The Silicon Valley Health Trend Making Doctors Nervous

So, Rachel, a little while ago, you got into a little spat online. Tell me what that was about. Yeah. So a few weeks ago, a startup in San Francisco announced that it was going to launch a new product, which is a whole body imaging technique. And it led to this really interesting, kind of nasty at this point, discourse between medical doctors like me and folks in tech. And that sort of conversation came down to doctors being very wary that this kind of data can sometimes cause more harm than good. And folks on the tech side saying, basically, how can more data ever be bad? Isn't more data always helpful in informing decisions, research, et cetera, et cetera? And it led to this conversation between you and I, actually, about is more data about your body always good? And that's the question that we're going to be talking about today in a bunch of different ways. It's not entirely new. People have been trying to track data about their body and their health forever in more systematic ways, maybe over the last 10 years. But the prospect of AI really kind of changes the landscape here and makes us think again about what the future holds. Is it science fiction to imagine that there will be a day when an AI could predict 20 years in advance when a person is staring down the barrel of a neurodegenerative disease? And act at a time when maybe we could actually reverse it? We're now looking at a future where many people are telling us that machine learning can process huge amounts of data much more quickly, much more intelligently than anyone has before. And essentially learn things about how we are living, what health is, what illness is, and how we might be able to do better to manage our health going forward. I'm David Wallace-Wells. I'm a writer for New York Times Opinion. And a columnist for The Times Magazine. I'm Rachel Bedard. I'm an internal medicine doctor in Brooklyn and a contributing writer at New York Times Opinion. So before we talk about the very now and the kind of distant future, let's talk a little bit just about the recent past. Over a couple of decades, doctors have become a little bit more skeptical than I think the average layperson about the possibility that knowing more is always good. Tell me about where that came from. Where that came from, what that suspicion arises around, and what normies like me don't understand. Yeah, so I think there are a few factors here. One is, you know, over the last several decades, our ability to collect data about the body has taken off radically, right? So imaging techniques, blood tests, tracking devices, all of these things can provide so, so much information. That may or may not. That may or may not correlate in any meaningful way to what people feel in their bodies, how they're functioning, their clinical outcomes. When you're talking about studying people who feel healthy to see if actually they might be sick, you're talking about screening a healthy population for hidden pathologies. And there have been lots and lots of studies over time to try to do this. And what we have found is the results are really mixed. So the most sort of famous cautionary tale is South Korea. South Korea, in the early part of this century, instituted a policy where they were screening universally for thyroid cancer with thyroid ultrasounds. Thyroid ultrasounds, non-invasive. They don't cause any harm to do. Fine. What they found, though, when they followed that experiment over time was that the incidence of finding thyroid cancer went up 15 times. And it made no difference to mortality from thyroid cancers. So which means, like, you're. You're basically finding 15 times more cancers that weren't actually clinically significant, that weren't going to hurt people. And that's. Well, let me just pause you there. Like, how how is that? Like, how can that be? How can that be? I mean, I understand, like, there are some things that are below a clinical threshold, which maybe we don't want to worry about. But how can it be that when we see are seeing so many more cases of something, it doesn't have any population level benefit? It could be in two ways. One thing is that there are just absolutely like indolent cancers that can sort of exist in small. Very, very, very slow growing ways that are just not going to ever become clinically significant in a person's lifetime. Like prostate cancer. There's sort of this old adage that, like, more men die with undiagnosed prostate cancer than get diagnosed with it in their life. I've heard people say we shouldn't even talk about it as a cancer. We should treat it as something else because the word cancer scares people into treatment. So that's one thing. The other thing is whether or not screening when somebody is asymptomatic is actually useful. Right. So it. It may be that if you wait until people's thyroid cancer becomes clinically significant until it's found because they have symptoms or on an exam of their neck. If you wait until then and intervene at that point, it's fine. The vast majority of thyroid cancers are caught pretty early. And when they're caught, they're very treatable and people do really well. And so there may be no additional benefit to catching them way earlier. It doesn't. That