Determining a cutoff score for the family burden interview schedule using three statistical methods.

BACKGROUND: While it is widely acknowledged that family burden can be ameliorated with effective psycho-social interventions, how to measure family burden and define a valid cutoff to identify family caregivers in need of such interventions remains a key question. The purpose of the present study was to determine a statistically valid cutoff score for the Family Burden Interview Schedule (FBIS), using the cutoff scores of the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder Scale (GAD-7) as the reference. METHODS: The FBIS, PHQ-9, and GAD-7 were administered to a representative community sample of 327 family caregivers of schizophrenia patients. A FBIS cutoff score was determined using three different statistical methods: tree-based modeling, K-means clustering technique and linear regression. Contingency analysis was conducted to compare the FBIS cutoff with depression and anxiety scale scores. RESULTS: Findings proposed a cutoff score of 23 for the FBIS, with sensitivity being 76% for PHQ-9 and 74% for GAD-7, specificity being 68% for PHQ-9 and 67% for GAD-7. CONCLUSION: This cutoff score would enable health care providers to assess family caregivers at risk and provide necessary interventions to improve their quality of life.

Who cares for the schizophrenia individuals in rural China - A profile of primary family caregivers.

OBJECTIVE: The present study aims to provide a comprehensive profile of the primary family caregivers of schizophrenia individuals in rural China. METHOD: A cross-sectional study was conducted with a sample of 327 primary family caregivers of schizophrenia individuals recruited through a one-stage cluster sampling in Ningxiang County of Hunan province, China. The social demographic and psychological profiles of primary caregivers were measured using standard scales and self-designed scales. RESULTS: The typical caregiver profile consists of a 58-year old married first degree relative (mostly parents or spouses) with a low socio-economic position. Most of them have been caregiving for over 10 years (74.3%) and have some physical illness (67.0%). The major caregiving activities were medicine management (71.6%) and hospital visit (69.4%), yet there is still 17.1% primary caregivers involved with neither of the care. Most (84%) of caregivers reported some kind of burden, with anxiety in 45.9% of caregivers and depression in 45.4%. Family caregivers also reported positive aspects of caregiving including a well-functional family (51.0%) and rewarding feelings (58.3%). CONCLUSION: The findings of the present study have brought attention to a special group of family caregivers for schizophrenia, with implications for intervention on them in the future.

Reported family burden of schizophrenia patients in rural China.

We aim to assess the level of family burden of schizophrenia patients and identify its predicting factors in a rural community sample of China. A sample of 327 primary caregivers was recruited through a one-stage cluster sampling in Ningxiang County of Hunan province, China. Family burden was assessed using the Family Burden Interview Schedule (FBIS) of Pai and Kapur. Our results showed that the mean score of FBIS was 23.62±9.76 (range, 0-48), with over half (52%) caregivers reported their family burden being moderate and severe. Among the six domains of family burden, financial burden (76%) was the commonest burden, while disruption of family interactions (37%) was the least mentioned. A multivariate analysis of family burden revealed that patient being admitted for over 3 times, caregiver being female, having a middle school education, and with additional dependents, as well as higher care network function were positive predictors of family burden, while higher patient function and family function, and increasing patient age were negative predictors of family burden. Intervention to decrease family burden may be best served by improving family function and exploring alternative care model instead of hospitalization.