Predicting parents' use of booster seats
Bibliographic record
Abstract
OBJECTIVE: To examine the simultaneous contribution of multiple factors associated with parents' use of booster seats. METHODS: Using the theory of planned behaviour framework, constructs of the theory were tested for usefulness in predicting self-reported intent and behaviour with respect to parents' use of booster seats. Through the use of structural equation modelling, the study demonstrated the most significant predictors of the intent to use a booster seat and reported use of booster seats in a Canadian sample (n=1480) of parents of school-aged children, 4-9 years. RESULTS: The strongest predictors of intent to use booster seats were attitudes (benefits of booster seat use) and second, subjective norms (perceived booster seat use in the community). Parent barriers were inversely associated with intent and use of booster seats and child barriers with use. Intent and norms had the greatest effect on use, both positive and equally influential. The final model explains 30% of the variance in booster seat use. CONCLUSION: Messages that address the benefit to the child in preventing injury could be beneficial if spread more diversely, establishing a social norm. Legislation, enforcement and local policy could positively influence the perceived culture that supports and expects booster seat use for school-aged children.
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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 | 0.000 | 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) | 0.001 | 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 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".