Eun Jung Cha1, Sumin Hong1, Doo-Heum Park2, Seung-Ho Ryu2, Jee Hyun Ha2, Hong Jun Jeon3. 1. Department of Psychiatry, Konkuk University Medical Center, Seoul, Republic of Korea. 2. Department of Psychiatry, Konkuk University Medical Center, Seoul, Republic of Korea; Department of Psychiatry, School of Medicine, Konkuk University, Seoul, Republic of Korea. 3. Department of Psychiatry, Konkuk University Medical Center, Seoul, Republic of Korea; Department of Psychiatry, School of Medicine, Konkuk University, Seoul, Republic of Korea. Electronic address: hjjeon@kuh.ac.kr.
Abstract
BACKGROUND: Panic disorder is an anxiety disorder presenting panic attacks as a defining feature, with cognitive and behavioral symptoms that are associated with the panic attacks. Recently, the use of network analysis is increasing to determine the symptoms and mutual reinforcing patterns that conceptualize a mental disorder. This study aimed to improve our understanding of panic disorder by estimating a network structure of its symptoms. METHOD: Data from 257 patients diagnosed with panic disorder who visited the outpatient psychiatric clinic from 2018 to 2020 were collected. Panic attacks, cognitive and behavioral symptoms concerning the panic attacks, depression, and anxiety sensitivity dimensions such as fear of cardiovascular symptom, fear of publicly observable anxiety reaction, fear of respiratory symptom, and fear of cognitive dyscontrol were computed. Bootstrapping was applied to estimate the 95% confidence intervals for each edges. RESULTS: The resulting network indicated fear of cognitive dyscontrol, impairment in social functioning, phobic avoidance of situations, and panic-focused anticipatory anxiety to be central symptoms in panic disorder. Interestingly, panic attacks and distress during panic did not emerge as central. Depression was strongly linked to fear of cognitive dyscontrol. LIMITATIONS: The sample size limits network comparison tests between those with comorbid depression or agoraphobia. In addition, the cross-sectional design limits the opportunity to draw causal conclusions regarding the symptoms. CONCLUSIONS: These results have implications in etiology of panic disorder and support the efficaciousness of Cognitive Behavioral Therapy. Future network analyses may employ longitudinal designs to investigate causal relationships between the symptoms.
BACKGROUND: Panic disorder is an anxiety disorder presenting panic attacks as a defining feature, with cognitive and behavioral symptoms that are associated with the panic attacks. Recently, the use of network analysis is increasing to determine the symptoms and mutual reinforcing patterns that conceptualize a mental disorder. This study aimed to improve our understanding of panic disorder by estimating a network structure of its symptoms. METHOD: Data from 257 patients diagnosed with panic disorder who visited the outpatient psychiatric clinic from 2018 to 2020 were collected. Panic attacks, cognitive and behavioral symptoms concerning the panic attacks, depression, and anxiety sensitivity dimensions such as fear of cardiovascular symptom, fear of publicly observable anxiety reaction, fear of respiratory symptom, and fear of cognitive dyscontrol were computed. Bootstrapping was applied to estimate the 95% confidence intervals for each edges. RESULTS: The resulting network indicated fear of cognitive dyscontrol, impairment in social functioning, phobic avoidance of situations, and panic-focused anticipatory anxiety to be central symptoms in panic disorder. Interestingly, panic attacks and distress during panic did not emerge as central. Depression was strongly linked to fear of cognitive dyscontrol. LIMITATIONS: The sample size limits network comparison tests between those with comorbid depression or agoraphobia. In addition, the cross-sectional design limits the opportunity to draw causal conclusions regarding the symptoms. CONCLUSIONS: These results have implications in etiology of panic disorder and support the efficaciousness of Cognitive Behavioral Therapy. Future network analyses may employ longitudinal designs to investigate causal relationships between the symptoms.