JOURNAL ARTICLE
Linguistic Measurement Invariance and Stability-Equivalence of the Personality Inventory for DSM-5 Among Bilingual Participants.
Published In: Journal of Personality Disorders, 2025, v. 39, n. 2. P. 133 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Leclerc, Philippe; Corff, Yann Le; Lapalme, Mélanie; Bégin, Vincent; Forget, Karine; Gamache, Dominick; Savard, Claudia; Rolland, Jean-Pierre 3 of 3
Abstract
The linguistic equivalence of the Personality Inventory for DSM-5 (PID-5) has never been investigated using a within-subject design, that is, among bilingual individuals. Also, the stability-equivalence of the PID-5 using two linguistic versions is unknown. Thus, this within-subject, test-retest study aims at (a) establishing the measurement invariance of the PID-5 among bilinguals, and (b) providing indices of stability-equivalence using distinct versions with tight confidence intervals. Data from a sample of bilingual participants (N = 605), who were administered the PID-5 over a 1-2-week interval in French and English, were utilized. The PID-5 reached the (full) strong invariance level using longitudinal invariance analyses, indicating that the PID-5 structure is the same and that scores are interchangeable, while controlling for sampling confounds. The indices of stability-equivalence were high across traits. The PID-5 yields scores reflective of genuine differences, at least at the domain level, providing solid ground to study personality across societies. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Personality Disorders. 2025/04, Vol. 39, Issue 2, p133
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2025
- ISSN:0885-579X
- DOI:10.1521/pedi.2025.39.2.133
- Accession Number:184797981
- 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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