The CORRECT way to read a scientific abstract

We have a very fun workshop planned. So an overview of how this presentation will work. We'll have an introduction to who we are. We'll go through just a quick example of a journal article and how the news represented it so that you can see why this is so important. And then we'll have an introduction to a process you can use to read and understand a scientific abstract. And then we'll do some practice. This will be very interactive, so you're encouraged to jump in. And then we'll have some practical takeaways at the end and a question and answer session. So I'll start by introducing Dr. Marshall Hagins. Dr. Hagins' first career was actually as a professional dancer on Broadway. He left dance ultimately to pursue a PhD in biomechanics from New York University. And a second doctorate from the University of St. Augustine in manual physical therapy. He's an emeritus professor in the Department of Physical Therapy at Long Island University and a senior clinical research associate at the Harkness Center for Dance Injuries in Manhattan. He's worked with members of the New York City Ballet, the American Ballet Theatre, Merce Cunningham Dance Company, among others. And he has been the company physical ther— Or Mark Morris Dance Group for over 25 years. He's published over 40 papers in the areas of dance medicine, ergonomics, and yoga, and he currently has funding from the NIH to study the effects of yoga on hypertension. And next I will introduce Dr., or Eddie Stern, who is getting his master's. I want to call him doctor because he knows so much. We call it an honorary doctorate. So Eddie Stern is a yoga instructor, author, and lecturer from New York City who has been actively involved in many facets of yoga education for over 30 years, including the running of his school, Ashtanga Yoga New York, since 1995, which closed but is now at Broome Street Ganesh Temple. In New York City, he has been committed to programs that have shown to reduce gun violence and the traumatic effect of gun violence on affected communities through yoga, meditation, and therapeutic wellness interventions. And he's authored many curricula and led trainings in wellness practices for public education that have reached over 80,000 school children and educators across many states. Since 2010, he has written yoga protocols that have been used in research studies examining the efficacies of asana-based practices. And he is the co-board chair of Life Camp for the Reduction of Gun Violence in New York City. An advisory board member for the Black Yoga Teachers Alliance, creator of the Breathing app, which is amazing. I recommend it to so many patients, as well as the Yoga 365 app, co-author of Engineering Health, an online yoga and physiology course with NYU Tandon School of Engineering, and so many contributions, and a co-publisher of Namarupa Magazine. And he currently gives frequently talks with Dr. Deepak Chopra on the inner meanings of yoga and how it is a practice for enlightenment. If you'd like to learn more about Eddie, he has a book, One Simple Thing, which I highly recommend. And I'll introduce myself. I'm Jonathan. I'm a resident physician in neurology in New York City, which means that I'm a medical doctor that treats disorders like stroke, seizure, multiple sclerosis, Parkinson's, and neuropathy. And I'm also a longtime yoga student of Sri Dharma Mitra. And this conference for me is a way to bring together 2 of my biggest interests. So I'm very honored to be here with all of you. So we will now get started. Eddy, you can take it away.

Okay, great. So thanks everybody for joining. And Jonathan, thank you for inviting Marshall and myself to be here with you today. We will be talking about how to read a scientific study or an abstract of a scientific study. Quite often what we see in the media in reporting of scientific findings does not accurately represent what the studies were about. So we have here a sample study that is from scientific journal, the Journal of Internal Medicine, The Influence of Anti-Inflammatory Diet and Smoking on Mortality and Survival in Men and Women: 2 Prospective Cohort Studies. And what the press said about this was, wine and chocolate can help you live longer. Study. So obviously those 2 headlines are egregiously different. If we could go to the next slide, please. Separate study in August found that consuming 3 bars of chocolate every month could cut your risk for heart failure by 13%. Now, as enticing as that is, I tried it and all I did was gain weight. And the study headline for this one was, an influence of anti-inflammatory diet and smoking on mortality and survival in men and women, 2 prospective cohort studies. So the conclusion here, as you can read, was adherence to a diet with high anti-inflammatory potential may reduce all-cause and cancer mortality and prolong survival time, especially among smokers. So how did we get from this scientific original article and research findings to A headline that says eating 3 bars of chocolate a month can help reduce cancer and mortality rates. So that's what we're going to look at today. And I will now turn it over to our next esteemed speaker.

