Clustering Adolescent Emotion Regulation Profiles via Gaussian Mixture Models
Keywords:
Adolescence, Emotion Regulation, Gaussian Mixture Models, Latent Profile Analysis, Mental Health, Person-Centered ApproachAbstract
Objective: The objective of this study was to identify and characterize the latent profiles of cognitive and habitual emotion regulation strategies among a normative adolescent sample utilizing a person-centered analytical framework.
Methods and Materials: This cross-sectional study involved a sample of Greek adolescents (aged to years) recruited via cluster sampling. Participants completed the validated Greek translations of the Cognitive Emotion Regulation Questionnaire (CERQ) and the Emotion Regulation Questionnaire (ERQ). Data were analyzed using Gaussian Mixture Modeling (GMM) to identify unobserved, multivariate configurations of emotion regulation strategies. Model fit indices, including the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and entropy, were utilized to determine the optimal number of latent profiles (denoted as ).
Findings: The GMM analysis revealed a profile solution as optimal. The largest group, labeled Adaptive Regulators ( , ), exhibited high use of constructive strategies (e.g., cognitive reappraisal) and low use of detrimental strategies. Maladaptive Regulators ( , ) were characterized by high levels of catastrophizing, rumination, and expressive suppression, alongside deficits in adaptive coping. The remaining Average Regulators ( , ) demonstrated mean-level scores across all assessed dimensions. Demographic analyses indicated a significant association between biological sex and profile membership ( , ), with females significantly overrepresented in the Maladaptive Regulators profile. No significant differences were observed across early versus late age groups ( , ).
Conclusion: Adolescents do not utilize emotion regulation strategies in isolation but rather deploy complex, distinct multivariate configurations. Identifying these latent profiles highlights the critical vulnerability of the maladaptive subgroup and underscores the necessity for targeted, personalized mental health interventions, such as tailored cognitive-behavioral or socio-emotional therapies, to mitigate psychopathology risk and promote normative developmental trajectories.
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