Brain smart – Let's play safely: Evaluation of a concussion education program in schools
Bibliographic record
Abstract
Objectives There are two objectives for this paper. First, to determine effects of a concussion education program in a local school board in terms of concussion-specific knowledge in children and confidence in identifying and managing concussion in adults. Second, to identify differences and similarities in concussion knowledge between children who participate in sports and those who do not and between children with a history of one or more concussions and those without. Design A cross sectional survey regarding concussion knowledge was distributed randomly to students and adults at both pre- and posteducation timepoints. A concussion education program was disseminated across the school board for students between the distribution survey timepoints. Following the education program, adults and students completed their respective post-test surveys. Chi-squared tests in SPSS determined the significance of between-group differences. Results All 17 adults (100.0%) who had received concussion education recently reported confidence in their knowledge of concussion management, compared to 35.7% adults who had not received education for over a year (p = 0.020). For students, all of whom completed the concussion education training between the pre- and post-tests, there were no significant differences in concussion knowledge scores between athletes and non-athletes (either in or outside of school) or between those with a history of concussion and those without. There were no significant changes in concussion knowledge between the pre- and post-tests, except for one question. Conclusion Concussion education programs increase confidence of concussion management protocols in adults involved in sport, but they require improvements to better support knowledge amelioration, particularly for target groups that are at high risk of sustaining another injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".