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John P. A. Ioannidis
Ioannidis in 2015
Born (1965-08-21) August 21, 1965 (age 59)
New York City, U.S.
NationalityAmerican, Greek
Alma materUniversity of Athens Medical School
Athens College
Known forMetascience
Scientific career
FieldsMedicine, metascience
InstitutionsStanford School of Medicine

John P. A. Ioannidis (/ˌiːəˈniːdɪs/ EE-ə-NEE-diss; Greek: Ιωάννης Ιωαννίδης, pronounced [i.oˈanis i.oaˈniðis]; born August 21, 1965) is a Greek-American physician-scientist, writer and Stanford University professor who has made contributions to evidence-based medicine, epidemiology, and clinical research. Ioannidis studies scientific research itself - in other words, meta-research - primarily in clinical medicine and the social sciences.

He has served on the editorial board of over twenty scientific journals including Journal of the American Medical Association (JAMA), Journal of the National Cancer Institute (JNCI) and The Lancet.

Ioannidis's 2005 essay "Why Most Published Research Findings Are False" was the most-accessed article in the history of Public Library of Science (PLOS) as of 2020, with more than three million views.[1][2]

Ioannidis was a prominent opponent of lockdowns during the COVID-19 pandemic, and he has been accused of promoting conspiracy theories about COVID-19 policies and public health and safety measures.[3][4][5][6]

Early life and education

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Born in New York City in 1965, Ioannidis was raised in Athens, Greece.[7] He was valedictorian of his class at Athens College, graduating in 1984, and won a number of awards, including the National Award of the Greek Mathematical Society.[8] He graduated in the top rank of his class at the University of Athens Medical School (1990), then attended Harvard University for his medical residency in internal medicine. He did a fellowship at Tufts University for infectious disease[9] and received a PhD in biopathology at the University of Athens (1996).[10]

Career

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He is a very highly cited medical researcher, with an h-index of 239 on Google Scholar in January 2023.[11]

From 1998 to 2010, Ioannidis was chairman of the Department of Hygiene and Epidemiology, University of Ioannina School of Medicine. In 2002, he became an adjunct professor at Tufts University School of Medicine.[12][8] He has also been president of the Society for Research Synthesis Methodology.[8]

He holds four academic appointments at Stanford University: Professor of Medicine, Professor of Epidemiology and Population Health, Professor (by courtesy) of Statistics and Professor (by courtesy) of Biomedical Data Science.[10][5] He is director of the Stanford Prevention Research Center, and co-director, along with Steven N. Goodman, of the Meta-Research Innovation Center at Stanford.[13][14]

Research

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Further information: Metascience
John Ioannidis (2005), "Why Most Published Research Findings Are False"[15]

Ioannidis's 2005 paper "Why Most Published Research Findings Are False"[2] is the most downloaded paper in the Public Library of Science.[10][16][17][18] In the paper, Ioannidis says that most published research does not meet good scientific standards of evidence. Ioannidis has also described the replication crisis in diverse scientific fields including genetics,[19] clinical trials,[20] neuroscience,[21] and nutrition.[22] His work has aimed to identify solutions to problems in research, and on how to perform research more optimally.[23][24][25] In a series of five papers about research published in The Lancet and titled "Research: increasing value, reducing waste",[25] Ioannidis co-authored papers discussing prioritization, transparency and the assessment of existing evidence when making decisions for the funding of research so that they meet the needs of users of research[26] and examining how to correct weaknesses in research design, methods, and analysis by involving experienced statisticians and methodologists and avoiding stakeholders with conflicts of interest.[27][28]

Ioannidis's research at Stanford focuses on meta-analysis and meta-research – the study of studies.[29] Thomas Trikalinos and Ioannidis coined the term Proteus phenomenon to describe tendency for early studies on a subject to find larger effect than later ones.[30]

He was an early and influential public critic of Theranos, the now-fallen Silicon Valley blood test startup that at its height was valued at up to $9 billion. He criticized it for "stealth research" that it had not made available for other scientists to review.[31][32][33]

Meta-research

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Ioannidis has defined meta-research to include "thematic areas of methods, reporting, reproducibility, evaluation, and incentives (how to do, report, verify, correct, and reward science)".[34] He has performed large-scale assessments of the presence of reproducible and transparent research indicators such as data sharing, code sharing, protocol registration, declaration of funding and conflicts of interest in biomedical sciences,[35] social sciences,[36] and psychology.[37] He has led or co-led efforts to define[38] and improve reproducibility in science,[39] e.g. computational reproducibility,[40][41] and to reduce research waste in study design, conduct, and analysis.[42] Ioannidis has co-authored the Manifesto for Reproducible Science,[43] an eight-page document illuminating the need to fix the flaws in the current scientific process and mitigate the "reproducibility crisis" in science.[44]

In "Why Most Published Research Findings are False" (2005), Ioannidis focused on why most published research findings cannot be validated.[2] In a later paper on PLOS Medicine (2014), he discusses what can be done to improve this situation and make more published research findings to be true[45] and in a third paper (2016) he showed why clinical research in particular is usually not useful and how this can be amended.[46] In the first of the three PLOS papers he stated that "a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance".[47] In the second paper, he discussed solutions: "adoption of large-scale collaborative research; replication culture; registration; sharing; reproducibility practices; better statistical methods; standardization of definitions and analyses; more appropriate (usually more stringent) statistical thresholds; and improvement in study design standards, peer review, reporting and dissemination of research, and training of the scientific workforce".[48][49][50] In the third paper, he proposed eight features that are important for useful clinical research: problem base, context placement, information gain, pragmatism, patient-centeredness, value for money, feasibility, and transparency.[51] Ioannidis was invited to present his findings as a keynote speaker at the "Evidence Live 2016" conference, hosted jointly by the Centre for Evidence-Based Medicine (CEBM) at the Nuffield Department of Primary Care Health Sciences, University of Oxford and the BMJ.[52]

Meta-analysis

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Ioannidis has developed and popularized several methods for meta-analysis and has made several conceptual advances in this field. These include methods for assessing heterogeneity and its uncertainty,[53] methods for meta-analysis involving multiple treatments,[54] methods and processes for umbrella reviews,[55][56] and several approaches to identifying bias and adjusting the results of meta-analyses for bias, such as publication bias and reporting bias resulting in funnel-plot asymmetry.[57] He has also alerted about the misuse and misinterpretation of bias tests.[58] Along with David Chavalarias, he catalogued 235 biases across the entire publication record of biomedical research.[59] Ioannidis has been critical of flawed, misleading and redundant meta-analyses, estimating that few meta-analyses in medicine are both bias-free and clinically useful.[60] He has performed empirical evaluations of the concordance of results between meta-analyses and large trials[61] and between randomized trials and non-randomized studies.[62][63][64]

Evidence-based medicine

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Ioannidis has been one of the strong proponents and earlier advocates of evidence-based medicine. However, he has alerted that, over the years, as evidence-based medicine acquired more prominence and influence, it was hijacked to serve other agendas that are often biased.[65] In an essay written to honor his late mentor David Sackett, he stated that "Influential randomized trials are largely done by and for the benefit of the industry. Meta-analyses and guidelines have become a factory, mostly also serving vested interests. National and federal research funds are funneled almost exclusively to research with little relevance to health outcomes. We have supported the growth of principal investigators who excel primarily as managers absorbing more money. Diagnosis and prognosis research and efforts to individualize treatment have fueled recurrent spurious promises. Risk factor epidemiology has excelled in salami-sliced, data-dredged articles with gift authorship and has become adept to dictating policy from spurious evidence. Under market pressure, clinical medicine has been transformed to finance-based medicine. In many places, medicine and health care are wasting societal resources and becoming a threat to human well-being. Science denialism and quacks are also flourishing and leading more people astray in their life choices, including health. Evidence-based medicine still remains an unmet goal, worthy to be attained."[66][67] He has described four inter-related problems that create what he calls the Medical Misinformation Mess: "First, much published medical research is not reliable or is of uncertain reliability, offers no benefit to patients, or is not useful to decision makers. Second, most healthcare professionals are not aware of this problem. Third, they also lack the skills necessary to evaluate the reliability and usefulness of medical evidence. Finally, patients and families frequently lack relevant, accurate medical evidence and skilled guidance at the time of medical decision-making."[68][69] He has supported these views by contributing to a meta-epidemiological study which found that only 1 in 20 interventions tested in Cochrane Reviews have benefits that are supported by high-quality evidence.,[70] and a related study showing that the quality of this evidence does not seem to improve over time.[71]

