Automatic Thought Systems: A Multinational Network Analysis Study

The aim of this study was to represent gender-based network models within a multinational sample to enhance the understanding of the interaction and clustering of indicators from the perspective of multivariate systemic models that describe the psychological phenomenon of automatic thoughts. A total of 3,964 participants from six countries (Saudi Arabia, China, Spain, Georgia, Turkey, and Peru), aged between 18 and 72 years (M = 25.0; SD = 9.20; 63.8% female), were included. The Automatic Thoughts Questionnaire was administered. The internal structure validity of the ATQ-8 was evaluated using confirmatory factor analysis (CFA). A Gaussian graphical model (GGM), representing a network based on regularized partial correlations, was employed. Nonparametric bootstrapping procedures based on 1,500 samples were used to assess the precision of edge estimations. The most central and statistically significant edge and node values were analyzed. Networks were compared across countries using the NetworkComparisonTest package. Network analysis reveals the internal structure of automatic thoughts, going beyond simple correlations or factorial models. The present study demonstrated that certain automatic thoughts (e.g., concerns related to self-worth) represent the core of negative thought patterns, making them ideal targets for intervention. The findings provide evidence of the interconnectedness among negative automatic thoughts. Concerns about self-worth emerged as the most central and influential nodes in this multinational study.