| MEASUREMENT PROPERTIES | |
| Limitations | >=5 European languages (English) |
| Observations |
EQ-5D-3L Translations >170 languages in self-complete paper format. EQ-5D-5L Translations >120 languages in self-complete paper format. EQ-5D-Y Translations > 30 languages. |
| 1. RELIABILITY | |
| A. Internal Consistency | Tested |
| Cronbach's (Describe) |
>0.7. For the EQ-5D-5L, Cronbach’s alpha was 0.86. |
| B. Reliability intraobserver or test-retest | Tested |
| Continuous scores: intraclass correlation coefficient (ICC) Dichotomus: Cohen kappa (Describe) |
ICC for the EQ-5D Index: 0.64–0.78 ICC for the EQ-5D VAS: 0.70–0.85 The ICC of the EQ-5D-5 L was 0.828 |
| C. Reliability interobserver or Measurement error | Tested |
| Standard error of measurement (SEM), smallest detectable change (SDC) or Limits of agreement (LoA) (Describe) |
Bland–Altman plots indicated poor agreement between EQ-5D and SF-6D/15D. In both plots involving EQ-5D, some patients had differences between EQ-5D and the other utility measures exceeding 0.5, a few patients even had a difference of 1.0 |
| 2. VALIDITY | |
| A. Content validity: face validity | Tested |
| Expert opinion (relevance and comprehensiveness) (Describe) |
The dimensions were selected after a detailed examination of existing health status measures, including the Quality of Well-Being Scale, Sickness Impact Profile, Nottingham Health Profile, and Rosser Index. The number of health states in each dimension was deliberately kept to a minimum so that the measure could easily be administered and used for decision making |
| B. Construct Validity: Structural validity |
Tested |
| Hypotheses-testing | Tested |
| Cross-cultural validity | Tested |
| Brief Description |
Confirmatory Factor Analysis confirmed the robust nature of the EQ-5D and its mono-factorial structure (EFA: Total Variance 50.39% - CFA: chi2 = 3.596; p approximately equal .60; RMSEA = 00; CFI = 1.00; RMR = .007) |
| C. Criterion validity | Not Tested |
| Comparison with a 'gold standard' Continuous scores: correlations, ROC curves Dichotomus: Sensitivity & Specificity (Describe) |
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