Nutrilize a Personalized Nutrition Recommender System: an Enable Study

Abstract

A nutrition assistance system gives feedback on one’s dietary behavior and supports behavior change through diverse persuasive elements like self-monitoring, personalization, and reflection implemented e.g. with visual cues, recommendations or tracking. While an automated recommender system for nutrition could provide great benefits compared to human nutrition advisors, it also faces a number of challenges in the area of usability like efficiency, efficacy and satisfaction. In this paper, we propose a mobile nutrition assistance system that specifically makes use of personalized persuasive features based on nutritional intake that could help users to adapt their behavior towards healthier nutrition. In a pilot study with 14 participants using the application for 3 weeks we investigate how the different features of the overall system are used and perceived. Based on the measurements, we examine which functions are important to the users and determine necessary improvements.