Healthy Lifestyles Can Affect Your Chromosomes with Dr. Thomas Robinson, MD, Professor Stanford Medical School

that were designed to help them reduce their screen time versus kids who were in a school in which they didn't receive that curriculum and followed them over time. And what we found is that, in fact, for one, at least based on self-reports, we could reduce their screen time. And at the same time, the kids who received those interventions, those curriculum to reduce screen time, gained less weight, became less obese than children who did not receive that curriculum. And they also became less aggressive on the playground and less likely to be nominated by their peers as being violent and aggressive. They became less commercialistic, less materialistic in terms of the requesting toys and products that were advertised on TV from their parents. And it improved their school performance, all from just reducing screen times.

Welcome to the Mind Body Space Podcast, where you can stress less and boost your performance and wellness down to the cellular level just by listening. Hi, I'm Dr. Juna Bobby MD, a mom MD passionate about sharing evidence-based tips to keep you and your family well. For the past 10 years, I've been teaching the science of resilience to high-achieving individuals at many different schools and organizations. And currently I'm on faculty at the Juilliard School Pre-College Division teaching gifted students how to stress less and perform at their best. I started this podcast because I wanted to share what I learned with my students, fellow parents, educators, and anyone who's interested as I explore fascinating topics like neuroscience and meditation with experts in education, medicine, and psychology. Your support makes this possible. Please subscribe and share with a family friend, anyone who needs to stress less, boost performance, and be happier. If you have questions for my guests or for me, or if you have a topic that you'd like us to cover, please head on over to mindbodyspace.com/podcast and ask away, and we will answer your questions on the podcast on the on the last Friday of every month.

If you need a good night's sleep, head on over to my YouTube channel, Fall Asleep Easy, to drift off and sleep like a baby. Thank you so much for being here, Tom, and I really appreciate you taking your time out of your super busy day. I guess you're doing a little vacation and work.

Yeah, well, mostly work and fitting in recreation.

That's fantastic. That's like California, right? Unlike New York.

Yeah, but we have a— it's get in as much as we can.

I'm so honored to have here with me today, Dr.

Thomas Robinson, the Irving Shulman MD Endowed Professor in Child Health and a professor of pediatrics and medicine.

Dr. Thomas Robinson has dedicated his career to designing solutions to improve health and wellbeing of children, families, and the planet. Dr. Robinson is a world-renowned scientist who has pioneered obesity prevention and treatment research, and he's the director of the Stanford Solutions Science Lab. Where he conducts individual, family, school, and community-based randomized controlled trial tests for behavioral, social, and environmental interventions to prevent and treat childhood obesity. His research was founded on the solution-oriented research paradigm where he applies concepts of process motivators and stealth interventions to promote sustainable improved health and wellbeing in children and their families. He's gonna tell us more about those stealth interventions today, which I am really excited to hear more about. He has published hundreds of articles to help children and their families live healthier lives. Dr. Robinson is also a principal investigator for the Human Screenome Project in the Screenomics Lab at Stanford University. The Human Screenome Project is a technology platform which analyzes what people are actually looking at in real time. The aim of the project is to actually see what people are doing on their screens to find out the effects of media on our mental and physical health, on our education, relationships, and even politics and democracy. It captures subject screens, I believe, every 5 seconds, but Dr. Robinson will tell us a little bit more about that today. So I'm really excited to have you here. Thank you for being here, and thank you so much for dedicating your life to this important work for our children.

Oh, well, thank you for having me. It's a pleasure to be here and have a chance to talk about the work we're doing.

Yes. Tell us about the Stanford Solution Science Lab and the solution-oriented research paradigm.

Right. That's a mouthful, isn't it, when you bring them together? Solution-oriented research really came about as through my frustration of sitting on national panels and committees that were charged with coming up with recommendations to help policymakers, parents, physicians, other health professionals, you know, decide what the priorities should be, guidelines and recommendations. And frequently the case is that the questions we were asked to address usually weren't addressed directly in the available research. So you had to extrapolate so much research is really focused on problems, on the causes of diseases, the causes of problems, risk factors, and not on what makes things better. Yet what the information everybody needs is what should we do? How do we do it? To whom? Where? When? You know, how? And so it's really those practical issues of solutions we're really missing from the literature. So the solution-oriented paradigm was was developed because really I said, well, how could I move this forward? So more of our research actually led to actionable solutions, the, the actual practical and policy-relevant outcomes that people are interested in. And so solution research in the Solution Science Lab is really focused on the way we design our studies in a way, instead of just looking at the causes of problems, let's look at the causes of solutions. And at the end of the day, if you're only studying problems— so for example, you know, we did a lot of early work on screen time and obesity in children. And in that work, there were a number of papers that came out that were observational epidemiological papers that showed that the more kids reported, you know, watching screens and spending time on screens, the heavier they were over time. But that told you that maybe those two things were related. But it didn't tell you, first of all, because they were observational studies, epidemiological studies, they didn't really tell you anything about cause and effect. They gave you a hypothesis that those were related, but it didn't— you couldn't prove it from observational data. And then also, even if you found an answer, you know, whether they were related or unrelated, you know, related or inversely related or null, then you still wouldn't know what to do about it if you found what you thought you were going to find, because you were still held with the fact of saying, oh, you better reduce your television, your screen time because you're going to be at higher risk for obesity. We said, well, that doesn't really help us that much. The other thing is we found is that a lot of that research really was based on self-reports. So there was a lot of wiggle room in there, a lot of problems with the accuracy. So even if you came up with a null result, you didn't know if it was a null result because people just reported inaccurately about their screen time or whether it was because there was really no relationship. So the way to address that was to say, well, you know, I don't really need to prove whether screen time causes obesity. I'm more interested in knowing whether there's something I can do about screen time that would reduce obesity or reduce weight gain. And that's the solution-oriented approach. So we designed a bunch of randomized clinical trials in which we developed methods to reduce screen time. And that took a while to do, a lot of pilot work and other things to help families do that and help children do that. And then, then we tested those in randomized controlled trials in which we tested kids who were given, for example, in a school setting, curricula that were designed to help them reduce their screen time versus kids who were in a school in which they didn't receive that curriculum and followed them over time. And what we found is that, in fact, for one, at least based on self-reports, we could reduce their screen time. And at the, at the same time, the kids who received those interventions, those curriculum to reduce screen time, gained less weight, became less obese, than children who did not receive that curriculum. And they also became less aggressive on the playground and less likely to be nominated by their peers as being violent and aggressive. They became less commercialistic, less materialistic in terms of the requesting toys and products that were advertised on TV from their parents. And it improved their school performance, all from just reducing screen time. So the idea was from a solution-oriented perspective, is that we found that we didn't have to first prove that screen time caused obesity before we said we're going to go directly to a solution. Now, if it hadn't worked, we could have said, well, that didn't work. We need to try something else. And so you don't lose any time with it, but you don't lose the time of just having hypotheses that don't lead to knowledge of what the solutions are.

