Patient perspectives of the Self-management and Educational Technology tool for Atrial Fibrillation (SETAF): A mixed-methods study in Singapore.

Abstract

Atrial fibrillation (AF) is the most common arrythmia and is associated with costly morbidity such as stroke and heart failure. Mobile health (mHealth) has potential to help bridge the gaps of traditional healthcare models that may be poorly suited to the sporadic nature of AF. The Self-management and Educational technology support Tool for AF patients (SETAF) was designed based on the preferences and needs of AF patients but more study is required to assess the acceptance of this novel tool. Explore the usability and acceptance of SETAF among AF patients in Singapore. A mixed methods study was conducted with AF patients who were purposively sampled from an outpatient cardiology clinic in Singapore. After 6 weeks of using SETAF, semi-structured interviews were performed, and data were analyzed inductively following a thematic analysis approach. Results from a short 4-item survey and application usage data were also analyzed descriptively. Both qualitative and quantitative results were organized and presented following the Technology Acceptance Model (TAM) framework. A total of 37 patients participated in the study and 19 were interviewed. Participants perceived SETAF as useful for improving AF knowledge, self-management and access to healthcare providers and was easy to use due to the guided tutorial and user-friendly interface. They also identified the need for better personalization of content, psychosocial support features and reduction of language barriers. Application usage data revealed preference for AF related content and decreased interaction with the motivational message component of SETAF over time. Overall, most of the participants would continue using SETAF and were willing to pay for it. AF patients in Singapore found SETAF useful and acceptable as a tool for AF management. The insights from this study not only support the potential of mHealth but may also inform the design and implementation of future mHealth tools for AF patients.