The Future of Nursing for Planetary Health Is Today: Essential Transitions for Education and Research
Bibliographic record
Abstract
The triple planetary crisis of climate change, pollution, and biodiversity loss has deleterious consequences for local and global public health. Nursing is among the diverse evidence-based disciplines now working to advance planetary health for all. We offer examples from nurse scholars at two academic institutions in the United States, sharing insights and best practices for integrating planetary health in nursing education and research. At both institutions, planetary health is embedded across courses and tailored to align with nursing competencies and the Planetary Health Education Framework. Students’ international exposure fosters a global perspective on health equity and environmental resilience. This curriculum transformation demonstrates a paradigm shift towards environmental and social responsibility in nursing, preparing future nurses to address complex planetary health issues. This article also explores the role of nursing research in promoting planetary health, focusing on the intersection of health inequities and environmental justice in racialized and low-income communities. Examples include Indigenous-led research to address gender-based violence and environmental exploitation, highlighting the interconnectedness of land and body sovereignty in Indigenous health. Additionally, research on the health impacts of pollution in Black communities demonstrates how environmental hazards increase chronic health issues. Nurse-led research advocates for collaborative partnerships to support public health resilience in communities overburdened by the triple planetary health crisis. The research has revealed that public health nurses require increased organizational support to promote planetary health. Our collective expertise in nursing education and research illustrates the need for nurses to serve as champions for social, environmental, and multispecies justice. We advocate for nursing school leadership to strategically incorporate planetary health resources emphasizing justice, equity, diversity, and inclusion. Institutional support is vital for planetary health education and research, and merit systems should recognize the time and effort needed to build authentic community partnerships. The article concludes with a call for nursing leadership in planetary health, emphasizing the transformative potential of nursing to advocate for and protect all forms of life.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".