Disaster Awareness and Preparedness Among Older Adults in Canada Regarding Floods, Wildfires, and Earthquakes
Bibliographic record
Abstract
Abstract Older adults are significantly impacted by natural hazards and disasters that are exacerbated by climate change. Understanding their awareness and preparedness is essential for enhancing disaster resilience. This study investigated the attitudes, actions, and recommendations of older adults regarding natural hazards that pose risks in their geographic area—specifically floods, wildfires, and/or earthquakes in Canada. Methods for this study included survey and focus groups with older adults (n = 161 and n = 10, respectively) and other high-risk groups from across Canada, that are vulnerable to these natural hazards. The main findings from this study are that current awareness and preparedness among older adults is low, though stronger perceptions of risks are associated with risks specific to geographic locations where respondents live. Several barriers, such as hazard vulnerability misperceptions, cost-related reasons, and lack of hazard awareness have resulted in low awareness and preparedness among these populations. The two main recommendations arising from this research are: (1) improve awareness and preparedness with tailor-made emergency preparedness materials for older adults; and (2) adopt community-based approaches to disaster preparedness through existing community groups to strengthen social connections with a focus on locally specific hazards. The findings from this research can be applied to other hazards, including heatwaves and pandemics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".