Zeng Qiyan, Zhu Lining, He Zhipeng
Research Academy for Rural Revitalization of Zhejiang Province, Zhejiang A & F University, Hangzhou, China.
College of Economics and Management, Zhejiang A & F University, Hangzhou, China.
J Appl Gerontol. 2025 Mar;44(3):439-449. doi: 10.1177/07334648241273387. Epub 2024 Aug 21.
The basic premise of this study is that the traditional method to treating all older people as coming from the same distribution misspecifies the true model and ignores potentially important information in wellbeing outcomes of social participation. Using data from the China Longitudinal Aging Social Survey (CLASS), this paper proposes a finite mixture model (FMM) to identify the heterogeneous relationship between volunteer participation and older people's subjective well-being (SWB) and then explore the determinants of wellbeing heterogeneity in volunteer participation. The results reveal that older people can be classified into two latent subgroups, that is the volunteering beneficiary group (accounting for about 42%) and the volunteering non-beneficiary group (accounting for about 58%). The FMM is therefore more appropriate in estimating the complex impact of volunteering. Rural older people with poorer health, weaker social networks, better economic status, and better community environments are more likely to benefit from volunteer participation. Our findings have suggested some practical implications to increase the probability of benefit from volunteer participation.
本研究的基本前提是,将所有老年人视为来自同一分布的传统方法错误地指定了真实模型,并忽略了社会参与福祉结果中潜在的重要信息。利用中国老年社会追踪调查(CLASS)的数据,本文提出了一种有限混合模型(FMM),以识别志愿者参与与老年人主观幸福感(SWB)之间的异质关系,然后探讨志愿者参与中幸福感异质性的决定因素。结果显示,老年人可分为两个潜在亚组,即志愿者受益组(约占42%)和志愿者非受益组(约占58%)。因此,有限混合模型在估计志愿者活动的复杂影响方面更为合适。健康状况较差、社会网络较弱、经济状况较好以及社区环境较好的农村老年人更有可能从志愿者参与中受益。我们的研究结果为提高从志愿者参与中受益的概率提出了一些实际意义。