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Computational methods for predicting and understanding food judgment
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Gandhi, Natasha, Zou, Wanling, Meyer, Caroline, Bhatia, Sudeep and Walasek, Lukasz (2022) Computational methods for predicting and understanding food judgment. Psychological Science, 33 (4). pp. 579-594. doi:10.1177/09567976211043426 ISSN 0956-7976.
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Official URL: https://doi.org/10.1177/09567976211043426
Abstract
People make subjective judgments about the healthiness of different foods every day, which in turn influence their food choices and health outcomes. Despite their importance, there are few quantitative theories about the psychological underpinnings of such judgments. This study introduces a novel computational approach that can approximate people’s knowledge representations for thousands of common foods. We use these representations to predict how both lay decision-makers (general population) and experts judge the healthiness of individual foods. We also apply our method to predict the impact of behavioral interventions such as the provision of front-of-pack nutrient and calorie information. Across multiple studies with data from 846 adults, our models achieve very high accuracy rates (r2 from 0.65 to 0.77), and significantly outperform competing models based on factual nutritional content. These results illustrate how new computational methods applied to established psychological theory can be used to better predict, understand, and influence health behavior.
| Item Type: | Journal Article | |||||||||
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| Subjects: | B Philosophy. Psychology. Religion > BH Aesthetics G Geography. Anthropology. Recreation > GT Manners and customs T Technology > TX Home economics |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | |||||||||
| Library of Congress Subject Headings (LCSH): | Food , Food adulteration and inspection, Food adulteration and inspection -- Data processing, Food -- Quality, Judgment (Aesthetics) , Food -- Labeling, Food habits | |||||||||
| Journal or Publication Title: | Psychological Science | |||||||||
| Publisher: | SAGE Publications | |||||||||
| ISSN: | 0956-7976 | |||||||||
| Official Date: | 1 April 2022 | |||||||||
| Dates: |
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| Volume: | 33 | |||||||||
| Number: | 4 | |||||||||
| Page Range: | pp. 579-594 | |||||||||
| DOI: | 10.1177/09567976211043426 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 19 August 2021 | |||||||||
| Date of first compliant Open Access: | 19 August 2021 | |||||||||
| RIOXX Funder/Project Grant: |
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