Latest / Wellness, Actually with Emily Oster & Perry Wilson, MD / Understanding Panic Headlines: How studies that influence your parenting choices get published

Transcript

Understanding Panic Headlines: How studies that influence your parenting choices get published · Wellness, Actually with Emily Oster & Perry Wilson, MD

• 0:01
  Speaker 1: I'm Emily Oster. This is parent Data, and today.
• 0:05
  Speaker 2: New tests reveal popular cereals and snacks could have potentially
• 0:10
  Speaker 2: dangerous levels of the same chemical found in weed killer.
• 0:17
  Speaker 3: Here at parent Data, we talk a lot about panic headlines,
• 0:22
  Speaker 3: you know, the headlines.
• 0:23
  Speaker 1: That cycle through your feed about coffee.
• 0:25
  Speaker 3: And wine and sleep and lead and the causes of autism.
• 0:29
  Speaker 3: And many of the panic headlines contradict the last panic headline.
• 0:34
  Speaker 3: Some of them end up debunked, or maybe there was
• 0:37
  Speaker 3: a math error. They're not as scary as they originally seem,
• 0:40
  Speaker 3: but in the moment these feel so scary and urgent.
• 0:45
  Speaker 1: There is new research that impacts you if you're a
• 0:47
  Speaker 1: coffee drinker.
• 0:48
  Speaker 4: Can more screen make your child autistic? Nearly forty percent
• 0:53
  Speaker 4: of parents use white noise machines to help their children
• 0:56
  Speaker 4: sleep sounder and longer. However, some health experts are concerned
• 0:59
  Speaker 4: about the effects that these machines could be having on
• 1:02
  Speaker 4: a child's brain development.
• 1:03
  Speaker 5: More and more women are actually throwing out their tampons,
• 1:06
  Speaker 5: opting out of using tampons for fears of toxic chemicals
• 1:09
  Speaker 5: that could be harmful, according to.
• 1:11
  Speaker 1: A recent Consumer Reports start a news study from.
• 1:13
  Speaker 4: Japan study on rats show that those raised in continuous way. Today,
• 1:17
  Speaker 4: researchers in Japan say the more time your child is
• 1:21
  Speaker 4: exposed to it, the more likely they could land on
• 1:24
  Speaker 4: the autism spectrum.
• 1:25
  Speaker 1: The study was conducted between one.
• 1:30
  Speaker 3: If you're a parent just trying to follow the science,
• 1:33
  Speaker 3: do what's best for your kid. Sometimes it feels like
• 1:36
  Speaker 3: you're being absolutely and really nonsensically bombarded with the wrong
• 1:41
  Speaker 3: things to do. And when it all feels like too much,
• 1:45
  Speaker 3: I like to call doctor Babu. Jenna Babu is an
• 1:49
  Speaker 3: economist like me, but unlike me, he's also a medical
• 1:53
  Speaker 3: doctor and he loves natural experiments, which means an experiment
• 1:59
  Speaker 3: he can't can observing people existing in naturally occurring circumstances.
• 2:05
  Speaker 3: For example, he has some excellent work on flu shots
• 2:09
  Speaker 3: showing that kids whose birthdays fall in the fall are
• 2:13
  Speaker 3: more likely to get their flu shots because they can
• 2:15
  Speaker 3: get them at their yearly well visits. And then he's
• 2:19
  Speaker 3: able to study the impact on flu shots and find,
• 2:22
  Speaker 3: for example, the kids are less likely to get the flu, and.
• 2:25
  Speaker 1: So are their elderly relatives.
• 2:27
  Speaker 3: This isn't a randomized trial that you can set up yourself.
• 2:32
  Speaker 3: This is finding something clever in the data that can
• 2:36
  Speaker 3: allow you to generate a causal estimate even though it
• 2:41
  Speaker 3: hasn't been explicitly randomized. If you've read Freakonomics, you're familiar
• 2:47
  Speaker 3: with this kind of research. And for me, I love
• 2:50
  Speaker 3: this stuff and I love BAPU, And the reason we
• 2:54
  Speaker 3: brought them back today is because we wanted to talk
• 2:56
  Speaker 3: about how research can be abused on it makes its
• 3:00
  Speaker 3: way into the world. I wanted to talk about how
• 3:04
  Speaker 3: we get to that splashy headline that warns you that
• 3:07
  Speaker 3: there's lead in your cheerios, or you have to throw
• 3:09
  Speaker 3: out all your black plastic cooking utensils, or how screens
• 3:13
  Speaker 3: give your kids autism?
• 3:15
  Speaker 1: How do we get there?
• 3:17
  Speaker 3: How does the research that informs that get published If
• 3:23
  Speaker 3: it's not the researchers aim to make us worry, they're
• 3:25
  Speaker 3: just curious data nerds. Why does it feel like they're
• 3:29
  Speaker 3: colluding with the newspapers to scare the crap out of parents.
• 3:33
  Speaker 3: So that's what PAPU and I are going to talk about,
• 3:35
  Speaker 3: what the researchers are actually aiming to do, and then
• 3:38
  Speaker 3: what happens to that research when it arrives in your
• 3:41
  Speaker 3: headlines to freak you out. We talk about the complicated
• 3:45
  Speaker 3: relationship between causality and correlation, the academic and popular incentives
• 3:50
  Speaker 3: to publish these kinds of headlines, and also who decides
• 3:54
  Speaker 3: what research is worth sharing with the world. This is
• 3:59
  Speaker 3: on the fase conversation about research, but really it's about
• 4:02
  Speaker 3: reassurance that there are a lot of reasons behind publishing
• 4:05
  Speaker 3: a story about lead and cheerios that have nothing to
• 4:08
  Speaker 3: do with you, or how dangerous cheerios actually are, or
• 4:12
  Speaker 3: whether you're a good parent who cares about the health
• 4:14
  Speaker 3: and well being of your kids. You are, and you
• 4:17
  Speaker 3: do don't throughout your cheerios. But also, if you're curious,
• 4:21
  Speaker 3: listen to the journey that headline chok to land in
• 4:23
  Speaker 3: your lap.
• 4:26
  Speaker 1: After the break, Doctor Babu.
• 4:28
  Speaker 3: Jenna, Babu Jenna, thanks for joining me.
• 4:39
  Speaker 2: Thank you for having me.
• 4:42
  Speaker 3: You've actually been on the Parent Data podcast before, but
• 4:46
  Speaker 3: for people who weren't listening, like you know, two and
• 4:48
  Speaker 3: a half years ago or whenever.
• 4:50
  Speaker 1: I had you. Could you introduce yourself?
• 4:53
  Speaker 2: First of all, it feels like yesterday, but that's right.
• 4:55
  Speaker 1: Oh, it just feels it's so such a treat. You're
• 4:58
  Speaker 1: always in my.
• 4:58
  Speaker 5: Head except yeah, my name is Babu Jenna. I'm an economist,
• 5:04
  Speaker 5: physician and professor at Harvard Medical School. I have a
• 5:09
  Speaker 5: book called Random acx of Medicine with Chris Worsham, and
• 5:12
  Speaker 5: a podcast called Freaconomics MD.
• 5:16
  Speaker 1: I think it's important to emphasize that although you.
• 5:17
  Speaker 3: Start with being an economist, you are, unlike me, also
• 5:21
  Speaker 3: an actual doctor.
• 5:24
  Speaker 2: That's true. I'm a doctor doctor.
• 5:26
  Speaker 1: Yeah, you see patients.
• 5:28
  Speaker 2: I do.
• 5:29
  Speaker 5: I was actually just on service for a couple of
• 5:31
  Speaker 5: weeks at Mass General in Boston.
• 5:34
  Speaker 1: In the emergency room or no, I work.
• 5:37
  Speaker 2: In the general medical floor.
• 5:38
  Speaker 5: So I spent about two weeks there in a stretch,
• 5:41
  Speaker 5: and so I just finished up yesterday.
• 5:44
  Speaker 3: Do you feel like you get a lot of ideas
• 5:46
  Speaker 3: for your economics work from your doctoring?
• 5:50
  Speaker 5: Yeah?
• 5:50
  Speaker 2: I do.
• 5:51
  Speaker 3: Yeah.
