Canadian Minor Hockey Participants’ Knowledge about Concussion
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In Canada and the USA, ice hockey is a cause of traumatic brain injury. Post-concussive symptoms are the most important feature of the diagnosis of concussion in sports and it is recommended that athletes not return to play while still symptomatic. Lack of knowledge of concussions could therefore be one of the main detriments to concussion prevention in hockey. The purpose of this research is to describe what minor league hockey players, coaches, parents and trainers know about concussion and its management. METHODS: A questionnaire to assess concussion knowledge and return to play guidelines was developed and administered to players at different competitive levels (n = 267), coaches, trainers and parents (total adults n = 142) from the Greater Toronto Area. RESULTS: Although a majority of adults and players could identify mechanisms responsible for concussion, about one-quarter of adults and about a quarter to a half of children could not recall any symptoms or recalled only one symptom of a concussion. A significant number of players and some adults did not know what a concussion was or how it occurred. Almost half of the players and a fifth of the adults incorrectly stated that concussion was treated with medication or physical therapy. Nearly one quarter of all players did not know if an athlete experiencing symptoms of concussion should continue playing. CONCLUSIONS: This study demonstrated that a significant number of people held misconceptions about concussion in hockey which could lead to serious health consequences and creates a need for better preventive and educational strategies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".