Pan American climate resilient health systems: a training course for health professionals
Bibliographic record
Abstract
Objectives: To describe the development, implementation, and results of a training course designed to equip health professionals from the Pan American Health Organization region with the knowledge and tools needed to adapt health systems to current climate realities. Methods: course was a 9-week live-virtual course in March-April 2023, which was delivered through Zoom and offered in English, Spanish, and French. All lectures were delivered by local and regional climate and health experts. The curricular foundation of this initiative was the Global Consortium on Climate and Health Education core competencies for health professionals. Participants completed pre- and post-course surveys. Results: A total of 1212 participants attended at least one of the nine sessions and 489 (from 66 countries) attended at least six sessions. Of these, 291 participants completed both the pre- and post-course surveys which were used in the analysis. Longitudinal survey results suggested an improvement in participants' climate and health communication, an increased frequency of incorporating climate knowledge in professional practice, and improved confidence in engaging in climate initiatives. At the same time, many participants expressed a need for additional training. Conclusions: The results indicate that live-virtual courses have the potential to empower health professionals to contribute to climate resilience efforts by: increasing their communication skills; changing their professional practice; increasing their ability to lead climate and health activities; and preparing them to assess vulnerability and adaptation in health systems, measure and monitor environmental sustainability, and apply a health equity lens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".