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Related Concept Videos

Role of Communication in the Nursing Process I: Assessment and Diagnosis01:25

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  1. Home
  3. Research Domains
  5. Information And Computing Sciences
  7. Artificial Intelligence
  9. Natural Language Processing
  11. Prevalence Of Words And Phrases Associated With Large Language Model-generated Text In The Nursing Literature.
  1. Home
  3. Research Domains
  5. Information And Computing Sciences
  7. Artificial Intelligence
  9. Natural Language Processing
  11. Prevalence Of Words And Phrases Associated With Large Language Model-generated Text In The Nursing Literature.

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

Hannah E Bailey1, Heather Carter-Templeton, Gabriel M Peterson

  • 1Author 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).

Computers, Informatics, Nursing : CIN
|January 2, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

Generative artificial intelligence (AI) tools are increasingly used in nursing publications, with notable increases in AI-associated terms appearing in articles since 2023. This trend necessitates developing verification methods and transparent use policies for AI-generated content in scholarly works.

Keywords:
Artificial intelligence (AI)Generative AI useLarge language model (LLM)–based generative AINursing articles

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Area of Science:

  • Nursing Research
  • Health Informatics
  • Artificial Intelligence

Background:

  • Generative artificial intelligence (AI) tools are rapidly evolving and becoming accessible across disciplines.
  • Distinguishing AI-generated text from human writing is challenging, raising concerns about unverified information in scholarly publications.
  • The integration of AI into academic writing presents both opportunities and challenges for researchers and publishers.

Purpose of the Study:

  • To investigate the prevalence and extent of generative AI usage in published nursing articles.
  • To identify specific linguistic markers indicative of AI-generated content within the nursing literature.

Main Methods:

  • Utilized the Dimensions database to retrieve nursing articles containing terms related to generative AI.
Words and phrases associated with LLM-generated text
  • Conducted a keyword analysis to detect words and phrases disproportionately associated with large language model-based AI.
  • Analyzed trends in the appearance of these terms over time, with a focus on the period starting in 2023.

    • Main Results:

    • Observed a significant increase in the occurrence of specific nouns, verbs, adverbs, and phrases associated with generative AI in nursing articles from 2023 onwards.
    • These linguistic patterns suggest a growing adoption of generative AI tools by authors in the nursing field.
    • The findings highlight a discernible shift in scholarly writing practices influenced by emerging AI technologies.

    Conclusions:

    • Generative AI is increasingly impacting the landscape of published nursing research.
    • Nurses, authors, reviewers, and editors must prepare for the widespread presence of AI in scholarly communication.
    • Developing robust methods for content verification, establishing policies for transparent AI use, and ensuring the safety of evidence consumers are critical next steps.