Crunching the numbers. Responsibly.
Preprints in biology are becoming more popular, but only a small fraction of the articles published in peer-reviewed journals have previously been released as preprints. To examine whether releasing a preprint on bioRxiv was associated with the attention and citations received by the corresponding peer-reviewed article, we assembled a dataset of 74,239 articles, 5,405 of which had a preprint, published in 39 journals. Using log-linear regression and random-effects meta-analysis, we found that articles with a preprint had, on average, a 49% higher Altmetric Attention Score and 36% more citations than articles without a preprint. These associations were independent of several other article- and author-level variables (such as scientific subfield and number of authors), and were unrelated to journal-level variables such as access model and Impact Factor. This observational study can help researchers and publishers make informed decisions about how to incorporate preprints into their work.
articles with a preprint had, on average, a 49% higher Altmetric Attention Score and 36% more citations than articles without a preprint
large adjusted observational analysis supports the association, but residual selection prevents causal interpretation
These associations were independent of several other article- and author-level variables, and were unrelated to journal-level variables such as access model and Impact Factor
adjusted journal models and meta-regression support conditional associations, subject to unmeasured confounding
the amount of time between release of the preprint and publication of the article was positively associated with the article’s Attention Score, but not its citations
secondary observational meta-analysis supports the stated association without establishing its cause
These effect sizes were ~4 times larger than those for having an author with an affiliation in the U.S. or at a Nature Index institution
reported coefficient comparisons support the relative magnitude within the fitted observational models
Derived from the full evaluation — not a separate score.
Strengths
The dataset includes 74,239 articles, including 5,405 with preprints, across 39 journals. Journal-specific regression followed by random-effects meta-analysis strengthens the evidence beyond earlier smaller studies.
↳ Results, paragraphs 1 and 6; Table 1
CrossRef citation counts were checked against Web of Science, and inferred author publication age was compared with manual identification. The analysis also compared log-linear, Gamma, and negative-binomial model families and examined models with and without MeSH principal components.
↳ Methods, Collecting the Data and Inferring Author-Level Variables; Figure 1—figure supplement 8; Figure 2—figure supplement 2
The title and findings use associational language, while the Discussion explicitly identifies self-selection and increased visibility as competing explanations. The conclusion does not claim that releasing a preprint causes higher attention or citation counts.
↳ Title; Abstract; Discussion, paragraph 7
Limitations
Observable adjustment cannot account fully for factors such as author behavior or underlying research appeal that may influence both preprinting and later attention. The Discussion recognizes this but the analysis does not bound unmeasured confounding.
↳ Discussion, paragraph 7
The analysis includes only journals with at least 50 preprinted articles and excludes multidisciplinary journals. The findings therefore apply most directly where bioRxiv use was already sufficiently established.
↳ Methods, Collecting the Data; Discussion, paragraph 2
Researchers and publishers are named as intended users, but the estimates cannot show that adopting preprinting will produce the reported gains. This limits direct translation into policy or individual publication decisions.
↳ Abstract; Discussion, paragraphs 7–8
The study’s strongest feature is its combination of scale, journal stratification, extensive covariate adjustment, and random-effects synthesis. Validation of CrossRef citations and inferred author publication age, along with comparisons among several model families, supports the execution of the conditional-association analysis. The score remains below the top methodological band because preprinting is self-selected and the available covariates cannot remove unmeasured differences in author behavior or research appeal. Its practical relevance is clear, but translation and transferability are constrained by noncausal identification and selection of bioRxiv-active life-science journals.
Nabu’s assessment, alongside the field’s view.
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Strong3.9
Confidence highThe study meaningfully extends earlier bioRxiv analyses through a substantially larger sample, journal-stratified models, field adjustment, and journal-level meta-regression. Its central association had already been reported, making the contribution confirmatory and incremental rather than field-defining.
We sought to build on these efforts by leveraging the rapid growth of bioRxiv
The analysis combines extensive observable-confounder adjustment, model-family comparisons, random-effects synthesis, and validation of citation and author-history measures. Residual self-selection and unmeasured article or author characteristics remain unresolved, limiting the analysis to conditional associations.
having a preprint on bioRxiv could be merely a marker for research likely to receive more attention and citations anyway
The paper presents a traceable progression from data assembly through journal-specific regression and meta-analysis, with effect estimates and uncertainty stated consistently. Associational wording is maintained in the title, abstract, results, and discussion.
Because our data are observational, we cannot conclude that releasing a preprint is causal
The paper distinguishes its contribution from the closest prior and concurrent studies and connects sampling, metric, temporal, and causal limitations to interpretive consequences. The literature discussion is strongest around immediately adjacent preprint studies rather than broadly surveying complicating evidence.
our results only apply to journals that have published at least 50 articles that have a preprint on bioRxiv
Lower confidence on Methodological Rigour, Positioning — domain match limited.
No concerns4 of 4 checks
The sample sizes, primary estimates, model descriptions, and associational framing are consistent across the Abstract, Results, Methods, and Discussion.
The paper provides a persistent Figshare DOI for code and reproducible data and explains why article-level Altmetric data cannot be redistributed. The bibliometric design does not require human-participant ethics approval.
Flags: 2 declared / 5 total
26 of 26 checkable references verified
28 references in manuscript 2 are books, websites or datasets — counted, but not index-checkable
No retraction notice found in Retraction Watch.
Sources: Retraction Watch ✓
Where this paper’s evidence sits on the path from initial observation to real-world use.
The study analyzes actual publication, attention, and citation data across journals, making it relevant to current practice. Observational identification prevents it from showing that adopting preprinting will itself improve these outcomes.
without a randomized trial they are extremely difficult to distinguish
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