Mapping relative proximity within an internalizing symptoms network

Understanding how symptom domains relate to one another (e.g., whether generalized anxiety is more similar to depression than to panic) is central to psychiatric classification. We demonstrate a procedure for quantifying relative proximity, defined as whether one symptom domain is statistically closer to another compared to other domains. As a motivating application, we examine the structure of internalizing symptoms characterized by fear, distress, avoidance, and heightened arousal. Using a network approach, we analyzed data from six questionnaires assessing depression, generalized anxiety disorder (GAD), social anxiety disorder, panic disorder, posttraumatic stress disorder (PTSD), and obsessive-compulsive disorder (OCD) symptoms. In a community sample of young adults (n = 2051; ages 17-23), we estimated a symptom-level Gaussian graphical model, used community detection to characterize the network's modular structure, and derived shortest path length to quantify the relative proximity of predefined symptom domains. We then used permutation testing to determine whether distress-related symptom domains (depression, GAD, and PTSD) showed greater empirical proximity to one another compared to fear-related domains (social anxiety, panic, and OCD). Results indicated reciprocal proximity between the depressive and GAD symptom domains compared to other internalizing domains. PTSD showed its greatest relative proximity to depression and GAD. Panic, social anxiety, and OCD did not form a cohesive fear community and showed variable relative proximity to both distress- and fear-related domains. Overall, these findings lend support for a distress-based internalizing dimension encompassing depression, GAD, and possibly PTSD, while providing limited evidence for a fear-based dimension including social anxiety, panic, and OCD.