What procedures are students doing during undergraduate surgical clerkship?
Bibliographic record
Abstract
BACKGROUND: Many North American medical schools have removed didactic surgical teaching from the nonclinical years, and there has been a trend toward shortening surgical clerkships. Of concern is that this policy has led to a decrease in surgical exposure and a diminished interest in students pursuing a surgical career. We aimed to determine the effect of curricular change on practical experiences during surgical clerkship and to evaluate overall practical clinical exposure of students during surgical clerkship. METHODS: We collected validated experience logbooks completed before (1999-2001) and after (2001-2003) the curriculum change at the University of Alberta and converted them into electronic format. The study analyzed 10 procedures and 5 patient management situations. We assessed numbers of procedures performed and student performance on the Objective Structured Clinical Exam (OSCE) and Multiple-Choice Question (MCQ) examinations before and after the curriculum change. In addition, we completed an overall survey of all 4 classes (2000, 2001, 2002, 2003), measuring clinical exposure. We reviewed a total of 428 logbooks. RESULTS: There were significant gaps in clinical exposure, which was demonstrated by more than 70% of students in each class failing to complete 8 of 15 procedures or managements at least once. No significant change in practical surgical exposure resulted from the curriculum change. The curriculum change did result in a decrease in end-of-rotation MCQ score performance, which was demonstrated by a 5% decrease in the class average after the curriculum change. Students' performance on ward evaluations and their OSCE scores were unaffected. CONCLUSION: We were encouraged that a major change in how surgical education is delivered did not have a detrimental effect on subjective and objective evaluations of student performance. However, we are concerned that a considerable number of students appeared to have not performed several inpatient procedures. Further study is warranted to determine whether this is a common problem in other schools. There is a clear need at our school, and no doubt at others, to establish skills centres and other strategies to ensure that this component of medical education is appropriately and effectively taught.
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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 | 0.001 | 0.010 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".