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Open Science and COVID-19 Randomized Controlled Trials: Examining Open Access, Preprinting, and Data Sharing-Related Practices During the Pandemic

Authors: John A. Borghi; Cheyenne Payne; Lily Ren; Amanda L. Woodward; Connie Wong; Christopher Stave;

Open Science and COVID-19 Randomized Controlled Trials: Examining Open Access, Preprinting, and Data Sharing-Related Practices During the Pandemic

Abstract

AbstractThe COVID-19 pandemic has brought substantial attention to the systems used to communicate biomedical research. In particular, the need to rapidly and credibly communicate research findings has led many stakeholders to encourage researchers to adopt open science practices such as posting preprints and sharing data. To examine the degree to which this has led to the adoption of such practices, we examined the “openness” of a sample of 539 published papers describing the results of randomized controlled trials testing interventions to prevent or treat COVID-19. The majority (56%) of the papers in this sample were free to read at the time of our investigation and 23.56% were preceded by preprints. However, there is no guarantee that the papers without an open license will be available without a subscription in the future, and only 49.61% of the preprints we identified were linked to the subsequent peer-reviewed version. Of the 331 papers in our sample with statements identifying if (and how) related datasets were available, only a paucity indicated that data was available in a repository that facilitates rapid verification and reuse. Our results demonstrate that, while progress has been made, there is still a significant mismatch between aspiration and the practice of open science in an important area of the COVID-19 literature.Open MaterialsWe are committed to making the details of our research process as open as possible. The data and code that underlie our analyses are archived and published through the Dryad Data Repository (https://doi.org/10.5061/dryad.mkkwh7137). Documentation and instructions for manuscript screening and data extraction are available on Protocols.io (https://dx.doi.org/10.17504/protocols.io.x54v9jx7zg3e/v1). Author contributions are outlined in Supplementary Table 1.

Arrizabalaga, O., Otaegui, D., Vergara, I., Arrizabalaga, J., & Méndez, E. (2020). Open Access Fraser, N., Brierley, L., Dey, G., Polka, J. K., Pálfy, M., Nanni, F., & Coates, J. A. (2021). The Li, R., von Isenburg, M., Levenstein, M., Neumann, S., Wood, J., & Sim, I. (2021). COVID-19 Rudis, B., Gandy, D., Breza, A., Jütte, M., & Campbell, P. (2019). waffle: Create Waffle Chart Manipulation. https://dplyr.tidyverse.org, https://github.com/tidyverse/dplyr Wu, F., Zhao, S., Yu, B., Chen, Y.-M., Wang, W., Song, Z.-G., Hu, Y., Tao, Z.-W., Tian, J.-H., Pei, Y.-Y., Yuan, M.-L., Zhang, Y.-L., Dai, F.-H., Liu, Y., Wang, Q.-M., Zheng, J.-J., Xu, L., Holmes, E. C., & Zhang, Y.-Z. (2020). A new coronavirus associated with human respiratory disease in China. Nature, 579(7798), 265-269.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Funded by
WT
Project
  • Funder: Wellcome Trust (WT)
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