Self-Diagnosis through AI-enabled Chatbot-based Symptom Checkers: User\n Experiences and Design Considerations

Abstract

Recently, there has been a growing interest in developing AI-enabled\nchatbot-based symptom checker (CSC) apps in the healthcare market. CSC apps\nprovide potential diagnoses for users and assist them with self-triaging based\non Artificial Intelligence (AI) techniques using human-like conversations.\nDespite the popularity of such CSC apps, little research has been done to\ninvestigate their functionalities and user experiences. To do so, we conducted\na feature review, a user review analysis, and an interview study. We found that\nthe existing CSC apps lack the functions to support the whole diagnostic\nprocess of an offline medical visit. We also found that users perceive the\ncurrent CSC apps to lack support for a comprehensive medical history, flexible\nsymptom input, comprehensible questions, and diverse diseases and user groups.\nBased on these results, we derived implications for the future features and\nconversational design of CSC apps.\n

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