Journal of Occupational
Health and Epidemiology
Rafsanjan university Of medical sciences
Volume 15, Issue 1 (Winter 2026)
J Occup Health Epidemiol 2026, 15(1): 1-2 |
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Vazirinejad R, Ahmadirad H. A Framework for Transparent Disclosure of Generative AI in Scholarly Publications. , J Occup Health Epidemiol. 2026; 15 (1) :1-2
URL: http://johe.rums.ac.ir/article-1-1181-en.html
URL: http://johe.rums.ac.ir/article-1-1181-en.html
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1- Professor, Occupational Safety and Health Research Center, NICICO, World Safety Organization, Rafsanjan University of Medical Sciences, Rafsanjan, Iran.
2- Ph.D. in Clinical Biochemistry, Pistachio Safety Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. ,hahmadirad@yahoo.com
2- Ph.D. in Clinical Biochemistry, Pistachio Safety Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. ,
Article history
Received: 2025/12/18
Accepted: 2026/03/18
ePublished: 2026/03/30
Accepted: 2026/03/18
ePublished: 2026/03/30
Subject:
Epidemiology
Keywords: No Keywords
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On the brink of the digital transformation of work environments, we are witnessing the emergence of a new paradigm in occupational safety and health. Algorithmic management, as one of the prominent achievements of Industry 5 (Fifth industrial revolution), holds the potential to fundamentally transform traditional HSE approaches. This evolution aligns with the directions of the International Labour Organization (ILO) in promoting "decent work" and "adequate protection for all workers," which form the core of the organization's theme for the upcoming year.
Nowadays, the use of artificial intelligence (AI) in medicine and scientific research has become one of the most important concerns due to its complex mix of positive and negative consequences. The rapid rise of generative AI in recent years has further established it as a transformative technology in scholarly research and authorship, offering immense potential to enhance the quality of scientific work. However, its use requires ultimate caution and strict transparency measures, as a lack of oversight can lead to confusion and doubt regarding authorship integrity and the accuracy of generated content. In this evolving landscape, the ethical responsibility of researchers and authors remains paramount to ensure the trustworthy integration of AI in scientific advancement.
Clearly stating how and to what extent AI was used is crucial not only for maintaining epistemic trust among experts, researchers, and the general readership but also as a fundamental requirement for upholding the integrity of scientific standards, ensuring the fidelity of the research process, and strengthening the overall academic publishing ecosystem.
This Editorial outlines an essential framework and methodologies for authors to transparently disclose their use of artificial intelligence (AI) tools in scholarly publications. It will discuss the necessary level of detail in reporting and elucidate the significant benefits of such transparency for both the scientific and cultural communities.
To this end, authors are mandated to provide an explicit declaration within the manuscript’s accompanying cover letter, detailing any instances of generative artificial intelligence (AI) utilization. This disclosure must include granular details regarding the specific AI employed and its function. Furthermore, to ensure clarity for both reviewers and readers, these details should be reiterated at the end of the manuscript itself. Such transparency is essential for maintaining the integrity and enabling the informed execution of the peer-review process.
For instance, Adam Cheng (2025) examined the ethical aspects of using artificial intelligence in academic writing, specifically clarifying their use of ChatGPT through a dedicated statement at the end of their article [1]. This practice exemplifies the transparency we now
require.
Nowadays, the use of artificial intelligence (AI) in medicine and scientific research has become one of the most important concerns due to its complex mix of positive and negative consequences. The rapid rise of generative AI in recent years has further established it as a transformative technology in scholarly research and authorship, offering immense potential to enhance the quality of scientific work. However, its use requires ultimate caution and strict transparency measures, as a lack of oversight can lead to confusion and doubt regarding authorship integrity and the accuracy of generated content. In this evolving landscape, the ethical responsibility of researchers and authors remains paramount to ensure the trustworthy integration of AI in scientific advancement.
Clearly stating how and to what extent AI was used is crucial not only for maintaining epistemic trust among experts, researchers, and the general readership but also as a fundamental requirement for upholding the integrity of scientific standards, ensuring the fidelity of the research process, and strengthening the overall academic publishing ecosystem.
This Editorial outlines an essential framework and methodologies for authors to transparently disclose their use of artificial intelligence (AI) tools in scholarly publications. It will discuss the necessary level of detail in reporting and elucidate the significant benefits of such transparency for both the scientific and cultural communities.
To this end, authors are mandated to provide an explicit declaration within the manuscript’s accompanying cover letter, detailing any instances of generative artificial intelligence (AI) utilization. This disclosure must include granular details regarding the specific AI employed and its function. Furthermore, to ensure clarity for both reviewers and readers, these details should be reiterated at the end of the manuscript itself. Such transparency is essential for maintaining the integrity and enabling the informed execution of the peer-review process.
For instance, Adam Cheng (2025) examined the ethical aspects of using artificial intelligence in academic writing, specifically clarifying their use of ChatGPT through a dedicated statement at the end of their article [1]. This practice exemplifies the transparency we now
require.
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