). The objective of this research was to determine the incidence of concussions in high school sport, the knowledge of the signs, symptoms, and consequences of SRC, and how likely student athletes are to report a concussion. METHODS: A cross-sectional survey of athletes (N = 225) from multiple sports in five high schools in one Manitoba school division was conducted. RESULTS: Participants in this study were well aware of the signs, symptoms, and consequences of SRC. Cognitive and emotional symptoms were the least recognized consequences. SRC is prevalent in high schools in both males and females across all sports. Of the 225 respondents, 35.3% reported having sustained an SRC. Less than half (45.5%) reported their concussion. Athletes purposely chose not to report a concussion in games (38.4%) and practices (33.8%). Two major barriers to reporting were feeling embarrassed (3.4/7) and finding it difficult (3.5/7) to report. There was, however, strong agreement (Mean 5.91/7, SD 0.09) when asked if they intend to report a concussion should they experience one in the future. CONCLUSIONS: The results suggest that high school athletes would benefit from more SRC education. Coaches and team medical staff must be trained to be vigilant for the mechanism, signs, and symptoms of injury in both game and practice situations. This study will also inform the implementation of pending legislation in Manitoba and perhaps other provinces in Canada.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".