The authors indicate that the current empirical evidence supporting a belief in a negative connection between the two is largely based on secondary analyses of large-scale social datasets. Though these datasets provide a valuable resource for highly powered investigations, their many variables and observations are often explored with an analytical flexibility that marks small effects as statistically significant, thereby leading to potential false positives and conflicting results.
The researchers address these methodological challenges by applying specification curve analysis (SCA) across three large-scale social datasets (total n = 355,358) to rigorously examine correlational evidence for the effects of digital technology on adolescents. The association they find between digital technology use and adolescent well-being is negative but small, explaining at most 0.4% of the variation in well-being. Taking the broader context of the data into account suggests that these effects are too small to warrant policy change.
The research also shows that previous research in this area is deeply flawed.
This twitter thread by Patrick Markey provides an excellent overview on the publication.