连接点:使用网络方法来研究幸福谱
Anne Landvreugd1,2, Margot P van de Weijer1,2, Dirk H M Pelt1,2
1Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Current psychology (New Brunswick, N.J.)
|September 26, 2024
概括
心理测量网络方法揭示了不同的积极和消极幸福集群. 诸如生活满意度,神经病症和抑郁症状等关键指标是理解整体幸福感的最核心.
科学领域:
- 积极心理学是积极的心理学.
- 心理测量 心理测量 心理测量
- 网络分析 网络分析
背景情况:
- 在积极心理学中定义幸福感带来了挑战.
- 现有的模型可能无法完全捕捉到幸福的复杂结构.
- 心理测量网络方法为研究构造结构提供了一种新的方法.
研究的目的:
- 用心理测量网络方法研究幸福的结构.
- 确定幸福结构中最核心的组成部分.
- 检查积极和消极幸福指标的相互联系.
主要方法:
- 使用心理测量网络方法与来自荷兰双胞胎登记册的荷兰成年人.
- 使用混合图形模型和LASSO规范化用于网络估计.
- 通过修剪和估计样本验证了网络结构和准确性.
主要成果:
- 确定了一个具有明显正面 (生活满意度,幸福,繁荣) 和负面 (抑郁症状,孤独,神经症) 集群的网络.
- 确定了四个中心节点:一个生活满意度项目,一个神经病症项目和两个抑郁症项目.
- 证明了正面和负面幸福现象之间的相互联系,挑战严格划分的领域.
结论:
- 网络方法有效地可视化了福祉的复杂,相互关联的性质.
- 已确定的中心节点可以作为未来福祉研究的有效指标.
- 结果支持对幸福的整体观点,拒绝严格分离的领域.
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