老年人结构型社会资本与抑郁的随机截距交叉滞后分析 &#x0002A;

俞懿; 黎光明

doi:10.16719/j.cnki.1671-6981.20230616

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心理科学 ›› 2023, Vol. 46 ›› Issue (6) : 1399-1407. DOI: 10.16719/j.cnki.1671-6981.20230616

社会、人格与管理

老年人结构型社会资本与抑郁的随机截距交叉滞后分析^*

俞懿, 黎光明^*

作者信息 +

A Random Intercept Cross-Lagged Panel Analysis of Structural Social Capital and Depression in Older Adults

Yu Yi, Li Guangming

Author information +

文章历史 +

摘要

采用随机截距的交叉滞后模型,使用中国健康与养老追踪调查（CHARLS）2013年、2015年和2018年三波的数据,探究老年人结构型社会资本与抑郁之间的关系。结果表明：（1）在交叉滞后效应上,老年人抑郁程度能显著负向预测结构型社会资本;（2）抑郁对老年人结构型社会资本的显著影响仅发生在后一阶段（T2→T3）;（3）老年人结构型社会资本与抑郁的交叉滞后关系具有跨性别的不变性,但呈现出婚姻的差异。

Abstract

Background:The physical and mental health problems among older adults have gradually become the focus in the field of mental health. The Social Capital Theory is a new approach to improve the mental health of the elderly and alleviate depression. Structural social capital originates from the concept of social capital and emphasizes practical participation in various networks, including formal activities and informal contacts. Previous studies have shown that structural social capital has a negative impact on depression. Specifically, regular participation in social activities and frequent contact with others can reduce the risk of depression. However, most prior studies were cross-sectional, which identified the impact of structural social capital on depression among foreign residents, middle-aged and young people. There is a lack of longitudinal research investigating the impact of depression on structural social capital among the elderly. Based on the China Health and Retirement Longitudinal Study (CHARLS), this study used a random intercept cross-lagged panel model to explore the causal relationship between structural social capital and depression in older adults.

Methods:CHARLS is a large-scale longitudinal survey designed to investigate the social, economic, and health status of residents aged 45 and over in Chinese Mainland. This study used three waves of data, including 2013, 2015, and 2018 data from CHARLS. Structural social capital was measured by participation in 9 activities in the past month, and the depressive symptom was assessed by the Center for Epidemiological Studies Depression (CES-D) scale. First, the Pearson correlation analysis was conducted to examine the association between structural social capital and depression. Next, repeated measures analysis of variance (ANOVA) was used to investigate the difference between different sex and marriage. At last, A random intercept cross-lagged panel model was used to find the cross-time relationship between structural social capital and depression. All data were analyzed using SPSS 25.0 and Mplus 8.3.

Results:The results indicated that: (1) The random intercept cross-lagged panel model revealed that depression had a significant negative impact on the structural social capital, while the impact of structural social capital on depression was not significant. (2) The significant impact of depression on structural social capital was found in the latter stage (T2→T3). Compared with the former stage (T1→T2), it showed a significant upward trend in the latter (T2→T3). (3) There was a significantly different cross-lagged relationship between a widow and married elderly, while no difference existed between males and females.

Conclusion:The one-way impact of depression on structural social capital among older adults was found. This significant impact only occurred in the latter stage owing to the development and severity of the depression. This evidence highlights the importance of depression in older adults and suggests the impact of structural social capital to prevent subsequent depression among widowed adults.

导出引用

俞懿, 黎光明. 老年人结构型社会资本与抑郁的随机截距交叉滞后分析^*[J]. 心理科学. 2023, 46(6): 1399-1407 https://doi.org/10.16719/j.cnki.1671-6981.20230616

Yu Yi, Li Guangming. A Random Intercept Cross-Lagged Panel Analysis of Structural Social Capital and Depression in Older Adults[J]. Journal of Psychological Science. 2023, 46(6): 1399-1407 https://doi.org/10.16719/j.cnki.1671-6981.20230616

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