'Robust Evidence for Nature's Influence on Dietary Choice Decisions' (AsPredicted #88393)
Author(s) Maria Langlois (INSEAD) - langlois@smu.edu Pierre Chandon (INSEAD) - pierre.chandon@insead.edu
Pre-registered on 2022/02/17 - 01:06 PM (PT)
1) Have any data been collected for this study already? No, no data have been collected for this study yet.
2) What's the main question being asked or hypothesis being tested in this study? We expect that exposure to nature will lead to healthier food consumption intentions when compared to exposure to urban environments.
3) Describe the key dependent variable(s) specifying how they will be measured. We operationalize food choice through a hypothetical choice task in which participants will choose a drink, main course, and side dish, which are framed as a free meal offering that they would be able to consume while enjoying the view depicted in one of the 2 scenes (i.e., their randomly assigned condition of nature or urban). Respondents will have the option to choose 1 out of 4 drinks (two of which are healthy & two of which are unhealthy), 1 out of 4 side dishes (two of which are healthy & two of which are unhealthy), and 1 out of 4 main courses (two of which are healthy & two of which are unhealthy).
4) How many and which conditions will participants be assigned to? Between-subjects design (nature vs. urban) with random assignment to condition. For the nature condition, we will utilize the last of the nature photos (sunny beach view) utilized by Clarke et al., 2021. For the urban condition, we will use the second urban photo (modern building without people) utilized by Clarke et al., 2021.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. We plan on conducting analyses which compare food choices across environmental contexts using binomial logistic regressions, with an interaction between environmental context (nature vs. urban) and the healthiness of the food (as measured in an online pre-test as a continuous measure). As a robustness check, we will also conduct an interaction analysis between environmental context and an a priori categorical (binary) healthy/unhealthy coding of foods in order to ensure that results replicate regardless of how foods are rated on healthiness. Additionally, we will utilize conditional logit to account for the fact that the same individuals are making a 1 in 4 choice decision (e.g., one out of 4 drink options) on 3 occasions (for a drink, a main dish, and a side).
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. Participants will be excluded: if they indicate that they are not using an eligible device, if meta-data reveals an operating system or desktop resolution that is likely to be a cell phone/tablet (browser resolution height under 500), and if they failed the attention check (which consists of a recall question).
7) How many observations will be collected or what will determine sample size? No need to justify decision, but be precise about exactly how the number will be determined. The sample size was determined based on the effect size observed in our previous pre-registered online study, yielding 920 participants.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) We capture dieting behavior, sex, and residential environment (rural, suburban, urban) for exploratory purposes.
