Social Anxiety and Depression: Two Peas in a Pod?

anxietea

A guest post by Haley Elliott

Imagine getting a text from a friend saying they can’t hang out this weekend and spending the next several hours wondering if they don’t want to be friends anymore. Or experiencing an overwhelming sense of panic at the very thought of presenting your research at the conference you’re attending next month. What if the fear of being watched or running into someone you know made it difficult to do something as simple as grocery shopping?

These experiences are just a few examples of how social anxiety disorder (SAD) can impede a person’s daily life. SAD, characterized by an intense fear and avoidance of social situations that involve interacting with strangers or performance evaluation, is the third most prevalent psychiatric disorder in the U.S., affecting almost 15 million people.

SAD has a high rate of comorbidity with depression, further complicating symptom severity and treatment of individuals suffering from SAD. More specifically, comorbid depression in individuals with SAD has been linked to SAD persistence, alcohol abuse, higher risk for suicide, and poorer treatment outcomes. Treatment of individuals with comorbid psychological disorders is particularly challenging, given the mechanisms of comorbidity are poorly understood. Frontline manualized evidence-based psychotherapies (EBPs) often provide little to no guidance on how to deal with comorbidity, and clinician capacity is strained trying to learn and integrate independent protocols to treat patients with comorbid disorders.

Comorbidity Defined

Why have the mechanisms underlying comorbidity between psychological disorders been so elusive in research thus far? Perhaps the answer can be found in how clinicians and researchers define comorbidity.

Until recently, comorbidity has been viewed through the lens of diagnostic labels and their unobservable latent causes. From this point of view, SAD and MDD occur together because of a relationship between two isolated latent variables. This approach, however, is not particularly useful in figuring out how the disorders are related or what to target during treatment of individuals with both SAD and MDD. Medical disorders (e.g. the flu, cancer, common cold) can be easily attributed to some underlying variable, such as a specific virus or a tumor. Research to date has yet to identify such latent causes in psychological disorders that we can target in treatment.

The network approach to psychopathology offers a new way to define comorbidity based on interactions between observable symptoms. This approach visualizes symptoms as self-sustaining feedback loops which, when activated, constitute an episode of the disorder. From this view, comorbidity can be defined as a series of causal interactions between symptoms, which often cluster together in stable groups. These clusters can then be connected by “bridge symptoms,”which may be valuable targets for treatment.

Network analysis has been used to examine comorbidity in many different contexts, including:

SAD and Depression: A Recent Network Analysis

A recent study by Heeren, Jones, and McNally (2018) used network analysis to examine comorbidity with depression in patients with SAD. Again, comorbid depression in patients with SAD has been linked to a more severe course of illness and poorer treatment outcomes, so identifying bridge symptoms between the two disorders could improve treatment and provide direction for preventative interventions. In theory, treating bridge symptoms should have a and deactivate symptoms throughout both the depression and SAD networks.

sadnet

The depression symptoms most strongly associated with SAD symptoms include:

  • Suicidal ideation
  • Loss of interest
  • Loss of pleasure*

The SAD symptoms most strongly associated with depressive symptoms include:

  • Avoidance of participating in small groups*
  • Avoidance of going to a party
  • Fear of working while being observed

Of these bridge symptoms, loss of pleasure and avoidance of participating in small groups emerged as having the highest influence. Based on prior work which examines the potential utility of using network analysis in clinical practice, targeting bridge symptoms during treatment could deactivate nodes in both the SAD and the depression networks.

What’s Next?

While an increasing number of studies have begun to apply network analysis to investigate comorbidity between different disorders, additional research is necessary to see how effective targeting bridge symptoms during treatment is in practice. Shifting our definition of comorbidity away from one based on unobservable latent variables (i.e. depression) which cause symptoms, and towards one where symptoms are causally linked to one another and constitute the disorders themselves could have profound effects on treatment and prevention.

This approach does not necessarily preclude the idea that boxes can be drawn around discrete, but related, disorders. Symptoms do tend to cluster together in stable, predictable ways. For example, in SAD, fear speaking up at a meeting is clearly linked to avoidance of situations that would force an individual to do so. What is important to realize is that how symptoms interact with one another varies at an individual level, which generates significant heterogeneity at the individual level. One person’s experience with SAD and comorbid depression is not the same as every other patient’s experience simply because we use the same diagnostic label for them.

If we truly want to move forward with developing effective treatment and preventative interventions for individuals with comorbid psychological disorders, we must begin taking a more individualized approach that looks at how symptoms interact with one another in a specific patient’s network. Doing so will allow clinicians to more accurately select which treatment will be most effective for individual patients and hopefully increase positive outcomes in the long-term.

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

w

Connecting to %s