Abstract

BackgroundThe current study's goal was to examine the multivariate patterns of associations between schema modes and emotion regulation mechanisms in personality disorders. Schema modes are either integrated or dissociative states of mind, including intense emotional states, efforts to regulate emotions, or self-reflective evaluative thought processes. Exploring the multivariate patterns of a shared relationship between schema modes and emotion regulation strategies may lead to a better understanding of their associations and a deeper understanding of the latent personality profiles that organize their associations in a mixed personality disorder sample.MethodsPatients who have personality disorders (N = 263) filled out five different self-report questionnaires, out of which four measured adaptive and maladaptive emotion-regulation strategies (Cognitive Emotion Regulation Questionnaire, Difficulty of Emotion Regulation Scale, Five Factor Mindfulness Questionnaire, Self-Compassion Scale), and the fifth one assessed schema modes (Schema Mode Inventory). We conducted canonical correlation analysis in order to measure the multivariate patterns of associations between the 26 emotion regulation and the 14 schema mode subscales.ResultsWe found strong multivariate associations between schema modes and emotion regulation strategies. Collectively, the full model based on all canonical variate pairs was statistically significant using the Wilks’s Λ = .01 criterion, F (364,2804.4) = 3.5, p < .001. The first two canonical variate pairs yielded interpretable squared canonical correlation (Rc2) effect sizes of 74.7% and 55.8%, respectively. The first canonical variate pair represents a general personality pathology variable with a stronger weight on internalization than externalization, and bipolarity in terms of adaptive vs. non-adaptive characteristics. We labeled this variate pair "Adaptive/Non-Adaptive." The second canonical variate pair, labeled "Externalizing", represents externalizing schema modes and emotion regulation strategies.ConclusionUsing a multivariate approach (CCA), we identified two independent patterns of multivariate associations between maladaptive schema modes and emotion regulation strategies. The Adaptive/Non-Adaptive general personality pathology profile and the Externalizing personality pathology profile may lead to a deeper understanding of personality disorders and help psychotherapists in their conceptualization in order to design the most appropriate interventions.

Highlights

  • Theoretical Background Schema Therapy (ST) was developed by J.E

  • Canonical Correlation Analysis A CCA was conducted using nine Cognitive Emotion Regulation Questionnaire (CERQ), six Difficulties in Emotion Regulation Scale (DERS), five FFMQ, six Self-Compassion Scale (SCS) sub-scales as independent variables, and the 14 SMI schema modes as dependent variables to analyze the multivariate shared relationship between schema modes and emotion regulation strategies

  • The Non-adaptive side of the first canonical variate pair represents the general personality pathology, or 'p factor', with externalizing and internalizing pathology, which is an indicator of a broad predisposition to psychopathology

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Summary

Introduction

Theoretical Background Schema Therapy (ST) was developed by J.E. Young [1] to treat personality disorders and chronic Axis I disorders. A central element of ST is the concept of schema mode, which is a recurring pattern of intense emotions, thoughts, feelings, and behavior that is active at a given point in time [2]. When maladaptive schema modes are active, the person is in a dissociative state of mind. The adaptive Healthy Adult mode integrates adaptive thoughts, behaviors, and cognitions leading to wellfunctioning emotion regulation, while the Happy Child is a mode where basic emotional needs are met, and the person feels loved, accepted and agented. Exploring the multivariate patterns of a shared relationship between schema modes and emotion regulation strategies may lead to a better understanding of their associations and a deeper understanding of the latent personality profiles that organize their associations in a mixed personality disorder sample

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