This research paper is a very confusing read, even for someone who is quite familiar with this kind of research. Yet what is said in the paper is crucial to the case being made by Jean Twenge (and Jon Haidt) that government intervention is urgently needed to curb the harms of social media to the mental health of teens. I’ll use the abstract of the paper to discuss how to find flaws in a research study that is intended to influence public health policy.

Parents and school teachers and administrators cannot be expected to interpret original research studies on their own. But they might learn from discussions like this one to be more skeptical of experts who claim their advice is based on social science, but who make emotional appeals and rely on anecdotes to rouse their readership into action.

The ratio of emotional story-telling to actual scientific evidence is very high in stories in the popular press expressing alarm about the damaging effects of teen girls’ use of social media on their mental health.

There is an excess of hype and drama about this topic, even in op-eds in the New York Times. When in doubt, be skeptical of social scientists who try too hard to convince you that they are correct and that other experts have just not noticed something that is obvious to them.

In a widely discussed article, Jean Twenge says that she has been studying generational trends in mental health for over 25 years and that she never before found such a dramatic change in mental health as she saw around 2012.

Have Smartphones Destroyed a Generation? More comfortable online than out partying, post-Millennials are safer, physically, than adolescents have ever been.

Around 2012, I noticed abrupt shifts in teen behaviors and emotional states. The gentle slopes of the line graphs became steep mountains and sheer cliffs, and many of the distinctive characteristics of the Millennial generation began to disappear. In all my analyses of generational data — some reaching back to the 1930s — I had never seen anything like it.

Twenge has advice for parents and teachers:

If you were going to give advice for a happy adolescence based on this survey, it would be straightforward: Put down the phone, turn off the laptop, and do something — anything — that does not involve a screen.

Twenge commands special authority because her views are said to be derived from the best available evidence.

However, most of the key research that Twenge and her fellow advocate Jonathan Haidt cite was not conducted by either of them. I suspect that many of the authors of these studies they cite would disagree with Twenge and Haidt’s interpretation of their work, some vigorously so. That situation makes one centerpiece study led that was led by Twenge particularly important.

The key research article by Twenge and her colleagues is here.

Increases in Depressive Symptoms, Suicide-Related Outcomes, and Suicide Rates Among U.S…In two nationally representative surveys of U.S. adolescents in grades 8 through 12 ( N = 506,820) and national..

The article is unfortunately paywalled, but here is its abstract. We can do a lot with it.

In two nationally representative surveys of U.S. adolescents in grades 8 through 12 (N = 506,820) and national statistics on suicide deaths for those ages 13 to 18, adolescents’ depressive symptoms, suicide-related outcomes, and suicide rates increased between 2010 and 2015, especially among females. Adolescents who spent more time on new media (including social media and electronic devices such as smartphones) were more likely to report mental health issues, and adolescents who spent more time on nonscreen activities (in-person social interaction, sports/exercise, homework, print media, and attending religious services) were less likely. Since 2010, iGen adolescents have spent more time on new media screen activities and less time on nonscreen activities, which may account for the increases in depression and suicide. In contrast, cyclical economic factors such as unemployment and the Dow Jones Index were not linked to depressive symptoms or suicide rates when matched by year.

The editors at a top psychology journal, Clinical Psychological Science, and the reviewers the editors picked were obviously impressed enough to recommend the article and its abstract be published in the form that we now see.

I noticed lots of things that made me suspicious because I have higher standards for talking about risks to health than most psychologists do.

• I received excellent training in my Ph.D. studies as a research-oriented clinical psychologist. I received my doctorate in 1975 but then began working in situations where medical scientists and public health officials demanded stricter standards than what was required of psychologists trying to get published in a respectable psychology journal. Lives depended on what a different kind of expert decided about risks from the often limited and flawed data that was available to them.

The COVID pandemic and the quick decisions that had to be made about what advice could be given concerning vaccination, social distancing and lockdowns put this kind of expertise on display. The world-class experts giving briefings on the best of cable news were good at policing each other to avoid exaggerating what was known and to admit they did not know. “We don’t know yet” was often the best answer, as frustrating as it was.

For a start, I expect more information from an abstract than this one provided. The authors did not follow standard advice on what to include in an abstract. I’ll have a future story documenting how abstracts attached to paywalled articles like the one we are discussing here can actually kill people, aside from spreading misconceptions.

