- Article
 
Rethinking Mental Health Assessment: A Network-Based Approach to Understanding University Students’ Well-Being with Exploratory Graph Analysis
- Laura García-Pérez,
 - Mar Cepero-González and
 - Jorge Mota
 
                              (1) Background: Mental health (MH) in university students is often studied through isolated variables. However, a dynamic systems perspective suggests that psychological well-being results from interactions among multiple dimensions such as personality, mood, resilience, self-esteem, and psychological distress. (2) Methods: A total of 928 university students (M = 21.01 ± 1.95) completed validated questionnaires: Big Five Inventory (BFI-44) for personality, Profile of Mood States (POMS), Connor-Davidson Resilience Scale (CD-RISC 25), Rosenberg Self-Esteem Scale, and Depression Anxiety Stress Scale (DASS-21). Exploratory Graph Analysis (EGA) using the EGAnet package in RStudio (v. 2025.09.01) was employed to identify latent dimensions and their interconnections. (3) Results: EGA revealed five stable and interconnected dimensions with good fit indices (TEFI = −9.00; ≥0.70): (a) Personality as socio-emotional regulation, (b) Mood as a generalized affective continuum, (c) Resilience as a unified coping process, (d) Self-esteem based on competence and self-worth, and (e) Psychological distress integrating depression, anxiety, and stress. (4) Conclusion: MH appears as a complex and dynamic network of interrelated psychological components. This network-based approach provides a more integrative understanding of well-being in students and supports the development of interventions that target multiple dimensions simultaneously, enhancing effectiveness in academic settings.
3 November 2025



