The reliability of experimental findings depends on the rigour of experimental design. Here we show limited reporting of measures to reduce the risk of bias in a random sample of life sciences ...publications, significantly lower reporting of randomisation in work published in journals of high impact, and very limited reporting of measures to reduce the risk of bias in publications from leading United Kingdom institutions. Ascertainment of differences between institutions might serve both as a measure of research quality and as a tool for institutional efforts to improve research quality.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines are widely endorsed but compliance is limited. We sought to determine whether journal-requested completion of an ARRIVE ...checklist improves full compliance with the guidelines.
In a randomised controlled trial, manuscripts reporting in vivo animal research submitted to PLOS ONE (March-June 2015) were randomly allocated to either requested completion of an ARRIVE checklist or current standard practice. Authors, academic editors, and peer reviewers were blinded to group allocation. Trained reviewers performed outcome adjudication in duplicate by assessing manuscripts against an operationalised version of the ARRIVE guidelines that consists 108 items. Our primary outcome was the between-group differences in the proportion of manuscripts meeting all ARRIVE guideline checklist subitems.
We randomised 1689 manuscripts (control:
= 844, intervention:
= 845), of which 1269 were sent for peer review and 762 (control:
= 340; intervention:
= 332) accepted for publication. No manuscript in either group achieved full compliance with the ARRIVE checklist. Details of animal husbandry (ARRIVE subitem 9b) was the only subitem to show improvements in reporting, with the proportion of compliant manuscripts rising from 52.1 to 74.1% (
= 34.0, df = 1,
= 2.1 × 10
) in the control and intervention groups, respectively.
These results suggest that altering the editorial process to include requests for a completed ARRIVE checklist is not enough to improve compliance with the ARRIVE guidelines. Other approaches, such as more stringent editorial policies or a targeted approach on key quality items, may promote improvements in reporting.
Throughout the global coronavirus pandemic, we have seen an unprecedented volume of COVID-19 researchpublications. This vast body of evidence continues to grow, making it difficult for research users ...to keep up with the pace of evolving research findings. To enable the synthesis of this evidence for timely use by researchers, policymakers, and other stakeholders, we developed an automated workflow to collect, categorise, and visualise the evidence from primary COVID-19 research studies. We trained a crowd of volunteer reviewers to annotate studies by relevance to COVID-19, study objectives, and methodological approaches. Using these human decisions, we are training machine learning classifiers and applying text-mining tools to continually categorise the findings and evaluate the quality of COVID-19 evidence.
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