Social Media is a drug and a smartphone is our dealer, right?
It goes without saying that there are masses press coverage linking digital technology to the rise in depression and a sharp decline in well-being in children. However, Amy Orben challenged her audience to be more critical when it came to the data they consume during her Social Media Week London session.
Every time there’s a new wave in society it causes concern.
“Screen time is now linked to 12 deadly cancers and short-sightedness – I read this a week ago in the Telegraph,” she noted, but couldn’t trace the individual scientists who claimed this, to question their resources and methods.
It was clear that Orben was tactful with her data, and pinpointed the main reasons why it’s important to look at the wider picture. Or graph, in her case.
There is a generational change in well-being levels but it is difficult to pinpoint why.
It’s vital to question the narrative. Orben has access to UK data and found a trend that the drop in well-being is driven by young girls. She proposes this could be down to change in hormones (a biological factor) or girls being more open to saying they’re upset (a sociological factor). What is social media is effectively a scapegoat?
‘Screen time’ as a concept is problematic and counterproductive.
“How long social media is used for isn’t a good measure of effects,” explained Orben. It’s quality over quantity. How we connect, the content we consume and our connections matter more than duration.
Negative general effects of social media and technology use on well-being are present but are extremely small.
Almost anything that has a lean, no matter how small, will become statistically significant enabling the press to create headlines from them.
Such effects are most often not linear
Data showing effects isn’t straightforward. Orben’s key research partner, Andrew Przybylski, found in 2017 that the effects of overusing technology over time have a much smaller negative impact on a child than how much sleep they had. “The way science does stats isn’t transparent,” explained Obren, “there are thousands of analytical considerations you have to make.”
An overwhelming factor is individual differences. Social and economic backgrounds and lifestyle choices will undoubtedly affect and alter data. Are disadvantaged children those who suffer most? Obren showed a review published by nature last year that demonstrated just that. “By asking in general, we are destined to fail as academics,” she finished.
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