Biased Cognitions & Social Anxiety: Building a Global Framework for Integrating Cognitive, Behavioral, and Neural Processes

• Main Author: Wolf-Gero Lange (auth)
• Other Authors: Pierre Philippot (auth), Alexandre Heeren (auth), Quincy Wong (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: Frontiers Media SA 2015
• Series: Frontiers Research Topics
• Subjects: Neurosciences; clinical psychology; Behavior Therapy; experimental cognitive psychopathology; cognitive biases; Affective Neuroscience; anxiety disorders and cognitive bias modification; Cognitive Therapy; social anxiety
• Online Access: DOAB: download the publication; DOAB: description of the publication

Social anxiety (SA) is a common and incapacitating disorder that has been associated with seriously impaired career, academic, and general social functioning. Regarding epidemiological data, SA has a lifetime prevalence of 12.1% and is the fourth most common psychopathological disorder (Kessler et al., 2005). At a fundamental point of view, the most prominent cognitive models of SA posit that biased cognitions contribute to the development and maintenance of the disorder (e.g., Clark & Wells, 1995; Rapee & Heimberg, 1997). Over the last decades, a large body of research has provided evidence that individuals suffering from SA exhibit such biased cognitions at the level of visual attention, memory of social encounters, interpretation of social events, and in judgment of social cues. Such biased cognitions in SA has been studied in different ways within cognitive psychology, behavioral psychology, clinical psychology, and cognitive neuroscience over the last few decades, yet, integrative approaches for channeling all information into a unified account of biased cognitions in SA has not been presented so far. The present Research Topic aims to bring together theses different ways, and to highlight findings and methods which can unify research across these areas. In particular, this Research Topic aims to advance the current theoretical models of SA and set the stage for future developments of the field by clarifying and linking theoretical concepts across disciplines.