Graduated: December 15, 2017
Creating a Smartphone Application for Image-Assisted Dietary Assessment among Older Adults with Type 2 Diabetes
In the United States, the older population aged 65 or over numbered 44.7 million in 2013 and is anticipated to reach approximately 74 million people by 2030. More than one in four people in the United States aged 65 years and older have diabetes. For diabetes care, medical nutrition therapy (MNT) is recommended as a clinically effective intervention. For personalized MNT, it is essential for dietitians to assess the nutritional status of patients with a variety of dietary data (i.e., meal patterns, food choices, and overall dietary balance). However, it is difficult to obtain accurate information because traditional dietary assessment methods (e.g., 24-hour dietary recall (24HR), food records) are based on self-reported data. In particular, those methods might be inappropriate for older adults because they have special considerations with diminished functional statuses (i.e., diminished vision and memory loss). To address this problem, researchers developed and validated dietary assessment methods using the images of food items for improving the accuracy of self- reporting of traditional methods. Nevertheless, little is known about the usability and feasibility of image-assisted dietary assessment methods for diabetic older adults and their satisfaction with the methods. To my knowledge, no studies evaluated the image-assisted dietary assessment methods with both health providers (i.e., dietitians) and patients (i.e., diabetic older adults), though both are essential stakeholders in the dietary assessment process. Further, little is known about the usability and feasibility of smartphone applications for image-assisted dietary assessment, though a smartphone is the device that can perform multiple tasks (i.e., capturing, viewing, and transmitting images) required for image-assisted dietary assessment. Filling these gaps may reduce the error of self-reporting by diabetic older adults and result in more accurate dietary assessment. The goal of this research is to improve the accuracy of traditional dietary assessment methods among older adults with type 2 diabetes. To achieve the goal, I created Food Record App for Dietary Assessment (FRADA), a smartphone application for capturing, viewing, and transmitting the images of food and beverages and evaluated the usability and feasibility of FRADA and the satisfaction of diabetic older adults with the application. Further, I evaluated the satisfaction of dietitians with the image-assisted 24HR session. The findings of this research support the evidence that image-assisted dietary assessment using FRADA could be potentially used to improve the accuracy of dietary assessment by reducing the error of self-reporting. Also, this study reveals design opportunities to facilitate communications between older adults and dietitians for better dietary assessment. To my knowledge, this is the first attempt to evaluate a smartphone application with both older adults and dietitians through a lab-based and deployment study based on 24HR.
The aims of this study are:
Aim 1: To create a smartphone application for the image-assisted dietary assessment and determine the usability of the application for diabetic older adults.
Aim 2: To determine the feasibility of the smartphone application with diabetic older adults for the image-assisted dietary assessment.
Aim 3: To determine the satisfaction of diabetic older adults with the smartphone application for the image-assisted dietary assessment and determine the satisfaction of dietitians with the image-assisted 24HR session.
Last Known Position:
Assistant Professor, Department of Computer Science and Engineering, University of Seoul (South Korea)
Drs. Peter Tarczy-Hornoch (Chair), George Demiris, Lingtak-Neander Chan, Mark Zachry