So— That's incredible. I love that. That's amazing. And how old were these kids?

Oh, in those studies, they ranged from— we did studies with preschoolers up through middle schoolers, I think, in different studies. And so it was a number of different studies. I was going to mention this because you'll understand this. You know how in another part of the solution-oriented paradigm is really was creating a, what I call a litmus test for how you know if you're doing solution-oriented research. And as a clinician, you'll understand this, is that we try and teach our medical students and our residents not to order a test, right, a diagnostic test or a screening test, unless they know how they're going to interpret the answer and then it's going to lead them to do something differently. So no matter what the answer is, you should know what you're going to do with it. You shouldn't just order because you're curious. You need to know what it's— what you're going to do with it, and that once you get an answer, it's going to change what you do to treat the patient. I said, well, that's a really good that's the same type of thing. You know, clinicians, we're action-oriented, we're always intervening, we're solution-oriented. So why don't we apply that same principle to research we do? So you don't do a study, or if you want to do solution-oriented research, it's not the only type of research to do, but if you want to do solution-oriented research, then don't do the study unless, or the study should, you know what you will conclude from the answer to the study, positive, negative, or null. So if you get an answer, if it's not going to change your mind, if you believe that screen time causes obesity and you get a study that says they're unrelated or that it even caused weight loss, you know, you're not— and you're not going to believe it, then why do this study if you weren't going to believe the result in the first place? So you better know what you're going to conclude regardless of what the outcome is, and then it's going to change what you do to take care of the patient or the population.

So basically designing studies that are actually gonna make an impact on public health.

Correct.

That's, that's the idea. An impact at least on, on what we do, all the things we need to know to do either as professionals or as patients or as policymakers.

Mm-hmm. I love that you said you have to think about what the, what you're gonna do with those results before you order them. And I'm a radiologist, so when, you know, I was doing, oh, right. When I was doing rotations through the ER, what people just order studies constantly. And obviously you're a pediatrician and pediatricians are definitely a little less likely to order studies immediately. So, um, yeah.

Our patients tend to be a little more healthful or more healthy than, than some other groups. Yeah.

Yes. And you wanna avoid radiation as much as possible with kids, but definitely I used to get into a lot of fights because they would order, even on pediatric populations, they would order studies with pre and post-contrast and delayed imaging and all that. So, but anyway, I really appreciate that. So how did you get interested in pediatric obesity in the first place?

Early, early in my career. In fact, as a, I think probably as a resident when I really solidified that. And during medical school, I got hooked on the idea of prevention. Once again, is that's, you know, prevention versus treatment. Even though I was in medical school and you're learning to treat disease and diagnose and treat disease, is that so much of what we see in medicine is preventable. And, you know, the bulk of our GDP is going to taking care of people at the end of life for a lot of things that could have been prevented if they'd started earlier with more healthful lifestyles. And so I got really interested in prevention at that time. The two big areas of popular research for public health and prevention were gang and gun violence and HIV. So I started getting interested in those and looking into those, but I noticed That was the beginning of the onset of the obesity epidemic in the US. And it became clear to me that the obesity epidemic was becoming a huge problem, even though at that time, I'm not sure we would've called it the future obesity epidemic, but it had many of the characteristics that made it almost a perfect public health problem in that it involved social forces that were really out of individual control. You know, your individual behavior was important, But the food industry played a huge role in it and creating an environment in which food was highly plentiful and it tastes really incredibly good and it's cheap. And they spent billions of dollars to make you like it and want you to have more of it. And the entertainment industry was out there trying to get you to spend all your attention on entertainment and be sedentary. And the transportation industry was there to make you be sedentary and not have to, you know, to drive everywhere instead of taking public transportation. And other things. And so it had all these social factors that made it really, really tough for people to maintain a healthy weight. At the same time, there was this whole stigma, societal stigma against it. So similar to something like HIV, except HIV was invisible until at that point you got Kaposi's sarcoma and other things that made people aware that you were sick. But for many people, it's— and today it's invisible. So there wasn't the discrimination, but there's tremendous discrimination against people based on weight. And so at the same time that our society is discriminating against people based upon their weight, and there's tremendous stigma that has impacts on your psychology as well as, you know, social factors, the way whether you get paid more or less, all kinds of factors that affect you in a social way, going against all these pressures of society to make you heavier and consume more and exercise less. And so I've realized that this is really a huge challenge. This is gonna be, to me, a really tough thing to study. And so that's why I chose it.

Um, really—

that's amazing that you saw that back in that time because I don't think people were talking about it as much. I certainly wasn't looking at prevention until I had kids, you know, of my own. The minute I had kids, I was like, wait, prevent everything. And that's when I started, um, getting into lifestyle medicine and mind-body medicine. But I really appreciate your foresight in that. And I want to get back to what you said about children or people who are obese and the societal factors and the shame that's put on it. However, their environment is affecting them. And that's why you went to get your MPH, right? Master's in Public Health.

