Modeling individual differences in emotion regulation repertoire in daily life with multilevel latent profile analysis.
Emotion
; 20(8): 1462-1474, 2020 Dec.
Article
em En
| MEDLINE
| ID: mdl-31478725
ABSTRACT
Emotion regulation (ER) repertoire-the range of different ER strategies an individual utilizes across situations-is assumed to enable more adaptive ER and greater well-being. ER repertoire has been operationalized by a quantitative index (sum of ER strategies across situations) or by applying a person-centered approach to global self-reports of dispositional ER. We aimed to assess ER repertoire in daily life by using an experience sampling methodology (ESM) and a person-centered approach that could account for nested data. We used multilevel latent profile analyses of ESM data (N = 179, 9-10 prompts per day over 21 days) to (a) group the occasions into latent profiles of momentary ER strategies, (b) group individuals whose distributions of ER profiles differed across occasions into latent classes, and (c) examine well-being correlates of class membership at the person level. At the occasion level, we identified nine ER profiles that differed in degree of use (e.g., no use of any vs. strong use of all strategies) and in specific combinations of strategies (e.g., situation selection and acceptance vs. suppression and ignoring). At the person level, we identified 5 classes of individuals differing in the degree to which they used various momentary ER profiles versus one predominant profile across situations. Well-being was highest for individuals who used multiple ER profiles of active strategies and lowest for individuals who used ER profiles focused on suppression. Hence, both ER repertoire width and the specific make-up of the ER repertoire were relevant for the relation between ER repertoire and well-being. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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Coleções:
01-internacional
Base de dados:
MEDLINE
Limite:
Adolescent
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Adult
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Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article