A network perspective on real-life threat, anxiety, and avoidance

BackgroundAnxiety, approach, and avoidance motivation crucially influence mental and physical health, especially when environments are stressful. The interplay between anxiety and behavioral motivation is modulated by multiple individual factors. This proof-of-concept study applies graph-theoretical network analysis to explore complex associations between self-reported trait anxiety, approach and avoidance motivation, situational anxiety, stress symptoms, perceived threat, perceived positive consequences of approach, and self-reported avoidance behavior in real-life threat situations. MethodsA total of 436 participants who were matched on age and gender (218 psychotherapy patients, 218 online-recruited nonpatients) completed an online survey assessing these factors in response to the COVID-19 pandemic. Results and DiscussionThe resulting cross-sectional psychological network revealed a complex pattern with multiple positive (e.g., between trait anxiety, avoidance motivation, and avoidance behavior) and negative associations (e.g., between approach and avoidance motivation). The patient and online subsample networks did not differ significantly, however, descriptive differences may inform future research.