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The William Harvey Research Institute - Faculty of Medicine and Dentistry

Comparing preprints and their finalized publications during the pandemic

A new study involving Queen Mary University of London researchers has explored how preprints compare with their published versions. 

Cartoon hand with magnifying glass in front of papers

Cartoon hand with magnifying glass in front of papers. Credit:

Preprinting, the sharing of freely available manuscripts prior to peer-review, has been on the rise in the biosciences since 2013 and experienced a surge during the Covid-19 pandemic, expediting the dissemination of timely research.

But concerns over the quality of preprints have existed since the emergence of preprinting in the sciences.

A new study led by Queen Mary’s Dr Jonathon Coates manually compared over 180 preprints, posted on bioRxiv and medRxiv, to their published versions in the first 4 months of the Covid-19 pandemic. Dr Coates notes, “Approximately 40 per cent of the early Covid-19 research was first shared as a preprint and these were used in policy and public health decisions. Therefore, knowing the quality of these preprints is vital in having trust in science at a time when many are attempting to erode that trust.”

Coates and his colleagues compared all the Covid-19 preprints posted and published within the first four months of the pandemic and found that over 83 per cent of Covid and 93 per cent of non-Covid-related life sciences articles do not change from their preprint to final published versions.

Coates adds, “With such a large proportion of early Covid-19 literature shared as non-peer reviewed preprints it is essential to know if those studies are reliable or not. By manually comparing the preprints to their peer reviewed, published, versions we show that over 83 per cent of Covid-19 and 93 per cent of non-Covid preprints are reliable and trustworthy.”

The findings, published in open access journal PLOS Biology, were supported by another publication in the same journal, led by the University of Pennsylvania’s Perelman School of Medicine, which used machine learning and textual analytics to explore the relationships between nearly 18,000 bioRxiv preprints and their published version.

Dr. Jonathan Coates is a Postdoctoral Researcher at the Centre for Microvascular Research.

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