So we're going to go over now some background information to understand how to read a scientific abstract. And to start with this, I want to go over levels of evidence. Which really means, how do you know how trustworthy information is? So for example, let's say you go to the doctor, you're told you have high blood pressure, and you tell some of your friends, I was just diagnosed with high blood pressure, and someone tells you, I've heard that if you eat a lot of garlic, your blood pressure will go down. Can you trust that information? It's really important to know, is this information I can trust? And what we call that level of evidence, it's actually not even on this chart. It's anecdotal evidence. This is what someone else has experienced, and it's really just a limited sample of information. Obviously, there are many confounds when the effect is experienced by one person. And so what you begin to try to do as you increase the level of evidence and increase the level of validity. Is control for a lot of these compounds. So the first level above anecdotal evidence is expert opinion. So let's say you went to someone who specialized in high blood pressure and they have seen thousands of people, and while they haven't conducted many studies, they may have seen that garlic actually works for people with high blood pressure. And obviously this still isn't perfect, but it is an improvement than over just hearing one friend who had this benefit. But going further still, someone could do a case report where they look at one or maybe a few people, write it up and show all of the variables that may have contributed. So maybe this person who started taking garlic supplements actually also started exercising and also started eating better, or maybe eating the garlic supplements Prevented them from eating foods that actually were contributing to their high blood pressure. So someone who writes up a case report could think about all of these contributions and in a non-mathematical way analyze qualitatively what's going on, meaning just think about the contribution of each of them. And what case reports really do is set you up to then do further studies. And this is now going higher on the level of evidence scale. And the next one you could do is a case-control study. And what you do here is you look backwards. So you find people who have high blood pressure and see if they took garlic supplements. And what you're looking for is, did the people who take, who took garlic supplements have less high blood pressure later on? But this obviously doesn't control for all those outside things like Did they change their diet? Did they exercise more? Did they reduce their salt intake? So what you could do next is a cohort study where instead of looking backwards, you look forwards. So you find people with high blood pressure and you put them on garlic supplements and you monitor what happens to them over time. If you wanted to take that even further, you could now add a control group. People who are taking supplements, but they're fake. They're called placebo. So you compare the people who took garlic supplements to the people who took a placebo, which does not contain anything, but obviously has the pill and makes you think you're taking something. And that would be a randomized controlled trial where you sort people randomly into these 2 groups and see the comparison between them. And this is a very good level of evidence. It allows you to isolate One thing at a time. So did the garlic pills work, right? Because the 2 groups should be similar, otherwise should have the same education about whether they're changing their diet, changing their exercise. And then the only thing that's different between them is the garlic. And this is what allows you to understand, was the garlic actually making a difference here? And then going even further, a higher level of evidence. Is where you could look at multiple other studies. So let's say there are 3 randomized controlled trials that have been published before, 4 cohort studies, and 5 case controls. You can now put all of them together into a systematic review, and this is where people describe the effects of multiple studies and try to synthesize them into one conclusion. And if you wanted to make it mathematical and go even further, the single highest level of evidence is a meta-analysis. Which Dr. Khalsa mentioned in his prior talk. And what a meta-analysis is, instead of just describing the synthesis of all of these studies, you actually combine them mathematically. So you take all of the data and put it together and do one analysis to show, was this intervention effective for this outcome or not? And so this is a framework for you to think about how valid is the data that I'm looking at. How, what kind of study was it? And how strong is that type of study? Recognizing that the lower ones are more susceptible to bias and confounds. Okay. And if you have questions, please don't hesitate to write them in the chat as we're going and we'll be able to answer them at the end.

Okay. I'm up.

Yes, you're up.

