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  1. Informed Consent, Big Data, and the Oxymoron of Research That Is Not Research.John P. A. Ioannidis - 2013 - American Journal of Bioethics 13 (4):40 - 42.
    (2013). Informed Consent, Big Data, and the Oxymoron of Research That Is Not Research. The American Journal of Bioethics: Vol. 13, No. 4, pp. 40-42. doi: 10.1080/15265161.2013.768864.
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    When Null Hypothesis Significance Testing Is Unsuitable for Research: A Reassessment.Denes Szucs & John P. A. Ioannidis - 2017 - Frontiers in Human Neuroscience 11.
  3.  92
    Ethics and Epistemology in Big Data Research.Wendy Lipworth, Paul H. Mason, Ian Kerridge & John P. A. Ioannidis - 2017 - Journal of Bioethical Inquiry 14 (4):489-500.
    Biomedical innovation and translation are increasingly emphasizing research using “big data.” The hope is that big data methods will both speed up research and make its results more applicable to “real-world” patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, (...)
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    Medical necessity under weak evidence and little or perverse regulatory gatekeeping.John P. A. Ioannidis - 2023 - Clinical Ethics 18 (3):330-334.
    Medical necessity (claiming that a medical intervention or care is – at minimum – reasonable, appropriate and acceptable) depends on empirical evidence and on the interpretation of that evidence. Evidence and its interpretation define the standard of care. This commentary argues that both the evidence base and its interpretation are currently weak gatekeepers. Empirical meta-research suggests that very few medical interventions have high quality evidence in support of their effectiveness and very few of them also have relatively thorough assessments of (...)
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    Therapy and prevention for mental health: What if mental diseases are mostly not brain disorders?John P. A. Ioannidis - 2019 - Behavioral and Brain Sciences 42.
    Neurobiology-based interventions for mental diseases and searches for useful biomarkers of treatment response have largely failed. Clinical trials should assess interventions related to environmental and social stressors, with long-term follow-up; social rather than biological endpoints; personalized outcomes; and suitable cluster, adaptive, and n-of-1 designs. Labor, education, financial, and other social/political decisions should be evaluated for their impacts on mental disease.
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    Interpretation of tests of heterogeneity and bias in meta‐analysis.John P. A. Ioannidis - 2008 - Journal of Evaluation in Clinical Practice 14 (5):951-957.
  7. Hypothesis, analysis and synthesis, it’s all Greek to me.Ioannis Iliopoulos, Sophia Ananiadou, Antoine Danchin, John P. A. Ioannidis, Peter D. Katsidis, Christos A. Ouzounis & Vasilis J. Promponas - 2019 - eLife 8:e43514.
    The linguistic foundations of science and technology include many terms that have been borrowed from ancient languages. In the case of terms with origins in the Greek language, the modern meaning can often differ significantly from the original one. Here we use the PubMed database to demonstrate the prevalence of words of Greek origin in the language of modern science, and call for scientists to exercise care when coining new terms.
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    Science with or without statistics: Discover-generalize-replicate? Discover-replicate-generalize?John P. A. Ioannidis - 2022 - Behavioral and Brain Sciences 45.
    Overstated generalizability is common in research. It may coexist with inflation of the magnitude and statistical support for effects and dismissal of internal validity problems. Generalizability may be secured before attempting replication of proposed discoveries or replication may precede efforts to generalize. These opposite approaches may decrease or increase, respectively, the use of inferential statistics with advantages and disadvantages.
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    Translational Research May Be Most Successful When It Fails.John P. A. Ioannidis - 2015 - Hastings Center Report 45 (2):39-40.
    In this issue of the Hastings Center Report, Jonathan Kimmelman and Alex London argue that in assessing the success of clinical translation, it is narrow‐minded to focus only on how many new drugs get licensed and how quickly they achieve licensure. Kimmelman and London show that clinical translation should be judged on its ability to generate as comprehensive an intervention ensemble as possible for the tested interventions. I would like to extend Kimmelman and London's position in two ways. First, I (...)
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    Why replication has more scientific value than original discovery.John P. A. Ioannidis - 2018 - Behavioral and Brain Sciences 41.
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  11. Effectiveness of antidepressants: an evidence myth constructed from a thousand randomized trials? [REVIEW]John P. A. Ioannidis - 2008 - Philosophy, Ethics, and Humanities in Medicine 3:14.
    Antidepressants, in particular newer agents, are among the most widely prescribed medications worldwide with annual sales of billions of dollars. The introduction of these agents in the market has passed through seemingly strict regulatory control. Over a thousand randomized trials have been conducted with antidepressants. Statistically significant benefits have been repeatedly demonstrated and the medical literature is flooded with several hundreds of.
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