Ioannidis: why most published research findings are false

John Ioannidis publishes the most-cited paper in the history of medicine, mathematically demonstrating that most published research findings are likely false.

Ioannidis's paper 'Why Most Published Research Findings Are False' (2005) used a Bayesian model to show that, under conditions common in biomedical research — low statistical power, small effect sizes, analytical flexibility, and conflicts of interest — most published findings are probably false.

The key argument is that the post-study probability (positive predictive value) depends not just on the p-value, but on the prior probability, statistical power, and the number of teams investigating the same question.

The paper has been cited over 12,000 times and catalyzed the open science movement. It inspired large-scale replication projects and reforms in scientific publishing policies.

Ioannidis's recommendations — larger sample sizes, pre-registration, replications, and meta-analyses — have become standards in many areas of psychology and medicine.

Significance: This is one of the most significant developments in the psychology of our time. Its repercussions continue to be felt years later and have fundamentally changed how we understand the human mind and clinical practice.