Okay. What Jonathan just laid out, we're going to go into a little more detail or more detail, a way of saying. When you look at an abstract, how do you actually determine what level of evidence it is? And the pieces that you see in front of you, your population, intervention, comparison, and outcome. By the way, a really nice thing is to think PICO, an acronym, if you want to put that in your heads. PICO, those are 4 good things to look at and think about when you're looking at an abstract. Another cheap trick when you first look at an abstract, I'm presuming that most of you are not scientists and haven't looked at a lot of abstracts. That's what we're doing here. But a cheap trick is that usually the title or somewhere in the abstract, it will tell you, was it a case series? Was it a controlled trial? Was it randomized? Is it a meta-analysis? So typically it will tell you what the authors have characterized the level of evidence. But what we're going to do right now is go through some of these things and talk about how a study earns its level of evidence. Evidence. This chart is fantastic. It might be a little more than we're going to chew off today and some, so all the details, but I'm going to, I'm going to do the highlights for you and what I think is most important. Let's think about population first. Science has lots of jargon and unless you've studied it, sometimes the jargon, just when you start to try to absorb the information, you get lost in the jargon. So let's talk about what population is. Population, the identity or the thing that you want to study. Let's say that you want to study the ocean as an example, a metaphor for what we're going to talk about. You want to study the ocean and you're going to go and you're going to take out teaspoons out of the ocean. You're going to put the liquid in those teaspoons under a microscope, and you're going to examine that. And at the end of that, you're going to say, I know something about the ocean because I have taken samples from the population of the ocean. So in this case, the ocean is the population that you're trying to say something about at the end of the day. So for example, we'll talk about high blood pressure a lot here, I suspect, as an example, because it's such a clear example. If you wanted to do a study on high blood pressure, your population would be people with high blood pressure, and you would go out and recruit people to your study that have high blood pressure, and that would be your sample. The underlying idea in science is the people that you study represent the population. The teaspoon of water represents the ocean. And that gets us to this idea of generalizability. When you do a scientific study, the people you actually study, the sample, is generalizable to the population because you believe that it represents the actual population. So in terms of quality of the study and what to trust when you're looking at an abstract, the first thing, and I think one of the most important things, is how many people are in the study. You can have studies on mice, you can have studies on cells, and you can have studies on other kinds of populations. And we'll even see, we're going to do a paper here in this talk today where the population is actually other studies. But generally speaking, when you're looking at yoga studies, the population will be people because that's Who— it's hard to get mice to do yoga. So the population will be people. And one of the most important things you want to look at is how many people were in the study. And the answer is more is better. More people is always better. So if you have 5 people in a yoga study, you've essentially done— you could think of it as you've done 5 experiments. If you have 100 people in a yoga study, you've essentially done 100 experiments. And the rule in science is the more experiments, the better. The more experiments you do, the closer to the truth you get. So when you look at a study, fewer people, not so good. And typically most yoga studies will have— good ones will have at least 25 to 50. And if you can get hundreds of people, that's even better. So when you look at this abstract, you're thinking population, you're thinking how many people in the study. There's an idea that you'll see in the third column, third row there. Is the sample diverse enough? They're trying to answer the question. When you look at that, does the teaspoon represent the ocean? So if you took your teaspoons off the coast of Texas, they might have some oil in them. And then if you relied on that sample alone, you would think, oh, the ocean is full of oil because the teaspoons were not representative. They were not diverse enough to represent the population. If you did a yoga study on flexibility, does yoga affect flexibility? And you went out and you gathered the only people who, because you had friends who were dancers. You only gather dancers. And guess what? Dancers are already very flexible. So your study would prove that yoga doesn't improve flexibility very much because they were already flexible. So your sample would not have reflected the true diversity of the population, which is people. So big take-home message, how many people in the study and is the sample diverse enough? So moving on to intervention, the big take-home here is what are they calling yoga? Most people, there's no one who's telling us in a definitive way what yoga is. And that's the same problem for scientists. Is it breathing? Is it physical exertion? Is it meditation? Is it a spiritual component? And lots of other things which may be included on the rubric of yoga. So one of the things you want to look for in this abstract is what are they calling yoga? I've seen a lot of studies where they would only give breathing. They would do an expanded exhalation and they would say, oh, yoga. is great for X, Y, and Z for calming the nervous system or whatever, but they haven't really done all of yoga. And so that's, that's a disservice to yoga many times. It's hard to study yoga. It's hard to study things which have multiple modalities. And that's true for all of science. But one of the things you want to look for, how many people in the study, is the sample diverse? And you want to say, what are they calling yoga and how many practices, maybe the lineage. How often they practiced, how long, et cetera. A lot of this information you will not get in the abstract. Admittedly, you might have to go read the study, but it is something that's important you should look at. Let's go to comparison group. So the first thing, a comparison group means you have yoga, which is your primary intervention. And then you have this other thing, which is a comparison group. What are you going to compare the yoga to? The first thing to determine is, is there a comparison group? So many times in yoga studies, They'll just take 50 people and they'll give them yoga and they'll say, and they'll measure the people before, they'll measure the people after and say, there was a change. Look, yoga did this for these people. The problem of not having, if it's the case that there's no comparison group, the problem of not having a comparison group is that you don't know if those people would've changed just because of time or some other factors. So it is better to have a comparison group. Than not. That's the first rule. The second thing to think about is you'll see a lot of yoga studies where they'll compare yoga, they'll say with blood pressure, and they'll give yoga to a group of people with blood pressure and they won't give— and they'll have 2 groups, but the comparison group will be standard and usual care. So this is jargon for meaning we didn't do anything to these people. We just watched them. Standard and usual care. So you can imagine that it's much easier to prove that yoga does something compared to doing nothing, as opposed to comparing yoga to something that is known to benefit.