• 5:51
  Speaker 5: I mean there's like all sorts of random things that
• 5:53
  Speaker 5: you see in the hospital, things that patients will say,
• 5:57
  Speaker 5: or problems that you'll encounter, which I think certainly have
• 6:02
  Speaker 5: you given me ideas in the past. A couple of
• 6:03
  Speaker 5: ideas came from things I saw in the hospital.
• 6:05
  Speaker 1: I'm just always curious about that.
• 6:07
  Speaker 3: You seem like a person who gets many of your
• 6:09
  Speaker 3: research ideas from just walk like walking around in the
• 6:12
  Speaker 3: world or things that happened in your own life.
• 6:15
  Speaker 5: Yeah, and chat GPT is feels quite good at this.
• 6:18
  Speaker 5: I don't know if you've tried it for coming up
• 6:19
  Speaker 5: with ideas, but it's not bad.
• 6:22
  Speaker 3: Were you just write in like, I need a research idea.
• 6:25
  Speaker 3: I'm a crazy doctor who likes natural experiments. Give me
• 6:28
  Speaker 3: a research idea.
• 6:29
  Speaker 2: Yeah.
• 6:29
  Speaker 5: So, for example, I had some dinner with some students
• 6:32
  Speaker 5: at Harvard the other night, and we were talking about
• 6:34
  Speaker 5: chat GPT, and so I said to the bart you know,
• 6:37
  Speaker 5: suppose I want to study whether or not playing football
• 6:42
  Speaker 5: as a youth impacts.
• 6:43
  Speaker 2: Your long term health.
• 6:45
  Speaker 5: And so I asked, chat GPT, that's what I want
• 6:47
  Speaker 5: to know. Give me some natural experiments to try to
• 6:51
  Speaker 5: figure this out. And CHATCHEPT came up with a couple
• 6:53
  Speaker 5: of good ideas. It says, all right, well, let's look
• 6:55
  Speaker 5: at whether or not Pop Warner programs come into certain
• 7:00
  Speaker 5: at certain times. Let's look at age cutoffs, let's look
• 7:04
  Speaker 5: at changes in policies towards contact versus no contact football.
• 7:10
  Speaker 5: You know, all very plausible ideas. And I don't think
• 7:12
  Speaker 5: anybody has studied this question before, and so it was
• 7:16
  Speaker 5: remarkable that it was able to come up with ideas
• 7:18
  Speaker 5: that all made a lot of sense. None of them
• 7:20
  Speaker 5: I would pursue, but not bad.
• 7:23
  Speaker 2: Not bad.
• 7:25
  Speaker 3: I feel like my use of GPT is more limited.
• 7:29
  Speaker 3: Yesterday I had it make me an image of Elf
• 7:31
  Speaker 3: on the shelf, which was actually very was actually very good. Okay,
• 7:36
  Speaker 3: But the purpose of this call is not to advertise
• 7:39
  Speaker 3: the products of open AI, which is not a not
• 7:43
  Speaker 3: a sponsor, but to talk about a topic that I
• 7:48
  Speaker 3: think you and I both care a lot about, which
• 7:51
  Speaker 3: is why so much of the research that people hear
• 7:56
  Speaker 3: about in the world is just correlation and not causation.
• 8:03
  Speaker 1: And you know, we've I talk about this a.
• 8:05
  Speaker 3: Lot, and I guess that the I want to sort
• 8:08
  Speaker 3: of set the stage for the problem that we're talking about,
• 8:11
  Speaker 3: But then I actually want to talk about like why
• 8:13
  Speaker 3: this happens, which for me is the more interesting, the
• 8:15
  Speaker 3: more interesting question. So, uh, the canonical example of this
• 8:19
  Speaker 3: problem is, you know, the sort of studies show that
• 8:24
  Speaker 3: you know, new studies shows that you know, coffee like
• 8:29
  Speaker 3: generates makes you live, you know, generates higher longevity, or
• 8:33
  Speaker 3: new study shows that coffee makes you die sooner, or
• 8:37
  Speaker 3: you know new A lot of this stuff happens in nutrition,
• 8:39
  Speaker 3: and it's kind of.
• 8:40
  Speaker 1: Either specific or it can be very general.
• 8:42
  Speaker 3: You know, new study shows that, like people who consume
• 8:45
  Speaker 3: more ultra processed foods, you die sooner. And and these
• 8:50
  Speaker 3: are places where often when people send them to me,
• 8:53
  Speaker 3: then I say, you know it's correlation and not causation,
• 8:56
  Speaker 3: but can you give me your answer?
• 8:59
  Speaker 1: You know, I'm your page.
• 9:00
  Speaker 3: I come and I say, I saw this new study
• 9:01
  Speaker 3: that says blah blah blah about coffee, Like, how do
• 9:04
  Speaker 3: you help me understand what is the problem with that?
• 9:08
  Speaker 3: What are some of your concerns about that study?
• 9:11
  Speaker 5: Well, so, typically if someone going to ask me that
• 9:14
  Speaker 5: kind of question, I'd say, all right, Well, if their
• 9:16
  Speaker 5: goal is to understand whether taking this medication, taking this supplement,
• 9:22
  Speaker 5: drinking coffee is going to actually improve the quality or
• 9:27
  Speaker 5: length of their life, how would you study it? And
• 9:29
  Speaker 5: I'd say to them, the only way to really study
• 9:31
  Speaker 5: this is to do a randomized trial where you take
• 9:34
  Speaker 5: a bunch of people and you randomize some of them
• 9:37
  Speaker 5: to getting.
• 9:40
  Speaker 2: The product.
• 9:40
  Speaker 5: In this case, it could be coffee, it could be medication,
• 9:43
  Speaker 5: And you take an otherwise similar group of people and
• 9:46
  Speaker 5: you randomize them to not getting that, and then you
• 9:50
  Speaker 5: study differences in whatever outcome you care about. It could
• 9:53
  Speaker 5: be blood pressure, could be weight, could be how long
• 9:56
  Speaker 5: you live. And if you see something there, then you
• 9:59
  Speaker 5: can say it's because of the thing that you did,
• 10:02
  Speaker 5: in this case drinking coffee. In the real world, though,
• 10:06
  Speaker 5: you don't have that randomization for the most part, and
• 10:08
  Speaker 5: so you have people who drink a lot of coffee
• 10:10
  Speaker 5: and people who don't. And I would explain to them
• 10:12
  Speaker 5: that people who drink a lot of coffee are different
• 10:14
  Speaker 5: than people who don't. And because of that, you don't
• 10:17
  Speaker 5: know if it's the coffee that's leading to this health
• 10:20
  Speaker 5: outcome or everything else that is different in those people
• 10:24
  Speaker 5: who drink a lot of coffee. And I think most
• 10:27
  Speaker 5: most people would understand that idea if told in that way.
• 10:31
  Speaker 3: I mean, the other thing I will sometimes tell people
• 10:35
  Speaker 3: is think about this choice and think about whether it
• 10:40
  Speaker 3: seems like people are making it randomly. So people say,
• 10:44
  Speaker 3: you know, there's a relationship between family dinner, you know,
• 10:47
  Speaker 3: having a family dinner, homegook, family meal every night, and
• 10:50
  Speaker 3: outcomes for kids and your school outcomes.
• 10:53
  Speaker 1: Just ask them to think about, you know.
• 10:55
  Speaker 3: Once you accept the best way to do this would
• 10:57
  Speaker 3: be randomization, you would ask sort of compare groups who
• 11:00
  Speaker 3: do it and who do not. How close is that
• 11:03
  Speaker 3: to randomization? Like how much randomness do you think there
• 11:06
  Speaker 3: is in this choice? And with many of these choices
• 11:09
  Speaker 3: like what I eat or whether I have family dinner
• 11:11
  Speaker 3: or whatever it is, it doesn't really seem very random.
• 11:16
  Speaker 3: It doesn't seem like there's a very important component of
• 11:18
  Speaker 3: randomization there. That's like the world is not doing a
• 11:21
  Speaker 3: good job randomizing for you.