That was a part of it. A part of it was very pragmatic. It was so I didn't have to start paying back my student loans during medical school while I wanted to do full-time research. So it was while I stayed in school, I could do that. And so I spent a year getting a master's in public health to learn. And really it was life-changing. It gave me a different perspective that you don't get in medical school. I mean, I was learning about neo-Marxist health policy and all kinds of other things and really learning about the way that public health professionals, their perspective on problems that are different from the way we're trained to do it as physicians. So to have both of those perspectives, has been really valuable to me. It made me focus on a lot of the social, psychological, environmental factors that really determine our health even more than sometimes our biology. You frequently hear your zip code's more important than your genetic code. That's true. When you look at the amount of variation in health that is due to genes, it's smaller than what you could predict just by knowing what zip code someone lives in.

That's incredible.

When you look across the population and you're seeing the same type of thing with so many parts of life. I mean, there's terrific research by Raj Chetty at Harvard, an economist, used to be at Stanford, who looks at where people were born and where they lived and links that to their income level when they're adults, even controlling for their parent levels of income and things. And so just the resources that are available, the social ties that you make, all of those things that, that play into where you live and what neighborhood you live in really have a a large determinant on where you end up, even with something like income and certainly with health.

Yes. And obesity. I mean, you do talk about the socioeconomic factors that play into obesity as well.

Definitely. Yeah. And, and, you know, and it's funny in our country, I mean, obesity is a worldwide problem now. Yes.

Yes.

When it first started, it was mostly in the more, you know, advanced developed countries as opposed to the middle-income developing country. But we're seeing is that as it's spread across the world, for example, in China or in India, it tends to affect the groups that are upwardly mobile, right? The groups that are increasing their income level or higher income levels, because they have more access to our, unfortunately, our Western ways of life and our Western habits and products, economics and everything that drives these unhealthy or what people call a toxic environment.

Mm-hmm. Well, you're a pediatrician and you were talking about chronic diseases and how what you do in childhood affects that way down the line. And a lot of parents, now will say, oh, my child is resilient. They can bounce back from these things, these habits or bad things that happen later in life. You know, they could eat this way or basically people think that children can bounce back from a lot of bad habits. I mean, I know my answer, but I would love to know yours.

Yeah. I think you can start at any time in life. It's beneficial no matter how old you are, how poor your habits were before to change your behaviors. At any point. There's a type of research called the early determinants research where people say that, you know, your first 2 years of life or your first 5 years of life determine the whole rest of your life. And I have a colleague who says, well, if that's true, then adolescent medicine is just palliative care, which I think is a really great description of that approach, is that no, it's not over at 5, it's not over at 2, it's not over at 18, but you have a lot easier time and it's better the earlier you start. And sometimes that thinking has created divides within the prevention research world of saying, oh, we need to go earlier and earlier and earlier to start. Whereas I would argue we need effective approaches at every age group. So even though I'm a pediatrician, I hugely believe in intervening in the elderly, in seniors at any age group. And that just hasn't changed as I've gotten older. That's been something I've believed in along the way. It's really a whole life course approach. And the sooner you start, the better. But that doesn't mean you give up. If you have obesity when you're a 17-year-old, doesn't mean it's too late that you have to give up. Now, given— and you're probably aware of this— that if you have obesity prior to puberty in childhood, that your risk of being an adult with obesity is, I don't know, about, about half or so. You know, it changes over time. When we look back at historic data, it's tough to know what it is now, but it's to say about half. Whereas if you take that obesity and that goes with you through into adolescence, into your teen years, it goes up to 70% or 80% or more of your risk of being an adult with obesity. And it also increases the risk of you having a higher BMI, a higher body weight when you are an adult than people who became obese as an adult. And The risk factors associated with obesity, the comorbidities, are all associated with the degree of obesity. And so that means children who carry their obesity into adulthood on average tend to have more health problems associated with it than children who started later or than people who developed their obesity as adults. So yes, start early, try and prevent it. Prevention is the best, but you know, it's never too late to start. Right.

But primordial prevention is best, right? So I don't know if people are aware of the health effects of obesity. I know you talk about how it affects every single organ in our body.

Exactly. And I think that's one thing that makes it also a very interesting problem to study and why it's so important to prevent it. The common ones that most people know about are diabetes, type 2 diabetes, much higher risk of type 2 diabetes. And actually, if you're Asian or South Asian, the risk is even higher because people of South Asian or Asian descent actually develop the comorbidities at lower weights than Europeans.

I was going to talk about that because the BMI shows that Asians have lower BMIs than other races. However, diabetes is higher in that population and the waist-to-hip ratio is lower for disease occurrence.

Yeah. The thresholds of where you start to have problems.

Yes.

That's the word.

I mean, there's no clean— There's no clear threshold, but that, so you tend to have those problems. Asians and South Asians tend to have problems at a lower BMI than Europeans or a lower waist-to-hip ratio.

Mm-hmm. That's why when my friends tell me, oh, you look so good. I'm like, no, I have this abdominal weight that's starting.

Yes. Anyway, what we don't wanna promote, I also have studied eating disorders over time too. Oh, okay. So we don't wanna promote people's, you know, developing the other way as well. And there is a, a lot of people who believe an emphasis on trying to prevent or treat obesity is going to increase eating disorders. But we know that people with obesity are at increased risk to start with as well. So that's one of the things you had said about different parts of the body. One of the things that we're concerned about is the risk of developing disordered eating behaviors, of, of, you know, doing something, trying an unhealthful way of controlling your weight.

Mm-hmm. Um, but sometimes normal could be the disordered eating. I mean, if I'm eating a lot of junk food that's ultra-processed and makes me addicted to it, that's creating abnormal eating patterns for me.

