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  • 标题:How to Improve the Well-Being of Youths: An Exploratory Study of the Relationships Among Coping Style, Emotion Regulation, and Subjective Well-Being Using the Random Forest Classification and Structural Equation Modeling
  • 本地全文:下载
  • 作者:Jiang, Xiaowei ; Ji, Lili ; Chen, Yanan
  • 期刊名称:Frontiers in Psychology
  • 电子版ISSN:1664-1078
  • 出版年度:2021
  • 卷号:12
  • 页码:1115
  • DOI:10.3389/fpsyg.2021.637712
  • 出版社:Frontiers Media
  • 摘要:The relationship between coping styles and subjective well-being (SWB) has recently received considerable empirical and theoretical attention in the scientific literature. However, the mechanisms underlying this relationship have largely remained unclear. The aim of the present research was to determine whether emotion regulation mediated the relationship between coping styles and SWB. We examined a hypothetical model among 1247 Chinese college students based on the integration of theoretical models. The SWB questionnaire, Ways of Coping Questionnaire (WCQ) and Emotion Regulation Questionnaire (ERQ) were used to measure SWB, emotion regulation strategies and coping styles, respectively. The random forest method was applied to predict life satisfaction (LS) and estimate the average variable importance to LS. The results of the study indicated that positive coping (PC) can indirectly influence LS via cognitive reappraisal (CR) and can indirectly influence expression suppression (ES) via positive affect (PA), and negative coping (NC) can indirectly influence negative affect (NA) via ES. In addition, NC was positively associated with both ES and NA. CR was found to be positively associated with PA. The findings indicated that coping styles play an important role in the SWB of college students. These findings provide insight into how coping styles impact SWB and have implications for the development and assessment of emotion regulation-based interventions.
  • 关键词:subjective well-being (SWB); Emotion regulation (ER); Coping Style; Random forest (bagging) and machine learning; Structural equation model - SEM
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