• 11:23
  Speaker 5: Yeah, and another way to put it, and we have
• 11:26
  Speaker 5: a technical term that we use in our studies called
• 11:29
  Speaker 5: falsification tests. I would say to them, all right, suppose
• 11:32
  Speaker 5: that I showed you that people who drive expensive cars
• 11:35
  Speaker 5: live longer. Would you say to me that buying an
• 11:39
  Speaker 5: expensive car will make you live longer? And most people
• 11:42
  Speaker 5: say no, absolutely not. And I'd say, well, what if
• 11:45
  Speaker 5: it's the case that people who drink a lot of
• 11:46
  Speaker 5: coffee drive fancy your cars or something like that. Then
• 11:50
  Speaker 5: they would sort of get Okay, I get it. There's
• 11:52
  Speaker 5: like there's there are other factors that are going to
• 11:54
  Speaker 5: be correlated with some outcome, but could not plausibly be
• 11:59
  Speaker 5: so in a ca.
• 12:01
  Speaker 3: My favorite thing I ever did about this was a
• 12:03
  Speaker 3: time when I took every food in the National Health
• 12:07
  Speaker 3: and Nutrition Examination Survey, and I correlated it with the weight,
• 12:11
  Speaker 3: and I showed that like, for example, dandelion greens are
• 12:15
  Speaker 3: associated with a lower weight, but iceberg lettuce is associated
• 12:18
  Speaker 3: with having a higher weight, And.
• 12:20
  Speaker 1: Like you know, chemical based.
• 12:22
  Speaker 3: Sugar substitutes are associated with higher weight, but plant based
• 12:25
  Speaker 3: sugar substitutes are associated with lower weight, which for me
• 12:28
  Speaker 3: was like such an illustration of like, you know, who's
• 12:31
  Speaker 3: eating iceberg lettuce?
• 12:31
  Speaker 1: Who's eating what kind of idiots eating dandelion greens? You know,
• 12:34
  Speaker 1: it's like my dad and he's also doing every other thing.
• 12:37
  Speaker 3: And I think that kind of thing can make this
• 12:39
  Speaker 3: quite vivid when you're just like, you know, well, actually,
• 12:44
  Speaker 3: what do you.
• 12:44
  Speaker 1: Think is going on?
• 12:45
  Speaker 3: And as soon as you point that out to someone,
• 12:46
  Speaker 3: the fancy car is a good example, it's like, oh yeah, okay,
• 12:51
  Speaker 3: Like it's not that this is not that complicated a
• 12:54
  Speaker 3: point to make two people I find.
• 12:57
  Speaker 5: Yeah, yeah, but I mean, just to be fair, they're
• 13:00
  Speaker 5: pretty high quality evidence about dan line greens and dimension
• 13:04
  Speaker 5: that's not true, there's not Can I just ask a
• 13:08
  Speaker 5: clarifying question when you say dandelion greens, are those the
• 13:11
  Speaker 5: same thing as those fancy little microgreens that you get.
• 13:14
  Speaker 3: No, a dan lion green is literally a part of
• 13:17
  Speaker 3: a dandelion. It's like instead of eating, you don't eat
• 13:20
  Speaker 3: the flower, but.
• 13:21
  Speaker 1: You eat the greens.
• 13:23
  Speaker 3: Yeah, microgreens are a delicious treat associated with uh, you know,
• 13:28
  Speaker 3: higher rates of IQ.
• 13:30
  Speaker 5: Or I'll say the following though, that's like, you know,
• 13:33
  Speaker 5: the astute listener will know that my name is A
• 13:36
  Speaker 5: is an Indian name, and so it's not uncommon for
• 13:39
  Speaker 5: Indian people to take flowers and like like fry them
• 13:43
  Speaker 5: in some like flour like do it comes out delicious?
• 13:46
  Speaker 2: I don't think it's healthy though.
• 13:48
  Speaker 3: Right, the flowers might be good for you, but the
• 13:52
  Speaker 3: frying somewhat negates It's actually that people are frying their
• 13:56
  Speaker 3: iceberg lettice.
• 13:57
  Speaker 2: That's exactly exactly.
• 14:01
  Speaker 4: So.
• 14:01
  Speaker 3: A thing I find puzzling about this space is I
• 14:07
  Speaker 3: feel like if you explained this, and I have to
• 14:11
  Speaker 3: my thirteen year old, this concept that you know, correlation
• 14:16
  Speaker 3: is not causation and that you would really want to
• 14:20
  Speaker 3: worry quite a lot about the other things that might
• 14:25
  Speaker 3: be driving these relationships.
• 14:26
  Speaker 1: I feel like that is a.
• 14:27
  Speaker 3: Very intuitive idea, and you know, not that like everybody
• 14:31
  Speaker 3: sees it immediately, but that it isn't very hard for
• 14:33
  Speaker 3: people to understand. Even in a you know, a short conversation,
• 14:37
  Speaker 3: you can kind of get people to see it. I mean,
• 14:39
  Speaker 3: I think, you know, I spend a lot of time
• 14:41
  Speaker 3: on Instagram short form Instagram videos.
• 14:43
  Speaker 1: Explaining this, and I think some of the time it hits.
• 14:46
  Speaker 3: The question I find more puzzling is why are there
• 14:49
  Speaker 3: so many papers which do this, which are written by
• 14:53
  Speaker 3: people who haven't just watched a forty five second Instagram
• 14:57
  Speaker 3: video or had one conversation with you, but who have
• 15:00
  Speaker 3: spent literally many, many years taking classes on these exact
• 15:06
  Speaker 3: topics and then writing papers. And these people are, you know,
• 15:10
  Speaker 3: professors or like, they have a lot of education, They're smart,
• 15:15
  Speaker 3: and I just fundamentally don't understand why so much of
• 15:20
  Speaker 3: this literature keeps happening, and whether the people who are
• 15:24
  Speaker 3: writing it think that they are uncovering something causal or not.
• 15:32
  Speaker 1: Do you have any insight?
• 15:34
  Speaker 5: I have answers, I don't know if they're insightful, But well,
• 15:37
  Speaker 5: let me just say the following. First of all, and
• 15:40
  Speaker 5: at some point later day, I'm going to tell you
• 15:41
  Speaker 5: about a paper that we have coming out in probably
• 15:45
  Speaker 5: a couple of weeks. It will be December, so I
• 15:46
  Speaker 5: don't know when this will air, but it will fall
• 15:49
  Speaker 5: into this category of a very weird sort of correlation.
• 15:54
  Speaker 2: And the.
• 15:57
  Speaker 5: Way that we would describe it in the way that
• 15:59
  Speaker 5: we do justscribed as finding, which I know I'm making
• 16:02
  Speaker 5: it sort of sound very sort of like wow, what's
• 16:04
  Speaker 5: what's he going to drop on me in a moment?
• 16:07
  Speaker 5: Is it's just a hypothesis. So I would have no
• 16:10
  Speaker 5: problem if people would do the kinds of studies that
• 16:13
  Speaker 5: you're describing, which are purely correlational studies, no sort of experiment,
• 16:18
  Speaker 5: serving as the backbone behind the idea and saying, look,
• 16:22
  Speaker 5: here's this interesting observation. We don't know what to make
• 16:25
  Speaker 5: of it. It could be causal for X, y Z
• 16:28
  Speaker 5: reason like there's a there's a channel by which this thing,
• 16:33
  Speaker 5: in this case dandelions, could have an effect on some
• 16:37
  Speaker 5: health outcome and it would work by this mechanism. You know,
• 16:41
  Speaker 5: this flower affects this protein in the body. This protein
• 16:44
  Speaker 5: in the body affects these cells. These cells affect the
• 16:47
  Speaker 5: development dementia something like that. Totally fine with that, because
• 16:51
  Speaker 5: then a reader could say, all right, well, you know
• 16:52
  Speaker 5: I want to investigate this or not investigate and investigate
• 16:55
  Speaker 5: this any further. But that's not the way the studies
• 16:57
  Speaker 5: come out. The studies come out as you know, danne
• 17:00
  Speaker 5: greens are you know, strongly associated with dementia, and therefore
• 17:04
  Speaker 5: you should eat you know fewer or more of these
• 17:07
  Speaker 5: day online greens. The question that is to your questions
• 17:09
  Speaker 5: like why do you see this? And among educated researchers,
• 17:13
  Speaker 5: I think it's two things. Probably one is I think
• 17:17
  Speaker 5: that they might at their core believe.
• 17:20
  Speaker 2: This to be true.
• 17:22
  Speaker 5: And this is something I've been thinking a lot about now,
• 17:24
  Speaker 5: which is sort of how do your beliefs impact the
• 17:27
  Speaker 5: way that you do science, the way that you do research.
