2006
DOI: 10.1007/s11136-005-4364-8
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Abstract: For patient and proxy ratings, the EQ-5D had the best combination of measurement properties, although it had a substantial ceiling effect for patient ratings. Proxy QOL ratings did not accurately reflect patients' ratings.

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Cited by 109 publications
(168 citation statements)
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“…[12,13] Given that different types of QOL measures assess different dimensions of QOL and that utility scores for the same disease can vary substantially depending on the utility measure used, [14] the objective of this study was to evaluate whether there are consistent predictors of caregiver-rated patient QOL across a spectrum of QOL measures or whether predictors of caregiver-rated patient QOL vary with different QOL measures in a large national sample of community-living patients with AD. In addition, we wanted to address some gaps in the literature on predictors of caregiver ratings of patient QOL in AD: conflicting data on the impact of caregiver factors on caregiver ratings; little information on the predictive ability of patients' cognitive performance as measured by the Alzheimer's Disease Assessment ScaleCognitive Subscale (ADAS-Cog), which is a more sensitive measure of cognitive impairment in AD than the MMSE; [15] lack of data on the predictors of caregiver ratings as measured by the Quality of Well Being (QWB) index and Short-Form 36; [16] and little available research incorporating comprehensive multiple regression models that include a full spectrum of patient factors (core dementia symptoms, demographics and comorbidity) and caregiver factors (demographics, comorbidity, burden and depression).…”
Section: Introductionmentioning
confidence: 99%
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“…[12,13] Given that different types of QOL measures assess different dimensions of QOL and that utility scores for the same disease can vary substantially depending on the utility measure used, [14] the objective of this study was to evaluate whether there are consistent predictors of caregiver-rated patient QOL across a spectrum of QOL measures or whether predictors of caregiver-rated patient QOL vary with different QOL measures in a large national sample of community-living patients with AD. In addition, we wanted to address some gaps in the literature on predictors of caregiver ratings of patient QOL in AD: conflicting data on the impact of caregiver factors on caregiver ratings; little information on the predictive ability of patients' cognitive performance as measured by the Alzheimer's Disease Assessment ScaleCognitive Subscale (ADAS-Cog), which is a more sensitive measure of cognitive impairment in AD than the MMSE; [15] lack of data on the predictors of caregiver ratings as measured by the Quality of Well Being (QWB) index and Short-Form 36; [16] and little available research incorporating comprehensive multiple regression models that include a full spectrum of patient factors (core dementia symptoms, demographics and comorbidity) and caregiver factors (demographics, comorbidity, burden and depression).…”
Section: Introductionmentioning
confidence: 99%
“…These utility indexes, which are scored on 0-1 scales, differ in terms of content, structure and scoring function. [14,16] They have been shown to be reliable and valid for caregiver ratings of AD patients. [13,16] We used version 2/3 of the HUI, which allows for the derivation of HUI2 and HUI3 scores, [25] but report here only HUI3 ratings as the HUI2 and HUI3 scores were highly correlated and yielded equivalent results.…”
mentioning
confidence: 99%
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“…Studies on clinical populations have found a two-week test-retest reliability of 0.75 for patients with mild dementia (Naglie et al, 2006), three-month test-retest reliability of 0.72-0.77 for patients with hip fracture (Jones, Feeny, & Eng, 2005), and one-week test-retest reliability of 0.84 for patients undergoing breast reduction surgery (Thoma, Sprague, Veltri, Duku, & Furlong, 2005). Validity of the HUI3 has been assessed in many general and clinical populations.…”
Section: Measures Of Health Outcomesmentioning
confidence: 99%