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 Vol. 51; no. 8; pp. 915 - 919 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier Ltd
01.12.2011
Elsevier |
| Subjects | |
| Online Access | Get full text |
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| Abstract | ► 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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| AbstractList | 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. ► 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. 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. [Copyright Elsevier Ltd.] 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. |
| Author | Roesch, Scott C. Merz, Erin L. |
| AuthorAffiliation | 1 SDSU/UCSD Joint Doctoral Program in Clinical Psychology, 6363 Alvarado Court, Suite 103, San Diego, CA 92120-4913, USA 2 Department of Psychology, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4611, USA |
| AuthorAffiliation_xml | – name: 2 Department of Psychology, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4611, USA – name: 1 SDSU/UCSD Joint Doctoral Program in Clinical Psychology, 6363 Alvarado Court, Suite 103, San Diego, CA 92120-4913, USA |
| Author_xml | – sequence: 1 givenname: Erin L. surname: Merz fullname: Merz, Erin L. email: emerz@ucsd.edu organization: SDSU/UCSD Joint Doctoral Program in Clinical Psychology, 6363 Alvarado Court, Suite 103, San Diego, CA 92120-4913, USA – sequence: 2 givenname: Scott C. surname: Roesch fullname: Roesch, Scott C. organization: SDSU/UCSD Joint Doctoral Program in Clinical Psychology, 6363 Alvarado Court, Suite 103, San Diego, CA 92120-4913, USA |
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| Keywords | Latent profile analysis Personality Person-centered approach Five Factor Model Human Big Five personality model Self esteem Latent variable model Coping |
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| Snippet | ► 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... Interactions among the dimensions of the Five Factor Model (FFM) have not typically been evaluated in mental health research, with the extant literature... |
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| SubjectTerms | Anxiety-Depression Biological and medical sciences Five Factor Model Fundamental and applied biological sciences. Psychology Heterogeneity Latent profile analysis Person-centered approach Personality Personality traits Personality. Affectivity Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Selfreport Validation |
| Title | A latent profile analysis of the Five Factor Model of personality: Modeling trait interactions |
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