The global prevalence of vaccine misinformation has underscored the crucial necessity to combat false information and explore innovative solutions like chatbots. These artificial intelligence (AI)-powered tools play a pivotal role in disseminating accurate information and mitigating the adverse effects of misinformation. This study aimed to investigate what factors motivated users to combat vaccine misinformation using chatbot tools, and their active communication actions and anti-misinformation behaviors.
Researchers surveyed 612 chatbot users in the United States and utilized structural equation modeling for data analysis.
The findings of this study revealed that both situational and gratification motivations of chatbot users significantly contributed to three essential types of communicative actions: information-seeking, forwarding and forfending. Meanwhile, the data demonstrated that except for information forfending, both information-seeking and forwarding communicative actions could enhance user engagement with anti-misinformation behavior.
The originality of this study lies in its integration of two key motivational frameworks – gratification and situational motivations – within the context of AI-driven tools like chatbots, particularly in combating misinformation. While previous research has explored the use of chatbots or the role of situational motivations in communication separately, this study uniquely combines these concepts to enhance the situational theory of problem-solving (STOPS) model and uses and gratifications (U&G) theory. Additionally, the practical implications for chatbot design and communication strategies targeted at misinformation are a significant contribution, demonstrating how motivation-driven interactions can be used to improve user engagement and public health outcomes.
