Caregiver Burden: Looking Beyond the Unidimensional Total Score.

Abstract

The Zarit Burden Interview allows caregiver burden to be interpreted from a total score. However, recent studies propose a multidimensional Zarit Burden Interview model. This study aims to determine the agreement between unidimensional (UD) and multidimensional (MD) classification of burden, and differences in predictors among identified groups. We studied 165 dyads of dementia patients and primary caregivers. Caregivers were dichotomized into low-burden and high-burden groups based upon: (1) UD score using quartile cutoffs; and (2) MD model via exploratory cluster analysis. We compared UD versus MD 2×2 classification of burden using κ statistics. Caregivers not showing agreement by either definition were classified as "intermediate" burden. We performed binary logistic regression to ascertain differences in predictive factors. The 2 models showed moderate agreement (κ=0.72, P<0.01), yielding 104 low, 20 intermediate (UD "low burden"/MD "high burden"), and 41 high-burden caregivers. Neuropsychiatric symptoms [odds ratio (OR)=1.27, P=0.003], coresidence (OR=6.32, P=0.040), and decreased caregiving hours (OR=0.99, P=0.018) were associated with intermediate burden, whereas neuropsychiatric symptoms (OR=1.21, P=0.001) and adult children caregivers (OR=2.80, P=0.055) were associated with high burden. Our results highlight the differences between UD and MD classification of caregiver burden. Future studies should explore the significance of the noncongruent intermediate group and its predictors.