John P. A. Ioannidis ( ; , ; born 21 August 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 (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.
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.
Early life and education Born in New York City in 1965, Ioannidis was raised in Athens, Greece.John Ioannidis , Harvard School of Public Health. 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. 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 and received a PhD in biopathology at the University of Athens (1996).
Career He is a highly cited medical researcher, with an h-index of 278 on Google Scholar in January 2026.
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. He has also been president of the Society for Research Synthesis Methodology.
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. 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.
Research
Ioannidis's 2005 paper "Why Most Published Research Findings Are False" is the most downloaded paper in the Public Library of Science. 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, clinical trials, neuroscience, and nutrition. His work has aimed to identify solutions to problems in research, and on how to perform research more optimally. In a series of five papers about research published in The Lancet and titled "Research: increasing value, reducing waste", 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 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.
Ioannidis's research at Stanford focuses on meta-analysis and meta-research – the study of studies. 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.
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.
Meta-research 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)". 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, social sciences, and psychology. He has led or co-led efforts to define and improve reproducibility in science, e.g. computational reproducibility, and to reduce research waste in study design, conduct, and analysis. Ioannidis has co-authored the Manifesto for Reproducible Science, an eight-page document illuminating the need to fix the flaws in the current scientific process and mitigate the "reproducibility crisis" in science.
In "Why Most Published Research Findings are False" (2005), Ioannidis focused on why most published research findings cannot be validated. 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 and in a third paper (2016) he showed why clinical research in particular is usually not useful and how this can be amended. 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". 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". 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. 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.
Meta-analysis 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, methods for meta-analysis involving multiple treatments, methods and processes for umbrella reviews, 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. He has also alerted about the misuse and misinterpretation of bias tests. Along with David Chavalarias, he catalogued 235 biases across the entire publication record of biomedical research. 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. He has performed empirical evaluations of the concordance of results between meta-analyses and large trials and between randomized trials and non-randomized studies.
Evidence-based medicine 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. In an essay written to honor his late mentor David Sackett, he stated that:
He has described four inter-related problems that create what he calls the Medical Misinformation Mess:
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 and a related study showing that the quality of this evidence does not seem to improve over time.
Statistical methods and inference Ioannidis has made methodological and conceptual contributions to the debates surrounding the use and misuse of statistical methods and inference. He has been an advocate of the approach to redefine statistical significance by requesting more stringent statistical significance thresholds; he has proposed and empirically validated stringent thresholds for genome-wide significance in genetics; and has been critical of the approach to entirely abandon statistical significance.
Reporting guidelines Ioannidis has contributed to several influential guidelines for reporting different types of research, such as PRISMA for meta-analyses, TRIPOD for multivariable prognostic and diagnostic models, 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 and has contributed to PRISMA for harms, a guideline for reporting of harms in meta-analyses.
Genetic and molecular epidemiology Ioannidis was one of the first to advocate the use of meta-analysis in genetic epidemiology to assess replication and the incorporation of meta-analysis in large-scale consortia of multiple investigators performing genome-wide association studies. He led and contributed to many such efforts in diverse areas of genetic epidemiology and in other areas of molecular epidemiology.
Nutrition Ioannidis has been critical of nutritional epidemiology research practices and has recommended reforms to improve the credibility of research in the field. 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 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.
Association studies and big data 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. 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. He has worked on the potential uses of such approaches in big data and artificial intelligence.
Psychiatry 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. He has identified the potential for sponsorship bias in meta-analyses in mental health 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.
Neuroscience