Mapping Emotion Regulation Patterns Within the Alternative Model of Personality Disorders Personality Traits.
Published In: Journal of Personality Disorders, 2024, v. 38, n. 4. P. 311 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Stulcbauer, Lewis B.; Chen, Wai; Gross, James J.; Krueger, Robert F.; Preece, David A. 3 of 3
Abstract
Personality pathology is associated with emotional problems that are potentially attributable to problematic emotion regulation strategy patterns. We evaluated the emotion regulation strategies associated with the pathological personality traits in the Alternative Model of Personality Disorders (AMPD). A total of 504 participants completed measures of AMPD traits and strategy usage, which were analyzed using hierarchical regressions and latent profile analysis (LPA). Regression results demonstrated that each trait was associated with a unique strategy pattern: negative affect with emotional overengagement, detachment with socialemotional avoidance, antagonism with emotional externalization/avoidance, disinhibition with emotional avoidance and overengagement, and psychoticism with strategies linked to psychotic/dissociative experiences. The LPA identified three profiles with heightened AMPD traits: an internalizing/distressed profile, an externalizing/distressed profile, and a schizoid-schizotypal profile; each had a unique strategy pattern that varied depending on trait composition. This research highlights the relevance of emotion regulation strategy patterns in the assessment, conceptualization, and treatment of personality pathology. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Personality Disorders. 2024/08, Vol. 38, Issue 4, p311
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2024
- ISSN:0885-579X
- DOI:10.1521/pedi.2024.38.4.311
- Accession Number:178816405
- Copyright Statement:Copyright of Journal of Personality Disorders is the property of Guilford Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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