Jeffrey A Burr1, Jan E Mutchler, Francis G Caro. 1. Department of Gerontology, McCormack Graduate School of Policy Studies, University of Massachusetts Boston, 100 Morrissey Boulevard, Boston, MA 02125-3393, USA. jeffrey.burr@umb.edu
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.
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.