Statistical methods and inference

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Ioannidis has made methodological and conceptual contributions to the debates surrounding the use and misuse of statistical methods and inference.[72] He has been an advocate of the approach to redefine statistical significance by requesting more stringent statistical significance thresholds;[73][74][75] he has proposed and empirically validated stringent thresholds for genome-wide significance in genetics;[76] and has been critical of the approach to entirely abandon statistical significance.[77][78]

Reporting guidelines

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Ioannidis has contributed to several influential guidelines for reporting different types of research, such as PRISMA for meta-analyses,[79] TRIPOD for multivariable prognostic and diagnostic models,[80] and others on clinical trials and observational research. He is the lead author of the CONSORT for harms, a guideline that provides guidance on how to properly report on harms in randomized trials[81][82] and has contributed to PRISMA for harms, a guideline for reporting of harms in meta-analyses.[83][84]

Genetic and molecular epidemiology

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Ioannidis was one of the first to advocate the use of meta-analysis in genetic epidemiology to assess replication[85] and the incorporation of meta-analysis in large-scale consortia of multiple investigators performing genome-wide association studies.[86][87] He led and contributed to many such efforts in diverse areas of genetic epidemiology and in other areas of molecular epidemiology.[88][87]

Nutrition

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Ioannidis has been critical of nutritional epidemiology research practices and has recommended reforms to improve the credibility of research in the field.[89][90] By means of empirical reviews, he has highlighted that there are studies suggesting that almost every nutrient is associated with cancer risk, which is an implausible situation[91][92] He has also suggested that more attention is needed for proper disclosures of both financial and non-financial conflicts of interest in nutrition research. He also co-authored the DIETFITS randomized trial that showed no difference between a low-fat and a low-carb diet.[93][94]

Association studies and big data

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In an effort to improve the credibility of research on risk factors, Ioannidis has proposed that exposure-wide or environment-wide association studies should be performed and he has outlined the similarities and differences between such studies and genome-wide association studies in genetics.[95][96] By assessing all risk factors together instead of one at a time, this practice aims to reduce selective reporting and publication bias. He has also advocated for the use of large national population databases with systematically collected data to minimize bias and improve yield of trustworthy discoveries.[97] He has worked on the potential uses of such approaches in big data[98] and artificial intelligence.[99][100]

Psychiatry

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Ioannidis has performed critical assessments of the evidence behind mental health interventions (pharmacotherapy and psychotherapy). He co-authored a network meta-analysis on more than 500 randomized trials of anti-depressants showing a modest benefit from these medications for major depression.[101][102][103] He has identified the potential for sponsorship bias in meta-analyses in mental health[104][105] and has empirically assessed the totality of meta-analyses on mental health interventions, estimating that beneficial effects do exist, but they tend to be modest and thus a research agenda is needed to identify more effective interventions.[106]

Neuroscience

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Along with colleagues, Ioannidis has performed empirical evaluations and meta-research assessments of large numbers of scientific studies in neuroscience and have found that lack of power is a very common problem, leading to both false-negatives (the inability to discover true signals) and false-positives (finding spurious signals).[107][108]

Economics

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In empirical assessments of all meta-analyses that have been conducted on economics topics, Ioannidis and colleagues have found that most of the studies in these fields are small and under-powered. Using bias detection and correction methods, they have concluded that nearly 80% of the reported effects in the empirical economics literature is exaggerated; typically by a factor of two, and with one-third inflated by a factor of four or more.[109][110]

Editorial appointments

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Ioannidis has served on the editorial board of a number of scientific journals,[10] including the European Journal of Clinical Investigation (editor-in-chief, 2010–2019),[10][111] BMC Medicine,[112] International Journal of Epidemiology,[113] Journal of the American Medical Association,[114] Journal of Clinical Epidemiology,[115] Journal of Infectious Diseases,[116] International Journal of Molecular Epidemiology and Genetics,[117] International Journal of Epidemiology,[113] Journal of Translational Medicine,[118] Journal of Evaluation in Clinical Practice,[119] Clinical Chemistry,[120] Physiological Reviews,[121] Royal Society Open Science,[122] Research Integrity and Peer Review,[123] BioMed Central Infectious Diseases,[112] Biomarker Research,[124] Diagnostic and Prognostic Research,[125] PLoS Medicine,[126] PLoS Biology,[127] The Lancet,[126] Annals of Internal Medicine,[126] JNCI,[126] and Science Translational Medicine.[126]

COVID-19

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In an editorial on STAT published March 17, 2020, Ioannidis wondered whether the global response to the COVID-19 pandemic may be a "once-in-a-century evidence fiasco" and asked for obtaining more reliable data to deal with the pandemic.[5] He made a rough estimation that the coronavirus could cause 10,000 U.S. deaths if it infected 1% of the U.S. population, but argued that more data was needed to determine how widely the virus would spread.[128][3][5] The virus in fact eventually became widely disseminated, and would cause more than one million deaths in the U.S.[129][128][3] Ioannidis expressed doubt that vaccines or treatments would be developed and tested in time to affect how the pandemic would unfold.[130] Marc Lipsitch, Director of the Center for Communicable Disease Dynamics at the Harvard T.H. Chan School of Public Health, objected to Ioannidis's characterization of the global response in a reply that was published on STAT the next day after Ioannidis's.[131]

In March 2020, Ioannidis tried to organize a meeting at the White House where he and colleagues would caution President Donald Trump against "shutting down the country for [a] very long time and jeopardizing so many lives in doing this," according to a proposal he submitted. The meeting did not come to pass, but on March 28, after Trump said he wanted the country reopened by Easter, Ioannidis wrote to his colleagues, "I think our ideas have inflitrated [sic] the White House regardless".[3]

Ioannidis widely promoted a study of which he had been co-author, "COVID-19 Antibody Seroprevalence in Santa Clara County, California", released as a preprint on April 17, 2020. It asserted that Santa Clara County's number of infections was between 50 and 85 times higher than the official count, putting the virus's fatality rate as low as 0.1% to 0.2%.[n 1][133][129] Ioannidis concluded from the study that the coronavirus is "not the apocalyptic problem we thought".[134] The message found favor with right-wing media outlets, but the paper drew criticism from a number of epidemiologists who said its testing was inaccurate and its methods were sloppy.[135][136][137] Writing for Wired, David H. Freedman said that the Santa Clara study compromised Ioannidis's previously excellent reputation and meant that future generations of scientists may remember him as "the fringe scientist who pumped up a bad study that supported a crazy right-wing conspiracy theory in the middle of a massive health crisis."[4] Ioannidis has also promoted the idea that there were financial incentives to put COVID-19 on death certificates and as such, they were unreliable during the pandemic, as well as the idea that doctors killed COVID-19 patients through premature intubations. Both of these beliefs contradict the available evidence.[138]

It was later reported that the study received $5,000 in funding from the founder of the JetBlue airline, which led to criticism over a potential conflict of interest.[139][140] In a guest opinion article in Scientific American, former colleagues of Ioannidis wrote that a legal firm had determined he had no financial conflict.[141] A review by the Stanford School of Medicine faulted the study for shortcomings including a public perception of a conflict of interest, but found "no evidence that any of the study funders influenced the design, execution, or reporting of the study".[128]

Amid controversy over his COVID-19 work and his frequent televised interviews, Ioannidis was harassed in memes and emails, including one falsely claiming his mother died of COVID-19. Some scientists and commentators voiced concerns over the backlash and the highly politicized scientific dispute in general.[128][142]

In March 2021 Ioannidis estimated the global infection fatality rate from COVID-19 at 0.15%, in an article in the European Journal of Clinical Investigation (EJCI).[143] In an article in Science-Based Medicine, David Gorski said that the EJCI article included ad hominem criticisms against a co-author of a higher estimate who had criticized his work on Twitter.[129]

In February 2022 Ioannidis co-authored a paper examining the role of indoor and outdoor air quality in the spread of SARS-CoV-2, which concluded that environmental health may be a crucial component in the prevention of COVID-19 and suggested preventive measures such as indoor CO2 monitoring and mechanical ventilation.[144]

In 2022, Ioannidis authored a paper in BMJ Open arguing that signatories of the Great Barrington Declaration were shunned as a fringe minority by those in favor of the John Snow Memorandum. According to him, the latter used their large numbers of followers on Twitter and other social media and op-eds to shape a scientific groupthink against the former, who had less influence as measured by the Kardashian Index.[145][146] The BMJ published responses to his paper, including a comment by Gavin Yamey, David Gorski, and Gideon Meyerowitz-Katz which argued that Ioannidis's paper featured "factual errors, statistical shortcomings, failure to protect the named research subjects from harm, and potentially undeclared conflicts of interest that entirely undermine the analysis presented."[147] In the same exchange of comments on The BMJ, Ioannidis addressed the concerns of Yamey, Gorski and Meyerovitz-Katz in his "Fourth set of replies", additionally stating that his "COVID-19 papers have been cited about 5 thousand times in the scientific literature by tens of thousands of scientists and were discussed by millions of people," and dismissed conflict of interest by asserting that he did not sign the Great Barrington Declaration or any other petition or signature collection on COVID-19, as he is against the notion that scientific matters and evidence could be decided by signature collections and prefers these matters be handled by heavily moderated public debates.[148]

