Data sharing in acupuncture meta-analyses: Associations with journal policies and practical considerations.

Background: Data sharing can reduce research waste, enable researchers to avoid duplicating efforts, and allow resources to be effectively directed towards addressing new clinical questions. This study aimed to evaluate data sharing practices and identify associated factors in acupuncture meta-analyses. Methods: A PubMed search identified meta-analyses of any type of acupuncture (April 2022 to December 2023). Journal guidelines were classified by data sharing policies, and their associations with data availability statements (DASs) and data availability, were examined using chi-squared tests or generalised estimating equations analyses. Results: Of 3713 studies, 300 were included. Articles published in journals with data sharing policies were more likely to include DASs compared to those without (75.8 % vs. 21.7 %, Conclusions: Mandatory journal data sharing policies were associated with more frequent inclusion of DASs and provision of raw data, but neither a policy nor a DAS alone ensured reusable datasets. Mandatory policies paired with adequate training and supports may help improve transparency, promote reusability and reproducibility of results, and reduce research waste.