Implementación de la inteligencia artificial en la docencia de enfermería: retos éticos y pedagógicos.
DOI:
https://doi.org/10.59814/resofro.2024.4(4)369Palabras clave:
Inteligencia artificial; realidad virtual; educación en enfermería; ética.Resumen
Introducción: La integración de la inteligencia artificial (IA) en la educación en enfermería está transformando la formación de los futuros profesionales de la salud al ofrecer experiencias de aprendizaje personalizadas y eficientes. Sin embargo, el uso de IA plantea preocupaciones éticas y pedagógicas que necesitan ser abordadas para garantizar una implementación efectiva y justa en los programas de formación. Metodología: Se realizó una revisión exhaustiva de la literatura reciente en PubMed para identificar estudios relevantes sobre la implementación de IA en la educación en enfermería. Se utilizaron los términos MeSH "inteligencia artificial," "realidad virtual," y "educación en enfermería," combinados con operadores booleanos AND y OR para refinar la búsqueda. La búsqueda se centró en artículos publicados en los últimos 5 años. Resultados: La revisión reveló que la IA puede mejorar la educación en enfermería al proporcionar herramientas de aprendizaje adaptativas y simulaciones realistas. Sin embargo, también surgieron preocupaciones sobre la ética de su uso, como la posible exacerbación de desigualdades y la dependencia excesiva de la tecnología. Los estudios resaltaron la necesidad de una regulación adecuada para abordar estos desafíos. Conclusiones: La IA tiene el potencial de revolucionar la educación en enfermería, pero su integración debe ser manejada cuidadosamente para evitar problemas éticos y pedagógicos. Es crucial que los educadores y responsables de políticas desarrollen estrategias para maximizar los beneficios y mitigar los riesgos asociados con el uso de IA en la formación de enfermería.
Descargas
Métricas
Citas
Abuzaid, M. M., Elshami, W., & Fadden, S. M. (2022). Integration of artificial intelligence into nursing practice. Health and Technology, 12(6), 1109–1115. https://doi.org/10.1007/s12553-022-00697-0
Associated Medical Services (AMS) Healthcare. (2018). Compassion in a technological world: Advancing AMS' strategic aims. http://www.ams-inc.on.ca/wp-content/uploads/2019/01/Compassion-in-a-Tech-World.pdf
Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial intelligence and reflections from educational landscape: A review of AI studies in half a century. Sustainability, 13(800). https://doi.org/10.3390/su13020800
Chang, Y. M., & Lai, C. L. (2021). Exploring the experiences of nursing students in using immersive virtual reality to learn nursing skills. Nurse Education Today, 97, 104670. https://doi.org/10.1016/j.nedt.2020.104670
De Bruyckere, P., & Kirschner, P. A. (2020). Computer-assisted learning. In A. Tatnall (Ed.), Encyclopedia of Education and Information Technologies (pp. 348–355). Springer International Publishing. https://doi.org/10.1007/978-3-030-10576-1_191
De Gagne, J. C. (2023). The State of Artificial Intelligence in Nursing Education: Past, Present, and Future Directions. International Journal of Environmental Research and Public Health, 20(6), 4884. https://doi.org/10.3390/ijerph20064884
De Gagne, J. C., Hwang, H., & Jung, D. (2023). Cyberethics in nursing education: Ethical implications of artificial intelligence. Nursing Ethics. Advance online publication. https://doi.org/10.1177/09697330231201901
European Commission. (2021). Digital Education Action Plan 2021–2027: Resetting education and training for the digital age. Retrieved March 3, 2023, from https://education.ec.europa.eu/focus-topics/digital-education/action-plan
Farghaly Abdelaliem, S. M., Dator, W. L. T., & Sankarapandian, C. (2022). The Relationship between Nursing Students' Smart Devices Addiction and Their Perception of Artificial Intelligence. Healthcare (Basel, Switzerland), 11(1), 110. https://doi.org/10.3390/healthcare11010110
Fernandes, M. N. D. F., Esteves, R. B., Teixeira, C. A. B., & Gherardi-Donato, E. C. D. S. (2018). The present and the future of Nursing in the Brave New World. Revista Escola de Enfermagem da USP, 52, e03356. https://doi.org/10.1590/S1980-220X2017031603356
Hannaford, L., Cheng, X., & Kunes-Connell, M. (2021). Predicting nursing baccalaureate program graduates using machine learning models: A quantitative research study. Nurse Education Today, 99, 104784. https://doi.org/10.1016/j.nedt.2021.104784
Horey, S., Ang, E., Yap, J., Ng, E. D., Lau, S. T., & Chui, C. K. (2019). A virtual counseling application using artificial intelligence for communication skills training in nursing education: Development study. Journal of Medical Internet Research, 21(10), e14658. https://doi.org/10.2196/14658
