Clinical Research Directory

Food Menu Labelling Effects on Individuals With Eating Disorders and Other Mental Health Conditions.

Calorie labelling in out-of-home (OOH) settings was introduced by the government in England as part of a wider strategy to 'tackle obesity' (DHSC, 2020). The OOH sector encompasses outlets where food and drinks are prepared for immediate consumption, on or off the premises (DHSC, 2021). Increased consumption of OOH food is associated with greater intake of energy and nutrients of concern; therefore, is implicated in poorer dietary quality and ill-health (Gesteiro et al., 2022). The key ambition for the calorie labelling policy was to inform consumers of the calorie content of their food choices, making it easier to select healthier food choices (DHSC, 2020). An additional potential benefit of the policy was to prompt reformulation by the food industry to either reduce the calorie content of foods on offer or provide new lower calorie options (DHSC, 2021). The calorie labelling policy in England was criticised at the time of implementation in the media for its potential to cause harm in individuals with eating disorders (Polden et al., 2023). However, limited research had explored effects on individuals with eating disorders (Robinson et al., 2023). It is estimated that over a million individuals in the UK are living with an eating disorder (Beat Eating disorders, 2026). Therefore, it is important for research to understand the impact of food labelling interventions on mental health outcomes in individuals with eating disorders and other mental health conditions, and whether alternative nutritional labelling practices that are not focused on calories alone could have positive health impacts without unintended negative consequences. One alternative form of nutritional labelling that could be considered in OOH settings is Nutri-score. Nutri-score provides food items with a label from A (dark green, healthiest) to E (Red, least healthy) according to the content of both positive (e.g. fibre, protein) and negative (e.g. saturated fat, salt, sugar) nutrients. Nutri-score has been implemented as a front-of-pack label in several countries across Europe, with positive impacts on the healthiness of food purchasing in supermarkets (Andreani et al., 2025). Two studies have assessed Nutri-score in OOH settings, also finding associations between Nutri-score and healthier food choices (Chandon \& Indaburu, 2026; Julia et al., 2021). However, Nutri-score on food menus has not previously been examined in terms of the potential impact on individuals with eating disorders and other mental health outcomes. Nutri-score encompasses the nutritional quality of a food product, by accounting for both positive and negative components. This may be less harmful to individuals with eating disorders as it would remove the focus on calorie content. Previous qualitative research has shown that individuals with eating disorders may support labelling strategies that provide more holistic approaches to nutrition (Trompeter et al., 2026). It could also be of benefit to general population health to focus on helping individuals to consume a well-rounded diet higher in positive nutrients (fibre, protein), with high fruit, vegetable and nut content, and lower in negative nutrients that contribute to ill health (salt, sugar, fats). To date, limited research has compared Calorie labelling to Nutri-score in the general population or among those living with mental health conditions, like eating disorders. OBJECTIVES This new study will explore the impact of Nutri-score labelling vs Calorie labelling vs no labelling (Control) in a simulated OOH food delivery ordering platform (common setting for food purchasing and calorie labelling is required by law in England) on participants' perceived effectiveness of nutritional labelling, healthiness of food choices, positive and negative affect, and perceived impacts on mental health. We will examine effects in a general population sample (no eating disorder diagnosis), a sample of participants with a past or current diagnosis of an eating disorder by a medical practitioner and a sample of participants with a common mental health condition diagnosed by a medical practitioner without eating disorder (e.g., anxiety), in order to understand potential effects across groups of participants who may differ in their risk of poorer mental health in response to nutritional labelling. (references in attached protocol)

Fast Food Online Delivery Purchase Behaviour in the Presence and Absence of Price-based Incentives

Consumption of out-of-home (OOH) food is associated with significantly greater energy and less-healthy nutrient (i.e. fats, salt and sugar) intake. The price of food is a key consideration of food choice, particularly for individuals of lower socioeconomic position (SEP). Little research to date has examined the causal effect of removing price-based incentives on purchasing behaviour in OOH food settings. One online randomised controlled trial explored the effect of removing three types of price-based incentives individually and in combination, on food choice through a virtual food delivery platform. This study found that energy selection was 7-8% lower when price incentives were removed. While not statistically significant, Bayes factors indicted that data comparing control vs "all promotions removed" conditions were inconclusive (BF10 = 0.55) and therefore could not provide support for the alternative or null hypotheses. A limitation of this study is that the outcome was hypothetical food choice. As participants would not pay for or receive their selected meals, the prices of foods may have been less salient, thus reducing the potential for impact. In the present study, exploring real-world consumer behaviour (as opposed to hypothetical choice) will better determine the potential impact of removing price-based incentives in the OOH food sector.

Piaget-Based Nutrition Education in Preschools

This explanatory sequential mixed-methods study evaluated a six-week Piaget-based nutrition education programme for preschool children. Seven public preschools were randomized at the school level to an intervention condition (three preschools) or a usual-curriculum control condition (four preschools). The intervention consisted of six weekly, approximately 30-minute, developmentally tailored sessions delivered to groups of children in their usual classrooms. Mothers completed measures of children's food consumption frequency, nutrition behavior, and eating behavior before and immediately after the programme. Following the quantitative phase, three focus groups with 18 mothers from intervention preschools explored perceived changes and helped interpret the quantitative patterns. Because preschool identifiers were not retained in the final analytical dataset, the reported child-level analyses did not adjust for clustering and are interpreted as exploratory.