 So over the last few years, certainly since COVID, there has been real, you know, you could argue hysteria, a real emphasis, a real focus, a real passion around this crisis that we are told has happened in teen mental health. And that, you know, this is since 2012. So this is a crisis that was happening even before COVID and then is accelerated after COVID. And teen mental health is, you know, is an issue that everybody is talking about and trying to find causes to. I think I've talked about this on a few shows. And some of the most popular causes that seem, you know, pretty popular out there among commentators of all stripes, maybe the most popular cause is social media. Teen mental health started supposedly to deteriorate at about the same time, at about the same time as the Apple iPhone came out. And the iPhone, as a consequence, it's blamed on iPhones and Instagram and TikTok and body shaming and all this kind of stuff related to this. So all of this, of course, is based on statistics and this is always where it gets interesting, right? Like most social sciences, like medical sciences, most of the information we have are based on stats. And, you know, stats can be tricky, very tricky. What are we measuring? Has the definition of what we're measuring changed? Are we measuring the thing that really is happening? Are we measuring something completely different? And then, of course, you can get into are we using the right methodology? Is it statistically significant? And, yeah, it's statistics and the so-called the science that people claim based on it is a tricky thing. And as I came across this article, which I think illustrates this really, really well. So this is an article that was just published. I think it was published. Maybe it's, no, it's an NBER, National Bureau of Economic Research Working Paper. It's part of the Working Paper series. It's by Adrian Corridor Walden and Janet Curie. It is brand new. It was just published this month, July 2013. It's out of the NBER in Cambridge, Massachusetts. And it's been a working paper that's, yeah, that's the essence, right? So what this paper does is it examines the startling pre-pandemic increase in recorded suicidal behaviors among new Jersey children. And I'm reading the paragraph here from the study from among New Jersey children, 10 to 18. So this is pre-pandemic increase in recorded suicidal behavior. 10 to 18 years old presented at hospital emergency departments between 2008 and 2019. So this is pre-COVID. We show that there was relatively little increase in teen self-injury, intentional self-harm, suicidal attempts, or in completed suicide in New Jersey over this period. So no increase, relatively little increase. Instead, the rise that is documented that everybody fears, that everybody's worried about, the rise is mainly accounted for by a sharp increase in diagnosis of suicidal ideation. Suicide ideation is a serious condition that is grouped with self-harm in commonly used mental health disorder classification systems, such as the clinical classification software or the child and adolescents. We show that the increase in reports of suicidal ideation over this time period corresponded with two sets of changes in medical practices. The first is new guidelines from the United States Preventive Services Task Force and other professional organizations recommending screening of adolescent girls for depression, which was announced in 2011. And then the Affordable Care Act made it part of the mandatory for insurance companies to provide coverage for this. So, A, there was a change in guidance on how to treat, how to evaluate children. And the second change was a revision to the instructional notes included in the new version of whatever hospitals were required to start using new versions of this classification of diseases in October 2015. Our results had just that they may always have been large numbers of children and adolescents with serious mental health conditions, but that the changes in screening and coding practices helped to bring the problem to light. So, there wasn't an increase. What there was is a change in how things are classified. No increase in suicide, no increase in self-harm, all of those are flat. What increased was in ideation, thinking about suicide, imagining suicide. But it turns out that they only started measuring that in 2011 and then in 2015, which saw another jump, which you don't measure, you don't know. It's quite possible that if you'd measured that all along, then ideation would be flat and there's no there, there. So, this is applied just to one aspect of mental health, which is suicide and self-harm. But what the authors of this paper suggest is, before we rush to the conclusion that there is some mental health emergency here, that there's some crisis in America, maybe we need to look more carefully at the data, maybe we need to look at things like how these things are defined, what is actually being measured, are the standards being changed. And I talked about autism on a previous show and the dramatic increase in autism and a number of people wrote to me saying, a lot of that increase is just a question of different definitions, collapsing of a lot of other mental disorders into one phenomena. Or if one compares adults diagnosed with autism and children diagnosed with autism, the percentage of the population seems to be the same, suggesting that it hasn't really shifted over time that much. So, my point here is a broader point, because I don't know what the right answer is with mental health, oh, the autism for that matter. My point is, be very, very careful with citing these kind of statistical papers. And that's for me and for you and for everybody. Because almost none of these papers are as thorough. And this is why usually in a particular field you need multiple papers, multiple researches, multiple trials, multiple investigations. So, be wary of jumping out on the bandwagon when things really seem to suggest something. Be wary of statistics more broadly, very, very few people out there. God, I mean almost no layperson that I know of knows how to interpret statistics. Unless you've been trained to interpret statistics, you don't know how to do it. Sorry, you just don't. And if you want a good illustration of this, I highly recommend Stephen Pinker's book Rationality, where he takes you through some examples of probability problems, where the answers to the problems are so counterintuitive that almost nobody gets them right. And those are simple probability problems. Those are not econometric difficult statistical econometric problems. This is why you need experts. You really do. And your intuition, what you think is right, what you believe is right, what your emotions are telling you is right, is not necessarily right. Usually it's not actually. But to interpret the actual statistical results, you need, for a lot of these things, you need a translator. And as a consequence, I mean, this is part of the problem that we face today. We don't trust our experts, and justifiably so in some cases. The experts are too motivated by a social agenda and a political agenda. This is going to create real substantial problems. Real substantial problems. And nobody out there, and the lack of trust in experts is going to be a real, show a real decline, a civilizational decline.