Adolescence is a dynamic time in development which is associated with enhanced opportunities and vulnerabilities due to vast physical, psychological, and social changes. A rising prevalence of depression and anxiety among adolescents in the U.S., with approximately 22% with severe impairments (Bose, 2017; NIMH, 2019), has evoked growing concerns around causes for this rise, especially considering the digital age. Adolescents are the largest adopters of technology, with approximately 95% having access to a mobile device, 71% using one or more social media platforms, and 45% claiming to be online “almost constantly” (Pew Research Center, 2018). While many studies have shown associations between screen time and poor mental health outcomes (Kırcaburun et al., 2018; Lemola et al., 2015; McBride, 2017; Sampasa-Kanyinga & Lewis, 2015; Stiglic & Viner, 2019; Twenge & Campbell, 2018; Twenge et al., 2018), recent reviews of the literature show mixed and inconsistencies in these findings (Best et al., 2014; Odgers, 2018; Rideout, 2018; Sarmiento et al., 2018; Wartella et al., 2016).
A recent rigorous analysis of large-scale datasets by Orben and Przybylski (2019) revealed associations between screen time and wellbeing in adolescents suggesting small effects sizes which can be comparable to many other possible and unrelated correlates to mental health outcomes in adolescents. This posits a greater consideration that must be made in statistical inferences in efforts to address the complex nature in the rise of internalizing behaviors such as depressive and anxiety symptoms in youth.
Many established lines of research investigating predictors, beyond individual factors such as screen time (Odgers, 2018) and cognitive functioning (Shortt & Spence, 2006), to poor mental health outcomes in adolescents include family (Sander & McCarty, 2005) and peer factors (Garland & Fitzgerald, 1998; MacPhee & Andrews, 2006), school functioning (Juvonen et al., 2000; Fröjd et al., 2008), neighborhood (Aneshensel & Sucoff, 1996) and community factors (Huynh & Fuligni, 2010). This multi-level perspective echoes the social ecological framework (Bronfenbrenner & Morris, 2006; Stokols, 2018), which recognizes the interplay of the various ecologies, proximal and distal to the individual, on mental health during this developmental period. The objective of this study is to investigate the social ecological factors associated with adolescent mental health in the digital age. Using a multimodal baseline dataset from the Adolescent Brain and Cognitive Development (ABCD) study (Volkow et al., 2017), we will be able to characterize correlates to mental health outcomes of a diverse U.S. adolescent cohort, inclusive of the various ecological factors. The aims of this study are threefold: (1) to evaluate the associations between screen time and internalizing behaviors, (2) to evaluate the associations between multi-level ecological factors previously identified as risk factors for increases in internalizing behaviors among adolescents, and (3) explore differences in these associations stratified by socioeconomic and racial/ethnic groups.