Identifying Cognitive-Affective Risk Subgroups for Explosive Anger in a General Population Sample: A Cluster Analysis...

Area of Science:

• Psychology
• Neuroscience
• Criminology

Background:

• Recurrent impulsive aggression exhibits significant heterogeneity in underlying risk mechanisms.
• Current assessment and intervention strategies often fail to address this heterogeneity.
• Identifying distinct mechanistic profiles can improve risk assessment and treatment matching for explosive anger.

Purpose of the Study:

• To identify subgroups within a general population sample based on cognitive, emotional, and impulsivity risk factors.
• To examine whether these identified subgroups differ in aggression-related and violence-related outcomes.

Main Methods:

• A UK-based adult general population sample (N = 773) completed validated measures of cognitive distortions, emotion dysregulation, and trait impulsivity.
• K-means cluster analysis was employed to identify subgroups with distinct mechanistic profiles.
• Subgroup stability was assessed using multiple validation procedures, and comparisons were made on aggression history, trait aggression, antisocial behavior, and violent tendencies.

Main Results:

• Three distinct risk profiles emerged: 'Multi-Domain High Risk', 'Elevated-Impulsivity', and 'Low-Risk'.
• The 'Multi-Domain High Risk' group exhibited the highest levels of aggression and violence.
• Individuals in the 'Multi-Domain High Risk' group were significantly more likely to report a history of violence and endorse violent responses compared to the 'Low-Risk' group.

Conclusions:

• Mechanism-based clustering successfully identified interpretable risk profiles for explosive anger.
• These profiles differ substantially in aggression- and violence-related outcomes, highlighting heterogeneity in risk.
• Further research with longitudinal and clinically diagnosed samples is needed to guide clinical applications.