Issues and controversies surrounding the diagnosis and treatment of social anxiety disorder

Expert Review of Neurotherapeutics (Impact Factor: 2.78). 01/2014; 12(8). DOI: 10.1586/ern.12.81


Although much has been learned about social anxiety disorder (SAD) in recent decades, many questions and controversies surrounding its diagnosis and treatment have remained. Similar to the state of affairs with other psychiatric disorders, no clear pathophysiology has been identified for SAD, and the question of where to draw the line between shyness, SAD and even avoidant personality disorder continues to be debated. Much of the evidence to date suggests that among persons with SAD, it is under-recognized and undertreated; however, other researchers contend that it may be overdiagnosed in some individuals. Questions also remain as to how best treat these individuals, such as with pharmacotherapy, psychotherapy or a combination of the two. The aim of this review is to provide an overview of the controversies related to the diagnosis and treatment of SAD. In addition, suggestions for future research are provided that could perhaps clarify these remaining questions, such as maximizing treatment efficacy by targeting broader outcomes such as quality of life and addressing common comorbidities that occur with SAD.

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Available from: Kristy L Dalrymple, Sep 18, 2014
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    • "Recent studies on brain characteristics of SAD have demonstrated structural alterations in a number of temporal and frontal regions as well as in limbic structures, but in comparison to the functional studies, the findings are more mixed with no clear pattern of structural deviation [9] [10] [11] [12] [13]. Thus, to date, no reliable biomarker of SAD has been detected [14]. Analyses of brain imaging data typically use univariate methods to compare conditions or groups. "
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    ABSTRACT: Functional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n=14) from healthy controls (n=12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD.
    Behavioural brain research 11/2013; 259(100). DOI:10.1016/j.bbr.2013.11.003 · 3.03 Impact Factor
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    ABSTRACT: Since the inclusion of subtypes of social anxiety disorder (SAD) in the DSM-III-R, the most studied have been generalized versus specific subtypes. Previous research indicated that the generalized subtype was associated with greater severity, comorbidity and functional impairment compared to the specific subtype, but more recent evidence supports a dimensional conceptualization of SAD. Earlier studies also possessed limitations, such as heterogeneity in definitions of generalized SAD. Based on the more recent findings and the limitations of the earlier studies, the DSM-5 eliminated the generalized specifier. However, it also retained a categorical system by including a performance-based fear specifier, thus leaving an open debate on whether or not a dimensional or categorical system best describes SAD. Future research could examine other, more recent concepts as potential subtypes (e.g., attentional biases), or perhaps the larger question of the overall utility in subtyping SAD.
    Expert Review of Neurotherapeutics 11/2013; 13(11):1271-83. DOI:10.1586/14737175.2013.853446 · 2.78 Impact Factor
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    ABSTRACT: Evidence-based practice emphasizes the integration of empirically supported treatments with clinical expertise and unique client characteristics. The present study describes an integrative approach using Acceptance and Commitment Therapy (ACT) and skills training adapted from Dialectical Behavior Therapy (DBT) to treat a client with avoidant personality disorder (AvPD), comorbid adjustment disorder, and self-injurious behavior. The process of matching the therapies to the client and specific techniques to symptoms and problem behaviors is described. Ongoing clinical measures indicated reductions in depression, hopelessness, and anxiety. Behavioral measures indicated remission of cutting behavior and increases in social and physical activities. Results from a 1-month follow-up suggested maintenance of gains and continued reduction in symptoms. The Minnesota Multiphasic Personality Inventory-2 (MMPI-2) profile at follow-up as compared with pre-treatment indicated significant decreases in the client’s experience and perception of her symptoms. Endorsements on the Acceptance and Action Questionnaire-II (AAQ-II) at mid-treatment and follow-up suggested that the client achieved greater psychological flexibility. This case serves as evidence that individuals with AvPD and significant symptoms of anxiety and depression can be receptive to, and can benefit from, the integration of third-generation cognitive-behavioral therapies.
    Clinical Case Studies 03/2015; DOI:10.1177/1534650115575788
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