Video gaming in a hyperconnected world: A cross-sectional study of heavy gaming, problematic gaming symptoms, and online socializing in adolescents
Aims Examining online social interactions along with patterns of video gaming behaviors and game addiction symptoms has the potential to enrich our understanding of disorders related to excessive video game play. Methods We performed latent class analysis in a sample of 9733 adolescents based on heavy use of games, social networking and instant messaging, and game addiction symptoms. We used latent class regression to determine associations between classes, psychosocial well-being and friendship quality. Results We identified two types of heavy gaming classes that differed in probability of online social interaction. Classes with more online social interaction reported fewer problematic gaming symptoms than those with less online social interaction. Most adolescents estimated to be in heavy gaming classes had more depressive symptoms than normative classes. Male non-social gamers had more social anxiety. Female social gamers had less social anxiety and loneliness, but lower self-esteem. Friendship quality attenuated depression in some male social gamers, but strengthened associations with loneliness in some male non-social gamers. Conclusions In adolescents, symptoms of video game addiction depend not only on video game play but also on concurrent levels of online communication, and those who are very socially active online report fewer symptoms of game addiction.
|Keywords||Depression, Friendship quality, Loneliness, Social anxiety, Social networking, Video games|
|Persistent URL||dx.doi.org/10.1016/j.chb.2016.11.060, hdl.handle.net/1765/108382|
|Journal||Computers in Human Behavior|
Colder Carras, M. (Michelle), van Rooij, A.J, van de Mheen, H, Musci, R. (Rashelle), Xue, Q.-L. (Qian-Li), & Mendelson, T. (Tamar). (2017). Video gaming in a hyperconnected world: A cross-sectional study of heavy gaming, problematic gaming symptoms, and online socializing in adolescents. Computers in Human Behavior, 68, 472–479. doi:10.1016/j.chb.2016.11.060