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. 2021 Jun 22:10:491.
doi: 10.12688/f1000research.53874.2. eCollection 2021.

Rates and predictors of data and code sharing in the medical and health sciences: Protocol for a systematic review and individual participant data meta-analysis

Affiliations

Rates and predictors of data and code sharing in the medical and health sciences: Protocol for a systematic review and individual participant data meta-analysis

Daniel G Hamilton et al. F1000Res. .

Abstract

Numerous studies have demonstrated low but increasing rates of data and code sharing within medical and health research disciplines. However, it remains unclear how commonly data and code are shared across all fields of medical and health research, as well as whether sharing rates are positively associated with implementation of progressive policies by publishers and funders, or growing expectations from the medical and health research community at large. Therefore this systematic review aims to synthesise the findings of medical and health science studies that have empirically investigated the prevalence of data or code sharing, or both. Objectives include the investigation of: (i) the prevalence of public sharing of research data and code alongside published articles (including preprints), (ii) the prevalence of private sharing of research data and code in response to reasonable requests, and (iii) factors associated with the sharing of either research output (e.g., the year published, the publisher's policy on sharing, the presence of a data or code availability statement). It is hoped that the results will provide some insight into how often research data and code are shared publicly and privately, how this has changed over time, and how effective some measures such as the institution of data sharing policies and data availability statements have been in motivating researchers to share their underlying data and code.

Keywords: Code sharing; Data sharing; Health sciences; Medicine; Meta-analysis; Systematic review.

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Conflict of interest statement

Competing interests: DGH is a PhD candidate supported by an Australian Commonwealth Government Research Training Program Scholarship. The Laura and John Arnold Foundation funds the RIAT Support Centre (no grant number), which supports the salaries of ARF and KH. KH's project was supported by the Food and Drug Administration (FDA) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award U01FD005946 totalling US$5,000 with 100 per cent funded by FDA/HHS. The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement, by FDA/HHS, or the U.S. Government. The authors declare that no grants were involved in supporting this work.

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