The study examines the association between adolescent well-being and digital technology use, addressing methodological challenges in large-scale social datasets. Using Specification Curve Analysis (SCA) across three datasets (n_tot = 355,358), the researchers find a small negative association between digital technology use and adolescent well-being, explaining at most 0.4% of the variation in well-being. The effects are too small to warrant policy changes. The study highlights the need for transparent and robust analytic practices, considering the high number of possible analyses and the potential for researcher degrees of freedom. The findings suggest that while digital technology use may have a small negative impact, other factors such as smoking marijuana and bullying have more significant negative effects on well-being. Proper control variables and pre-specified analyses are crucial for accurate interpretations.The study examines the association between adolescent well-being and digital technology use, addressing methodological challenges in large-scale social datasets. Using Specification Curve Analysis (SCA) across three datasets (n_tot = 355,358), the researchers find a small negative association between digital technology use and adolescent well-being, explaining at most 0.4% of the variation in well-being. The effects are too small to warrant policy changes. The study highlights the need for transparent and robust analytic practices, considering the high number of possible analyses and the potential for researcher degrees of freedom. The findings suggest that while digital technology use may have a small negative impact, other factors such as smoking marijuana and bullying have more significant negative effects on well-being. Proper control variables and pre-specified analyses are crucial for accurate interpretations.