Speaker 1: Welcome to tech Stuff, a production from iHeartRadio. Hey there,
Speaker 1: and welcome to tech Stuff. I'm your host, Jonathan Strickland.
Speaker 1: I'm an executive producer with iHeart Podcasts and how the
Speaker 1: tech are you? So today I thought I would talk
Speaker 1: about something that hits a bit close to home, which
Speaker 1: is the relationship between social media, social networks, and mental health.
Speaker 1: This is a very complicated topic for a whole bunch
Speaker 1: of reasons. I mean, for one thing, just to be
Speaker 1: transparent with all of y'all, I'm a gen xer, okay.
Speaker 1: I grew up in an era in which there was
Speaker 1: a pretty darn hefty stigma attached to all things mental health,
Speaker 1: Like if you had mental health struggles, the feeling was
Speaker 1: that somehow that was your fault and a failing of
Speaker 1: you personally. So to this day, while I recognize the
Speaker 1: importance of mental health and seeking help when you're struggling,
Speaker 1: like when a friend of mine tells me, oh, I
Speaker 1: found this awesome therapist, I'm so happy for them, it's
Speaker 1: still a barrier for me, which is screwed up. Like rationally,
Speaker 1: I can recognize it as being important, and I can
Speaker 1: be happy for my friends to seek that health and
Speaker 1: yet I still have the blocks, the mental blocks that
Speaker 1: are rock solid when it comes to my own mental health,
Speaker 1: which kind of stinks, Like it really stinks when you
Speaker 1: are trying to think of things rationally and you still
Speaker 1: encounter this because you're like, Okay, some things go beyond rationality.
Speaker 1: I have to admit that. But apart from my own
Speaker 1: personal reasons, it's a tricky topic because it's really hard
Speaker 1: to be definitive about things that relate to mental health.
Speaker 1: There are all different types of human beings out there
Speaker 1: in the world, and there's stuff that could roll right
Speaker 1: off the back of one person but really traumatically impact
Speaker 1: someone else, and it often can be really different, dificult
Speaker 1: to determine a causal relationship between different factors. Now by that,
Speaker 1: I mean there are a ton of studies out there
Speaker 1: that have looked into the potential impact of social media
Speaker 1: on mental health. For example, a study might find that
Speaker 1: people who identify as being depressed or experiencing anxiety might
Speaker 1: be spending a lot more time on social media sites
Speaker 1: than people who do not identify as that. But does
Speaker 1: that mean the social media sites are causing this anxiety
Speaker 1: and depression that by staying on these sites that's what's
Speaker 1: making people feel anxious and depressed. Or could it mean
Speaker 1: that people who are already experiencing anxiety and depression are
Speaker 1: seeking out social media sites. You know, maybe that's a
Speaker 1: coping mechanism for them. In other words, it's the old
Speaker 1: phrase correlation is not causation. Just because two things appear
Speaker 1: to happen together doesn't mean that one caused the other.
Speaker 1: They could be unrelated. They could both be caused by
Speaker 1: the same common factor. We just don't know without looking
Speaker 1: into it further. So today I thought, you know what,
Speaker 1: I'm going to actually go through one of these studies.
Speaker 1: Because I've talked about studies in general, but typically I'm
Speaker 1: reading about an article that's written about the study. I'm
Speaker 1: not reading the study itself. So I found a study
Speaker 1: from twenty twenty that was a sort of meta analysis
Speaker 1: on the subject of mental health and social networking sites. Now,
Speaker 1: if you are unfamiliar with the term meta analysis, that
Speaker 1: is a type of study that looks at the results
Speaker 1: of other studies in order to reach some conclusion. So
Speaker 1: you might say, all right, let's take these thirty studies
Speaker 1: about this one topic. Really look at what the conclusions
Speaker 1: are of all of them and see if we can
Speaker 1: use that to draw new conclusions. So in this case,
Speaker 1: the researchers of this particular study, they identified fifty papers
Speaker 1: about social media and mental health using Google scholar. By
Speaker 1: the way, when they did the search terms for things
Speaker 1: like mental health and social media and social networking, they
Speaker 1: came up with tens of thousands of papers. Even with
Speaker 1: social media and mental health together, it was like eighteen
Speaker 1: thousand papers. From that group, they got fifty, and from
Speaker 1: that list of fifty, they paired the list down to
Speaker 1: sixteen studies. They had a whole process for reviewing these
Speaker 1: papers and determining whether or not they fit within their
Speaker 1: own study. And as you can see, with sixteen, that
Speaker 1: means fewer than half of those fifty made it through. Eight.
Speaker 1: Of those studies that they'd considered. They were cross sectional studies.
Speaker 1: That means it's a study where they analyzed data, or
Speaker 1: the original researchers analyzed data from a group of subjects
Speaker 1: at a single point in time, so it's like a
Speaker 1: cross section of time. That made up half of the
Speaker 1: papers that they were looking at. Two of the sixteen
Speaker 1: were qualitative STUF studies. That means they were looking at
Speaker 1: non quantifiable information and trying conclusions from that. So, in
Speaker 1: other words, these studies look at stuff like social phenomena,
Speaker 1: which you cannot really measure with scientific units. Right, if
Speaker 1: you're measuring, like in chemistry, you're using units of like
Speaker 1: weight and volume, those are quantifiable. You can put actual
Speaker 1: units of measurement to them. If you're saying how happy
Speaker 1: is society, that's not really quantifiable. That's qualitative, not quantifiable.
