Predicting Anxiety Symptoms Using the Uncertainty and Anticipation Model of Anxiety: A Prospective Longitudinal Study
摘要
The Uncertainty and Anticipation Model of Anxiety (UAMA) identifies five core components of pathological anxiety: inflated estimates of threat cost and probability, increased threat attention and hypervigilance, deficient safety learning, heightened reactivity to threat uncertainty, and avoidance. Despite the theoretical relevance of this model, the predictive validity of these components remains underexplored.
MethodsIn a prospective longitudinal study, 165 participants with varying levels of anxiety risk completed self-report measures of the five UAMA components at baseline. Anxiety, stress, and depressive symptoms, as well as real-life anxiety, were assessed at a 6-month follow-up. Multiple regression analyses examined the incremental predictive validity of UAMA components beyond baseline symptom levels.
ResultsIncreased threat attention and hypervigilance uniquely predicted anxiety symptoms, even after accounting for other UAMA components and baseline anxiety symptoms. Moreover, heightened reactivity to threat uncertainty significantly predicted anxiety, stress, and depressive, symptoms at follow-up.
ConclusionsSelf-reported increased threat attention and hypervigilance may serve as a distinct marker for identifying individuals at risk for developing anxiety symptoms. These findings support the predictive validity of the UAMA model, namely two components, heightened reactivity to uncertainty and increased threat attention and hypervigilance.