An integrative network approach to social anxiety disorder: The complex dynamic interplay among attentional bias for threat, attentional control, and symptoms. (August 2016)

• Record Type: Journal Article
• Authors: Heeren, Alexandre; McNally, Richard J.
• Is Part Of: Journal of anxiety disorders. Volume 42(2016:Aug.)
• Page Start: 95
• Page End: 104
• Publication Date: 2016-08
• Subjects: Network analysis -- Graph theory -- Attentional bias for threat -- Attention networks -- Social anxiety disorder -- Community detection -- Computational social sciences; Anxiety -- Periodicals; Anxiety Disorders -- Periodicals; Angoisse -- Périodiques; Electronic journals; 616.8522
• DOI: 10.1016/j.janxdis.2016.06.009
• Languages: English
• ISSNs: 0887-6185

Abstract

Graphical abstract: Highlights: We present network models of relations among measures of attentional components and symptoms of social anxiety disorder. The orienting component of attention as well as both avoidance and fear of social situations plays a central role. Neither attentional engagement with nor difficulty disengaging from threat exhibits high relative importance. Abstract: Cognitive models posit that social anxiety disorder (SAD) is associated with and maintained by biased attention allocation vis-à-vis social threat. However, over the last decade, there has been intense debate regarding whether AB in SAD results from preferential engagement with or difficulty in disengaging from social threat. Further, recent evidence suggests that AB may merely result from top-down attentional impairments vis-à-vis non-emotional material. Consequently, uncertainty still abounds regarding both the relative importance and the mutual interactions of these different processes and SAD symptoms. Inspired by novel network approaches to psychopathology that conceptualize symptoms as complex dynamic systems of mutually interacting variables, we computed weighted directed networks to investigate potential causal relations among laboratory measures of attentional components and symptoms of social anxiety disorder. Global and local connectivity of network structures revealed that the three most central variables were the orienting component of attention as well as both avoidance and fear of social situations. Neither preferential attention engagement with threat nor difficulty disengaging from threat exhibited high relative importance as predictors of symptoms in the network. Together, these findings suggest the value of extending the network approach beyond self-reported clinical symptoms to incorporate process-level measures from laboratory tasks to gain new insight into the mechanisms of SAD.