A longitudinal simulation‐based ethical–legal curriculum for otolaryngology residents
Bibliographic record
Abstract
OBJECTIVE: To develop, implement, and evaluate a longitudinal, simulation-based ethics and legal curriculum designed specifically for otolaryngology residents. METHODS: Otolaryngology residents were recruited to participate in a yearly half-day ethical-legal module, the curriculum of which spanned 4 years. Each module included: three simulated scenarios, small-group multisource feedback, and large-group debriefings. Scenarios involved encounters with standardized patients. Residents' ethical-legal knowledge was assessed pre- and postmodule with multiple-choice questions, and ethical reasoning was assessed by a variety of evaluators during the simulated scenario using a locally developed assessment tool. Participants completed an exit survey at the end of each module. RESULTS: Eighteen residents completed four modules from the academic years of 2008 to 2009 to 2011 to 2012. The first year was considered a pilot module, and data were collected for the following 3 years. Knowledge of legal issues improved significantly among residents (mean at pre = 3.40 and post = 4.60, P < 0.05). Residents' ethical reasoning skills also improved across years (mean 3.60/5 in 2009-2010, 3.76/5 in 2010-2011, and 4.33 in 2011-2012, P < 0.05). Survey results revealed a statistically significant self-perceived improvement in ethics reasoning skills (mean pre = 3.62, post = 4.86, P < 0.05). Participants reported that the curriculum was relevant to their practice (85%), that the debriefings were of high quality (83%), and that they would recommend this module to others (88%). CONCLUSION: To our knowledge, this is the first study exploring a longitudinal simulation-based ethical-legal curriculum tailored to otolaryngology-head and neck surgery residents. This educational program resulted in a both objective and subjective improvement in legal and ethics knowledge and skills. LEVEL OF EVIDENCE: NA. Laryngoscope, 127:2501-2509, 2017.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".