OVERVIEW OF PREVENTIVE MEDICINE PHYSICIAN TRAINING: A SCOPING REVIEW
Bibliographic record
Abstract
This study aimed to provide an overview of the global status of preventive medicine physician training. A descriptive scoping review was conducted. The results show that preventive medicine physician training worldwide varies, with undergraduate programs in Russia, China and Vietnam, and postgraduate training in the U.S., Canada, France, and Italy. Common challenges include limited specialty recognition, inconsistent competencies, and unclear professional identity. In China, training is theory-heavy; in the U.S., workforce shortages and unstable funding persist; Italy shows high contract placement but some residents continue job searching. In Vietnam, the six-year undergraduate program ensures a workforce pipeline but lacks practical exposure, interdisciplinary collaboration, and modern skills such as digital health and emergency response. Recommendations include strengthening field-based and practical training; standardizing curriculum programs and certification; expanding career opportunities; ensuring stable funding; and integrating preventive medicine with clinical practice to enhance professional recognition and prepare physicians for evolving public health challenges.
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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 | 0.012 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.028 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".