Planetary Health in Health Guidelines and Health Technology Assessments: A Scoping Review
Bibliographic record
Abstract
ABSTRACT Introduction Individual human health is inextricably linked to planetary health, which refers to the health of human civilization and the natural systems on which it depends. These systems are captured by the nine planetary boundaries which together define a safe operating space for humanity. The health sector contributes to the transgression of these boundaries, thereby jeopardizing both individual and planetary health. However, there is a growing interest in the health sector in incorporating the preservation of planetary boundaries into health guidelines and health technology assessments (HTAs), which synthesize evidence and guide healthcare decisions. Methods This scoping review aims to describe methodological guidance and considerations for incorporating planetary health in health guidelines and HTAs. We conducted a scoping review adhering to the JBI methodology including articles from several databases since inception until September 2023. We used narrative synthesis and descriptive statistics to describe eligible studies. Results Of the 38 included studies, 14 (37%) were commentaries, six (16%) were methodological papers, and four (10·5%) were health guidelines. Included studies focused primarily on greenhouse gas emissions as an outcome. The included health guidelines were rated at a median of 52% (range: 16% to 67%) on AGREE II for methodological quality. Discussion Key findings pertain to the normative significance of planetary health in guidelines and HTAs, scope and quality of included studies, inconsistencies in methods, and challenges in implementation. These findings will inform future Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) guidance on planetary health. Registration A protocol of this scoping review was registered in Open Science Framework ( https://osf.io/3jmsa ) and published in the journal Systematic Reviews (10.1186/s13643‐024‐02577‐2).
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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 | 0.019 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".