How to Research for Wellness

How do you know if the health information you're reading is actually trustworthy?

In this episode of Wellness in Every Season, Autumn welcomes back Dr. Theresa Lyons, scientist, researcher, and founder of Navigating AWEtism, for a practical conversation about one of the most important wellness skills you can develop: learning how to evaluate health research for yourself.

After her daughter's autism diagnosis, Dr. Lyons discovered that the advice she received from professionals didn't always match what the scientific literature was showing. That experience changed the trajectory of her life and taught her how critical it is to distinguish between headlines, opinions, AI-generated summaries, and peer-reviewed research.

Whether you're researching autism, nutrition, chronic illness, supplements, or any other health topic, this episode will help you become a more confident and informed consumer of medical information.

In this conversation, you'll learn:

- Why headlines and mainstream articles don't always reflect the latest science
- How to recognize higher-quality health information
- When to use PubMed, Google Scholar, and AI—and when not to
- How to identify bias in both research and your own thinking
- What clinical trial phases actually mean
- Why study size, funding, and conflicts of interest matter
- How to read a research paper without feeling overwhelmed
- What systematic reviews and meta-analyses are—and why they're valuable
- Why asking better questions often leads to better health decisions
- How to partner with your healthcare providers while becoming a stronger advocate for yourself or your family

If you've ever felt overwhelmed by conflicting wellness advice online, frustrated by changing health recommendations, or unsure which sources to trust, this episode offers a practical framework for researching with greater confidence and clarity.

Connect with Dr. Theresa Lyons

🌐 Work with Dr. Lyons: https://awetism.co/work-together

🌐 Navigating AWEtism: https://navigatingawetism.com

📺 YouTube: https://www.youtube.com/@navigatingawetism

📱 Instagram: @navigating_awetism

Dr. Lyons translates complex scientific research into practical, understandable information, helping families make informed, evidence-based decisions while navigating autism and related health topics.

For more wellness tips and exclusive content, join my newsletter! Sign up now at https://wellness-in-every-season.kit.com/5-days-to-mastering-mornings-and-evenings receive a free 5-day guide called "Awaken and Unwind: 5 Days to Mastering Life's Mornings and Evenings." 

Transcript

SPEAKER_02 0:00

I have Dr. Teresa Lyon with me again. She was in episode one that she was talking about autism and how you can grow out of it. And the reason why I had her come back on is I want her to teach us how to break it. Welcome to Wellness in Every Season. We talk all things wellness to help you align yourself, align with your goals, get find balance in your life, and just recalibrate yourself. If you are listening for the first time, welcome, welcome. I'm so glad you're here. And let's get started in the rest of the podcast. And I want you, Dr. Lyon, to share with us really quick a snapshot of why this mattered using that reporter story again. Because it's so common, and we live in an age of AI where we're just gonna use that without double checking our sources. So tell us what happened and why it mattered.

SPEAKER_00 1:09

I'll give the short version of the story. So I have a PhD in computational chemistry from Yale University. I'm a chemist through and through. I also have two masters in chemistry, one in organic synthesis, where for my thesis I created a new chemical reaction, and the other master's is general chemistry. My bachelor's was also chemistry, too. So in no chemistry, I worked in the pharmaceutical industry. And when my daughter was diagnosed with autism, I asked the doctors, okay, what do we do? And there was like no options whatsoever. They're like, pretty much gets worse, now better. There's medications, but that's really just to treat irritability. And you can do some behavioral stuff, but that there's long wait lists and mixed results. So I went to PubMed and did the research. I want quality information. I'm a scientist, I know where to get it. That's PubMed, the actual research publications. So I went there and read one study that showed about 10%, and this was about 13 years ago, that 10% of kids with autism lost their diagnosis, and they were calling that an optimal outcome. So this is contrary to anything any doctor in person had told me. So they told me it gets worse, not better. 10% is worth understanding. Wait, 10%? What is that 10% doing? Like I need to understand that. So that was the research, the quality information that I had. Throughout this, I'm researching everywhere. And I read two articles on Yahoo talking about how autism is lifelong and there's nothing you can do. And so, as a parent, at the beginning of this journey, I'm like, this journalist is saying that it's lifelong. I have one publication that says it's 10% can lose the diagnosis. What what a so torn? And so I researched the journalist, found him, tracked him down, emailed him, and he explained to me that he researched both those articles that were published on Yahoo. This is mainstream, and this is back in the day when Yahoo was like the place to go. And so he's like, I put in like two hours of research for those articles and just turned them. And I thought, goodness, two completely different things. Right. So at that moment, I remembered shutting down my laptop and going for a walk and being like, whoa, I almost trusted mainstream media more than my academic background of being a chemist and how I built my career. And I really told myself, you have to be careful with where you get information. You can't let someone's it was really an opinion, it was just regurgitation of what had been out there in mainstream. So it's really important to get quality information. And I know how hard it is. I was so torn. I'm like, this is Yahoo. This is two articles, and they're just published. Why is he not mentioning anything about optimal outcomes? And it's because he didn't research it. He didn't care. He just had to put two articles out. So it's really important for parents of kids with autism or anyone researching anything health related. You really have to have this critical lens of what is this information? Where did it come from? What's the quality of it? And really dive into it. Now, yes, I have a background in being able to do that. I did that in academia and in the pharmaceutical industry. So today we can go through it and walk through how do we think about things so that we make decisions based on quality information and not just regurgitation of information. Yeah, I am very excited for this. Like my daughter's life would have been completely different if I had listened to mainstream information. My life would be different, and not for the better. Her life, her future, just everything would not be what it is today if I followed misinformation. That's really the truth of it.

