Interactions between symptoms of depression, stress, and anxiety in university students: A network analysis
The psychological processes of depression, stress, and anxiety have traditionally been measured by indicators and analyzed by dimensional reduction methods (e.g. exploratory factor analysis). Due to some limitations on the results obtained by the classical methods, we considered a Network Analysis approach. In this setup, the symptoms form a complex dynamical system with interactions among them. The symptoms could mediate, moderate, increase, or decrease other symptoms. In this study, we built the symptom networks to analyze the interactions of the factors of the depression, anxiety, and stress processes in a sample of university students. We used a Network Analysis in JASP to estimate the network structure of DASS21 symptoms (Depression, Anxiety Stress Scale) evaluated in 174 university students from the Benemérita Universidad Autónoma de Puebla, Mexico. We built the networks through the Graphic Gaussian Model to discriminate edges and we selected the lowest EBIC model. We measured the indices of centrality, cluster, strength, closeness, and intermediates. We present the results for students of different areas of knowledge and the corresponding gender networks. Based on the results, appropriate intervention programs could be constructed for the particular symptoms shown in the different groups of participants.