Reception

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In 2010, David H. Freedman in The Atlantic stated in a special edition about "Brave Thinkers" that Ioannidis "may be one of the most influential scientists alive."[149][150]

In 2011, Sharon Begley's article "Why Almost Everything You Hear About Medicine Is Wrong" in Newsweek said Ioannidis was "cementing his role as one of medicine's top mythbusters".[151]

In 2013, Richard Smith's article "Time for science to be about truth rather than careers" likened listening to Ioannidis to "listening to a great opera or watching a gripping football match: you feel inspired, uplifted, and privileged."[152]

In 2014, The Economist featured Ioannidis and Steven Goodman in an article on the Meta-Research Innovation Center at Stanford,[153] and George Johnson of the New York Times wrote an article on the importance of reproducible research, profiling Ioannidis's two 2005 papers as playing a critical role in raising concern about the issue in the scientific community, as later expressed by the journal Nature.[154]

In 2015, Ioannidis was profiled in The BMJ and described as "the scourge of sloppy science".[155]

In 2016, Quartz ran a feature on Ioannidis titled "The man who made scientists question themselves has just exposed huge flaws in evidence used to give drug prescriptions".[64]

In 2017, Wired mentioned Ioannidis as "arguably the replication crisis' chief inquisitor."[110]

In 2019, a STAT article on the healthcare replication crisis mentioned that Ioannidis had found that only a minority of widely cited health research studies carried out over the last decade could be replicated, with at least 1 in 6 actually being contradicted by later studies,[156] and Elsevier featured his analogy of reproducibility in research to "taming a complex beast".[157]

In 2021, David Gorski's article "What the heck happened to John Ioannidis?" described statements by Ioannidis about COVID-19 as inflammatory and politically charged, and said Ioannidis had made egregious ad hominem attacks. Gorski called Ioannidis "a cautionary tale of how even science watchdogs can fall prey to hubris."[129]

In 2022, Jeffrey Lee Funk and Gary N. Smith writing at MarketWatch described how Ioannidis is “widely-known as the godfather of science reform” and narrated how he was the first to criticize Theranos"[158] and Graham Hilard at the Washington Examiner wrote that for the replication crisis in science, “the true clarion call was sounded in 2005 with the appearance of John P. A. Ioannidis’s Why Most Published Research Findings Are False,” describing the paper as a "shock treatise.”[159]

Awards and honors

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Ioannidis has received elected membership to the National Academy of Medicine,[160] the European Academy of Sciences and Arts,[161] the European Academy of Cancer Sciences,[162] the American Epidemiological Society[162] and the Association of American Physicians.[163] For the 2022-2023 term, he is vice-president and president-elect of the Association of American Physicians.[163][10]

See also

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Notes

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  1. ^ On May 11, the study's authors revised the study with new figures stating the number of infections was 54 times higher than the official count.[132][129]

