Screen time has little impact on adolescent wellbeing, research finds
According to a new study from researchers at the University of Oxford, at most, only 0.4% of adolescent wellbeing is linked to technology and screen time. This study, published January 14th in Nature Human Behavior, is the most conclusive study thus far that has looked into adolescent relationships with technology.
“Our findings demonstrate that screen use itself has at most a tiny association with youth mental health,” said lead researcher Professor Andrew Przybylski, Director of Research at the Oxford Internet Institute, University of Oxford. “The 0.4% contribution of screen use on young people’s mental health needs to be put in context for parents and policymakers.
“Within the same dataset,” Przybylski continued, “we were able to demonstrate that including potatoes in your diet showed a similar association with adolescent wellbeing. Wearing corrective lenses had an even worse association.”
The data pulled from 300,000 teens and parents throughout the U.K. and U.S.A. showed that smoking marijuana and getting bullied had, on average, 2.7% times and 4.3% times more impact on wellbeing than technology use, as did lack of sleep and not eating breakfast.
Researchers used a method called Specification Curve Analysis to reach their conclusion and avoid bias, as has been previously included in similar studies.
“Even when using the same datasets, each researcher brings different biases with them and analyses the data slightly differently,” study author Amy Orben, College Lecturer at the Queen’s College, University of Oxford, said. “Of the three datasets we analysed for this study, we found over 600 million possible ways to analyse the data. We calculated a large sample of these and found that – if you wanted – you could come up with a large range of positive or negative associations between technology and wellbeing, or no effect at all.”
“We needed to take the topic beyond cherry-picked results, so we developed an approach that helped us harvest the whole orchard,” Przybylski added.
The Specification Curve Analysis explored the entire range of correlations between adolescent wellbeing and technology use within the full dataset. Furthermore, researchers examined practical significance rather than statistical significance by using information gathered by questions within the existing dataset.
“Research’s reliance on statistical significance can yield bizarre ‘results,’” Orben said. “We need to look at the size of the association to make a judgement on practical significance. If you told me the amount of time a teenager spends on digital devices, I could not do very well predicting their overall wellbeing, as only 0.4% is associated with technology use.”
“Bias and selective reporting of results is endemic to social and biological research influencing the screen time debate,” Przybylski explained. “We need to put scientific findings in context for parents, policymakers and the general public. Our approach provides an excellent template for data scientists wanting to make the most of the excellent cohort data available in the UK and beyond.”