Recognizing individual variability in misophonia: Identifying symptom-based subgroups with Gaussian mixture modeling

Abstract

Misophonia is characterized by intense emotional and physiological reactions to everyday sounds such as chewing and tapping. While previous researchers have focused on defining and characterizing the disorder, limited attention has been given to the variability in symptom presentations across individuals. In this study, we sought to identify distinct subgroups of individuals with misophonia by applying a Gaussian finite mixture model to explore the heterogeneity of symptom profiles. Sixty treatment-seeking participants completed the Duke Misophonia Interview, which assessed the presence and severity of various behavioral, affective, and cognitive symptoms. Items from this measure served as model indicators. Two clusters were found: anticipatory and reactive. The anticipatory group reported heightened awareness of potential triggers, preemptive anticipatory distress, and increased avoidance behaviors, while the reactive group primarily displayed emotional and physiological responses during the occurrence of sounds. Notably, both groups reported similar frequencies of misophonic triggers, but the anticipatory group demonstrated greater internalizing symptoms, such as intrusive thoughts or rumination about misophonic sounds and social isolation. Our findings support the need for tailored interventions that address subgroup-specific symptom patterns. Future researchers should aim to include larger sample sizes and develop more comprehensive models to capture the full spectrum of misophonia symptoms, including externalizing behaviors.