Social Anxiety Typologies in Gamers A Latent Class Analysis Approach - Mukhammad Iskhaq Khakim; Rizky Putra Santosa (Universitas Negeri Semarang, 2026)
Gaming and esports have become increasingly embedded in the daily lives of young adults, yet the psychological experiences of gamers remain unevenly understood. Social anxiety, for example, is often examined as if all players experience it in similar ways. Such an assumption may overlook important differences between individuals. Drawing on a secondary dataset of 13,050 gamers, this study used Latent Class Analysis (LCA) to identify hidden patterns of social anxiety based on responses to the Social Phobia Inventory (SPIN). Seventeen SPIN items were converted into binary indicators before model estimation. Several class solutions were compared using AIC, BIC, and entropy values. The analysis supported a five-class structure consisting of Minimal Anxiety, Performance Anxiety, Moderate Anxiety, Interaction Anxiety, and Severe Anxiety profiles. Distinct response configurations emerged across classes, particularly between performance-related fear and interaction-related discomfort. These findings indicate that social anxiety among gamers does not develop in a uniform manner. Instead, different groups appear to experience anxiety in context-specific ways that may require different forms of psychological support in gaming and esports environments