Evaluating the Effectiveness of an Ultraprocessed Food Warning Label in Chile
Phase: NA
Conditions: Diet, Healthy
Sponsor: University of North Carolina, Chapel Hill

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Testing Ultraprocessed Front-of-Package Labels in Chile 
NCT06293963 
April 10th, 2025 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Study Protocol and Analytic Plan 
Introduction 
This study aims to examine the effects of a warning label signaling that a product is 
ultraprocessed among a sample of Chilean parents. This document pre-specifies our 
planned analytic approach prior to data collection. 
 
Study Protocol 
Participants will complete an online randomized experiment programmed in Qualtrics. 
After providing informed consent and completing a parent study, participants will be 
randomly assigned into 1 of 2 arms: a control arm or an ultraprocessed warning label 
arm. In the control arm, products will carry only nutrient warning labels per Chile's 
current policy, while in the ultraprocessed warning label arm, products will carry both 
nutrient labels and an ultraprocessed warning label. 
Participants will see three different mock bags of potato chips with the same flavor 
(designed to mitigate confounding by product type or flavor) displayed in a random 
order. All three products will be ultraprocessed. One product will not be high in any 
nutrients of concern, one will be high in sodium, and one will be high in sodium and 
saturated fat. For each product, participants will rate their purchase intentions, 
perceived product healthfulness, and indicate whether they believe the product to be 
ultraprocessed. 
 
Hypotheses 
Correct identification of UPFs (co-primary outcome): We predict that, compared to the 
control arm, correct identification of products as UPFs will be higher among participants 
in the UPF warning label arm (H1). 
 
Purchase intentions (co-primary outcome): We predict that, compared the control arm, 
product purchase intentions will be lower among participants in the UPF warning label 
arm (H2). 
 
Perceived product healthfulness (secondary outcome): We predict that, compared the 
control arm, perceived product healthfulness will be lower among participants in the 
UPF warning label arm (H3). 
 
Moderation hypotheses: We predict that the impact of the UPF label on purchase 
intentions (H4) and perceived product healthfulness (H5) will be greater for the product 
not high in any nutrients of concern than for the products high in one or two nutrients of 
concern.  
 
 
Main Analyses 
We will use a two-sided critical alpha of 0.05 to conduct all statistical tests. All 
confidence intervals presented will use a 95% confidence level. Analyses of the primary 

and secondary outcomes will include all participants according to the trial arm to which 
they were randomized. 
For correct identification of products as UPF (dichotomous outcome), we will first 
descriptively report unadjusted proportions of correct identification for each product and 
for all three products simultaneously (i.e., whether the participant identifies all three 
products as UPFs nor not) in each experimental arm. To test H1, we will fit a logistic 
mixed-effects regression model. The model will include random intercepts to account for 
repeated measures within participants. The model will regress identification of products 
as UPFs on indicator variables for experimental arm, indicator variables for product, and 
their interactions. After model estimation, we will test the joint statistical significance of 
the interaction terms, and, if not statistically significant, we will drop the interactions from 
the models. Regardless of the presence of the interaction terms in the final model, we 
will obtain predicted probabilities of correct identification of products as UPF by 
experimental arm for each separate product, which we will use to conduct a joint test of 
statistical significance of the differences in predicted probabilities across products. If 
such differences are jointly significant, we will report the average differential effect 
(ADE) of the UPF label (i.e., differences in predicted probabilities between experimental 
arms) for each product. Alternatively, if these differences are not jointly significant, we 
will report the ADE of the UPF label across products. 
For purchase intentions and perceived healthfulness (continuous outcomes), we will first 
descriptively report unadjusted mean scores for each product and averaged across 
products in each experimental arm. To test H2 and H3, we will use linear mixed-effects 
regression models. Models will include random intercepts to account for repeated 
measures within participants. Models will regress each outcome on indicator variables 
for experimental arm, indicator variables for product, and their interactions. After model 
estimation, we will test the joint statistical significance of the interaction terms. If the 
interactions are jointly significant, we will keep them in the model and report the average 
differential effect (ADE) of the UPF label (i.e., differences in predicted means between 
experimental arms) for each product. Alternatively, if the interactions are not jointly 
significant, we will drop them from the models and report the ADE of the UPF label 
across products. We will use complete case analysis to handle any missing data. 
 
Sample Size and Power 
This study will occur in a survey that will follow a parent experiment. The total sample of 
3,300 size was calculated based on the primary outcomes of the parent study. Using 
G*Power3.1, we determined that the minimum effect size we would be able to detect 
with this pre-determined sample size. With an alpha of 0.05, 80% power, and 1 degree 
of freedom, we would be able to detect an effect of d=0.06 or larger. We concluded that 
this sample size would be enough, given that, on a previous study using similar labels, 
we found an effect size of d=0.16 on correct identification of products as UPF. 
 
Exclusions and Outliers 

We will exclude participants who complete the survey implausibly quickly (defined as 
<1/3 of the median completion time) and those who completed less than 90% of the 
survey. 
 
Interim Analyses 
No interim analyses are planned.