Emergency and disaster preparedness among children and youth with disabilities and chronic conditions, their caregivers and service providers: a scoping review
Bibliographic record
Abstract
PURPOSE: People with disabilities, especially children and youth, are often not considered in emergency and disaster preparedness planning, which leaves them vulnerable and at a higher risk of the negative effects of natural and human caused disasters. The purpose of this study was to understand the extent of emergency and disaster preparedness and factors influencing preparedness among children and youth with disabilities and chronic conditions, their caregivers and service providers. METHODS: Our scoping review involved searching six international databases that identified 1146 studies of which 27 met our inclusion criteria. RESULTS: The studies in this review involved 2613 participants (i.e., children, parents, educators and clinicians) across nine countries over a 20-year period. Our results highlighted the following trends: (1) the extent of emergency preparedness; (2) factors affecting emergency preparedness; and (3) interventions to enhance preparedness. CONCLUSIONS: Our findings underscore the critical need for more attention to emergency preparedness for children and youth with disabilities, their families and service providers and their inclusion in planning.
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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".