Use as directed: do standard drink labels on alcohol containers help consumers drink (ir)responsibly? Real‐world evidence from a quasi‐experimental study in Yukon, Canada
Bibliographic record
Abstract
INTRODUCTION AND AIMS: This paper examines the impact of an alcohol labelling intervention on recall of and support for standard drink (SD) labels, estimating the number of SDs in alcohol containers, and intended and unintended use of SD labels. DESIGN AND METHODS: A quasi-experimental study was conducted in Canada where labels with a cancer warning, national drinking guidelines and SD information were applied to alcohol containers in the single liquor store in the intervention site, while usual labelling continued in the two liquor stores in the comparison site. Three waves of surveys were conducted in both sites before and at two time-points after the intervention with 2049 cohort participants. Generalised estimating equations were applied to estimate changes in all outcomes. RESULTS: Participants in the intervention relative to the comparison site had greater odds of recalling [adjusted odds ratio (AOR) 5.69, 95% confidence interval (CI) 3.02, 10.71] and supporting SD labels (AOR 1.49, 95% CI 1.04, 2.12) and lower odds of reporting using SD labels to purchase high strength, low-cost alcohol (AOR 0.65, 95% CI 0.45, 0.93). Exposure to the labels had negligible effects on accurately estimating the number of SDs (AOR 1.06, 95% CI 0.59, 1.93) and using SD labels to drink within guidelines (AOR 1.04, 95% CI 0.75, 1.46). DISCUSSION AND CONCLUSIONS: Evidence-informed labels increased support for and decreased unintended use of SD labels. Such labels can improve accuracy in estimating the number of SDs in alcohol containers and adherence to drinking guidelines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".