Examining the role of emotion regulation, anger, and anxiety in misophonia: A network model - Matthew R. Hanna; Amanda C. Collins; Yanyan Shan; Bill Chen; Siyuan Wang; M. Zachary Rosenthal (PLoS ONE, 2025)
Background Misophonia, characterized by intense negative reactions to specific sounds, is associated with significant emotional distress. The connections among misophonia severity and factors like emotion regulation, anxiety, and anger remain unclear. This study uses network analysis to clarify these relationships in adults with self-reported misophonia symptoms, identifying key intervention targets and processes driving symptom severity. Methods A community sample of adults with misophonia symptoms and impairment (N = 205) completed psychometrically validated self-report measures, including the Duke Misophonia Questionnaire (DMQ), Misophonia Questionnaire (MQ), and assessments of emotion regulation, anxiety, and anger. Network analysis was conducted to identify associations among misophonia severity, anxiety, anger, and emotion regulation components. Centrality indices were used to evaluate the most influential factors in the network, and community detection was employed to explore underlying clusters. Results Misophonia severity was most strongly associated with emotional awareness, nonacceptance, anxiety, and anger. The network analysis revealed that nodes representing emotion regulation strategies, nonacceptance, and impulsivity had the highest centrality and expected influence values, indicating their significant role in the overall network. Community detection identified two distinct clusters: one reflecting emotion dysregulation and misophonia, and the other related to emotional clarity and awareness. Conclusions This study highlights the importance of nonacceptance, emotional awareness, anger, and anxiety in understanding misophonia severity. Interventions targeting anger, anxiety, and nonacceptance may be most effective in managing misophonia symptoms. Future research should explore these relationships longitudinally to better inform treatment approaches.