Virtual OSCE examinations during COVID-19 A 360 satisfaction assessment from examiners and candidates.
Bibliographic record
Abstract
INTRODUCTION: We sought to determine the satisfaction rates of examiners and candidates in a virtual Objective Structured Clinical Exam (OSCE) of graduating Canadian urology residents. METHODS: An annual mock exam, aimed at simulating the licencing urology exam for Canadian graduates, was moved to an online format for the 2020 cohort. This exam consists of an OSCE, and a written multiple-choice exam. The Telemedicine Satisfaction Questionnaire (TSQ), a previously validated tool for clinical encounters with three sub-domains (quality of care provided, similarity to face-to-face encounter, and perception of the interaction) was modified for the purposes of evaluating the OSCE encounter. The TSQ was sent electronically to all examiners and candidates after the exam. RESULTS: There were 14/16 responses from examiners (87.5%) and 24/39 responses from candidates (61.5%). Overall, the format was judged to be a good experience by 13/14 (92.9%) of examiners and 21/24 (87.5%) of candidates; however, when asked specifically if the virtual OSCE was an acceptable way to determine a candidate's competency to practice urology independently, only 8/14 (57.1%) of examiners and 15/24 (62.5%) of candidates agreed. CONCLUSIONS: This study demonstrates an overall good satisfaction rate among both examiners and candidates when using a teleconference format for a mock OSCE.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".