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

Frontiers in Psychology

article

Margherita Brondino¹  Roberto Burro¹  Margherita Pasini¹ 

[1] Department of Human Science, University of Verona

关键词: latent growth mixture modeling;    trajectories;    positive affect;    emotion regulation strategies;    longitudinal data;   

DOI  :  10.3389/fpsyg.2020.01575

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

CC BY