SPEAKER_02 5:22

And that's the same for anybody saying that.

unknown 5:25

Yeah.

SPEAKER_01 5:27

Especially because we'll look at nutrition for a second.

SPEAKER_02 5:33

Growing up, I go to my grandmother's house and everything tastes like cardboard or sugar on top. Because it the no-carb diet was the way to go. And then it was no sugar, and then it was protein rich. And if we follow whatever trending, it negatively impacts our health. And it can be very expensive too. Whatever the crisis is. Or thinking of negatively impacting health.

SPEAKER_00 6:07

Not even having that hope. If I listen to my doctors and the specialists, they did not talk about this data. Whether they knew it or not, maybe they didn't want to get my hopes up. I was not given the accurate information in order for me to make good decisions. I was regurgitated information. It was not cutting edge, it was not truthful, and could have negatively impacted us. There were so many points where I had to have that confidence in myself, which was extremely hard. Like I was shook for a few days after talking to this journalist and being like, wow, I almost made huge decisions based on some guy who did research for a few hours. It can be tiring and overwhelming. You have the diagnosis, the stress of all that, and then you have to figure out how do I make sense of this.

SPEAKER_02 7:02

Two questions the first is rhetorical. How many times have we spent two hours of research think that's good enough? When we're not focusing on what quality and the non-retorical question is, are we double checking our bias? How do we do that? Because you're hearing what everybody else is saying. Right. How do you prevent that echo chamber bias? Because if you're researching that way, you're gonna find research that proves you right.

SPEAKER_00 7:35

I've been trained to not have a bias. I do have a bias, but I'm aware of it. I have been trained to catch that and be careful of that. And it it is something I definitely think about, probably more than most people. When you're starting to do research, you don't want to find only things that agree with your viewpoint because you haven't gone far enough. That might just be surface. And that's if I was back in the day, if I had only searched on Yahoo on Google, I never would have found this information. And it was in part, like, yes, I know to go to PubMed because that is my training, right? But I also know when I read that article, I was like, okay, now I have something that is different than what I've been told. And when I was doing that research, it was more, I need to know what are my options. So I went in very neutral and then found this information and then found mainstream information that was just reconfirming more and more of the narrative. And that's where it got sticky, where it's like, okay, which way am I going? Now, to talk about bias a little bit, so I understand that, right? So I read that research article and I talked to journalists. Then I reached out to the author of that scientific article, had a phone call with her and wanted to know, okay, what did you see? What is possible? I really wanted to make that real. And then, because I'm a researcher, I started talking to different parents who had the same experience of their child no longer had autism. So I ended up doing about 40 interviews of those parents to really understand what did they do, what were the symptoms, because autism was entirely new to me. Autism is so different. I didn't fully understand that. I'm glad I was naive in that sense, because I might not have started. But having that additional data of 40 parents and speaking to them and asking them questions gave me more confidence in the data. And so that's also how I can counter my bias, right? Because I was more in that neutral zone because I am a researcher. And so that's why it was like, let me see what the data tells me. And then I had that understanding of okay, what I'm doing is cutting edge. This is not the standard approach that everyone is taking. So I have to be comfortable being in that area of risk, right? Where it's like, okay, 10%. Some parents would be like, 10%. That's impossible. That's too small. But that's also my mindset. I'm thinking 10%. Okay, that's something there. So this is all the things you have to think about when you come across information and you decide, okay, I'm going to follow that. That is the direction I'm going into. You really have to be comfortable because you'll get a lot of pushback because you're doing something different. So you have to be comfortable with that. And only now on the other side, where I'm like, oh yeah, okay, I really had to be comfortable with everyone telling me that's what are you doing? And I'm like, I have the science here. I spoke to 40 parents, right? So my comfort was in the data, but it was being challenged by different people's comments until then doctors started being like, Hey, what are you doing? And one of my daughter's specialists encouraged me to start navigating autism. She's like, You really need to educate others. I was not planning that, but I'm passionate about science, quality information, and how do you think about it. So that's how we are where we are.

