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A latent profile analysis of the Five Factor Model of personality: Modeling trait interactions
► Latent profile analysis was used to model interactions using the Five Factor Model. ► A three-profile solution provided the best fit to the data. ► The profiles were termed well-adjusted, reserved, and excitable. ► The well-adjusted group reported better psychological outcomes in general. ► The ex...
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Published in: | Personality and individual differences 2011-12, Vol.51 (8), p.915-919 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | ► Latent profile analysis was used to model interactions using the Five Factor Model. ► A three-profile solution provided the best fit to the data. ► The profiles were termed well-adjusted, reserved, and excitable. ► The well-adjusted group reported better psychological outcomes in general. ► The excitable group reported more anxiety compared to the reserved group.
Interactions among the dimensions of the Five Factor Model (FFM) have not typically been evaluated in mental health research, with the extant literature focusing on bivariate relationships with psychological constructs of interest. This study used latent profile analysis to mimic higher-order interactions to identify homogenous personality profiles using the FFM, and also examined relationships between resultant profiles and affect, self-esteem, depression, anxiety, and coping efficacy. Participants (N=371) completed self-report and daily diary questionnaires. A 3-profile solution provided the best fit to the data; the profiles were characterized as well-adjusted, reserved, and excitable. The well-adjusted group reported better psychological functioning in validation analyses. The reserved and excitable groups differed on anxiety, with the excitable group reporting generally higher anxiety than the reserved group. Latent profile analysis may be a parsimonious way to model personality heterogeneity. |
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ISSN: | 0191-8869 1873-3549 |
DOI: | 10.1016/j.paid.2011.07.022 |