example, that cautionary tale does not. Mean that sort of we've closed the case on, like, how should we look for thyroid cancer forever? Right. But it means given the screening technique that we know how to use now, applying it at the population level to asymptomatic people seems to have no clinical benefit and instead causes a fair amount of harm because that 15 fold increase in cases means follow up surgery, biopsies, surgeries and all of those things. One big question that I have about this, not just. About thyroid cancer, but the question of, you know, what we can learn about the body in general is if we look at the state of play now and we say, given the treatment techniques we have given the screening techniques we have now expanding our screening to the whole population isn't going to have a benefit. Is that because we already know everything there is to know that is useful about such a disease or other diseases? Or is it something about the limits of our screening in a future where we could zoom down, you know, have much more information about particular cancers? Presumably, more data would be good, right? It really matters if you know what you're going to do with the data. OK, so let me give you an example that's a more live question, which is screening for Alzheimer's disease. Alzheimer's disease, incredibly prevalent, clinically devastating, on the rise. Right. And until relatively recently, we had very few. Interventions to offer people if you knew that they were at increased risk for Alzheimer's. We didn't have anything that made the disease slow down or reverse its course. In the last 10 years, we have both found new screening techniques, blood tests that can find sort of evidence of early plaques in the brain, basically, that are developing well before you have any clinical symptoms. And the other thing that's happened in the last 10 years is, for the first time, there have been new approved treatments for people who are in very early stages of Alzheimer's. That's a total game changer, because in that case, if you'd had that blood test 20 years ago and you didn't really have anything to offer people, the rationale for screening would be really low, right? Because you would say, you're just going to tell people this. They don't know that for sure it means they're going to get Alzheimer's, but it maybe freaks them out for the rest of their lives. But Alzheimer's is in my family. I would never have gotten the screening test 20 years ago. It's really different if you have an intervention to offer people that may be meaningfully disease modifying. And so the question of whether screening is useful and the data is useful also goes in tandem with, like, what are you going to do with the result when you get it? So what's the big problem with this particular full-body scan that we're talking about today? Like, why is this an example of something that is going to give us. information that is not useful, maybe counterproductive, as opposed to helpful to the people who are getting it? Yeah, so embedded in that question is, like, sort of the whole thing. Yeah, okay, so let's unpack. Let's unpack it. So the first thing is, like, when you talk about it being helpful to the people who get it, it really depends what the person's getting it for, right? If you're, like, I don't know, Joe Rogan, and you're a fitness-obsessed gym bro who is working out several hours a day, and really obsessively tracking, you know, your diet and all of these metrics about yourself, and you want to collect these images because you want to be able to see the relative proportions of muscle-to-body fat in your body, whole-body ultrasound's probably okay for that. And if that's something that Joe Rogan finds, like, meaningful on a personal level to himself, like, he's like, this makes me feel better about the way that I'm taking care of myself, go with God, Joe Rogan, enjoy, you know? And that's sort of what the company is saying right now. The company is saying this is not for medical use. This is, like, a general wellness thing that people can use in order to track their body composition. That's, though, a really different prospect than the way in which this conversation about it online was sort of extrapolating the potential benefits of such a technique, which were, like, you're going to be able to get a monthly scan that will track the appearance of abnormalities in the body that may or may not be clinically significant and make sense. of them and that becomes a problem for a few reasons the first is that we know when we scan people that we're finding stuff in their bodies all the time that we don't know what it means um we call them incidentalomas and because they're incidental findings that are like totally indeterminate significance we're always finding like schmutz on people's adrenal glands and there's all this you know there are guidelines about like how big does the schmutz have to be for you to decide that you're going to scan again and which interval etc etc but that stuff's meaningfully costly and potentially harmful because um you have to pay for scans and with time and money you get biopsies you know all of these things that are potentially harmful without any benefit so that's one reason that it makes doctors really nervous