928 Development and validation of a survey on fathers’ attitudes towards child injury prevention
Bibliographic record
Abstract
Background The purpose of this study was to develop and validate a survey instrument to measure fathers’ attitudes regarding injury prevention for their children. Parents play an important role in reducing child injury risk; however, our understanding of the unique role that fathers play in keeping children safe is limited. Our previous research indicated that fathers believed risk played an important role in their children’s development and that they aimed to balance these risks with protecting children from injury. Methods We developed a survey to measure two main dimensions of fathers’ parenting attitudes: child protection from injury (16 items) and child risk engagement (24 items). The survey content was created using a 4-step process utilising expert feedback, cognitive interviews with fathers and pilot-testing. The survey was administered to fathers of children ages 6–12 years visiting the Emergency Department of a children’s hospital in British Columbia, Canada. We used confirmatory factor analysis to validate the factor structure of the questionnaire. Results There were 302 fathers who completed the questionnaire, with 45% children attending hospital for an injury and 55% for another medical concern. Following analysis, the child protection from injury factor was found to consist of eight items (Cronbach’s alpha of 0.75) and the child risk engagement factor consisted of six items (Cronbach’s alpha of 0.77). Correlation between the factors was low suggesting the dimensions are independent. Conclusions These survey data provide support for the idea that for fathers, child protection from injury and child risk engagement reflect distinct attitudinal dimensions. These results add to our understanding of fathers’ conceptions related to child safety and offer direction for development of injury prevention messages and interventions that are tailored to fathers’ perspectives and experiences.
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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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".