SPEAKER_02 11:32

So we understand bias that our own thinking, that yes, up with our own hypothesis, and we're busy trying to prove that egos in it. You talked about PubMed, and if I remember correctly, that is one where it's free. Where there are other journals where you have to pay for them, is that correct?

SPEAKER_00 11:54

PubMed has most of the scientific journals. Some are free, some you have to pay per article. There's definitely different ways. I had academic credentials, and so for me, I could read any article full length, which was extremely helpful. But you can always read the abstract conclusion a lot of times. It depends on the journal, but you get at least a snippet of what the conclusion is.

SPEAKER_02 12:27

It can be good, but when you want to dive into it and you can't and you're locked out of it. I learned about Google Scholar, which is great. And if you're on different government websites, sometimes they have the unlocked article. I've learned that in the research class that I took and several other classes, that the amount of people who are in a study can matter as well. If it is cutting edge, and explain to us what cutting edge is. My husband uses this term at work, so I know what it is. But explain what that is and why sometimes it will be a smaller sample size in a study.

SPEAKER_00 13:04

The way research goes in health is you have three phases of clinical trials. A lot of times it's also done pre-clinical in cells, like in test tubes. It might be in different animal models. You're basically examining the mechanism of action when you're in animal models and cells, trying to establish this is why something is happening in our body when we do something. When you're looking at changes therapeutic-wise, you have preclinical, which is cells or animals, then you have phase one, which is to say that what we're doing is safe. You have a small sample size, maybe 10 patients, and you show that you're not killing anyone, you're not causing any really bad, harmful effects. Typically, this is done on healthy patients. It depends on the therapeutic area. Sometimes the patient enrollment is of that particular therapeutic area. Safety. That's really what is important. And then phase two is if things are safe, then you go to larger numbers and you start looking about okay, is this what kind of effect does it have on different goals? So it might be quality of life, it might be measured a certain way. You might be measuring a specific like blood marker. So some type of biomarker that you take in a blood test or urine test or some type of thing you can quantify. It also can be like oncology, they're looking at life, right? So how long did the patient live longer? So there's many different measurements, but in phase two, you're getting into maybe hundred-ish type patients. And then phase three is when you get more into you, you're hoping for like a thousand patients or more. Now, keep in mind it depends on your therapeutic area and the motivation for having these studies. And this is where in autism there's a challenge. So I was a medical strategist for the pharmaceutical industry. That is how I understand all the different phases and things like that. For the most part, pharmaceutical companies or supplement companies are paying for these clinical trials, which means they show that it works, and then now they can charge for whatever it is that they developed or showed that worked. So you have forever. But it takes forever, right? So you might have a clinical trial where you're collecting data for three months for that patient. It might take three months to recruit that patient. You're gonna find them and do the pretest and sign all the paperwork. But then three months before that, or for six months, you had to do institutional review boards and make sure that it's ethical what you're doing, right? So it takes time to keep in mind. But the motivation is we are doing this so that we can have a product that shows XYZ. So in autism, it is very difficult to find phase three clinical trials where you have thousands of patients with autism testing something because there's no pharmaceutical company out there that has something that actually targets the root cause of autism. So this is the other thing to keep in mind, right? So a lot of people say, Oh, I want evidence, I want to see 10,000 patients and have been enrolled. Okay, if you're doing that in autism and you don't have a company that's sponsoring it, what are you doing? Are you getting a university to do this? Phase three clinical trials are millions, tens of millions of dollars. So when you're looking at the data, you also want to analyze and say, is it feasible to have had 10,000 patients as a data point, right? In a phase three clinical trial? Where am I going to be comfortable and say, all right, this seems safe? This seems aligned with what I need, depending on what you're researching for. And then you make a decision that way. So this is all stuff that you want to be thinking about when you're trying to say, Am I cutting edge? Your cutting edge, if you're in any of that preclinical phase one, phase two, phase three. And even after there's an FDA approval for something, a lot of times doctors are like, let's let it ride for a couple of years before we say that we're confident in doing this. Right. So you have to be mindful of all of that. And your doctor might be super conservative and be like, I don't typically make recommendations or follow anything until five years post-FDA. Totally fine.

