Elsevier

Journal of Affective Disorders

Volume 228, 1 March 2018, Pages 75-82
Journal of Affective Disorders

Research paper
Mapping network connectivity among symptoms of social anxiety and comorbid depression in people with social anxiety disorder

https://doi.org/10.1016/j.jad.2017.12.003Get rights and content

Highlights

  • Social anxiety disorder (SAD) and depressive symptoms often covary.

  • We applied network analytic methods to characterize the symptom-to-symptom associations between these disorders.

  • For each disorder, symptoms exhibiting the strongest cross-association with the other disorder were identified.

Abstract

Background

Social anxiety disorder (SAD) and depressive symptoms often covary. Yet, uncertainty still abounds vis-à-vis the individual symptom-to-symptom associations between these two disorders. Inspired by the network approach to psychopathology that conceptualizes comorbidity as a natural consequence arising from bridge symptoms that can transmit activation from one disorder to the other, we applied network analytic methods to characterize the associations among core symptoms of SAD—i.e. fear and avoidance of social situations—and comorbid depressive symptoms among 174 individuals with DSM-IV-TR criteria for SAD.

Methods

We first explored the general structure of these symptoms by estimating a regularized partial correlation network using the graphical LASSO algorithm. Then, we specifically focused on the symptoms’ importance and influence. Of critical interest was the estimation of the unique influence of each symptom from one disorder to all symptoms of the other disorder using a new metric called bridge expected influence.

Results

The graphical LASSO revealed several cross-associations between SAD and comorbid depression. For each disorder, symptoms exhibiting the strongest cross-association with the other disorder were identified.

Limitations

Given our cross-sectional data, our findings can only suggest hypotheses about cause-effect relationships.

Conclusions

This study adds to a small but growing empirical literature revealing that the co-occurrence between two disorders is best portrayed as sets of symptom-to-symptom connections. As some individual symptoms show differential association in the co-occurrence between SAD and depression, those symptoms may be valuable targets for future research and treatment.

Section snippets

Participants

The sample consisted of 174 individuals (72% female) with a primary DSM-IV-TR diagnosis of SAD. In addition, 47 had a comorbid diagnosis of major depressive disorder, 26 had a diagnosis of depression (not otherwise specified), and 5 had a diagnosis of dysthymia. The participants constitute a convenience sample of individuals who were recruited for five other studies who had, as a result of participating in those studies, completed questionnaires measuring symptoms of social anxiety and

Network estimation

We used a Graphical Gaussian Model (GGM) to estimate networks whose edges represent conditional independence relationships between nodes when controlling for the effects of all other nodes (Epskamp et al., 2017a). We regularized our model by running the graphical LASSO (Least Absolute Shrinkage and Selection Operator; Friedman et al., 2008). The aims of this procedure are two-fold. First, it computes (regularized) partial correlations between pairs of symptoms, thereby eliminating spurious

Results

In the figures depicting the networks and the centrality plots, we used the following abbreviations to designate the fear and avoidance of social situations as well as depressive symptoms. Each social situation from the LSAS is designated by a number ranging from 1 to 24 accompanied either by the letter “f” or “a”, representing fear and avoidance, respectively. Depressive symptoms are identified by the letter “d” and a number ranging from 1 to 21, referring to the 21 symptoms of the BDI-II.

Discussion

Many people with SAD also suffer from depression. To our knowledge, this is the first study to examine the empirical network structure of fear and avoidance of distinct situations among individuals with SAD and their relation with comorbid depression symptoms. Perhaps the most striking result was the observation, in line with previous network studies (e.g., Bekhuis et al., 2016; McNally et al., 2017b; Robinaugh et al., 2014), that not all nodes were equally important in determining the

Acknowledgments

The authors are thankful to the McNally Lab's members for their thoughtful comments and suggestions on a previous version of this manuscript.

Funding

This work was supported by a postdoctoral fellowship from the Helaers Foundation for Clinical Neuroscience; the Belgian Foundation for Vocation (“Vocatio”); and the WBI World Excellence Grant—BioWin: The Competitive Cluster in Health and Life Sciences of Wallonia [grant number: sub/2015/228106243177], all awarded to Dr. Alexandre Heeren. These foundations did not exert any editorial influence over this article.

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