Towards engaging and personalized mHealth tools: co-design, data-driven and just-in-time adaptive approaches

Emerging technologies such as virtual coaches, smartphone apps, smart garment (i.e. mHealth tools) offer great potential for supporting people in adopting healthy lifestyle behaviours. Research shows that mHealth tools can be effective in promoting health behaviours (such as physical activity and healthy dietary intake), although effect sizes vary a lot and effects are mainly short term and not sustainable on the long term. The effectiveness of mHealth tools depends on the inclusion of effective behaviour change techniques, but also on sufficient and sustained engagement with the mHealth tool by the end-users. However, getting end-users to engage with a mHealth tool and keep on engaging with it is challenging. Little is known on how to create more engaging mHealth tools, what factors and approaches contribute to higher engagement levels in mHealth tools and how big data (e.g. log event data) and machine learning can be utilized to gain more insights in these factors. In this symposium, four presenters from different disciplines (i.e. system engineering, design, health promotion) will share their results on how to develop more engaging and personalized mHealth tools. We will focus on the value of co-design approaches in the development process of a virtual coach for supporting older adults to adopt a healthy diet (Lean Kramer), on the potential of wearable sensors and adaptive interventions for increasing engagement in an exergame (Ayla Schwarz), on how just-in-time support in a physical activity promoting smartphone app impacts its feasibility and acceptance (Karlijn Sporrel), and lastly on the importance of gaining insight into personal preferences using log data factors to enable personalized mHealth tools (Raoul Nuijten). Finally, the discussant (Olga Perski, expert on engagement in digital health applications) will reflect upon the presentations to elicit a lively audience discussion on challenges and next steps towards the development of more engaging mHealth tools. Topics that will be discussed include how to come to a uniform definition of engagement, how to measure engagement, how to harness data science (e.g. machine learning, self-learning algorithms) for personalized and engaging mHealth and what can be learned from design research.