Emotion-specific regulation components differentially predict profiles of adolescent psychosocial dysfunction

Area of Science:

• Psychology
• Adolescent Psychiatry
• Developmental Psychology

Background:

• Emotion regulation (ER) difficulties are a transdiagnostic risk factor for adolescent psychopathology.
• High intercorrelations among ER components hinder research.
• A data-driven approach is needed to identify distinct dysfunction profiles and stable ER predictors.

Purpose of the Study:

• To identify distinct profiles of adolescent dysfunction using a data-driven approach.
• To select a parsimonious set of stable, emotion-specific regulatory predictors.
• To examine the emotion-context dependency of ER strategies in predicting dysfunction severity.

Main Methods:

• A sample of 795 Iranian adolescents completed measures of emotion-specific ER (CERSA), psychosocial adjustment (SDQ), pathological traits (PID-5-BF), and disability (WHODAS-12).
• Person-centered cluster analysis identified dysfunction profiles, followed by ordinal LASSO penalized regression to select stable ER predictors, embedded within a full-pipeline bootstrap.
• Latent profile analysis was used for sensitivity analysis and replication.

Main Results:

• Three stable clusters emerged, reflecting a severity gradient: low-, moderate-, and high-dysfunction, replicated via latent profile analysis.
• Eight stable ER predictors were retained, with general dysregulation across emotions being the strongest maladaptive predictor.
• Specific strategies showed context-dependent effects: Rumination-Anger predicted greater dysfunction, while Reappraisal-Anger and Support Seeking-Sadness predicted lower dysfunction severity.

Conclusions:

• General dysregulation may represent transdiagnostic vulnerability in adolescents.
• Specific ER strategies demonstrate emotion-context dependency, supporting functionalist theories.
• The adaptiveness of ER strategies depends on matching them to an emotion's specific function.