If you are a parent like me, you probably live with a constant nagging bit of guilt at the back of your mind about how much time your kids spend staring at screens. After all, isn’t too much screen time supposed to be bad?
Well, maybe not. It turns out that the scientific consensus about screen time—after more than a decade of study—is pretty inconclusive. For years, pediatricians warned parents that too much screen time would lead to “cyberbullying, “Facebook depression,” and sexting,” and psychologists warned that it was linked to heightened levels of anxiety or depression.
But in the past few years, researchers have quietly concluded that screen time does not appear to be the culprit that it was made out to be. Even one of the previously loudest critics of screen time’s effects on youth mental health, psychologist Jean Twenge (who worked on my college newspaper with me :-)), recently declared that “the relationship between screen time and kids’ mental health is more complicated than we thought.”
Instead, it appears that researchers may have been testing the wrong hypothesis. Quantity of screen time may not be as important as what kids are doing on their screens and what age they are when they are doing it. In other words, it’s quality not quantity that matters. And now researchers will likely need another decade or so to study quality, so we apparently won’t have an answer soon on what types of content to worry about.
To understand the latest research, this week I spoke with Amy Orben, who is the program lead track scientist of the MRC Cognition and Brain Sciences Unit of the University of Cambridge. She leads a research group investigating the links between digital technology use, mental health, and cognition in adolescence.
Before joining the University of Cambridge, Orben completed a Ph.D. in experimental psychology at the University of Oxford, for which she was awarded the British Psychological Society Award for Outstanding Contributions to Doctoral Research, and an M.A. in natural sciences at the University of Cambridge.
Our conversation is edited for brevity and clarity.
Angwin: Can you start by telling us what we know about the effects of screen time on children’s well-being and why it’s difficult to do research in this area.
Orben: After 10 years of research into screen time and well-being in children and young people, the results are still very mixed. On average, what we see is that there is at most a very small, negative relation between screen time and well-being in young people, and this is often in cross-sectional data, so we don’t know definitively if one causes the other or if it’s the other way around.
I just came back from a workshop at Harvard, and I think the main agreement we have in the field is that screen time is not a thing. I say this because screen time encompasses such a diverse set of activities, ranging from doing yoga on your iPad, to watching Netflix, to Skyping your grandparents or seeing distressing images on Instagram. Since it spans such a diverse set of activities and content, and because the users are so diverse, there is a clear reason why we’ve only found mixed and inconclusive effects in the literature when focused on screen time as a general concept.
Angwin: The small, negative association you mentioned—you found that in an earlier study you conducted. Can you tell us about it?
Orben: At the time, there wasn’t a lot of longitudinal work that tracked life satisfaction and social media use over time. We knew there was a small negative correlation, but it could be that more social media use caused lower life satisfaction, or that feeling worse caused more social media use, or it could be a third factor impacting both. For example, we know that in the U.S., children growing up in families of low socioeconomic status use more screens, and they also score worse on well-being questionnaires.
In this study we wanted to model these impacts longitudinally over time. For example, what happens if a person uses more social media than their own average in one year? Does that predict a decrease in their life satisfaction one year later? Or, if their life satisfaction differs in one year, how does that predict their social media use one year later? We found that both of these paths of impact existed. If I use more social media than normal in one year, that predicted a small decrease in life satisfaction one year later, but also if I felt worse, on average, in one year, that predicted more social media use a year later.
However, these effect sizes are very small. If we know someone’s social media use, we can only predict one percent, or around that benchmark, of a person’s life satisfaction overall. This has led to a lot of discussion and debate because small effects that scale over millions of people still matter, but they could also be very noisy. Life satisfaction is impacted by many things, so maybe we shouldn’t expect that our technologies can predict any more than a couple of percentage points.
Angwin: Is there any way to give us a sense of what a one percent difference is?
Orben: Some researchers have done work looking at how much your life satisfaction needs to change in order for you to notice it, and the number they found is below that, so it’s probably not a noticeable change for an individual.
In my early work, I looked at screen time in general, and I tried to put the effect sizes into perspective by comparing them to other activities. For example, we found that the negative correlation between digital technologies and well-being in teens was smaller than the negative correlation between wearing glasses and well-being. Naturally correlations do not allow us to make causal conclusions, but this gives us a flavor of the benchmarks of effect sizes we’re talking about here.
Angwin: You have a recent paper on the relationship between social media use and life satisfaction. Can you talk about what you found there?
Orben: For context, over roughly the last decade, in studies on the impact of, for example, social media use on the well-being of young people, all adolescents were grouped together into one big mass of people. This meant that the impact of social media on a 10-year-old was equated to the impact of social media on a 15-year-old, or a 20-year-old.
In this latest study, I was interested in whether the link between social media use and life satisfaction varies across specific times of adolescence and whether that differs between boys and girls, because puberty happens earlier in girls than boys. We found that in girls, there were two times during adolescence—between ages 11 to 13 and 19—where social media predicted a decrease in life satisfaction one year later. For boys, the window was 14 to 15, and 19.
This is really interesting because it raises the prospect that maybe the first window is due to pubertal processes that happen earlier in girls than in boys, and the second shared age at 19 could be due to a growing social life that everybody experiences, like moving from school to university.
Angwin: There are medical groups, such as The American Academy of Child & Adolescent Psychiatry, that have published guidelines for screen time use. Are these guidelines supported by science?
Orben: Time-based guidelines routinely disregard what the screens are doing. In the pandemic, I think people became a lot more discerning that Skyping grandparents using an iPad isn’t going to harm your child just because it’s via a screen; screen time is not a molecule that the body ingests, but sometimes we talk about it as if it is.
In the U.K., we have less guidance based on time because researchers do agree that time spent on screens isn’t a great measure of their impact. In the U.K., The Royal College of Pediatrics and Child Health doesn’t talk about a time limit but talks about the need for screens to complement the life of the family and not to displace or dominate family life. Naturally, that sort of advice is a lot less clear cut than giving definitive time measurements, so there are pros and cons to different approaches.
Angwin: It seems like the research conclusion is that it really matters what you are looking at on the screen. What is the state of the research looking at the effects of different types of screen content?
Orben: It’s extremely difficult to answer the content question because a lot of the data about what we see and how we interact with a platform is proprietary, and companies aren’t sharing their data. Big technology companies are sitting on vast amounts of data about what young people are seeing and interacting with. This data could be used to build exactly this knowledge base about what content is harmful and also what design features are beneficial or not for well-being and mental health. Over the last years, researchers have been voicing their opinions that, if we want better guidelines for screen use, then we need to allow researchers to access the necessary data to do this research.
Angwin: Lastly, you have written about our society’s repetitive technology panics. Can you talk about the history of technology panics and how this one fits in?
Orben: In society, whenever there is a technology that surpasses a certain level of popularity and starts impacting how we spend our time—and especially how our children spend their time—it starts to cause a lot of concern. I became interested in this because I was reading papers about the radio and peoples’ concerns that there would be widespread addiction to radio programs in the 1940s. I realized that more or less you could take sentences from these parenting magazines and change radio to smartphones and it would make complete sense.
Waves of concern in response to new technology are common and happen again and again throughout history, whether it’s a response to radio, television, video games, or social media. There’s an inherent repetitiveness to how we react to new things.
Because of this, we never really get the answer to questions like whether television causes aggression in children to increase because it’s inherently very complicated and researchers study it for 10 to 15 years and then all the funding and attention redirects to a new technology. This means there’s a lack of progress and understanding of these impacts over time.
As always, thanks for reading.
Additional Hello World research by Eve Zelickson.