Health research methodology education in Canadian emergency medicine residency programs: A national environmental scan
Bibliographic record
Abstract
OBJECTIVES: Our objective was to describe the variability of research methodology teaching among English-speaking Royal College of Physicians and Surgeons of Canada emergency medicine (RCPSC-EM) residency programs. We also aimed to identify barriers to teaching research methodology curricula. METHODS: An electronic survey was sent by email to program directors and residents of English-speaking RCPSC-EM training programs countrywide. Reminder emails were sent after two, four, and eight weeks. Quantitative, descriptive statistics were prepared, and qualitative data and themes were identified. RESULTS: We received a total of seven responses from the possible 12 program directors (response rate = 58.3%). Out of 354 potential resident respondents, 82 (23.2%) completed the survey. There was disparity between resident and program director responses with respect to the existence of curricula, preparation for Royal College exams, and usefulness for future practice. Barriers to teaching a research methodologies curriculum included lack of time, support, educated faculty, and finances. CONCLUSION: This survey demonstrates that Canadian EM residency programs vary with respect to research methodology curriculum, and discrepancies exist between residents' and program directors' perceptions of the curriculum. Given the lack of a standardized research methodology curriculum for these programs, there is an opportunity to improve training in research methodology.
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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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".