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Assessing acceptance of AI nurses for outpatients with chronic diseases: From nurses’ perspective

Ali Osman Uymaz, Pelin Uymaz, Yakup Akgül

Article ID: 2309
Vol 9, Issue 5, 2024, Article identifier:

VIEWS - 382 (Abstract) 172 (PDF)


The primary objective of this article is to investigate and forecast nurses’ attitudes toward using AI nurses for outpatients with chronic diseases. AI technology is used in hospitals in a disease-centric manner. However, it is desired by healthcare regulators to be used in an individual-centric and holistic manner. The research model was developed based on the Unified Theory of Accepting and Using Technology. In determining the causes and consequences of the attitudes, actions, ideas, and beliefs of the nurses, the screening technique of causal comparison was used. Research data was collected from registered nurses who work in research hospitals and use intelligent health technologies for inpatients. Based on 494 responses, this study conducted a dual-phase assessment using Partial Least Squares Structural Equation Modeling as well as the creation of an AI method known as deep learning (artificial neural network). According to the results, nurses are convinced that AI is a suitable tool for their nursing tasks and increases their efficiency and productivity. It has been determined that nurses have intentions to use AI nurses for outpatients with chronic diseases. However, nurses have concerns about the reliability of ambulatory patient data. The policies and strategies of regulators will affect the acceptance of AI technology, not only for nurses but for all healthcare professionals and patients.


artificial intelligence; health informatics; nursing care; deep learning; artificial neural network; partial least squares-structural equation modeling

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