Background: Providing care for a stroke survivor often times results in alterations of social and psychological functioning for caregivers. The ability to identify classes of responses may be useful to identify at-risk caregivers and intervention programs to meet specific needs.
Purpose: The purpose of this exploratory analysis was to identify classes of stroke caregivers based on Caregiver Task Difficulty, Task Time, Optimism, Threat, Depressive Symptoms, and Life Changes, all factors that are important components of the caregiving experience.
Methods: Baseline data on Caregiver Task Difficulty (OCBS), Task Time (OCBS), Optimism (LOT-R), Appraisal of Caregiving Threat (ACS), Depressive Symptoms (PHQ9), and Life Changes (BCOS) from 176 caregivers enrolled in an ongoing stroke caregiver intervention study (TASK II) were analyzed using Latent Profile Analysis. Number of latent classes and adequacy of fit were evaluated using Bayes Information Criteria (smallest value), Entropy (>.80), and parametric bootstrapped likelihood ratio tests (p < .05) produced by MPlus version 6.11.
Results: The typical caregiver was female (76%), White (71%), 53.4 years of age (SD=12.6), not employed (58%), spouse (45%) of the stroke survivor. Four latent classes were identified: (1) relatively low OCBS difficulty and time, low LOT-R optimism with relatively high ACS threat and PHQ9 and negative BCOS life changes; (2) relatively low task difficulty and time, high LOT-R, low ACS and PHQ9, and positive BCOS life changes; (3) moderate task difficulty and time, LOT-R, ACS, PHQ9, and BCOS; and (4) high task difficulty and time, low LOT-R, and high ACS, PHQ9, and negative BCOS life changes.
Conclusions: While needing future empirical validation, the four latent classes suggest 4 responses to caregiving that may be useful to (a) identify caregivers at risk for adverse outcomes, (b) tailor intervention programs, and (c) evaluate response to those interventions.