University of California, Davis
Davis, California, 95616, United States
NCT Number: NCT04637412
This study aims to develop a restaurant menu label to indicate foods and beverage items on restaurant menus that contain high amounts of added sugars and to test its perceived effectiveness.
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Notify Me18 year and older
All sexes
Interventional
Not applicable
Davis, California, 95616, United States
Objectives and hypotheses:
The goal of this study is to examine how added sugar restaurant menu labels influence U.S. adults' perceptions and reactions. Predictions:
In a between-subjects experiment with 3 arms (control label, icon-only added sugars label, and icon plus text added sugars label):
Additionally, using a within-subjects design:
The study will examine which label (control, icon, text plus icon) most discourages wanting to consume menu items high in added sugars.
Analyses will compare various icon and text options for the added sugars label to determine which icon and which text variations are perceived as most discouraging for wanting to consume items high in added sugars. The is no hypothesis about which will be perceived as more discouraging.
Planned analyses:
For predictions 1-2: linear regression model (OLS) regressing PME on indicator variables for experimental condition. The margins command in STATA will be used to conduct pairwise comparisons between each condition (i.e., icon-only vs. icon plus text label). Also, PME will be regressed on an indicator variable combining the added sugar label groups.
For predictions 3-4, Poisson regression with robust standard errors will be used to estimate relative probability, regressing each dichotomous outcome on indicator variables for experimental condition. The margins command in STATA will be used to conduct pairwise comparisons between each condition. The outcomes will be regressed on an indicator variable combining the added sugar label groups. If the Poisson regressions do not converge, logistic regression will be used.
For the within-subjects comparisons, mixed effects linear models will be used to assess the relationship between condition and rating of label discouragement for consuming items high in added sugars.
A critical alpha 0.05 will be used, and statistical tests will be two-tailed. Because this is an initial, exploratory study to help identify the best performing label to use in a larger trial, alpha level will not be adjusted to control for multiple comparisons.
If there is evidence of deviations from modeling assumptions required for the parametric tests above, non-parametric sensitivity analyses will be conducted.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Participants will be shown a sample of items from a restaurant menu, displayed with labels
Time frame: Up to approximately 5 minutes
Measured using 3 items adapted from Baig et al. (2018): scale 1-5, "This label makes me concerned about the health effects of consuming menu items high in added sugars", "This label makes consuming menu items high in added sugars seem unpleasant", "This label discourages me from wanting to consume menu items high in added sugars." This outcome is for the between-subjects experiment.
Time frame: Up to approximately 7 minutes
Based on a single item adapted from Baig et al. (2018): "This label discourages me from wanting to consume menu items high in added sugar" (scale 1-5). This outcome is the within-subjects objectives.
Time frame: Up to approximately 1 minute
Dichotomous response (yes/no) to the question, "Did you learn something new from this label?" This outcome is for the between-subjects experiment.
Time frame: Up to approximately 2 minutes
"Now please look at the menu items below, and select all the ones you think have more than half the daily value for added sugars" with 8 possible responses. A dichotomous outcome variable based on the distribution of correct answers in the sample will be created. This outcome is for the between-subjects experiment.
University of California, Davis
Other
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