Point‐of‐Care Ultrasound in Undergraduate Urology Education: A Prospective Control‐Intervention Study
Bibliographic record
Abstract
OBJECTIVES: The effect of point-of-care ultrasound (US) training on clinical reasoning in undergraduate medical education remains largely unknown, with concerns arising about possible confusion among learners when such clinical tools are introduced too early. We studied the effect of a urology point-of-care US module on the performance of questions designed to assess clinical reasoning in urinary tract obstruction and voiding dysfunction. METHODS: All second-year medical students at the University of Saskatchewan (Regina [n = 36] and Saskatoon [n = 61]) were enrolled in the study. Each cohort participated in the urology point-of-care US module concurrently with its Foundations in the Kidney and Urinary Tract course. The Regina cohort completed the point-of-care US module 1 week before the Saskatoon cohort, thus allowing for a control-intervention comparison of script concordance question scores to evaluate the effect that the urology point-of-care US module had on clinical reasoning skills. Secondary outcomes included program evaluation metrics, such as overall course performance, urology point-of-care US objective structured clinical examination performance, and student course evaluation data. RESULTS: The introduction of the urology point-of-care US module was not associated with a deterioration in scores on script concordance questions. There were no statistically significant differences between the Regina and Saskatoon students in their responses to the script concordance questions. There were statistically significant increases in student self-reported achievement of learning objectives, with the effect size being medium to large (Cohen d, 0.5-0.8). CONCLUSIONS: Point-of-care US training complements standard undergraduate classroom teaching of urology. Students effectively learned the skills to apply point-of-care US in their assessment of patients, and this process did not interfere with achieving the course objectives.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".