Identifying the central symptoms of problematic social networking sites use through network analysis Cover Image

Identifying the central symptoms of problematic social networking sites use through network analysis
Identifying the central symptoms of problematic social networking sites use through network analysis

Author(s): Andrea Svicher, Giulia Fioravanti, Silvia Casale
Subject(s): Behaviorism
Published by: Akadémiai Kiadó
Keywords: behavioral addictions; technological addictions; Generalized Problematic Internet Use Scale-2; problematic social media use; problematic social networking sites use; network analysis

Summary/Abstract: Background: Problematic social media use (PSMU) has received growing attention in the last fifteen years. Even though PSMU has been extensively studied, its internal structure is not fully understood. We used network analysis to evaluate which symptoms and associations between symptoms are most central to PSMU – as assessed by the Generalized Problematic Internet Use Scale-2 adapted for PSMU – among undergraduates. Method: Network analysis was applied to a large gender-balanced sample of undergraduates (n 5 1344 participants; M 5 51.9%; mean age 5 22.50 ± 2.20 years). Results: The most central nodes in the network were the difficulty of controlling one’s own use of social media, the tendency to think obsessively about going online, the difficulties in resisting the urge to use social media and the preference for communicating with people online rather than face-to-face. This last element was strongly associated with a general preference for online social interactions and the feeling of being more comfortable online. The network was robust to stability and accuracy tests. The mean levels of symptoms and symptom centrality were not associated. Conclusions: Deficient self-regulation and preference for online communication were the most central symptoms of PSMU, suggesting that these symptoms should be prioritized in theoretical models of PSMU and could also serve as important treatment targets for PSMU interventions.

  • Issue Year: 10/2021
  • Issue No: 3
  • Page Range: 767-778
  • Page Count: 12
  • Language: English