In New York Times Magazine, January 2006:
Many of us consider science the most reliable, accountable way of explaining how the world works. We trust it. Should we? John Ioannidis, an epidemiologist, recently concluded that most articles published by biomedical journals are flat-out wrong. The sources of error, he found, are numerous: the small size of many studies, for instance, often leads to mistakes, as does the fact that emerging disciplines, which lately abound, may employ standards and methods that are still evolving. Finally, there is bias, which Ioannidis says he believes to be ubiquitous. Bias can take the form of a broadly held but dubious assumption, a partisan position in a longstanding debate (e.g., whether depression is mostly biological or environmental) or (especially slippery) a belief in a hypothesis that can blind a scientist to evidence contradicting it. These factors, Ioannidis argues, weigh especially heavily these days and together make it less than likely that any given published finding is true.