Social media is linked to depression—or not. First-person shooter video games are good for cognition—or they encourage violence. Young people are either more connected—or more isolated than ever.

Such are the conflicting messages about the effects of technology on children’s well-being. Negative findings receive far more attention and have fueled panic among parents and educators. This state of affairs reflects a heated debate among scientists. Studies showing statistically significant negative effects are followed by others revealing positive effects or none at all—sometimes using the same data set.

A new paper by scientists at the University of Oxford, published in January in Nature Human Behaviour, should help clear up the confusion. It reveals the pitfalls of the statistical methods scientists have employed and offers a more rigorous alternative. And, importantly, it uses data on more than 350,000 adolescents to show persuasively that, at a population level, technology use has a nearly negligible effect on adolescent psychological well-being, measured in a range of questions addressing depressive symptoms, suicidal ideation, pro-social behavior, peer-relationship problems and the like. Technology use tilts the needle less than half a percent away from feeling emotionally sound. For context, eating potatoes is associated with nearly the same degree of effect and wearing glasses has a more negative impact on adolescent mental health.

“This is an incredibly important paper,” says Candice Odgers, a psychologist studying adolescent health and technology at the University of California, Irvine, who wasn’t involved in the research. “It provides a sophisticated set of analyses and is one of the most comprehensive and careful accountings of the associations between digital technologies and well-being to date. And the message from the paper is painstakingly clear: The size of the association documented across these studies is not sufficient or measurable enough to warrant the current levels of panic and fear around this issue.”

To date, most of the evidence suggesting digital technologies negatively impact young people’s psychological well-being comes from analysis of large, publicly available data sets. Those are valuable resources but susceptible to researcher bias, say Andrew Przybylski, an experimental psychologist at Oxford and his graduate student Amy Orben, co-authors of the new paper. To prove their point, they found over 600 million possible ways to analyze the data contained in the three data sets in their study. “Unfortunately, the large number of participants in these designs means that small effects are easily publishable and, if positive, garner outsized press and policy attention,” they wrote.

This type of research intends to modify the status quo. “We’re trying to move from this mind-set of cherry-picking one result to a more holistic picture of the data set,” Przybylski says. “A key part of that is being able to put these extremely miniscule effects of screens on young people in real-world context.”

That context is illuminating. Whereas their study found digital technology use was associated with 0.4 percent of the variation that disrupts adolescent well-being, the effects of smoking marijuana and bullying had much larger negative associations for mental health (at 2.7 and 4.3 respectively in one of the data sets). And some positive behaviors such as getting enough sleep and regularly eating breakfast were much more strongly associated with well-being than the average impact of technology use.

Strikingly, one of the data sets Przybylski and Orben used was “Monitoring the Future,” an ongoing study run by researchers at the University of Michigan that tracks drug use among young people. The alarming 2017 book and article by psychologist Jean Twenge claiming that smartphones have destroyed a generation of teenagers also relied on the data from “Monitoring the Future.” When the same statistics Twenge used are put into the larger context Przybylski and Orben employ, the effect of phone use on teen mental health turns out to be tiny.

The method the Oxford researchers used in their analysis is called Specification Curve Analysis, a tool that examines the full range of possible correlations and maps “the sum of analytical decisions that could be made when analyzing quantitative data.” Rather than reporting a handful of results, researchers using SCA report all of them. It is the statistical equivalent of seeing the forest for the trees. “It’s about setting a standard,” Przybylski says. “This kind of data exploration needs to be systematic.”

All of this is not to say there is no danger whatsoever in digital technology use. In a previous paper, Przybylski and colleague Netta Weinstein demonstrated a “Goldilocks” effect showing moderate use of technology—about one to two hours per day on weekdays and slightly more on weekends—was “not intrinsically harmful,” but higher levels of indulgence could be. And in a 2015 paper Odgers and a colleague reviewed the science addressing parents’ top fears about technology and found two important things: First, most of what happens online is mirrored offline. Second, effects really do depend on the user; benefits are conferred on some whereas risks are exacerbated for others, such as children who already suffer from mental health problems.

“We’re all looking in the wrong direction,” Odgers says. “The real threat isn’t smartphones. It’s this campaign of misinformation and the generation of fear among parents and educators.”