um the other reason i think that it makes me really nervous is because this is sort of part of this like larger trend of directing people to scan and then to scan again and then to scan again and then to scan again and back to consumer access to medical testing or what is sort of like medical testing adjacent right there are also companies that like um you know where you can be you can be ordering your own lab panels and then getting back all of this blood work and whether or not that's meaningful data about your health um it's sort of hard to say and once you get it back when there are abnormal values like your next step is you're taking it to your doctor and saying this seems to say you know these values are off like what am i going to do about it well some people are taking it to a doctor but also a lot of people are just monitoring it themselves right while monitoring or or taking action on it themselves what like what's that right like what are they doing like and there's a conceptual shift that's happened where you know previously they had sort of assumed that they were in relatively good health they start to see some indicators that may or may not mean anything but they've already stopped thinking of themselves as if not unhealthy then on some spectrum of wellness and performance in which they maybe should be doing better they should be addressing this or that and whether or not those improvements will actually help their well-being in the long run they're already mindful of what they could or should be doing so they've already like redefined their measure of wellness from like how am i feeling to what does my watch say how i'm feeling totally totally so in preparation for our conversation today i'm going to be talking about how i'm feeling about my health and i'm going to be talking about i have been wearing for the first time in my life a fitness tracker um like a sort of watch type device for the past week you're like really a late adopter this i'm a really late adopter and i'm also although i'm a letter i don't have anything you don't have anything you're just it's just it's just vibes and david wallace wells with body i'm doing great not me i've been tracking my data for a week and i cannot make any sense of it last night it told me i had a bad sleep but i felt i had a great sleep and i really did like look at the data this morning and i was like well what i don't know about what was happening you did have that feeling you didn't have the feeling of like i know better than this watch well i was like i feel pretty good two nights ago yeah i slept terribly and the watch that's where i thought it went fine and then this morning the the the device thinks that i slept badly and i woke up feeling much better and mostly i'm gonna defer to my own experience but i did like kind of look at the graph to be like what does it know that i don't know i mean there's data that's come out that says like you know there's a placebo effect and a no cebo effect to all of it right which is like if the if the device suggests to you that you had a bad sleep people experience more tiredness that day um whether or not it's true yeah i mean it reminds me a little bit of some of the conversation around mental health and diagnostic inflation the idea that once we have supplied the public with knowledge about what constitutes depression or anxiety once we've lowered the taboos against those um diagnoses probably that's all to the good but there are also some people who are would have thought of themselves as healthy previously who now understand themselves as struggling or mentally ill and the effect that that has on their lives is ambiguous yeah i mean and that sort of gets to like i think sort of both like the benefit and the peril of the wearable phenomenon um some a study in the journal of american medical association found like 40 percent of americans reported wearing a wearable so much 2024 and like the promise and the peril of it is mindfulness is actually pretty important so the peril is what you just described or what i just described about my sleep it gives you data that says actually you don't feel that good actually your resting heart rate's kind of high and you're sitting there thinking but i don't feel anxious i feel fine um and it gets you worrying and that can obviously get into a pretty vicious circle pretty quickly on the other hand the benefit of um wearing something like this is it can offer you data that then does the opposite that puts you on step counters there's data for step counters that it says that it does encourage people to walk more when they're tracking because it gamifies getting exercise i mean the thing that i have found most sort of useful about this past week's experiment has been tracking my steps and thinking well i really do want to hit a certain number every day and like i'm gonna go you know i'm gonna go get it get one more walk in in order to get there um and that obviously is to so there's a lot of stuff going on here there's a kind of a sociological story about the sorts of people who are drawn to this and why are people drawn to these you know measures of self-optimization and um why are they starting to see their body in terms of data which can be extracted um also to what extent is