Who or what is to blame? Examining sociodemographic relationships to beliefs about causes, control, and responsibility for cancer and chronic disease prevention in Alberta, Canada
Bibliographic record
Abstract
BACKGROUND: Beliefs about causes and responsibility for chronic diseases can affect personal behaviour and support for healthy policies. In this research we examined relationships between socio-demographics (sex, age, education, employment, political alignment, perceived health, household income, household size) and perceptions of causes and responsibility for health behaviour, chronic disease correlates, and attitudes about cancer prevention and causes. METHODS: Using data from the 2016 Chronic Disease Prevention survey in which participants (N = 1200) from Alberta, Canada responded to items regarding how much they believed personal health behaviours, prevention beliefs, and environmental factors (i.e., healthy eating, physical activity, alcohol, smoking, and where a person lives or works) are linked to getting cancer. Participants also responded to questions about causes and responsibility for obesity, alcohol, and tobacco (i.e., individual or societal). Relationships were examined using multinomial logistic regression on socio-demographics and survey items of interest. RESULTS: Men (compared to women) were less likely to link regular exercise, or drinking excessive alcohol, to reducing or increasing cancer risk. Similarly, men were less likely to link environmental factors to cancer risk, and more likely to agree that cancer was not preventable, and that treatment is more important than prevention. Finally, men were more likely to believe that alcohol problems are an individual's fault. Left and central voters were more likely to believe that society was responsible for addressing alcohol, tobacco, and obesity problems compared to right voters. Those with less than post-secondary education were less likely to believe that regular exercise, maintaining a healthy body weight, or eating sufficient fruits and vegetables were linked to cancer - or that society should address obesity - compared to those with more education. Households making above the median income (versus below) were more likely to link a balanced diet with cancer and were less likely to think that tobacco problems were caused by external circumstances. CONCLUSIONS: These results provide insight into the importance of health literacy, message framing, and how socio-demographic factors may impact healthy policy. Men, those with less education, and those with less income are important target groups when promoting health literacy and chronic disease prevention initiatives.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".