Patient-Engaged AI: The Nursing Path to Health Equity.

Introduction: Artificial intelligence (AI) technology in healthcare has emerged as a highly effective tool for enhancing health data analysis and patient engagement. Recent research examining patients' use of AI applications for self-managing health demonstrates notable benefits but also raises multiple concerns, including exacerbation of health disparities. Furthermore, limited information is available regarding nurses' interactions with patient-engaged AI (PEAI) and its impact on the nurse-patient relationship. Objective: Developing new theoretical frameworks is essential to strengthening the evidence base for AI in nursing practice. The proposed middle-range theory constitutes a significant advancement toward delineating domains of nursing research to define AI utilization within the nurse-patient relationship and addressing health disparities. Methods: Walker and Avant's steps were used to construct the theory, define concepts, and synthesize the literature and models. Results: An integrated theory-building synthesis identified 28 articles, from which five key themes emerged as crucial for mitigating health equity gaps: communication, end-user trust and perceptions, technology and design, self-management, and ethics and privacy. These impact patient engagement and, in turn, are influenced by health literacy. Conclusion: Nursing research and practice are positioned to contribute critical evidence to close health disparities and redefine the nurse-patient relationship within the transformative context of the AI revolution.