Emergencies in otolaryngology–head and neck surgery bootcamp: A novel canadian experience
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: A 1-day intensive course (bootcamp) was developed, to teach junior otolaryngology-head and neck surgery (OTO-HNS) residents emergency procedural skills, clinical reasoning, and communication skills. This learning paradigm utilized a number of novel task trainers, panel discussions, and emergency simulations. The study objective was to assess the educational value of this bootcamp. STUDY DESIGN: Prospective cohort survey. METHODS: Residents were recruited from regional teaching centers within a 2000-km radius of the simulation center. Preceptors fluent in English and in French were in attendance. Pre-bootcamp outcome measures included the Kolb Learning Style Inventory and a self-administered survey measuring confidence levels in performing specific OTO-HNS tasks. Post-bootcamp outcome measures included a survey evaluating the bootcamp experience and a structured follow-up telephone interview. RESULTS: Twenty-eight residents participated in the bootcamp from across the United States and Canada. When asked if they felt that "overall, the educational day was an effective learning process," the average score was 4.75/5.0. The vast majority of participants (92.9%) felt they would recommend the bootcamp to a future junior resident. Kolb learning styles that prefer active experimentation (acting, initiating, and deciding) were more common than those that utilize reflective observation (imagining, analyzing, reflecting), which favors a hands-on model of learning. CONCLUSION: This first Canadian OTO-HNS bootcamp demonstrated the feasibility and effectiveness of conducting a centralized bootcamp for regional training centers spanning multiple states/provinces and languages. Future bootcamps will be held annually and will ideally continue the natural evolution of surgical, hands-on training.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".