The widespread use of digital technologies by young people has spurred speculation that their regular use negatively impacts psychological well-being. Current empirical evidence supporting this idea 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. Here we 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 we find between digital technology use and adolescent well-being is negative but small, explaining at most 0.4 percent 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.