The Advanced Trauma Operative Management course in a Canadian residency program.
Bibliographic record
Abstract
BACKGROUND: The Advanced Trauma Operative Management (ATOM) course was first introduced into Canada in 2003 at the University of Toronto, with senior general surgery residents being the primary focus. We present an assessment of the course in this Canadian general surgery residency program. METHODS: We compared trainees' pre-and postcourse self-efficacy scores and multiple choice question (MCQ) examination results, using paired t tests and resident (n = 24) and faculty (n = 7) course ratings made according to a 10-item, 5-point Likert scale. Faculty were previously trained as ATOM instructors. RESULTS: Mean pre-and postcourse self-efficacy scores were 68.9 (standard deviation [SD] 24.0) and 101.4 (SD 14.8), respectively (p < 0.001). Mean pre-and post-MCQ scores were 16.4 (SD 3.2) and 18.8 (SD 2.7), respectively (p = 0.006). On the Likert scale (1 = strongly disagree, 5 = strongly agree), all faculty and residents rated the following items as 4-5: objectives were met; knowledge, skills, clinical training, judgment and confidence improved; the live animal is a useful representation of clinical trauma; and the course should be continued but would be more appropriate for the fourth rather than the fifth year of residency. Residents rated as 1-2 the item that the human cadaver would be preferable for learning the surgical skills. Of 24 residents, 20 rated as 3 or less the item stating that the course prepares them for trauma management more adequately than their regular training program. CONCLUSION: Self-efficacy, trauma knowledge and skills improved significantly with ATOM training. Preference was expressed for the live animal versus cadaver model, for ATOM training in the fourth rather than fifth year of residency and for the view that it complements general surgery trauma training. The data suggest that including ATOM training in Canadian general surgical residency should be considered.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".