11.21 Effect of sport participation on concussion knowledge and behaviours among high school students
Bibliographic record
Abstract
Objective To explore if sport participation, specifically high-risk and team, influenced concussion knowledge and behaviours among high school students. Design Cross-sectional. Setting Students completed a novel concussion survey at nine Canadian high schools. Participants 1330 students (592 males, 687 females, M=15.31±1.32 years) completed the survey. Students were recruited from 9 high schools and were excluded if they were younger than 12 or older than 19. Outcome Measures Responses were provided on the survey which examines student demographics, concussion knowledge, intention to report a concussion to an adult and intention to provide social support to a peer. Main Results Students who participated in high-risk and team sports were more likely to be male (P<0.0005) and have a concussion history (P<0.0005). Students who played high-risk and team sports had less favourable intentions to report a concussion (P=0.002; P=0.001) and less favourable intentions to provide social support (P<0.0005; P=0.004) compared to those that did not. Additionally, those that played team sports felt they knew a lot about concussions (P=0.047), however had lower knowledge scores compared to those that did not (P=0.044). There were no differences in knowledge scores between students who did and did not play high-risk sports. Conclusions This study highlights gaps in concussion knowledge as well as intended reporting and social support behaviours among students who play high-risk and team sports. This suggests that future concussion education and programming should be tailored towards these groups. Trial Registration ISRCTN registry (ISRCTN64944275).
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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 | 0.004 |
| 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 | 0.000 |
| 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".