References

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  1. ^ Browse the 'Best in Class' articles from PLOS – Top Views, Public Library of Science, archived from the original on October 22, 2020, retrieved October 15, 2020
  2. ^ a b c Ioannidis, John P. A. (August 30, 2005), "Why Most Published Research Findings Are False", PLOS Medicine, 2 (8): e124, doi:10.1371/journal.pmed.0020124, PMC 1182327, PMID 16060722, 3,128,135 View
  3. ^ a b c d Lee, Stephanie M. (July 24, 2020). "An Elite Group of Scientists Tried to Warn Trump Against Lockdowns in March". BuzzFeed News. Archived from the original on July 26, 2020. Retrieved July 26, 2020.
  4. ^ a b David H. Freedman (May 1, 2020). "A Prophet of Scientific Rigor—and a Covid Contrarian". Wired. Archived from the original on May 24, 2020. Retrieved May 24, 2020.
  5. ^ a b c d "A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data". Stat. March 17, 2020. Archived from the original on April 5, 2020. Retrieved April 26, 2020.
  6. ^ Antiochou, Konstantina; Psillos, Stathis (2022), Oswald, Steve; Lewiński, Marcin; Greco, Sara; Villata, Serena (eds.), "How to Handle Reasonable Scientific Disagreement: The Case of COVID-19", The Pandemic of Argumentation, vol. 43, Cham: Springer International Publishing, pp. 65–83, doi:10.1007/978-3-030-91017-4_4, ISBN 978-3-030-91016-7
  7. ^ John Ioannidis Archived February 22, 2014, at the Wayback Machine, Harvard School of Public Health.
  8. ^ a b c Ioannidis, John P.A. "Curriculum Vitae" (PDF). UoI. Archived from the original (PDF) on July 21, 2011. Retrieved November 4, 2010.
  9. ^ Freedman, David H. (2010). Wrong: Why Experts Keep Failing Us. Little, Brown & Co. ISBN 978-0-316-02378-8. Born in 1965 in the United States to parents who were both physicians, he was raised in Athens, where he showed unusual aptitude in mathematics and snagged Greece's top student math prize.
  10. ^ a b c d e f "John P.A. Ioannidis". Stanford Profiles. Archived from the original on December 11, 2019. Retrieved April 24, 2020.
  11. ^ Aguillo, Isidro F. (September 2020). "Highly Cited Researchers (h>100) according to their Google Scholar Citations public profiles". webometrics.info. Archived from the original on January 29, 2021. Retrieved January 31, 2021.
  12. ^ "John P.A. Ioannidis". Department of Hygiene and Epidemiology, University of Ioannina School of Medicine. Archived from the original on February 14, 2009. Retrieved December 31, 2008.
  13. ^ "John P. A. Ioannidis". CAP Profiles. Stanford School of Medicine. Archived from the original on July 4, 2014. Retrieved May 24, 2014.
  14. ^ "Prevention Research Center". Stanford School of Medicine. Archived from the original on June 29, 2014. Retrieved May 24, 2014.
  15. ^ Ioannidis, J. P. A. (2005). "Why Most Published Research Findings Are False". PLOS Medicine. 2 (8): e124. doi:10.1371/journal.pmed.0020124. PMC 1182327. PMID 16060722.
  16. ^ "Highly Cited Researchers". Archived from the original on April 2, 2012. Retrieved September 17, 2015.
  17. ^ Robert Lee Hotz (September 14, 2007). "Most Science Studies Appear to Be Tainted By Sloppy Analysis". The Wall Street Journal. Archived from the original on December 24, 2016. Retrieved December 5, 2016.
  18. ^ "PLOS ONE: Search Results". journals.plos.org. Archived from the original on February 18, 2022. Retrieved February 18, 2022.
  19. ^ Ioannidis, John P. A.; Ntzani, Evangelia E.; Trikalinos, Thomas A.; Contopoulos-Ioannidis, Despina G. (November 1, 2001). "Replication validity of genetic association studies". Nature Genetics. 29 (3): 306–309. doi:10.1038/ng749. ISSN 1061-4036. PMID 11600885. S2CID 6742347.
  20. ^ Ebrahim, Shanil; Sohani, Zahra N.; Montoya, Luis; Agarwal, Arnav; Thorlund, Kristian; Mills, Edward J.; Ioannidis, John P. A. (September 10, 2014). "REanalyses of randomized clinical trial data". JAMA. 312 (10): 1024–1032. doi:10.1001/jama.2014.9646. ISSN 0098-7484. PMID 25203082.
  21. ^ Button, Katherine S.; Ioannidis, John P. A.; Mokrysz, Claire; Nosek, Brian A.; Flint, Jonathan; Robinson, Emma S. J.; Munafò, Marcus R. (May 1, 2013). "Power failure: why small sample size undermines the reliability of neuroscience". Nature Reviews Neuroscience. 14 (5): 365–376. doi:10.1038/nrn3475. ISSN 1471-003X. PMID 23571845.
  22. ^ Ioannidis, John P. A. (September 11, 2018). "The Challenge of Reforming Nutritional Epidemiologic Research". JAMA. 320 (10): 969–970. doi:10.1001/jama.2018.11025. ISSN 0098-7484. PMID 30422271. S2CID 53293211. Archived from the original on January 22, 2021. Retrieved August 8, 2020.
  23. ^ Begley, C. Glenn; Ioannidis, John P. A. (January 2, 2015). "Reproducibility in science: improving the standard for basic and preclinical research". Circulation Research. 116 (1): 116–126. doi:10.1161/CIRCRESAHA.114.303819. ISSN 1524-4571. PMID 25552691.
  24. ^ Ioannidis, John P. A. (October 21, 2014). "How to Make More Published Research True". PLOS Med. 11 (10): e1001747. doi:10.1371/journal.pmed.1001747. PMC 4204808. PMID 25334033.
  25. ^ a b "Research: increasing value, reducing waste". www.thelancet.com. Archived from the original on November 5, 2021. Retrieved February 12, 2022.
  26. ^ Chalmers, Iain; Bracken, Michael B.; Djulbegovic, Ben; Garattini, Silvio; Grant, Jonathan; Gülmezoglu, A. Metin; Howells, David W.; Ioannidis, John P. A.; Oliver, Sandy (January 11, 2014). "How to increase value and reduce waste when research priorities are set". The Lancet. 383 (9912): 156–165. doi:10.1016/S0140-6736(13)62229-1. ISSN 0140-6736. PMID 24411644. S2CID 26542330. Archived from the original on May 18, 2022. Retrieved February 12, 2022.
  27. ^ Ioannidis, John P. A.; Greenland, Sander; Hlatky, Mark A.; Khoury, Muin J.; Macleod, Malcolm R.; Moher, David; Schulz, Kenneth F.; Tibshirani, Robert (January 11, 2014). "Increasing value and reducing waste in research design, conduct, and analysis". The Lancet. 383 (9912): 166–175. doi:10.1016/S0140-6736(13)62227-8. ISSN 0140-6736. PMC 4697939. PMID 24411645.
  28. ^ "NIH to Researchers: Credibility Counts". www.medpagetoday.com. January 27, 2014. Archived from the original on December 6, 2021. Retrieved May 13, 2022.
  29. ^ Joan O'C. Hamilton (2012), "Something Doesn't Add Up", Stanford Magazine, archived from the original on May 11, 2020, retrieved May 16, 2020
  30. ^ Handbook of Meta-analysis in Ecology and Evolution, Princeton University Press, 2013, p. 240, ISBN 9780691137292
  31. ^ Cha, Ariana Eunjung. "Theranos blood test: The insanely influential Stanford professor who called the company out for its 'stealth research'". Washington Post. ISSN 0190-8286. Archived from the original on December 15, 2021. Retrieved November 19, 2021.
  32. ^ Paul, Keri (August 30, 2021). "'Selling a promise': what Silicon Valley learned from the fall of Theranos". The Guardian. Archived from the original on November 19, 2021. Retrieved November 19, 2021.
  33. ^ Ioannidis, John P. A. (February 17, 2015). "Stealth Research: Is Biomedical Innovation Happening Outside the Peer-Reviewed Literature?". JAMA. 313 (7): 663–664. doi:10.1001/jama.2014.17662. ISSN 0098-7484. PMID 25688775. Archived from the original on May 18, 2022. Retrieved November 19, 2021.
  34. ^ Ioannidis, John P. A.; Fanelli, Daniele; Dunne, Debbie Drake; Goodman, Steven N. (October 2, 2015). "Meta-research: Evaluation and Improvement of Research Methods and Practices". PLOS Biology. 13 (10): e1002264. doi:10.1371/journal.pbio.1002264. ISSN 1545-7885. PMC 4592065. PMID 26431313.
  35. ^ Iqbal, Shareen A.; Wallach, Joshua D.; Khoury, Muin J.; Schully, Sheri D.; Ioannidis, John P. A. (January 4, 2016). "Reproducible Research Practices and Transparency across the Biomedical Literature". PLOS Biology. 14 (1): e1002333. doi:10.1371/journal.pbio.1002333. ISSN 1545-7885. PMC 4699702. PMID 26726926.
  36. ^ Hardwicke, Tom E.; Wallach, Joshua D.; Kidwell, Mallory C.; Bendixen, Theiss; Crüwell, Sophia; Ioannidis, John P. A. (2020). "An empirical assessment of transparency and reproducibility-related research practices in the social sciences (2014–2017)". Royal Society Open Science. 7 (2): 190806. Bibcode:2020RSOS....790806H. doi:10.1098/rsos.190806. PMC 7062098. PMID 32257301.
