Abstract
In social anxiety disorder (SAD) co-morbid depressive symptoms as well as avoidance behaviors have been shown to predict insufficient treatment response. It is likely that subgroups of individuals with different profiles of risk factors for poor treatment response exist. This study aimed to identify subgroups of social avoidance and depressive symptoms in a clinical sample (N = 167) with SAD before and after guided internet-delivered CBT, and to compare these groups on diagnostic status and social anxiety. We further examined individual movement between subgroups over time. Using cluster analysis we identified four subgroups, including a high-problem cluster at both time-points. Individuals in this cluster showed less remission after treatment, exhibited higher levels of social anxiety at both assessments, and typically remained in the high-problem cluster after treatment. Thus, in individuals with SAD, high levels of social avoidance and depressive symptoms constitute a risk profile for poor treatment response.
1. Introduction
Randomized controlled trials (RCTs) show that cognitive behavioral therapy (CBT) in various formats (individual, group, as well as guided internet-delivered self-help) is effective for people with social anxiety disorder, or SAD (e.g., Andersson et al., 2014, Clark et al., 2006, Heimberg, 2002 and Mayo-Wilson et al., 2014). However, even with the best psychological treatments, more than one in four do not improve sufficiently (e.g., Ponniah & Hollon, 2008), and this heterogeneity in treatment response is worthy of further investigation. It is a rule rather than an exception that people have several mental health and somatic problems (Harvey, Watkins, Mansell, & Shafran, 2004), and co-morbidity is an important factor to consider in relation to treatment response. Depression and other anxiety disorders are common co-morbid problems in people with SAD (Kessler et al., 2005, Rapee and Spence, 2004 and Schneider et al., 1992). Moreover, use of dysfunctional emotion regulation strategies like avoidance behaviors (both on an overt and a covert level) are common in SAD. Such behaviors are positively related to clinical severity, and have been shown to maintain the disorder (Harvey et al., 2004). Importantly, it is likely the inflexible use of dysfunctional emotion regulation strategies, like avoidance behaviors, to manage intense anxiety in a range of different social situations that maintains SAD rather than the level of anxiety per se (Harvey et al., 2004). Hence, both co-morbidity and avoidance behavior could underlie heterogeneity in treatment response in individuals with SAD.
Indeed, co-morbid depressive symptoms as well as high levels of avoidance behavior have previously been shown to predict suboptimal treatment response in people with SAD (e.g., Eskildsen et al., 2010, Hedman et al., 2012, Nordgreen et al., 2012 and Rodebaugh et al., 2004), although the results regarding depressive symptoms have been mixed (Eskildsen et al., 2010, Nordgreen et al., 2012 and Rodebaugh et al., 2004). It can further be hypothesized that a combination of risk factors may particularly increase the risk for poor treatment outcome, possibly explaining the mixed findings regarding depressive symptoms as a treatment predictor. In other words, there may be subgroups of individuals with different profiles of risk factors for poor treatment response. However, when examining such risk profiles we cannot rely only on variable-oriented methods such as regression based approaches, which are commonly used in analyses of RCTs. First, the relationship between the predictors and outcome might not be linear. Second, there might be subgroups of people with profiles consisting of a combination of risk factors which could be hidden in variable-oriented methods (useful in understanding what characteristics co-aggregate in a group of individuals) and for which person-oriented methods (useful in finding subgroups of individuals) like cluster analysis are needed. Thus, the overall purpose of the current study was to use person-oriented, in addition to variable-oriented, methods to examine if treatment outcome in SAD is related to patterns of social avoidance and depressive symptoms.
Using cluster analysis we sought, first, to identify subgroups of social avoidance and depressive symptoms in a clinical SAD sample before and after ICBT and, second, to compare the derived subgroups on diagnostic status after treatment and on social anxiety symptom severity before and after ICBT. A final aim was to examine individual stability and movement between subgroups (clusters) from pre- to post-treatment. We hypothesized that a cluster of high social avoidance and depressive symptoms would be possible to identify and that this would be particularly characterized by poor treatment outcome.
