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  • 标题:The Structure of Children’s Subjective Well-being
  • 本地全文:下载
  • 作者:Shazly Savahl ; Ferran Casas ; Sabirah Adams
  • 期刊名称:Frontiers in Psychology
  • 电子版ISSN:1664-1078
  • 出版年度:2021
  • 卷号:12
  • 页码:2048
  • DOI:10.3389/fpsyg.2021.650691
  • 出版社:Frontiers Media
  • 摘要:Research on children’s quality of life and subjective well-being has advanced over the past decade largely as a result of developments in childhood theory, children’s rights legislation, and the shift towards positive social science. However, in line with the uncertainty regarding the conceptualisation of subjective well-being, the structural configuration of children’s subjective well-being has not been considered in the literature. In the current study, we present and test a model of children’s SWB, which includes the context-free and domain-based cognitive components, and positive and negative affect. We further test the fit structure of a hierarchical structural (second-order) model of children’s SWB. We use data from the third Wave of the Children’s Worlds Survey. The data source includes a sample of 92 782 participants selected from 35 countries (girls = 49.7%) between the ages of 9 to 12-years. We found a good fit for the four-factor confirmatory factor model of children’s SWB. Correlations between the various latent factors were as anticipated – with positive correlations between the life satisfaction components and positive affect, and negative correlations with negative affect. We further found a good fit for the hierarchical structural model of children’s subjective well-being. The study extends the generalizability of the hierarchical structural configuration of the subjective well-being to child samples and provides a viable model to explore correlates and predictors of children’s SWB using the full conceptual model. Finally, we propound the tenability of a quadripartite hierarchical conceptual model of children’s SWB.
  • 关键词:structure of children's subjective well-being; children's subjective well;being; Children's Worlds Survey; Hierarchical structural model; confirmatory factor analysis
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