Wang Peng, Zhang Qian, Zhang Wenyu, Sun Jing
The International Medical Services, Peking Union Medical College Hospital, Peking, China.
The Neonatal Intensive Care Unit, Peking Union Medical College Hospital, Peking, China.
Front Med (Lausanne). 2024 Dec 18;11:1521712. doi: 10.3389/fmed.2024.1521712. eCollection 2024.
With the development of ChatGPT, the number of studies within the nursing field has increased. The sophisticated language capabilities of ChatGPT, coupled with its exceptional precision, offer significant support within the nursing field, which includes clinical nursing, nursing education, and the clinical decision-making process. Preliminary findings suggest positive outcomes, underscoring its potential as a valuable resource for enhancing clinical care. However, a comprehensive analysis of this domain is lacking, and the application of bibliometric methods remains rare. This study aims to describe and predict the developmental trajectory of the discipline, identify research hotspots and trends, and provide a comprehensive framework for the integration of ChatGPT in nursing.
Following the development of a search strategy in collaboration with librarians, the implementation of this strategy occurred in the Web of Science Core Collection (WoSCC) on June 30, 2024. For bibliometric and visual analyses-including evaluations of sources, institutions, countries, author collaboration networks, and keywords-Bibliometrix (version 4.4.2) and CiteSpace (version 6.2.R2 Basic) were employed.
A total of 81 articles published by 67 authors were retrieved from the Web of Science Core Collection database, covering the period of June 30, 2024. The number of published studies has exhibited an increasing trend. The "European Journal of Cardiovascular Nursing" emerged as the most productive journals, while the USA, the UK, and China were identified as the leading countries in terms of publication output. The top 10 keywords identified in this study include artificial intelligence, nursing education, large language models, ChatGPT, natural language processing, generative artificial intelligence, care, nursing practice, clinical decision-making, and deep learning.
ChatGPT is an emerging tool in the nursing field, currently in the foundational research phase. While there is significant international collaboration, cooperation among author groups remains somewhat limited. Studies focusing on ChatGPT in nursing primarily concentrate on two key themes: (1) the deep learning of ChatGPT in nursing and (2) the feasibility of its application. It is essential for nurses across various specialties to collaborate in exploring the diverse applications of ChatGPT within their domains, thereby fostering the ongoing development and enhancement of this technology.
随着ChatGPT的发展,护理领域的研究数量有所增加。ChatGPT先进的语言能力及其卓越的精准度,为护理领域(包括临床护理、护理教育和临床决策过程)提供了重要支持。初步研究结果显示出积极成果,凸显了其作为提升临床护理宝贵资源的潜力。然而,目前缺乏对该领域的全面分析,且文献计量方法的应用仍然较少。本研究旨在描述和预测该学科的发展轨迹,识别研究热点和趋势,并为ChatGPT在护理中的整合提供全面框架。
与图书馆员合作制定检索策略后,于2024年6月30日在科学网核心合集(WoSCC)上实施该策略。对于文献计量和可视化分析(包括对来源、机构、国家、作者合作网络和关键词的评估),使用了Bibliometrix(版本4.4.2)和CiteSpace(版本6.2.R2 Basic)。
从科学网核心合集数据库中检索到67位作者发表的81篇文章,涵盖2024年6月30日之前的时间段。已发表研究的数量呈上升趋势。《欧洲心血管护理杂志》成为发文量最多的期刊,而美国、英国和中国则是发文量领先的国家。本研究确定的前10个关键词包括人工智能、护理教育、大语言模型、ChatGPT、自然语言处理、生成式人工智能、护理、护理实践、临床决策和深度学习。
ChatGPT是护理领域的一种新兴工具,目前处于基础研究阶段。虽然存在大量国际合作,但作者群体之间的合作仍较为有限。护理领域中关于ChatGPT的研究主要集中在两个关键主题:(1)ChatGPT在护理中的深度学习;(2)其应用的可行性。各专业的护士必须合作探索ChatGPT在其领域的各种应用,从而促进该技术的持续发展和完善。