It's—

so having a comparison group is better than not having one. Standard and usual care is common and it's meaningful. But I would argue that another way to think about this is when you see a yoga study that compares with a comparison group. That is active, when it's the comparison group is actually doing something that is known to affect the outcome. For example, when Eddie and I did our study in high blood pressure, we compared people receiving yoga to people receiving physical exercise. And that physical exercise was matched in physical intensity to yoga. So at the end of the study, we showed that yoga improved blood pressure better than people who did physical exercise. That is to say, we could say this wasn't just the physical exercise folks. It was something else that yoga was adding. It was breathing, it was meditation, et cetera. So having a comparison group is good. Having one that's not standard usual care, but is active is even a little better. So that's what you want to look for there. And finally, in terms of outcome, outcome just means what do they think the yoga would do? What is it they're measuring to see that yoga changes? Is it blood pressure? Do they, do they believe that yoga is going to make people more serene or happier, or is it going to change their hormone level or help them sleep? Whatever that change is, that is the outcome. And you could easily get into the weeds, and scientists argue about this. What is the best way to measure a certain outcome? But I do think when you're looking at an abstract, one of the things you want to say is, what do the researchers think the study is going to change? And that is the outcome. And how did they measure that? Typically, the conclusion of the study will say something like, yoga changed X outcome or Y outcome. So that's what you're looking for in the conclusion. The big take-home message here is that all studies are not the same. Some are in fact better than others. And the ways that you can tell if they're better than others is the degree to which they have a big number of people that they're studying, whether they have an intervention that's well-described. Whether they have comparison groups and whether they're measuring something that's really important. One thing I didn't mention, I won't go into here, is randomization. Randomization is a good thing. Whenever you see that in a study, it means that the study has more validity. It's probably more true. So those are the things that I think are important for the study.

All right. So now we're going to practice finding abstracts. And we've already heard of these 2 resources, pubmed.gov. And Google Scholar. So I'm going to show you how I like to go through these, and I'm going to do this live with your suggestions. So start brainstorming what you think would be a good search to look up that you're interested in. And I'm going to share this with you. So put in the chat. Any, any ideas you have of things you would want to look up about yoga?

Yoga and chocolate.

Let's start with that one. All right. So thankfully it's good to know that there is no study on yoga and chocolate. Someone suggested yoga and self-regulation. So there are 120 results, and at this point you may want to filter them or understand what's going on. And I think for me, what I like to do is filter by date is the most helpful. So I'll do something like the last 5 years, just because those are going to be more up to date. And then I can see a lot of interesting papers. So let's say I wanted to start with this one. And they give us the abstract, but in order to see the full paper, it's sometimes difficult and very often you won't be able to. As Dr. Khalsa mentioned, you could email the researcher and try to get it, but I also like to try Google Scholar sometimes. So if you paste the title into Google Scholar and find it and then click HTML, you can often find the full paper, which thankfully I was worried it wasn't going to work live, but it worked for this example. So you can now read the full paper if you would like to. During this session, we're gonna focus on reading the abstract because that is what you're going to have the most access to. We could try one more example, I think, just for fun. So we have yoga and grief. It's a very interesting one. So there are 8 results. This is post-traumatic stress after stillbirth. It's a feasibility trial, so maybe Not as much data in there. This one is about physical activity in general, not yoga. And this one is also after stillbirth.

Yeah.

So a lot of these are pilots or feasibility studies, but it would still be interesting to take a look at them. And again, you could go to Google Scholar and try to find the full paper. So that's an overview of how to Find abstracts, and now we're going to get to practice a little. So we're going to start with a sample study and just take a look at the news article, but then go through the abstract together. And we're going to ask for you to call out specific parts of the abstract. All right.

