Using big data to explore the links of self-monitoring and decision making with nutrition and hydration behaviour

Lead Research Organisation: University of Warwick
Department Name: The Warwick Manufacturing Group


The precise scope of this project is yet to be finalised. However, it will have a primary focus on determining factors that affect eating and drinking behaviour within community settings (such as the workplace). Taking a behavioural sciences perspective, the initial aim will be to systematically review current literature, as well as potentially helpful motivation and decision making theories. From this review, a testable model will be developed and the hypotheses will be finalised. The research is likely to involve experimental and other quantitative methodologies. The outputs will contribute to the development of skills training programmes and interventions, which are likely to be digitally delivered.


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Gandhi N (2023) Computational Analysis of Superfood Representations in News Media in Journal of Food Products Marketing

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509796/1 30/09/2016 29/09/2021
1939178 Studentship EP/N509796/1 01/10/2017 30/07/2021 Natasha Gandhi
Description Our research has enabled us to successfully predict how the general public and nutritional experts judge the healthiness of nearly any food item. We can also successfully predict the impact of different nutrient labelling formats, commonly seen on the front of food packaging, on these healthiness judgments. Using a bottom-up approach, we found that people use associations with the concept of naturalness as a cue for food healthiness. Our results showed that these associations with food names play an important role in people's judgments of food healthiness, often more so than the nutritional composition of the food. This was the case even for registered dietitians, and when calorie labelling and monochrome key nutrient labelling was presented to participants. It was only when the traffic light label was shown that nutrient content was a better predictor, providing support for traffic light labelling as an effective intervention. Overall, this highlights that even in the presence of interventions aimed at aiding individuals to choose healthier options, food associations continue to exert a strong effect on people's judgments. Nutritional labelling neither substitutes for nor corrects for the strong effect of the associations that people rely on when deciding how healthy a food item is. As such, these results show a new area where interventions could be targeted to improve people's judgments and choices of healthy foods.
Exploitation Route Our research provides the foundations of an easily accessible tool that can be built upon and extended to evaluate the effectiveness of different interventions on food packaging aimed at helping the public make healthier food choices.
Sectors Agriculture

Food and Drink