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护理文献中与大语言模型生成文本相关的词汇和短语的流行情况。

Prevalence of Words and Phrases Associated With Large Language Model-Generated Text in the Nursing Literature.

作者信息

Bailey Hannah E, Carter-Templeton Heather, Peterson Gabriel M, Oermann Marilyn H, Owens Jacqueline K

机构信息

Author Affiliations: Data Driven WV, John Chambers College of Business and Economics (Ms Bailey), and School of Nursing, West Virginia University (Dr Carter-Templeton), Morgantown; School of Library and Information Sciences, North Carolina Central University, Durham (Dr Peterson); Duke University School of Nursing, Durham, NC (Dr Oermann); Dwight Schar College of Nursing and Health Sciences, Ashland University, OH (Dr Owens).

出版信息

Comput Inform Nurs. 2025 Apr 1;43(4):e01237. doi: 10.1097/CIN.0000000000001237.

Abstract

All disciplines, including nursing, may be experiencing significant changes with the advent of free, publicly available generative artificial intelligence tools. Recent research has shown the difficulty in distinguishing artificial intelligence-generated text from content that is written by humans, thereby increasing the probability for unverified information shared in scholarly works. The purpose of this study was to determine the extent of generative artificial intelligence usage in published nursing articles. The Dimensions database was used to collect articles with at least one appearance of words and phrases associated with generative artificial intelligence. These articles were then searched for words or phrases known to be disproportionately associated with large language model-based generative artificial intelligence. Several nouns, verbs, adverbs, and phrases had remarkable increases in appearance starting in 2023, suggesting use of generative artificial intelligence. Nurses, authors, reviewers, and editors will likely encounter generative artificial intelligence in their work. Although these sophisticated and emerging tools are promising, we must continue to work toward developing ways to verify accuracy of their content, develop policies that insist on transparent use, and safeguard consumers of the evidence they generate.

摘要

随着免费的、公开可用的生成式人工智能工具的出现,包括护理在内的所有学科可能都在经历重大变革。最近的研究表明,很难区分人工智能生成的文本和人类撰写的内容,从而增加了学术作品中分享未经证实信息的可能性。本研究的目的是确定已发表的护理文章中生成式人工智能的使用程度。Dimensions数据库用于收集至少出现一次与生成式人工智能相关的单词和短语的文章。然后在这些文章中搜索已知与基于大语言模型的生成式人工智能不成比例相关的单词或短语。从2023年开始,几个名词、动词、副词和短语的出现频率显著增加,这表明使用了生成式人工智能。护士、作者、审稿人和编辑在工作中可能会遇到生成式人工智能。尽管这些复杂的新兴工具很有前景,但我们必须继续努力开发方法来验证其内容的准确性,制定坚持透明使用的政策,并保护其生成证据的消费者。

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