Shared Care Networks Assisting Older Adults: New Insights From the National Health and Aging Trends Study

Gerontologist. 2023 Jun 15;63(5):840-850. doi: 10.1093/geront/gnac155.

Abstract

Background and objectives: Caregiving research often assumes older adults receiving care have a primary caregiver who provides the bulk of care. Consequently, little is known about the extent to which care responsibilities are shared more evenly within a care network, the characteristics associated with sharing, or the consequences for meeting older adults' care needs.

Research design and methods: We analyze a sample of U.S. older adults receiving care from the 2011 National Health and Aging Trends Study (n = 2,398). Based on variables reflecting differences in care hours, activities, and care provided by the whole network, we create network typologies for those with two or more caregivers (n = 1,309) using K-means cluster analysis. We estimate multinomial and logistic regression models to identify factors associated with network type and the association between type and unmet needs. We conduct analyses overall and for older adults living with and without dementia.

Results: Analyses reveal four network types: Small, low-intensity shared care network (SCN); large, moderate-intensity SCN; small, low-intensity primary caregiver network (PCN); and moderate-sized, high-intensity PCN. Among all older adults receiving care, 51% have a sole caregiver, 20% have an SCN with no primary caregiver, and 29% have a PCN. Among older adults with dementia receiving intense care, unmet needs are lower among those with an SCN (vs. PCN).

Discussion and implications: Findings underscore that the primary caregiver construct, although common, does not apply to a substantial share of care networks. Moreover, having an SCN when needs are high may be beneficial to meeting older adult's needs.

Keywords: Caregiver networks; Dementia; Unmet need.

MeSH terms

  • Activities of Daily Living*
  • Aged
  • Aging
  • Caregivers
  • Dementia*
  • Humans
  • Logistic Models