@Article{info:doi/10.2196/54987,
author="Zhang, Fang
and Liu, Xiaoliu
and Wu, Wenyan
and Zhu, Shiben",
title="Evolution of Chatbots in Nursing Education: Narrative Review",
journal="JMIR Med Educ",
year="2024",
month="Jun",
day="13",
volume="10",
pages="e54987",
keywords="nursing education; chatbots; artificial intelligence; narrative review; ChatGPT",
abstract="Background: The integration of chatbots in nursing education is a rapidly evolving area with potential transformative impacts. This narrative review aims to synthesize and analyze the existing literature on chatbots in nursing education. Objective: This study aims to comprehensively examine the temporal trends, international distribution, study designs, and implications of chatbots in nursing education. Methods: A comprehensive search was conducted across 3 databases (PubMed, Web of Science, and Embase) following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagram. Results: A total of 40 articles met the eligibility criteria, with a notable increase of publications in 2023 (n=28, 70{\%}). Temporal analysis revealed a notable surge in publications from 2021 to 2023, emphasizing the growing scholarly interest. Geographically, Taiwan province made substantial contributions (n=8, 20{\%}), followed by the United States (n=6, 15{\%}) and South Korea (n=4, 10{\%}). Study designs varied, with reviews (n=8, 20{\%}) and editorials (n=7, 18{\%}) being predominant, showcasing the richness of research in this domain. Conclusions: Integrating chatbots into nursing education presents a promising yet relatively unexplored avenue. This review highlights the urgent need for original research, emphasizing the importance of ethical considerations. ",
issn="2369-3762",
doi="10.2196/54987",
url="https://mededu.jmir.org/2024/1/e54987",
url="https://doi.org/10.2196/54987"
}