Examining the Effect of Anthropomorphic Design Cues on Healthcare Chatbots Acceptance and Organization-Public Relationships: Trust in a Warm Human Vs. a Competent Machine

Abstract

AI-powered healthcare chatbots demonstrate great promise in enhancing communication and fostering stronger relationships between healthcare organizations and their publics. This study conducted an experiment to examine how different anthropomorphic design cues shape chatbot acceptance and organization-public relationships by influencing trust in the chatbot. Results revealed an interesting dynamic: when users interacted with healthcare chatbot featuring human-like cues, they tend to place greater trust in the chatbot that showed warmth rather than competence. Conversely, in interactions with a chatbot embodying machine-like cues, a competent conversation style generated higher levels of trust compared to a warm style. This trust in human-computer interactions further enhanced users’ intentions to continue using the chatbot and follow its recommendations, alongside bolstering relational trust and satisfaction with the healthcare organization. These findings contribute to the theoretical understanding of human-chatbot interaction and offer practical insights by aligning chatbot design nuances with the broader strategic health communication goals.