Missing the mark: Current practices in teaching the male urogenital examination to Canadian undergraduate medical students
Bibliographic record
Abstract
INTRODUCTION: The urogenital physical examination is an important aspect of patient encounters in various clinical settings. Introductory clinical skills sessions are intended to provide support and alleviate students' anxiety when learning this sensitive exam. The techniques each Canadian medical school uses to guide their students through the initial urogenital examination has not been previously reported. METHODS: This study surveyed pre-clerkship clinical skills program directors at the main campus of English-speaking Canadian medical schools regarding the curriculum they use to teach the urogenital examination. RESULTS: A response rate of 100% was achieved, providing information on resources and faculty available to students, as well as the manner in which students were evaluated. Surprisingly, over one-third of the Canadian medical schools surveyed failed to provide a setting in which students perform a urogenital examination on a patient in their pre-clinical years. Additionally, there was no formal evaluation of this skill set reported by almost 50% of Canadian medical schools prior to clinical training years. CONCLUSIONS: To ensure medical students are confident and accurate in performing a urogenital examination, it is vital they be provided the proper resources, teaching, and training. As we progress towards a competency-based curriculum, it is essential that increased focus be placed on patient encounters in undergraduate training. Further research to quantify students' exposure to the urogenital examination during clinical years would be of interest. Without this commitment by Canadian medical schools, we are doing a disservice not only to the medical students, but also to our patient population.
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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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".