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The global spread of COVID-19 has caused a huge number of confirmed cases and deaths, which in return leads to a plethora of mental disorders across the world. In order to address citizens’ psychological problems, government agencies in many countries have employed AI-based chatbots to provide mental health services. However, there is a limited understanding of the determinants affecting citizens’ user experience and user satisfaction when mental health services supported by chatbots are provided. Thus, based on the Theory of Consumption Values (TCV), this study proposes an analytical framework to investigate the factors that are important to citizens’ user experience and user satisfaction when they interact with mental health chatbots. Analysis of data collected from 295 chatbot users in Wuhan and Chongqing reveals that personalization, enjoyment, learning, and condition are positively related to user experience and user satisfaction. However, voice interaction fails to devote to citizens’ user experience and user satisfaction. Thus, government agencies and their AI service contractors should enhance the functions and systems of mental health chatbots to ensure citizens’ user experience and user satisfaction. Also, they should more positively promote the use of mental health chatbots during the public health emergency.

international journal of human–computer interaction

It Is Me, Chatbot: Working to Address the COVID-19 Outbreak-Related Mental Health Issues in China. User Experience, Satisfaction, and Influencing Factors