ArticleThe American journal of nursing2025
Using Artificial Intelligence for Scholarly Writing.
Article in The American journal of nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Digital Mental Health Research Priorities, Revisited for the AI and Large Language Model Era.JMIR mental health · 2026Article
- AI in Oncology: Opportunity and Accountability.Journal of the advanced practitioner in oncology · 2026Article
- ChatGPT in healthcare: perceptions, ethical considerations, and practice implications among healthcare professionals in Ecuador and other countries in the Americas: a cross-sectional survey study.Frontiers in digital health · 2026Article
- Navigating artificial intelligence in qualitative research: ethical and practical considerations from concept to publication.Frontiers in research metrics and analytics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
abstractThe widespread availability of generative artificial intelligence (genAI) continues to transform the scholarly communication process. With wide access to genAI tools, authors now not only have the benefits these tools can provide, such as creation of text, tables, and figures, but also the responsibility to use these tools with integrity and transparency. Examples of concerns about the use of genAI tools include ethical and legal breaches; inaccurate, biased, or fabricated content; and lack of accountability. Given the potential for serious harm to patients as well as the undermining of the credibility of scholarly communication with the use of unchecked content, it is essential for nurse authors to also include their judgment and subject matter expertise in the preparation of a scholarly manuscript that includes AI-generated information. This article offers a brief overview of recent research findings related to the use of genAI tools to support scholarly writing and provides guidelines for clinicians, educators, and other nurse authors on the appropriate use of AI in the preparation of manuscripts. Information is also provided about authorship, accuracy of content and references, biases and misrepresentations within AI-generated content, plagiarism, and appropriate disclosure of AI tools in manuscript preparation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.