100 Establishing the effectiveness of a storybook for teaching home safety to preschool children
Bibliographic record
Abstract
Statement of Purpose Unintentional injuries are a serious concern for young children, frequently resulting in disability and death. Safety interventions that target the child as an agent of change are needed, particularly because parents cannot constantly supervise. The present study examined whether a storybook can educate about home hazards and reduce the hazard-directed risk behaviours of children aged 3.5 to 5.5 years. Methods Preschoolers were randomly assigned to the control condition (a storybook about healthy eating) or the intervention condition (a storybook about home hazards) and were required to read the assigned storybook with their mother for four weeks. Results Comparing children’s pre- and post-intervention knowledge and risk behaviours indicated that children in the intervention condition were able to identify more hazards, provide more comprehensive explanations, and demonstrate less risky behaviours, in comparison to those in the control group. Hence, the storybook improved both safety knowledge and behaviors. Conclusion Together, the findings suggest that a storybook can be an effective resource in educating young children about home safety and promoting safety practices that are likely to reduce risk of injury. Significance The findings indicate that engaging children in reading a storybook about home hazards with their parents can not only increase their knowledge but also reduce their hazard-directed risk behaviors at home.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".