For the study, Hunt and her team studied 143 undergraduates at the University of Pennsylvania over a number of weeks. They tested their mood and sense of well-being using seven different established scales. Half of the participants carried on using social media sites as normal. (Facebook, Instagram and Snapchat did not respond to request for comment.)
The other half were restricted to ten minutes per day for each of the three sites studied: Facebook, Instagram and Snapchat, the most popular sites for the age group. (Use was tracked through regular screen shots from the participants’ phones showing battery data.)
Net result: Those who cut back on social media use saw “clinically significant” falls in depression and in loneliness over the course of the study. Their rates of both measures fell sharply, while those among the so-called “control” group, who did not change their behavior, saw no improvement.
This isn’t the first study to find a link between social media use, on the one hand, and depression and loneliness on the other. But previous studies have mainly just shown there is a correlation, and the researchers allege that this shows a “causal connection.”
I’m guessing this study will get a good amount of attention because of this claim. Here is how this should work in the coming months and years:
- Other researchers should work to replicate this study. Do the findings hold with undergraduate students elsewhere in similar conditions?
- Other researchers should tweak the conditions of the study in a variety of ways. Move beyond undergraduates to both younger and older participants. (Most social media research involves relatively young people.) Change the national context. Expand the sample size. Lengthen the study beyond three weeks to look at longer-term effects of social media use.
- All the researchers involved need time and discussion to reach a consensus about all of the work conducted under #1 and #2 above. This could come relatively soon if most of the studies agree with the conclusions or it could take quite a while if results differ.
All together, once a claim like this has empirical backing, other researchers should follow up and see whether it is correct. In the meantime, it will be hard for the public, the companies involved, and policymakers to know what to do as studies build upon each other.