that really a phenomenon of you know achievement culture among the well-off versus something that might be extended profitably through the rest of the population there's that whole bucket like the kind of cartoon brian johnson like i'm gonna you know um not to say he brian johnson is um brian johnson is i mean it's it's amazing he's he's um a tech entrepreneur who who has devoted himself to the pursuit of longevity and maybe even um living forever yeah never dying the thing i care about the most is what is my heart rate before bed your goal in life now is to lower your heart rate and so the way you do that one is you have your final meal a day four hours before bed and he's started out as a like cartoon character who everybody was comfortable mocking for being so outlandishly committed to self-monitoring self-optimization at the expense of all other human pleasure but he's i think in the like last year sort of become like lovable as a completely unapologetic embodiment of something that i guess so many more of us are doing anyway and like we're glad that he's doing it in a cartoonish way so uninhibited so maybe so that we could feel better doing it in a slightly more neurotic way ourselves i also think like the other thing about brian johnson is i think he's um i mean he's definitely so like the ur example of this n of one experimentation that i think goes on with this the this data collection which is um you know i am going to track all of these things about myself and then make these modifications and then track what the modifications do and and the fact that there's data around it like it's supposed to sort of make it not anecdotal evidence but like n of one is n of one right and you can't actually you know tease apart causation and what is just placebo effect and all of these things when it's just your one body right like we have randomized control trials exactly because one person's experience is not enough to extrapolate to know things about the human body as a you know as a universal phenomenon but even i mean pulling back from the n of one problem you know i struggle to understand how to understand how to understand how to understand how to understand how to understand how to make sense of statistics at the population level too like if i'm reading about you know my father's cancer or whatever i'm talking to his doctor and his doctor's like this person has a 20 chance of surviving this year i'm wondering to myself does that 20 describe a matter of chance does it describe something fundamental to his biology which we don't understand which we're choosing to describe by treating it as a matter of chance and theoretically if we could know more about this cancer and this man and his history would we be able to produce an n of one assessment of what will happen with a particular cancer treatment over time in other words like are we dealing with the irreducible epistemological mystery of the body or is it conceivable that perhaps even in the relatively near future data better data better screening better information about genes and etc we could put all that into some sort of system and actually get a reliable assessment of like you know when rachel's gonna die you know or whatever i don't want to know um yeah so okay so two things about that so so the first is right the 20 is not a matter of chance right and that kind of broad statistic in some ways i think um the problems with it are why the sort of tech folks are so bullish on um on the data revolution that we're talking about today because among other things that 20 chance is it's retrospective right it's looking at you know meta-analyses from studies done sometime in the last decade or the last 15 years and it may or may not reflect what we know about um ben sass right the senator um there are the ex-senator who has pancreatic cancer um who got this devastating diagnosis and was told he has to live and And then was put on this experimental therapy and has sort of told the world, that it looks as though the cancer significantly receded in his body. So like that's not reflected in those statistics because the science being used to treat Ben Sasse did not exist when those statistics were derived, right? And part of what the data folks are saying is basically like, if we collect so much data, we're just gonna like iterate knowledge so fast. And when we give it to the robot overlords, the AI is gonna read that data and it's gonna see stuff that we could not possibly see. And it's gonna see it so quickly. And it's gonna suggest thousands of new ways to experiment on it, to intervene, whatever. And a lot of that may lead nowhere, but some of it's gonna lead somewhere. And if we just sort of like participate in that process, we're gonna have this explosion of useful knowledge that will come out of collecting so much noisy data. I hear you saying that, and I find that basically persuasive on an intuitive level. I also then think about, you know, this is not the first time that we've been sold promises about what big data will do to us and improve our lives. And I think about 23andMe, which told us that we were gonna not just learn about our ancestry, but also we're gonna learn a lot about our health because of getting it analyzed in some centralized way. And now here we