  37. ^ Hardwicke, Tom E.; Thibault, Robert T.; Kosie, Jessica E.; Wallach, Joshua D.; Kidwell, Mallory C.; Ioannidis, John P. A. (March 8, 2021). "Estimating the Prevalence of Transparency and Reproducibility-Related Research Practices in Psychology (2014–2017)". Perspectives on Psychological Science. 17 (1): 239–251. doi:10.1177/1745691620979806. ISSN 1745-6916. PMC 8785283. PMID 33682488.
  38. ^ "Define Your Terms". Genomeweb. June 3, 2016. Archived from the original on September 11, 2019. Retrieved March 22, 2022.
  39. ^ Begley, C. Glenn; Ioannidis, John P. A. (January 2, 2015). "Reproducibility in science: improving the standard for basic and preclinical research". Circulation Research. 116 (1): 116–126. doi:10.1161/CIRCRESAHA.114.303819. ISSN 1524-4571. PMID 25552691. S2CID 3587510.
  40. ^ Urbana-Champaign, University of Illinois at. "Report proposes standards for sharing data and code used in computational studies". phys.org. Archived from the original on March 22, 2022. Retrieved March 22, 2022.
  41. ^ Stodden, Victoria; McNutt, Marcia; Bailey, David H.; Deelman, Ewa; Gil, Yolanda; Hanson, Brooks; Heroux, Michael A.; Ioannidis, John P. A.; Taufer, Michela (December 9, 2016). "Enhancing reproducibility for computational methods". Science. 354 (6317): 1240–1241. Bibcode:2016Sci...354.1240S. doi:10.1126/science.aah6168. ISSN 1095-9203. PMID 27940837. S2CID 32551384. Archived from the original on March 22, 2022. Retrieved March 22, 2022.
  42. ^ Ioannidis, John P. A.; Greenland, Sander; Hlatky, Mark A.; Khoury, Muin J.; Macleod, Malcolm R.; Moher, David; Schulz, Kenneth F.; Tibshirani, Robert (January 11, 2014). "Increasing value and reducing waste in research design, conduct, and analysis". The Lancet. 383 (9912): 166–175. doi:10.1016/S0140-6736(13)62227-8. ISSN 0140-6736. PMC 4697939. PMID 24411645.
  43. ^ Munafò, Marcus R.; Nosek, Brian A.; Bishop, Dorothy V. M.; Button, Katherine S.; Chambers, Christopher D.; Percie du Sert, Nathalie; Simonsohn, Uri; Wagenmakers, Eric-Jan; Ware, Jennifer J.; Ioannidis, John P. A. (January 10, 2017). "A manifesto for reproducible science". Nature Human Behaviour. 1 (1): 0021. doi:10.1038/s41562-016-0021. ISSN 2397-3374. PMC 7610724. PMID 33954258.
  44. ^ MacDonald, Fiona (January 11, 2017). "Scientists Have Outlined an 8-Page Plan to Fix What's Wrong With Science". ScienceAlert. Archived from the original on December 14, 2021. Retrieved March 22, 2022.
  45. ^ Ioannidis, John P. A. (October 21, 2014). "How to Make More Published Research True". PLOS Medicine. 11 (10): e1001747. doi:10.1371/journal.pmed.1001747. ISSN 1549-1676. PMC 4204808. PMID 25334033.
  46. ^ Ioannidis, John P. A. (June 21, 2016). "Why Most Clinical Research Is Not Useful". PLOS Medicine. 13 (6): e1002049. doi:10.1371/journal.pmed.1002049. ISSN 1549-1676. PMC 4915619. PMID 27328301.
  47. ^ "Ioannidis 2005 PLoS Med - Bioblast". www.bioblast.at. Archived from the original on August 6, 2016. Retrieved March 22, 2022.
  48. ^ "Article: How to Make More Published Research True • Global Health Trials". globalhealthtrials.tghn.org. Archived from the original on April 13, 2022. Retrieved March 22, 2022.
  49. ^ Woolston, Chris (October 29, 2014). "A blueprint to boost reproducibility of results". Nature. doi:10.1038/nature.2014.16222. ISSN 1476-4687. S2CID 111524123. Archived from the original on March 25, 2022. Retrieved March 25, 2022.
  50. ^ "How to improve our scientific practice? - Technology Org". October 29, 2014. Archived from the original on May 18, 2022. Retrieved March 25, 2022.
  51. ^ "Reforming Clinical Research To Reduce Waste | Science 2.0". www.science20.com. August 27, 2014. Retrieved March 25, 2022.
  52. ^ "Archived copy" (PDF). Archived from the original (PDF) on May 18, 2022.{{cite web}}: CS1 maint: archived copy as title (link)
  53. ^ Ioannidis, John P. A.; Patsopoulos, Nikolaos A.; Evangelou, Evangelos (November 3, 2007). "Uncertainty in heterogeneity estimates in meta-analyses". BMJ (Clinical Research Ed.). 335 (7626): 914–916. doi:10.1136/bmj.39343.408449.80. ISSN 1756-1833. PMC 2048840. PMID 17974687.
  54. ^ Salanti, Georgia; Ades, A. E.; Ioannidis, John P. A. (February 2011). "Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial". Journal of Clinical Epidemiology. 64 (2): 163–171. doi:10.1016/j.jclinepi.2010.03.016. ISSN 1878-5921. PMID 20688472. Archived from the original on March 24, 2022. Retrieved March 24, 2022.
  55. ^ Ioannidis, John P. A. (October 13, 2009). "Integration of evidence from multiple meta-analyses: a primer on umbrella reviews, treatment networks and multiple treatments meta-analyses". Canadian Medical Association Journal. 181 (8): 488–493. doi:10.1503/cmaj.081086. ISSN 1488-2329. PMC 2761440. PMID 19654195.
  56. ^ Bellou, Vanesa; Belbasis, Lazaros; Tzoulaki, Ioanna; Evangelou, Evangelos; Ioannidis, John P. A. (February 2016). "Environmental risk factors and Parkinson's disease: An umbrella review of meta-analyses". Parkinsonism & Related Disorders. 23: 1–9. doi:10.1016/j.parkreldis.2015.12.008. hdl:10044/1/31820. ISSN 1873-5126. PMID 26739246. Archived from the original on March 24, 2022. Retrieved March 24, 2022.
  57. ^ Sterne, Jonathan A. C.; Sutton, Alex J.; Ioannidis, John P. A.; Terrin, Norma; Jones, David R.; Lau, Joseph; Carpenter, James; Rücker, Gerta; Harbord, Roger M.; Schmid, Christopher H.; Tetzlaff, Jennifer (July 22, 2011). "Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials". BMJ (Clinical Research Ed.). 343: d4002. doi:10.1136/bmj.d4002. ISSN 1756-1833. PMID 21784880. S2CID 18638787.
  58. ^ Ioannidis, John P. A. (October 2008). "Interpretation of tests of heterogeneity and bias in meta-analysis". Journal of Evaluation in Clinical Practice. 14 (5): 951–957. doi:10.1111/j.1365-2753.2008.00986.x. ISSN 1356-1294. PMID 19018930. Archived from the original on May 18, 2022. Retrieved March 24, 2022.
  59. ^ Chavalarias, David; Ioannidis, John P. A. (November 1, 2010). "Science mapping analysis characterizes 235 biases in biomedical research". Journal of Clinical Epidemiology. 63 (11): 1205–1215. doi:10.1016/j.jclinepi.2009.12.011. ISSN 0895-4356. PMID 20400265. Archived from the original on May 18, 2022. Retrieved March 24, 2022.
  60. ^ Ioannidis, John P. A. (September 2016). "The Mass Production of Redundant, Misleading, and Conflicted Systematic Reviews and Meta-analyses". The Milbank Quarterly. 94 (3): 485–514. doi:10.1111/1468-0009.12210. ISSN 1468-0009. PMC 5020151. PMID 27620683.
  61. ^ Cappelleri, J. C.; Ioannidis, J. P.; Schmid, C. H.; de Ferranti, S. D.; Aubert, M.; Chalmers, T. C.; Lau, J. (October 23–30, 1996). "Large trials vs meta-analysis of smaller trials: how do their results compare?". JAMA. 276 (16): 1332–1338. doi:10.1001/jama.1996.03540160054033. ISSN 0098-7484. PMID 8861993. Archived from the original on March 24, 2022. Retrieved March 24, 2022.
  62. ^ Ioannidis, J. P.; Haidich, A. B.; Pappa, M.; Pantazis, N.; Kokori, S. I.; Tektonidou, M. G.; Contopoulos-Ioannidis, D. G.; Lau, J. (August 15, 2001). "Comparison of evidence of treatment effects in randomized and nonrandomized studies". JAMA. 286 (7): 821–830. doi:10.1001/jama.286.7.821. ISSN 0098-7484. PMID 11497536. Archived from the original on March 24, 2022. Retrieved March 24, 2022.
  63. ^ Belluz, Julia (February 16, 2015). "John Ioannidis has dedicated his life to quantifying how science is broken". Vox. Archived from the original on March 25, 2022. Retrieved March 25, 2022.
  64. ^ a b Rathi, Akshat (September 20, 2016). "A Stanford medical professor just exposed huge flaws in evidence used to give drug prescriptions". Quartz. Archived from the original on March 24, 2022. Retrieved March 24, 2022.
  65. ^ Harvey, Lisa A. (October 2017). "Is evidence-based practice a sinking ship?". Spinal Cord. 55 (10): 885. doi:10.1038/sc.2017.106. ISSN 1476-5624. PMID 28984316. S2CID 4702224.
  66. ^ Ioannidis, John P. A. (May 1, 2016). "Evidence-based medicine has been hijacked: a report to David Sackett". Journal of Clinical Epidemiology. 73: 82–86. doi:10.1016/j.jclinepi.2016.02.012. ISSN 0895-4356. PMID 26934549. Archived from the original on July 5, 2017. Retrieved March 30, 2022.
  67. ^ Oransky, Ivan (March 16, 2016). ""Evidence-based medicine has been hijacked:" A confession from John Ioannidis". Retraction Watch. Archived from the original on March 30, 2022. Retrieved March 30, 2022.
