Materialien und Daten zum Research Paper "Can we trust a chatbot like a physician? A qualitative study on understanding the emergence of trust toward diagnostic chatbots"

The dataset contains data and materials that have been created and collected as empirical basis for the first paper "Can we trust a chatbot like a physician? A qualitative study on understanding the emergence of trust toward diagnostic chatbots" of the cumulative dissertation "Social Actor or Technology? Experimental Studies on the Perception of Chatbots Versus Humans and Their Implications for Anthropomorphic Chatbot Design". The research group first conducted a laboratory experiment (Study 1) in which participants had to take the perspective of a patient suffering from symptoms that were described in a scenario. Afterwards, they either interacted with a diagnostic chatbot only or with an additional physician after they had received the preliminary assessment from the chatbot. Data was collected by semi-structured pre- and post-interaction interviews focusing on the process and drivers of trust development. The interview manuscripts were analyzed and coded both inductively and deductively following the "Summarizing Content Analysis" approach (Mayring, 2000; Mayring, 2014). As a follow-up, the research group verified the coding system in a larger online survey (Study 2) during the COVID-19 pandemic in which participants interacted with a chatbot that was able to assess an individual's risk of a Corona infection.