A Bibliometric Analysis of Chatbot or ChatGPT in Nursing Fields from 2022 to 2024
DOI:
https://doi.org/10.31436/imjm.v25i02.2809Keywords:
Chatbot, ChatGPT, Generative Artificial Intelligence, Nursing, EducationAbstract
Nursing education has undergone a significant transformation as a result of artificial intelligence(AI). Chatbots, specifically ChatGPT, have emerged as vital AI technologies within the nursing domain as it is a computer program designed to simulate human conversation through text or voice interactions. This study aims to conduct a bibliometric analysis to gain insights into the publication trends, citation impact, and thematic evolution in nursing education and practice concerning ChatGPT and chatbots. A comprehensive bibliometric analysis was performed using VOSViewer, concentrating on citation networks for data analysis and visualisation. A review of LENS.org identified 344 relevant research publications regarding chatbots and ChatGPT within the nursing discipline, all of which were utilised in the study. The study examined various aspects, including types of publications, prominent authors, leading journals, participating nations, institutions, and the impact of ChatGPT on nursing practice. The primary objectives included categorising the papers, identifying the most influential authors, delineating the prominent areas and institutions in the field, and examining the impact of ChatGPT on nursing education and practice. The findings indicate that ChatGPT positively impacts nursing education by enhancing learning experiences, improving communication, and aiding clinical decision-making. The findings indicate that journal articles accounted for 76% of publications, with the U.S. leading in research output. The findings indicate that ChatGPT positively impacts nursing education by enhancing learning experiences, improving communication, and aiding clinical decision-making. Future research should focus on establishing frameworks for integrating ChatGPT into nursing education, addressing ethical implications, and assessing the long-term impacts on patient care.
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