So, right. Yeah, definitely. That would, I would, I was thinking more of sort of the classic, you know, anorexia nervosa, bulimia nervosa, but, but yeah, you could define a current American diet as an eating disorder, you know, in many ways for that. But that's just, you know, one is the mental health aspects of it. So disordered eating. Depression, actually a higher risk for memory loss. And even there's some studies showing adulthood that higher risk for dementia. There's also in children, even kids with obesity, especially, and even kids who've lost a lot of weight with obesity could be at increased risk for increased pressure in the brain, something called pseudotumor cerebri, which you're probably familiar with, which tends to show up in your higher risk, unknown why in this population, the population of children with obesity. That's the brain. If you go down, of course, we talked about the most common is the diabetes, heart disease, coronary artery disease, the atherosclerosis, stroke. Those are— you're at higher risk for those with obesity. Cancer. The International Cancer Foundation is predicting that by the middle of this century, obesity will be the number one cause of cancer worldwide, taking over tobacco, you know, exceeding tobacco because obesity is increasing at such a rapid I don't think the lay public is very aware of the link between cancer and obesity. Yeah, it's not as well publicized, but yes, no, cancer, about a dozen cancers in particular are tied to obesity and particularly some of the more common ones.

Like colon.

You know, tobacco as well throughout the body. But you know, people are probably— But like colon cancer.

I was a breast imaging specialist, so breast cancer, I know that.

Breast, colon, endometrial, you know, ovarian. Cervical, uterine cancers, prostate.

And you have talked about fatty liver disease, which actually can lead to a type of liver disease called cirrhosis, which is very similar to alcoholic liver disease.

Right. Pathologically, it's indistinguishable. And yeah, fatty liver disease, it's expected to become the number one reason for liver transplants in the future as well. And we see evidence of it even in kids, you know, children with obesity. We see evidence of damage to their liver. Even in children. And there's, at this point, there's no great treatments for it other than weight loss.

Mm-hmm. When it's fatty, it's reversible. So that's a, that's great news, right?

Yeah. When it turns, when the inflammation kicks in and you start to get fibrosis that you get with cirrhosis, and then it's not reversible.

Correct.

So then it's a big problem. You know, there are centers where they study this, where they're doing liver biopsies and are able to see changes that occur very early in life. Similarly, autopsy studies that have been done of kids who die in traumatic, you know, from like car accidents or young adults who die in battle in wartime. You look at their coronary arteries and the amount of atherosclerosis, the amount of that narrowing of the arteries and the plaque is directly related to their BMI, to their weight. Those effects are happening very early in life. Kidney disease. A higher risk for kidney failure and kidney disease. I can, I can go through every— arthritis.

Yeah.

Arthritis. Yeah. Impotence, infertility, premature birth, all kinds of, you know, basically any body system, any musculoskeletal use of the arthritis. But also there's a problem you see in kids with excessive obesity, sometimes called Blount's disease, which I'm guessing you're aware of through radiology.

Yes. But you can tell.

Yeah. Where it's, where there's a bowing of the bones of the legs, you know, and skiffy. Yeah. And skiffy as well. That's a problem. Common, even more common problem with obesity. Yeah. Where kids, the joints, they sort of fall off each other from the excess.

Because they're not fused yet. So they start to kind of slide off each other. So getting to your incredibly interesting research on telomeres. Do you say telomeres or telomeres? I say telomeres, but. Telomeres.

Yeah, I, I think I probably go back and forth.

Okay.

But it's, yeah, it's either, yeah, you can say, I think you can say it either way. I don't know.

So your incredible research on telomeres, can you tell everybody what that is and what it means and what you found?

Sure. Telomeres are, are these repeated sequences of DNA at the end of, of your chromosomes. And your chromosomes are how the DNA is stored in all your cells. Your genetic code. And every time the cells divide, there's damage to the ends of your chromosomes. And so these telomeres protect those chromosomes, the edge of those ends of those chromosomes. But because they are associated with cells, the telomeres get shorter as you age, you know, as the cells divide more over time. And they're seen as a marker of aging, of biological aging, of aging of your DNA at the DNA level. So older people have shorter telomeres than younger people. And you can even see it in children. As children, you know, age, the telomeres get shorter because these are happening to a measurable amount. And sicker people, people with chronic diseases like the heart disease and diabetes and those things, tend to have shorter telomeres than healthy people or people without those chronic diseases. So we were interested in that as sort of a biological measure of aging that occurs potentially with chronic disease that might be interesting to look at in its relationship to obesity. A lot of people have looked at obesity and found people who with obesity have shorter telomeres. But we did it from, again, from a solution-oriented perspective. We wanted to see what happens when we put people, when we put kids through a weight control program, a behavioral program 6-month program in which they learned to eat more healthfully, learn to be more physically active, and reduce their screen time, what would happen to them, to their telomeres over that period of time compared to a time when they weren't in the program. And so in that time, we were in the program was the year after the program ended. We followed them for an extra year. So we had children who with obesity who went through this program for 6 months. And then followed them for another year. And we measured their telomere length at the beginning of the 6 months.

Mm-hmm.

And at the end of the 6 months, at the end of the behavioral program, and then again a year later. And we found out during the 6 months, their, their telomeres on average actually got longer during that period of time. And then when we looked at the period of time for a year after the treatment, as they tended to, you know, some of them move back towards some of their previous habits, which happens if the program doesn't continue on and things, is that, that their telomeres then started to get shorter again. So we know it wasn't just that they started short and got longer and it was something called regression to the mean. We actually saw two slopes. We saw that the telomeres got longer and then shorter over the subsequent time. So we can attribute that association to that what else was going on during that period of time. Now, again, it wasn't an experiment, so it wasn't a cause and effect, but it allowed us to say, look at— in addition to the other changes we saw, we saw improvements in their blood lipids, in their cholesterol levels. In this program, we see improvements in their risk for diabetes and the measures of their insulin resistance. We see improvements in their weight, of course, if they go through this. We also saw improvements in their biological aging. So we actually retarded the accelerated aging that was occurring in kids with obesity during that period of time when they were losing weight. And so that was really remarkable to us that we actually could see effects at the genetic basis. We're also looking at other, you know, epigenetics and methylation and other patterns too, but we haven't in a different study. But we actually saw at the level of biology, we saw these changes. Beyond what we see clinically.

Mm-hmm.

