Systematic reviewers' perspectives on sharing review data, analytic code, and other materials: A survey

Background

There are many benefits of sharing data, analytic code, and other materials, yet these items are infrequently shared among systematic reviews (SRs). It is unclear which factors influence authors' decisions to share data, code, or materials when publishing their SRs. Therefore, we aimed to explore systematic reviewers' perspectives on the importance of sharing review materials and factors that might influence such practices.

Methods

We searched PubMed for SRs published from January to April 2021, from which we randomly allocated 50% to this survey and 50% to another survey on the replication of SRs. We sent an electronic survey to authors of these SRs (n = 4671) using Qualtrics. Quantitative responses were summarized using frequency analysis. Free-text answers were coded using an inductive approach.

Results

The response rate was 9% (n = 417). Most participants supported routine sharing of search strategies (84%) but fewer for analytic code (43%) or files documenting data preparation (38%). Most participants agreed that normative practices within the discipline were an important facilitator (78%). Major perceived barriers were lack of time (62%) and suitable sharing platforms (31%). Few participants were required by funders (19%) or institutions (17%) to share data, and only 12% of participants reported receiving training on data sharing. Commonly perceived consequences of data sharing were lost opportunities for future publications (50%), misuse of data (48%), and issues with intellectual property (40%). In their most recent reviews, participants who did not share data cited the lack of journal requirements (56%) or noted the review did not include any statistical analysis that required sharing (29%).

Conclusion

Certain types of review materials were considered unnecessary for sharing, despite their importance to the review's transparency and reproducibility. Structural barriers and concerns about negative consequences hinder data sharing among systematic reviewers. Normalization and institutional incentives are essential to promote data-sharing practices in evidence-synthesis research.