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[00:04] spk_0: welcome to science pods, where researchers share the stories behind their science. In this podcast, we hear from Emily Ho about recent research on painful truth or blissful ignorance to get started. We were curious to hear Emily's story of becoming a researcher.
[00:31] spk_1: My name is Emily Ho. I am a PhD student at Fordham, and in the summer I'll be joining Northwestern University School of Medicine and the Department of Medical Social Sciences. As a research assistant professor, I did my undergraduate studies at N Y U in downtown Manhattan, where I grew up. Sometime in the middle of my undergrad studies, I got really interested in the measurement of psychology. All of this psychological phenomenon is kind of swirling around us. And how do we sit down and actually quantify it and measure things that you know we can't measure? You know, if I were toe, ask you how tall you were, it be easy to just pull out of Ruler and give you a number. But with things that are a bit more abstract, like depression, or you know how introverted you are, it could be a little harder to do that. And that's where the field of quantitative psychology comes in where people develop models and scales to try to measure precisely things that are maybe not so precise. I decided to pursue my graduate studies at Fordham, which conveniently is also New York and also has a program in psycho metrics and quantitative psychology. And that's where I am.
[01:52] spk_0: Research studies rarely start out with the questions readily in hand. From the science lab to the pub. The paths that researchers take leading up to a study are as unique as the researchers themselves. So we asked, How did this study come about?
[02:13] spk_1: You know, there's obviously the literature, but there's also me and my two co author, George Lowenstein and David Hagman, and we were just kind of talking about how this deferred by ourselves like, Oh, if you were avoider, do you avoid information or whatever? And David was, Oh, I'm a total information seeker. I would want information, even if it hurts my feelings or whatever. And George said, Oh, I'm a total ostrich, right? I bury my head in the sand when the news is bad and that's it, and I like I thought I was somewhere in the middle and so we thought this was interesting because, you know, 33 of us with really different views. That's how this the conventional I'm going to say conventional with a quotation mark here, knowledge in in the literature, particularly the economics literature, is given that information is free. Assuming it is, I should say, because it's not always free, assuming that information is free and that it's easy to obtain, Why shouldn't you get it? Even if it doesn't change your decision making in any way you should always get? You know what's free kind of guided by this conventional wisdom. The standard argument in the literature is there's no one that's information avoidant right, Or if it is, it's just noise in the experiment. And so we shouldn't account for people's information preferences at all Well, in the last maybe 10 years, there's been a lot of empirical evidence, ah, lot of studies and experiments showing that when really people are faced with a real life decision to obtain really important information that they choose not to get it So an example is the study by Emily Oster, who's a health economist at Brown, where she basically samples all these people who have a risk of having Huntington's disease on Huntington's disease is this neurodegenerative disease that if one of your parents have it, you have a 50% chance of getting it yourself. And if you have it, it's basically a very debilitating disease with really early onset symptoms. And she samples all these people who have a chance of getting it, and she finds that most of them the overwhelming majority 93% of them don't want to get the information from this test. So that's a pretty big piece of evidence showing that there is information avoidance. It is prevalent, and it might have really, uh, long term consequences kind of how this idea starts.
[04:35] spk_0: To understand the findings of any research, you have to begin with the methods applied by the researcher. With this in mind, we asked Emily how this study was conducted. We will hear Emily's response after this short message. This episode is
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[05:02] spk_0: your research here again is Emily How
[05:11] spk_1: we wanted to test a few things. One was we wanted toe basically test this scenario based approach to writing items and see whether it could actually predict a real world outcome. Literally, a person has theocracy in to decide whether they want information or not, and then they can either choose to be forwarded to the site or not. So that was like sort of a test of the novel psychometric framework that we used. And then we also wanted to see whether these items, whether they could only predict health or finance or social decisions and whether it could predict other things as well. And so the because some of the behavioral economists I was working with were interested in economics issues. We chose political outcomes and climate change and, you know, things of that type we wanted to provide, like, a really robe bus test of the methodology and also of our scale. So that's one thing. And then the second thing that we did was right around the time we were designing this last study, we chanced upon in the literature a scale that was literally called establishing and information avoidance scale that had been published super recently, and we were like, Oh, no, you know, we saw the title and said, You know, have have our efforts been for nothing on eso We read it. They were like attitudinal measures. When it comes to X, I would rather not know this or ignorance is bliss but blah blah on. And so we said, Well, obviously we have to put thes items to the test as compared with our scale, so sort of it provided, actually a very neat test of the methodology and its predictive validity.
[06:54] spk_0: Having collected the data, we were curious to hear more about how the data were analyzed and what they showed.
[07:06] spk_1: So in our study, we do find that when we administer the same scale over a span of a month, either two weeks or a month, that people's responses are essentially the same. So we know that it's at least reliable up to a month, although I'm sure it's longer. I think some people just have very strongly held beliefs that are very difficult to shake, even in the face of a lot of evidence. There's sort of some some things in the literature that suggests that even if you are, you're given information. Sometimes that could even backfire and kind of make you even more convinced of your beliefs, even if you're given something to the contrary. So that's a very interesting psychological phenomenon we don't know that much about yet. And I think it's a harder question to answer about. Well, you know, we did sort of established that information preference seems to be a distinct trait that sort of stable over time. I shouldn't say sort of stable it a stable over time, but that we also say that it differs by domain. So and we show that with the exploratory factor models that you know, the same people who avoid health information isn't the same people who avoid finance information and like, Why is that and is that stable over time? And that's totally an open question. It's definitely very context specific. There hasn't been a lot of work done on the specific contexts in which people will avoid information. I don't know if the story is a simple as it makes me feel bad, so I'll avoid it because they're definitely issues where just to give you a really funny example. People watch depressing movies all the time, right, and they watch depressing movies, sometimes knowing exactly how depressing it's going to be and why did they finish and wait until the end? So that's that's an interesting kind of ruffle in the hole landscape of how we consume information and things like that.
[08:57] spk_0: Research results routinely have both expected and unexpected implications. This lead us to wonder what Emily believes will be the influence of this work,
[09:12] spk_1: the boundaries of when people avoid information when they don't how this triangulate with whether more information makes us happier or less happy, and when we need to kind of trade off happiness and practicality and and things like that. Of course I'm not an economist by training, so I don't know that sort of thing. But that's super interesting to me. We used to think that all you have to do is give people information, and that's it. But it's, ah, it's a bit more complicated than that when, like you get your you get in the way of yourself. You know, sometimes there one could argue right that its strategic, too, because CASS Sunstein has this great example of popcorn world. Well, you know, they start putting calorie labels on everything, and then you go to the theater and you really want popcorn, and then you look at the calories and then you're watching your movie without popcorn and you're just a lot less happy. And was the information a good thing or not? Right, Like you walk out of the theater and you're a lot less satisfied. And maybe it would have been better for you not to know the calories, you know, And you would have, you know, had a much better experience at the theater, so I that, you know, that's interesting as well. To me,
[10:20] spk_0: that was Emily Ho discussing recent research on painful truth or blissful ignorance. You can learn about this research, download a copy of this podcast or read the transcript at science pods dot com. We hope that you enjoy this science pods podcast. You can listen to other podcast at science pods dot com, where you can also subscribe to get new podcast delivered to your podcast player. If you have recently conducted research and want to share it with the world, whether it is in press on a pre print service or already published. You can create your science pod podcast in just a few minutes. Just visit science pods dot com to get started.