• 17:30
  Speaker 5: I mean, certainly, if you have a belief that something
• 17:33
  Speaker 5: is right or correct true, you might do research in
• 17:37
  Speaker 5: a way that validates that, and you might sort of
• 17:39
  Speaker 5: interpret the findings in a way that that validate that.
• 17:42
  Speaker 5: So I think that's one problem, and I think that
• 17:44
  Speaker 5: was something that we've maybe saw a lot of actually
• 17:47
  Speaker 5: during the COVID nineteen pandemic. And then the other problem
• 17:50
  Speaker 5: is I think that the incentives aren't there to do
• 17:55
  Speaker 5: something more like, you know, it takes more work to
• 17:57
  Speaker 5: do something clever and creative to solve a problem in
• 18:01
  Speaker 5: a more rigorous way. It takes more effort and more
• 18:03
  Speaker 5: thinking and more creativity, and if the incentives aren't there
• 18:06
  Speaker 5: to do that, then you're not going to do that.
• 18:09
  Speaker 5: And I think in general, medical journals don't require that
• 18:13
  Speaker 5: as a standard. You know, you write a lot of
• 18:15
  Speaker 5: economics papers. Economics papers do require that as a standard,
• 18:19
  Speaker 5: so you would not typically see those kinds of papers
• 18:21
  Speaker 5: published in the best economics journals, whereas you know, almost
• 18:25
  Speaker 5: every week in the best medical journals you'll see a
• 18:27
  Speaker 5: paper like that come out.
• 18:29
  Speaker 1: Yeah, I mean, I think that's a that's all for me.
• 18:33
  Speaker 3: Like that is an answer which is almost certainly right,
• 18:35
  Speaker 3: which is, you know, my incentive as a researcher is
• 18:38
  Speaker 3: to publish my papers in the best you know in JAMA.
• 18:41
  Speaker 3: And if JAMA is happy to see a correlation, then
• 18:45
  Speaker 3: I guess I then I then that's much easier paper
• 18:48
  Speaker 3: to produce than than you know, something else, And so
• 18:52
  Speaker 3: maybe I do that. That of course pushes the question
• 18:55
  Speaker 3: down the line to you know what, why don't the
• 18:58
  Speaker 3: editors of JAMA understand the difference between correlation and causality?
• 19:02
  Speaker 1: A question I asked myself frequently, and.
• 19:07
  Speaker 3: I get the impression when I read these papers that
• 19:12
  Speaker 3: people think that the kinds of empirical adjustments they do
• 19:16
  Speaker 3: are sufficient.
• 19:18
  Speaker 1: I mean, this is like when you read these papers.
• 19:19
  Speaker 3: So just to sort of back up for people who
• 19:21
  Speaker 3: don't spend their days in papers about coffee and longevity,
• 19:25
  Speaker 3: you know, it's very common in research like this for
• 19:28
  Speaker 3: researchers to talk about adjusting for variables. So they say,
• 19:33
  Speaker 3: you know, in the data, I see not only do
• 19:35
  Speaker 3: you eat dandelion greens, and you know how long do
• 19:38
  Speaker 3: you live? Or do you have dementia. Let's say, let's
• 19:41
  Speaker 3: keep with our dementia thing. So not only do I
• 19:43
  Speaker 3: see your dandelion greens and your dementia, but I also
• 19:46
  Speaker 3: see you know, whether you went to high school, and
• 19:49
  Speaker 3: you know, some categories of income, and your sex, and
• 19:52
  Speaker 3: your age and maybe your race, and maybe I see
• 19:57
  Speaker 3: more whatever it is, and they adjust for those They
• 20:00
  Speaker 3: use a statistical method to effectively try to match people
• 20:05
  Speaker 3: with similar values of those variables. It's not usually quite
• 20:08
  Speaker 3: that technique, but something where I basically said, I'm going
• 20:10
  Speaker 3: to try to hold constant these other features so I
• 20:14
  Speaker 3: can be closer to being causal and my view informed
• 20:20
  Speaker 3: by a lot of the research I've done is that
• 20:22
  Speaker 3: most of the time that's completely insufficient. And then in fact,
• 20:25
  Speaker 3: there's tons of things we don't see about people which
• 20:27
  Speaker 3: are very important for their choices of, say, what to eat,
• 20:30
  Speaker 3: that are not summarized. A full component of somebody's interest
• 20:34
  Speaker 3: in their health is not summarized by two categories of
• 20:37
  Speaker 3: education and three categories of income, and that these are
• 20:40
  Speaker 3: just really insufficient. But I wonder how much.
• 20:42
  Speaker 1: Of it is that I just have a particular, I.
• 20:46
  Speaker 3: Think informed, but maybe unusual view about just how important
• 20:50
  Speaker 3: unobservables are, and that most of the public health profession
• 20:54
  Speaker 3: has a different view about how important unobservables are.
• 20:57
  Speaker 1: I mean, how much do you think it's that?
• 21:02
  Speaker 5: I think that's part of it. But I'll tell you, you know,
• 21:05
  Speaker 5: as someone who spent most of my life writing the
• 21:09
  Speaker 5: kinds of studies where we're trying to find experiments and
• 21:12
  Speaker 5: publishing them mostly in medical journals, there's a lot of
• 21:18
  Speaker 5: papers that I've sent to journals where they come back
• 21:21
  Speaker 5: to me and the paper gets rejected and they'll explain
• 21:25
  Speaker 5: why they think this is not causal. And I'm always
• 21:30
  Speaker 5: thinking to myself, Wow, this is like definitely causal.
• 21:33
  Speaker 2: It may not be important, but it's definitely.
• 21:36
  Speaker 5: Causal, and we've gone through great lengths to show that
• 21:40
  Speaker 5: there's a causal relationship here. And it's not as if
• 21:45
  Speaker 5: the editors don't have an understanding of these ideas, which
• 21:48
  Speaker 5: is always puzzling to me, because they reject pay And
• 21:52
  Speaker 5: it's not just me, it's other people who I work
• 21:54
  Speaker 5: with who are submitting papers that are using these sort
• 21:56
  Speaker 5: of causal designs, and they'll get rejected. And one of
• 21:59
  Speaker 5: the reasons they'll get rich is because they'll say, you know,
• 22:01
  Speaker 5: we're not sure this is causal because of X, Y
• 22:03
  Speaker 5: and z. But then another paper which is not at
• 22:07
  Speaker 5: all causal will go through. And the only way I
• 22:11
  Speaker 5: can sort of rationalize this is to say that I
• 22:14
  Speaker 5: think everybody knows that these studies that we're talking about
• 22:19
  Speaker 5: are just can't be true. Like the only way this
• 22:22
  Speaker 5: makes sense is like they just can't be true, and
• 22:24
  Speaker 5: so you hold a different standard to them. Even though
• 22:26
  Speaker 5: the language is there which is sort of close to causal.
• 22:29
  Speaker 5: There's these disclaimers at the end about how the study
• 22:32
  Speaker 5: is not causal or you can't interpret anything about the
• 22:34
  Speaker 5: cause relationships here based on the study design. But I
• 22:38
  Speaker 5: think that they have an understanding of the issues, but
• 22:40
  Speaker 5: they are applied differently, And the question might be why
• 22:44
  Speaker 5: are they applied differently?
• 22:47
  Speaker 1: Do you think the reason they're implied?
• 22:48
  Speaker 3: First of all, that's an incredibly cynical view, although perhaps true.
• 22:52
  Speaker 3: But do you think the reason they're applied differently is
• 22:55
  Speaker 3: because you, as a journal editor, know that like if
• 23:00
  Speaker 3: you publish, not that your work is intimportant, but some
• 23:02
  Speaker 3: of the things that you work on, I think are not.
• 23:05
  Speaker 3: Some of the things you work on are very headline friendly,
• 23:07
  Speaker 3: but some of the things you work on are not
• 23:08
  Speaker 3: very headline friendly. And so you know, like you publish
• 23:12
  Speaker 3: a Bapuo paper, you know that it's causal, but maybe
• 23:15
  Speaker 3: the New York Times doesn't care you publish something that says,
• 23:19
  Speaker 3: you know, ultra processed foods caused dementia, or dandelion greens
• 23:22
  Speaker 3: don't cause dementia or whatever, like the New York Times,
• 23:25
  Speaker 3: well section they're calling, they're calling you, yeah, And I mean,
• 23:29
  Speaker 3: how much do you think that matters?
