Childhood psychological maltreatment and internet gaming addiction in Chinese adolescents: Mediation roles of maladaptive emotion regulation strategies and psychosocial problems.

BACKGROUND: Internet gaming addiction (IGA) is a global concern, especially among young children. There have been some suggestions that childhood psychological maltreatment influences the development of IGA, but evidence for this has thus far been lacking. OBJECTIVE: The goal of this study was to investigate the association between childhood psychological maltreatment and IGA in adolescents and the mediation roles of maladaptive emotion regulation strategies and psychosocial problems (depression and social anxiety). METHODS: This study recruited 1280 (girls = 690) middle school students with a mean age of 16.09 ± 0.98 years old. All participants undertook a standardized assessment of childhood psychological maltreatment, maladaptive emotion regulation strategies, psychosocial problems (depression and social anxiety), and IGA. RESULTS: We examined whether the effect of childhood psychological maltreatment on IGA was mediated by maladaptive emotion regulation strategies and psychosocial problems (depression and social anxiety). Both parallel and sequential mediation analysis showed that maladaptive emotion regulation strategies and depression mediated the relationship between childhood psychological maltreatment and IGA. CONCLUSIONS: Childhood psychological maltreatment is positively associated with IGA in adolescents. Maladaptive emotion regulation strategies and depression both significantly mediated the relationship between childhood psychological maltreatment and IGA.

Bidirectional selection between two classes in complex social networks.

The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals' neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.