Should parents fear potatoes as much as screens?
A new study says neither have serious positive or negative impacts on childhood well-being
t’s easy to worry about the impact of ubiquitous smartphones — doctors have tried to liken the effects of digital technology to serious drug addiction, and platforms like Instagram have been linked to depression and anxiety. Headlines comparing children’s phones to cocaine or calling technology the new gateway drug don’t help. But despite the panic, the reality is that many of the studies on screen time have been poorly conducted, and their results are inconclusive.
In fact, science-conscious clinical psychologists and researchers have been calling screen fears out as unfounded for years. In 2015, an editorial in the British Medical Journal questioned the claims against digital technology and asked for “less shock and more substance.” This has sparked an ongoing debate, confusing well-meaning parents.
Now, new research by University of Oxford scientists Amy Orben and Andrew Przybylski attempts to shed some light on the debate. They wanted to highlight the problems in how previous large-scale studies were analysed. So in a study published in Nature Human Behaviour, they investigated the methodology and datasets these conclusions have been drawn from, and found the many variables in these studies have led to potentially false positives.
To do so, the researchers took three large scale datasets with a sample of 350,000 adolescents, and assessed the impact of technology use on their well-being. But what does “technology use” mean? If I were to ask ten people, I’d likely get ten slightly different answers. This is the issue researchers face with large datasets. For example, ‘tech use’ could be defined as “television use on weekdays,” or “television use on weekends,” or more realistically, “hours per day spent on social media.” Changing how you define the key variable allows scientists to answer the same question in a lot of different ways. Orben and Przybylski found that just by changing the definition, they could come up with over 600 million theoretically justifiable analyses. For context, in science we usually say that 1 in every 20 statistical analyses will produce a false positive — meaning demonstrate an effect when there isn’t one. So this many different potential analyses means there are a huge number of false positives in the data.
The researchers then listed all of the different ways ‘well-being’ and ‘tech use’ could be defined, and plotted these as a specification curve analysis, a statistical approach which consists of three steps. The first is to identify all the justifiable ways of answering your question of interest based on your data (e.g. if you have a hundred ways of defining tech use you could run a hundred justifiable tests). The second step is to then run these individual analyses to show all the alternate ways of addressing the CONTINUE READING: Should parents fear potatoes as much as screens? | Salon.com