• 23:32
  Speaker 5: I think it matters. I'm and you know, as you're
• 23:34
  Speaker 5: saying that, my mind is sort of racing, like how
• 23:36
  Speaker 5: could you how could you sort of start to study that?
• 23:39
  Speaker 5: I mean, I wonder if there are any shocks to
• 23:43
  Speaker 5: media interest in these topics or something like that where
• 23:47
  Speaker 5: you could really show that when the New York Times
• 23:50
  Speaker 5: or something like that becomes interested in a topic, that
• 23:54
  Speaker 5: you start to see more papers being published in the
• 23:57
  Speaker 5: top journals on that or something to that, because I
• 24:00
  Speaker 5: do think that's part of it that the journals are
• 24:03
  Speaker 5: responding to. I mean, ultimately, the job of the journals
• 24:07
  Speaker 5: is to create scientific information that shapes the scientific record.
• 24:10
  Speaker 5: That's your certainly one goal, I think, but the other
• 24:13
  Speaker 5: is to sort of make sure people read their journal
• 24:15
  Speaker 5: to be to feel like they're being relevant, Like that's
• 24:17
  Speaker 5: the core part of their business model. So if they're
• 24:20
  Speaker 5: not publishing things that people don't want to read, that's
• 24:23
  Speaker 5: a problem. And one of the things that people have
• 24:26
  Speaker 5: an appetite for there's a demand for is this kind
• 24:29
  Speaker 5: of science. Now why that is I don't know, Or
• 24:34
  Speaker 5: why there's a demand for this low quality science, I
• 24:37
  Speaker 5: don't know. I mean, I certainly understand why there's an
• 24:39
  Speaker 5: interest in understanding whether or not coffee has an effect
• 24:41
  Speaker 5: in your life or all these things that we are
• 24:43
  Speaker 5: sort of do all the time.
• 24:46
  Speaker 1: Yeah, I mean, I think people.
• 24:50
  Speaker 3: Part of the reason for the demand is like if
• 24:52
  Speaker 3: you as the now we're like on one step you
• 24:55
  Speaker 3: know below this, But like the New York Times would
• 24:58
  Speaker 3: like people to click on their things and read them.
• 25:01
  Speaker 3: And something that says, you know, coffee has this effect,
• 25:05
  Speaker 3: or you know, plastics have or whatever. It is like
• 25:08
  Speaker 3: something that sort of causes people to worry about a
• 25:12
  Speaker 3: topic that is relevant for their lives. That is a
• 25:16
  Speaker 3: great thing to get people to click on. That's like
• 25:19
  Speaker 3: popular click clicker location.
• 25:22
  Speaker 2: Yeah, I mean there's a question of sort of what.
• 25:24
  Speaker 5: I don't know that the right word here is research integrity,
• 25:27
  Speaker 5: But you know, I will sometimes see things where people
• 25:31
  Speaker 5: will landbast a journalist for talking about a study that's
• 25:36
  Speaker 5: clearly not causal. And my view is, like, why are
• 25:38
  Speaker 5: we picking on the journalists. The journalist wasn't trained to
• 25:41
  Speaker 5: do this, right, We should be picking on the journal itself,
• 25:43
  Speaker 5: the journal editors, or even the researchers who decided to
• 25:47
  Speaker 5: do that, like they really should know better, and yet
• 25:52
  Speaker 5: they're they're doing that. And I think that, like, again,
• 25:55
  Speaker 5: we can always quibble about what's an important study or
• 25:58
  Speaker 5: a creative study that I would have no problem debating that,
• 26:02
  Speaker 5: But I think that most people can agree that certain
• 26:05
  Speaker 5: studies are just not likely to be right, or you
• 26:08
  Speaker 5: have no idea whether they're right or wrong. And I
• 26:10
  Speaker 5: think people would agree with that.
• 26:12
  Speaker 3: I mean, I think that's I find that very cynical,
• 26:15
  Speaker 3: and I think maybe a different way to say it
• 26:17
  Speaker 3: is I think it goes back to this thing you
• 26:19
  Speaker 3: said at the beginning about sort of people believe something
• 26:22
  Speaker 3: to be true, you know, if I believe it to
• 26:24
  Speaker 3: be true for whatever reason based on the outside, you know,
• 26:28
  Speaker 3: like based on other things I know about the world,
• 26:30
  Speaker 3: maybe from better studies, maybe something. If I really have
• 26:33
  Speaker 3: a core belief that like eating more ultra process foods
• 26:35
  Speaker 3: is bad for you, which I think is a belief
• 26:37
  Speaker 3: that many people have and may be a reasonable belief,
• 26:41
  Speaker 3: and then I publish a study in which there's a
• 26:44
  Speaker 3: correlation between you know, the share of your food that's
• 26:47
  Speaker 3: ultra processed and your health outcome, of which there are
• 26:50
  Speaker 3: many studies, even though almost all of those studies really
• 26:55
  Speaker 3: it's very hard to know how much of that affect
• 26:58
  Speaker 3: is the food and how much is all of the
• 26:59
  Speaker 3: other differences. And really maybe you would dig into people
• 27:02
  Speaker 3: and they would say, well, yeah, you know, there's probably
• 27:04
  Speaker 3: some other confounds that the fact that they they're more
• 27:07
  Speaker 3: comfortable saying to a journalist, you know, people should eat
• 27:11
  Speaker 3: less ulster processed foods, because they're coming in with the
• 27:15
  Speaker 3: belief that that is right, and that this is this
• 27:18
  Speaker 3: paper reinforces something which they really already thought it was true.
• 27:21
  Speaker 3: And even if you said, well, this particular paper didn't
• 27:23
  Speaker 3: really add that much to my knowledge, I was already
• 27:26
  Speaker 3: very sure that was true. And so I'm comfortable saying
• 27:28
  Speaker 3: that it should change people's behavior, not so much because
• 27:31
  Speaker 3: this particular piece of evidence that we've produced, but just
• 27:34
  Speaker 3: because I generally think that that's the thing people should do,
• 27:36
  Speaker 3: and this is an opportunity to express Then.
• 27:39
  Speaker 5: Yeah, I totally agree. It's such a hard question to study.
• 27:43
  Speaker 5: I mean, the way I've thought about this is like,
• 27:45
  Speaker 5: are there particular topics where you could reasonably show that
• 27:51
  Speaker 5: a researcher would have a particular view in mind, and
• 27:54
  Speaker 5: to see whether or not their studies sort of align
• 27:58
  Speaker 5: with those views.
• 28:00
  Speaker 2: You know.
• 28:01
  Speaker 5: The example that I sometimes tell my undergraduate students is,
• 28:05
  Speaker 5: you know, think about sort of evidence on masking. There's
• 28:09
  Speaker 5: not like a ton of studies, and certainly not a
• 28:11
  Speaker 5: ton of high quality studies on this, But if you
• 28:13
  Speaker 5: were to see that individuals who published research that showed
• 28:17
  Speaker 5: that masks are beneficial for the prevention of COVID nineteen
• 28:23
  Speaker 5: and you look at researchers who found the opposite. If
• 28:26
  Speaker 5: we looked at those researchers on social media prior to
• 28:29
  Speaker 5: ever publishing any studies on this topic, would those who
• 28:33
  Speaker 5: were in the first category be more likely to be
• 28:35
  Speaker 5: wearing masks, to be tweeting.
• 28:36
  Speaker 2: About masks things like that.
• 28:38
  Speaker 5: Like, I think that there are ways to sort of
• 28:40
  Speaker 5: show that our researchers views about the world. And I
• 28:45
  Speaker 5: won't even call it ideology because there's no ideology about
• 28:47
  Speaker 5: coffee and longevity. It's sort of I think it could
• 28:50
  Speaker 5: be true. There's an incentive for me to publish this,
• 28:53
  Speaker 5: so I'm going to do it. But thinking about how
• 28:56
  Speaker 5: the incentives, whether it's career incentives, financial incentives, ideological incentives,
• 29:03
  Speaker 5: how much the role of incentives play in the questions
• 29:07
  Speaker 5: that people ask and the way they study them and
• 29:10
  Speaker 5: the answers that they find. I think is an untapped
• 29:14
  Speaker 5: area for research, but could be really interesting.
