Peer-Reviewed Studies Flawed

[Monica]

Scientific peer reviews are a 'sacred cow' ready to be slaughtered, says former editor of BMJ

The peer review process – long considered the gold standard of quality scientific research – is a “sacred cow” that should be slaughtered, the former editor of one of the country’s leading medical journals has said.

Richard Smith, who edited the British Medical Journal for more than a decade, said there was no evidence that peer review was a good method of detecting errors and claimed that “most of what is published in journals is just plain wrong or nonsense”.

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Speaking at a Royal Society event earlier this week, he said an experiment conducted during his time at the BMJ, in which eight deliberate errors were included in a short paper sent to 300 reviewers, had exposed how easily the peer review process could fail.

“No-one found more than five, the median was two, and 20 per cent didn’t spot any,” he was quoted as saying by Times Higher Education. “If peer review was a drug it would never get on the market because we have lots of evidence of its adverse effects and don’t have evidence of its benefit.”

He said the process of peer review before publication could also work against innovative papers, was open to abuse, and should be done away with in favour of “the real peer review” of the wider scientific community post-publication.

“It’s time to slaughter the sacred cow,” he said...

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His comments come at a time of serious soul-searching within the scientific community, over the quality of much published research.

The editor of the second of the country’s two leading medical journals, Dr Richard Horton of The Lancet, wrote in an editorial earlier this month that “much of the scientific literature, perhaps half, may simply be untrue”, blaming, among other things, studies with small sample sizes, researchers’ conflicts of interest and “an obsession” among scientists for pursuing fashionable trends of dubious importance”.

“The apparent endemicity of bad research behaviour is alarming,” he wrote. “In their quest for telling a compelling story, scientists too often sculpt their data to fit their preferred theory of the world.”