Liaw, S. Y., Tan, J. Z., Bin Rusli, K. D., Ratan, R., Zhou, W., Lim, S., Lau, T. C., Seah, B., & Chua, W. L. (2023). Artificial Intelligence Versus Human-Controlled Doctor in Virtual Reality Simulation for Sepsis Team Training: Randomized Controlled Study. Journal of Medical Internet Research, 25, e47748. https://doi.org/10.2196/47748
McGrow, K. (2019). Artificial intelligence: Essentials for nursing. Nursing, 49(9), 46–49. https://doi.org/10.1097/01.NURSE.0000577716.57052.8d
Nagle, L. K., Kleib, M., & Furlong, K. (2020). Digital health in Canadian schools of nursing Part A: Nurse educators’ perspectives. Quality Advancement in Nursing Education - Avancées en formation infirmière, 6(1). https://doi.org/10.17483/2368-6669.1229
National Science Foundation. (n.d.). Artificial Intelligence at NSF. Retrieved March 3, 2023, from https://www.nsf.gov/cise/ai.jsp
O’Connor, S. (2021). Artificial intelligence and predictive analytics in nursing education. Nurse Education in Practice, 56, 103224. https://doi.org/10.1016/j.nepr.2021.103224
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(7893–7925). https://doi.org/10.1007/s10639-022-10925-9
Palanica, A., Flaschner, P., Thommandram, A., Li, M., & Fossat, Y. (2019). Physicians' perceptions of chatbots in health care: Cross-sectional web-based survey. Journal of Medical Internet Research, 21(4), e12887. https://doi.org/10.2196/12887
Pepito, J. A., & Locsin, R. (2019). Can nurses remain relevant in a technologically advanced future? International Journal of Nursing Sciences, 6(1), 106–110. https://doi.org/10.1016/j.ijnss.2018.09.013
Roberts, H., Cowls, J., Morley, J., Taddeo, M., Wang, V., & Floridi, L. (2021). The Chinese approach to artificial intelligence: An analysis of policy, ethics, and regulation. AI & Society, 36(1), 59–77. https://doi.org/10.1007/s00146-020-00992-2
Risling, T., & Low, C. (2019). Advocating for safe, quality, and just care: What nursing leaders need to know about artificial intelligence in healthcare delivery. Nursing Leadership (Toronto, Ont.), 32(2), 31–45. https://doi.org/10.12927/cjnl.2019.25963
Robert, N. (2019). How artificial intelligence is changing nursing. Nursing Management, 50(9), 30-39. https://doi.org/10.1097/01.NUMA.0000578988.56622.21
Ronquillo, C. E., Peltonen, L. M., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., et al. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. Journal of Advanced Nursing, 77(9), 3707-3717. https://doi.org/10.1111/jan.14855
Schneidereith, T. A., & Thibault, J. (2023). The Basics of Artificial Intelligence in Nursing: Fundamentals and Recommendations for Educators. The Journal of Nursing Education, 62(12), 716–720. https://doi.org/10.3928/01484834-20231006-03
Shorey, S., Ang, E., Yap, J., Ng, E. D., Lau, S. T., & Chui, C. K. (2019). A Virtual Counseling Application Using Artificial Intelligence for Communication Skills Training in Nursing Education: Development Study. Journal of Medical Internet Research, 21(10), e14658. https://doi.org/10.2196/14658
Shorey, S., Ang, E. N. K., Ng, E. D., Yap, J., Lau, L. S. T., Chui, C. K., & Chan, Y. H. (2023). Evaluation of a Theory-Based Virtual Counseling Application in Nursing Education. Computers, Informatics, Nursing: CIN, 41(6), 385–393. https://doi.org/10.1097/CIN.0000000000000999
Song, K. (2023). Korea is leading an exemplary AI transition. Here is how. OECD. Retrieved March 3, 2023, from https://oecd.ai/en/wonk/korea-ai-transition
Sun, G. H., & Hoelscher, S. H. (2023). The ChatGPT storm and what faculty can do. Nurse Educator. Advance online publication. https://doi.org/10.1097/NNE.
Swan, B. A., & Haas, S. (2021). Assessing the knowledge and attitudes of registered nurses about artificial intelligence in nursing and health care. Nursing Economic$, 39(3), 139-143.
Topaz, M., Murga, L., Gaddis, K. M., McDonald, M. V., Bar-Bachar, O., Goldberg, Y., et al. (2019). Mining fall-related information in clinical notes: Comparison of rule-based and novel word embedding-based machine learning approaches. Journal of Biomedical Informatics, 90, 103103. https://doi.org/10.1016/j.jbi.2019.103103
Zhou, Y., Li, Z., & Li, Y. (2021). Interdisciplinary collaboration between nursing and engineering in health care: A scoping review. International Journal of Nursing Studies, 117, 103900. https://doi.org/10.1016/j.ijnurstu.2021.103900
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2024 Diana Elvira Narváez Bastidas, Jamel Vanessa Ocampo Rodríguez, María Paulina Morales Guijarro, Sonia Abigail Cevallos Cevallos
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.