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  • 标题:Relationship Between Trait Mindfulness and Sleep Quality in College Students: A Conditional Process Model
  • 本地全文:下载
  • 作者:Ding, Xiaoqian ; Wang, Xinshu ; Yang, Zirong
  • 期刊名称:Frontiers in Psychology
  • 电子版ISSN:1664-1078
  • 出版年度:2020
  • 卷号:11
  • 页码:1-9
  • DOI:10.3389/fpsyg.2020.576319
  • 出版社:Frontiers Media
  • 摘要:Sleep quality can affect the physical and mental health, as well as the personal development of college students. Mindfulness practices are known to ameliorate sleep disorder and improve sleep quality. Trait mindfulness, an innate capacity often enhanced by mindfulness training, has been shown to relate to better sleep quality and different aspects of psychological well-being. However, how individual difference factors such as trait mindfulness relate to sleep quality remain largely unclear, which limits the optimization and further application of mindfulness-based intervention schemes targeting the improvement of sleep quality. In this study, we aimed to investigate how negative emotions and neuroticism may influence the relationship between trait mindfulness and sleep quality. A conditional process model was built to examine these relationships in 1423 Chinese young adults. Specifically, the conditional process model was constructed with trait mindfulness as the independent variable, sleep quality as the dependent variable, negative emotions as the mediating variable and neuroticism as the moderating variable. Our results showed that negative emotions mediated the link between mindfulness and sleep quality, and that neuroticism had a moderating effect on the relationship between mindfulness and sleep quality. Together, these findings suggested a potential mechanism of how trait mindfulness influences sleep quality, provided a therapeutic target for which mindfulness-based interventions may act upon to improve sleep quality, and offered a basis for prediction of different intervention effects amongst individuals.
  • 关键词:mindfulness; sleep quality; negative emotions; neuroticism; conditional process model
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