Prevalence and Content of Generative Artificial Intelligence Use Policies in Iranian Medical Science Journals

The rapid growth of generative artificial intelligence (AI) tools has created new opportunities for scientific publishing while also introducing challenges related to research integrity and editorial ethics. Although awareness of these opportunities and challenges is increasing globally, there is limited evidence regarding how Iranian journals have addressed the use of AI through formal policies in scientific publishing. This study investigates the prevalence and content of AI use policies in Iranian medical science journals.

A cross-sectional descriptive study was conducted using medical journals listed in the Iranian Research Information System (IRIS). Of the 429 journals initially identified, inactive or inaccessible journals were excluded, resulting in a final sample of 411 journals. From August to October 2025, each journal website was manually examined using a structured checklist designed to assess 25 variables related to the existence and specific content of AI use policies. The data were analyzed using descriptive and inferential statistical methods in Microsoft Excel and SPSS.

Among 411 journals, 117 (28.5%) had a publicly accessible AI use policy. The adoption of such policies was significantly more prevalent in English-language journals, those indexed in major international databases, and journals affiliated with the Committee on Publication Ethics (COPE). Among the journals with policies, the most commonly included elements were mandatory disclosure of AI use (99.1%), clarification of permission type (98.3%), and author responsibility (88.0%). In contrast, only a small proportion of journals specified the consequences of policy violations or provided guidance on AI-assisted translation.

The findings indicate that AI policy development within Iranian medical science journals remains in its nascent stages. It is essential to establish clearer and more comprehensive AI usage policies to promote transparency, accountability, and responsible AI practices in scientific publishing.