title: The effects of nutrition labeling on consumer food choice: a psychological experiment and computational model.
abstract: The widespread availability of calorie-dense food is believed to be a contributing cause of an epidemic of obesity and associated diseases throughout the world. One possible countermeasure is to empower consumers to make healthier food choices with useful nutrition labeling. An important part of this endeavor is to determine the usability of existing and proposed labeling schemes. Here, we report an experiment on how four different labeling schemes affect the speed and nutritional value of food choices. We then apply decision field theory, a leading computational model of human decision making, to simulate the experimental results. The psychology experiment shows that quantitative, single-attribute labeling schemes have greater usability than multiattribute and binary ones, and that they remain effective under moderate time pressure. The computational model simulates these psychological results and provides explanatory insights into them. This work shows how experimental psychology and computational modeling can contribute to the evaluation and improvement of nutrition-labeling schemes.
authors.affiliation: Department of Psychology and Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
authors.forename: Peter
authors.initials: P
authors.lastname: Helfer
authors.affiliation: Department of Psychology and School of Computer Science, McGill University, Montreal, Quebec, Canada.
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Shultz
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D002170:Canada; D002755:Choice Behavior; D003198:Computer Simulation; D003258:Consumer Behavior; D003657:Decision Making; D002149:Energy Intake; D005247:Feeding Behavior; D005260:Female; D005502:Food; D005515:Food Labeling; D005518:Food Preferences / Q000523:psychology*; D015438:Health Behavior; D006801:Humans; D008297:Male; D008875:Middle Aged; D018673:Nutrition Policy; D009765:Obesity; D012044:Regression Analysis; D012923:Social Class; D014481:United States; D055815:Young Adult
keywords: computational modeling; decision making; nutrition labeling