Hypervigilance as a Specific Longitudinal Predictor of Anxiety Symptoms: A Self-Report Study
C. Sorroche, L. Prat-Torres, P. Chavarría-Elizondo, V. De la Peña-Arteaga, I. Martínez-Zalacaín, A. Juaneda-Seguí, E. Vilajosana, J. Raduà, C. Soriano-Mas, M. À. FullanaIntroduction
Hypervigilance is a distinctive attentional control state involving increased scanning of the environment to detect potential threats (Richards et al., Neurosci Biobehav Rev 2014; 47:102–117). Although it has been conceptually linked to anxiety, its specificity in predicting anxiety versus depressive symptoms remains unclear.
Objectives
This study aimed to examine the discriminant predictive validity of hypervigilance over time, assessing whether it serves as a specific longitudinal marker for anxiety symptoms compared to depressive symptoms.
Methods
A sample of 165 adults with varying levels of anxiety risk completed the Brief Hypervigilance Scale (BHS; Bernstein et al., Psychol Trauma 2015; 7:448–455) at baseline. Anxiety and depression symptoms were assessed six months later using the respective subscales of the Spanish version of the Depression Anxiety Stress Scales (DASS-21; Daza et al., J Psychopathol Behav Assess 2002; 24:195–205). Hierarchical regression analyses were conducted, controlling for age and baseline symptom levels.
Results
Hypervigilance significantly predicted anxiety symptoms at follow-up (β = .250, p = .003), accounting for an additional 4.1% of the variance beyond baseline anxiety. In contrast, its predictive value for depressive symptoms was non-significant (β = .119, p = .080). These findings suggest that hypervigilance may serve as a specific marker for anxiety vulnerability.
Conclusions
Self-reported hypervigilance demonstrates longitudinal specificity in predicting anxiety symptoms, but not depressive symptoms. These results support its potential utility in early identification and prevention strategies targeting anxiety disorders.
Disclosure of Interest
C. Sorroche: None Declared, L. Prat-Torres: None Declared, P. Chavarría-Elizondo: None Declared, V. De la Peña-Arteaga: None Declared, I. Martínez-Zalacaín: None Declared, A. Juaneda-Seguí: None Declared, E. Vilajosana: None Declared, J. Raduà Paid Instructor of: Dr. Raduà reports receiving continuing medical education honoraria from Inspira Networks for a machine learning course promoted by Adamed, outside the submitted work., C. Soriano-Mas: None Declared, M. À. Fullana: None Declared