are a decade or two later, we all spit into those tubes. We got some information about where our families come from, which turns out not to be all that reliable. And the company went under, like, did we actually learn anything about our health from that? And I understand that the future is big and we shouldn't always impose short timelines on promises and say, if they said it was gonna happen in five years and it didn't happen by 10, that means it's a hopeless cause. But I do wonder just in a really big picture, when we hear the AI leaders say casually, this is gonna help us cure cancer or this will help us cure all disease. I think to myself, how should we assess that claim in a world where data has improved medical treatment, but not really solved anything quite yet? So the best case scenario is that it creates a new productive tension with clinical research. So, you know, there are lots of extremely valid critiques that I share about how the clinical research enterprise is sort of broken or inadequate to our moment, too slow, driven by sort of the wrong, like, profit motives and sort of the wrong questions and all of these things. And here along comes, like, this new way, of being able to collect and make sense of data that is currently largely being pursued outside the clinical research framework. Like, you know, when I talk about end-of-one experiments, I mean, like, there are, you know, thousands, maybe millions of people who are tracking things about themselves and then making changes to their lifestyle and then learning things theoretically about their own health that in aggregate might be really useful for everyone to know. But the problem with that is, there are lots of different points at which things go wrong. You mentioned, like, you know, it says you are 2% from Sub-Saharan Africa, and it's like, "No, you're not." You know what I mean? And that's because there's a- My wife is, like, sure that her dad was from India, which she definitely was not, yeah. So, right, exactly. So, like, you know, that goes to the reliability of the assessment tool, right? And Theranos, Theranos was proposed as, like, you'll be able to go and prick your finger and get all of this data back, and then the problem with Theranos was the tool wasn't that good, right? But I've also had a lot of people say to me they were just too early, over-promised, and then felt forced to come to market. And if we fast-forward 10 years, we're probably gonna have something like Theranos that's quite useful. Yeah, and I think that that's not wrong, actually. I mean, there are, that, the promise of Theranos is alive. There are companies that are getting FDA approval to basically do the 2026 version of Theranos. I think that's a conceptual reason why that would not be possible. No, there's not a conceptual, I don't think that we should think of any of it as having conceptual limitations so much as questions about how you're building in rigor to figure out how you know what you know. But then in the present tense, that just makes me think, okay, so maybe the info that we get from this full-body scan isn't so great. Maybe even the info that we're getting directly from our little wearables isn't so great, and maybe certain kinds of people are putting too much faith in that information and reorganizing their lives in ways that may not ultimately benefit them, may even cause them some harm. Nevertheless, we're talking about a huge amount of new information being generated, at the very least, for some robots to chew through to make some hypotheses about correlations and things we may do to improve our health. And I just think, I don't know, isn't that, I think it's potentially really exciting and good if, again, for me, it's about the rigor. There is lots of things that you can imagine being helpful to you on an individual level, like disease screening tools or other kinds of tracking. And as a physician, like, I would be so thrilled if, you know, we figured out how to detect pancreatic cancer, one of the most deadly cancers. You know, we don't have a reliable screening tool for that cancer. And if we figured one out, that would be really exciting. So it's not that I'm, like, either anti-scientific progress or anti-big data as a way of potentially driving hypothesis formation. But it does seem, at least the way that you're sketching it out, then theoretically concerning that so much of this, you know, self-monitoring is taking place in a sort of sociological context in which people are, like, skeptical of doctors. They may not be actually even providing that information to any centralized source that can make use of it in a meaningful way. They're also doing a lot of stuff. I don't mean to, like, you know, stereotype all of Silicon Valley Twitter or whatever, but they're doing a lot of, like, gray market peptides. They're, you know, they're doing biohacking of various kinds. And they are doing so thinking that they are, like, outmaneuvering, outsmarting the slow-moving scientific establishment, not that they are serving some collective good, and that raises a couple of big questions, one of which is, like, to what extent are we aggregating this data in a way that will be made useful to the population as a whole? But it's also, like, who are the people