Speaker 1: So those were the kinds of studies for two of
Speaker 1: the sixteen papers that they chose. It's tricky to do
Speaker 1: a qualitative analysis because you're still trying to come to
Speaker 1: a scientific conclusion, but you're using unquantifiable factors to do so.
Speaker 1: So they get a little whibbly wobbly, and a lot
Speaker 1: of this stuff falls into fields like sociology, which, by
Speaker 1: the way, I love sociology is one of my favorite
Speaker 1: classes when I was in college. But sociology is by
Speaker 1: its nature difficult to grow because of a lack of
Speaker 1: quantifiable units. Anyway, three of the remaining studies were longitudinal studies.
Speaker 1: That means they explored the same list of variables and
Speaker 1: how those variables changed over a long period of time.
Speaker 1: So this is like if you have a group of
Speaker 1: subjects and you are observing them periodically over a long
Speaker 1: course like potentially years. The remaining studies were systematic, meaning
Speaker 1: they looked at patterns that would indicate cause and effect.
Speaker 1: Are there recognizable and reliable patterns so much so that
Speaker 1: should you start to see one thing, you would immediately
Speaker 1: begin to draw conclusions that a pattern exists, even if
Speaker 1: it's not readily evident at the time. One of the
Speaker 1: really big challenges of meta analyses is that you have
Speaker 1: to try and synthesize the findings of different studies that
Speaker 1: are all using totally different methodologies, and you do this
Speaker 1: while you're trying to draw your own conclusions. That's pretty
Speaker 1: tough because you might accidentally misinterpret findings in an effort
Speaker 1: to reach the conclusion you've already made. Or you might
Speaker 1: pair two different papers together to say these papers support
Speaker 1: one another, but because they're different methodologies, it may not
Speaker 1: be as clear as that. Right. If the methods were
Speaker 1: totally different, then yeah, the conclusions might be similar, but
Speaker 1: you might not be able to say this study supports
Speaker 1: this other study because they they took such different pathways
Speaker 1: to get there. You can't be sure that they are
Speaker 1: actually saying the same thing, and there's bias that you
Speaker 1: have to deal with. Everybody has bias, and suppressing bias
Speaker 1: is important. It's also really hard to do. Sometimes it's impossible.
Speaker 1: You likely are going to have your own bias when
Speaker 1: you go into a study, like you might already have
Speaker 1: a preconceived idea of something that you're just expecting to prove.
Speaker 1: So that will make you pay more attention to the
Speaker 1: things that really reinforce your bias and potentially dismiss or
Speaker 1: discount things that are not aligned with your bias unless
Speaker 1: it gets to a point where it's just overwhelmingly impossible
Speaker 1: to ignore. So this gets into things like cherry picking,
Speaker 1: right where you're cherry picking the points of data that
Speaker 1: support your perspective or your argument. Now, I'm not saying
Speaker 1: that all meta analyzes are bad. I'm just saying they're
Speaker 1: tricky to do and they're easy to do poorly, So
Speaker 1: they're not bad just out of the gate, but they
Speaker 1: are hard to do well. And obviously your conclusions are
Speaker 1: only as reliable as the individual studies are. Like, you
Speaker 1: could do a fantastic meta analysis, but if all the
Speaker 1: studies that are part of your meta analysis are crap,
Speaker 1: then the results of your meta analysis aren't reliable either.
Speaker 1: Garbage in, garbage out kind of thing. So that's why
Speaker 1: that selection process was important. So while they only use
Speaker 1: six out of fifty papers that they selected out of
Speaker 1: a larger like eighteen thousand potential papers, you can at
Speaker 1: least say, well, they had a process there to try
Speaker 1: and weed out things that would either be a bad
Speaker 1: fit or were poorly designed. So this paper, I haven't
Speaker 1: even mentioned the title yet. Here's the title. You can
Speaker 1: look this up and read it yourself. It's social Media
Speaker 1: Use and its Connection to Mental health, a systematic review.
Speaker 1: And this was by a collection of authors. There's like
Speaker 1: six or seven authors attached to this. I found it
Speaker 1: by using the National Library of Medicine when I was
Speaker 1: looking for a paper to talk about, and it was
Speaker 1: originally published in a web based peer reviewed medical journal
Speaker 1: called Curious. Now let's cur eus. We're going to get
Speaker 1: to the paper in a second, and I'll also have
Speaker 1: more to say about Curious at the end of this episode, because,
Speaker 1: as it turns out, Curious has its own curious reputation.
