Department of Sociology, Michigan State University, East Lansing, Michigan, USA.
J Gerontol B Psychol Sci Soc Sci. 2023 Feb 19;78(2):341-351. doi: 10.1093/geronb/gbac123.
Personal networks provide social support for older adults, perhaps especially during the coronavirus disease 2019 (COVID-19) pandemic when traditional avenues may be disrupted. We provide one of the first population-based studies on how prepandemic personal networks predict support during the pandemic among older adults, with attention to gender and race variation.
We analyzed longitudinal data from the National Social Life, Health, and Aging Project Round 3 (2015/2016) and COVID-19 Round (2020; N = 2622, 55.68% female, 78.75% White, aged 50-99), a nationally representative survey of community-dwelling older Americans. We considered structure (i.e., size, density) and composition (i.e., proportion female and kin) of prepandemic personal networks, estimating multinomial logistic models to predict self-reported need and receipt of instrumental help and emotional support during the pandemic.
Larger prepandemic confidant networks predicted higher risk of receiving needed pandemic help and support, higher risk of receiving help and support more often than prepandemic, and lower risk of being unable to get help. Denser prepandemic networks also predicted higher risk of receiving pandemic help and support. Furthermore, how network size and density related to support differed with respondent race and a greater proportion of kin in prepandemic networks predicted higher risk of receiving help for non-White older adults only.
Older adults' prepandemic confidant network structure and composition can provide underlying conditions for receiving pandemic social support. Findings speak to policies and programs that aim to foster social support or identify vulnerable groups that suffer the greatest unmet need for support during a global crisis.
个人网络为老年人提供社会支持，尤其是在冠状病毒病 2019（COVID-19）大流行期间，传统途径可能会受到干扰时。我们提供了首批关于大流行前个人网络如何预测大流行期间老年人支持情况的基于人群的研究之一，其中关注了性别和种族差异。
我们分析了来自国家社会生活、健康和老龄化项目第三轮（2015/2016 年）和 COVID-19 轮（2020 年；N=2622，55.68%为女性，78.75%为白人，年龄在 50-99 岁之间）的纵向数据，这是一项针对美国社区居住老年人的全国代表性调查。我们考虑了大流行前个人网络的结构（即规模、密度）和组成（即女性和亲属的比例），使用多项逻辑回归模型预测大流行期间自我报告的工具性帮助和情感支持需求和接受情况。
较大的大流行前知己网络预测有更高的获得所需大流行帮助和支持的风险，有更高的获得帮助和支持的频率比大流行前更高的风险，以及获得帮助的可能性更低的风险。密度更大的大流行前网络也预测了更高的获得大流行帮助和支持的风险。此外，网络规模和密度与支持的关系因受访者种族而异，大流行前网络中亲属比例较高预测非白人老年人获得帮助的风险更高。
老年人的大流行前知己网络结构和组成可以为获得大流行期间的社会支持提供潜在条件。研究结果为旨在促进社会支持或确定在全球危机期间最需要支持但支持不足的弱势群体的政策和计划提供了依据。