who are making sense of it? Is it, you know, somebody who thinks he feels really great after having adjusted his sleep schedule in X way and is broadcasting that on social media? Or is it being processed through someone who can meaningfully make sense of that data for people who aren't already sort of drinking the cool, cool it? Yeah, I think it's, like, really in vogue right now to say, like, basically sort of all regulation is just in the way. And actually a lot of regulation and a lot of sort of this slow, iterative, deliberate nature of traditional biomedical research reflects hard-won lessons about what happens when you make too many assumptions and leaps from correlations to causations. The other thing is the population of study really matters, right? So when we're talking about the most avid fitness tracker users, you're talking predominantly about, like, a mostly healthy population, maybe a population that's more invested in its health than even the, you know, sort of the regular general population. You could even call that, they're not even worried about illness. They're, like, focused on wellness. Yeah, they're interested in optimization, right? That's a population that potentially has different physiology than, you know, than the sort of average person. And almost certainly a different diet and. Yeah, different habits, all of those things. Whereas, you know, your population of interest really defines so much about the data that you're going to get, right? If you're collecting all of the, I don't know, the lab values from a population at a heart failure clinic, like, those people are sick. They have heart failure. What that tells you is it tells you something about the heart failure population. It's not going to tell you something about someone who doesn't have heart failure. The other thing that I've been wearing for a week is a continuous glucose monitor. So Maha Culture is, like, very into the continuous glucose monitor, which is a, it's a sensor in my arm that is basically, that is continuously monitoring my blood sugar. And it's a tool that was developed for diabetics so that they could get sort of continuous feedback and. Yeah, my mom has one. Yeah. As does my mother-in-law, who's not diabetic. And the idea, the idea there is to give you, for diabetics, is it gives them feedback that's really important about how what they eat correlates to their blood sugar levels. And that's because they have impaired glucose metabolism. But the sort of Mahaverse, especially like Casey Means, who was nominated for Surgeon General, who wrote this book called Good Energy, and she and her brother are like big Maha influencers, she said something like continuous glucose monitors are like the foundation of the health revolution or something, encourage people who are not diabetic to use it as a way of getting critical feedback about how what you eat corresponds to your blood sugar. Yeah. Your, your glucose metabolism and how you feel. I don't have diabetes and I don't have prediabetes and I don't have glucose intolerance. And I've been wearing this for a week and my glucose has just been in a normal range the entire time. And it's higher when I eat ice cream. Surprise, surprise. And it's lower when I wake up in the morning and haven't eaten in a while. Yeah. And even still, it's within a range of normal and those higher values are not necessarily problematic. They just reflect that I'm like taking calories in. Those lower values aren't either. So whether that data is meaningful or will ever be meaningful, like I don't really know. But what do you make of the broader impulse here of people like the Means siblings asking us all, suggesting that we all start monitoring our glucose levels as though we are diabetics, recommending that the population as a whole treat our bodies as a source of constant anxiety? And really, like a patient would, as opposed to someone who is well. I mean, so much of the promise of Maha is to extract people from chronic illness and from, you know, obesity and, you know, dozens of other things that they think we can do relatively painlessly. And yet the process by which they're asking us to do that really asks us all to treat ourselves as ill and think a lot about how we're staying healthy. On the right side of that dividing line and what might push us over it. I know you've thought a lot about Maha in general, bodily autonomy, which is also tied up here because we're talking about kind of health surveillance. Like, what is going on here? Yeah, well, I mean, OK, so I would say that the Means siblings, Casey's brother is named Callie. He works for the administration. What do I think it's about for them? I mean, I think that they are emblematic in two ways. One, there is a problem. There's a profit motive. She sells wearables directly to consumers and tells them that this is the way that you're going to revolutionize your health. The profit motive drives a ton about sort of what products are released, how they're marketed, all of those things. The second is it's very consistent with a Maha ethos that says that your lifestyle is the primary determinant of your health. Right. And that. And so is your responsibility. And so and it's in and it's individual. So. If you take responsibility and you live