Analyzing Use Intentions for Health-Diagnostic Chatbots: An Extended Technology Acceptance Model Approach

This study investigates the factors influencing the intention to use AI-powered health diagnostic chatbots. A research model was proposed based on the Technology Acceptance Model, subjective norms, perceived trust, perceived risk, and self-efficacy. Using Partial Least Squares Structural Equation Modeling, the study assessed the model with 274 valid responses. The results revealed that perceived usefulness, subjective norms, perceived trust, and self-efficacy significantly influence the intention to use AI-powered health diagnostic chatbots. However, perceived ease of use and perceived risk did not impact the intention to use such chatbots. The study also discusses how these findings can assist developers in promoting the long-term adoption of AI-powered health diagnostic chatbots among potential users.