Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model Analysis

The influence of Positive Affect (PA) on people’s well-being and happiness and the related positive consequences on everyday life have been extensively described by positive psychology in the past decades. This study shows an application of Latent Growth Mixture Modeling (LGMM) to explore the existe...

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Main Authors: Margherita Brondino, Daniela Raccanello, Roberto Burro, Margherita Pasini
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Psychology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fpsyg.2020.01575/full
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author Margherita Brondino
Daniela Raccanello
Roberto Burro
Margherita Pasini
author_facet Margherita Brondino
Daniela Raccanello
Roberto Burro
Margherita Pasini
author_sort Margherita Brondino
collection DOAJ
description The influence of Positive Affect (PA) on people’s well-being and happiness and the related positive consequences on everyday life have been extensively described by positive psychology in the past decades. This study shows an application of Latent Growth Mixture Modeling (LGMM) to explore the existence of different trajectories of variation of PA over time, corresponding to different groups of people, and to observe the effect of emotion regulation strategies on these trajectories. We involved 108 undergraduates in a 1-week daily on-line survey, assessing their PA. We also measured their emotion regulation strategies before the survey. We identified three trajectories of PA over time: a constantly high PA profile, an increasing PA profile, and a decreasing PA profile. Considering emotion regulation strategies as covariates, reappraisal showed an effect on trajectories and class membership, whereas suppression regulation strategy did not.
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spelling doaj.art-9541554dfa7543809c6c8c34c13f7a5c2022-12-22T01:36:22ZengFrontiers Media S.A.Frontiers in Psychology1664-10782020-07-011110.3389/fpsyg.2020.01575501844Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model AnalysisMargherita BrondinoDaniela RaccanelloRoberto BurroMargherita PasiniThe influence of Positive Affect (PA) on people’s well-being and happiness and the related positive consequences on everyday life have been extensively described by positive psychology in the past decades. This study shows an application of Latent Growth Mixture Modeling (LGMM) to explore the existence of different trajectories of variation of PA over time, corresponding to different groups of people, and to observe the effect of emotion regulation strategies on these trajectories. We involved 108 undergraduates in a 1-week daily on-line survey, assessing their PA. We also measured their emotion regulation strategies before the survey. We identified three trajectories of PA over time: a constantly high PA profile, an increasing PA profile, and a decreasing PA profile. Considering emotion regulation strategies as covariates, reappraisal showed an effect on trajectories and class membership, whereas suppression regulation strategy did not.https://www.frontiersin.org/article/10.3389/fpsyg.2020.01575/fulllatent growth mixture modelingtrajectoriespositive affectemotion regulation strategieslongitudinal data
spellingShingle Margherita Brondino
Daniela Raccanello
Roberto Burro
Margherita Pasini
Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model Analysis
Frontiers in Psychology
latent growth mixture modeling
trajectories
positive affect
emotion regulation strategies
longitudinal data
title Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model Analysis
title_full Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model Analysis
title_fullStr Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model Analysis
title_full_unstemmed Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model Analysis
title_short Positive Affect Over Time and Emotion Regulation Strategies: Exploring Trajectories With Latent Growth Mixture Model Analysis
title_sort positive affect over time and emotion regulation strategies exploring trajectories with latent growth mixture model analysis
topic latent growth mixture modeling
trajectories
positive affect
emotion regulation strategies
longitudinal data
url https://www.frontiersin.org/article/10.3389/fpsyg.2020.01575/full
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AT robertoburro positiveaffectovertimeandemotionregulationstrategiesexploringtrajectorieswithlatentgrowthmixturemodelanalysis
AT margheritapasini positiveaffectovertimeandemotionregulationstrategiesexploringtrajectorieswithlatentgrowthmixturemodelanalysis