Research finds heavy Facebook users make impaired decisions like drug addictsTechCrunch #Social_MediaJanuary 11, 2019
Researchers at Michigan State University are exploring the idea that there’s more to “social media addiction” than casual joking about being too online might suggest.
Their paper, titled “ Excessive social media users demonstrate impaired decision making in the Iowa Gambling Task” (Meshi, Elizarova, Bender and Verdejo-Garcia) and published in the Journal of Behavioral Addictions, indicates that people who use social media sites heavily actually display some of the behavioral hallmarks of someone addicted to cocaine or heroin .
The study asked 71 participants to first rate their own Facebook usage with a measure known as the Bergen Facebook Addiction Scale .
As the study explains, “Participants are also informed that some decks are better than others and that if they want to do well, they should avoid the bad decks and choose cards from the good decks.”
What the researchers found was telling.
Study participants who self-reported as excessive Facebook users actually performed worse than their peers on the IGT, frequenting the two “bad” decks that offer immediate gains but ultimate result in losses.
That difference in behavior was statistically significant in the latter portion of the IGT, when a participant has had ample time to observe the deck’s patterns and knows which decks present the greatest risk.
The IGT has been used to study everything from patients with frontal lobe brain injuries to heroin addicts, but using it as a measure to examine social media addicts is novel.
Along with deeper, structural research, it’s clear that researchers can apply to social media users much of the existing methodological framework for learning about substance addiction.
The study only looked at Facebook use, “because it is currently the most widely used [social network] around the world,” but one could expect to see similar results with the billion-plus monthly Instagram and potentially the substantially smaller portion of people on Twitter.