Plastic Surgery Inclusion in the Undergraduate Medical Curriculum: Perception, Challenges, and Career Choice—A Comparative Study
Bibliographic record
Abstract
Objective. The undergraduate medical curriculum has been overcrowded with core learning outcomes with no formal exposure to plastic surgery. The aim of this study was to compare medical students from two educational settings for the basic understanding, preferred learning method, and factors influencing a career choice in plastic surgery. Design and Setting. A prospective cohort study based on a web-based anonymous questionnaire sent to final year medical students at Birmingham University (United Kingdom), McGill University (Canada), and a control group (non-medical staff). The questions were about plastic surgery: (1) source of information and basic understanding; (2) undergraduate curriculum inclusion and preferred learning methods; (3) factors influencing a career choice. A similar questionnaire was sent to non-medical staff (control group). The data was analysed based on categorical outcomes (Chi-square χ2) and level of significance p≤0.05 . Results. Questionnaire was analysed for 243 students (Birmingham, n=171/332 , 52%) (McGill n=72/132 , 54%). Birmingham students (14%) considered the word “plastic” synonymous with “cosmetic” more than McGill students (4%, p<0.025 ). Teaching was the main source of knowledge for McGill students (39%, p<0.001 ) while Birmingham students and control group chose the media (70%, p<0.001 ). McGill students (67%) more than Birmingham (49%, p<0.010 ) considered curriculum inclusion. The preferred learning method was lectures for McGill students (61%, p<0.01 ) but an optional module for Birmingham (61%). A similar proportion (18%) from both student groups considered a career in plastic surgery. Conclusions. Medical students recognised the need for plastic surgery inclusion in the undergraduate curriculum. There was a difference for plastic surgery source of information, operations, and preferred method of learning for students. The study highlighted the urgent need to reform plastic surgery undergraduate teaching in collaboration with national educational bodies worldwide.
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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 | 0.003 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".