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How to Make More Published Research True - John Ioannidis

Simon

Senior Member
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Location
Monmouth, UK
Another fine salvo from Dr John "Most published research is False" Ioannidis at Stanford

PLOS Medicine: How to Make More Published Research True

Summary Points
  • Currently, many published research findings are false or exaggerated, and an estimated 85% of research resources are wasted.
  • To make more published research true, practices that have improved credibility and efficiency in specific fields may be transplanted to others which would benefit from them—possibilities include:
  1. the adoption of large-scale collaborative research;
  2. replication culture; registration;
  3. sharing;
  4. reproducibility practices;
  5. better statistical methods;
  6. standardization of definitions and analyses;
  7. more appropriate (usually more stringent) statistical thresholds;
  8. and improvement in study design standards, peer review, reporting and dissemination of research, and training of the scientific workforce.
  • Selection of interventions to improve research practices requires rigorous examination and experimental testing whenever feasible.
  • Optimal interventions need to understand and harness the motives of various stakeholders who operate in scientific research and who differ on the extent to which they are interested in promoting publishable, fundable, translatable, or profitable results.
  • Modifications need to be made in the reward system for science, affecting the exchange rates for currencies (e.g., publications and grants) and purchased academic goods (e.g., promotion and other academic or administrative power) and introducing currencies that are better aligned with translatable and reproducible research.
The achievements of scientific research are amazing... However, true and readily applicable major discoveries are far fewer. Many new proposed associations and/or effects are false or grossly exaggerated [2],[3], ...

Given the abundance of data, research on research (i.e., meta-research) can derive empirical estimates of the prevalence of risk factors for high false-positive rates (underpowered studies; small effect sizes; low pre-study odds; flexibility in designs, definitions, outcomes, analyses; biases and conflicts of interest; bandwagon patterns; and lack of collaboration) [3]. Currently, an estimated 85% of research resources are wasted [5].

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