International Planetary Health Education in Undergraduate and Graduate Medical Curricula: A Scoping Review
Bibliographic record
Abstract
Background Climate change is a public health emergency, yet planetary health education is absent for many medical and health professions trainees. Objective To perform a scoping review exploring the inclusion of planetary health in undergraduate and graduate medical education. Methods A search strategy was developed with a health sciences librarian and run on 6 databases from their inception to February 2022: MEDLINE, Embase, APA PsycInfo, CINAHL, Global Health, and Scopus. The Arksey and O’Malley framework was employed to broadly select publications that described the implementation of planetary health in undergraduate and postgraduate medical education. Commentaries were included if they outlined a potential curriculum. Extracted data was grouped thematically using an iterative approach based on competencies described, key considerations, and anticipated barriers. Results After screening 2407 articles, 42 were included. Thirty articles involved medical education at undergraduate or postgraduate levels, while 10 discussed multidisciplinary education including veterinary medicine, public health, and nursing. Two articles discussed planetary heath education for staff physicians. Reported competencies included eco-medical literacy, environmental inequity, and planetary health advocacy. Key considerations for curricular development included longitudinal implementation, interprofessional collaboration, and experiential learning through quality improvement projects. Barriers to implementation included time constraints and the lack of knowledgeable educators and administrative support for curricular change. Conclusions This scoping review outlines key recommendations and barriers to help facilitate the implementation of planetary health education in medical training.
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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 | 0.021 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.023 | 0.026 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 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".