Speaker 1: I'm not saying it's a bad paper, but I am
Speaker 1: saying like it is a matter of debate among the
Speaker 1: research circle, and yeah, I kind of tripped into that
Speaker 1: one without anticipating it. So first, before we get to
Speaker 1: the actual paper, I think it is important to establish
Speaker 1: the connection between socialization in general and mental health. Human
Speaker 1: beings are social animals, even though some days I feel
Speaker 1: like I should just run off to be a hermit
Speaker 1: in the woods. Some days, y'all, that compulsion is a
Speaker 1: strong one. So in a different scientific paper by Deborah
Speaker 1: Umberson and Jennifer carraz Montez title Social Relationships and Health
Speaker 1: a Flashpoint for Health Policy, there is a very powerful
Speaker 1: statement that I wanted to share. Quote Captors use social
Speaker 1: isolation to torture prisoners of war to drastic effect. Social
Speaker 1: isolation of otherwise healthy, well functioning individuals eventually results in
Speaker 1: psychological and physical disintegration and even death. In quote, that
Speaker 1: is a heck of a way to argue for the
Speaker 1: power of socialization, because when we are deprived of socialization,
Speaker 1: we suffer. Generally speaking, studies show that the quantity and
Speaker 1: quality of our social relationships have an enormous impact on
Speaker 1: our well being, both mental health and physical health. People
Speaker 1: who maintain more and high quality social relationships tend to
Speaker 1: live longer and healthier than those who do not. So,
Speaker 1: you know, for being someone who has very few friends
Speaker 1: at this point, like I don't hang out with very
Speaker 1: many people at all, I look at this and I
Speaker 1: think I need to get out there more and actually
Speaker 1: for meaningful friendships, not just be like, hey, how's it going,
Speaker 1: what's your sign? Nice to see you come here. Often
Speaker 1: like to actually get meaningful relationships because they are very
Speaker 1: important to our health. So there is strong evidence supporting
Speaker 1: a link between socialization in general and mental health. There's
Speaker 1: lots of research that says that it's an important factor
Speaker 1: for our mental health. Is this aspect of socialization not
Speaker 1: that people who are kind of loaners or whatever are
Speaker 1: mentally unwell, that's not necessarily the case. But generally speaking,
Speaker 1: we tend, we humans tend to do better when we
Speaker 1: have good socialization. Now let's move on to social networks. Now.
Speaker 1: I'm sure some of y'all out there are old enough
Speaker 1: like me to remember a time before there were really
Speaker 1: online social networks, or at least a time before we
Speaker 1: had sites that served purely as a social network. I
Speaker 1: think back to the bulletin Board System or BBS days
Speaker 1: and I can remember logging into a service and skimming
Speaker 1: the message boards, and these BBSs often existed on a
Speaker 1: single person's computer somewhere. So this wasn't the Internet. You
Speaker 1: weren't logging into a network of networks. You were literally
Speaker 1: dialing into a computer that hosted this bulletin board. Now
Speaker 1: that computer might link to other computers and share a
Speaker 1: message board between them, which increased the reach of the
Speaker 1: bulletin board system, but it still wasn't the Internet yet,
Speaker 1: not for the average person, but for a lot of folks,
Speaker 1: it was a preview of what the Internet would be.
Speaker 1: It was just on a much smaller scale, kind of
Speaker 1: think of like a community bulletin board version of the Internet.
Speaker 1: And back in those days, a lot of folks, myself included, thought, Wow,
Speaker 1: this technology is going to transform the world. We're going
Speaker 1: to be able to communicate with each other instantly, no
Speaker 1: matter where in the world we happen to be. We'll
Speaker 1: be able to find people who share our interests and
Speaker 1: make friends in brand new ways. It is going to
Speaker 1: be amazing. In fact, I'm going to tell you another
Speaker 1: story to sort of illustrate this Before I get to that. However,
Speaker 1: let's take a quick break to thank our sponsors. Okay,
Speaker 1: so before the ad break, I promised y'all a story.
Speaker 1: So when I was a kid, I loved fantasy novel
Speaker 1: I mean I still do, but I don't read them
Speaker 1: as much as I used to because I read a
Speaker 1: lot of other stuff now. But when I was a kid,
Speaker 1: I wasn't really into science fiction very much. I mean
Speaker 1: I liked some science fiction movies and television shows, but
Speaker 1: I didn't read science fiction books. I loved fantasy novels.
Speaker 1: I knew precisely three other kids in my personal life
Speaker 1: who also liked fantasy novels to various degrees. So our
Speaker 1: tiny little social group of four people kind of helped
Speaker 1: us get through the experiences of like middle and high
Speaker 1: school because none of us fit in particularly well with
Speaker 1: the rest of the student body. I wouldn't say we
Speaker 1: were like ostracized or ridiculed or anything. I mean, maybe
Speaker 1: we were, but I wasn't aware of it, which is
Speaker 1: probably for the best. But like, I just didn't integrate
Speaker 1: well with the main student body, not being so savvy
Speaker 1: with things like mainstream entertainment or sports or any of that. However,
Speaker 1: you know, there was something special about my childhood that
Speaker 1: my friends lacked, and that was that my parents write
Speaker 1: science fiction and fantasy and horror and mysteries and other
Speaker 1: types of fiction. They are published authors. My father has
Speaker 1: written more than a hundred published works at this point
Speaker 1: in that field in fiction. And one way that my
Speaker 1: parents would promote their work it was really my dad.
