A systematic review on the impact of alcohol warning labels
Bibliographic record
Abstract
Findings on the effects of alcohol warning labels (AWLs) as a harm reduction tool have been mixed. This systematic review synthesized extant literature on the impact of AWLs on proxies of alcohol use. PsycINFO, Web of Science, PubMED, and MEDLINE databases and reference lists of eligible articles. Following PRISMA guidelines, 1,589 articles published prior to July 2020 were retrieved via database and 45 were via reference lists (961 following duplicate removal). Article titles and abstracts were screened, leaving the full text of 96 for review. The full-text review identified 77 articles meeting inclusion/exclusion criteria which are included here. Risk of bias among included studies was examined using the Evidence Project risk of bias tool. Findings fell into five categories of alcohol use proxies including knowledge/awareness, perceptions, attention, recall/recognition, attitudes/beliefs, and intentions/behavior. Real-world studies highlighted an increase in AWL awareness, alcohol-related risk perceptions (limited findings), and AWL recall/recognition post-AWL implementation; these findings have decreased over time. Conversely, findings from experimental studies were mixed. AWL content/formatting and participant sociodemographic factors also appear to influence the effectiveness of AWLs. Findings suggest conclusions differ based on the study methodology used, favoring real-world versus experimental studies. Future research should consider AWL content/formatting and participant sociodemographic factors as moderators. AWLs appear to be a promising approach for supporting more informed alcohol consumption and should be considered as one component in a comprehensive alcohol control strategy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| 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".