Abstract

This paper groups persons who have transitioned into family caregiving using a latent class analysis and examines class differences on measures of well-being. Latent classes were identified for a sample of 251 participants who became family caregivers while participating in a longitudinal national study, and linear regression analyses compared average well-being change scores across classes. Fit indices supported a four-class solution dispersed along two conceptual dimensions: caregiving intensity and caregiving stain. The largest class (35.5%) was characterized as low intensity, low strain. The smallest class (12.7%) was characterized as high intensity, high strain, and these caregivers had significantly worse well-being change scores compared to the other caregiving classes. Categorizing caregivers by differing levels of care intensity and caregiving strain helps identify caregivers who are at most risk for poor psychosocial outcomes, determines which caregivers might benefit from specific caregiver support programs, and informs investigators on possible refinements to interventions.

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