So that's why we thought it was interesting to study is because people say, well, weight is just cosmetic. Or even though we've, we've talked about already, it's not just cosmetic and weight is, you know, it has many other really significant problems associated with it. But as well, we even see this in our biological aging. One of the cool parts too, that I think you'll appreciate because of your interest is that, you know, people, investors and venture capitalists and all these tech people in Silicon Valley where we are, where I am, they're investing all of this money into all these wild ways of increasing their longevity and, and usually high-tech methods and crazy regimens that people can do. Yeah. All kinds of things. And yet what we showed is that, wow, you can slow aging, you know, and even potentially reverse it a little bit from what we've known all along, you know, eating a more healthful diet, being more physically active. And spending less time in front of screens. It's not rocket science here. It's the— it's not that we have to come up with some new discovery. Potentially, I can't say we increase longevity because we'd have to follow these kids for a long time and a lot more of them, but potentially slowing aging down just from all the things that we know we should be doing anyway.

Simple things can be so powerful. Yeah. I'm going to get up after this interview and go eat my veggies and oranges. Go for a run. But so for the lay public, when the telomeres are longer, that means your biological age is younger. So, but the most interesting thing is that it went back and forth, which means that you can reverse some of the effects, right?

There were differences and there's, there's controversy because, you know, these could be a different distribution of the type of cells that were measured at two different times and periods of time. These were white blood cell telomeres. That we got and the distribution of your white blood cells could change over time. So we didn't see telomeres get longer. What we saw is the average telomere length got longer. So the distribution of cells. So we know that that was occurring. And during the other period of time, the average telomere length got shorter. So, because it is controversial, there is— I mean, we know you can extend your telomeres. There's something called telomerase, which, which does that. But And there are a lot of people studying that. There was the part of a Nobel Prize, Elizabeth Blackburn at UCSF. Yeah. Yeah. And well, now UCSF and she, so there, there, we know that telomeres can get longer, but this wasn't, we didn't study it in that way. We were looking at the population of the cells. So it's probably safe for me to say that we slowed biological aging. We have slowed the accelerated aging associated with obesity more than I would say that we definitely You know, we didn't go, it didn't go in and necessarily, we don't know if the telomeres actually got longer, the individual telomeres.

Got it.

Okay.

So I'm really interested in the concept of stealth interventions for applied behavioral change. I saw one of your videos where you got people to stand up and give a standing ovation, and you said that was baking in healthy behaviors just to get people to stand up after you know, they've been sitting for a long time. I love this idea of like mini behavioral changes. Can you tell us a little more about that?

Sure. Again, a lot of things come out of my own frustrations of why, you know, we've had a lot of success in our interventions at changing behavior. A lot of that I attribute to our foundation in good behavioral science and knowing the theory and understanding the theory and how to apply it. But I still get frustrated because Even the best behavioral interventions frequently revert. You know, they're short-lived. They tend to be moderate effect sizes. You know, I want to produce large effects on people, have large impacts, and have them be sustainable over time. And so I started thinking about, well, what are examples of where people change their behavior and change it dramatically and change and stick with it over time? Well, the classic example is sort of religious conversions or religions. Where people don't have a problem. Seventh-day Adventists, you know, are much more likely to stick to being vegetarians than someone doing it for their health purposes. Or, you know, people who keep kosher or even, you know, in an extreme, there are people who give their life for a religious or ideological cause. It doesn't have to be religion, but an ideological cause. And that's pretty powerful. I mean, we don't see that in health behavior change, you know, by telling people that if you don't do this, you're going to get cancer or heart disease or, diabetes. And so why not? And what is special about those things? Because sort of the classic theory would say if it's more relevant to you personally, it should work. So your health should be a motivator. But I started looking for other things that I thought were other ideological-type movements. I've always said if I could get it through the human subjects internal review board, I'd start a religion. But I don't think they'd ever approve— let me do that. So what are other religions that are out there? Well, environmentalism and animal rights, you know, activism, lots of social movements that exist where they are treated almost like a religion to people or almost because they have some of the same characteristics. And so we started looking at those and many of them actually overlap with the same types of behaviors, the behaviors, the goals of those overlap with the behaviors we have for obesity prevention and chronic disease prevention. So for example, the two biggest contributors to greenhouse gases globally are livestock production and transportation. Well, what are— what are two of the biggest contributors to weight gain and obesity and heart disease? Well, eating an animal-rich diet, you know, highly processed food and being sedentary. So from a solution point of view, I can change my behavior, eat a lower, mostly plant-based diet, and walk and bike and take mass transit instead of drive to save the planet. And as a side effect, I'm actually helping my health. I'm achieving health benefit. Same type of thing is with the teenage girls who come to see a pediatrician and are vegetarian. Rarely are they doing it for their health reasons. They're doing it because they don't want to to hurt animals, then they think, well, that's your motivation. So a stealth intervention, even though the word kind of sounds kind of stealthy, is not about deception. It's not meant to be about deception. It's really about building interventions that help people change for the reasons that are important to them, not necessarily reasons that are most important to me. So my focus for them as a physician and as a public health professional is on their health. But if I can get that as a side effect, like having them change their behavior for other reasons that are more salient to them, terrific. Then we both win. It's a win-win. You know, other examples like the standing ovation type one, that's a simple one. Getting up, you know, scientific meetings, people frequently have built-in standing ovations to do that. So they're standing up occasionally. But, you know, Team in Training or those other charities that train you to run a 5K or a 10K or a half marathon or swim an Ironman or things to raise money for a charitable cause. Same type of thing. You can get a person who would never do that for their own health, you know, purposes to start to run, who would train to raise money for another thing because it's this higher purpose, this collective purpose. There's collectivism in doing it with a group, with other people. You know, part of this, when I started thinking about it, is why are these things so effective? I mean, right now we're seeing political protests on campuses. When I was in, in my day, I'm going to date myself, as an undergrad, the big thing was apartheid, protesting apartheid in South Africa. Well, people were really willing to march and to do sit-ins around ending apartheid and ending, you know, investment in South Africa. Companies and things like that in the South African government at that time, that was highly motivating to people. Those same people, though, weren't necessarily going a mile away to a poor part of town to teach a kid to read, which, which they had much more control of in many ways. So, right, if you have much more control over that, you really aren't going to stop climate change on your own, but you could help a kid get out of poverty by helping them with school. And helping a family with school. What I've come up with in my thinking about this is the theory sort of of stealth interventions is that it prevents you from failing in many ways. There's a fear of failure in that if you go to a poor neighborhood and try to work with a kid and help them get out of poverty, there's a chance that they may not like you, that they may, that you may fail, that they have other things that make it too hard. If you protest You know, climate change. If you don't end climate change, you haven't failed. You still succeeded by being part of the movement. So that's where process motivators come in too. The process of making that change is motivating in itself. You don't have to achieve the end goal. Like with weight, same type of thing. If I'm only worried about my weight and I'm trying to change my eating behavior and I step on the scale and I've gained a pound or two, then that's a real hit to my confidence level. And what we call self-efficacy. That's a real hit to my confidence. And so I've somewhat failed at that. You know, it's not working, or my weight is plateaued and that's not working. Whereas if I'm altering my eating behavior because I'm trying to save the environment, then I haven't lost it all. I can keep doing it. I'm going to continue doing it and trying doing more and trying to eat lower on the food chain and even fewer processed foods. And become more and try and change my family environment and what my family eats, what my kids eat, what my parents eat, those type of things, and have an effect on the environment. And then as more people do those things as well, I'm not alone. If I'm trying to do weight, I may be alone. If I'm doing those things, I'm part of a community which creates norms around behavior too. That makes it easier to fulfill those norms. Also, if we're successful, it changes policy. So then, you know, grocery stores start stocking more healthful foods because they're better for the environment and they start creating sections of low-carbon foods and institutions. And your employer builds bike racks so you will bike to work and things that also make the behavior easier to sustain. So it has this really synergistic effect that magnifies the likelihood that you are going to make more greater magnitude changes. Mm-hmm. I said magnitude twice there. That really magnifies the likelihood that you'll make larger changes, more dramatic changes, and that you will sustain them over time.