• 29:18
  Speaker 3: Yeah, And I think, I mean there's so many pieces
• 29:20
  Speaker 3: of the incentives. There's my personal incentives, there's you know,
• 29:22
  Speaker 3: how aligned am I with some you know, with an
• 29:25
  Speaker 3: existing set of beliefs that that other people have. You know,
• 29:29
  Speaker 3: I think there is some work on like whether it
• 29:31
  Speaker 3: is you know, how much more difficult it is to
• 29:33
  Speaker 3: publish something that goes again some existing scientific paradigm, which,
• 29:37
  Speaker 3: of course, in some ways it should be, because if
• 29:39
  Speaker 3: you know, everyone says the sky is blue, and you
• 29:41
  Speaker 3: write a paper that says the sky is green, like, probably.
• 29:45
  Speaker 1: We shouldn't publish your paper.
• 29:46
  Speaker 3: But yeah, you know, but that kind of thing in
• 29:50
  Speaker 3: settings in which is less clear, can can result in
• 29:55
  Speaker 3: you basically sort of stasis in a in a field
• 29:59
  Speaker 3: until sort of something surprising happens.
• 30:02
  Speaker 5: Yeah, you know what conversations I've never had. I've never
• 30:05
  Speaker 5: asked a journal editor.
• 30:06
  Speaker 2: Why they publish these studies.
• 30:07
  Speaker 5: I would love to know the answer that question.
• 30:10
  Speaker 3: I would love to know the answer to that question too.
• 30:12
  Speaker 3: I've never managed to find someone to discuss it with me.
• 30:15
  Speaker 3: I mean, the other thing it's very interesting is probably
• 30:17
  Speaker 3: like two in the weeds for here, but like an
• 30:21
  Speaker 3: aspect that's totally so. In economics, like, the peer review
• 30:24
  Speaker 3: process is very very different than medicine, and economics like,
• 30:26
  Speaker 3: the peer review process takes an extremely long time, and
• 30:28
  Speaker 3: there are.
• 30:29
  Speaker 1: Many people who have means.
• 30:31
  Speaker 3: It's too extreme in some ways in my view, but
• 30:33
  Speaker 3: it's you know, you'll have five different people writing you
• 30:35
  Speaker 3: three pages about how terrible your paper is, and every
• 30:38
  Speaker 3: single line is the worst. You'll revise and resubmit, and
• 30:41
  Speaker 3: it's just like a lot of commenting and a lot
• 30:44
  Speaker 3: of like people reading things in great detail. The referee
• 30:50
  Speaker 3: process in medicine is much faster, but it also is
• 30:54
  Speaker 3: way much more about like, here is this paper, do
• 30:58
  Speaker 3: I like it or not?
• 30:59
  Speaker 1: More or less as is? And then you know.
• 31:02
  Speaker 3: That that kind of allows for less space for an
• 31:05
  Speaker 3: expert reviewer to fix something.
• 31:08
  Speaker 2: Yeah, yeah, you know, we have this paper.
• 31:12
  Speaker 5: I'll tell you the finding.
• 31:15
  Speaker 1: Are you going to tell me the finding of the paper? Now?
• 31:17
  Speaker 2: I'm going to tell you that.
• 31:17
  Speaker 5: Oh no, I just I want to tell you another
• 31:19
  Speaker 5: because it does illustrate some of the things we're talking
• 31:21
  Speaker 5: about now.
• 31:21
  Speaker 2: But then I want to do.
• 31:22
  Speaker 1: That and I want to hear about this.
• 31:23
  Speaker 5: Yeah, yeah, so we have this paper that shows so
• 31:29
  Speaker 5: a couple of years ago we had this paper in
• 31:31
  Speaker 5: the New Aternal Medicine that showed that kids who are
• 31:32
  Speaker 5: born in August have higher rates of ADHD diagnosis than
• 31:36
  Speaker 5: kids who were born in September, and the idea was
• 31:38
  Speaker 5: that in this other economists had shown this as well.
• 31:41
  Speaker 5: But the idea is that kids were born in August
• 31:43
  Speaker 5: are often the youngest kids in their class, and so
• 31:46
  Speaker 5: when they behave differently, that's sort of perceived to be
• 31:49
  Speaker 5: reflective of ADHD, as opposed to the recognition that these
• 31:52
  Speaker 5: kids are just younger for their their grade. And that
• 31:56
  Speaker 5: all stems from the idea that ADHD is a subjective diagnosis.
• 31:59
  Speaker 5: You don't see the same thing for asthma, you don't
• 32:01
  Speaker 5: see the same thing for diabetes, because those are more
• 32:04
  Speaker 5: objectively determined. And now fast forward a couple years later,
• 32:08
  Speaker 5: we have this paper now which shows that the diagnosis
• 32:13
  Speaker 5: of ADHD goes up on Halloween. And so we look
• 32:19
  Speaker 5: at millions of visits to pediatricians on Halloween versus all
• 32:23
  Speaker 5: the surrounding days. We definitely account for the possiblity that
• 32:28
  Speaker 5: parents who go to the doctor on Halloween take their
• 32:30
  Speaker 5: kid there might be different and we show that we
• 32:32
  Speaker 5: don't think that that's what's going on, and we show
• 32:35
  Speaker 5: that the diagnosis rate of ADHD is higher, and what
• 32:39
  Speaker 5: we think is going on is that there are some
• 32:41
  Speaker 5: children who the provider was thinking about this as a
• 32:45
  Speaker 5: possibility of a diagnosis ADHD, but they never sort of
• 32:48
  Speaker 5: pull the trigger on the diagnosis. But on that day,
• 32:52
  Speaker 5: the behavior the child is different for obvious reasons, right,
• 32:54
  Speaker 5: Like they're excited about Halloween, right, So they're just less attentive,
• 32:58
  Speaker 5: they're not answering questions, and so that diagnosis gets made.
• 33:02
  Speaker 2: It's not a huge.
• 33:02
  Speaker 5: Effect, but it's it's clearly measurable. You can see it
• 33:05
  Speaker 5: in the data. And you know, we write this paper
• 33:08
  Speaker 5: up and we don't know whether this is underdiagnosis or overdiagnosis.
• 33:12
  Speaker 5: Could be it could be overdiagnosis, right like something as
• 33:15
  Speaker 5: arbitrary as Halloween leads you to make a diagnosis that
• 33:19
  Speaker 5: you otherwise wouldn't have made. But it could also be underdiagnosis,
• 33:22
  Speaker 5: like these children could be. This could be what we
• 33:24
  Speaker 5: call a stress test, Like you do a cardiac stress
• 33:27
  Speaker 5: test to look for heart disease. This could be an
• 33:30
  Speaker 5: ADHD stress test where if that child responds in such
• 33:32
  Speaker 5: a way on Halloween that you now think about the
• 33:36
  Speaker 5: diagnosis of ADHD more firmly, that might be indicative of
• 33:39
  Speaker 5: something that needs to be addressed in that child. So
• 33:42
  Speaker 5: that could be underdiagnosis. So we write this paper and
• 33:46
  Speaker 5: we send it to a lot of places, medical journals,
• 33:48
  Speaker 5: all good places, and you know, most of the reviews
• 33:51
  Speaker 5: are actually generally like on the methods, they don't have
• 33:54
  Speaker 5: anything to say. But from a number of places we've
• 33:57
  Speaker 5: gotten feedback back, both from the editors and from sometimes
• 34:01
  Speaker 5: reviewers about how this finding is highly stigmatizing to the disease,
• 34:06
  Speaker 5: and we've had an extraordinarily difficult time to get it published.
• 34:09
  Speaker 5: Now we're trying going a different route, but you know,
• 34:13
  Speaker 5: my pushback has been, well, look, you know we're not
• 34:16
  Speaker 5: calling it. We're not saying that this over diagnoses or
• 34:19
  Speaker 5: this these are frivolous diagnoses. In fact, if this is
• 34:22
  Speaker 5: under diagnosis, you know, what does it mean to a
• 34:24
  Speaker 5: parent that the for their child, the only way that
• 34:28
  Speaker 5: they would have gotten diagnosed with ADHD is if by
• 34:31
  Speaker 5: chance they happened to go on Halloween, and otherwise it
• 34:33
  Speaker 5: wouldn't have been diagnosed with a condition that their child
• 34:36
  Speaker 5: might have. Like that arbitrariness and the diagnosis I think
• 34:40
  Speaker 5: should should be concerning to people. It might be inevitable,
• 34:45
  Speaker 5: but it should certainly be something that flags your attention.
