Evaluation of a Community-based Concussion Prevention and Advocacy Program at the University of Ottawa
Bibliographic record
Abstract
Background: Injury prevention and advocacy often receives little attention in medical education despite constituting a leading cause of morbidity and premature deaths. Brain Waves is a national concussion prevention program where medical student volunteers (MSVs) deliver a one-hour interactive presentation at the classroom level. This paper reviews the data from the past eleven years of curriculum delivery, highlighting the successes and challenges towards initiating an injury prevention advocacy program at the medical school level.
 Methods: Our database included demographics collected from 2007 to 2017 as well as online survey ratings and written feedback from participating teachers and MSVs for the 2016 and 2017 school years.
 Results: The Ottawa’s Brain Waves program has been successful in the recruitment of 636 MSVs and delivering the curriculum to 9848 elementary school students over the past 11 years. Survey responses from MSVs (N=36) rated their experience positively on a 5-item Likert scale for the following dimensions for the injury prevention curriculum: Training satisfaction (4.72±0.46), Competence (4.80±0.41) and Timing (4.51±0.67). Teacher responses (N=10) showed that 90% rated the program as “Good” or “Excellent”. Written feedback from MSVs and teachers highlighted the importance of time management, focused-lesson plans and activity-based engagement.
 Conclusions: Through involvement in the Ottawa Brain Waves program, MSVs actively contributed to mitigating risks of accidental brain injuries, adapted to the needs of the classroom and heightened their curiosity in community-based advocacy.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".