Survey on the perception of urology as a specialty by medical students
Bibliographic record
Abstract
INTRODUCTION: Upon inquiring with medical students and urologists across Canada, it is evident that urology is perceived as a male-dominant specialty, among other stereotypes. These misperceptions may hamper the recruitment of the best and brightest trainees. With that in mind, we surveyed medical students at our institution to obtain an objective assessment of their perception of urology and to determine the cause for misperceptions. METHODS: A 25-factor, validated, anonymous, cross-sectional, self-reported, electronic survey was sent to all medical students at McMaster University to assess their perception of urology. The survey was piloted among students and educational leaders to optimize face and content validity, and minimize measurement bias. Six variables (years in training, role model, a family member or friend in urology, gender, and exposure) were selected a priori and entered into a logistic regression model to determine factors associated with a positive impression of the specialty. RESULTS: The overall response rate was 70%. Of the respondents, 66% had no exposure to urology and 61% found the amount of exposure to be inadequate. Urology staff and resident involvement in education was considered to be poor by over 30% of medical students. Over 70% perceived urology to be a specialty with a great gender imbalance. On multivariate analysis, exposure to urology was the most important factor (p<0.001) associated with students' positive perception of the specialty, in addition to male gender, earlier years in training, and positive role models. CONCLUSIONS: Concerns regarding inadequate urology exposure and poor staff and resident involvement in undergraduate education were seen as potential causes for misperceptions of the specialty. Increasing exposure to urology, encouraging female students, constant effort to approach senior students, and providing mentorship are found to be important factors in establishing a positive perception of urology.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".