“Why Most Published Research Findings Are False” or “Much of the scientific literature, perhaps half, may simply be untrue”

Regular readers of this blog, and the small number of other autism science blogs, will have noticed how often research findings are contradictory.  In autism there is often a good reason why things are contradictory, because in some of the underlying dysfunctions both too much, or too little, (hyper or hypo) both lead to “autism”.     

Take the relatively simple case of GI problems in autism; estimates of prevalence range from 9 to 91%.  Such a variation is of course absurd and on the basis of which study you choose to quote, you can make whatever case you want.

   

Given that autism is not a single disease like say rheumatic fever, another very odd inflammatory disease, it makes anything very much harder to prove.

In the wider world of medical research there is an ongoing debate about research studies in general.  Most of this research is in much simpler types of disease, where you can accurately include in your trial only people with the same single biological dysfunction.

It has been suggested recently in the Lancet, one of the world’s top medical journals, that perhaps as much of half of the findings in research are untrue.

Much of the scientific literature, perhaps half, may simply be untrue.

   

The case against science is straightforward: much of the scientific literature, perhaps half, may simply be untrue. Afflicted by studies with small sample sizes, tiny effects, invalid exploratory analyses, and flagrant conflicts of interest, together with an obsession for pursuing fashionable trends of dubious importance, science has taken a turn towards darkness. As one participant put it, “poor methods get results”. The Academy of Medical Sciences, Medical Research Council, and Biotechnology and Biological Sciences Research Council have now put their reputational weight behind an investigation into these questionable research practices. The apparent endemicity of bad research behaviour is alarming. In their quest for telling a compelling story, scientists too often sculpt data to fit their preferred theory of the world. Or they retrofit hypotheses to fit their data. Journal editors deserve their fair share of criticism too. We aid and abet the worst behaviours. Our acquiescence to the impact factor fuels an unhealthy competition to win a place in a select few journals. Our love of “significance” pollutes the literature with many a statistical fairy-tale. We reject important confirmations. Journals are not the only miscreants. Universities are in a perpetual struggle for money and talent, endpoints that foster reductive metrics, such as high-impact publication. National assessment procedures, such as the Research Excellence Framework, incentivise bad practices. And individual scientists, including their most senior leaders, do little to alter a research culture that occasionally veers close to misconduct.

Can bad scientific practices be fixed? Part of the problem is that no-one is incentivised to be right. Instead, scientists are incentivised to be productive and innovative. Would a Hippocratic Oath for science help? Certainly don't add more layers of research red-tape. Instead of changing incentives, perhaps one could remove incentives altogether. Or insist on replicability statements in grant applications and research papers. Or emphasise collaboration, not competition. Or insist on preregistration of protocols. Or reward better pre and post publication peer review. Or improve research training and mentorship. Or implement the recommendations from our Series on increasing research value, published last year. One of the most convincing proposals came from outside the biomedical community. Tony Weidberg is a Professor of Particle Physics at Oxford. Following several high-profile errors, the particle physics community now invests great effort into intensive checking and re-checking of data prior to publication. By filtering results through independent working groups, physicists are encouraged to criticise. Good criticism is rewarded. The goal is a reliable result, and the incentives for scientists are aligned around this goal. Weidberg worried we set the bar for results in biomedicine far too low. In particle physics, significance is set at 5 sigma—a p value of 3 × 10^–7 or 1 in 3·5 million (if the result is not true, this is the probability that the data would have been as extreme as they are). The conclusion of the symposium was that something must be done. Indeed, all seemed to agree that it was within our power to do that something. But as to precisely what to do or how to do it, there were no firm answers. Those who have the power to act seem to think somebody else should act first. And every positive action (eg, funding well-powered replications) has a counterargument (science will become less creative). The good news is that science is beginning to take some of its worst failings very seriously. The bad news is that nobody is ready to take the first step to clean up the system.

Ten years ago John Ioannidis, a well-known Professor of Medicine now at Stanford, published a much more complex paper saying essentially the same thing.  That paper, below, was recently highlighted to me by one reader of this blog, who is involved in such research.

  

Why Most Published Research Findings Are False

Conclusion

  

Since modern medicine, and indeed some autism therapy, is all about being “evidence based”, this does pose a big problem.

When the experts are telling us not to trust the evidence, what/who do you trust?

Getting into debates about almost anything to do with autism, with anyone, usually gets you nowhere at all.  Even the most basic points are disputed. This is at least one thing that people can agree on.

In the end it comes down to your own experience and judgement; I hope it is good.

In spite of all its shortcomings, I continue to marvel at how easy it is to access what you want from the vast amount of accumulated research, draw your own conclusions and act on them. I wish more people did the same.