Rather than doing their own research to collect new data, these authors relied on existing survey data sets collected for other purposes. This leaves lots of questions about they did this that the authors do not address in a transparent way.

How did the authors integrate this data from different sources in one study? Relying on someone else’s data is attractive and may at first seem expedient, but effectively and validly doing requires a lot of difficult decision-making.

Inevitably, the original researchers did not ask the right survey questions for new research. What questions in the surveys best fit the new issues researchers wanted to address? How could the new researchers verify that their selection from already collected data was most valid and relevant to their issues?

Twenge and her co-authors imply in the abstract that they had been able somehow to integrate the survey questions with information from the national statistics on deaths by suicide. I knew that was bunk. Ethics committees overseeing the protection of human subjects insist the data be anonymized so that identification and matching of people across data sets becomes virtually impossible.

Then, there is the problem of the small number of suicides in this relatively low-risk group. Let’s stop here and apply some numbers I revealed last time.

Any potential risk factors the authors can find in these pre-existing survey questions must pass the test of predicting relatively infrequent events with some percision. The abstract suggests the authors may have succeeded (“which may account for the increases in depression and suicide), but that would be statistically improbable, given the basic rate of death by suicide and any conceivable fluctuation in the study period of this article.

For 2017, we have about 420 suicides to explain among 20.5 million girls. I wish the authors luck in using whatever fancy statistics they can muster to predict which girls will die by suicide with the risk factors they can pull from other people’s data. Chances are no one died by suicide or only a chance handful from participants in the survey data they acquired. Neither Twenge and her co-authors or readers can tell.

Not being able to identify which of the teens completing the survey died by suicide means the authors will be left making speculative statements beyond what their data allow.

The authors used the term “iGen adolescents” in the abstract to describe the teens they studied. That fits with Jean Twente’s best-selling books, but I was skeptical about such a sweeping term being able to capture much of the similarities and differences in an increasingly diverse and divided America in the association of use of social media and mental health.

Was any similarity of teens falling in this age range more important than the vast range of differences? Consider one white teen having alcoholics or Trump supporters for parents versus another teen having teetotaler Hindu parents who insisted that their teen study hard enough to go to medical school and become a physician? White teens with two Ivy League faculty as parents versus a Black teen raised by a single grandmother who dropped out of high school and does not have internet? Versus a Black teen raised by a single grandmother who dropped out of high school, but the great of the story is the teen’s mother was an innocent victim of random gun violence and the grandmother insists the teen fulfill the mother’s dream and go to college, no excuses accepted?

I could generate thousands of these kinds of contrasts, and some would be quite absurd.

The final conclusion where I seem to be headed is that a generational label like iGen or Generation Z cannot capture much of variations among teens — or across an individual teen’s transition into adulthood and afterward.

“iGen” [Don’t you like the cool choice of labels so that you automatically think of having “iPhones” as what 25 million American teen girls have in common?] might serve to highlight some things teens that might be missed that teens have in common. Surely it misses a lot of things teens don’t have in common, whether they are from radically different backgrounds or with nearly identical demographics but just different in the place of social media in their lives.

The authors end their abstract with straight-faced reassurance that they controlled for “cyclical economic factors such as unemployment and the Dow Jones Index,” matched by year. I can just imagine some badass experts at conferences I have attended who would lie in wait for a speaker to say such a silly thing.

Academics who think their research saves lives can be real a*holes when dealing with other academics whose research they think will never save any lives.

Imagine the response of experts accustomed to identifying health risks from correlations found in survey or surveillance data. Unprepared for what they would hear, some would have spilled coffee on their fancy suits and chocked on the stale Danish from the free conference breakfast as they scrambled to correct the speaker, not allowing anyone to discuss what else the presenter had to say.

I can imagine the string of cliched criticism that could be unleashed.

“Of course, you know that correlation does not equal causality.”

“You can’t do magic with statical controls of correlations when all you have is somebody else’s survey data they collected for some other purposes.”

“What a dumb choice! Are you a psychologist who does not understand regression analysis or do you have books to sell at the conference? Will your next slide tell us where to find your Tedtalk?

