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Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

motherjones.com

21–30 of 102 posts

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#22

I 100% agree with the headline; especially for research papers even more than clinical trials. However, I'm a bit puzzled by the weird direction the journalist ran with this, which is straight to his preconceived notions that are not that supported by the data he's looking at. But there's a bit more to this than just that one chart. In addition to self-correction (e.g. beginning to require pre-registration of trials)…

I'll go one stronger and say "You Shouldn't Trust Any One Scientific Study You See".

Individual studies can be really interesting. They're important for researchers to know about to inform their future work. But any one study - even ones that are done honestly, with good methodology and sound foundations - can be just totally wrong. There could be confounding factors you couldn't have known about that completely invalidate the result. Your test subjects could be unusual in some way, your animal models could be a poor analogue for humans in this particular case, you could have just had really aberrant statistical flukes in your statistic sampling.

It's the body of scientific research, the dozens, hundreds, thousands of studies stacked on top of each other that bring certainty.

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#23
post #15

Clinical trials != scientific studies in general. Motherjones is doing a great disservice implying equivalence.

If anything, clinical trials should be more reliable than the average scientific study: after all they are experiments , with well defined numbers (sample size, effects measurement, controlled conditions). Compare with all non-experimental science- including for example most environmental and climate science, where, if experiments are made at all, the results are wildly extrapolated and generalized.

If humans are the equivalent of atoms, or molecules, or rockets, or planets or whatever other scientific thing you are studying.

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#24
This would seem to indicate that the results of drug research are unpredictable. Therefore, if you are required to predict your results, you are set up to fail.

My question is: Was the free-range research actually effective? Or, was it "technically-correct effective just so you can't call me out on a failure, moving on..."

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#25

I'm cynical and have no trouble believing that results were twisted immensely prior to the rule change in 2000. The incentives are huge: profit, prestige, or simply job security. I do wonder if this chart misrepresents something, though: there are studies that produce incidental--but genuinely valuable--discoveries. It's unclear to me if that accounts for the pre-2000 results or not. With the new rules, would there h…

> With the new rules, would there have to be another study stating the new objective? I think it's only fair to force you to replicate at least once the positive result you think you see in the data you collected for another purpose before you can claim you got something.

Yes, the linked article is saying that researchers used to employ techniques like 'p-hacking' (among others) in order to report results that were favorable/novel. That the scientists and clinicians in charge teased the data too much.

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#26
post #4
post #2

I want a chart like that but for journalism.

I don't follow this comment. What would you plot on the vertical axis?

Clickthroughs, presumably.

I assume that taruz is saying that journalists should be required to say what they're investigating before publishing an investigative report. Right now, they start investigating, and if there's something outrageous (even if it wasn't what they were initially looking for), they publish. Sometimes they even skip the "start investigating" part and just put up a tip-line for anyone who has a beef to get a story out there.

This is great for manufacturing outrage and hence clicks, but it gives the public a hugely skewed perspective on how the world is. Imagine that 0.01% (1 in 10,000) of all peoples' actions are outrageous and will piss off a large portion of planet. Most people, by those numbers, would say that the majority of folks are decent, law-abiding citizens. Now imagine that a news outlet is allowed to freely go over someone's life, and they end up evaluating 1000 actions. There's a 10% chance that they'll find something outrageous. Now imagine that 10 such reporters do this to 10 people, and if any one of them finds something publishable (= outrageous), they go to press. Suddenly there's a 64% chance that one of them will find something, and you've likely got your news cycle for the day.

With the millions of people looking for something bad that a tip-line can generate, outrage is virtually assured. And that's where journalism is today. The world isn't actually a worse place than it was in 1980; in fact, by most metrics it's significantly better. But we've increased the amount of unpleasantness that people can be exposed to by 3-4 orders of magnitude and then implemented a selection filter that ensures that only the worst stories go viral. Of course we get only bad news; that's all that's economically viable, and we have such a large sample size that we can surely find it.

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#27

I 100% agree with the headline; especially for research papers even more than clinical trials. However, I'm a bit puzzled by the weird direction the journalist ran with this, which is straight to his preconceived notions that are not that supported by the data he's looking at. But there's a bit more to this than just that one chart. In addition to self-correction (e.g. beginning to require pre-registration of trials)…

Agreed, further:

>every significant clinical study of drugs and dietary supplements for the treatment or prevention of cardiovascular disease between 1974 and 2012

There is room for a lot of bias when selecting which studies are 'significant' and on topic. Not to mention deciding which metric to report from the study.

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#28
post #2

I want a chart like that but for journalism.

I'd have to agree with this; every news outlet tries to treat a lack of proper controls as a breaking story / massive conspiracy theory to get a buzz going around the topic. I think it's important to inform people but unfortunately, most people would rather buy into the idea that there was malicious intent rather than also evaluating the possibility that, like most evolving business areas, it takes time to build in the proper procedures to attain measurably objective results. This happens in every industry and isn't unique to science, however, in this case, the physicians recommending these drugs to their patients should have been able to read between the lines or at the very least have a managed treatment plan to evaluate the efficacy on those they're treating.

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#29
> Then, in 2000, the rules changed. Researchers were required before the study started to say what they were looking for. They couldn’t just mine the data afterward looking for anything that happened to be positive. They had to report the results they said they were going to report. And guess what? Out of 21 studies, only two showed significant benefits.

Why is this considered good? Isn't this just a counterproductive limitation? Significant benefits found without knowing what are they going to be in advance are still significant benefits and if they are observed scientifically and proven reproducible I'm glad we've found them.

> Once they had to explain beforehand what primary outcome they were looking for, practically every study came up null. The drugs turned out to be useless.

Aren't newly discovered drugs meant to undergo strict and targeted clinical trials? How can they even be considered being drugs before this? And how can they turn out to be useless after passing this stage?

Also in some cases when nobody wants to fund clinical trials despite very interesting life-enhancing effects supposed or when it's clear the time to general availability through the fully white research and approval chain is going to take longer than people want to wait some non-approved substances happen to be sold on eBay (or, for more questionable substances, on black market), hundreds or thousands of people buy it and report their experience on reddit and this data can be a source for further clues for research.

Re: Chart of the Decade: Why You Shouldn’t Trust Every Scientific Study You See

#30

I 100% agree with the headline; especially for research papers even more than clinical trials. However, I'm a bit puzzled by the weird direction the journalist ran with this, which is straight to his preconceived notions that are not that supported by the data he's looking at. But there's a bit more to this than just that one chart. In addition to self-correction (e.g. beginning to require pre-registration of trials)…

I'll go one stronger and say "You Shouldn't Trust Any One Scientific Study You See". Individual studies can be really interesting. They're important for researchers to know about to inform their future work. But any one study - even ones that are done honestly, with good methodology and sound foundations - can be just totally wrong. There could be confounding factors you couldn't have known about that completely inva…

I think you meant “shouldn’t”.
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