Speaker 1: At this point. Mom would also write, but that was
Speaker 1: later on. Dad would go to different regional science fiction
Speaker 1: and fantasy conventions where fans would come together and they
Speaker 1: would hang out and party and have a great time
Speaker 1: for a weekend. These conventions had names like Dixie Trek,
Speaker 1: Dixie Dixie Trek, or Phoenix Con. Atlanta is known as
Speaker 1: the City of the Phoenix, or the Atlanta Fantasy Fair.
Speaker 1: That was a really big one. So these days, the
Speaker 1: really big one in the Southeast is Dragon Con. And
Speaker 1: in fact, my dad was the first toastmaster Dragging when
Speaker 1: it first got started. And it was at these science
Speaker 1: fiction and fantasy conventions that I saw the power of community.
Speaker 1: So in the quote unquote real world, a fantasy novel
Speaker 1: geek could end up feeling pretty darn isolated in those days,
Speaker 1: but at these conventions I would become part of an
Speaker 1: enormous community of fans, so you could go to panel
Speaker 1: discussions about your favorite book where people would talk about
Speaker 1: fan theories or discuss certain works in depth, or sometimes
Speaker 1: you might even get a chance to hear the author
Speaker 1: himself or herself speak, And everything was a celebration of
Speaker 1: the geeky interests for the most folks attending, I mean,
Speaker 1: it was an experience you just couldn't replicate back home,
Speaker 1: because there just weren't enough people you knew in your
Speaker 1: everyday life where you could have these kinds of interactions.
Speaker 1: These conventions were special. They gave fans a place in
Speaker 1: time to really engage in their interests and to celebrate them.
Speaker 1: So early on the Internet seemed to be shaping up
Speaker 1: in a way that it could do this, but through computers. Right,
Speaker 1: that could involve creating, you know, communities that celebrate specific
Speaker 1: interests online, and you wouldn't be restricted to just attending
Speaker 1: a convention one weekend out of the year in order
Speaker 1: to get together with friends and talk about, you know,
Speaker 1: the latest episode of Quantum Leap or whatever. Now you
Speaker 1: could go online and join a forum dedicated to your
Speaker 1: favorite show or movie or book series or whatever. And
Speaker 1: if there wasn't one, out there, you could make one
Speaker 1: and folks would find it. Now way back in the day,
Speaker 1: I remember joining a forum called the Bronze, and it
Speaker 1: was a community that celebrated the television series Buffy the
Speaker 1: Vampire Slayer, and I ended up meeting up a bunch
Speaker 1: of other fans that way, including someone who ultimately went
Speaker 1: on to write for the series Angel, which spun off
Speaker 1: of Buffy. I met some of the musicians who provided
Speaker 1: music for the show's soundtrack. I even ultimately ended up
Speaker 1: meeting some of the actors, writers, and directors of the series.
Speaker 1: So first I met them online and then later I
Speaker 1: met them in person. It was great. So for a
Speaker 1: while it seemed like the Internet and the Web in particular,
Speaker 1: we're going to revolutionize the way we socialize with one another,
Speaker 1: and a lot of us who were optimists thought that
Speaker 1: we might be able to form really deep, meaningful relationships
Speaker 1: online and that would be just as important and relevant
Speaker 1: and deep and meaningful as the relationships we had out
Speaker 1: in the quote unquote real world. It ended up being
Speaker 1: true for me. I mean, I met my partner online
Speaker 1: way back in the nineteen nineties and we're still together
Speaker 1: thirty years later. But social platforms would end up introducing
Speaker 1: a lot more than just a way to connect with
Speaker 1: other people. I don't think the optimists out there took
Speaker 1: into account the development of recommendation algorithms, for example. So
Speaker 1: the algorithm's job, when you really get on to it
Speaker 1: is to convince you to stay on the platform for
Speaker 1: as long as possible, to hold your attention as long
Speaker 1: as it possibly can. So the algorithm is supposed to
Speaker 1: serve up material that you're going to find engaging. Now
Speaker 1: that doesn't mean good, but engaging, because it doesn't matter
Speaker 1: if the stuff you see makes you feel happy or sad,
Speaker 1: or angry or scared or any other specific emotion. That
Speaker 1: doesn't matter at all to the algorithm. What matters is
Speaker 1: that you stay there, You don't leave the page. Preferably,
Speaker 1: you engage with whatever the content is, you know, by
Speaker 1: clicking that you like it, or leaving a comment, or
Speaker 1: perhaps best of all, sharing it with other people. That's
Speaker 1: really the algorithm's job, And the recommendation algorithm is necessary
Speaker 1: because the social networking site is a business. We're the product,
Speaker 1: right The site isn't selling anything to us, apart from
Speaker 1: some sites that offer like a premium experience in return
Speaker 1: for a subscription. Otherwise, these companies make their money through advertising.
