The quality of a simulation examination using a high‐fidelity child manikin
Bibliographic record
Abstract
PURPOSE: Developing quality examinations that measure physicians' clinical performance in simulations is difficult. The goal of this study was to develop a quality simulation examination using a high-fidelity child manikin in evaluating paediatric residents' competence about managing critical cases in a simulated emergency room. Quality was determined by evidence of the reliability, validity and feasibility of the examination. In addition, the participants' responses regarding its realism, effectiveness and value are presented. METHOD: Scenario scripts and rating instruments were carefully developed in this study. Experts were used to validate the case scenarios and provide evidence of construct validity. Eighteen paediatric residents, 'working' as pairs, participated in a manikin-based simulation pre-test, a training session and a post-test. Three independent raters rated the participants' performance on task-specific technical skills, medications used and behaviours displayed. At the end of the simulation, the participants completed an evaluation questionnaire. RESULTS: The manikin-based simulation examination was found to be a realistic, valid and reliable tool. Validity (i.e. face, content and construct) of the test instrument was evident. The level of inter-rater concordance of participants' clinical performance was good to excellent. The item analysis showed good to excellent internal consistency on all the performance scores except the post-test technical score. CONCLUSIONS: With a carefully designed rating instrument and simulation operation, the manikin-based simulation examination was shown to be reliable and valid. However, a further refinement of the test instrument will be required for higher stake examinations.
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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 | 0.003 | 0.009 |
| 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".