Understanding the relationships among adolescents' internet dependence, reward, cognitive control processing, and learning burnout: a network perspective in China

Abstract

Alterations in the reward and cognitive control systems are commonly observed among adolescents with internet dependence (ID), and this impairment is often accompanied by social dysfunctions, such as academic burnout. However, the intercorrelations among ID, reward, cognitive control processing, and learning burnout remain unclear. We recruited 1074 Chinese adolescents to investigate the complex interrelationships among these variables using network analysis. The resulting network revealed patterns that connected ID to the behavioral inhibition/activation system (BIS/BAS), self-control, and learning burnout; these results exhibited reasonable stability and test-retest consistency. Throughout the network, the node of BAS-drive was the critical influencing factor, and the node of self-control was the protection factor. In addition, several symptoms of learning burnout and ID were positively associated with sensitivity to punishment. As revealed by the network comparison test, the network constructed among internet dependent (ID) group differed from the network constructed among internet nondependent (IND) group not only in the edges between BIS and learning burnout but also in terms of the edges associated with learning burnout. In conclusion, this study provides insights into the complex mechanisms underlying ID among adolescents from the perspective of the network relationships between core influencing factors and negative consequences. It validates the dual-system model of risky behavior among adolescents and offers a foundation for early warning and interventions for ID in this context.

Keywords: Adolescents; BAS/BIS; Internet dependence; Learning burnout; Network analysis; Self-control.

Fig. 1

(A) Graphical representation of the network model of ID, behavioral inhibition/activation system, self-control, and learning burnout. (B) Standardized EI centrality estimates. Note Blue edges indicate positive relations, and red edges indicate negative relations. Thicker edges represent stronger associations. YDQ: Young’s Diagnostic Questionnaire; BIS: Behavioral Inhibition System; BAS1: Drive; BAS2: Reward Responsiveness; BAS3: Fun-Seeking; SCS: Self-Control Scale; LBS1: Emotional Exhaustion; LBS2: Lack of Learning Self-Efficacy; LBS3: Alienated Relationship with Teacher; LBS4: Physical Exhaustion (the thickest edge represents a value of 0.38)

Fig. 2

(A) Bootstrapped 95% confidence intervals of the edge weights of the network; (B) Nonparametric bootstrapped difference tests for the edge weights of the network. Note The red line indicates the sample values, and the gray area represents 95% confidence intervals. All bootstrap confidence intervals were sufficiently small to ensure a fair amount of confidence regarding their stability. Black boxes represent nodes that do differ significantly from one another, while gray boxes indicate nodes that do not differ significantly from one another. The diagonal represents the standardized node’s expected influence. YDQ: Young’s Diagnostic Questionnaire; BIS: Behavioral Inhibition System; BAS1: Drive; BAS2: Reward Responsiveness; BAS3: Fun-Seeking; SCS: Self-Control Scale; LBS1: Emotional Exhaustion; LBS2: Lack of Learning Self-Efficacy; LBS3: Alienated Relationship with Teacher; LBS4: Physical Exhaustion

Fig. 3

(A) The network models of the ID group (n = 385) and (B) the IND group (n = 689); (C) standardized EI estimates of the networks of the ID and IND groups. NoteBlue edges indicate positive relations, and red edges indicate negative relations. Thicker edges represent stronger associations. YDQ: Young’s Diagnostic Questionnaire; BIS: Behavioral Inhibition System; BAS1: Drive; BAS2: Reward Responsiveness; BAS3: Fun-Seeking; LBS1: Emotional Exhaustion; LBS2: Lack of Learning Self-Efficacy; LBS3: Alienated Relationship with Teacher; LBS4: Physical Exhaustion; SCS: Self-Control Scale