Speaker 1: The more valuable the landscape is, the more these sites
Speaker 1: can charge to put ads across that landscape. And if
Speaker 1: the site can assure advertisers that their ads are going
Speaker 1: to match up with appropriate audiences, thus improving the chance
Speaker 1: that folks will actually click through the ad to buy something,
Speaker 1: then they can charge even more for those ads. So again,
Speaker 1: the emotional reaction users have while they're using the service,
Speaker 1: that doesn't matter, because sad people they're worth exactly the
Speaker 1: same amount of money as happy people as long as
Speaker 1: they're staying engaged on the site. If you are happy
Speaker 1: or sad, you're worth the same amount to Facebook. And
Speaker 1: it's easier to find stuff that makes users sad or
Speaker 1: anxious or whatever. Well, naturally, if it's easier to find
Speaker 1: that stuff, that material is going to get served up
Speaker 1: to users more frequently, and you're going to be encountering
Speaker 1: that stuff on a more frequent basis. Now, if you
Speaker 1: contrast that with the early days of social networking sites,
Speaker 1: before they had found a way to monetize their operations,
Speaker 1: then things are drastically different. You often had sites that
Speaker 1: used a much more straightforward approach to content organization. I
Speaker 1: still miss the old days where I could log into
Speaker 1: a site like Facebook and I could just look at
Speaker 1: my friends' posts in reverse chronological order, so all I
Speaker 1: had to do was keep scrolling, and I would eventually
Speaker 1: catch up on what everyone was doing, and I would
Speaker 1: know I had a good idea, like I've seen everything.
Speaker 1: But today, if I go to Facebook, I get a
Speaker 1: hodgepodge of posts from the last several days. They're organized
Speaker 1: in no discernible order, and there's tons of ads peppered
Speaker 1: into boot. All right, now, let's get back to the paper.
Speaker 1: So according to the meta analysis paper that I mentioned
Speaker 1: at the top of the episode, the negative impact of
Speaker 1: social media, or the correlation between social media and the
Speaker 1: mental health problems is apparent. And then that sounds logical.
Speaker 1: I mean, there's like a common sense element to that, right,
Speaker 1: I mean I just explained that the site is designed
Speaker 1: to keep people there as long as possible, and the
Speaker 1: way to do that is to catch and hold their attention,
Speaker 1: and negative stuff can do that fairly effectively. So it's
Speaker 1: no surprise that negative stuff rises to the top and
Speaker 1: that this can have an impact on people. But that's
Speaker 1: still a long way to go from proving there's a
Speaker 1: causal link between social networking use and mental health issues.
Speaker 1: So the paper did share some pretty interesting findings. One
Speaker 1: of those is that a person's age didn't seem to
Speaker 1: affect the impact of social networking use, so whether you
Speaker 1: were old or young, there didn't seem to be much
Speaker 1: of a change there, although a lot of the studies
Speaker 1: would end up focusing on pre adolescent users. Gender, however,
Speaker 1: did seem to have a factor when it came to impact.
Speaker 1: Those who identified as female were, in the words of
Speaker 1: their authors, much more likely to experience a negative impact
Speaker 1: to mental health than those who identified as male. Now,
Speaker 1: I'm not sure how much I should actually trust this
Speaker 1: paper if I'm honest, because as I was reading it
Speaker 1: early on, I found an error in the paper. It
Speaker 1: includes a bar graph that shows gender distribution among the
Speaker 1: various platforms, And so this paper came out in twenty twenty,
Speaker 1: so keep that in mind. But even so, the distribution
Speaker 1: caught me off guard because it flew in the face
Speaker 1: of what I had believed. It doesn't mean that I
Speaker 1: was right and the paper was wrong, but it did
Speaker 1: surprise me. So the one for Twitter was the one
Speaker 1: that really surprised me. Now keep in mind, again, this
Speaker 1: paper came out in twenty twenty. Twitter was still Twitter
Speaker 1: back in those days. And if you had asked me
Speaker 1: in twenty twenty, what do you think the gender distribution
Speaker 1: is on Twitter? I would have guessed it skewed male,
Speaker 1: that there'd be more men on Twitter than women, But
Speaker 1: in fact, it apparently was much more skewed toward females.
Speaker 1: So men made up only thirty eight percent of Twitter
Speaker 1: users according to this study. However, this is where we
Speaker 1: get to the mistake in the bar chart. So the
Speaker 1: chart says that eighty two percent of Twitter users were
Speaker 1: female in twenty twenty. Eighty two percent. Now clearly that's wrong.
Speaker 1: Like if I told you eighty two percent of the
Speaker 1: people on Twitter in twenty twenty were women, you would
Speaker 1: automatically say no, that cannot be right. But even the
Speaker 1: chart itself proves that it's wrong because the two numbers
Speaker 1: are supposed to add up to one hundred right, eighty
Speaker 1: two percent are women, and yet it also says thirty
Speaker 1: eight percent are men. If you add those together you
Speaker 1: get one hundred and twenty percent. So my guess is
Speaker 1: the bar chart should have said sixty two percent women,
Speaker 1: not eighty two. I was surprised to see a mistake
Speaker 1: like that make it all the way through edits into publishing, because, again, curious.
