Interpersonal Psychotherapy for Social Anxiety Disorder

2012 ◽  
pp. 169-184 ◽  
Author(s):  
Joshua D Lipsitz
Keyword(s):  
Differential Diagnosis ◽  
Anxiety Disorder ◽  
Social Anxiety ◽  
Medical History ◽  
Empirical Evidence ◽  
Social Anxiety Disorder ◽  
Interpersonal Psychotherapy ◽  
Symptom Change ◽  
Case Discussion ◽  
Change State

Chapter 10 discusses interpersonal psychotherapy for social anxiety disorder, and covers interpersonal problem areas, stages of IPT, assessing symptom change, state of the empirical evidence, and a case example showing personal, psychiatric, family, and medical history, differential diagnosis and indication for IPT, IPT formulation, and case discussion.

Processes in cognitive behavior therapy for social anxiety disorder: Predicting subsequent symptom change

2019 ◽  
Vol 67 ◽  
pp. 102118 ◽  
Author(s):  
Fredrik Santoft ◽  
Sigrid Salomonsson ◽  
Hugo Hesser ◽  
Elin Lindsäter ◽  
Brjánn Ljótsson ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Social Anxiety ◽  
Social Anxiety Disorder ◽  
Behavior Therapy ◽  
Cognitive Behavior Therapy ◽  
Cognitive Behavior ◽  
Symptom Change

scholarly journals Does Centrality in a Cross-Sectional Network Suggest Intervention Targets for Social Anxiety Disorder?

2018 ◽  
Author(s):  
Thomas Rodebaugh ◽  
Natasha April Tonge ◽  
Marilyn Piccirillo ◽  
Eiko I Fried ◽  
Arielle Horenstein ◽  
...  
Keyword(s):  
Anxiety Disorder ◽  
Social Anxiety ◽  
Social Anxiety Disorder ◽  
Partial Correlation ◽  
State Of The Art ◽  
Symptom Change ◽  
Cross Sectional ◽  
Network Analyses ◽  
Treatment Data ◽  
Item Properties

Objective: Network analysis allows us to identify the most interconnected (i.e., central) symptoms, and multiple authors have suggested that these symptoms might be important treatment targets. This is because change in central symptoms (relative to others) should have greater impact on change in all other symptoms. It has been argued that networks derived from cross-sectional data may help identify such important symptoms. We tested this hypothesis in social anxiety disorder. Method: We first estimated a state-of-the-art regularized partial correlation network based on participants with social anxiety disorder (N = 910) to determine which symptoms were more central. Next, we tested whether change in these central symptoms were indeed more related to overall symptom change in a separate dataset of participants with social anxiety disorder who underwent a variety of treatments (N = 244). We also tested whether relatively superficial item properties (infrequency of endorsement and variance of items) might account for any effects shown for central symptoms. Results: Centrality indices successfully predicted how strongly changes in items correlated with change in the remainder of the items. Findings were limited to the measure used in the network and did not generalize to three other measures related to social anxiety severity. In contrast, infrequency of endorsement showed associations across all measures. Conclusions: The transfer of recently published results from cross-sectional network analyses to treatment data is unlikely to be straightforward.

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