'It's about a bad system': Fraud and fabrication in scientific research

How competition and limited funding can lead to dishonesty

People in white coats work in a lab
Scientists in a laboratory of the University of La Rioja. After accusations at the U of M, we wanted to dig deeper into why scientific fraud and misconduct occur.
Urcomunicacion via Wiki Commons File

On July 21, an article is Science magazine questioned the integrity of a key Alzheimer's study — sending shockwaves through the world of science and academia.

The allegations lodged against a University of Minnesota research team center around a claim that one of the researchers, Sylvain Lesné, falsified images used in the study.

The study has been foundational in understanding Alzheimer’s and treatment development for the disease.

Lesné did not respond to a request for comment. Colleague Karen Ashe said in an email she is devastated that Lesné may have misled her and the scientific community. She said she is working with the journal to rectify the situation, but that the research findings stand even without those images.

The University of Minnesota told us it will "follow its processes to review the questions any claims have raised.”

To dig deeper into scientific fraud and misconduct — and why it occurs — MPR News host Tom Crann spoke with Ray De Vries, professor emeritus at the Center for Bioethics and Social Sciences in Medicine at the University of Michigan.

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Hear the full conversation by using the audio player above or reading the transcript below. It has been lightly edited for clarity and length.

When you heard about this situation at the University of Minnesota, what did you think?

Well, I thought, this is nothing new. This is an example of the problem we have with how we organize and pay for science in the United States.

Several years ago, we did research on what are the things associated with people who are, let's say, dishonest in their scientific research. Especially when you look at this case, it's like, "oh, these researchers must be bad people". But we had a suspicion that it was something more about a bad system.

In the United States, we believe, essentially, the best way to get the best science is to have scientists compete with each other. And what we found is that when scientists compete, it actually leads them to cut corners because it was in the interest of the scientist to continue getting funding for their research.

Tell us more about the spectrum of what you see when it comes to scientific fraud and what you refer to as cutting corners for competitive advantage.

If you look at the whole science industry, you want to be the first one to report findings on some significant new breakthrough. So you're looking at your data and you think, well, if I just eliminate an outlier, my data will be cleaner, it'll make a stronger case — more likely to be published. And if I get published, it's more likely I'll get my next grant. Then you you slip into things like, as we've seen in this case, apparently manipulating images to make the hypothesis you believe in look more true than it really is.

If the allegations in this case at the University of Minnesota are true, what impact does that have on research, specifically on Alzheimer's, and more generally?

Let's say only 1 percent of all researchers engage in these kinds of behaviors, when the data that they're creating gets into the scientific record, it has this huge effect.

So scientists start using that as their starting point and it's changing the entire direction of scientific research. I think that's the case we've seen here: 16 years of research has been based on a paper that may have been using falsified data.

If it's shown that these are in fact falsified data, the paper will be retracted. But that paper lives on, especially now in the era of the internet.

What needs to change in order to prevent something like this from happening in the future?

The key thing here is realizing that we have to change the reward structure of science. Because we reward scientists for cutting edge discoveries, we don't reward them for doing replication studies.

And this is [another] important fact that if you look at funding from the National Institute of Health over the last 20 years, it's essentially been flat. This means that we have a number of trained scientists out there competing for the same pot of money that's staying the same size.

This creates the problem of: in this competitive atmosphere, why would I share my data if I'm at Minnesota with a lab at Michigan because they might get the next grant.

Some people suggest the creation of research consortia where all these laboratories come together and when one lab makes an advancement, all the labs get the information — and they carry that on.

When people hear something like this, what do they need to keep in mind?

Science has ways, as shown in this case, of being self correcting. I think we need to trust that the majority of scientists are trustworthy. They are checking on each other.

If anything, we need more efforts to promote cooperation rather than the kind of competition that leads to certain scientists saying “I'll do anything to get the next grant.'“