Personal and Professional Development in Undergraduate Health Sciences Education
Bibliographic record
Abstract
During the last decade, ''medical professionalism'' has been scrutinized as a consequence of pressures from within and outside the health sciences professions. In response, professional organizations have reviewed ethical principles and developed explicit guidelines for the behavior of their members. Medical educators have revised undergraduate curricula with a view to supporting the development and maintenance of these essential professional behaviors. This article outlines perspectives on professionalism before describing the evolution of personal and professional development curricula in undergraduate health science education. While the bulk of data on personal and professional development in the health sciences has come from human medicine, the principles are being recognized as applying to the breadth of the health professions. In the veterinary profession, the dyad of the physician-patient relationship of human medicine is expanded to the triad of the veterinarian-patient-client relationship, and this brings with it an added set of professional relationships and responsibilities. In order to be faithful to the primary literature and not expand beyond the various authors' data and conclusions, this article is presented principally in the terms of human medical education. For those in veterinary education, it is hoped that the inferences and applications will be readily apparent. In this article, challenges associated with defining content and educational methods are outlined, as well as selection criteria for medical school and promoting the value of PPD to students. Approaches to assessment, implementation, and evaluation of PPD curricula are also discussed. Two case studies are presented. The article concludes with suggestions for curriculum development.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".