A network perspective on real-life threat: Complex associations between trait and situational anxiety, stress, and individual approach-avoidance tendencies

Abstract

Anxiety and approach-avoidance conflicts are crucial factors influencing mental and physical health, especially when environments are stressful. Their interplay is modulated by multiple state and trait factors. Therefore, focusing on some specific associations, which represents the dominant approach in most previous work on anxiety and avoidance, can only provide limited insights and does not capture the whole complexity of the interaction patterns between psychological factors. This study applied graph-theoretical network analysis to investigate associations between self-reported trait anxiety, approach and avoidance tendencies, situational anxiety, stress symptoms, perceived threat, perceived positive consequences of approach, and avoidance behavior in situations of real-life threat. 541 participants (218 psychotherapy patients, 323 participants from the general community) completed an online survey assessing threat-related traits and states, and responses towards public situations during the COVID-19 pandemic. The resulting psychological network revealed a complex pattern with positive (e.g., between trait anxiety, avoidance motivation, and avoidance behavior) and negative associations (e.g., between approach and avoidance motivation). The patient and community subsample networks were not significantly different, but descriptive effects may inform future research. Our study shows that network analysis provides a promising tool to get comprehensive insights into complex associations between state and trait factors influencing psychological health.