JMIR Publications

ABSTRACT

Background:

The Australian Dietary Guidelines (ADGs) translate the best available evidence in nutrition into food choice recommendations. However, adherence to the ADGs is poor in Australia. Given following a healthy diet can be a potentially cost-effective strategy for lowering the risk of chronic diseases, there is an urgent need to develop novel technologies for individuals to improve their adherence to the ADGs.

Objective:

This study described the development process and design of a prototype mobile app for personalized dietary advice based on the ADGs for adults in Australia, with the aim to explore the usability of the prototype. The goal of the prototype was to provide personalized evidence-based support for self-managing food choices in real time.

Methods:

The guidelines of the design science paradigm were applied to guide the design, development and evaluation of a progressive web app using the Amazon Web Services Elastic Compute Cloud services via iterations. The Nutrition Care Process elements, the strategies of cognitive behavioral theory and the ADGs were translated into the prototype features guided by the Persuasive Systems Design model. A gain-framed approach was adopted to promote positive behavior change. A cross-modal image-to-recipe retrieval under Apache-2.0 license was deployed for dietary assessment. A survey using the Mobile Application Rating Scale and semi-structured in-depth interviews were conducted to explore the usability of the prototype through convenience sampling (n =15).

Results:

The prominent features of the prototype included the use of image-based dietary assessment, food choice tracking with immediate feedback leveraging gamification principles, personal goals setting for food choices, as well as the provision of recipe ideas and information on the ADGs. The overall prototype quality score was ‘acceptable’ with a median of 3.46 (interquartile range: 2.78, 3.81) of 5 points. The median score of the perceived impact of the prototype on healthy eating based on the ADG was 3.83 (interquartile range: 2.75, 4.08) of 5 points. In-depth interviews identified the use of gamifications for tracking food choices and innovation in image-based dietary assessment as the main drivers of the positive user experience of using the prototype.

Conclusions:

A novel evidence-based prototype mobile app was successfully developed leveraging cross-disciplinary collaboration. The detailed description of the development process and design of the prototype enhances transparency of the prototype and provides detailed insights into its creation. This study provides a valuable example of developing novel, evidence-based apps for personalized dietary advice on food choices using recent advancement in computer vision. A revised version of the prototype is currently under development.