The impact of climate change related extreme weather events on people with pre-existing disabilities and chronic conditions: a scoping review
Bibliographic record
Abstract
PURPOSE: People with disabilities experience a disproportionate impact of extreme weather events and there is a critical need to better understand the impact that climate change has for them. Most previous reviews focus on the risk of acquiring a new disability or injury after a climate-related event and not the impact on people with pre-existing disabilities or chronic conditions, which is the purpose of this study. METHODS: We conducted a scoping review while searching seven international databases that identified 45 studies meeting our inclusion criteria. RESULTS: The studies included in our review involved 2 337 199 participants with pre-existing disabilities and chronic conditions across 13 countries over a 20-year period. The findings demonstrated the following trends: (1) the impact on physical and mental health; (2) the impact on education and work; (3) barriers to accessing health and community services (i.e., lack of access to services, lack of knowledge about people with disabilities, communication challenges, lack of adequate housing); and (4) coping strategies (i.e., social supports and connecting to resources) and resilience. CONCLUSIONS: Our findings highlight the critical need for rehabilitation clinicians and other service providers to explore opportunities to support their clients in preparing for climate-related emergencies.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".