Date of Award
12-2015
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Legacy Department
Human Centered Computing
Committee Chair/Advisor
Caine, Kelly
Committee Member
Muth, Eric
Committee Member
Remy, Sekou
Abstract
Food overconsumption is a major contributor to weight gain leading to obesity. Constant exposure to larger amounts of food and beverage has caused many individuals to experience “portion distortion,†the perception that bigger portion sizes are appropriate for consumption at a single sitting. Independently and accurately changing this perception can be very difficult even if one has a desire to do so. In response to these observations, we developed and tested Picture-Perfect Portions, a mobile application designed to combat overconsumption, at the individual level, by leveraging the power of simple visualizations to help adults understand and adjust their food consumption practices. Data were collected from 141 participants eating a meal of macaroni and cheese in a laboratory setting. In a 2 x 2 x 2 between-subjects experimental design, participants were assigned to one of eight conditions: 1) Small (17 cm diameter) Plate, Without Picture-Perfect Portions (App), Without 400-Calorie food consumption target (Goal), 2) Small Plate, With App, Without Goal, 3) Small Plate, Without App, With Goal, 4) Small Plate, With App, With Goal, 5) Large (26.4 cm diameter) Plate, Without App, Without Goal, 6) Large Plate, With App, Without Goal, 7) Large Plate, Without App, With Goal, or 8) Large Plate, With App, With Goal. Both grams of food consumed of first serving (grams consumed, first serving) and total grams of food consumed during the meal (grams consumed, all servings) were measured as the main dependent variables. These variables were log-transformed for analysis. In total, fifty participants used and evaluated the app. The mean System Usability Scale (SUS) score for Picture-Perfect Portions is 75.2 ± 12.4 (median 78.8). This suggests that Picture-Perfect Portions is an application with high overall system usability. An ANOVA of ln(grams consumed, first serving) for all participants revealed a main effect of PLATE SIZE such that, on average, participants given a large plate consumed more of the first serving than participants given a small plate. A main effect of PLATE SIZE was also observed for the dependent variable ln(grams consumed, all servings) such that, on average, the total amount of food consumed by participants given a large plate was more than the total amount of food consumed by participants given a small plate. A main effect of DEVICE was observed for all participants under the “With Goal†treatment such that, on average, participants with a 400-Calorie consumption goal and the assistance of Picture-Perfect Portions ate less of the first serving than participants with a 400-Calorie consumption goal without the assistance of the app. In addition, a significant effect of DEVICE on ln(grams consumed, first serving) was observed for the “Small Plate†treatment such that, on average, participants using the app ate less than participants not using the app. These results demonstrate the powerful effect of plate size on individuals’ food consumption. They also, however, demonstrate that there are scenarios in which “just-in-time†feedback from an application such as Picture-Perfect Portions can impact food consumption, especially for those individuals with a specific food consumption goal.
Recommended Citation
James, Melva, "Iterative Design and Testing of a Mobile Application to Support Food Consumption Monitoring and Decision Making" (2015). All Dissertations. 1567.
https://open.clemson.edu/all_dissertations/1567