That’s literally how you do review studies.

obviously publication bias exists, a study that shows nothing (good or bad) happening when a drug is used is less likely to get published, but that’s a broad problem.

oh the Ahlquist et al population study with 2.5 million participants was marked “low quality” due to “exposure limitations”.

can someone explain to me how you limit exposure in a population study?

Fake news and political propaganda warning!

this is originally from may, and passed review in june. idk how related it is to the current nonsense.

at higher rates than children of pregnant mothers who were not exposed to acetaminophen.

Whew! I, a child of an un-pregnant mother, don’t need to get diagnosed then

Published by Harvard? I guess this is what you get when you shake down a university.

We really are entering the era of Idiocracy

It certainly got posted in the context of the current debate. Or this wouldn’t have been posted today. And experts said what people currently think this study means is not at all what its factual/scientific significance is. So I’d say it’s misinformation unless we add a good amount of context here.

I mean for once the study doesn’t seem to say at all what’s in the title here, that tylenol may increse children’s autism risk. As far as my reading skills get me, that’s just not a conclusion of the paper… They kinda say reading some other papers “supports an association” and they “preclude definitive causation”. And they “recommend judicious acetaminophen use […] under medical guidance”. Explicitly not “broad limitation”.

So ultimately what they say is further research needs to be done to either find a link between these things or rule it out. And people need to be careful in the meantime. “…” may cause “…” is what people falsely assume to be the jist of it.

that’s usually how pop-sci journalism goes, unfortunately.

Unfortunately misinformation to outright anti-intellectualism are big these days. I think it’s one of the major issues of society and we better find ways to deal with it, because people are getting hurt by this.

And the “journalist” writing the linked article for Harvard (wtf?) uses exactly the phrases flagged as wrong by the peer-review. On the upside, people here seem to still be able to downvote this.

Search for studies containing links between ADHD and Tylenol to determine if there’s a link between ADHD and Tylenol. P-hacking much? That is straight-up cherry-picking results to fit the hypothesis.

The article shows more differentiation than the title. There must be literally hundreds or things you should be careful about during pregnancy; but after reading this article; and if I would be pregnant, I would use paracetamol.

Baccarelli noted in the “competing interests” section of the research paper that he has served as an expert witness for plaintiffs in a case involving potential links between acetaminophen use during pregnancy and neurodevelopmental disorders.

Hey everyone - a new Andrew Wakefield just dropped!

A search for those terms returns any study that looks at those terms, regardless of whether or not a link is indicated. How else do you expect to determine the validity of a hypothesis if you don’t look at studies that test that hypothesis?

I see we are back to pseudoscience created by charlatans. Coming soon the newest snake oil that will heal any aliment.

No, it doesn’t. It returns studies that contain Tylenol AND ADHD. There’s an immediate bias in favour of the hypothesis. They should be searched separately, then you would look at how many contain both, then look at how many correlate the two. Presenting only the data that correlates the two is presenting that data out of context: choosing the data to fit the hypothesis. P-hacking.

The media has done the same thing with climate change. They present for debate one scientist ‘for’ climate change and one scientists ‘against’ climate change as though there is a 50/50 chance that climate change is real, despite 99% of scientists falling on the ‘for’ side. A balanced debate would have involved 100 climate scientists with ‘1’ against and 99 ‘for’. Instead we now have people who think that climate change denial is reasonable because the data was presented in an unbalanced, or biased, way.

If you only present that data that you think is relevant then you bias the result in your favour. If the data for all studies investigating the cause of ADHD was included, and then the % including Tylenol, then the % correlating Tylenol with ADHD, you would have a very different number… A much more honest one.

I understand your passion here, but it’s a little misguided.

The goal of this study is not to try to determine a singular cause for autism. That’s some outside political bullshit that’s relevant in a broad sense, but not the stated purpose of this study.

They set out to look at a potential link between Tylenol and ADHD, so they look at studies involving Tylenol and ADHD. It’s pretty straightforward. P-Hacking would be selecting only studies that did show a positive correlation between Tylenol use and ADHD.

Your climate change metaphor is just wildly off base, I don’t know what to say here honestly.

As others here have pointed out, the study is mildly flawed but the real issue is that the inconclusive results are being wildly misrepresented.

Yeah… That climate change example was a bit of a stretch. I was just highlighting how easy it is to mislead people with part of the picture, rather than the whole ugly mess.

I still think that omitting studies into the cause of ADHD that don’t include Tylenol is misrepresenting the data.

If there are 1000 studies into the cause of ADHD, and only 50 mention Tylenol, then omitting the other 950 is dishonest. Let’s say 25 of the 50 find a correlation, then 25/50 is way different to 25/1000! That’s where I see the P-hacking.

Thanks for being civil, too.

Of course! It’s always refreshing to engage with someone with good intentions.

So, this would only be a misrepresentation if the authors were claiming to look for causes of Autism.

Good science is based on testing a hypothesis. ‘What causes X’ is not a testable hypothesis, it’s too broad, the variables aren’t defined. ‘Does Y effect X?’ is a testable hypothesis, and a solid basis for initial research.

The question of ‘what causes autism’ is a huge one that can’t be answered by a single study. Each potential factor needs to be evaluated on its own merit, and this study does exactly that (with admittedly questionable results).

However, something like the recent HHS report is exactly the place where it’s wildly irresponsible to present only one potential hypothesis as a ‘cause’. That’s where we would expect a high level view of a range of established factors (since obviously there is no one ‘cause’).

June? So when RFK promised to find the cause of autism?