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COMPARATIVE STUDY
JOURNAL ARTICLE
RESEARCH SUPPORT, U.S. GOV'T, NON-P.H.S.
VALIDATION STUDIES
Comparison of health-related quality of life measures for chronic renal failure: quality of well-being scale, short-form-6D, and the kidney disease quality of life instrument.
Quality of Life Research 2008 October
BACKGROUND: Studies have found that health-related quality of life (HRQOL) measurements with different conceptual bases yield widely varying results within the same study sample. Using data from a cohort of patients with chronic kidney failure, the purpose of this study was to compare the Quality of Well-Being Scale-Self-Administered (QWB-SA), the Short-Form-6D (SF-6D), and the Kidney Disease Component Summary (KDCS).
METHODS: Baseline data from a multi-site prospective observational study of 322 veterans receiving hemodialysis were analyzed. Descriptive statistics were calculated. Confirmatory factor analysis was conducted to determine how closely the three HRQOL tools reflected the same underlying construct.
RESULTS: Our confirmatory factor analysis offered strong evidence that the subscales of the QWB-SA, SF-6D, and 7-subscale KDCS measured more than one factor in this study sample. In the three-factor model, the SF-6D and 7-subscale KDCS correlated .911 (P < .05), indicating 83% of the variance in the 7-subscale KDCS was correlated with the SF-6D. However, a two-factor model, in which the highly correlated SF-6D and 7-subscale KDCS were combined, fit the data almost as well as the three-factor model.
CONCLUSION: The three HRQOL measures addressed different underlying HRQOL constructs in this sample. The QWB-SA was significantly different from the SF-6D and KDCS.
METHODS: Baseline data from a multi-site prospective observational study of 322 veterans receiving hemodialysis were analyzed. Descriptive statistics were calculated. Confirmatory factor analysis was conducted to determine how closely the three HRQOL tools reflected the same underlying construct.
RESULTS: Our confirmatory factor analysis offered strong evidence that the subscales of the QWB-SA, SF-6D, and 7-subscale KDCS measured more than one factor in this study sample. In the three-factor model, the SF-6D and 7-subscale KDCS correlated .911 (P < .05), indicating 83% of the variance in the 7-subscale KDCS was correlated with the SF-6D. However, a two-factor model, in which the highly correlated SF-6D and 7-subscale KDCS were combined, fit the data almost as well as the three-factor model.
CONCLUSION: The three HRQOL measures addressed different underlying HRQOL constructs in this sample. The QWB-SA was significantly different from the SF-6D and KDCS.
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