Investigating Motivations and Patient Profiles for Personalization of Health Applications for Behaviour Change

Abstract

Personalization is a key aspect when developing applications targeting health behaviour change. However, the use of personalized mobile interventions for lifestyle behaviour is still in its infancy. Based on our former research on mobile applications to support cardiac patients in health behaviour change, we identified four key motivations to enhance the personalization offered in applications targeting health behaviour change. In this paper, we propose a mixed-methods approach, using both qualitative and quantitative data collected in prior studies, to apply personalization in the design of health applications. Our approach consists of five steps: 1) collecting data for personalization, 2) detecting patient profiles using clustering methods, 3) understanding patient profiles using a graph-ical representation, 4) describing patient profiles using personas, and 5) personalizing a health application according to patient profiles. One of the major strengths of our approach is that it combines established HCI techniques such as personas and data visualization techniques with methods from big data analytics and artificial intelligence to identify ways to personalize health applications. We conclude by presenting future directions to apply personalization in the domain of health technologies.