Comparison of risk engagement and protection survey (REPS) among mothers and fathers of children aged 6-12 years
Bibliographic record
Abstract
BACKGROUND: Parental attitudes regarding child safety and risk engagement play important roles in child injury prevention and health promotion efforts. Few studies have compared mothers' and fathers' attitudes on these topics. This study used the risk engagement and protection survey (REPS) previously validated with fathers to compare with data collected from mothers. METHODS: Multi-group confirmatory factor analysis was used with a sample of 234 mothers and 282 fathers. Eligible parents had a child 6-12 years attending a paediatric hospital for an injury-related or other reason. We tested the factor structure of the survey by examining configural, metric and scalar invariance. Following this, mothers' and fathers' mean scores on the two identified factors of child injury protection and risk engagement were compared. RESULTS: Comparing mothers' and fathers' data showed the two-factor structure of the REPS held for the mothers' data. Comparing mean scores for the two factors suggested that fathers and mothers held equivalent attitudes. For the combined sample, parent injury protection attitude scores were significantly higher for daughters versus sons. In addition, attitude scores were significantly lower for injury protection and higher for risk engagement among parents born in Canada compared with those who were not. CONCLUSIONS: The REPS allows for valid assessment of injury protection and risk engagement factors for fathers and mothers. Mothers conceptualised the two factors as distinct concepts, similar to fathers. The REPS can be used to inform parenting programme development, implementation and evaluation.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".