The Future of Nursing Care with Artificial Intelligence: Balancing Pros and Cons
Keywords:
Artificial Intelligence; ChatGPT; Benefits; Harms; Nursing.Abstract
The integration of artificial intelligence (AI) technologies, such as ChatGPT, into nursing practice, has introduced novel opportunities and challenges. This abstract explores the multifaceted impact of ChatGPT on nursing care, highlighting its potential benefits and pitfalls. ChatGPT serves as a comprehensive knowledge resource, offering nurses instant access to medical information and fostering continuous learning. Additionally, it facilitates educational innovation by providing interactive learning experiences and hands-on training opportunities. This study employed a comprehensive literature review approach to explore the impact of ChatGPT on nursing care. Relevant articles were identified through searches of electronic databases, including PubMed, CINAHL, and Google Scholar, using keywords such as "ChatGPT," "artificial intelligence," "nursing care," and "healthcare." Studies published in peer-reviewed journals between 2010 and 2023 were included in the analysis. The literature review revealed a growing body of evidence on the utilization of ChatGPT in nursing care, highlighting its potential to enhance communication, decision support, and administrative efficiency. Several studies reported positive outcomes associated with ChatGPT adoption, including improved patient satisfaction, increased access to clinical information, and reduced workload for nursing staff. The findings of this study highlight the complex interplay between the promise and pitfalls of ChatGPT integration in nursing care. While AI technologies offer exciting opportunities to augment healthcare delivery, they also present inherent risks that must be addressed proactively. Nurses play a crucial role in navigating the impact of ChatGPT on patient care, advocating for ethical AI use, and preserving the human-centric nature of nursing practice.
Downloads
References
Lee, J. S., & Hsiang, J. (2020). Patent claim generation by fine-tuning OpenAI GPT-2. World Patent Information, 62, 101983.
OpenAI, O., Plappert, M., Sampedro, R., Xu, T., Akkaya, I., Kosaraju, V., ... & Zaremba, W. (2021). Asymmetric self-play for automatic goal discovery in robotic manipulation. arXiv preprint arXiv:2101.04882.
Larrabee, J. H., & Bolden, L. V. (2001). Defining patient-perceived quality of nursing care. Journal of nursing care quality, 16(1), 34-60.
Blackman, I., Henderson, J., Willis, E., Hamilton, P., Toffoli, L., Verrall, C., & Harvey, C. (2015). Factors influencing why nursing care is missed. Journal of clinical nursing, 24(1-2), 47-56.
Salisu, S., Alyasiri, O. M., Younis, H. A., Sahib, T. M., Ali, A. H., Noor, A. A., & Hayder, I. M. (2024). Measuring the Effectiveness of AI Tools in Clinical Research and Writing: A Case Study in Healthcare. Mesopotamian Journal of Artificial Intelligence in Healthcare, 2024, 8-15.
Younis, Hussain A., Taiseer Abdalla Elfadil Eisa, Maged Nasser, Thaeer Mueen Sahib, Ameen A. Noor, Osamah Mohammed Alyasiri, Sani Salisu, Israa M. Hayder, and Hameed AbdulKareem Younis. 2024. "A Systematic Review and Meta-Analysis of Artificial Intelligence Tools in Medicine and Healthcare: Applications, Considerations, Limitations, Motivation and Challenges" Diagnostics 14, no. 1: 109. https://doi.org/10.3390/diagnostics14010109.
Noor, A. A., Younis, H. A., Abbas, F. N., Salisu, S., Alyasiri, O. M., Hayder, I. M., & Sahib, T. M. (2024). An Analytical Review of CHATGPT Influence on Healthcare, Media, and Education Advancements. Journal of AL-Turath University College, 2(38).
Younis, H. A., Ruhaiyem, N. I. R., Ghaban, W., Gazem, N. A., & Nasser, M. (2023). A systematic literature review on the applications of robots and natural language processing in education. Electronics, 12(13), 2864. https://doi.org/10.3390/electronics12132864.
Stalp JL, Denecke A, Jentschke M, Hillemanns P, Klapdor R. (2024). Quality of ChatGPT-Generated Therapy Recommendations for Breast Cancer Treatment in Gynecology. Current Oncology, 31(7):3845-3854. https://doi.org/10.3390/curroncol31070284.
T. M. Sahib, O. M. Alyasiri, H. A. Younis, D. Akhtom,I. M. Hayder, S. Salisu, and Muthmainnah (2023). A comparison between ChatGPT-3.5 and ChatGPT-4.0 as a tool for paraphrasing English Paragraphs. In International Applied Social Sciences (C-IASOS-2023) Congress. pp 471-480.
Mohammed, O., Sahib, T. M., Hayder, I. M., Salisu, S., & Shahid, M. (2023). ChatGPT Evaluation: Can It Replace Grammarly and Quillbot Tools?. British Journal of Applied Linguistics, 3(2), 34-46.
Sahib, T. M., Younis, H. A., Alyasiri, O. M., Ali, A. H., Salisu, S., Noore, A. A., & Shahid, M. (2023). ChatGPT in Waste Management: Is it a Profitable. Mesopotamian Journal of Big Data, 2023, 107-109.
Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. Metabolism, 69, S36-S40.
Baqir, H. A., Younis, H. A., & Alyasiri, O. M. (2023). Utilizing GPT-4 for Morphological Identification of Bed Bugs. Abhath Journal of Basic and Applied Sciences, 2(2), 38-41.
Holzinger, A., Langs, G., Denk, H., Zatloukal, K., & Müller, H. (2019). Causability and explainability of artificial intelligence in medicine. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(4), e1312.
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Information Systems Research and Practice
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