  68. ^ Ioannidis, John P. A.; Stuart, Michael E.; Brownlee, Shannon; Strite, Sheri A. (September 28, 2017). "How to survive the medical misinformation mess". European Journal of Clinical Investigation. 47 (11): 795–802. doi:10.1111/eci.12834. ISSN 0014-2972. PMID 28881000. S2CID 5353059.
  69. ^ "How to solve the medical misinformation mess". Lown Institute. February 14, 2020. Archived from the original on April 17, 2021. Retrieved April 1, 2022.
  70. ^ Howick, Jeremy; Koletsi, Despina; John P.A., Ioannidis; Madigan, Claire; Pandis, Nikolaos; Loef, Martin; Walach, Harald; Sauer, Sebastian; Kleijnen, Jos; Seehra, Jadbinder; Johnson, Tess; Schmidt, Stefan (2022). "Most healthcare interventions tested in Cochrane Reviews are not effective according to high quality evidence: a systematic review and meta-analysis". J Clin Epi. 148: 160–169. doi:10.1016/j.jclinepi.2022.04.017. PMID 35447356. S2CID 248250137.
  71. ^ Howick, Jeremy; Koletsi, Despina; Pandis P.A., Nikolaos; Fleming, Padhraig; Loef, Martin; Walach, Harald; Schmidt, Stefan; Ioanidis, John P.A. (2020). "The quality of evidence for medical interventions does not improve or worsen: a metaepidemiological study of Cochrane reviews" (PDF). J Clin Epidemiol. 126: 154–159. doi:10.1016/j.jclinepi.2020.08.005. PMID 32890636. S2CID 221512241.
  72. ^ Bruce, Peter. "Are Scientists Doing Too Much Research?". Scientific American Blog Network. Archived from the original on January 5, 2022. Retrieved April 9, 2022.
  73. ^ Ioannidis, John P. A. (April 10, 2018). "The Proposal to Lower P Value Thresholds to .005". JAMA. 319 (14): 1429–1430. doi:10.1001/jama.2018.1536. ISSN 0098-7484. PMID 29566133. Archived from the original on May 18, 2022. Retrieved April 1, 2022.
  74. ^ Benjamin, Daniel J.; Berger, James O.; Johannesson, Magnus; Nosek, Brian A.; Wagenmakers, E.-J.; Berk, Richard; Bollen, Kenneth A.; Brembs, Björn; Brown, Lawrence; Camerer, Colin; Cesarini, David (January 2018). "Redefine statistical significance". Nature Human Behaviour. 2 (1): 6–10. doi:10.1038/s41562-017-0189-z. hdl:10281/184094. ISSN 2397-3374. PMID 30980045. S2CID 3291437. Archived from the original on April 1, 2022. Retrieved April 1, 2022.
  75. ^ "Rethinking Science's Magic Number". www.pbs.org. February 28, 2018. Archived from the original on April 1, 2022. Retrieved April 1, 2022.
  76. ^ Panagiotou, Orestis A.; Ioannidis, John P. A.; Genome-Wide Significance Project (February 2012). "What should the genome-wide significance threshold be? Empirical replication of borderline genetic associations". International Journal of Epidemiology. 41 (1): 273–286. doi:10.1093/ije/dyr178. ISSN 1464-3685. PMID 22253303.
  77. ^ Ioannidis, John P. A. (June 4, 2019). "The Importance of Predefined Rules and Prespecified Statistical Analyses: Do Not Abandon Significance". JAMA. 321 (21): 2067–2068. doi:10.1001/jama.2019.4582. ISSN 0098-7484. PMID 30946431. S2CID 93002033. Archived from the original on May 18, 2022. Retrieved April 1, 2022.
  78. ^ Resnick, Brian (July 31, 2017). "What a nerdy debate about p-values shows about science — and how to fix it". Vox. Archived from the original on May 7, 2022. Retrieved May 12, 2022.
  79. ^ Liberati, Alessandro; Altman, Douglas G.; Tetzlaff, Jennifer; Mulrow, Cynthia; Gøtzsche, Peter C.; Ioannidis, John P. A.; Clarke, Mike; Devereaux, P. J.; Kleijnen, Jos; Moher, David (July 21, 2009). "The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration". BMJ. 339: b2700. doi:10.1136/bmj.b2700. ISSN 0959-8138. PMC 2714672. PMID 19622552. Archived from the original on April 2, 2022. Retrieved April 3, 2022.
  80. ^ Moons, Karel G. M.; Altman, Douglas G.; Reitsma, Johannes B.; Ioannidis, John P. A.; Macaskill, Petra; Steyerberg, Ewout W.; Vickers, Andrew J.; Ransohoff, David F.; Collins, Gary S. (January 6, 2015). "Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration". Annals of Internal Medicine. 162 (1): W1–73. doi:10.7326/M14-0698. hdl:1874/333472. ISSN 1539-3704. PMID 25560730. S2CID 24729487. Archived from the original on April 3, 2022. Retrieved April 3, 2022.
  81. ^ Ioannidis, John P. A.; Evans, Stephen J. W.; Gøtzsche, Peter C.; O'Neill, Robert T.; Altman, Douglas G.; Schulz, Kenneth; Moher, David; CONSORT Group (November 16, 2004). "Better reporting of harms in randomized trials: an extension of the CONSORT statement". Annals of Internal Medicine. 141 (10): 781–788. doi:10.7326/0003-4819-141-10-200411160-00009. ISSN 1539-3704. PMID 15545678. S2CID 17032571. Archived from the original on April 3, 2022. Retrieved April 3, 2022.
  82. ^ Bandholm, Thomas; Thorborg, Kristian; Ardern, Clare L.; Christensen, Robin; Henriksen, Marius (February 21, 2022). "Writing up your clinical trial report for a scientific journal: the REPORT trial guide for effective and transparent research reporting without spin". British Journal of Sports Medicine. 56 (12): 683–691. doi:10.1136/bjsports-2021-105058. ISSN 0306-3674. PMC 9163716. PMID 35193854. S2CID 247056557. Archived from the original on May 12, 2022. Retrieved May 12, 2022.
  83. ^ Zorzela, Liliane; Loke, Yoon K.; Ioannidis, John P.; Golder, Su; Santaguida, Pasqualina; Altman, Douglas G.; Moher, David; Vohra, Sunita; PRISMAHarms Group (February 1, 2016). "PRISMA harms checklist: improving harms reporting in systematic reviews". BMJ (Clinical Research Ed.). 352: i157. doi:10.1136/bmj.i157. ISSN 1756-1833. PMID 26830668. S2CID 6726816.
  84. ^ "PRISMA". prisma-statement.org. Archived from the original on March 19, 2022. Retrieved May 12, 2022.
  85. ^ Ioannidis, J. P.; Ntzani, E. E.; Trikalinos, T. A.; Contopoulos-Ioannidis, D. G. (November 2001). "Replication validity of genetic association studies". Nature Genetics. 29 (3): 306–309. doi:10.1038/ng749. ISSN 1061-4036. PMID 11600885. S2CID 6742347. Archived from the original on April 13, 2022. Retrieved April 4, 2022.
  86. ^ McCarthy, Mark I.; Abecasis, Gonçalo R.; Cardon, Lon R.; Goldstein, David B.; Little, Julian; Ioannidis, John P. A.; Hirschhorn, Joel N. (May 2008). "Genome-wide association studies for complex traits: consensus, uncertainty and challenges". Nature Reviews Genetics. 9 (5): 356–369. doi:10.1038/nrg2344. ISSN 1471-0064. PMID 18398418. S2CID 15032294. Archived from the original on April 8, 2022. Retrieved April 4, 2022.
  87. ^ a b Holden (June 6, 2013). "Meta-research update". The GiveWell Blog. Archived from the original on May 17, 2021. Retrieved May 12, 2022.
  88. ^ Ioannidis, John P. A.; Gwinn, Marta; Little, Julian; Higgins, Julian P. T.; Bernstein, Jonine L.; Boffetta, Paolo; Bondy, Melissa; Bray, Molly S.; Brenchley, Paul E.; Buffler, Patricia A.; Casas, Juan Pablo (January 2006). "A road map for efficient and reliable human genome epidemiology". Nature Genetics. 38 (1): 3–5. doi:10.1038/ng0106-3. ISSN 1061-4036. PMID 16468121. S2CID 23985692. Archived from the original on May 25, 2021. Retrieved April 4, 2022.
  89. ^ Armitage, Hanae (July 16, 2018). "5 Questions: John Ioannidis calls for more rigorous nutrition research". Stanford Medicine News Center. Archived from the original on April 11, 2022. Retrieved May 12, 2022.
  90. ^ "Diet: Is nutrition science a more reliable source of advice than your grandmother?". To infinity, and beyond!. December 15, 2019. Archived from the original on April 20, 2021. Retrieved May 12, 2022.
  91. ^ Schoenfeld, Jonathan D; Ioannidis, John PA (2013). "Is everything we eat associated with cancer? A systematic cookbook review". The American Journal of Clinical Nutrition. 97 (1): 127–134. doi:10.3945/ajcn.112.047142. PMID 23193004.
  92. ^ O'Connor, Anahad (September 29, 2018). "More Evidence That Nutrition Studies Don't Always Add Up". The New York Times. ISSN 0362-4331. Archived from the original on April 7, 2022. Retrieved April 6, 2022.
  93. ^ Gardner, Christopher D.; Trepanowski, John F.; Del Gobbo, Liana C.; Hauser, Michelle E.; Rigdon, Joseph; Ioannidis, John P. A.; Desai, Manisha; King, Abby C. (February 20, 2018). "Effect of Low-Fat vs Low-Carbohydrate Diet on 12-Month Weight Loss in Overweight Adults and the Association With Genotype Pattern or Insulin Secretion: The DIETFITS Randomized Clinical Trial". JAMA. 319 (7): 667–679. doi:10.1001/jama.2018.0245. ISSN 0098-7484. PMC 5839290. PMID 29466592. Archived from the original on May 18, 2022. Retrieved April 6, 2022.
