Data driven studies on the efficacy of healthcare applications and strategies for improving user compliance with these applications

Abstract

With the recent interest in wellness, the use of various smartphone healthcare applications has grown rapidly. However, there is a lack of research on the efficacy of healthcare applications and strategies for improving user compliance with these applications. This thesis has conducted research on the efficacy and promotion strategies of smartphone healthcare applications through three studies. In the first study, I examined whether mood logs collected through emoticon questionnaires through smartphone application is effective for depression screening. In the second study, it was proved that the accuracy of depression screening could be improved by applying high quality data filtered by machine learning methods. In the third study, I verified whether the promotional effect offered by a firm to the customer is effective in improving application retention.