Validity and Feasibility Evidence of Objective Structured Clinical Examination to Assess Competencies of Pediatric Critical Care Trainees*
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to provide validity and feasibility evidence for the use of an objective structured clinical examination in the assessment of pediatric critical care medicine trainees. DESIGN: This was a validation study. Validity evidence was based on Messick's framework. SETTING: A tertiary, university-affiliated academic center. SUBJECTS: Seventeen pediatric critical care medicine fellows were recruited in 2012 and 2013 academic year. INTERVENTIONS: None. All subjects completed an objective structured clinical examination assessment. MEASUREMENTS AND MAIN RESULTS: Seventeen trainees were assessed. Simulation scenarios were developed for content validity by pediatric critical care medicine and education experts using CanMEDS competencies. Scenarios were piloted before the study. Each scenario was evaluated by two interprofessional raters. Inter-rater agreement, measured using intraclass correlations, was 0.91 (SE = 0.09) across stations. Generalizability theory was used to evaluate internal structure and reliability. Reliability was moderate (G-coefficient = 0.67, Φ-coefficient = 0.52). The greatest source of variability was from participant by station variance (40.6%). Pearson correlation coefficients were used to evaluate the relationship of objective structured clinical examination with each traditional assessment instruments: multisource feedback, in-training evaluation report, short-answer questions, and Multidisciplinary Critical Care Knowledge Assessment Program. Performance on the objective structured clinical examination correlated with performance on the Multidisciplinary Critical Care Knowledge Assessment Program (r = 0.52; p = 0.032) and multisource feedback (r = 0.59; p = 0.017), but not with the overall performance on the in-training evaluation report (r = 0.37; p = 0.143) or short-answer questions (r = 0.08; p = 0.767). Consequences were not assessed. CONCLUSION: Validity and feasibility evidence in this study indicate that the use of the objective structured clinical examination scores can be a valid way to assess CanMEDS competencies required for independent practice in pediatric critical care medicine.
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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 | 0.109 | 0.341 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".