  94. ^ "Low-fat or low-carb? It's a draw, study finds". ScienceDaily. Archived from the original on May 12, 2022. Retrieved May 12, 2022.
  95. ^ Ioannidis, John P. A.; Loy, En Yun; Poulton, Richie; Chia, Kee Seng (November 18, 2009). "Researching Genetic Versus Nongenetic Determinants of Disease: A Comparison and Proposed Unification". Science Translational Medicine. 1 (7): 7ps8. doi:10.1126/scitranslmed.3000247. ISSN 1946-6234. PMID 20368180. S2CID 366302. Archived from the original on April 7, 2022. Retrieved April 7, 2022.
  96. ^ von Stumm, Sophie; d’Apice, Katrina (January 2022). "From Genome-Wide to Environment-Wide: Capturing the Environome". Perspectives on Psychological Science. 17 (1): 30–40. doi:10.1177/1745691620979803. ISSN 1745-6916. PMC 8785306. PMID 33645332.
  97. ^ Hsing, Ann W.; Ioannidis, John P. A. (September 2015). "Nationwide Population Science: Lessons From the Taiwan National Health Insurance Research Database". JAMA Internal Medicine. 175 (9): 1527–1529. doi:10.1001/jamainternmed.2015.3540. ISSN 2168-6114. PMID 26192815. Archived from the original on April 7, 2022. Retrieved April 7, 2022.
  98. ^ Khoury, Muin J.; Ioannidis, John P. A. (November 28, 2014). "Big data meets public health". Science. 346 (6213): 1054–1055. Bibcode:2014Sci...346.1054K. doi:10.1126/science.aaa2709. ISSN 0036-8075. PMC 4684636. PMID 25430753.
  99. ^ Nagendran, Myura; Chen, Yang; Lovejoy, Christopher A.; Gordon, Anthony C.; Komorowski, Matthieu; Harvey, Hugh; Topol, Eric J.; Ioannidis, John P. A.; Collins, Gary S.; Maruthappu, Mahiben (March 25, 2020). "Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies". BMJ. 368: m689. doi:10.1136/bmj.m689. ISSN 1756-1833. PMC 7190037. PMID 32213531. Archived from the original on April 7, 2022. Retrieved April 7, 2022.
  100. ^ Journal, British Medical. "Concerns over 'exaggerated' study claims of AI outperforming doctors". medicalxpress.com. Archived from the original on November 28, 2020. Retrieved May 12, 2022.
  101. ^ Cipriani, Andrea; Furukawa, Toshi A.; Salanti, Georgia; Chaimani, Anna; Atkinson, Lauren Z.; Ogawa, Yusuke; Leucht, Stefan; Ruhe, Henricus G.; Turner, Erick H.; Higgins, Julian P. T.; Egger, Matthias (April 7, 2018). "Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis". Lancet. 391 (10128): 1357–1366. doi:10.1016/S0140-6736(17)32802-7. ISSN 1474-547X. PMC 5889788. PMID 29477251.
  102. ^ "Anti-depressants: Major study finds they work". BBC News. February 22, 2018. Archived from the original on April 8, 2022. Retrieved April 8, 2022.
  103. ^ "These Antidepressants Are Most Effective, Study Says". Time. Archived from the original on April 8, 2022. Retrieved April 8, 2022.
  104. ^ Ebrahim, Shanil; Bance, Sheena; Athale, Abha; Malachowski, Cindy; Ioannidis, John P. A. (February 1, 2016). "Meta-analyses with industry involvement are massively published and report no caveats for antidepressants". Journal of Clinical Epidemiology. 70: 155–163. doi:10.1016/j.jclinepi.2015.08.021. ISSN 0895-4356. PMID 26399904. Archived from the original on September 14, 2018. Retrieved April 8, 2022.
  105. ^ "Reviews Of Medical Studies May Be Tainted By Funders' Influence". NPR.org. Archived from the original on April 8, 2022. Retrieved April 8, 2022.
  106. ^ Leichsenring, Falk; Steinert, Christiane; Rabung, Sven; Ioannidis, John P.A. (February 2022). "The efficacy of psychotherapies and pharmacotherapies for mental disorders in adults: an umbrella review and meta-analytic evaluation of recent meta-analyses". World Psychiatry. 21 (1): 133–145. doi:10.1002/wps.20941. ISSN 1723-8617. PMC 8751557. PMID 35015359.
  107. ^ Button, Katherine S.; Ioannidis, John P. A.; Mokrysz, Claire; Nosek, Brian A.; Flint, Jonathan; Robinson, Emma S. J.; Munafò, Marcus R. (May 2013). "Power failure: why small sample size undermines the reliability of neuroscience". Nature Reviews Neuroscience. 14 (5): 365–376. doi:10.1038/nrn3475. ISSN 1471-0048. PMID 23571845. S2CID 455476.
  108. ^ "Bad Stats Plague Neuroscience". The Scientist Magazine®. Archived from the original on April 4, 2022. Retrieved April 9, 2022.
  109. ^ Ioannidis, John P. A.; Stanley, T. D.; Doucouliagos, Hristos (October 1, 2017). "The Power of Bias in Economics Research". The Economic Journal. 127 (605): F236–F265. doi:10.1111/ecoj.12461. ISSN 0013-0133. S2CID 158829482.
  110. ^ a b Rogers, Adam. "A New Study of Economics as a Science Says It's Still Dismal". Wired. ISSN 1059-1028. Archived from the original on March 20, 2022. Retrieved April 9, 2022.
  111. ^ "European Journal of Clinical Investigation". www.wolterskluwer.com. Archived from the original on February 13, 2022. Retrieved February 13, 2022.
  112. ^ a b "BMC Infectious Diseases". BioMed Central. Archived from the original on February 13, 2022. Retrieved February 13, 2022.
  113. ^ a b "Editorial_Board". Oxford Academic. Archived from the original on February 13, 2022. Retrieved February 13, 2022.
  114. ^ "About This Journal". JAMA. 307 (20): 2127. May 23, 2012. doi:10.1001/jama.307.20.2127. ISSN 0098-7484.
  115. ^ "Editorial Board - Journal of Clinical Epidemiology - Journal - Elsevier". www.journals.elsevier.com. Archived from the original on May 18, 2022. Retrieved February 13, 2022.
  116. ^ "Reviewers". The Journal of Infectious Diseases. 188 (12): 1962–1965. December 15, 2003. doi:10.1086/380619. ISSN 0022-1899.
  117. ^ Kehoe, Patrick; Cerhan, James R; Pedersen, Nancy; Wei, Qingyi; Ambrosone, Christine B; Arnett, Donna K (March 31, 2010). "Editorial Board of International Journal of Molecular Epidemiology and Genetics (As of March 31, 2010)". International Journal of Molecular Epidemiology and Genetics. 1 (1): 83. ISSN 1948-1756. PMC 3076753. PMID 21537455.
  118. ^ "Journal of Translational Medicine". BioMed Central. Archived from the original on May 18, 2022. Retrieved February 13, 2022.
  119. ^ "Journal of Evaluation in Clinical Practice". Wiley Online Library. doi:10.1111/(ISSN)1365-2753. Archived from the original on May 18, 2022. Retrieved February 13, 2022.
  120. ^ "Editorial Board". Oxford Academic. Archived from the original on October 30, 2021. Retrieved February 13, 2022.
  121. ^ "Physiological Reviews". Physiological Reviews. Retrieved February 13, 2022.[dead link‍]
  122. ^ "Royal Society Open Science". Royal Society Open Science. 2014. doi:10.1098/rsos.
  123. ^ "Research Integrity and Peer Review". BioMed Central. Archived from the original on February 13, 2022. Retrieved February 13, 2022.
  124. ^ "Biomarker Research". BioMed Central. Archived from the original on February 13, 2022. Retrieved February 13, 2022.
  125. ^ "Diagnostic and Prognostic Research". BioMed Central. Archived from the original on February 14, 2022. Retrieved February 14, 2022.
  126. ^ a b c d e "Ioannidis". MIDAS. Archived from the original on February 14, 2022. Retrieved February 14, 2022.
  127. ^ Ioannidis, John P. A.; Boyack, Kevin W.; Baas, Jeroen (October 16, 2020). "Updated science-wide author databases of standardized citation indicators". PLOS Biology. 18 (10): e3000918. doi:10.1371/journal.pbio.3000918. ISSN 1545-7885. PMC 7567353. PMID 33064726.
  128. ^ a b c d Jamison, Peter (December 16, 2020). "A top scientist questioned virus lockdowns on Fox News. The backlash was fierce". The Washington Post. Archived from the original on February 23, 2021. Retrieved March 25, 2021.
  129. ^ a b c d e "What the heck happened to John Ioannidis?". Science-Based Medicine. March 29, 2021. Archived from the original on March 31, 2021. Retrieved March 31, 2021.
  130. ^ Sridhar, Devi (March 24, 2022). "Why can't some scientists just admit they were wrong about Covid?". The Guardian. Archived from the original on March 24, 2022. Retrieved March 24, 2022.
  131. ^ Lipsitch, Marc (March 18, 2020). "We know enough now to act decisively against Covid-19. Social distancing is a good place to start". Archived from the original on October 19, 2020. Retrieved October 20, 2020.
  132. ^ Ting, Eric (May 12, 2020). "Researchers adjust results of startling Santa Clara antibody study". SF Gate. Archived from the original on August 7, 2020. Retrieved August 8, 2020.
