Probing the effect of OSCE checklist length on inter-observer reliability and observer accuracy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The Objective Structured Clinical Examination (OSCE) is a widely employed tool for measuring clinical competence. In the drive toward comprehensive assessment, OSCE stations and checklists may become increasingly complex. The objective of this study was to probe inter-observer reliability and observer accuracy as a function of OSCE checklist length. METHOD: Study participants included emergency physicians and senior residents in Emergency Medicine at Dalhousie University. Participants watched an identical series of four, scripted, standardized videos enacting 10-min OSCE stations and completed corresponding assessment checklists. Each participating observer was provided with a random combination of two 40-item and two 20-item checklists. A panel of physicians scored the scenarios through repeated video review to determine the 'gold standard' checklist scores. RESULTS: Fifty-seven observers completed 228 assessment checklists. Mean observer accuracy ranged from 73 to 93% (14.6-18.7/20), with an overall accuracy of 86% (17.2/20), and inter-rater reliability range of 58-78%. After controlling for station and individual variation, no effect was observed regarding the number of checklist items on overall accuracy (p=0.2305). Consistency in ratings was calculated using intraclass correlation coefficient and demonstrated no significant difference in consistency between the 20- and 40-item checklists (ranged from 0.432 to 0.781, p-values from 0.56 to 0.73). CONCLUSIONS: The addition of 20 checklist items to a core list of 20 items in an OSCE assessment checklist does not appear to impact observer accuracy or inter-rater reliability.
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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 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it