Speaker 1: The journal that published this paper is a peer reviewed journal,
Speaker 1: and typically part of peer review means checking for things
Speaker 1: like stupid mistakes, and yet this one made it all
Speaker 1: the way through into published format. And maybe it's not
Speaker 1: fair to judge a paper purely by a single mistake,
Speaker 1: but that is such a simple, careless error, and one
Speaker 1: that's actually really easy to catch if you're just I mean,
Speaker 1: I was just casually reading this. I wasn't reading this
Speaker 1: as an editor, and I just caught it immediately. Well,
Speaker 1: that raises concerns about the rest of the findings of
Speaker 1: the paper, right, like, if this mistake made it through,
Speaker 1: and it made it through not just the writing, but
Speaker 1: the peer review and the editing processes, and still made
Speaker 1: it through to publishing, how can I count on the
Speaker 1: findings of the rest of the paper. But let's carry on,
Speaker 1: because I had already chosen this one, so I was like, well,
Speaker 1: let's see it through to the grizzly end. So the
Speaker 1: paper actually takes its time getting going, which I appreciate
Speaker 1: it's kind of like me. The researchers justify their work
Speaker 1: by calling out the need for systematic reviews, essentially pointing
Speaker 1: out that social networking sites are still relatively young and
Speaker 1: that as a result, there's not much research information available
Speaker 1: that you can work from, and that their own paper
Speaker 1: stands as a resource mainly for future research like this
Speaker 1: isn't to draw firm conclusions, but rather to help serve
Speaker 1: as a sort of summary for more than a dozen
Speaker 1: studies conducted in the area, so that people who are
Speaker 1: looking into it further are more readily able to identify.
Speaker 1: I don't know how useful that is, honestly, because again
Speaker 1: they also pointed out that when they went through Google
Speaker 1: scholar to look for scholarly works on the subject of
Speaker 1: mental health and social networks, they found like seventeeny eighteen
Speaker 1: thousand hits and if there's that many hits, and then
Speaker 1: they selected fifty, I don't know what criteria they used
Speaker 1: just to select the initial fifty, apart from they wanted
Speaker 1: to avoid duplicates, they selected fifty and narrowed it down
Speaker 1: to sixteen. I'm not sure that that's going to be
Speaker 1: a huge help to future researchers, so I question that
Speaker 1: particular part of the justification. But the research site in
Speaker 1: the paper is interesting and it really runs the spectrum,
Speaker 1: like they summarize what each of the papers are. They
Speaker 1: don't go into a lot of detail about the findings,
Speaker 1: which is interesting to me. There are studies that concluded
Speaker 1: that there's no real link between social media use and
Speaker 1: mental health, which seems to be counterproductive to the point
Speaker 1: the paper was making. Others that were cited found that
Speaker 1: social media could exacerbate mental health problems, so the suggestion
Speaker 1: there was that the issues were already present and the
Speaker 1: use of social media made them worse. Some discovered that
Speaker 1: reading posts correlated more with depression than creating posts, So
Speaker 1: it's not just using social network, but how are you
Speaker 1: using it, Like if you're just doom scrolling, that would
Speaker 1: be associated more with stuff like anxiety and depression, but
Speaker 1: if you are creating that isn't a Few of the
Speaker 1: studies focused on gender and found that people identifying as
Speaker 1: women were more prone to social media addiction than those
Speaker 1: who identified as men. One study titled the Use of
Speaker 1: Social Media by Australian pre Adolescents and its Links with
Speaker 1: Mental Health found that young users of sites like Instagram
Speaker 1: and YouTube reported more body image issues and more eating
Speaker 1: disorders than those who did not use those sites. That
Speaker 1: was something that was really brought to light when the
Speaker 1: Facebook whistleblower came forward a couple of years ago. And
Speaker 1: the paper goes on to explain that many, but not all,
Speaker 1: of the various studies included in their meta analysis indicated
Speaker 1: a correlation between mental health and social media use. I'll
Speaker 1: expand on that further, and then I'll talk more about Curious,
Speaker 1: the journal that this was published in. But first let's
Speaker 1: take another quick break. Okay, we're back. So before that break,
Speaker 1: I was talking about how the various studies, most of
Speaker 1: them were indicating some form of correlation between mental health
Speaker 1: and social media use, which, again, that seems to go
Speaker 1: along with common sense. I think most people, if you
Speaker 1: ask them if they were familiar with social networks at
Speaker 1: any rate, they would probably say, yeah, I think that
Speaker 1: if you use social networks a lot, you're probably dealing
Speaker 1: with some mental health issues, challenges like anxiety and depression. However,
Speaker 1: common sense, it's dangerous to go along with that, right, Like,
Speaker 1: everyone could have this kind of common sense still be wrong.
Speaker 1: It could be that once you look into something purely
Speaker 1: from a scientific approach, the links that were believed to
Speaker 1: be there don't actually exist. I'm thinking of stuff like
Speaker 1: quantum mechanics, Like the world of quantum mechanics is counterintuitive
Speaker 1: because it doesn't behave along the same laws as what
Speaker 1: we experience in the classical world. Like classic physics and
Speaker 1: quantum physics seem to conflict with one another, and it
Speaker 1: can be really hard to grasp certain concepts in quantum
Speaker 1: physics because they run counter intuitive to the way we
Speaker 1: experience the world. So their common sense would fail you
Speaker 1: if you were just to use that to guide your way.
