丧偶前的社会支持与孤独模式有关:使用健康和退休研究的增长混合模型
Gina Lee1, Natasha Nemmers2, Daniel Russell3
1Center for Demography of Health and Aging, University of Wisconsin-Madison, WI, USA.
Aging & mental health
|June 26, 2024
概括
寡妇的老年人经历了更高的孤独感. 失去配偶前的社会支持减轻了失去配偶后的孤独感,突出了它对幸福感的保护作用.
科学领域:
- 老年学是一门学科.
- 心理学 心理学 心理学
- 社会学 社会学 社会学
背景情况:
- 对老年人来说,孤独是一个很大的问题,特别是在失去配偶之后.
- 了解悲伤后的孤独轨迹对于开发有针对性的干预措施至关重要.
研究的目的:
- 为了比较寡妇和非寡妇的老年人之间的孤独程度.
- 为了识别寡妇个体中独特的孤独轨迹.
- 检查丧失前的社会支持对丧失期间和丧失后的孤独的影响.
主要方法:
- 利用了来自健康和退休研究的数据 (N=2500).
- 使用t测试和潜增长曲线模型进行群组比较.
- 应用增长混合模型和多项逻辑回归来分析孤独模式和社会支持.
主要成果:
- 丧偶人士报告说,丧偶后的孤独程度显著上升.
- 他们发现了三个孤独模式:增加的孤独 (IL),低和稳定的孤独 (LSL) 和减少的孤独 (DL).
- 与LSL组相比,IL和DL组的个人从配偶,孩子和朋友那里获得的社会支持较少.
结论:
- 丧偶前的社会支持对老年人丧偶后的心理健康有保护作用.
- 社会支持网络在调节丧亲期间的孤独轨迹方面发挥着至关重要的作用.
相关概念视频
02:12Relationship Formation
40.0K
What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
40.0K
01:17Bonanno's Theory of Grieving
72
Grieving is a complex psychological and emotional process that varies significantly among individuals. George Bonanno's research on bereavement identified four distinct patterns of grieving, offering a nuanced understanding of how people cope with significant loss, such as the death of a spouse, over extended periods. These patterns — resilience, recovery, chronic dysfunction, and delayed grief — highlight the diversity in emotional responses and adaptive mechanisms.
Resilience
Resilience
72
01:22Applications of Life Tables
59
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
59
01:21Cancer Survival Analysis
342
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
342
01:15Assumptions of Survival Analysis
121
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
121
01:14Parametric Survival Analysis: Weibull and Exponential Methods
408
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
408