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中年及老年人的生产性活动集群:交叉形式与时间投入

Productive activity clusters among middle-aged and older adults: intersecting forms and time commitments.

作者信息

Burr Jeffrey A, Mutchler Jan E, Caro Francis G

机构信息

Department of Gerontology, McCormack Graduate School of Policy Studies, University of Massachusetts Boston, 100 Morrissey Boulevard, Boston, MA 02125-3393, USA.

出版信息

J Gerontol B Psychol Sci Soc Sci. 2007 Jul;62(4):S267-75. doi: 10.1093/geronb/62.4.s267.

Abstract

OBJECTIVE

This study investigated the latent structure of productive activity among middle-aged and older adults. Whereas most researchers have examined forms of productive activity as discrete behaviors, our approach captured the reality that many persons engage in more than one activity and commit varying degrees of time to these activities.

METHODS

We took the data for this study from the Americans' Changing Lives survey. The activities examined include formal volunteer work, informal help to others, unpaid domestic work, caregiving, and paid work. We describe the complex clusters of activities and time commitment to those activities using latent class cluster analysis.

RESULT

Our results demonstrated that a four-cluster model fit the data well. Specifically, the findings showed that middle-aged and older adults fell into four clusters: helpers, home maintainers, worker/volunteers, and super helpers. We also show how individual characteristics (e.g., age, gender, race) are associated with the likelihood of being in one of these four groups.

DISCUSSION

This measurement strategy provides a foundation for future research into how experts can employ productive activity clusters to understand better well-being across the life course. This is important because our results show that many activities do not occur independently but rather are linked in patterned ways.

摘要

目的

本研究调查了中老年人生产性活动的潜在结构。大多数研究人员将生产性活动形式视为离散行为,而我们的方法捕捉到了这样一个现实,即许多人从事不止一项活动,并在这些活动上投入不同程度的时间。

方法

我们从“美国人生活变化”调查中获取本研究的数据。所考察的活动包括正式志愿工作、对他人的非正式帮助、无薪家务劳动、照料以及有偿工作。我们使用潜在类别聚类分析来描述活动的复杂集群以及对这些活动的时间投入。

结果

我们的结果表明,四聚类模型与数据拟合良好。具体而言,研究结果显示中老年人分为四类:帮助者、家庭维持者、工作者/志愿者和超级帮助者。我们还展示了个体特征(如年龄、性别、种族)如何与属于这四组之一的可能性相关联。

讨论

这种测量策略为未来研究专家如何利用生产性活动集群更好地理解整个生命历程中的幸福感奠定了基础。这很重要,因为我们的结果表明许多活动并非独立发生,而是以有模式的方式相互关联。

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