SPEAKER_02 17:47

That might align and might work for some parents or patients, but for others, like they don't want to risk their license of if something goes wrong, you sue them because we're gonna sue a happy society.

SPEAKER_00 18:00

It depends, right? This is where you want that partnership with the doctor. You shouldn't go into a doctor and just be like, okay, you don't like to do anything for five years post-fDA approval. Okay, so I'll just wait, especially when you're talking about a child's health, right? And you're analyzing the risks and the benefits, right? So if a child is five years old, they're in kindergarten. If you wait five years, they're 10, we're talking medal school. Exchange right exactly. So there's no right or wrong answer, but you want to think about it. How conservative do I want to be? It depends on the risk, right? So if there's not much downside, then you might want to have that conversation with that conservative doctor and say, all right, have you worked with other patients who have done this? Why are you not comfortable with this? And you might even come to the conclusion of this is not the right doctor for me, because I am not conservative like that when it comes to making this decision. You might be conservative in other areas, but when you're talking about a specific aspect of health, you might say, no, this data is something I'm comfortable with. And I want to work with a doctor who will work with me, right? And that doctor is usually medicine as a practice, right? And this is the other thing that most people don't realize. Doctors try different things because it is a practice, and they try and they see. We don't like to think about it like that because we just think the doctor has the answer. But there's very few answers. This is where you need to think critically and you need to have that partnership with the doctor where you can have that back and forth dialogue of discussing different things and weighing that risk and then doing something either with the doctor or finding a different doctor. And the reverse could be true too. You might be working with a doctor who is, let's say, publishing, we call them key opinion leaders. They might be the doctor who had done the clinical trials, right? So they're gonna have a totally different knowledge base to draw from because they're doing the research. So if you're someone who's like, yes, that makes sense for my child, I want to work with the doctor who did the clinical trial because think about the knowledge they have. So that's the doctor I want to work with because I want to be aggressive in this particular area. You don't have to be aggressive in everything, because maybe this one area is what makes sense for your child. So this it's not all doctors should be conservative or all doctors should be cutting edge. You have to analyze what it is that I want, what it makes sense for my child. And this takes a lot of work, right? This is like oh, I don't need this on top of everything that's going on in life. But unfortunately, this is the kind of thinking you have to do when there is a diagnosis and when you're building your healthcare team. So it's important to have all of this as as strategies.

SPEAKER_02 21:02

I know you already prepared the articles we're gonna go over, but I'm gonna put you on the spot for just a second. Can you show us where you would go to start the research? So I would probably start with Google Scholar. If I still was in school, I would use the research library. I could get some more stuff there.

SPEAKER_01 21:23

Can I share my screen?

SPEAKER_02 21:25

Looking through this, what advice would you have for somebody who is not used to reading research articles because that is a different language? Maybe somebody who's more used to reading the average population level is fourth grade level. So if you're reading at a lower level and these articles are written at a PhD level, what kind of advice would you have along the way? This is where I start. Love using NI8. But yeah, so good.

SPEAKER_00 22:03

PubMed is is usually where I start. If I get any idea, any thought, that's where I'm going. AI was not available when I was doing this initial research for my daughter. And you have to be really careful with AI. You can't just blindly trust it. So even now with AI, that is not the first place that I go. I go into public.

SPEAKER_02 22:27

The more I play with it. Because it will lead you the striction, and you'll have to be able to say, no, it's more here. And then it back. So that's why it depends.

SPEAKER_00 22:39

Yeah, yes, so it's like I find AI has a bias. I find my AI has more bias than I do. So the prompts I give it would be like, let's say it's autism. And I'll walk you through how I would do it for AI and how I would do it for PubMed. I would type in autism and do custom filters. So I'd be like, all right, I want the last five years. Because this is my initial sweep. Like if I'm like, okay, let me try and understand what autism is.

SPEAKER_02 23:09

So I would do it off with anything with over six years old. So five years makes sense.

