ArticleHealth and quality of life outcomes2018
Exploring the causal and effect nature of EQ-5D dimensions: an application of confirmatory tetrad analysis and confirmatory factor analysis.
Article in Health and quality of life outcomes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Psychometric properties of the EQ-5D-5L: a systematic review of the literature.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021Pooled it
- Quality of Life, Social Networking, and Mental Health: Generational Differentiation and Uniqueness in the Context of South Korea.Journal of clinical medicine · 2025Article
- Depicting patient-reported outcome measures within directed acyclic graphs: practice and implications for causal reasoning.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Article
- Psychometric evaluation of EQ-5D-5L in OHCA survivors from the TTM2 trial: aResuscitation plus · 2025Article
- Comparing Generic Paediatric Health-Related Quality-of-Life Instruments: A Dimensionality Assessment Using Factor Analysis.PharmacoEconomics · 2024Article
- Development of the Young Disability Questionnaire (spine) for children with spinal pain: field testing in Danish school children.BMJ open · 2023Article
- Validation of the National Aeronautics and Space Administration Task Load Index (NASA-TLX) adapted for the whole day repeated measures context.Ergonomics · 2022Article
- Longitudinal study of patients' health-related quality of life using EQ-5D-3L in 11 Swedish National Quality Registers.BMJ open · 2022Article
- Combining EQ-5D-5L items into a level summary score: demonstrating feasibility using non-parametric item response theory using an international dataset.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2022Article
- Article
- Validity of EQ-5D-5L health-related quality of life questionnaire in self-reported diabetes: evidence from a general population survey.Health and quality of life outcomes · 2021Article
- Does the EQ-5D usual activities dimension measure what it intends to measure? The relative importance of work, study, housework, family or leisure activities.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2020Article
- A conceptual map of health-related quality of life dimensions: key lessons for a new instrument.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2020Article
- Article
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe relationship between the various items in an HRQoL instrument is a key aspect of interpreting and understanding preference weights. The aims of this paper were i) to use theoretical models of HRQoL to develop a conceptual framework for causal and effect relationships among the five dimensions of the EQ-5D instrument, and ii) to empirically test this framework.
methodsA conceptual framework depicts the symptom dimensions [Pain/discomfort (PD) and Anxiety/depression (AD)] as causal indicators that drive a change in the effect indicators of activity/participation [Mobility (MO), Self-care (SC) and Usual activities (UA)], where MO has an intermediate position between PD and the other two effect dimensions (SC and UA). Confirmatory tetrad analysis (CTA) and confirmatory factor analysis (CFA) were used to test this framework using EQ-5D-5L data from 7933 respondents in six countries, classified as healthy (n = 1760) or in one of seven disease groups (n = 6173).
resultsCTA revealed the best fit for a model specifying SC and UA as effect indicators and PD, AD and MO as causal indicators. This was supported by CFA, revealing a satisfactory fit to the data: CFI = 0.992, TLI = 0.972, RMSEA = 0.075 (90% CI 0.062-0.088), and SRMR = 0.012.
conclusionsThe EQ-5D appears to include both causal indicators (PD and AD) and effect indicators (SC and UA). Mobility played an intermediate role in our conceptual framework, being a cause of problems with Self-care and Usual activities, but also an effect of Pain/discomfort. However, the empirical analyses of our data suggest that Mobility is mostly a causal indicator.
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