Social Modeling of Virtual Healthy Food Intake - Bulsing, Patricia Johanna; Salmon, Stefanie Johanna (Frontiers in Computer Science, 2022)
People tend to adapt the amount of their food intake to that of others around them. This so-called social modeling of eating has been extensively studied over the past decades. The current study complements these experiments and aims to investigate social modeling of healthy food intake using a video paradigm in which a virtual model consumed either a small or a large portion of apple. In addition, it was tested whether modeling effects of a virtual female confederate were equally strong in male and female participants. Thirty participants (13 female, 17 male) completed the low norm condition in which a virtual model consumed 30 g of apple. Another 30 participants (17 female, 13 male) were allocated to the high norm condition in which a virtual model consumed 100 g of apple. Participants completed an irrelevant task, after which their own intake of apple was measured. Average intake in the low norm condition was 3 g, average intake in the high norm condition was 26 g (p < 0.001). In conclusion, participants adapted their intake to that of the virtual model. This effect was found irrespective of gender; female and male participants equally adapted their intake to that of a female virtual model. Stimulating food intake via a virtual model in people who have difficulty to meet dietary requirements or inhibiting food intake in people who tend to consume too much would be interesting new steps in the development of healthcare applications.