Perceptions About Alcohol Harm and Alcohol-control Strategies Among People With High Risk of Alcohol Consumption in Alberta, Canada and Queensland, Australia
Bibliographic record
Abstract
OBJECTIVES: To explore alcohol perceptions and their association hazardous alcohol use in the populations of Alberta, Canada and Queensland, Australia. METHODS: Data from 2500 participants of the 2013 Alberta Survey and the 2013 Queensland Social Survey was analyzed. Regression analyses were used to explore the association between alcohol perceptions and its association with hazardous alcohol use. RESULTS: Greater hazardous alcohol use was found in Queenslanders than Albertans (p<0.001). Overall, people with hazardous alcohol were less likely to believe that alcohol use contributes to health problems (odds ratio [OR], 0.46; 95% confidence interval [CI], 0.27 to 0.78; p<0.01) and to a higher risk of injuries (OR, 0.54; 95% CI, 0.33 to 0.90; p<0.05). Albertans with hazardous alcohol use were less likely to believe that alcohol contributes to health problems (OR, 0.48; 95% CI, 0.26 to 0.92; p<0.05) and were also less likely to choose a highly effective strategy as the best way for the government to reduce alcohol problems (OR, 0.63; 95% CI, 0.43 to 0.91; p=0.01). Queenslanders with hazardous alcohol use were less likely to believe that alcohol was a major contributor to injury (OR, 0.39; 95% CI, 0.20 to 0.77; p<0.01). CONCLUSIONS: Our results suggest that people with hazardous alcohol use tend to underestimate the negative effect of alcohol consumption on health and its contribution to injuries. In addition, Albertans with hazardous alcohol use were less in favor of strategies considered highly effective to reduce alcohol harm, probably because they perceive them as a potential threat to their own alcohol consumption. These findings represent valuable sources of information for local health authorities and policymakers when designing suitable strategies to target alcohol-related problems.
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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) | 0.001 | 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) | 0.000 | 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".