Conversational Agents in Healthcare: Using QCA to Explain Patients’ Resistance to Chatbots for Medication

Abstract

Complete information is very important to the accuracy of diagnosis in healthcare. Therefore, the idea to use conversational agents recording relevant information and providing it to healthcare facilities is of rising interest. A promising use case of the involvement of conversational agents is medication, as this data is often fragmented or incomplete. The paper at hand examines the hindrances in the way of patients sharing their medication list with a chatbot. Basing on established theories and using fuzzy-set qualitative comparative analysis (QCA), we identify bundles of factors that influence patients lacking willingness to interact with a chatbot. Those typologies of patients can be used to address these hindrances specifically, providing useful insights for theory and healthcare facilities.