Maybe the badass expert would be in an uncharacteristically charitable mood and simply explain:

“I appreciate your effort to find support for a hypothesis that excites you.You should realize that you are relying on statistical controls to settle some issues of causality that are not readily solved. If you were to rely on such controls, you are first making the assumption that you have isolated all the variables that could possibly explain away your findings. I don’t think these crude economic indicators begin to do that. Secondly, you are assuming that these variables are measured without error. I don’t think an economist would say these two variables perfectly measure year to year differences in the economy affecting either teen’s use of social media or dying by suicide.”

One final cynical a*hole comment before we move on —

“If we had used your approach to statistical analysis, we would have concluded at the early days of mystery in the HIV/AIDS epidemic that someone using poppers to enhance orgasm during casual sex or simply having too many Judy Garland LPs in their vinyl collection was a modifiable risk factor.”

Frightened and humiliated, the psychologist trying to finish their talk would miss a very serious and useful message that was being disguised here.

Not knowing what you are doing with bad data and a computer program can lead to all kinds of compelling, but spurious correlations to get worked up about, some more plausible for a while than the modifiable risk factor you are listening for in very noisy data.

So, just what did Twenge and colleagues do with “two nationally representative surveys of U.S. adolescents in grades 8 through 12 (N = 506,820) and national statistics on suicide deaths for those ages 13 to 18, adolescents’ depressive symptoms, suicide-related outcomes, and suicide rates increased between 2010 and 2015?”

That is a true mystery that is never clarified in this abstract. I was stumped at first. I gave the authors the benefit of a doubt and thought maybe they did some kind of prospective analysis, looking ahead and predicting later things that happened to individuals from their earlier responses on surveys.

I had to get a copy of the paywalled article. The overall design of the study was still difficult to decipher from the methods section, where it should have been laid out in detail and given a name, like case-control or cohort study.

I eventually figured out that the authors did not have two “nationally representative surveys of U.S. adolescents.” They had over two dozen cross-sectional retrospective studies (a one-time survey asking about the past year) with nonoverlapping samples and important differences in the questions that were asked. No questions at all about social media in the survey for some years (!).

This dog’s breakfast of a design for this study will be the topic of my next article about this study, as we dig deeper into what can reasonably be claimed from this study and what cannot — if we stick to principles of best science, not just good story-telling.

The post A Stunningly Bad Study Claims Social Media Devastates Teen Girls’ Mental Health appeared first on Medika Life.

Social media is the ultimate equalizer. It gives a voice and a platform to anyone willing to engage. — Amy Jo Martin

Agreeing with Dickens when he wrote, “It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness…” we look for hope in a time of darkness. Where can we find it as we wait? Technology may hold some hope.

As we mask up, researchers have a field day because of the plethora of factors to investigate. What about masks? Do they provide a means to hide our emotions on Facetime, create a new acceptance of people, or cause furtherance of backing off?

If we’re using social media and showing a portion of our faces, aren’t most of our faces and expressions covered by a mask? All good questions and researchers are probably on it.

Masks do affect how we perceive someone and what kind of interaction we will have. A mask removes our ability to perceive the entire face with all its characteristics — features we depend on to make our assessment of them. And masks cause problems not solely for us but for AI’s famed facial recognition algorithms.

Facial recognition software is particularly bad at recognizing African Americans and other ethnic minorities, women, and young people, often misidentifying or failing to identify them, disparately impacting certain groups. That’s when masks aren’t even in the equation. Add masks and it become more difficult.

Prior research on facial expressions and perception has depended on mouth curvature and similar facial movements, all hidden by masks. Our understanding of others, their intentions, and our communication are all affected by masks — and that can make us uncomfortable, anxious, or depressed; perhaps all three.

Most existing emotion-recognition systems analyze an individual’s facial expression…For example, if the corners of a person’s mouth are raised, the machine might rule that the person is in a good mood, whereas a wrinkled nose suggests anger or disgust.

One study did look at the effect of masks and made an assumption that waits to be tested.

Importantly, the inclusion of masks also led to a qualitative change in the way masked faces are perceived. In particular, holistic processing, the hallmark of face perception, was disrupted for faces with masks, as suggested by a reduced inversion effect.

The researchers believe that “…we provide novel evidence for quantitative and qualitative alterations in the processing of masked faces that could have significant effects on daily activities and social interactions.”

