The Caregiver Burden Inventory in evaluating the burden of heart failure patients' caregivers: a multicenter study

The importance of caregiver (CG) in the management of many diseases has been well documented, especially for chronic illnesses, as heart failure (HF). For this reason, the maintenance of an acceptable healthy condition and the avoidance of CGs' burden have been underlined as topic issues. Many studies have highlighted that CGs' burden negatively impacts on the quality of life of patients. Many instruments have been validated to measure CGs' burden in different illness contexts but very few have been validated in HF patients' CGs.Purpose. The aim of this study was dual: 1) to provide a psychometric validation of the Caregiver Burden Inventory - CBI in a cohort of HF patients' CGs; 2) to identify determinants of CG burden, considering socio-demographic, clinical, and psychological variables, measured both for patients and their CGs.

This was a cross-sectional study on Italian HF patients and their CGs, enrolled from different outpatient centers in 28 Italian provinces. CG was defined as the unpaid person, inside or outside the family, who provides the most informal care, as well as designated by the patients. CG strain, quality of life, perceived social support, and contributions to self-care, and patient comorbidities, cognitive function, contributions to self-care, activities of daily living, physical and emotional quality of life, as well as sociodemographic characteristics, duration, severity, and type of HF were measured. Confirmatory factor analyses (CFA) were used to evaluate the structural models of CBI dimensionality and multiple regression analyses were conducted to investigate determinants of CG burden.

In total, 505 HF patients (44.6% female, mean age 75.6 ± 10.7years) and their CGs (52.2% female, mean age 56.9 ± 14.8years) were enrolled. CFA showed the items clustered into the original five factors proposed by Novak and Guest (1989): time-dependence, developmental, physical, social and emotional burden. This five-factor model fitted good (X2(242)=513.287, p<.001; CFI=.95; RMSEA=.047; SRMR=.067), better than other different models, and the dimensions showed high internal consistency (Cronbach's alphas were.908,.917,.875,.893, and.925 respectively). Regression analyses revealed that CG quality of life, CG perceived social support, CG contributions to self-care, and patients disability in activities of daily living, as well as disease severity were the major predictors of CBI dimensions.

 CBI proved to be a valid and reliable multidimensional instrument for evaluating the impact of burden of HF patients' CGs. This tool and the identified determinants of CG burden can be considered to tailor interventions aimed at improving CG outcomes. Finally, this study also suggest that the comparison of burden of CGs of patients with different disease is possible using this questionnaire.