SPEAKER_00 23:14

There are times where I will do historical analysis. Sometimes, let's say there was a phase two study, right? And I know that takes maybe three years. I'll go back on that search term for all of the years so that I can see how that progressed. I can look at what was done in animals, what was done in test tube or in vitra. There are times where I do want to see the historical data because it gives me the full picture of what's been found. There are times that I definitely will do all history. Okay, so text availability. I still keep this as I like, I like all of it. If you only want to see free full text, you can select this and you'll only get articles where you can click and it's free and you get the PDF.

SPEAKER_02 24:03

An abstract is like the clipboard of an abstract here for me is I could find keywords, and if they're basing this research off something else, then maybe I can find that, and that's a free version that I can read. It could be doing research, which is not cutting edge. I love the meta-analysis, which means they put together everybody else's research.

SPEAKER_00 24:28

So abstract is the summary, right? This is gonna give you what it was looking for. It gives you study size, right? It's giving you a decent amount of information. It'll give you usually the conclusions in the last sentence or two. So sometimes you look at the title and then actually we might have jumped the gun just a little bit. Okay, let me just go back to give the initial sweep so that everyone understands. So we're talking about whether or not you want to use free full text. I don't recommend selecting this because then you're starting to get a bias, right? Just because I can't read the full article doesn't mean I should discount it, right? Because now we're saying I'm only going to be seeing what is free. How do you get articles that are free, right? There's controversy into that, right? If you select only free full text, you're starting to introduce bias. So I would not do that. I would accept that I might only be able to read an abstract and be okay with that, at least on this initial suite. Now you're getting to article type. That's why I wanted to swing back because you started talking about analysis. So people can see, all right, I can select the meta-analysis if I want. To answer your question about if I did not have a PhD and I wanted to read research, but I didn't have a joy of reading all this dense stuff, right? I happen to enjoy that. I would select review, right? Which means that I'm going to get a nice summary of stuff, or I would do a systematic review. They're pretty similar. So this is really reviewing everything. It's probably going to talk about pre-clinical. It's really going to give me that historical explanation. So when you click on those as options, that's what you're going to get. And so, like, here's a free article, but also here's an article that is not free. When they're free, it says it here. And when you don't see anything there, it's not free, right? But you can still see the abstract of it. So if you want to start to get a quick read, this is how you would do it. Reviews. Now you're talking about meta-analysis. Meta-analysis is going to explore only data related to clinical trials and put all that information together and come up with one kind of universal conclusion. If I were to do a meta-analysis, I would probably change the publication date to the last year or two. I don't want a meta-analysis of data from five years ago. Give me a meta-analysis of the last year because this is more cutting-edge. Meta-analysis is really looking at clinical trials. So it's a little bit different than a review. I can let it be older because I'm trying to just get that general idea of what is the research telling me, what has been done. So for a meta-analysis, I usually have it much more recent so that I capture those recent trials. So that's like a slight difference.

SPEAKER_02 27:40

But what with another career path? I would have so much fun doing meta-analysis. I love meta-analysis.

SPEAKER_00 27:46

I would do all like you learn so much in here. A little side note, when I was doing all this research for my daughter, life was really stressful and really overwhelming. So the way I would make life fun is I would finally get my daughter down for sleep, and then I would pop popcorn, and I would sit in front of PubMed and be like, having fun. This is my socialness for the day, right? Everybody loves PubMed and popcorn. So not Netflix, but like this is what I did in the beginning to really understand all the different information. And I found joy in it, because this is what I had done for years. Okay, so that is PubMed, and that is what I would do in the beginning to get that initial, okay. Let me really understand what's going on. Any questions on that?

SPEAKER_02 28:42

I found interesting in one of the classes was looking at the names of the author. Sometimes you'll find the same, you'll get a good idea of like, okay, these people work in this field. But I was also taught to click on them because it gives like that brief bio, and you can find out are they somebody who has done work in this field? They're not a chiropractor that's suddenly talking about autism. I also want a researcher that's talking about it. That makes sense.

SPEAKER_00 29:18

Now you're getting into analysis, too.

unknown 29:21

Go ahead.

