Untapped Potential: Performance of Procedural Skills in the Family Medicine Clerkship.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: While family medicine residency directors have expressed concern about low procedural skills proficiency among incoming residents, curricular recommendations do not provide widely accepted guidance. This study was designed to describe requirements and experiences in procedural skill training during the family medicine clerkship and test the hypothesis that more rural placements may support this training. METHODS: The survey was conducted as part of the CAFM Educational Research Alliance (CERA) Family Medicine Clerkship Director (CD) 2013 survey. All Liaison Committee on Medical Education (LCME)-accredited medical schools in the US and Canada with a family medicine educator as family medicine or primary care CD were surveyed. CDs answered questions about clerkship structure and procedure experience and requirements for students. Choosing from a list of procedures, respondents detailed how often students perform specific skills during a rotation. RESULTS: The response rate was 73% (94 out of 129). Thirty-six procedures were performed during the family medicine clerkship. Of the procedures performed at least once, the most common were Pap test (57.1%), vaginal swab (42.9%), ECG recording (41.9%), urinalysis (40.0%), and throat swab (39.0%). Of the procedures performed more than three times, the most common were Pap test (21.0%) and sterile technique (20.0%). Learners in rural rotations were more likely to perform a range of procedures. CONCLUSIONS: Though exposed to a wide range of procedures during the family medicine clerkship, students did not often repeat procedures. Creation of a core list of procedures and taking better advantage of rural placements may improve procedural skill training in the family medicine clerkship.
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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 | 0.003 | 0.019 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".