Social marketing to address attitudes and behaviours related to preventable injuries in British Columbia, Canada
Bibliographic record
Abstract
Background Social marketing is a tool used in the domain of public health for prevention and public education. Because injury prevention is a priority public health issue in British Columbia, Canada, a 3-year consultation was undertaken to understand public attitudes towards preventable injuries and mount a province-wide social marketing campaign aimed at adults aged 25–55 years. Methods Public response to the campaign was assessed through an online survey administered to a regionally representative sample of adults within the target age group between 1 and 4 times per year on an ongoing basis since campaign launch. A linear regression model was applied to a subset of this data (n=5186 respondents) to test the association between exposure to the Preventable campaign and scores on perceived preventability of injuries as well as conscious forethought applied to injury-related behaviours. Results Campaign exposure was significant in both models (preventability: β=0.27, 95% CI 0.20 to 0.35; conscious thought: β=0.24, 95% CI 0.13 to 0.35), as was parental status (preventability: β=0.12, 95% CI 0.03 to 0.21; conscious thought: β=0.18, 95% CI 0.06 to 0.30). Exposure to the more recent campaign slogan was predictive of 0.47 higher score on conscious thought (95% CI 0.27 to 0.66). Discussion This study provides some evidence that the Preventable approach is having positive effect on attitudes and behaviours related to preventable injuries in the target population. Future work will seek to compare these data to other jurisdictions as the Preventable social marketing campaign expands to other parts of Canada.
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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 | 0.001 | 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) | 0.002 | 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 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".