SPEAKER_00 29:22

So what you're getting into is analysis of each individual article now. So if we want, we can go there. Certainly, like the next thing to look at would be all right, what is the publication and what is the date? So, like, how relevant is it? Again, that's why you want to use that filter. And so then you look, the next thing is you look at the affiliations. This is important because you do value a publication from Harvard or Yale, because I mean Yeah. So you have no bias there. So I mean there are certain institutions that are deeply knowledgeable in certain aspects, right? So Harvard and Yale, they're not tops in everything, right? Many things, yes. So there is that analysis of who are the authors and where are they from? And sometimes that is part of a bias because a lot of times scientists from the US are generally valued more than other countries historically. That's the way it's been, but historically, you look for information in the US. So you're looking at, all right, these are universities, right? And so we have a university, University of Alabama. A lot of times I like to look, is this one research group, right? So is this a publication that basically is coming from one perspective, where they have a head researcher and grad students or postdocs or stuff like that? Or is this more kind of a collaborative project between a few universities? Because then in many ways, the idea has been vetted from different angles and different perspectives. So it's not saying one is better, but how do you trust this as information? You want to look at is this one person's opinion or is this two sites or three sites? That makes a difference. We happen to pick one that doesn't have no abstract, right? We can skip down and the conflict of interest. Every publication has it. A lot of times, professors don't have conflict of interest. However, some do, because some professors start different companies, right? Professors who have started different pharmaceutical companies, different diagnostic companies, right? So you do want to look at, all right, are they publishing this and benefiting from it? That doesn't automatically discount the publication. You can't be biased in the sense of, oh, they're gonna make money off it, right? Because we all know billion-dollar drugs that generate that billion dollars because they work. So you can't say that just because someone's gonna make money off it doesn't mean that this is not quality research. Because again, what is that engine that drives phase one, phase two, phase three? It's revenue. So you have to have some understanding that there's gonna be a financial interest of somebody eventually, otherwise, this research wouldn't be done. A lot of times that early preclinical research has no conflict of interest because those are the beginnings of the ideas, and then it's later down. But so it's certainly important to know that just because you'll see different pharmaceutical companies that are doing clinical trials, and you'll be like, ah, okay. It doesn't mean you discount the research that is done, but you have a different lens that court holds it up. That's when trial size becomes important, right? There's some supplement companies who do a small trial on like 10 people, so now that they can have a claim, right? I have a claim that this changes that. All right, you looked at 10 people, right? Okay, it's better because then nothing, because at least you believe in your product so much that you would invest money in doing a clinical trial. You had to have certain expertise, right? So that means you really believe in the product, so it definitely helps, but I wouldn't say that I would discount it entirely or blindly trust it. So this is where you're trying to analyze. So if you're thinking of it's like on a scale, it's like, all right, I'll put three blocks there and maybe one block, because you're gonna make money off it, right? But this is all the analysis that you're doing on articles.

SPEAKER_02 33:49

How do we read them?

SPEAKER_00 33:50

How do you read them? Okay, so let's say this was one of the articles that I had referenced in the previous episode. Really big one. This is quality. Yeah. So again, like we start at the top. We clicked on our article. This is persistence of autism spectrum disorder from early childhood to school age. All right, and we have uh a whole bunch of different authors, right? We have MD MPH, PhD. So I like to look at who are the people doing the research. So we looked first at the publication, that's a good publication. We have the title, so we kind of know oh, persistence. Oh, okay, interesting. I always thought autism is just autism, right? So the title itself is like, oh, okay, interesting. And so we look at the authors, and usually down on the bottom of the first page, affiliations. I'm looking at that first to accept my mind. You have Boston Children's Hospital. Okay, we got JAMA, we got Boston Children's Hospital. We're in that area, right? We're about as quality as can get. And so we have a quality journal, we have a well-respected uh university and hospital, and this is the corresponding author. Sometimes I look at that, like you had mentioned before. Is there someone who's publishing a lot on that? This is where you might be like, all right, what is this person and what have they published on before? So that's another jumping off point. I want to jump off that point right now because I try and get a good understanding of one article before I start going too wide. So you got to do a deep dive. And this is where you start to get into it. The importance. This article, this journal has this. I have the full publication here. So you're gonna obviously get more than just the abstract. I will say I think it's not bad. Don't look at how many pages because you're gonna set yourself up. There's probably at least two pages that are references, so don't worry about that. I would not look at that whatsoever. Because on the first page, you can get a good enough understanding that many times you don't have to deep further. So don't look there because you might be like, oh, that article's too long, I don't want to read it. If you think, all right, one page, one page, like you can do it.

SPEAKER_02 36:10

This is important beyond our understanding level, reading level. Is it something that we can then put into AI to bring down to our language level?

