As readers know, I love data and research. I am always skeptical and want to make sure it makes sense, is replicated and is methodologically sound, but it is the best way to get some approximation of truth. But trusting research has gotten harder and harder, because the ideologues in our universities and think tanks will simply make stuff up to support their messaging. The lack of any morals in this group means the research is increasingly found to be bogus. And this is a particular issue in health care, of all disciplines, where it is especially dangerous. The Economist, which has become a depressingly woke publication in recent years, still couldn’t fail to note the trend in a recent article.
The article focuses on a team of researchers devoted to uncovering false medical research. This group has identified hundreds of likely fraudulent papers, many with data that is simply made up. In health care, research is used to create guidelines for physicians to determine the best treatments for patients. If the research is false, so are the guidelines, and patients are getting care that likely not only isn’t good for them, but may actually harm them.
Researchers may do false research to get published, to boost their reputations, or to make money from sponsors of trials. What is particularly depressing is that peer review almost never catches the false research and journals are extremely reluctant to retract obviously fake papers. So the medical community has no idea whether it can trust the research behind care guidelines or not. This affects the health care of every American. The problem will only get worse, as more and more incompetents are admitted to the practice of medicine and research solely on the basis of DEI. These dunces will be incapable of real research so they will have to resort to fakery.
The solution is a mandated set of checks that must be in place before research is used as a basis for care decisions, including multiple replications of results in other trials and an individual examination of the source data for the alleged research findings. It will make research more expensive, but it will save lives and money in the long run.
And if you think health care research is bad, it is the paradigm of excellence compared to social sciences research, which is completely corrupted by DEI and ideology, and climate “science”, which is nothing but made-up data and models, costing the world trillions of dollars for no purpose. (Economist Article)
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Excellent posting. I just yesterday read an article in Imprimis, Feb 2023, Vol 52, No 2, about the problems with the American health care system. It was adapted from a speech by Dr. John Abramson. I wondered if you have read it, and if so what you think.
The recent example is the Gas Stoves attributable to 12.7% of Asthma cases. The authors used population attribution fraction analysis which is quite useful. However, PAF has its limitations and becomes very weak when there are multiple cofounding variables, which is the case with asthma. Asthma rates across various states have relatively minor variations (8-12%ish) while gas stove usage varies considerably, Florida with 9% gas stove usage, while NY, CA , have high gas stove usage, 60% ish. Yet asthma rates are very similar. I ran a quick calculation by state, and approximately 20 of the states, have a negative correlation compared to the remaining 30 states. In other words, zero correlation.
While I cant say the study was “academic fraud, the use of a methodology that is well known to be invalid with multiple cofounding variables strikes me as highly suspect .
Thanks for posting. While I suspected the problem in social areas, it surprises me in medicine. However, it ought not … that’s where the big bucks are.
After working in higher education for many years, I can attest that there can be great pressure exerted on faculty to ‘publish’ – that the only way to move ahead is to get something published in a journal somewhere. I would imagine this might lead a significant number of folks to not be as rigorous as they should (at best) or just get something ‘on paper’, as it were, regardless if it is factually accurate or if they must distort data just to get it done (at worst).