Managing injury risks for children with disabilities and chronic health conditions: parent perspectives
Bibliographic record
Abstract
Introduction Research indicates a higher risk of injury for children with certain types of disabilities and chronic health conditions. Parents play a large role in mitigating childhood injury risks, yet there has been little research examining how injury risks related to children's disabilities or chronic conditions are perceived and managed by parents. Purpose To investigate the injury prevention attitudes and practices of parents who have a child with a disability or chronic health condition. Method Qualitative semi-structured interviews were conducted with parents of children 1–5 years in British Columbia, Canada. Questions addressed parents' safety concerns, use of prevention strategies, impact of children's health challenges on safety efforts, and factors supporting or undermining parents' efforts. Grounded theory methods guided data analysis. Results Parents of children with a range of disabilities and chronic conditions were interviewed. Some reported concerns and safety strategies specific to certain conditions. For example, concerns related to running away were expressed by parents of children with autism. Other concerns and strategies were uniform across health issues, for example, making arrangements for safe childcare appropriate to children's special needs. Both active supervision and environmental modifications were highlighted as important strategies for injury prevention. Conclusion These results provide new information regarding injury prevention concerns, experiences and needs of families who have children with disabilities and chronic conditions. Parents' perspectives are invaluable for enhancing practitioner awareness about injury prevention issues and are important to consider in the design of child injury prevention programs.
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 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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".