correctly and you do not allow yourself to ever be exposed to the toxic substances and, you know, tap water that might make you sick, et cetera, et cetera. Right. Like if you read Casey's book, which I have, it has this really wild list of things that she claims she does around her own health and that she encourages everyone to do around optimizing their lifestyle and their environment and their home for wellness. Um, and it's very, very much like you have to do this. And if you don't do this, then you are putting yourself at risk. Um, and so I do think this is like all of a piece with this very lifestyle oriented way of thinking about its wellness, not health, really. Um, and, um, the corollary, which is like, if you get sick, like maybe you were, you know, eating the wrong things, not getting enough sleep, et cetera, et cetera. It's your fault. Yeah. Yeah. So we've been talking a lot about this sort of phenomenon that I think is visible to a lot of people as a wealthy elite enterprise. I wonder how that looks to you as a clinician, whether your patients are engaging with this kind of stuff and to what extent we can, you know, think about it as a sort of universal phenomenon of 2026 or something that, you know, is just happening over in Silicon Valley and we can treat with the skepticism that we treat a lot of stuff coming out of there. So I think we know from. that 40% statistic, like it's definitely not, it's escaped containment, right? Like this isn't Brian Johnson, you know, testing the like composition of his tears or whatever, like lots of, you know, many, many, many Americans are wearing some kind of tracking device. My particular patients are not. However, I work in a homeless clinic and my patients cannot afford this kind of device right now. Secretary Kennedy has said that wearables are something that he thinks are really important and that he, I think he and Dr. Oz have like worked towards Medicare plans and things being able to cover them. So they absolutely may become more accessible with even public insurance in the next couple of years. But for my patient population, the challenges to their health and their lifestyle are like not things that are going to be responsive to knowing a ton more about what this data says, right? Like they're living in this world. circumstances where things are so out of control that this is not useful to them. And I think that that's kind of an important point, which is like for the data to become meaningful, you have to have a high degree of, you know, control, both sort of agency, agency, interest in it. You have to be very agentic about your life and have a lot of control over your lifestyle. You need to be able to say like, I'm not going to eat this anymore. I'm going to pay for the more expensive this instead. Um, that having been said, there are lots of sort of, um, clinical wearable tools that we prescribe for short term. For folks, most importantly, we prescribe people with heart monitors, like that we think that they may be having abnormal heart rhythms that are on and off. We don't pick them up when they come into clinic. Um, and I prescribe those to my patients all the time and find them really useful. That's like a really clear clinical use. And actually the best clinical data that we have about wearables being useful is around exactly that. There's something called the Apple Heart Study, which like looked at, I don't know, hundreds of thousands of people wearing Apple watches and picked up abnormal heart rhythms that were clinically significant. And the watch helped pick those up in a way that they would never have, you know, been picked up in clinic. And probably it does absolutely, um, help prevent strokes and other things like that. So there's definitely like clinical utility here. Um, even at the moment, even at the moment, but the distinction there, I think is like, whether we're talking about this sort of like lifestyle wellness idea, which I do sort of still think of as basically being, um, in the purview of people who have enough stability in their lives and enough opportunity and resources to, to do this optimization stuff, um, versus the sort of clinical indications. I'm asking you to wear this because I'm looking for X because I'm concerned about this clinical question. That's a really different sort of proposition. So just to end, are you going to keep wearing that watch? Um, I think I'm probably not going to continue to wear it. I'm going to keep wearing it. I'm going to continue to wear this, um, particular tracking device after exactly after the next 10 minutes. Um, but, um, I will say that like, even before I wore this, I like looked at my step count on my phone, which is a cruder way of sort of trying to gauge it every day. And I have found that useful. And in general, I do think that everybody has to sort of decide for themselves a little bit, like what degree of mindfulness and how much data to inform that mindfulness is, for me, it's helpful to sort of have a gross sense of like, have I moved today or not in some kind of quantified way. Um, so I'm just going to go back to doing that, but like, no, I don't want the sleep score anymore. It just, it introduces confusion before I've even had a coffee. Rachel, thank you very much. Thank you, David.