Cornwell Benjamin, Schumm L Philip, Laumann Edward O, Kim Juyeon, Kim Young-Jin
Department of Sociology, Cornell University, Ithaca, New York.
Department of Health Studies, University of Chicago, Illinois.
J Gerontol B Psychol Sci Soc Sci. 2014 Nov;69 Suppl 2(Suppl 2):S75-82. doi: 10.1093/geronb/gbu037.
This article describes new longitudinal data on older adults' egocentric social networks collected by the National Social Life, Health, and Aging Project (NSHAP). We describe a novel survey technique that was used to record specific personnel changes that occurred within respondents' networks during the 5-year study period, and we make recommendations regarding usage of the resulting data.
Descriptive statistics are presented for measures of network size, composition, and structure at both waves, respondent-level summary measures of change in these characteristics between waves, as well as measures that distinguish between changes associated with losses of Wave 1 network members, additions of new ones, and changes in relationships with network members who were present at both waves.
The NSHAP network change module was successful in providing reliable information about specific changes that occurred within respondents' confidant networks. Most respondents lost at least one confidant from W1 and added at least one new confidant between waves as well. Network growth was more common than network shrinkage. Both lost and new ties were weaker than ties that persisted throughout the study period.
These data provide new insight into the dynamic nature of networks in later life, revealing norms of network turnover, expansion, and weakening. Data limitations are discussed.
本文介绍了由美国国家社会生活、健康与老龄化项目(NSHAP)收集的关于老年人以自我为中心的社交网络的新纵向数据。我们描述了一种新颖的调查技术,该技术用于记录在为期5年的研究期间受访者社交网络中发生的特定人员变动情况,并就所得数据的使用提出建议。
呈现了两期调查中网络规模、构成和结构指标的描述性统计数据,以及两期之间这些特征变化的受访者层面汇总指标,还有区分与第一期网络成员流失、新成员加入以及与两期都存在的网络成员关系变化相关的变动情况的指标。
NSHAP网络变化模块成功提供了有关受访者密友网络中发生的特定变化的可靠信息。大多数受访者在第一期到第二期之间至少失去了一位密友,并且至少增加了一位新密友。网络增长比网络收缩更为常见。失去的关系和新建立的关系都比整个研究期间持续存在的关系更弱。
这些数据为晚年网络的动态性质提供了新的见解,揭示了网络更替、扩张和弱化的规律。同时讨论了数据的局限性。