Knowledge, Attitudes and Concussion Information Sources Among First Nations in Ontario
Bibliographic record
Abstract
OBJECTIVE: Hockey is a popular sport played by many First Nation youth. Concussion frequently goes unrecognized and unreported in youth hockey. Unintentional injuries among Indigenous youth occur at rates three to four times the national Canadian average. The study sought to examine knowledge, attitudes and sources of concussion information among First Nations people attending a provincial hockey tournament. METHODS: A cross-sectional survey was undertaken. The survey by Mzazik et al. were modified to use in this study. Participants included youth (6-18 years) hockey players (n=75), parents (n=248) and coaches (n=68). The main outcome measure was total knowledge index (TKI) which consisted of the sum of correct responses to 15 multiple choice questions. Additional data gathered included demographics, concussion history, attitudes toward concussion and sources of information. Descriptive statistics included proportion comparisons. Variables were tested using χ 2 and analysis of variance. RESULTS: Overall TKI scores (out of a total of 15) were low; players (5.9±2.8), parents (7.5±2.6) and coaches (7.9±2.6). Participants with higher knowledge scores reported more appreciation of the seriousness of concussion. Sources of information about concussion differed by study group, suggesting the need for multiple knowledge translation strategies to reach youth, parents and coaches. CONCLUSIONS: Future initiatives are urgently needed to improve education and prevention of concussion in First Nations youth hockey. Collaborating and engaging with communities can help to ensure an Indigenous lens for culturally safe interventions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".