Deficiencies in Concussion Education in Canadian Medical Schools
Bibliographic record
Abstract
BACKGROUND: Recent reports raise concern that physician knowledge of the identification and management of concussion may be deficient. There is little information known about the adequacy of concussion education provided to physicians or medical students. The present study assesses the concussion curriculum offered at medical schools in Canada. METHODS: We asked all 17 Canadian medical schools to complete a questionnaire on their concussion curriculum, including the following: year of medical school offered; format/setting; and estimated teaching hours. The responses were organized into three categories: (1) concussion-specific education; (2) head injury education incorporating a concussion component; and (3) no concussion education. RESULTS: Replies were received from 14 (82%) of the 17 medical schools in Canada. Of the 14 responding schools, four (29%) provided concussion-specific education, six (43%) offered head injury education that incorporated a concussion component, and four (29%) reported no concussion teaching in their curriculum. CONCLUSION: We found deficiencies in the concussion education curriculum provided in the majority of Canadian medical schools. To address this issue, we recommend that all medical schools should, at a minimum, include a one-hour formal concussion-specific teaching session in an early year of their curriculum to be followed by clinical exposure to concussed patients in the later years of medical school. Future studies will be necessary to evaluate if these recommended curricular enhancements are effective in remedying the reported gaps in physicians' concussion knowledge and whether the improved curriculum translates into better care for patients suffering concussion.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".