Artificial intelligence-based nursing curricula in Iran and other Gulf countries: A narrative review

Abstract

Integrating artificial intelligence (AI) in nursing education offers transformative potential for improving clinical decision-making and patient care. This study compares AI-based nursing curricula in Iran and Persian Gulf countries, exploring implementation strategies, identifying gaps, and assessing opportunities for regional collaboration to enhance nursing education and healthcare outcomes. A comprehensive review of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted. PubMed, Scopus and Google Scholar data were analyzed, focusing on AI tools, teaching strategies, and student outcomes in nursing education from 2010 to 2024. Keywords such as “artificial intelligence”, “nursing education”, “Iran”, and “Persian Gulf” were employed. Inclusion criteria encompassed studies addressing AI integration within nursing curricula in Iran and Persian Gulf nations. Findings revealed significant disparities in AI adoption across countries. Iran is in the early stages, with limited implementation and infrastructure, while Qatar and the United Arab Emirates (UAE) demonstrate advanced integration, employing AI for simulations and adaptive learning. Common challenges include the lack of trained professionals and high costs. Despite these obstacles, students globally are interested in AI technologies, highlighting the potential for enhanced learning experiences and regional standardization. AI integration can revolutionize nursing education, preparing students for complex clinical scenarios and improving healthcare quality. Regional collaboration and investment in AI infrastructure are essential for sustainable implementation.

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