The Mass Production of Redundant, Misleading, and Conflicted Systematic Reviews and Meta-analyses.
By John P. A. Ioannidis. Milbank Quarterly, 2016
1,225 citations recorded by the source corpus.
Subfields: Information Systems and Management, Safety Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/1ed61ebb55384250ec69b4058999c31c9794fc50
How researchers see this paper
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In Information Systems and Management
In Safety Research
- T. Ben-Ari
- Shinichi Nakagawa
- David Moher
- David Makowski
- John Antonakis
- Michael D. Jennions
- Matthew J. Page
- D. Beillouin
In Statistics and Probability
- Matthew J. Page
- J. Koricheva
- J. Gurevitch
- Z. Munn
- David Moher
- George Davey Smith
- Gibran Hemani
- M. Lagisz
Citations in the corpus
- Time to challenge the spurious hierarchy of systematic over narrative reviews? (2018, background): “More generally, there is growing evidence that the science of systematic reviews is becoming increasingly distorted by commercial and other conflicts of interest, leading to reviews, which—often despite ticking the boxes on various quality checklists—are unnecessary, misleading or partisan.(19,41) T”
- Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension (2021, background): “Instead, the synthesis serves a useful role in unearthing flaws in the existing primary studies and guiding newer studies (Ioannidis, 2016).”
- What kind of systematic review should I conduct? A proposed typology and guidance for systematic reviewers in the medical and health sciences (2018, background): “It has been argued recently that there is mass production of reviews that are often unnecessary, misleading and conflicted with most having weak or insufficient evidence to inform decision making [66].”
- On doing better science: From thrill of discovery to policy implications (2017, background): “…and procedures so that other researchers are able to faithfully reproduce it (see Atwater, et al., 2014; Cortina, et al., 2016; Goodman, Fanelli, & Ioannidis, 2016; Nosek et al., 2015); computational steps taken to arrive at analyzed datasets and results, as well as programing and needed computer…”
- Evaluations of the uptake and impact of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement and extensions: a scoping review (2017, background): “The transparency of SRs and meta-analyses of health research has been called into question on many occasions [5].”
- Generating translatable evidence to improve patient care: the contribution of human factors (2020, neutral): “Worse still, some data are used intentionally to obfuscate (Ioannidis, 2016; Launer, 2020).”
- Two-sample Mendelian randomization: avoiding the downsides of a powerful, widely applicable but potentially fallible technique (2016, background): “It is important that the recent rise of two-sample Mendelian randomization studies shown in Figure 1 does not recapitulate the epidemic of ‘redundant, misleading, and conflicted systematic reviews and metaanalyses’ recently reported by Ioannidis.(36) The possibility of this happening is prefigured b”
- Meta-analysis and the science of research synthesis (2018, neutral): “While the number of published meta-analyses has continued to increase rapidly within and among disciplines, too many meta-analyses are of low quality 13-15 .”
- Evidence map of crop diversification strategies at the global scale (2019, methodology): “Low-quality meta-analyses are strongly criticized (Kirsch et al 2008, Pullin and Knight 2012, Ioannidis 2016) and negatively impact the image of usefulness of such method (Whittaker 2010).”
- SANRA—a scale for the quality assessment of narrative review articles (2019, background): “While systematic reviews are not per se superior articles and while certain systematic reviews have been criticized lately [3], non-systematic reviews or narrative reviews have”