From Anxiety to Trust: Understanding AI Chatbot adoption in Emergency Healthcare

Abstract

The integration of artificial intelligence (AI) in healthcare is transforming emergency department (ED) operations by streamlining service efficiency. This study investigates the key factors influencing the adoption of AI-driven chatbots to enhance patient flow and reduce waiting times. A survey was conducted in Portugal with 296 individuals who often turn to the internet for health advice and have experienced emergency situations where quick and accurate guidance is critical, and analyzed using partial least squares. Grounded in UTAUT and frameworks of security, trust, and anxiety, the model explained 76.7% of the variance in the actual use of health chatbots. Anxiety moderates the relationship between intention to use and actual use and behavioral intention mediates the relationship between trust and use. By assessing symptoms and guiding patients to less-crowded hospitals, AI chatbots demonstrate the potential to reduce ED congestion and improve decision-making.