The aim of this study is to compare responses to 6 different types of labels for restaurant menus: 1) a QR code on all items (control); 2) High Climate Impact label; 3) High Climate Impact Warning label; 4) Climate Grade label; 5) Climate Grade label also displaying full range of possible grades; 6) Estimated Environmental Cost label. Participants will be randomized to 1 of these 6 labeling arms. Each participant will view a menu based on a real-world restaurant with one of the 6 labels shown on applicable menu items, select the menu item they would like, and then respond to survey questions about each label.
This is an online randomized controlled trial in which researchers will use a survey company to recruit participants to an online survey. In the study, participants will be randomized to 1 of 6 labeling arms: 1) a QR code on all items (control); 2) High Climate Impact label; 3) High Climate Impact Warning label; 4) Climate Grade label; 5) Climate Grade label also displaying full range of possible grades; 6) Estimated Environmental Cost label. Labels will only appear alongside main menu items and will be assigned using thresholds for greenhouse gas emissions set a priori in kilograms of CO2 equivalent per kilogram of food. Each participant will view a menu based on a real-world restaurant with one of the 6 labels shown on applicable menu items, select the menu item they would like, then respond to survey questions about each label.
For dichotomous outcomes, the investigators will directly estimate the probability ratio using Poisson regression with a robust error variance, regressing the outcome on indicators for experimental condition. For continuous outcomes, the investigators will use linear regression models, regressing the outcome on indicators for experimental condition. A critical alpha 0.05 will be used, and statistical tests will be two-tailed. Investigators will compare all experimental label conditions to the control label, then compare each experimental label to each other using pairwise comparisons.
