Perioperative Human-Centered Communication on AI-Supported Real-Time Imaging

This study investigates whether a structured, human-centered explanation about the use of artificial intelligence (AI)-supported real-time imaging systems can reduce preoperative anxiety and improve patients' sense of control before elective surgery. Advances in medical imaging and AI technologies have increased their visibility in clinical settings, including the perioperative period. However, limited information is available on how explanations about such technologies influence patients' psychological responses. In particular, uncertainty or misunderstanding about AI-supported systems may contribute to increased anxiety in some patients. In this randomized controlled trial, adult patients scheduled for elective surgery will be assigned to one of two groups. The control group will receive standard preoperative information routinely provided by the hospital. The intervention group will receive standard information plus a short, structured, and non-technical explanation about AI-supported real-time imaging systems, focusing on their role, limitations, and relevance to patient safety. Levels of preoperative anxiety and perceived control will be assessed before and after the information session using validated questionnaires. The study does not test or evaluate the technical performance of any AI system. Instead, it focuses on how communication and explanation about AI-supported technologies may influence patients' psychological preparedness for surgery. The findings may help inform human-centered and ethically responsible approaches to communicating about advanced technologies in perioperative care.

The increasing integration of artificial intelligence (AI)-supported real-time imaging systems into clinical workflows has transformed diagnostic and perioperative practices. While the technical performance and clinical utility of these systems have been widely studied, considerably less attention has been given to how patients perceive and psychologically respond to information about AI-supported technologies used in their care. Preoperative anxiety is a common psychological stressor among surgical patients and is associated with adverse perioperative outcomes, including increased postoperative pain, delayed recovery, and reduced patient satisfaction. Perceived control has been identified as a key psychological factor that can buffer the negative effects of anxiety, particularly in high-uncertainty clinical contexts such as the perioperative period. This single-center, parallel-group randomized controlled trial is designed to evaluate the psychological effects of a structured, human-centered communication intervention related to AI-supported real-time imaging systems. Adult patients scheduled for elective surgery will be randomly assigned in a 1:1 ratio to either an intervention group or a control group following baseline assessment. Participants in the control group will receive standard preoperative information routinely provided by the institution. Participants in the intervention group will receive standard information plus a brief (approximately 5-7 minutes), face-to-face, structured explanation about AI-supported real-time imaging systems. The intervention will use non-technical, patient-centered language and will address the general purpose of such systems, their role and limitations in clinical practice, and their relationship to patient safety and clinical decision-making. The intervention does not involve the use, testing, or evaluation of any specific AI software, device, or imaging system. Preoperative anxiety and perceived control will be assessed at baseline (prior to randomization) and again after the information session, before surgery. The primary analyses will compare changes in anxiety and perceived control between the intervention and control groups, with baseline values accounted for in the statistical models. This study does not aim to assess the diagnostic accuracy, technical performance, or clinical effectiveness of AI-supported imaging systems. Instead, it focuses on the communication and explanatory context surrounding such technologies, with the goal of informing human-centered, transparent, and ethically responsible strategies for integrating AI-supported systems into perioperative care.