Alcohol Labeling Study
Phase: NA
Conditions: Health Behavior
Sponsor: University of North Carolina, Chapel Hill

Complete Title: Alcohol Labeling Study 
Protocol Date: April 16, 2025 
NCT #: NCT06835920 
 
Study Principal Investigators:  
Marissa G. Hall 
University of North Carolina 
email: mghall@unc.edu 
 
Anna H. Grummon  
Stanford University 
email: agrummon@stanford.edu   
 
 
  
 
 

Protocol Synopsis  
 
Study title 
Alcohol Labeling Study 
Funder 
National Institute on Alcohol Abuse and Alcoholism 
Study rationale 
• 
Policymakers and public health organizations are increasingly 
interested in communicating alcohol’s harms to the public, 
including through mandated warning labels. 
• 
Communicating alcohol’s harms through front-of-package alcohol 
health warnings could reduce alcohol consumption and alcohol-
related health harms.   
• 
Few studies have experimentally evaluated whether front-of-
package alcohol warnings change drinking behavior.  
 
Study 
objectives 
Primary  
• 
Evaluate whether front-of-package alcohol health warnings 
reduce the number of alcoholic drinks consumed per day. 
 
Secondary 
• 
Evaluate whether front-of-package alcohol health warnings affect 
other alcohol-related behaviors and inform consumers.   
Study design 
 
Randomized clinical trial 
Number of 
participants  
~720 participants. 
Study duration 
Each participant is in the trial for ~3 weeks. The trial enrollment period is 
expected to last ~24 months. 
Study phases 
  
The trial will have two phases: 
(1) Screening: screening for eligibility and obtaining consent and  
(2) Intervention: intervention/experimental treatment 
 
Study protocol 
Participants will be invited to attend 3 in-person visits, spaced ~1 week apart. Participants 
will be instructed to bring 8 days’ worth of unopened alcohol containers to each trial visit. Study 
staff will randomize participants to 1 of 2 trial arms (front-of-package health warnings or control 
labels) at the first visit. At each visit, staff will apply labels per participants’ assigned arm to the 
front of all alcohol containers. Participants will take a computer survey at each visit. Participants 
will take a final survey remotely approximately 1 week after the final in-person visit. Participants 
will answer two questions by text message each day they are in the study.  
 
Statistical analysis plan 
General principles 
Analyses will be intent-to-treat, including all participants randomized at Visit 1, except when 
noted. We will use a critical alpha of 0.05 or 95% confidence intervals, and two-tailed tests to 
conduct all statistical tests. 
 
Predictions 
We predict that front-of-package alcohol health warnings will lead to fewer drinks consumed 
per day (primary outcome), compared to the control. In terms of secondary outcomes, we 
predict that compared to the control, front-of-package alcohol health warnings will lead to 

greater intentions to limit drinking, forgoing a drink, perceived control over drinking, learning 
something new, knowledge of harms from alcohol in warnings, reminding of harms of alcohol, 
and perceived likelihood of harms from alcohol. We predict that, compared to the control, front-
of-package alcohol health warnings will lead to lower maximum number of drinks consumed in a 
day, proportion of days drinking during the study, and perceived healthfulness of alcohol.  
 
Statistical methods 
We will descriptively present demographic characteristics separately for each trial arm but 
will not test for balance, following CONSORT guidelines. Assuming sufficient internal 
consistency (Cronbach's alpha>=0.70), we will average responses to all measures with 3 or 
more items. 
All analyses will be intent-to-treat, except where noted. To examine the impact of trial arm on 
the primary outcome, we will run a mixed effects linear regression model to account for 
repeated measures across participants. This model will regress number of drinks consumed per 
day on indicators for trial day when drinking was reported (within subjects, level 1 variable, fixed 
effect), whether the trial day when drinking was reported was a weekend versus weekday 
(within subjects, level 1 variable, fixed effect), and trial arm (between subjects, level 2 variable, 
fixed effect).  Analysis will treat the intercept as random. In “per protocol” sensitivity analyses, 
we will re-run the primary outcome model among those with high adherence to the labeling 
protocol.  
We will explore whether the impact of trial arm on the primary outcome differs by the 
following participant characteristics: baseline alcohol use, baseline intentions to limit drinking, 
gender, age, and education. Using the same modeling approach as for the primary outcome and 
separate models for each moderator, we will regress number of drinks consumed per day on 
trial arm, the moderator, and interactions between trial arm and the moderator. We will report 
the statistical significance of the interaction terms. We will estimate the impact of trial arm on the 
outcome at each level of the moderator, adjusting for these post-hoc tests using a Bonferroni-
Holm correction.  
Next, we will examine the impact of trial arm on secondary outcomes. We will use mixed 
effects linear and logistic models for outcomes with repeated measures. The predictor will be 
trial arm (between subjects, level 2 variable, fixed effect); analyses will treat the intercept as 
random. We will use standard logistic and linear models for outcomes measured only once, with 
trial arm as the only predictor.  
 
Sample size needs  
To estimate sample size needs, we assumed 21 repeated daily diary measures, 2 trial arms 
of equal size, an intraclass correlation of .60, and 15% missingness for any given daily diary 
measure. Power analyses used mixed effects linear regression, with 1,000 simulations. A 
sample size of 720 people would provide >85% power to detect effect sizes of d=.18 or larger 
and >80% power to detect effect sizes of d=.17 or larger. These effect sizes are conservative 
estimates as prior studies of non-alcoholic beverages indicate effect sizes of sugary drink health 
warnings on behavior of d=.251 and d=.41.2 
 
References 
1. 
Grummon AH, Taillie LS, Golden SD, Hall MG, Ranney LM, Brewer NT. Sugar-
sweetened beverage health warnings and purchases: A randomized controlled trial. Am 
J Prev Med. 2019;57(5):601-610. 
2. 
Hall MG, Grummon AH, Higgins ICA, et al. The impact of pictorial health warnings on 
purchases of sugary drinks for children: A randomized controlled trial. PLoS Med. 2022.