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Journal data-sharing policies and its impact in publications: A cross-sectional study protocol

Pinge Zhao, Xin Zhang, Liandi Dai, Baoguo Ma, Yu-Ting Duan, Yan Xu, Hongmei Wei, Shengwei Wu et al.

PLoS ONE, 2025

Abstract

Responsible data sharing in clinical research can enhance the transparency and reproducibility of research evidence, thereby increasing the overall value of research. Since 2024, more than 5,000 journals have adhered to the International Committee of Medical Journal Editors (ICMJE) Data Sharing Statement (DSS) to promote data sharing. However, due to the significant effort required for data sharing and the scarcity of academic rewards, data availability in clinical research remains suboptimal. This study aims to explore the impact of biomedical journal policies and available supporting information on the implementation of data availability in clinical research publications This cross-sectional study will select 303 journals and their latest publications as samples from the biomedical journals listed in the Web of Science Journal Citation Reports based on stratified random sampling according to the 2023 Journal Impact Factor (JIF). Two researchers will independently extract journal data-sharing policies from the submission guidelines of eligible journals and data-sharing details from publications using a pre-designed form from Apr 2025 to Dec 2025. The data sharing levels of publications will be based on the openness of the data-sharing mechanism. Binomial logistic regression analyses will be used to identify potential journal factors that affect publication data-sharing levels. This protocol has been registered in Open Science Framework (OSF) Registries:…

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Evidence Hub reads this as a cross-sectional. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.

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