That is fantastic. And I know that you had a part in Gen Z. I read that Gen Z is, um, one of the most, uh, caring generations and that 2 out of 3 of them will care about who they're buying from and what the values are of that company. So I'm pretty sure you and your research has had some influence on that with the amount of research coming out of your labs. I mean, it's incredible the work you're doing.

So thank you. Well, I'm, I'm not sure I can take, uh, some of that.

Please take some credit.

Please take some credit.

Yeah, but I, you've definitely, but I'm, I'm, you're definitely on the forefront of that. So I really appreciate it. I, I just really wanna thank you for that. Thank you.

Yeah.

And for dedicating your life to this. This is incredible. But before we go—

Well, what could be more fun? What could be more motivating?

I love animals.

Maybe ending climate change, but get to work with children and families and help them, you know, achieve the things that they want to achieve for themselves. So it's really, you know, to do the work I do is a true privilege.

Before we go, can we talk just for a few minutes about your Screenomics project, which sounds so interesting and fascinating?

Yeah. Like I said, I have a great job. Yeah, Screenomics came about, I mean, for a long time I've studied, as I gave in that example of screen time and obesity, I got very interested in screen time because of its relationship initially to obesity, but also because it's, you know, as I started researching it, kids spend a quarter to a third of their waking life in front of a screen. That's more time than they spend in school. That's more time than they spend with their parents. You know, the only thing they do more than spend on screens, and that's not always the case, is sleeping. You know, because it affects sleeping too. Now it came to me that even if screen time was only— had a small effect on children, that it would magnified over all these hours, it would tend to turn into something that was important from the perspective of someone who's interested in child health. So I started studying screen time. One of the real limits of understanding how to build better interventions to help people reduce their screen time or to understand how to prevent the negative impacts of screens, one of the real barriers was that we really didn't know how to measure what people were exposed to on their screens. And that's gone back in media research. That's gone back, you know, 5, 6 decades beyond. That's always been a huge weakness is we've always had to depend on what people tell us, how much time they spend on their screen. Well, it turns out whether it's television or magazines for that matter, or their smartphones, that people are are not very good at that, at telling you accurately.

I know when I look at my screen time data, I can't believe it sometimes.

Yeah. It's really quite amazing in that we find that people overestimate and underestimate. It's not just all consistent in that they're all over the place. Some people seem to be right on at times. So there might be some people who actually do it well, but for the most part, when you're looking, it's, it's all over the place. And so, and it turns out it's just so bad that you almost can't conclude anything from it. So we've had hundreds and hundreds of studies that have been done that really are based where the results are based on people's reports of how much time they're exposed to screens. So Screenomics was an approach that really came out of the work of two colleagues of mine, Byron Reeves, who's a media psychologist, and Neelam Ram, who's a developmental psychologist who studies time and change and how things change over time. A lot of stats and math and how we understand how things are changing over time and model them, which is what's happening in, you know, with screens. And then I bring in the health component and the health perspective and the intervention design perspective. As part of this group, and now we have a fourth collaborator who we work a lot with, Nick Haber, who's a computer scientist who does a lot of our AI, guides that part of the projects, who's a professor in the School of Education at Stanford too. And the other two are in communication and psychology.. And so we developed an app that goes on your phone and we also have one for the laptop and takes a picture of the screen every 5 seconds. By doing that, we are able to see everything that people see and do on their screens. We're the only people at least who admit to being able to do that. I'm sure other people are doing it. We know probably the National Security Council and the, you know, I know there's—

It's all there, right? I mean, they can look at what you're looking at.

Yeah, potentially. But the, the, I think the, the company— no one would admit to it in the corporate— I mean, they, they follow you around the internet and take all your typing you're doing and stuff, but we can actually see what's on the screen. So we see what's on the screen, then we build AI models to actually tell us what's on the screen, to scrape off all the text, to look at the images, and then we can look at, you know, what apps they're using, what they're seeing. Because it turns out that, especially when we started doing this, that everyone's experience is unique. That screen time, especially on smartphones, but also on laptops, is totally idiosyncratic. It's that both within a person, across time, and between people, no two people have what we call the same screenome. So the screenome is like the genome, right? But the screenome is a record of your life on screens as opposed to the genome, which is your genetic makeup. And so this is your makeup from your, your screen life.

