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Criollo-C, S., Guerrero-Arias, A., Jaramillo-Alcázar, Á., & Luján-Mora, S. (2021). Mobile learning Technologies for Education: benefits and pending issues. Applied Sciences, 11(9), 4111.

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Article

From Substitution to Redefinition: The SAMR Model as a Framework for AI Adoption in Nursing

1Director of Nursing, Central Division, Safwa, Saudi Ministry of Health, Saudi Arabia

2Nursing Department, Eastern Health Cluster, Saudi Ministry of Health, Saudi Arabia

3Clinical Nurse Educator, Saudi Ministry of Health, Ras-Tanura Hospital, Saudi Arabia

4Professional Development coordinator, Saudi Ministry of Health, Safwa, Saudi Arabia

5Nursing Manager of Professional Development, Central Division, Safwa General Hospital, Saudi Arabia.

6Nurse Education Coordinator, Saudi Ministry of Health, Safwa Hospital, Saudi Arabia

7Nursing Supervisor, Saudi Ministry of Health, Um-Alsahik, Saudi Arabia

8Nursing Department, Saudi Ministry of Health, Central Division, Saudi Arabia

9Nursing Department, CNE, Khobar Health Network, Saudi Ministry of Health, Saudi Arabia10Nursing Department, Saudi Ministry of Health, Central Division, Saudi Arabia

109Nursing Department, CNE, Khobar Health Network, Saudi Ministry of Health, Saudi Arabia10Nursing Department, Saudi Ministry of Health, Central Division, Saudi Arabia


American Journal of Nursing Research. 2025, Vol. 13 No. 2, 44-50
DOI: 10.12691/ajnr-13-2-5
Copyright © 2025 Science and Education Publishing

Cite this paper:
Sakna Habobi, Amani Abualrahi, Roqaia Bumarah, Shereen AlMatter, Shaima’a Al-Sanona, Zainab Alabdrabalnabi, Farha Al-Khwaildi, Maryam Alalaq, Izdehar Alawami, Aqeelah Alyossuf. From Substitution to Redefinition: The SAMR Model as a Framework for AI Adoption in Nursing. American Journal of Nursing Research. 2025; 13(2):44-50. doi: 10.12691/ajnr-13-2-5.

Correspondence to: Amani  Abualrahi, Nursing Department, Eastern Health Cluster, Saudi Ministry of Health, Saudi Arabia. Email: rahia4@hotmail.com

Abstract

Background: AI is transforming nursing through predictive analytics and simulations, enhancing learning and care. Challenges include ethics, technical issues, and institutional resistance. Aim: This study explores how AI strengthens nursing education and clinical workflows, utilizing the SAMR Model. Method: A systematic integrative review (2018–2024) used CINAHL, Ovid Medline, and PubMed with PRISMA guidelines.Results: AI boosts learning via simulations and adaptive tools; clinically, it aids diagnosis and monitoring. SAMR shows AI’s shift from basic tools to intelligent systems, though barriers like privacy and cost remain. Conclusion: AI aligns with healthcare goals like Saudi Vision 2030; success requires ethics, partnerships, and training

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