Designing Tailored Messages about Smoking and Breast Cancer: A Focus Group Study with Youth
Bibliographic record
Abstract
The purpose of this study was to design an approach to supporting the development of gender- and Aboriginal-specific messages regarding the link between tobacco exposure and breast cancer, drawing on youth perspectives. Focus groups were held with 18 girls (8 First Nations and Métis) and 25 boys (12 First Nations and Métis) to solicit advice in the design of messages. Transcribed data were analyzed for themes. Girls preferred messages that included the use of novel images, a personal story of breast cancer, and ways to avoid secondhand smoke. Boys endorsed messages that were "catchy" but not "cheesy" and had masculine themes. First Nations and Métis participants confirmed the use of Aboriginal symbols in messages as signalling their relevance to youth in their communities. The results can be used as a guide in developing tailored health promotion messages. Challenges in developing gender-appropriate messages for youth are described.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".