Evaluation of Patient Simulator Performance as an Adjunct to the Oral Examination for Senior Anesthesia Residents
Bibliographic record
Abstract
BACKGROUND: Patient simulators possess features for performance assessment. However, the concurrent validity and the "added value" of simulator-based examinations over traditional examinations have not been adequately addressed. The current study compared a simulator-based examination with an oral examination for assessing the management skills of senior anesthesia residents. METHODS: Twenty senior anesthesia residents were assessed sequentially in resuscitation and trauma scenarios using two assessment modalities: an oral examination, followed by a simulator-based examination. Two independent examiners scored the performances with a previously validated global rating scale developed by the Anesthesia Oral Examination Board of the Royal College of Physicians and Surgeons of Canada. Different examiners were used to rate the oral and simulation performances. RESULTS: Interrater reliability was good to excellent across scenarios and modalities: intraclass correlation coefficients ranged from 0.77 to 0.87. The within-scenario between-modality score correlations (concurrent validity) were moderate: r = 0.52 (resuscitation) and r = 0.53 (trauma) (P < 0.05). Forty percent of the average score variance was accounted for by the participants, and 30% was accounted for by the participant-by-modality interaction. CONCLUSIONS: Variance in participant scores suggests that the examination is able to perform as expected in terms of discriminating among test takers. The rather large participant-by-modality interaction, along with the pattern of correlations, suggests that an examinee's performance varies based on the testing modality and a trainee who "knows how" in an oral examination may not necessarily be able to "show how" in a simulation laboratory. Simulation may therefore be considered a useful adjunct to the oral examination.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".