Assessing fathers' attitudes towards protecting children from injuries and engaging in physical risks
Bibliographic record
Abstract
Background While most child injury prevention research has focused on mothers, research suggests fathers also play an important role. In a recent study, fathers described how they constantly balanced efforts to expose their children to new and potentially risky situations with needs to protect children from injury. Aim To develop and validate an instrument that measures fathers' attitudes and practices towards promoting risk engagement for their children and towards protective strategies to reduce injury risk. Methods We developed a survey instrument for testing with 300 fathers of children ages 6–12 years accessing services at a Canadian paediatric hospital. Survey items were developed using findings from past qualitative research with fathers, and existing literature. Content validity assessment was completed using expert opinion and cognitive interviews with fathers. The full sample consists of fathers with children attending hospital due to injury as well as non-injury reasons. Results Survey development included opinion from three content experts and cognitive interviews with five fathers. Items include fathers' attitudes and practices related to protecting children from injuries and children's engagement with risky, physical activities. Questions also address child injury history and fathers' perceptions of their role and level of involvement. Results will be compared and reported for the injured and the non-injured groups. Contribution Understanding fathers' attitudes towards child risk and safety is important for designing prevention messages that fit with their views on parenting. Potential uses for the instrument for further research and injury prevention practice will be discussed.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".