Speaker 1: So again, like while common sense might say, yeah, mental
Speaker 1: health and excessive social networking use are dangerously linked without
Speaker 1: actually studying it, you can't say that definitively. So the
Speaker 1: authors say that a causal relationship is unsupported based on
Speaker 1: the studies at this time. So again they're just kind
Speaker 1: of saying what I said before, which is that, yeah,
Speaker 1: there are these two different factors that appear to be correlated,
Speaker 1: but we can't definitively say one causes the other. So
Speaker 1: more studies are needed, in other words, and these studies
Speaker 1: need to be designed in order to determine if there
Speaker 1: is an actual causal relationship here, or if both mental
Speaker 1: health issues and an increase in social media use are
Speaker 1: perhaps symptoms of something else, or maybe just a comorbidity. So,
Speaker 1: in other words, the findings say pretty much all of
Speaker 1: what I said earlier in this episode, we don't have
Speaker 1: enough information to make a determination. Let's talk about some
Speaker 1: of the problems I have with this study. For one thing,
Speaker 1: I mean, it doesn't say anything ultimately. I mean that's
Speaker 1: kind of unfair, like saying, oh, it doesn't really say anything,
Speaker 1: or it says exactly what everybody already knows, which is
Speaker 1: that we don't know. But what the whole point of
Speaker 1: it was, it was to analyze these other studies and
Speaker 1: to see like if there were any common points that
Speaker 1: supported a more firm stance, And ultimately they found that
Speaker 1: it appears that there is a link between mental health
Speaker 1: and social networking use, but what that link is precisely
Speaker 1: is not possible to be determined at this point. Now,
Speaker 1: I also wanted to talk about Curious, the journal that
Speaker 1: it was published in. It has I would argue a
Speaker 1: bit of a shaky reputation based upon what I have
Speaker 1: seen it is a peer reviewed journal. That is a
Speaker 1: good thing. In general, it's a good thing. Peer review
Speaker 1: is important in that if it's done correctly, then papers
Speaker 1: that have issues are less likely to be accepted and published,
Speaker 1: which means they're less likely to muddy the scholarly output
Speaker 1: of researchers. You want good papers to get published so
Speaker 1: that we continue to build knowledge and not make things
Speaker 1: more murky by including stuff that is unsupported or poorly
Speaker 1: researched or poorly designed, whatever it may be. So you
Speaker 1: want a good, robust peer review process. However, peer review
Speaker 1: is a tricky thing to do. Even really notable papers
Speaker 1: that have really good reputations they have issues with peer review.
Speaker 1: It's tough. The peer review process over it Curious is
Speaker 1: reportedly a very fast one. There's a quick turnaround. Now.
Speaker 1: That can be a good thing for researchers who need
Speaker 1: their work to be published. There are students who need
Speaker 1: to publish works as part of their graduate work before
Speaker 1: they can graduate with an advanced degree. I suspect that
Speaker 1: this article or this paper was such a project. It
Speaker 1: comes across to me as, oh, these were students who
Speaker 1: took a bunch of other studies and then they produce
Speaker 1: this paper. It strikes me that way. I don't know
Speaker 1: that for sure, by the way, that's just the feeling
Speaker 1: I get as I read it. And of course, there
Speaker 1: are also positions and titles that require the holder of
Speaker 1: that position or title has to publish work at regular
Speaker 1: intervals or else risk losing their position. Like professors, there
Speaker 1: are a lot of professors at universities who are required
Speaker 1: to publish a certain number of papers per year. That's
Speaker 1: just the expectation, or else they can lose their position.
Speaker 1: And publication takes time, like especially for scientific papers. If
Speaker 1: you're talking about scientific or medical papers, that review process
Speaker 1: could take as long as a year, and ultimately there's
Speaker 1: no guarantee that the paper is going to go through.
Speaker 1: So if you're under the gun and you have to publish,
Speaker 1: and you really need your work to get out there
Speaker 1: in order for that to count toward you know, whether
Speaker 1: your graduation or holding your job or whatever, going through
Speaker 1: a lengthy peer review and editing process is not high
Speaker 1: on your list of priorities. So a resource that takes
Speaker 1: work and fast tracks it toward publication can be a
Speaker 1: huge help to those who need to have their work published.
Speaker 1: But obviously the flip side of this is that if
Speaker 1: this process is a fact fasttracked, mistakes can slip through.
