A mobile application providing a Mediterranean diet based on physical attributes and weight goal

Abstract

Dietary factors can play a harmful or protective role in the burden of chronic conditions, cancer risk and even mental health. In this regard, mobile diet applications have the potential to convey healthful dietary knowledge in a convenient and scalable manner. However, diet apps can be pedantic and counter-productive if a significant burden is placed on the user or low-quality dietary information is provided. The paper examines dietary research, mobile diet, user experience and application design concepts for developing and evaluating a mobile diet application with simplicity and facilitation of a Mediterranean Diet in mind. The overarching methodology is influenced by the Waterfall software development model. In terms of collecting primary data, a survey is carried out prior to the application's design, while User Acceptance Testing takes place after the implementation as part of the application's evaluation and testing. Both the survey and UAT target University staff and students, although the survey also targets Junior College staff. The application itself provides a healthful Mediterranean diet using an underlying deterministic model that does not capture medical information. It utilises several user attributes and a weight goal to get at a caloric estimate, for subsequently calculating food quantities of eight different food groups in accordance to the user's estimated calories and the compiled Mediterranean diet food distribution and food data set. The application’s design is influenced by Material Design for Android, with simplicity, user experience, and facilitation of healthy food choices in mind, and is evaluated as such. According to the initial evaluation, in theory, the application had been expected to be well received, and the UAT findings did indeed reflect the application positively with a SUS score of 87.5 ± 8.75 at a 99.9% confidence interval that places the app in the upper quartile of SUS scores. The majority of UAT participants preferred the developed application over ones that expect constant and precise food inputs, and each of the nine participants responded in the affirmative when asked on the likelihood of its use.