My brain flitting about from app to app to app to app.

Exactly. That's one of the things we see is the amount of fragmentation that occurs and the jumping from thing to thing to thing, from topic, not even just app to app, but also topic to topic even within an app. You know, if you're jumping from thing to thing, but it is, you know, you see one thing in a news story, you jump to send a text message to someone and then you're reminded that you need to see if someone liked your post on Instagram and then you have to jump over and check your airline reservation. And then you go back to, to see, oh, what's in my calendar? What did I need to do? And then you go back and someone responds to your text. It's crazy. And to the person who's doing it, for you as a user of your screen, it makes total sense, right? You're just jumping around. This is how you're— this is your mind on digital media. But to an outsider, it's all fragmented and we have to put this together into stories. And say, but we can then look at how these different patterns of use are potentially related. Well, first of all, understanding what these patterns of use are, how are people using digital media? Because actually we have a very limited understanding. Most of it's based on self-reports of how people use digital media. But, um, but also how those changes and how those things affect our health and our wellbeing and our politics and other things like that too. And so, like I said before, that it's totally idiosyncratic, even from hour to hour. No two people look alike. No two people's ScreenOMEs look alike. And your ScreenOME doesn't even look alike, that much like your ScreenOME from an hour ago or from yesterday at the same time of day or from two days ago or from two weeks. So asking someone on a questionnaire how many hours they spend on Instagram really isn't going to tell us very much. Because it's changing so much in all of this. Well, so far we've collected data from about 250 adults for a year. So every 5 seconds for a year that their phone was in use, and from 154 adolescents and 105 of their parents for 6 months. And then every 2 weeks during these, we also sent them surveys about their mental health, about other health, about their tobacco, alcohol, and drug use, about COVID This was started during COVID about COVID symptoms and their attitudes around COVID and beliefs around family relationships. All these, all these different factors that we measured that we can look at to see if there are patterns in people's screenomes that relate to what they report in terms of, for example, their mental health. We have already just submitted a paper looking at individuals, just simple measures of their screen use. And how highly correlated they are with their reports of their mental health, you know, depressive symptoms, ADHD symptoms, anxiety.

Was it a positive correlation or a negative correlation?

It's actually different in different people. It depends on— and it's different types of characteristics. So some people, you know, the dominant seems to be that they spend a lot on social media and other people, they're switching a lot. They switch apps a lot, so it's different people. And so it goes back into this individualization, which we're going more and more towards this idea that we're going to have to look at you as an individual, not the exposures that everyone is exposed to. Are there exposures that put you at risk? Well, that's probably the case, but are there periods of time in your life that you're being exposed to certain things that put you at risk? Because it's the combination of things, the context as well. When did you get that, that bullying message? Did you forget about it because you were in a positive mood because of other interactions you were having, or did it reinforce something else that happened to you just in the screen before it or in the hour before it or the minute before it? How do we connect those things to see what their interactions are in terms of how they produce, you know, important outcomes?

And have you seen any patterns or anything yet that is enlightening?

Yeah, we, we have. We're also doing a study that NIH is supporting too, of looking at the food screenome of adolescents that we're just starting, where we're collecting new ones. But we've seen, for example, some kids who have— now these are all correlations at this point— the kids who spend a tremendous amount of the time of their screenome is— involves food images and text. You know, that they're playing games that involve food. They are sending pictures of food in their social feeds. They're watching cooking shows and watching YouTube videos about food. They're talking in their text messages about food and eating. We found one teenager whose 37% of her screens on one day had food in them. 30% of the screens in one day. And so We're looking at relationships like that of feeding to, to what they say they report they ate as well. Let's see, what type of things are we seeing? We're seeing, well, first of all, a lot of this idiosyncrasy, the mental health, we're seeing definitely that different patterns in individuals can be repeatable and are highly correlated with it. So that would give you an idea that you could go in and on an individual basis, design an AI program that would, if you opted into it, obviously, that would help moderate your screen use, to change your screen use around. So if it felt that you were getting into a high-risk pattern of screen use, could send you the other way.

I need that.

Towards something else. I mean, we've actually found one of our former grad students, now he's a professor researcher in Taiwan, but he, one of the things that he found in part of his work was that there seems to be this natural up and down. If you look at the words on the screen, natural up and down in sentiment, you know, positive versus negative. If you have a period of time where all the text on the screen is negative sentiment, tends to go back towards the beginning. And it's a little bit of like a regression to the mean back and forth type of thing where you go one way, the other way. But we don't know if that are those algorithms that are driving that because they have been able to figure out that keeping you sort of in that Homeostasis is, keeps you on the screen longer.

You get a little negativity and then you see more positive things and you go negative. And you don't know if they're self-directed, the person is saying, oh, this is too upsetting. Now I'm going to look at something positive. Or if the algorithm is just pushing it into you.

Yeah, it could be me as a user saying, oh, that's too negative. And, you know, not conscious of it, but moving towards something, you know, going to cat videos from reading the news, you know, then, you know, cat videos are a little too sweet or something. So I, You know, then I'm going to read my email or something. I don't know what it is. It could be that, or it could be also some of the impact could be human nature trying to keep us in some homeostatic state where we don't go to too many extremes, or the algorithms having some role in keeping our attention as long as possible.

Wow.

That's part of why we also measure every 5 seconds and we would measure every 1 second if we could, but, and we're getting close to being able to, but we don't want to slow down people's phones or anything. It totally runs in the background. So it's not something that people are necessarily aware of. They're all volunteers. They all get a full consent. They know exactly what we're doing. They give us their data and tell us we can use it. We frequently, you know, while people freak out at the idea about data, they're giving away their data to companies constantly for free.

True.

To use against them.

True.

You know, to sell them stuff and other things. And so when they see an opportunity often to give their data to a researcher who is going to protect it, keep, maintain privacy, is not going to sell it to anybody, is not going to be used for anything else except for learning to help people over time. You know, we generally don't have a big problem, you know, having people volunteer to participate, even though we're seeing very, very personal parts of their lives.