SPEAKER_00 36:25

So what if you want to bring it down? I would just before going to AI or anything like that, I would just go to conclusions first. In an abstract, it's usually the last sentence or two. If you want to like get the cliff notes, okay, you have the title, persistence of autism, all right. What did they find? I don't want to be in suspense this whole time. You can just come down to the conclusions. So, you know, here the the findings of this cohort study suggest that among toddlers diagnosed with ASD, baseline adaptive function and sex may be associated with persistence of ASD. So that's a little wordy. So it's basically saying autism is not persistent throughout life, right? In a very complex way. If you then scoop up to the results, you can say, okay, 213 participants. That's a decent size, right? So now we're starting to think, okay, what did they really do here? Uh 213, and these are things you can look at for quickly. You don't need a PhD, right? You're looking at, okay, now what did they do? 213. Okay. Okay, kind of irrelevant. Boys versus girls. Like too many numbers. Let's keep skipping. All children with non-persistent autism. Okay, so now they're really talking about persistent versus non-persistent autism. So we know this publication is establishing that autism is not persistent, right? So this is now an article where it's like I've gotta understand the details, right? It's relevant. If you're at the beginning stage of autism, your child was disdiagnosed. What do I do? Maybe I need to print this out. This is an investment of my time. I need to understand what this is. So what you could do, you could copy and paste this into some type of AI and say, give me a two to three sentence summary on what this is saying at a fifth grade level. So you certainly could do that. I would be very careful. I would still try and figure out what the heck are they saying here? There's a lot of numbers, a lot of parentheses. I would print this out and maybe write it, but I'm old school. So when I need to really understand something, I will print it out so I can circle it and break it down piece by piece. Everybody does it differently. People might be able to do this on their screen. They might copy and paste certain things. How do you break down information? Everyone does it differently. I would print it out. They were measuring IQ and all of this data in here. The most important part, 37% did not continue to meet diagnosis criteria for autism. In parentheses, this is a new term now, non-persistent ASD. This is huge. AI does have biases. Ask AI is autism permanent? Is autism lifelong? And see what it tells you. That's gonna change depending upon the version and how they update it. That's why you really want to make sure you come to a source like this. This is why I have a YouTube channel, right? This is a lot of work. Most people don't like this. I happen to like this, right? That was the whole premise of my YouTube channel that I started over 10 years ago. Let me take one publication, let me break it down, explain the science in like eight minutes, and teach parents how to think about it in terms of their child. This is the analysis that has to be done, but you always want to make sure the information you're getting is from some kind of source like this. You might want to pull up the publication yourself if you're like, I want to trust X. Let me look at the publication, right? And you can kind of get a feel. Is that person stating what is actually in the publication? And this is how you would do it.

SPEAKER_02 40:32

Something that back is up.

SPEAKER_00 40:34

That's where you can start getting into the rest of the publication. They probably have a summary, they probably mention other studies because I've been in the field now 13 years. I know they're gonna reference that article from 2013 that shows 10% of kids with autism lost their diagnosis. This is how the field evolves. There was research done 10 years ago, and this is also the time it takes. This information doesn't just change overnight because it takes time to follow all these different there's 213 children, right? And they were followed over several years, and it takes time to write the publication and then submit it and have it reviewed and then edited. It's like it all takes time. Now we're starting to get it way past what most people have the tolerance level for. So there are times where I will just skip down to the references, right? So again, you have conflicts of insert interest, there's a grant, so you know, not nothing major that really is a red flag or anything like that. You can start to look at references. Okay, who are they referencing? This is when you're going. I would, if I was gonna start doing that, I probably would have printed it out and I'm gonna tear this apart. And I mean I've that right. So that would be your analysis at a PhD level, right? But this is where you can read the conclusions more. This study suggests that a substantial percentage of individuals clinically diagnosed with autism in early childhood no longer met criteria for autism at school age. That's huge, yeah, right? Parents are going to be making decisions based on old information. 37% of this cohort of 213, that's a decent study size. I'm not gonna expect to have a publication like this to have 10,000 data points. Not gonna happen. Who's funding this, right? There's absolutely no revenue benefit on this whatsoever for anyone. So you have to keep that in mind that this is getting funded by different grants from maybe family foundations and things like that. And it goes on to say that higher baseline adaptive scores and female sex were associated with non-persistent autism. This non-persistent autism is huge, right? Like we have a publication now that is saying autism is not lifelong, but scientists don't use marketing speak like that, right? Non-persistent. What does that really mean? Like you have to think about it. Wait, non-persistent. They no longer met criteria. This is how scientists talk, and this is also why it takes so long for the general public to understand it, because typically a pharmaceutical company, if a founding was made by this and there was a company that could make revenue off a finding like this, the next step they do is they start to do continuing medical education. So they'll go to the large conferences. Let's just use this as an autism example. They would go to large autism conferences, which actually there aren't many because there's no revenue for pharmaceutical companies with autism, but there's a few. And they would go there and they would host CME credits, they would host Lunch and Learns, they might start reaching out to different doctors, and that is how the information gets trickled down from the researchers at the And it gets passed down to other doctors who are are practicing are at the front lines. But there's nobody who's making a profit off this finding at all. And so this is why information will stay in PubMed and it won't get out to the general public. But this is exactly why I do what I do, because this is information that is vital and it changes how parents view their child, right? It changes how they advocate for them in school, how they involve them in family. It's so different.

