Association between cognitive measures, global brain surface area, genetics, and screen-time in young adolescents : Estimation of causal inference with machine learning

Sammanfattning: Screen media activity such as watching TV and videos, playing video games, and using social media has become a popular leisure activity for children and adolescents. The effect of screen time has been a highly debated topic; however, there is still very little known about it. Using a dataset from the Adolescent Brain Cognitive Development longitudinal study 4 217 young adolescents, that met the requirements, could be retrieved for this thesis project after processing of the data. This thesis project investigated causal order between genetic effect (cognitive performance Polygenic scores (PGSs)), screen time activity, brain morphology (structural Magnetic Resonance Imaging (sMRI) for surface area and cortical thickness), lack of perseverance, and cognitive performance (crystallized IQ) with a machine learning algorithm DirectLiNGAM. A clear correlation between screen media activity and PGS was found for all types of screen time activities but only video games and social media correlated to the global surface area. Furthermore,  TV and video seem to affect lack of perseverance, and lack of perseverance, in turn, affects time spent on video games. These findings imply that different types of social media are not as alike as we thought and can affect adolescents differently. Taken together, these findings support previous research on screen media activity's effect on lack of perseverance, brain morphology, and cognitive performance, and propose new causal inference between genetics and screen time. Lastly, the algorithm used in this thesis project inferred reasonable causal orders and can be seen as a very good complement to today's causal modeling.