Testing Alcohol Container Warning Labels Among Alcohol Consumers in the Field Over a 4-Week Period: A Protocol for a Randomized Field Trial
Bibliographic record
Abstract
OBJECTIVE: Online and lab-based experiments examining the impact of alcohol labels typically test a one-time exposure to labels and assess short-term, nonbehavioral outcomes. These studies do not simulate a real-world label dose or assess actual alcohol use. This pilot aimed to develop a new protocol for testing alcohol labels that better reflects real-world exposure by presenting labels on consumers' own alcohol products over time and assessing effects on several outcomes, including alcohol use. METHOD: Forty alcohol consumers in Canada completed an online baseline survey, were randomized to one of two label conditions (Control: recycle label; Intervention: cancer warning label), mailed labels according to their assigned condition, and asked to affix one label to all alcohol containers in their home over the 29 days in February 2024. Online surveys assessed label effects at three follow-up points, and Short Message Service (SMS) texts were used to promote protocol adherence. RESULTS: The protocol had high adherence and retention, with no differences between conditions. Survey response rates remained high at follow-ups, ranging between 80% and 100%. All participants (100%) said they were satisfied with the study, and 94% would recommend it to a friend. Preliminary label effectiveness results were promising--between baseline and Day 29, the mean number of standard drinks consumed in the past 7 days decreased in the intervention condition by 4.2 standard drinks (45%) and in the control by 0.3 standard drinks (3%). CONCLUSIONS: Findings suggest this proof-of-principle protocol affixing labels on consumers' own alcohol products offers the potential for greater experimental control and real-world label dose than online or lab-based experiments.
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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 | 0.004 |
| 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".