Journal
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
Volume 38, Issue 12, Pages 1182-1194Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/10447318.2021.1988236
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The global spread of COVID-19 has led to a significant increase in mental disorders, prompting many government agencies to use AI chatbots for mental health services. Research shows that personalization, enjoyment, learning, and condition positively impact user experience and satisfaction, while voice interaction does not. It is recommended that chatbot functions be enhanced to ensure user satisfaction and that their use be promoted during public health emergencies.
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.
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