Studying usage and experiences of mHealth technology for its improved usability - Mixed methods research for understanding users’ long-term engagement with the Few Touch application for self-management of Type 2 diabetes mellitus -

Abstract

In spite of a number of mHealth (use of mobile computing for health care) studies targeting people with diabetes, there has not yet been any clear evidence of its effect. Due to obscurity regarding subjects’ engagement with each component of the provided technology, it is not clear which factors are important and why. Considering that behavior change is a path of improvement in self-management of Type 2 diabetes mellitus (T2DM), it is crucial to investigate users’ usage and experiences of mHealth technology over time. Furthermore, ensuring usability of a technology is essential for the initial uptake and continuous usage of it. This research was conducted in three phases using mixed methods research. In Phases 1 and 2, long-term trials of a mobile phone-based self-help application “the Few Touch application” were carried out by involving two different user groups: one had been involved in the design process from an early stage and the other had not. In Phase 3, design of a food-information database module as a part of improvement of the Few Touch application was carried out by involving users and non-users. The study empirically showed the following: the users basically used and experienced the Few Touch application as a flexible learning tool in terms of self-management of T2DM. Patterns and degrees of usage varied a lot among users and they changed over time depending on each user’s needs and background both directly and indirectly relevant to T2DM. This was because motivation for continuation of usage was a result of balancing between expected benefit and effort required to use it. Usability of the technology could be improved by designing it so that it simplifies tedious self-management activities without posing extra effort to use the technology while it enhances the learning process and maximizes its learning effect