Point-of-Care Assessment of Medical Trainee Competence for Independent Clinical Work
Bibliographic record
Abstract
BACKGROUND: Clinical supervisors make frequent assessments of medical trainees' competence so they can provide appropriate opportunities for trainees to experience clinical independence. This study explored context-specific assessments of trainees' competence for independent clinical work. METHOD: In Phase One, 88 teaching team members from internal and emergency medicine were observed during clinical activities (216 hours), and 65 participants completed brief interviews. In Phase Two, 36 in-depth interviews were conducted using video vignettes. Data collection and analysis employed grounded theory methodology. RESULTS: Supervisors' assessments of trainee trustworthiness for independent clinical work involved consideration of four dimensions: knowledge/skill, discernment of limitations, truthfulness, and conscientiousness. Supervisors' reliance on language cues as a source of trustworthiness data was revealed. CONCLUSIONS: This study provides an initial exploration of context-specific competence assessments, which affect both patient safety and education, and provides a novel framework for study of the links between language use and competence.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".