Christopher D. Chambers
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Articles (10)
Year:
2023
Year:
2022
Studies of food-related behaviours often involve measuring responses to pictorial stimuli of foods. Creating these can be burdensome, requiring a significant commitment of time, and with sharing of images for future research constrained by legal copyright restrictions. The Restrain Food Database is an open-source database of 626 images of foods that are categorized as those people could eat more or less of as part of a healthy diet. This paper describes the database and details how to navigate it using our purpose-built R Shiny tool and a pre-registered online validation of a sample of images. A total of 2150 participants provided appetitive ratings, perceptions of nutritional content and ratings of image quality for images from the database. We found support for differences between Food Category on appetitive ratings which were also moderated by state hunger ratings. Findings relating to individual differences in appetite ratings as well as differences between BMI weight categories are also reported. Our findings validate the food categorization in the Restrain Food Database and provide descriptive information for individual images within this investigation. This database should ease the burden of selecting and creating appropriate images for future studies.
Year:
2022
Year:
2022
Year:
2021
Year:
2020
Year:
2020
Year:
2020
Year:
2020
Year:
2020
Collaborators (5)
Andrew Jones
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Anne Cooke
Chief Executive
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Roni Tibon
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Katherine Button
University of Bath
Chris Allen
Durham University
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