Abstract
Abstract
Objective
To evaluate whether and how the radiological journals present their policies on the use of large language models (LLMs), and identify the journal characteristic variables that are associated with the presence.
Methods
In this meta-research study, we screened Journals from the Radiology, Nuclear Medicine and Medical Imaging Category, 2022 Journal Citation Reports, excluding journals in non-English languages and relevant documents unavailable. We assessed their LLM use policies: (1) whether the policy is present; (2) whether the policy for the authors, the reviewers, and the editors is present; and (3) whether the policy asks the author to report the usage of LLMs, the name of LLMs, the section that used LLMs, the role of LLMs, the verification of LLMs, and the potential influence of LLMs. The association between the presence of policies and journal characteristic variables was evaluated.
Results
The LLM use policies were presented in 43.9% (83/189) of journals, and those for the authors, the reviewers, and the editor were presented in 43.4% (82/189), 29.6% (56/189) and 25.9% (49/189) of journals, respectively. Many journals mentioned the aspects of the usage (43.4%, 82/189), the name (34.9%, 66/189), the verification (33.3%, 63/189), and the role (31.7%, 60/189) of LLMs, while the potential influence of LLMs (4.2%, 8/189), and the section that used LLMs (1.6%, 3/189) were seldomly touched. The publisher is related to the presence of LLM use policies (p < 0.001).
Conclusion
The presence of LLM use policies is suboptimal in radiological journals. A reporting guideline is encouraged to facilitate reporting quality and transparency.
Critical relevance statement
It may facilitate the quality and transparency of the use of LLMs in scientific writing if a shared complete reporting guideline is developed by stakeholders and then endorsed by journals.
Key Points
The policies on LLM use in radiological journals are unexplored.
Some of the radiological journals presented policies on LLM use.
A shared complete reporting guideline for LLM use is desired.
Graphical Abstract
Funder
National Natural Science Foundation of China
Yangfan Project of Science and Technology Commission of Shanghai Municipality
Publisher
Springer Science and Business Media LLC