They didn’t pose an interesting question: how will being seen without a mask affect our newer social media relationships? Will it have any effect at all?

The Social Media Effect and Our Emotions

Every day, masks or not, the number of social media users increases. Every second, 11 people use social media for the first time.

In total, in North America, we spend an average of two hours, six minutes each day on social media, but this is an average, and many people may exceed that number of hours and minutes in their need to be rid of FOMO (fear of missing out). FOMO, in fact, is often a highly depression-evoking feeling.

The World Health Organization has proffered that the average global lifespan is 73.4 years. Based on that number of years and the amount of time we spend on social media, some estimate that we will spend six years and eight months using social media for whatever interests or ails us.

What’s the estimated world wide use of social media? “In 2020, there are an estimated 3.8 billion social media users worldwide, representing half the global population.”

But does social media affect us in positive or negative ways, or should we forget this entirely? We know it’s being used as therapist substitutes. So, there’s one potential benefit. If there aren’t therapists in an area, bots may be able to pick up the slack. Bots to the rescue, as it were.

Social Media Platform Use

Facebook and YouTube dominate this landscape, as notable majorities of U.S. adults use each of these sites. At the same time, younger Americans (especially those ages 18 to 24) stand out for embracing a variety of platforms and using them frequently. Some 78% of 18- to 24-year-olds use Snapchat, and a sizeable majority of these users (71%) visit the platform multiple times per day. Similarly, 71% of Americans in this age group now use Instagram and close to half (45%) are Twitter users. But those stats apply to 2018. What will it be in 2021?

Are there some solid reasons to use social media to help maintain your mental health, especially during trying times? It seems there are a number of them.

A study by a research team at Harvard University looked at the effects both positive and negative of social media and determined two things were important, the frequency and duration of use, and the number of contacts.

Social media, they found, was integrated into social and emotional connections, and there were three outcomes which they found salient; social well-being, positive mental health, and self-rated health. As a result of this research, their conclusion was that routine use of emotional connection with social media could have positive outcomes.

Social well-being was especially connected to three factors of age, education, and income. However, there was one intriguing finding. Social well-being and social media decrease with age.

…the study joins the few prior studies that have shown that beyond frequency and duration of use, (and) other aspects of use, such as type of use, should be considered in characterizing the link between social media use and health.

The Benefits and Potential Harm Need Further Exploration

There are benefits to being able to maintain contact to dispel loneliness, to play games to enhance skills and relieve boredom and to reach out for immediately help in a mental health crisis, that’s clear now to everyone or nearly everyone.

Social media allows anyone to join a group, engage in open communication on topics of interest, disseminate medical information, provide details on healthy lifestyles, recruit subjects for research, build communities, work for social change, and learn any subjects at any time of the day or night. It’s enormity is incredible.

But there are harms, too, and we need to balance both the positive and the negative and maintain some balance and recognize the problems.

We also know that social media can be used for not spreading truth but dangerous faux information, aka lies. This is how the virtual mask of social media plays into the hands of those with nefarious aims. A technology that was intended to connect the world and allow knowledge to be free for all, has proven to have a darker side.

Social media is a really awesome tool that can be used in so many positive ways. But, people NEED to consider the negative aspects to it as well. People should think about the consequences of the things they post or read on social media. Most importantly, we need to talk about these issues.

Don’t people hide behind the “masks” that social media provides? Do people really think it is without dire consequences if they publish highly personal information about themselves and others? We’ve received wake-up calls but not everyone is hearing them and the young and naive are vulnerable.

At this point, it would be premature to view the benefits of social media as outweighing the possible harms, when it is clear from the studies…that social media use can have negative effects on mental health symptoms, can potentially expose individuals to hurtful content and hostile interactions, and can result in serious consequences for daily life, including threats to employment and personal relationships. The harm and the benefits are real and we must accept both.

The question of age and gender, too, in addition to older adults, needs further exploration as noted in one study of 10–15 boys and girls.

High levels of social media interaction in early adolescence have implications for well-being in later adolescence, particularly for females. The lack of an association among males suggests other factors might be associated with their reduction in well-being with age. And this relationship in gender requires further exploration in order to address the factors involved in girls and well-being.

Social media is a great benefit, but it’s a “friend” we must carefully evaluate to parse out the good with the not-so-good. Use it, but beware not to let it abuse you as you do.

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