And Jonathan may add in one quick little thing here: part of the also purpose of Marshall's introduction to what comprises a scientific. Scientific study, for those who are not familiar with them, is to show how complex and complicated it is to do a study and how truly results will vary depending on the kind of population that you're drawing from, what you're trying to measure, et cetera. And to move from that level of complexity to the level of simplicity that we often see in modern media is the misrepresentation of the depth of research and how complicated it really is. And so what we're basically going to show you here is that when you go into— and this article here, Yoga May Be Good for the Brain in the New York Times, is an example of some good reporting on scientific research. But how that when you see something in the media that says yoga or meditation is good for X, Y, and Z, that you don't have to take that completely at face value just because you read the headline. But when you go into the news article, You can see where did this study come from, and if they don't have a direct link, you can pull that from the article, put it into PubMed, put it into Google Scholar, put it into a Google search, see what comes up, and then you can read the actual study for yourself and see if it's been accurately reflected in the news story that you were reading. And so that's the process that we're going to go through with you right now.

Yes, that was excellent. So this paper, Changes in Neural Connectivity and Memory Following a Yoga Intervention for Older Adults, a Pilot Study. And as Eddie mentioned, the New York Times reported yoga may be good for the brain. So we'll see if we agree with that headline conclusion. So this is the abstract. Pulled from PubMed. And what we're going to do is highlight different parts of the abstract in different colors. So if you look on the top left, red is going to be anything that has to do with the population. Orange is going to be anything that has to do with the intervention. Blue, the comparison, and green, the outcome. So I'm going to give everyone Unmute abilities, and you can shout out when you hear, when you read this abstract, any part that has to do with population, just shout it out and I'll highlight it. So we're focusing on population now. Any parts that stand out for population?

It says there was 55 participants. No, participants were over 55 years old.

And I think another key part of this statement is that they had MCI, which is mild cognitive impairment. They define it up here. So that's, that was the inclusion criteria, right? Who were these people? They were older participants with mild cognitive impairment.

Also in results, it says that 14 total, 11 LT participants completed the study.

Perfect. So we had 14 people in the intervention group and 11 in the comparison group. Anything else to do with population? I don't think so. I think that was it.

It doesn't say they were randomized to the groups, right?

Yes, it does say they were randomized. I was thinking of that as intervention, but I'll put a little red dot there. Of course, these categories overlap a bit. So why don't we move on to intervention now? So as you pointed out, randomized, they received a yoga intervention. Take it away for the rest.

Well, memory enhancement training for 12 weeks is the rest.

So I think 12 weeks is also part of the intervention, but I would actually call the memory enhancement training, this gold standard control, is actually the comparison. That's what we're comparing yoga to.

And the thing about this study that's great is they're comparing it to something that's already known to work in the field. So there, if it's, if you're thinking of this as a competition between yoga and something else, there's a good strong challenger here. If yoga does as well at or better than this, That would be a very strong statement to say about yogurt.

Exactly. People call that non-inferiority when something performs as well as the gold standard. Anything else to do with comparison? I don't think so. I think that was all for it. So it's amazing how in the abstract, all of the details that are outlined in the paper for the population, the intervention, and the comparison are boiled down to these very short Statements. So now we can go over the outcomes in green. Shout them out.

Verbal memory performance.

Great. Where do you see that?

In the results.

Good.

It looks like they measured improvements in depression and visuospatial memory.

Perfect.

Second line. It doesn't actually say what they measured, if it was a physiological measure or a Self-reported measure.

Very good.

That question, that's exactly right. That's where you get into the weeds on this kind of thing. There's what they're telling you they measured, but the real question is, how is that important to people's lives? Like, how does that impact their lives? Like, how do we know that visuospatial memory, how important is that? What does it do? How is it measured? But those are all great questions. And if you read the actual study, you can dig a little deeper in that, but that's That's, that's a great point.

We were going over this paper and this abstract earlier this week, and we were saying how this abstract really doesn't do the paper justice because there are so many details in the paper that aren't represented here.

And then there was one other thing that we discussed too, that Marcia was pointing out too, that if you look at the results of this study, the significant improvement in depression in visuospatial memory, improved verbal memory performance. Increased connectivity. All these things sound very positive. And then you get to the conclusion and it says yoga may be as effective as MET in improving functional connectivity. So we've read all these positive things and now we look at the conclusion, which is, eh, maybe it's gonna be as effective. So it's almost like the conclusion is a slight letdown from the positive or the positivity of the result.