• 34:48
  Speaker 2: And we've had a really.
• 34:49
  Speaker 5: Difficult time getting this thing published because, for lack of
• 34:53
  Speaker 5: better words, what I think are the optics. I mean,
• 34:54
  Speaker 5: that's what we're that's the feedback that we're getting.
• 34:57
  Speaker 3: That's very frustrating because, of course, if you sort of
• 35:02
  Speaker 3: have the very high minded view we're all supposed to
• 35:04
  Speaker 3: have of science, which is like, we're going to learn things,
• 35:06
  Speaker 3: and we're going to get data, and then we're going
• 35:07
  Speaker 3: to use it to make decisions and we're going to
• 35:09
  Speaker 3: you know, put truth out in the world to sort
• 35:13
  Speaker 3: of say, well, here's the thing, Like I believe it
• 35:15
  Speaker 3: to be true, but I feel that people shouldn't hear
• 35:17
  Speaker 3: it because it will make them feel bad, or it
• 35:20
  Speaker 3: will you know, the variety of reasons that I that's very.
• 35:24
  Speaker 1: That must be very frustrating.
• 35:26
  Speaker 5: It is, but we keep keep watching on. But tell
• 35:29
  Speaker 5: me when you're ready for this other random finding.
• 35:31
  Speaker 2: Yes, I'm ready.
• 35:32
  Speaker 3: Okay, So, so I have one other thing I want
• 35:35
  Speaker 3: to I want to close this out, and then I
• 35:36
  Speaker 3: want to hear your random finding.
• 35:37
  Speaker 1: Okay.
• 35:38
  Speaker 3: So when I once asked my undergraduate this like sort
• 35:42
  Speaker 3: of sums up this entire conversation. I once asked my
• 35:44
  Speaker 3: undergraduate class we had gone through one of these papers
• 35:47
  Speaker 3: that I was complaining about, and then I asked them
• 35:50
  Speaker 3: like this sort of question we're have here, just like
• 35:52
  Speaker 3: sort of whose fault is this? And there was a
• 35:55
  Speaker 3: kid who kind of thought about it for a while
• 35:57
  Speaker 3: and then he basically was like, well, I think it's
• 36:01
  Speaker 3: my fault. And he said, you know, I clicked on
• 36:05
  Speaker 3: that headline, and that's why they put up the headline,
• 36:08
  Speaker 3: and that's why the person wrote the story, and that's
• 36:11
  Speaker 3: why the journal took the article, and that's why the
• 36:13
  Speaker 3: researcher wrote the article so the journal would take it,
• 36:17
  Speaker 3: and the journal took it so the guy would write
• 36:19
  Speaker 3: about it, and the person wrote about it because they
• 36:21
  Speaker 3: knew it would get a good headline, and they put
• 36:23
  Speaker 3: the headline on so I would click on it, and
• 36:26
  Speaker 3: so this is my fault. And I was like, yeah,
• 36:28
  Speaker 3: I guess it is. It's like, thank you for the lesson.
• 36:33
  Speaker 3: So that's why twenty year olds are smart.
• 36:36
  Speaker 2: Yeah, that's almost like reader shaming. I don't know. I wouldn't.
• 36:39
  Speaker 2: I don't think it's his fault. I don't think it's
• 36:43
  Speaker 2: his fault at all.
• 36:50
  Speaker 3: More parenting it including the importance of debunking panic headlines
• 36:55
  Speaker 3: for the sake of parents' mental health, and we finally
• 36:58
  Speaker 3: get to Bapu's groundbreaking research after the break, just to
• 37:15
  Speaker 3: sort of close it because it's a parenting podcast. I
• 37:18
  Speaker 3: think that so much of what I spend my time
• 37:22
  Speaker 3: doing is sort of dialing down people's panic around these
• 37:26
  Speaker 3: kind of headlines which come up all the time in parenting.
• 37:28
  Speaker 1: Because if you had to.
• 37:30
  Speaker 3: Pick a space in the world to write panicky headlines,
• 37:34
  Speaker 3: parenting would be it, because that's really what people like
• 37:37
  Speaker 3: to click and I guess just to like not to
• 37:40
  Speaker 3: put too fine a point on it, but I think
• 37:43
  Speaker 3: actually in the parenting space it can be quite bad
• 37:47
  Speaker 3: in the sense of, you know, we talk about this,
• 37:49
  Speaker 3: you and I talk about this like oh, like of
• 37:51
  Speaker 3: course nobody thinks that this is true, and like, you know,
• 37:54
  Speaker 3: researchers know it's not.
• 37:55
  Speaker 1: But here's why.
• 37:55
  Speaker 3: Here's the sort of interesting academic thing. But I think
• 37:58
  Speaker 3: for many people who who click on these adlines, who
• 38:01
  Speaker 3: see them, actually it does make them feel really bad,
• 38:06
  Speaker 3: and it does make them worry about behaviors which are
• 38:10
  Speaker 3: which they're already taking. You know, I let my kid
• 38:12
  Speaker 3: watch a screen and is it my fault that you know?
• 38:15
  Speaker 1: They have ADHD?
• 38:16
  Speaker 3: It's such a common question, and so it's not free
• 38:20
  Speaker 3: these things. This is not just an academic debate once
• 38:22
  Speaker 3: it gets out into the world.
• 38:25
  Speaker 5: So your your statement makes me think of a like
• 38:29
  Speaker 5: a research question, which is, you know, I think the
• 38:33
  Speaker 5: journals and the people who write these articles probably view
• 38:35
  Speaker 5: these articles as being costless, meaning that there's no cost
• 38:39
  Speaker 5: imposed on society from generating this kind of knowledge. But
• 38:42
  Speaker 5: what if you did a study where you showed that
• 38:46
  Speaker 5: if there is a paper that comes out that shows
• 38:49
  Speaker 5: some purported link between autism or ADHD or something, you know,
• 38:56
  Speaker 5: where we don't have a good firm understanding of what's
• 38:57
  Speaker 5: causing it, and it links it to a very common
• 39:00
  Speaker 5: behavior or common thing that people might do. I wonder
• 39:05
  Speaker 5: if you see, like in the weeks or months following that,
• 39:08
  Speaker 5: you see you know, increased diagnoses of anxiety or depression,
• 39:15
  Speaker 5: or increased prescription fills among mothers versus of young children
• 39:20
  Speaker 5: who have that condition versus mothers of young children who
• 39:23
  Speaker 5: do not have that condition, or something like that. You
• 39:25
  Speaker 5: have to find something that was really splashy that got
• 39:27
  Speaker 5: people like, oh my goodness, could this possibly be true?
• 39:31
  Speaker 5: But if your sort of hypothesis is right, which I
• 39:34
  Speaker 5: totally think it is. I mean, you see studies like
• 39:36
  Speaker 5: this and you think, oh, what did I do wrong?
• 39:38
  Speaker 5: You didn't want to do anything wrong? Yeah, what I
• 39:40
  Speaker 5: do wrong? It's a paralyzing feeling, I think for a parent.
• 39:44
  Speaker 5: So it would be great to do that, to show
• 39:46
  Speaker 5: that these studies have impact. It's not you know, maybe
• 39:49
  Speaker 5: coffee and you know, heart attacks is not a good
• 39:53
  Speaker 5: one because no one's really going to feel bad, but
• 39:54
  Speaker 5: they're probably.
• 39:56
  Speaker 3: Tail and all and autism Thailand. I mean, it's like
• 39:59
  Speaker 3: a bunch of these things where I hear about them
• 40:01
  Speaker 3: a lot.
• 40:03
  Speaker 2: Or vaccine related things. Yeah, you know, like you know,
• 40:06
  Speaker 2: you know what you know?
• 40:07
  Speaker 5: What is the cause of effect of vaccines on various
• 40:09
  Speaker 5: different or COVID nineteen vaccine of various different outcomes? If
• 40:12
  Speaker 5: your child had some outcome and you ascribed it to
• 40:15
  Speaker 5: a vaccine, your view of vaccines might be different. Your
• 40:20
  Speaker 5: views of the federal government might be different after that,
• 40:23
  Speaker 5: for reasons that were sort of totally unfounded and would
• 40:27
  Speaker 5: never have entered your mind had that kind of study
• 40:29
  Speaker 5: not been published.
