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To assess the relative noticeability of the following added-sugar menu label elements using a factorial experiment: label type (icon-only vs. icon-plus-text label vs. boxed icon), color (black vs. red), size (100% vs. 150% of the height of the menu item text), and placement (left vs. right side of item).
Full description
The objective of this aim is to assess the relative noticeability of legally-viable added-sugar menu label characteristics. The investigators will use a between-subject experiment with a factorial design. Participants will be randomized to label type (icon-only vs. icon-plus-text label vs. boxed icon), color (black vs. red), size (100% vs. 150% of the height of the menu item text), and placement (left vs. right side of item). This results in 24 arms of the experiment.
The primary outcomes are noticing a nutrition label and recognition of the label. Secondary outcomes are knowledge of items that are high in added sugar and perceived message effectiveness (PME) of labels.
For dichotomous outcomes (e.g., noticing the label, recalling label meaning), the investigators will directly estimate the probability ratio using Poisson regression with a robust error variance, regressing the outcome on an indicator for the level of the factor. For continuous outcomes (e.g., knowledge, PME scale), the investigators will use linear regression models regressing the outcome on an indicator for experimental condition.
A critical alpha 0.05 will be used, and statistical tests will be two-tailed. Exploratory outcomes include selection of ≥1 item high in added sugar and grams of sugar ordered from each menu, analyzed using the methods described above. The investigators will also explore proportions or means for the following process measures about reactions to the warning labels: Perception that the labels grabbed attention and support for an added sugars warning label policy. Additionally, the investigators will explore differences in the primary outcomes between each of the 24 unique conditions. If there is evidence of interactions between label elements, investigators will modify the modeling approach to account for those interactions (e.g., using interaction terms and stratified models).The investigators will use multiple testing corrections for families of outcomes (primary and secondary).
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4,581 participants in 24 patient groups
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Brittany Lemmon, MS
Data sourced from clinicaltrials.gov
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