Data sharing statements in five high-impact anesthesiology journals (2020–2023): a cross-sectional study

Purpose: In this study, we sought to evaluate the presence, quality, and accessibility of data sharing statements (DSS) in research articles published in five high-impact anesthesiology journals from 2020 to 2023. Data sharing is foundational to research transparency and reproducibility. As anesthesiology evolves, understanding how DSS are implemented in selected high-impact journals can inform open science efforts within anesthesiology research. Methods: We conducted a cross-sectional study of five top-ranked anesthesiology journals selected using 2023 Clarivate Journal Impact Factor (JIF) rankings. Eligible studies (2020–2023) were screened in duplicate using Rayyan, and data were extracted using a structured Google Form. We used a large language model (ChatGPT, GPT-4) to aid in the exploratory thematic development of DSS, with manual validation by investigators. Results: Among 1,123 included articles, DSS prevalence varied by journal and year. In Anaesthesia, Critical Care & Pain Medicine, articles with DSS increased from 15% (4/26) in 2020 to 30% (9/30) in 2023, whereas the prevalence of DSS remained below 8% in Anesthesia & Analgesia. Government-funded studies were more likely to include DSS (β = 0.734, P = 0.047), while higher JIF was negatively associated with DSS inclusion (β = −0.298, P = 0.008). Thematic analysis showed “Conditional Data Availability” was the most frequent DSS type (74%). Of authors contacted, 28% responded, and 14% ultimately agreed to share data for replication. Conclusions: We found that DSS were underused in leading anesthesiology journals. Strengthening journal policies, funder mandates, and education on data sharing practices may promote greater transparency in anesthesia research. Because our analysis focused on a limited sample of journals, findings may not be generalizable to the entire field of anesthesiology.