TY - JOUR T1 - Characteristics, quality and volume of the first 5 months of the COVID-19 evidence synthesis infodemic: a meta-research study JF - BMJ Evidence-Based Medicine JO - BMJ EBM DO - 10.1136/bmjebm-2021-111710 SP - bmjebm-2021-111710 AU - Rebecca Abbott AU - Alison Bethel AU - Morwenna Rogers AU - Rebecca Whear AU - Noreen Orr AU - Liz Shaw AU - Ken Stein AU - Jo Thompson Coon Y1 - 2021/06/03 UR - http://ebm.bmj.com/content/early/2021/06/03/bmjebm-2021-111710.abstract N2 - Objective The academic and scientific community has reacted at pace to gather evidence to help and inform about COVID-19. Concerns have been raised about the quality of this evidence. The aim of this review was to map the nature, scope and quality of evidence syntheses on COVID-19 and to explore the relationship between review quality and the extent of researcher, policy and media interest.Design and setting A meta-research: systematic review of reviews.Information sources PubMed, Epistemonikos COVID-19 evidence, the Cochrane Library of Systematic Reviews, the Cochrane COVID-19 Study Register, EMBASE, CINAHL, Web of Science Core Collection and the WHO COVID-19 database, searched between 10 June 2020 and 15 June 2020.Eligibility criteria Any peer-reviewed article reported as a systematic review, rapid review, overview, meta-analysis or qualitative evidence synthesis in the title or abstract addressing a research question relating to COVID-19. Articles described as meta-analyses but not undertaken as part of a systematic or rapid review were excluded.Study selection and data extraction Abstract and full text screening were undertaken by two independent reviewers. Descriptive information on review type, purpose, population, size, citation and attention metrics were extracted along with whether the review met the definition of a systematic review according to six key methodological criteria. For those meeting all criteria, additional data on methods and publication metrics were extracted.Risk of bias For articles meeting all six criteria required to meet the definition of a systematic review, AMSTAR-2 ((A MeaSurement Tool to Assess systematic Reviews, version 2.0) was used to assess the quality of the reported methods.Results 2334 articles were screened, resulting in 280 reviews being included: 232 systematic reviews, 46 rapid reviews and 2 overviews. Less than half reported undertaking critical appraisal and a third had no reproducible search strategy. There was considerable overlap in topics, with discordant findings. Eighty-eight of the 280 reviews met all six systematic review criteria. Of these, just 3 were rated as of moderate or high quality on AMSTAR-2, with the majority having critical flaws: only a third reported registering a protocol, and less than one in five searched named COVID-19 databases. Review conduct and publication were rapid, with 52 of the 88 systematic reviews reported as being conducted within 3 weeks, and a half published within 3 weeks of submission. Researcher and media interest, as measured by altmetrics and citations, was high, and was not correlated with quality.Discussion This meta-research of early published COVID-19 evidence syntheses found low-quality reviews being published at pace, often with short publication turnarounds. Despite being of low quality and many lacking robust methods, the reviews received substantial attention across both academic and public platforms, and the attention was not related to the quality of review methods.Interpretation Flaws in systematic review methods limit the validity of a review and the generalisability of its findings. Yet, by being reported as ‘systematic reviews’, many readers may well regard them as high-quality evidence, irrespective of the actual methods undertaken. The challenge especially in times such as this pandemic is to provide indications of trustworthiness in evidence that is available in ‘real time’.PROSPERO registration number CRD42020188822.Data are available upon reasonable request. Requests for data sharing should be sent to the corresponding author at r.a.abbott@exeter.ac.uk. ER -