Assessment of Generative Artificial Intelligence Policies across Dermatology Journals

Abstract

INTRODUCTION: The rapid integration of generative artificial intelligence (GenAI) into academic research has prompted ethical and regulatory concerns, particularly regarding its responsible use in scholarly publishing. Despite emerging recommendations from international organizations such as the Committee on Publication Ethics (COPE) and the International Committee of Medical Journal Editors (ICMJE), journal-specific guidance remains inconsistent. METHODS: This study evaluated the presence and characteristics of GenAI-related policies across 92 dermatology journals indexed in the 2024 Journal Citation Reports. Four reviewers independently assessed author instructions and publisher policies, collecting journal metrics, and applying logistic regression to explore associations with guideline adoption. RESULTS: GenAI-specific guidance was found in 82.6% of journals, with 60.5% linking to publisher-level policies. Most journals (90.8%) prohibited GenAI authorship and required author accountability, yet only 2.6% referenced ICMJE guidance. Disclosure of GenAI use was mandated by 98.7%, although only a minority required specification of tool version (28.0%) or manufacturer (17.3%). GenAI image generation was addressed in 55.3% of policies, with ChatGPT mentioned by 46.1% of journals. COPE membership and use of COPE AI guidance were significantly associated with the presence of journal-level GenAI policies. While journals with GenAI guidance exhibited higher impact and citation metrics in univariable analysis, no predictors remained significant in multivariable models. CONCLUSION: These findings highlight broad yet uneven adoption of GenAI policies in dermatology publishing. Gaps in specificity, transparency, and alignment with international standards may pose risks to research integrity, emphasizing the need for clearer, standardized, and field-specific editorial guidance on GenAI use.

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