What I've Learned: All about science...

When medical science said to stop eating eggs, I didn't. I like eggs.

When medical science, the government, and a million tv commercials said that fat is bad for us and we should drastically reduce our intake, I didn't. I like fat. I like whole milk. I love butter. Low-fat cookies are, to me, nonsensical.

When medical science said that aluminum caused Alzheimer's, everyone threw their aluminum cookware away. I kept mine.

Now research shows that eggs are okay to eat, reducing fat in our diets seems to have done more harm than good and made us fatter, not skinnier, and aluminum in the brain is an effect of Alzheimer’s, not the cause.

I smile, cook my omelet in my aluminum pan--in butter--and wash it down with a glass of whole milk.

How is it that scientists, particularly medical researchers, manage to reach such amazingly wrong conclusions--conclusions that are later overturned?

John Ioannidis can tell you.

A few years back, Ioannidis did a statistical analysis of major medical research papers. He found that the most popular papers, and hence the most behavior-changing ones, had results that were later reversed after further study. Ioannidis wrote a paper that summed up what he and his team found. It's called "Why Most Published Research Findings Are False." Here are some of the conclusions it makes:

The smaller the study, the more likely it's wrong.

The smaller the effect seen in a study, the more likely it's wrong.

The more variables tested in a study, the more likely it's wrong.

The more flexible designs, definitions, and outcomes are, the more likely it's wrong.

The greater the financial interest in it being right, the more likely it's wrong.

The hotter the field of research, the more likely it's wrong.

In September of this year, Ioannidis, who is a medical doctor and holds a doctorate in science, became division chief of the Stanford Prevention Research Center. Suddenly there is renewed interest in his 2005 paper.

In the November issue of Atlantic magazine (on news stands now), there's an article called "Lies, Damned Lies, and Medical Science," by David H. Freedman. In it, Dr. Ioannidis tells why bone-headed conclusions from badly-done research (my words) are not easily killed by the peer-review process.

"Even when the evidence shows that a particular research idea is wrong, if you have thousands of scientists who have invested their careers in it, they'll continue to publish papers on it," he says. "It's like an epidemic, in the sense that they're infected with these wrong ideas, and they're spreading it to other researchers through journals."

What Dr. Ioannidis seems to be suggesting is, when a major medical finding is reported, wait a good while before taking it seriously.

Heck, I've been doing that for years.

When medical science said to stop eating eggs, I didn't. I like eggs.

When medical science, the government, and a million tv commercials said that fat is bad for us and we should drastically reduce our intake, I didn't. I like fat. I like whole milk. I love butter. Low-fat cookies are, to me, nonsensical.

When medical science said that aluminum caused Alzheimer's, everyone threw their aluminum cookware away. I kept mine.

Now research shows that eggs are okay to eat, reducing fat in our diets seems to have done more harm than good and made us fatter, not skinnier, and aluminum in the brain is an effect of Alzheimer’s, not the cause.

I smile, cook my omelet in my aluminum pan--in butter--and wash it down with a glass of whole milk.

How is it that scientists, particularly medical researchers, manage to reach such amazingly wrong conclusions--conclusions that are later overturned?

John Ioannidis can tell you.

A few years back, Ioannidis did a statistical analysis of major medical research papers. He found that the most popular papers, and hence the most behavior-changing ones, had results that were later reversed after further study. Ioannidis wrote a paper that summed up what he and his team found. It's called "Why Most Published Research Findings Are False." Here are some of the conclusions it makes:

The smaller the study, the more likely it's wrong.

The smaller the effect seen in a study, the more likely it's wrong.

The more variables tested in a study, the more likely it's wrong.

The more flexible designs, definitions, and outcomes are, the more likely it's wrong.

The greater the financial interest in it being right, the more likely it's wrong.

The hotter the field of research, the more likely it's wrong.

In September of this year, Ioannidis, who is a medical doctor and holds a doctorate in science, became division chief of the Stanford Prevention Research Center. Suddenly there is renewed interest in his 2005 paper.

In the November issue of Atlantic magazine, on news stands now, there's an article called "Lies, Damned Lies, and Medical Science," by David H. Freedman. In it, Dr. Ioannidis tells why bone-headed conclusions from badly-done research (my words) are not easily killed by the peer-review process.

"Even when the evidence shows that a particular research idea is wrong, if you have thousands of scientists who have invested their careers in it, they'll continue to publish papers on it," he says. "It's like an epidemic, in the sense that they're infected with these wrong ideas, and they're spreading it to other researchers through journals."

What Dr. Ioannidis seems to be suggesting is, when a major medical finding is reported, wait a good while before taking it seriously.

Heck, I've been doing that for years.