Browsing by Subject "Nursing Ethics"

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    Implications of Generative Artificial Intelligence on Ethics in Nursing Education: State of The Art Review
    (Universidad de Murcia. Servicio de Publicaciones, 2025) Luque Loor, Andy Hermógenes; Cedeño Orejuela, José André; Melis Sosa, Ariel; Añazco Moreira, Paola Ceciliana; Vinces Sornoza, Tatiana Paola; Villavicencio Macías, Reina Yadira; Zambrano Zambrano, Gema Paola; Pino Andrade, Silvia Cristina; Sin departamento asociado
    The rapid advancement of generative artificial intelligence (GAI) presents both opportunities and ethical challenges in nursing education. GAI has the potential to enhance teaching, learning, and clinical decision-making through personalized learning resources and simulation of healthcare sce-narios. However, it also introduces multifaceted ethical dilemmas, which require careful considera-tion in its integration into nursing curricula. This study aims to critically examine the ethical implica-tions of GAI adoption in nursing education, focusing on its impact on ethical principles, clinical rea-soning, academic integrity, and pedagogical strategies. We synthesized peer-reviewed evidence published between January 2023 and August 2025 in a state-of the-art review. Studies were selected from PubMed, Scopus, and Web of Science using specific search terms related to GAI, ethics, and nursing education. Data extraction was performed using a predefined template, capturing key variables such as ethical principles, methodological approaches, and recommended pedagogical safeguards. The integration of GAI in nursing education raises concerns regarding academic integrity, automation bias, AI "hallucinations," data privacy, and equity. However, it also offers opportunities for improving clinical reasoning, knowledge, and attitudes among students. The results underscore the need for clear gov-ernance frameworks, hybrid pedagogical approaches with "human-in-the-loop," and explicit guide-lines for transparency, bias mitigation, and data protection. GAI can enhance learning in nursing education when used responsibly. Ethical risks, such as the degradation of ethical reasoning and issues of privacy and equity, require careful management. A hybrid design approach, coupled with ethical training and continuous evaluation of AI use, is essential to ensure GAI's benefits while safeguarding professional judgment and patient safety.