JOURNAL ARTICLE
Contingent Self-Esteem and Narcissism: An Exploration of Momentary Processes.
Published In: Journal of Personality Disorders, 2025, v. 39, n. 6. P. 486 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Edershile, Elizabeth A.; Jensen, Lily C. X.; Wright, Aidan G. C. 3 of 3
Abstract
Contingent self-esteem, or the notion that self-worth is tied to successes or failures, is theorized to be important to narcissism. Contingent self-esteem likely manifests as a dynamic between transient states (e.g., emotions) and feelings of self-worth. The current study examined whether narcissism was associated with the link between negative affect and self-esteem. Participants (N = 862) came from two samples of undergraduates and one of community individuals. Participants completed trait-based assessments of narcissism and an ecological momentary assessment protocol capturing state-level negative affect and self-esteem. Grandiosity was associated with higher average momentary self-esteem (β =.12). Vulnerability and contingent self-esteem were associated with higher momentary averages of negative affect (βs =.23; 20, respectively) and lower momentary averages of self-esteem (βs = -.37; -.32, respectively). Vulnerability and contingent self-esteem also amplified the negative affect and self-esteem link (βs = -0.10 and -0.11, respectively). The findings suggest that contingent self-esteem is an important process underlying narcissism. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Personality Disorders. 2025/12, Vol. 39, Issue 6, p486
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2025
- ISSN:0885-579X
- DOI:10.1521/pedi.2025.39.6.486
- Accession Number:189732815
- 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.