And the, what, and the reason for that in this particular study is it is what Jonathan mentioned. about non-inferiority. Basically, they're not saying the yoga group distributed a statistically significant improvement in depression and visual spatial memory compared to MET, right? They didn't say that. What they said is the yoga helped people and it helped people as much as the gold standard. But when you read that first part, you think, oh, yoga beat MET, or it's really fantastic. But really, when the conclusion is actually more accurate, the conclusion is valid. It takes the exact right angle of take into what the study's finding was. Yoga may be as effective as this other thing, which is actually fantastic because that's the gold standard. And we know that yoga has, does very little harm to anybody. So it's a good thing to find.

Yeah. And that this idea of non-inferiority you'll find is very prevalent when it comes to yoga studies and lots of different medical sciences, pretty much all of them. That if we can, the idea is not to show as yoga researchers that yoga is better than everything, but that it's no worse than any of the other standard interventions. And that means you have a choice, that the choice between maybe given a statin drug and doing yoga might help you in some cases just as much. So now we have more choices in treatment protocols, and in certain cases, yoga might be a safer intervention if you're not taking a drug, for example, that could have other side effects. And Molly—

I'll just—

Yeah, go ahead. I was just gonna say Molly's bringing up a great point that they might also be using the language maybe because this is a pilot study with a small sample size. So they, they then follow up in their second sentence of the conclusion that these findings should be confirmed in larger prospective studies. Awesome. And prospective, just so you guys know, is when we were talking before about forward-looking studies versus backward-looking studies. Forward-looking studies are prospective, backward-looking studies are retrospective.

And I just wanted to throw in, despite what Eddie said being true, that it's great that yoga is the equivalent. I would say also there's nothing wrong with proving that yoga is better than other things.

And I think in this one, they very interesting. So they don't outline this in the results, but in the paper they showed clearly that on many measures of memory performance that yoga and MET performed Equivalently. So again, non-inferiority, but then there were specific areas where yoga outperformed MET, specifically in depression and visuospatial memory.

Oh, Jonathan, could you describe MET for us?

Yeah. Yeah. So it's a memory enhancement training. I'm definitely not an expert at it, but it is an occupational therapy intervention that is designed to develop coping strategies and ways around any memory deficits. So patients who are experiencing mild cognitive impairment or mild dementia are able to have an improved quality of life and work around their deficits.

Thank you. Sounds like a combination of those 2 things would be pretty good also. Probably.

Ben, you say something also about proving and disproving in science, because I think a lay reader might not realize that you don't actually ever Prove the intervention, that you just proved the null hypothesis. Just wearing my hat from 30 years ago at university.

Yeah, this is very subtle. I have a professor who has this great line that science proceeds by destruction. And what you do is you have to come up with a theory, an explanation of how something works and the relationship between variables, and then you try to prove it wrong. And if you try for a very long time and you can't prove it wrong, Then maybe it's right. But when I think a really good summary of all of the scientific work that's done is that in the end, everything is a simplification. So all models are wrong, but some are useful, right? So it may not be that for everyone, yoga is better than memory enhancement training, but having this data on a population level is very helpful because it helps us know who to recommend it for and that we can recommend it with confidence.

Well, and as you know, sorry, and as the studies accumulate, of course, the evidence becomes stronger, which is the point that you're making with review articles and meta-analyses. Like in the '60s, they thought smoking was wrong. By the end of the '60s, they knew it was pretty, pretty positive that it was having a huge impact on our health or whatever that time window is. So. As the studies rolled in, we got more and more evidence. And so now you could probably say that the two are definitely linked, but it's because of all of that research, which is what we need to do in yoga.

Exactly. All right. Shall we move on to the next study, which is a little more challenging?

All right.

So this one, Yoga Effects on Brain Health: A Systematic Review of the Current Literature. And this one is by Dr. Goteg, who presented at the conference last year. And by the way, she just had her child and is on maternity leave, so everyone wish her well. And the news reporting of this, doing yoga just once or twice a week can boost brain performance. So let's go through the abstract and see if we agree with that. So again, red is population, orange intervention. Blue comparison, green outcome. And let's start with population. Just shout it out again. This one's harder, so I'll, I'll point it out.

The population was the 11 studies.

Yes, exactly. Love that. Yeah, that's very tricky.