• 40:32
  Speaker 1: Okay, to close, can you please tell us your result.
• 40:34
  Speaker 1: I'm dying.
• 40:35
  Speaker 5: Wow, Now I kind of feel bad because you're going
• 40:37
  Speaker 5: to see there's a link between what I literally just
• 40:39
  Speaker 5: said and what I'm about to say.
• 40:41
  Speaker 2: All right, but that's life, all right, So let me
• 40:44
  Speaker 2: just frame it about it.
• 40:45
  Speaker 5: There was a study I don't know, maybe ten years ago,
• 40:49
  Speaker 5: a long time ago, which looked at taxi cab drivers
• 40:52
  Speaker 5: in London and it showed that a particular part of
• 40:58
  Speaker 5: the brain called the hippocampus is enlarged in an enhancing
• 41:04
  Speaker 5: way in these drivers. And the reason why is because
• 41:07
  Speaker 5: they had to memorize all these streets they're driving around.
• 41:09
  Speaker 5: There is actually a test that they had to take
• 41:11
  Speaker 5: called the Knowledge and the idea was that because of
• 41:13
  Speaker 5: the hippocampus is involved in spatial processing and spatial recognition,
• 41:19
  Speaker 5: that that part of the brain becomes stronger, for lack
• 41:22
  Speaker 5: of better words, just like if you exercise certain parts
• 41:24
  Speaker 5: of your body, they'll become stronger. Same intuition. The hippocampus
• 41:28
  Speaker 5: has also been implicated in Alzheimer's disease. Now the study
• 41:33
  Speaker 5: that's coming out and it's coming out in the British
• 41:36
  Speaker 5: Medical Journal in a.
• 41:36
  Speaker 2: Couple of weeks.
• 41:38
  Speaker 5: We use this data that you're probably familiar with, where
• 41:41
  Speaker 5: death certificates in the United States have recently been linked
• 41:44
  Speaker 5: to occupation. So we're looking at these data and what
• 41:47
  Speaker 5: kind of questions can we answer? And I think about
• 41:50
  Speaker 5: this study in London taxicab drivers a long time ago,
• 41:55
  Speaker 5: and I'm like, well, I wonder what if we look
• 41:57
  Speaker 5: at taxicab drivers in the United States. What is you know,
• 42:01
  Speaker 5: what do rates of Alzheimer's dementia look like in taxicab
• 42:04
  Speaker 5: drivers as a cause of death compared to every other occupation.
• 42:08
  Speaker 5: And so we look at something like four hundred and
• 42:10
  Speaker 5: fifty occupations, and taxicab drivers and ambulance drivers not like EMTs,
• 42:16
  Speaker 5: but ambulance drivers who are just literally doing the same thing.
• 42:19
  Speaker 5: They have to drive all different places, they don't know
• 42:21
  Speaker 5: where they're going, they have to memorize these roads. They
• 42:24
  Speaker 5: have the two lowest rates of Alzheimer's related dementia contributing
• 42:28
  Speaker 5: to mortality than all other occupations, and we show that
• 42:34
  Speaker 5: they have No, they're not lower in terms of other
• 42:37
  Speaker 5: forms of dementia that are not thought to be related
• 42:39
  Speaker 5: to sort of hippocampus or what we call Alzheimer's disease.
• 42:43
  Speaker 5: And so it's a very strange finding. And of course
• 42:47
  Speaker 5: we're not going to come out and say you should
• 42:50
  Speaker 5: become a taxi cab driver. We're not going to come
• 42:52
  Speaker 5: out and say you should stop using Google Maps.
• 42:55
  Speaker 3: I think the headline here is is, like, you know,
• 42:58
  Speaker 3: using Google Maps dementia.
• 43:01
  Speaker 1: That's the headline I would go with.
• 43:02
  Speaker 5: And I've already shortaged stocks for Google or alphabet whatever.
• 43:05
  Speaker 2: It's called an anticipation of this.
• 43:07
  Speaker 5: But like you know, we literally one of the last
• 43:09
  Speaker 5: lines to say is you know, we view this as
• 43:12
  Speaker 5: just generating a hypothesis. It's an idea. Think more about
• 43:16
  Speaker 5: how you might study this in a more causal way.
• 43:19
  Speaker 2: We don't.
• 43:19
  Speaker 5: We're not arguing that this is causal. We're not using
• 43:22
  Speaker 5: causal language. We're just saying it's an idea, a really
• 43:26
  Speaker 5: strange idea. And so I think that, like there is
• 43:29
  Speaker 5: space for correlational studies that are a answering interesting questions that
• 43:35
  Speaker 5: have not been already published on fifty times before in
• 43:38
  Speaker 5: the last two years. So there is space for those
• 43:40
  Speaker 5: studies if they're a answering or looking for interesting relationships
• 43:45
  Speaker 5: that haven't previously been studied, and b not claiming more
• 43:50
  Speaker 5: than what they're claiming and saying, look, here's what here's
• 43:52
  Speaker 5: what it makes us think about, here's how we should
• 43:55
  Speaker 5: look at this further. I think those kinds of things
• 43:57
  Speaker 5: are useful.
• 43:57
  Speaker 3: Yeah, And I think from this there's like a million
• 44:00
  Speaker 3: sort of quite interesting studies one could think about doing
• 44:03
  Speaker 3: that would dial more into causality.
• 44:06
  Speaker 1: Like the thing the obvious thing that comes to mind.
• 44:07
  Speaker 3: For me is, you know, randomly in like basically fMRI,
• 44:13
  Speaker 3: put people in an fMRI machine and then you know,
• 44:16
  Speaker 3: have them do two months in which they do some
• 44:19
  Speaker 3: training on you know, different kinds of maps and sort
• 44:23
  Speaker 3: of like linking this to some of these this research
• 44:25
  Speaker 3: questions around you know, can we encourage people to stay
• 44:28
  Speaker 3: undamented by like pushing their brain in various ways?
• 44:32
  Speaker 5: Yeah, yeah, looking at that and then maybe doing memory
• 44:34
  Speaker 5: assessments of these individuals. I mean, there's all sorts of
• 44:37
  Speaker 5: ways that you could do this, and to be honest,
• 44:40
  Speaker 5: probably none of them would work, but that that's totally fine.
• 44:43
  Speaker 5: But it's just sort of at least it's a different
• 44:46
  Speaker 5: idea than what we see.
• 44:51
  Speaker 1: I love it, Thank you, Bapu. I really love having you.
• 44:55
  Speaker 2: I love being here. Thank you. It feels like just yes, sir.
• 45:11
  Speaker 3: Parent Data is produced by Tamar Avishai with support from
• 45:14
  Speaker 3: the Parent Data Team and PI Rex. If you have
• 45:17
  Speaker 3: thoughts on this episode. Please join the conversation on my
• 45:20
  Speaker 3: Instagram at prof Emily Oster, and if you want to
• 45:24
  Speaker 3: support the show, become a subscriber to the parent Data
• 45:27
  Speaker 3: newsletter at parentdata dot org, where I write weekly posts
• 45:30
  Speaker 3: on everything to do with parents and data to help
• 45:33
  Speaker 3: you make better, more informed parenting decisions. And just for fun,
• 45:38
  Speaker 3: I'd encourage you to go to our website and just
• 45:40
  Speaker 3: search for panic headlines. The articles that come up run
• 45:44
  Speaker 3: the gamut from whether you should worry about lead in
• 45:46
  Speaker 3: your tampons or white noise or breast pump bacteria or microplastics,
• 45:51
  Speaker 3: and after digging into the data, the answer is almost
• 45:54
  Speaker 3: always no. Cut yourself some slack at parent data dot org.
• 46:00
  Speaker 3: There are a lot of ways you can help people
• 46:02
  Speaker 3: find out about us. Leave a rating or a review
• 46:04
  Speaker 3: on Apple podcasts, Text your friend about something you learned
• 46:07
  Speaker 3: from this episode. Debate your mother in law about the
• 46:10
  Speaker 3: merits of something parents do now that is totally different
• 46:13
  Speaker 3: from what she did. Closet a story to your Instagram,
• 46:16
  Speaker 3: demunking a panic headline of your own. Just remember to
• 46:19
  Speaker 3: mention the podcast too, Write penelpe right, mom, We'll
• 46:23
  Speaker 1: See you next time.