SPEAKER_02 44:33

I know that there are so many people who write in the newspaper that don't know how to read this properly. The Lemoith quote thing. So here's the idea that if you see something mentioned, you can go to PubMed, you can research it, like Dr. Lyon walked us through.

SPEAKER_00 44:55

Yeah. And you don't, I really to anyone who does not have a PhD or anyone even with a PhD who don't like doing this, not everybody enjoys this, like me, don't go past the first page. There's no need because if you think, oh my gosh, I have to understand, like I get it, but you don't have to go past the first page. I skipped through that, right? A lot of words. We have now recruitment process, yeah, numbers, paragraphs, or tables. Oh my gosh, like who wants to do this? Oh my goodness, it just is there's so much data. Why is that? Oh, because it's quality information.

SPEAKER_02 45:31

Other people who want to continue research based on this.

SPEAKER_00 45:35

For someone who does not like looking at these kinds of articles, don't go past the first page. It's not necessary. If you want to make sure you're getting quality information, don't go past the first page. Otherwise, it'll be overwhelming that you'll have resistance to even looking at any of these articles. Not everybody's like, I want to know these details. Many people are like, I don't want to know it. So that's fine too. But if you feel you're gonna get overwhelmed by all this information and you don't understand it, and it's gonna be frustrating, could be a trigger, and then you're getting irritated and then annoyed, and that's the exact opposite of what you started out to do. Just have a rule with yourself. First page only. I'm a first page only person, totally fine. There are many PhD researchers who are first page only as well.

SPEAKER_02 46:24

Where do we find your YouTube channel if we want to learn more, dig into this? Even if we're not looking for anything autism, but we're trying to figure out how to research for our own wellness team.

SPEAKER_00 46:38

You can just type my name into YouTube and my channel will pop up. I've had it for over 15 years, and we have over 15,000 subscribers. I do have people who watch my videos who are not autism specific because they do address things like inflammation. And there are some people who really appreciate the way I'm explaining the science. And I do have people post comments like, you know, how does this apply for lupus? And it's it's great that they at least understand the way I'm explaining the mechanism of action, and then they start to say, okay, is that relevant to me? So I'm teaching parents how to apply it to their child with autism, but many people find the science that I explain relevant.

SPEAKER_02 47:23

Thank you for this. Thank you for coming on again. If you have questions, reach out to Dr. Lyons or myself. We are happy to help you. I asked her the question at the beginning of the show because I know somebody who is looking for somebody to coach for adult son who has autism. She helped anybody. Family members, children, adult autism. If you are looking for that support reach out to at the end of this, I'm going to be connecting that for reach out to me. Another thought that came to mind is if you are struggling to understand a research article, think about that has an upper level degree with like excited to nerd out over it. Break it down to your is not a sign of you're stupid. There are PhDs who don't know how to read research articles because they don't have a research understanding within their PhD. So you're not stupid. You are very smart in a totally different area. We're a cray box, right? With all different colors. Think of it that way. And we hope that you enjoyed this and that it was meaningful to you. Even if you feel like you don't need this in your life right now, at some point you will. And I'm sure you know somebody who could use this who is constantly sending you Facebook things, making it seem like it's real life and late breaking news.

SPEAKER_01 48:55

Let's kind of get rid of that, please. And thank you. Thank you. I'm gonna run off. Okay.

SPEAKER_02 49:04

Sounds good. Thank you so much for listening to this episode. I hope that you found the answers that you needed and you had some amazing aha moments. Please share this episode with others because it helps us align ourselves and then better align the world so that we can seek the healing that we really are looking for. As part of the legal language, I am a certified life coach with a bachelor's in applied health. That is what I am leaning on for this. This is general advice taken aside. See you in the next episode.