Yeah. The study of a study.

It's a study of studies. Exactly. And that's why this is a systematic review, right? That was that second tier from the top.

Okay.

I don't think there's anything else describing the population here. Let's move on to the intervention.

Would that be the current knowledge of yoga or not?

Which line do you see that in?

The article aims to summarize the current knowledge of yoga practice and its documented positive effects. Would that be— no, that's not right. You know what?

It describes what yoga is, but it doesn't say that physical postures, rhythmic breathing, and meditation exercises were included in the 11 studies that They examined.

That is an excellent point. So I think this does go a step beyond the previous abstract in describing what yoga is, but they don't quantify that all of the 11 studies included these interventions. But I do think this is the intervention that they're describing.

Okay.

Anything else describing the intervention? I don't think so. We can go on to the comparison. This is really important.

I don't see a comparison, but the studies might have had groups, right?

Excellent. So the abstract does not report what comparisons were included, even a range saying 5 of the 11 studies were controlled. So we do not have that information from the abstract. Very good. And now the outcome.

A positive effect of the yoga practice on the structure and/or function of the hippocampus, amygdala, prefrontal cortex. Et cetera, et cetera.

Very good.

Pardon my highlighting.

Good.

And I'll add that as part of their conclusion, they include their conclusion as the last sentence here. They call this promising early evidence that behavioral interventions like yoga may hold promise to mitigate age-related and neurodegenerative declines, as many of the regions identified are known to demonstrate significant age-related atrophy.

Good.

Any other commentary on this abstract?

Just a question, and I'm sorry if you wanna wait till after, but who is it? The same authors of the study that writes the abstract, or is it written by someone else who studies the study?

It is the authors who write the abstract.

Interesting that they leave out good information.

They, they have limits imposed on them.

Gotcha.

Yeah.

Yep.

I also think what you're raising is a really interesting point because sometimes when you're writing an abstract, you know the study so well. That parts of it are obvious to you. You're like, of course that we had a control group, but you have to write it.

Absolutely. I don't write science papers, but I write other papers and the summary, you often leave really important things out because you're blind to them sometimes.

Yeah. All right. So we'll move on now to some practical takeaways. So you can take a picture of this slide, save it, but what we really were hoping you could get out of this. I think Dr. Higgins is going to explain.

I think hopefully what you got out of this is that when you, I think all of us, when we read science in the media, we're curious about what yoga does. We read something and we want it to be useful in our lives or useful for our students or something. Hopefully what I think the big takeaway here is that there are different levels of evidence. Number one. Number two, the media doesn't, cannot really honestly, even if they're trying very hard, often portray the complexity that's inherent in the research. So it does take, you have to be careful, buyer beware. Hopefully we've given you some ways to think about this. All science articles are not equal. So on this list here, first item is process. You get better at this the more you do it. And although science is full of jargon, and if you're not a science person, but you're curious, what I would suggest is that each time you look up an article, if there's a word you don't understand, just go to Wikipedia, look it up. And once you do this more and more, you'll see those words repeating over and over again. You'll begin to understand what's going on better. But it's a process and it's language and you have to kind of learn it if you want to understand this stuff. Level of evidence matters. And we know the systematic review or meta-analysis. On top of that, we go all the way down to anecdotal evidence. Many times that will be in the abstract explicitly, but you can evaluate— the next point, you can evaluate the abstract based on this PICO model that we've done. More people, active controls, randomization, detailed descriptions of interventions are always better. And beware of clickbait. So that's it.

Awesome. Does anyone have any questions? I know we're cutting close to the time limit, so we'll wrap up shortly, but we can take a couple of questions. And Marshall and Eddie, if either of you have something to go to at 11, it's okay to hop off.

Okay.

I'm just curious why the PICO doesn't have a category for the conclusion. So you wanna be able to draw your own conclusions? Is that why that model doesn't Have you looked specifically at the conclusion?

I think the outcome includes the conclusion to some extent, but I do think also it's very important to try to draw your own conclusion based on what you otherwise analyzed with PICO and especially compare it to the conclusions the paper has.

I think the value of the PICO is to try and determine the quality of the article as opposed to what it actually found. So most people, the conclusion actually look at to, to really see what it says about things, but As Jonathan just said, the, probably the most utilitarian thing about PICO would be, does the conclusion match what they did to find the answer? Is it valid?