Computer-based assessments of expected satiety predict behavioural measures of portion-size selection and food intake
Wilkinson, Laura L. , Hinton, Elanor C., Fay, Stephanie H., Ferriday, Danielle, Rogers, Peter J., & Brunstrom, Jeffrey M. (2012) Computer-based assessments of expected satiety predict behavioural measures of portion-size selection and food intake. Appetite, 59(3), pp. 933-938.
Previously, expected satiety (ES) has been measured using software and two-dimensional pictures presented on a computer screen. In this context, ES is an excellent predictor of self-selected portions, when quantified using similar images and similar software. In the present study we sought to establish the veracity of ES as a predictor of behaviours associated with real foods. Participants (N = 30) used computer software to assess their ES and ideal portion of three familiar foods. A real bowl of one food (pasta and sauce) was then presented and participants self-selected an ideal portion size. They then consumed the portion ad libitum. Additional measures of appetite, expected and actual liking, novelty, and reward, were also taken. Importantly, our screen-based measures of expected satiety and ideal portion size were both significantly related to intake (p < .05). By contrast, measures of liking were relatively poor predictors (p > .05). In addition, consistent with previous studies, the majority (90%) of participants engaged in plate cleaning. Of these, 29.6% consumed more when prompted by the experimenter. Together, these findings further validate the use of screen-based measures to explore determinants of portion-size selection and energy intake in humans.
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|Item Type:||Journal Article|
|Keywords:||Portion size, Expected satiation, Expected satiety, Food intake, Liking, Reward|
|Subjects:||Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > NUTRITION AND DIETETICS (111100) > Nutrition and Dietetics not elsewhere classified (111199)
Australian and New Zealand Standard Research Classification > PSYCHOLOGY AND COGNITIVE SCIENCES (170000) > COGNITIVE SCIENCE (170200) > Cognitive Science not elsewhere classified (170299)
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Exercise & Nutrition Sciences
|Deposited On:||01 May 2013 22:33|
|Last Modified:||02 May 2013 21:07|
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