Abstract
Recent advancements in digital technology have significantly impacted healthcare, with the rise of chatbots as a promising avenue for healthcare services. These chatbots aim to provide prevention, diagnosis, and treatment services, thereby reducing the workload on medical professionals. Despite this trend, limited research has explored the variables influencing user experiences in the design of healthcare chatbots. While the impact of visual representation within chatbot systems is recognized, existing studies have primarily focused on efficiency and accuracy, neglecting graphical interfaces and non-verbal visual communication tools. This research aims to delve into user experience aspects of symptom checker chatbots, including identity design, interface layout, and visual communication mechanisms. Data was collected through a comprehensive questionnaire involving three distinct chatbots (Healthily, Mediktor and Adele – a self-developed solution) and underwent meticulous analysis, yielding valuable insights to aid the decision process when designing effective chatbots for symptom checking.
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Campos Ferreira, M., Veloso, M., Tavares, J.M.R.S. (2024). A Comprehensive Examination of User Experience in AI-Based Symptom Checker Chatbots. In: Duarte, S.P., Lobo, A., Delibašić, B., Kamissoko, D. (eds) Decision Support Systems XIV. Human-Centric Group Decision, Negotiation and Decision Support Systems for Societal Transitions. ICDSST 2024. Lecture Notes in Business Information Processing, vol 506. Springer, Cham. https://doi.org/10.1007/978-3-031-59376-5_8
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