Adapting to climate change: strategies and perspectives from humanitarian health workers – A qualitative study
Bibliographic record
Abstract
Introduction: Climate change is contributing to humanitarian health crises. However, research on the intersection of climate change and health in humanitarian settings often prioritises understanding impacts over identifying solutions. This study adopts a solutions-oriented approach, engaging humanitarians working in medical projects to explore both existing and potential adaptation strategies to mitigate the adverse health effects of climate change. Materials and Methods: The study involved 49 semi-structured qualitative interviews with humanitarian health workers from Médecins Sans Frontières (MSF) across 30 countries. Conducted in English, French, Spanish, Portuguese, and Arabic, the interviews focused on identifying adaptation solutions to address climate-related health impacts at individual, community, and organizational levels. Data were analysed using a hybrid coding approach, combining deductive and inductive techniques informed by framework analysis. Results and Discussion: The research highlights a perception of high vulnerability and low readiness to address climate change in the studied countries, exposing an adaptation gap-the disparity between adaptation needs and current efforts. Initially, participants found it challenging to identify adaptation strategies, often focussing on mitigation (emission reduction) rather than adaptation. From the adaptation activities identified, we developed an 'Adaptation Continuum' framework, which ranges from maladaptation to resilience-building. Additionally, we created a matrix of climate change adaptation (CCA) examples to illustrate how health risks can be addressed in contexts characterised by high vulnerability and low adaptive capacity. Conclusion: Health and humanitarian actors are witnessing the profound impacts of climate change on communities and projects worldwide. Despite ongoing efforts to adapt, there remains a lack of consensus on how to effectively operationalize these initiatives. This research introduces the 'Adaptation Continuum', a conceptual framework designed to guide the planning, implementation, and evaluation of adaptation activities in four key domains: knowledge and awareness, infrastructure and technological solutions, operational adaptation, and policy and advocacy.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".