I was going to say, probably in the beginning, they're maybe they're on better behavior and then, and then they probably forget about it.

Right? Well, it is, we make sure we remind them so they know, because we feel like that's appropriate, but I think we don't see changes in their behavior over time too much. I mean, we see maybe people, when we talk to people, they tell us acted a little bit differently or more aware of it at the beginning, like you said, and maybe, but also I think it is especially younger generations are aware that nothing they do is private.

No, I don't think they are. I have kids, they forget.

Yeah.

Totally forget.

Yeah. Well, maybe they forget, but they're, they don't seem as concerned about it as older people.

They don't get concerned until they're looking for jobs.

Yeah. I mean, to see what they, right. To see what they put on their Instagram and TikTok. I don't know. But part of it is looking at these every 5 seconds or very rapidly is being able to create hopefully precision interventions, right? Which would be just for you. That would be a truly personalized intervention because it would be based on your screenome and it would learn from you over time what makes you happy and what makes you sad, what makes you exercise, what makes you sedentary. It depends on what you're interested in changing in your life. You know, what it's— what has led to toxic relationships, you know, what communication patterns, what is not things.

And so, um, so your personal AI coach, basically, right?

And some people may feel is creepy too, but you would opt in because it's to help you achieve your own goals. In addition, changing medicine in terms of the way we define health and disease or wellness and, and illness is that, you know, right now so many of our measures are artifacts of the way we measure them. I mean, what we have available. So why is depression, what we call depression, that's something that occurs over the prior 2 weeks, right? What have you, have you felt these symptoms over the prior 2 weeks? Have you lost interest in things that drive you? Have you slept too much or not enough? And all these things over the past 2 weeks. Well, that's because that's about what you can do when you interview someone. You have to say, what have you done over the 2 weeks? When you're actually observing someone every 5 seconds, you can look at how their mood is going like this, up and down, second to second, minute to minute, hour to hour. Why is our concept of depression something that occurs over longer periods of time? Why isn't it something we would call it? You'd call it something else, I guess. And maybe that's what puts you at risk, that fluctuations and that pattern of fluctuations that puts you at risk for things happening.

So you could have like an objective measure.

Just be a different way of redefining some of these things and a different timescale. So that's where Professor Rahm comes in, in terms of the idea of studying time, studying changes over time, is that the timeframe in which you study something affects your interpretation of it. And we've seen that in many different cases that you classify people differently, whether you're looking at changes on a minute-to-minute basis whether you're taking, looking at changes on the day-to-day variation, or whether you're looking at changes on the week-to-week or every 2-week variation, you come up with very different conclusions about people based upon those. Over 2 weeks, what's your average or what's your variation over that period of time is much different than what's your variation from minute to minute.

I want to talk to him too. This is fascinating. What do you think about augmented reality? That's going to change everything, right?

It's another tool that could, yeah. I mean, that would make for some of these, I think the principles are not going to change, but it could help. I see a lot of these technologies as tools to help us with our interventions. You know, I've been doing apps and we used to do PC interventions. We were doing computer-based interventions when people were networked. I did some of the early clinical trials of network intervention where people had to go to a computer center to get on a computer and use it. Because that's how long ago it was. And so, but as the technology improves and as, you know, our abilities to communicate in different ways improve. So augmented reality, yeah, you can bring much more information to bear into that. There's a stealth intervention is Pokémon Go, right?

Was a stealth intervention. Yeah, and say they're not going to be sitting anymore because if it's on your face and you're interacting with reality with it, then we won't be stuck, you know, in our screens like we've been sitting here for an hour.

Yeah, we'll, we'll see which one of these sticks.

Do you get to go visit the innovation labs there at Stanford?

It's one of the exciting things about being at Stanford and in the Bay Area is that, that everybody is, is so excited about innovation and doing something new. Not everybody, but there's an ecosystem that's unlike anywhere else I've ever been. And you meet people and there, there's a non-zero chance that they're they're starting a new startup, you know.

Do you have any tips for parents, educators, students, anything you want to close out with?

Hmm.

Well, on the screen theme, which I think is where we sort of ended, I would say, well, actually it's for everything. The general tip I would say is that for parents in particular is that you're the most important model for your kids. You can't just say what you want them to do. You have to actually model it for them. You have to do it. Set a good example. And so if you want your kids to spend less time on their screens or be exposed to less content, certain types of content, then you need to model that into that too. If you don't want them having their phones in their bedroom and being up night— up all night. And I can tell you, because we have the data that shows— we have the direct data that shows that a lot of kids are up all night scrolling on TikTok, you know, even with school the next morning. And they're doing the same thing in school sometimes.

I thought you were going to say the parents are doing it too.

We do have some parents who do that as well, but if you don't want your kids to do it, you have to stop doing it. And so these strategies like not letting phones go into the bedroom, if you want that to be the case for your kids— now it doesn't— not every rule has to be the same for adults or kids, but it's a lot easier to make that rule if everybody in the family does the same thing. And if you're not using your screens at the dinner table, you know, if you put them down and you're not using your screens during family time or on vacations or other things. And so That's why I'd say would be most important in terms of that is that for parents to make your life easier is that know that your kids are going to copy what you do as well. Also, if you try and force them to do something that you're not willing to do yourself or that you're not willing to enforce, then it's not going to work as well. So think about instead of always being a policeman, think about being a support. Help your child sort of achieve their goals. Talk with them about their goals, even if you're Helping to steer them towards those goals. And then you're the support mechanism. You help them succeed as opposed to you imposing everything upon them.

Teamwork and consistency. Okay, great. Thank you so much, Tom. Really appreciated this conversation. This is amazing work you're doing. And I want to thank you again for the public health impact that you've had over your career and I can't wait to see what you're going to do next.

Well, my pleasure. Thanks for giving me the opportunity to talk about this stuff. As you can tell, I really enjoy what I do and enjoy talking about it.

I'm having my passion moment also doing preventative medicine. Thank you. Thank you.

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