Speaker 1: Like I mentioned one earlier in this episode, it was
Speaker 1: clearly a mistake, and it made it all the way
Speaker 1: through the process. I actually found a few things in
Speaker 1: this paper that struck me as odd or poorly worded,
Speaker 1: Like there were bits where I thought that sentence is
Speaker 1: missing something, the syntax doesn't quite work. I'm not entirely
Speaker 1: certain what they were trying to say, so several passages
Speaker 1: in the paper struck me as in need of editing,
Speaker 1: just for the purposes of clarity, if nothing else. And
Speaker 1: the thought occurred to me that if I had written
Speaker 1: this for HowStuffWorks dot Com and had submitted it, my
Speaker 1: editor would have returned it to me with a note
Speaker 1: that said I needed to rewrite that passage. Then again,
Speaker 1: maybe it's because I'm not a scientist. Because I'm reading
Speaker 1: this the way an English major reads a paper. I'm
Speaker 1: not reading it the way a scientific researcher does. And
Speaker 1: that's a fair statement, right. I am not a scientific researcher,
Speaker 1: so maybe I am being unfair with this. I did
Speaker 1: some digging and found there's actually a quite a bit
Speaker 1: of disagreement about Curious in the research space as to
Speaker 1: whether it's a good resource or like you know, a
Speaker 1: junk journal or something along those lines. So some people
Speaker 1: have pointed to it as being really helpful if you
Speaker 1: need to get your work published and seen, and that
Speaker 1: when it comes to that, it ends up being an
Speaker 1: incredible resource. Others have argued that the journal has a
Speaker 1: low rejection rate, meaning it doesn't reject a lot of
Speaker 1: articles right off the bat, and that the fast turnaround
Speaker 1: time means that as a result, they publish a lot
Speaker 1: of low quality studies, or at least lower quality studies,
Speaker 1: And I fell down a rabbit hole. That is the
Speaker 1: mire of scientific publishing and how it puts researchers in
Speaker 1: a really tough position, and that a lot of journals
Speaker 1: end up being predatory right, like they end up looking
Speaker 1: to get researchers to spend thousands of dollars in things
Speaker 1: like the editing and peer review services, which makes me
Speaker 1: question the whole system. If I'm being honest with you now,
Speaker 1: I will say that even the critics of Curious said, no,
Speaker 1: it's not predatory. It's not like it's one of those
Speaker 1: journals set up to builk people out of money so
Speaker 1: that they can get their work in print. They're not
Speaker 1: like that, which is good, Like I'm glad to hear that,
Speaker 1: So I don't want to cast that aspersion on Curious.
Speaker 1: It does appear to be very much legitimate in that regard.
Speaker 1: It's just that the process being so fast tracked means
Speaker 1: that stuff that shouldn't slip through sometimes does. I have
Speaker 1: not read other papers in Curious, so I don't know
Speaker 1: how prevalent that is, but just reading this one, I
Speaker 1: thought there's some issues here. So anyway, that's why I
Speaker 1: went through this whole paper was to kind of get
Speaker 1: my head wrapped around what does the science say about this,
Speaker 1: because we often will hear things, especially in politics, that
Speaker 1: end up relating to the use of social media and
Speaker 1: social networking sites and how that impacts people's health. And
Speaker 1: while again it seems to go along with common sense,
Speaker 1: I think it's important for us to really recognize that
Speaker 1: we need more research in this area just so that
Speaker 1: we address the issue properly. Right, if the underlying problem
Speaker 1: is not the use of social networks, then limiting people's
Speaker 1: time on social networks or policing social networks so that
Speaker 1: they cause less harm or perceived harm. That's not going
Speaker 1: to actually solve the problem if it turns out that
Speaker 1: there's another issue that's really at play here and it
Speaker 1: just manifests both as mental health challenges and a desire
Speaker 1: to use social networks more. If you're just elimiting the
Speaker 1: social networks, then you're not really solving that common problem.
Speaker 1: So that's why more studies are really needed now. It
Speaker 1: may very well turn out to be that the over
Speaker 1: use of social networks does in fact impact mental health
Speaker 1: in a negative way, and thus by limiting your exposure
Speaker 1: to social networks you can improve your mental health. That
Speaker 1: might be true, but without the actual studies to support that,
Speaker 1: we don't know for sure, and we're just kind of
Speaker 1: stumbling around in the dark trying to come to a
Speaker 1: solution that may or may not address the problems we have.
Speaker 1: And there are better ways to go about doing that,
Speaker 1: and more scientific research is certainly one of those ways. Hopefully,
Speaker 1: the research that's done in the future will be done
Speaker 1: in such a way that the methodologies will be clear,
Speaker 1: they'll be replicable, so that if someone else wants to
Speaker 1: do the same study, they're going to get more or
Speaker 1: less the same sort of results. And that we can
Speaker 1: then draw firm conclusions and create real solutions from that work.
Speaker 1: Science is tricky, I mean, ultimately it's not. Science is
Speaker 1: not tricky when you get down if you boil it
Speaker 1: down to it to its core principles, which is that
Speaker 1: you know, you're asking questions, you're designing tests to test
Speaker 1: those questions, and you're coming up with answers. That's pretty simple,
Speaker 1: but going about it ends up being a lot more
Speaker 1: work and pretty complicated. But I hope you appreciated this
Speaker 1: episode and the look into what does it actually mean
Speaker 1: to read one of these studies? This one, I think
Speaker 1: it was almost like Baby's first study for me because
Speaker 1: against it was a meta analysis. It didn't actually dive
Speaker 1: into things like statistical analysis or anything like that. Like
Speaker 1: there were no complicated formula or anything like that that
Speaker 1: I needed to read over. I was just reading conclusions
Speaker 1: about other studies, So this was a pretty simplistic one.
Speaker 1: But yeah, it gave me a deeper appreciation for the
Speaker 1: challenges that people in the field face when they're trying
Speaker 1: to design their studies and publish their work, which wasn't
Speaker 1: my intent when I started out in this episode, but
Speaker 1: that's where I ended up. I hope all of you
Speaker 1: out there are doing really well, and I will talk
Speaker 1: to you again really soon. Tech Stuff is an iHeartRadio production.
Speaker 1: For more podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts,
Speaker 1: or wherever you listen to your favorite shows.