Development and testing of an objective structured clinical exam (OSCE) to assess socio-cultural dimensions of patient safety competency
Bibliographic record
Abstract
BACKGROUND: Patient safety (PS) receives limited attention in health professional curricula. We developed and pilot tested four Objective Structured Clinical Examination (OSCE) stations intended to reflect socio-cultural dimensions in the Canadian Patient Safety Institute's Safety Competency Framework. SETTING AND PARTICIPANTS: 18 third year undergraduate medical and nursing students at a Canadian University. METHODS: OSCE cases were developed by faculty with clinical and PS expertise with assistance from expert facilitators from the Medical Council of Canada. Stations reflect domains in the Safety Competency Framework (ie, managing safety risks, culture of safety, communication). Stations were assessed by two clinical faculty members. Inter-rater reliability was examined using weighted κ values. Additional aspects of reliability and OSCE performance are reported. RESULTS: Assessors exhibited excellent agreement (weighted κ scores ranged from 0.74 to 0.82 for the four OSCE stations). Learners' scores varied across the four stations. Nursing students scored significantly lower (p<0.05) than medical students on three stations (nursing student mean scores=1.9, 1.9 and 2.7; medical student mean scores=2.8, 2.9 and 3.5 for stations 1, 2 and 3, respectively where 1=borderline unsatisfactory, 2=borderline satisfactory and 3=competence demonstrated). 7/18 students (39%) scored below 'borderline satisfactory' on one or more stations. CONCLUSIONS: Results show (1) four OSCE stations evaluating socio-cultural dimensions of PS achieved variation in scores and (2) performance on this OSCE can be evaluated with high reliability, suggesting a single assessor per station would be sufficient. Differences between nursing and medical student performance are interesting; however, it is unclear what factors explain these differences.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".