AI with a Heart: How perceived authenticity and warmth shape trust in healthcare chatbots
The Anh Phan, Van Dat Bui
Abstract
As artificial intelligence (AI) continues to transform healthcare, AI-driven chatbots are increasingly utilized for patient communication, symptom assessment, and mental health support. However, the success of these chatbots depends on more than just accuracy; their perceived authenticity, warmth, and empathy significantly shape patient trust and engagement. This study examines the interplay between perceived authenticity, perceived warmth, and perceived empathy in influencing patient trust and visit intention. Through an empirical study, we find that perceived authenticity enhances both warmth and empathy, which in turn foster trust and increase visit intention. Additionally, we investigate the moderating role of chatbot type, revealing that while human-like design can enhance warmth perception, it does not necessarily amplify the effects of authenticity. These findings highlight the critical role of emotional intelligence in AI-driven healthcare interactions and suggest that chatbots should prioritize sincerity and socially attuned communication over mere anthropomorphic features. This study contributes to the growing discourse on AI-human trust dynamics and offers actionable insights for healthcare providers, AI developers, and policymakers seeking to integrate patient-centered AI solutions into clinical practice.