I mentioned before that 1/3 of medical studies are wrong. Turns out there is less than a 50% chance that a scientific paper is true.

This is significant because a paper is what scientists publish in journals to give the information from their studies. And these papers are what the next person relies on to assume information and build upon.

Most published scientific research papers are wrong, according to a new analysis. Assuming that the new paper is itself correct, problems with experimental and statistical methods mean that there is less than a 50% chance that the results of any randomly chosen scientific paper are true.

John Ioannidis, an epidemiologist at the University of Ioannina School of Medicine in Greece, says that small sample sizes, poor study design, researcher bias, and selective reporting and other problems combine to make most research findings false. But even large, well-designed studies are not always right, meaning that scientists and the public have to be wary of reported findings.

“We should accept that most research findings will be refuted. Some will be replicated and validated. The replication process is more important than the first discovery,” Ioannidis says.

In the paper, Ioannidis does not show that any particular findings are false. Instead, he shows statistically how the many obstacles to getting research findings right combine to make most published research wrong.

…But Solomon Snyder, senior editor at the Proceedings of the National Academy of Sciences, and a neuroscientist at Johns Hopkins Medical School in Baltimore, US, says most working scientists understand the limitations of published research.

“When I read the literature, I’m not reading it to find proof like a textbook. I’m reading to get ideas. So even if something is wrong with the paper, if they have the kernel of a novel idea, that’s something to think about,” he says.

However, as I said above, the papers are used as stepping stones. If you step on a stone and it turns out later it was a lily pad, then you’re sunk in a big lake without any useful information for all the time and money you put in.