Youth Screen Media Activity Patterns and Associations With Behavioral Developmental Measures and Resting-state Brain Functional Connectivity.

OBJECTIVE: Screen media activity (SMA) consumes considerable time in youth's lives, raising concerns about the effects it may have on youth development. Disentangling mixed associations between youth's SMA and developmental measures should move beyond overall screen time and consider types and patterns of SMA. We aimed to identify reliable and generalizable SMA patterns among youth and examine their associations with behavioral developmental measures and developing brain functional connectivity.

METHOD: Three waves of the Adolescent Brain and Cognitive Development (ABCD) data were examined. The Lifespan Human Connectome Project in Development (HCP-D) was interrogated as an independent sample. ABCD participants included 11,878 children at baseline. HCP-D participants included 652 children and adolescents. Youth-reported SMA and behavioral developmental measures (neurocognitive performance, behavioral problems, psychotic-like experiences, impulsivity, and sensitivities to punishment/reward) were assessed with validated instruments. We identified SMA patterns in the ABCD baseline data using K-means clustering and sensitivity analyses. The generalizability and stability of the identified SMA patterns were examined in HCP-D data and ABCD follow-up waves, respectively. Relationships were examined between SMA patterns and behavioral and brain (resting-state brain functional connectivity [RSFC]) measures using linear-mixed-effect modelling with false-discovery-rate (FDR) correction.

RESULTS: SMA data from 11,815 children (Meanage = 119.0 months, SDage = 7.5; 6,159 (52.1%) boys) were examined, and 3,151 (26.7%) demonstrated a video-centric higher-frequency SMA pattern and 8,666 (73.3%) demonstrated a lower-frequency pattern. The SMA patterns were validated in similarly-aged HCP-D youth. Compared to the lower-frequency-SMA-pattern group, the video-centric-higher-frequency-SMA-pattern group showed poorer neurocognitive performance (Beta=-0.12, 95%CI, [-0.08, -0.16], FDR-corrected p<.001), more total behavioral problems (Beta=0.13, 95%CI, [0.09, 0.18], FDR-corrected p<.001), and more psychotic-like experiences (Beta=0.31, 95%CI, [0.27, 0.36], FDR-corrected p<.001). The video-centric-higher-frequency-SMA-pattern group demonstrated higher impulsivity, more sensitivity to punishment/reward and altered RSFC among brain areas implicated previously in cognitive processes. Most of the associations persisted with age in the ABCD data, with more individuals (n=3,378, 30.4%) in the video-centric higher-frequency SMA group at one-year follow-up. A social-communication-centric SMA pattern was observed in HCP-D adolescents.

CONCLUSION: Video-centric SMA patterns are reliable and generalizable during late childhood. A higher-frequency-video-entertainment-SMA-pattern group showed altered RSFC and poorer developmental measures that persisted longitudinally. The findings suggest public health strategies aiming to decrease excessive time spent by children on video-entertainment-related SMA are needed. Further studies are needed to examine potential video-centric/social-centric SMA bifurcation to understand dynamic changes and trajectories of SMA patterns and related outcomes developmentally.