  133. ^ Mallapaty, Smriti (April 17, 2020). "Antibody tests suggest that coronavirus infections vastly exceed official counts". Nature. doi:10.1038/d41586-020-01095-0. PMID 32303734. S2CID 215810316. Archived from the original on November 21, 2020. Retrieved November 25, 2020.
  134. ^ McCormick, Erin (April 23, 2020). "Why experts are questioning two hyped antibody studies in coronavirus hotspots". The Guardian. Archived from the original on June 1, 2020. Retrieved November 21, 2020.
  135. ^ Vogel, Gretchen (April 21, 2020). "Antibody surveys suggesting vast undercount of coronavirus infections may be unreliable". Science. doi:10.1126/science.abc3831.
  136. ^ Schulson, Michael (April 24, 2020). "A Respected Science Watchdog Raises Eyebrows". Undark Magazine. Archived from the original on December 4, 2020. Retrieved November 22, 2020.
  137. ^ "Why unreliable tests are flooding the coronavirus conversation". National Geographic. May 6, 2020. Archived from the original on November 19, 2020. Retrieved November 25, 2020.
  138. ^ "Intubations and Accusations: Doctors were "just going crazy, and intubating people who did not have to be intubated"". Science-Based Medicine. September 19, 2021. Archived from the original on November 30, 2021. Retrieved November 30, 2021.
  139. ^ Lee, Stephanie (May 15, 2020). "JetBlue's Founder Helped Fund A Stanford Study That Said The Coronavirus Wasn't That Deadly". Buzzfeed. Archived from the original on May 29, 2020. Retrieved May 30, 2020.
  140. ^ Landsverk, Gabby. "A controversial study on coronavirus was partly funded by an airline founder who's criticized lockdowns, according to a new investigation from BuzzFeed News". Business Insider. Archived from the original on May 30, 2020. Retrieved May 30, 2020.
  141. ^ Brownlee, Jeanne Lenzer, Shannon. "The COVID Science Wars". Scientific American. Archived from the original on December 1, 2020. Retrieved December 1, 2020.{{cite web}}: CS1 maint: multiple names: authors list (link)
  142. ^ "The Herd Immunity Taboo". Tablet Magazine. May 20, 2020. Archived from the original on April 6, 2021. Retrieved March 29, 2021.
  143. ^ Ioannidis, John P. A. (2021). "Reconciling estimates of global spread and infection fatality rates of COVID-19: an overview of systematic evaluations". European Journal of Clinical Investigation. 51 (5): e13554. doi:10.1111/eci.13554. ISSN 1365-2362. PMC 8250317. PMID 33768536.
  144. ^ Piscitelli, Prisco; Miani, Alessandro; Setti, Leonardo; De Gennaro, Gianluigi; Rodo, Xavier; Artinano, Begona; Vara, Elena; Rancan, Lisa; Arias, Javier; Passarini, Fabrizio; Barbieri, Pierluigi (February 26, 2022). "The role of outdoor and indoor air quality in the spread of SARS-CoV-2: Overview and recommendations by the research group on COVID-19 and particulate matter (RESCOP commission)". Environmental Research. 211: 113038. Bibcode:2022ER....21113038P. doi:10.1016/j.envres.2022.113038. ISSN 0013-9351. PMC 8881809. PMID 35231456.
  145. ^ Knapton, Sarah (February 15, 2022). "Lockdown debate skewed because sceptical scientists were shunned on social media". The Telegraph. ISSN 0307-1235. Archived from the original on February 27, 2022. Retrieved March 3, 2022.
  146. ^ Ioannidis, John (February 1, 2022). "Citation impact and social media visibility of Great Barrington and John Snow signatories for COVID-19 strategy". BMJ Open. 12 (2): e052891. doi:10.1136/bmjopen-2021-052891. ISSN 2044-6055. PMC 8829837. PMID 35140152. Archived from the original on April 5, 2022. Retrieved April 10, 2022.
  147. ^ Yarney, Gavin M.; et al. (March 3, 2022). "A Simple Request to Professor Ioannidis: Please Address Our Concerns". BMJ Open. 12 (2): e052891. doi:10.1136/bmjopen-2021-052891. PMC 8829837. PMID 35140152. Archived from the original on May 13, 2022. Retrieved May 12, 2022.
  148. ^ Ioannidis, John P. (February 1, 2022). "Citation impact and social media visibility of Great Barrington and John Snow signatories for COVID-19 strategy". BMJ Open. 12 (2): e052891. doi:10.1136/bmjopen-2021-052891. ISSN 2044-6055. PMC 8829837. PMID 35140152.
  149. ^ Freedman, David H. (October 4, 2010). "Lies, Damned Lies, and Medical Science". The Atlantic. Archived from the original on August 24, 2020. Retrieved August 26, 2020.
  150. ^ "November 2010 Issue". The Atlantic. Archived from the original on March 23, 2021. Retrieved March 31, 2021.
  151. ^ Begley, Sharon (January 23, 2011). "Why Almost Everything You Hear About Medicine Is Wrong". Newsweek. Archived from the original on February 15, 2022. Retrieved February 15, 2022.
  152. ^ "Richard Smith: Time for science to be about truth rather than careers". The BMJ. September 9, 2013. Archived from the original on February 15, 2022. Retrieved February 15, 2022.
  153. ^ "Combating bad science: Metaphysicians". The Economist. Archived from the original on September 18, 2017. Retrieved September 1, 2017.
  154. ^ Johnson, George (January 20, 2014). "New Truths That Only One Can See". The New York Times. ISSN 0362-4331. Archived from the original on February 3, 2022. Retrieved February 15, 2022.
  155. ^ Ioannidis, J. (2015). "John Ioannidis: Uncompromising gentle maniac". BMJ. 351: h4992. doi:10.1136/bmj.h4992. ISSN 1756-1833. PMID 26404555. S2CID 10953475.
  156. ^ says, Johnny Johnson (July 16, 2019). "Fixing health care's replication crisis is important for researchers and patients". STAT. Archived from the original on February 18, 2022. Retrieved February 18, 2022.
  157. ^ Elsevier. "Reproducibility in research: taming a "complex beast"". Elsevier Connect. Archived from the original on March 22, 2022. Retrieved March 22, 2022.
  158. ^ Smith, Jeffrey Lee Funk and Gary N. "'Fake it till you make it' is an old trick Silicon Valley startups use to get money. Starry-eyed stock investors keep falling for it". MarketWatch. Retrieved February 8, 2023.
  159. ^ "The science crisis". Washington Examiner. April 29, 2022. Retrieved February 8, 2023.
  160. ^ "Stanford professor John Ioannidis elected member of National Academy of Medicine | eKathimerini.com". www.ekathimerini.com. Retrieved June 7, 2022.
  161. ^ "ΙΩΑΝΝΗΣ Π.Α. ΙΩΑΝΝΙΔΗΣ | Εταιρεία Συγγραφέων". www.authors.gr. Retrieved June 7, 2022.
  162. ^ a b "EBHC International Conference 2019 - John Ioannidis". www.ebhcconference.org. Retrieved June 7, 2022.
  163. ^ a b "Association of American Physicians". aap-online.org. Retrieved June 7, 2022.
  164. ^ "Meet the honorary degree recipients of Fall 2024". Daily News. Retrieved November 18, 2024.
  165. ^ "Program at a glance". European Journal of Clinical Investigation. 51 (S1): e13566. 2021. doi:10.1111/eci.13566. hdl:10174/31004. ISSN 1365-2362. S2CID 235382244. Archived from the original on February 4, 2022. Retrieved February 3, 2022.
  166. ^ Max-Delbrück-Centrum, Berliner Institut für Gesundheitsforschung-Charité und. "Visiting Fellows - BIH at Charité". www.bihealth.org. Archived from the original on February 3, 2022. Retrieved February 2, 2022.
  167. ^ "Novim 2018 Awards" (PDF). May 7, 2018. Archived (PDF) from the original on February 3, 2022. Retrieved February 3, 2022.
  168. ^ "Chanchlani Award Recognizes One of the Most Influential Scientists Alive". Global Health Graduate Programs. February 7, 2017. Archived from the original on February 3, 2022. Retrieved February 3, 2022.
  169. ^ "David-Sackett-Preis". EbM-Netzwerk (in German). Archived from the original on January 20, 2022. Retrieved February 3, 2022.
  170. ^ Σπαγαδώρου, Νατάσσα Ν (November 12, 2016). "Η Ελληνική Φαρμακευτική Εταιρεία βραβεύει τον ερευνητή των... ερευνών". Onmed.gr (in Greek). Archived from the original on February 3, 2022. Retrieved February 3, 2022.
  171. ^ "John Ioannidis to TC Doctoral Students: Saving Science and Humanity Begins with | Teachers College, Columbia University". Teachers College - Columbia University. Archived from the original on February 3, 2022. Retrieved February 3, 2022.
  172. ^ "The Esci Award for Excellence in Clinical Science". European Journal of Clinical Investigation. 37 (6): 528. 2007. doi:10.1111/j.1365-2362.2007.01831.x. ISSN 1365-2362. S2CID 221679709.
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