The importance of increasing urology exposure among undergraduates: A U.K. Perspective
Bibliographic record
Abstract
I read with great interest the recent paper by Jones et al 1 detailing the attitudes towards urology as a career choice amongst medical students and foundation year trainees in the U.K. The decline in undergraduate exposure to urology is also discussed and the results of an internet-based survey involving six medical schools are presented. This study excluded graduates from non-U.K. medical schools. The authors should acknowledge that many nonU.K. graduates (of which I am one) elect to train in urology in the U.K. at a postgraduate level due to its history of specialist training, which is internationally recognized. If non-U.K. graduates, at foundation level, had been included in this survey, urology may have been a more popular career option. According to the results in Figure 1, Jones at al report that urology was the least likely speciality to be chosen by new graduates, as only 7% would most likely pursue it as a career compared to general surgery at 17%. Interestingly, ophthalmology, another specialty often underrepresented at the undergraduate level, was not offered as a future career choice. Why was this omitted? It is reassuring to see that male catheterization was assessed as an index technique, but only 21% of males surveyed either agreed (17%) or strongly agreed (4%) at being confident at the procedure. This does indicate that junior practitioners receive inadequate training in catheter management, as previous studies have shown that 76% of newly qualified doctors feel their catheter training was inadequate.2 The secondary outcomes reported are commendable. The idea of a designated workshop day was supported by 88% of respondents. A 2013 study examining out-of-hours calls to urology registrars also supported the idea of a defined urology workshop at the beginning of a core rotation for junior trainees in an effort to reduce unnecessary out-ofhours calls.3 Although 68% of respondents stated that they felt comfortable making a referral, greater than one-third did not feel confident assessing an acute urology admission.1 We again demonstrated that junior trainees (foundation and core level) are the most frequent callers seeking advice, but that the advice relayed is frequently insufficient.3 Therefore, it should be acknowledged by the authors of this study that although 68% of respondents were comfortable making a referral, this is not an objective measurement, as the opinion of the recipient has not been sought, nor the quality of the referral validated. This work does highlight the decline in exposure to urology at the undergraduate level. This problem is not limited to the U.K., nor is it a new one: in 1994 Benson commented that 15% of new graduates had never experienced an undergraduate rotation in urology.4 Medical education has evolved with simulation-based training and problem-based learning (as opposed to bedside teaching and didactic lectures) and it is unfortunate that newly qualified practitioners may never experience rotations in certain specialties. The authors state that urology workshops are not routinely incorporated into U.K. undergraduate teaching and recommend their introduction. This is an important point, as designated workshops on catheter management, basic uroradiology, clinical assessment, and result interpretation prior to starting a foundation year may help to make urology more attractive as a postgraduate surgical career.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| 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".