EuroQol EQ-5D Quality of Life Scale

1. Abstract

The EuroQol EQ-5D Quality of Life Scale is globally recognized as one of the most widely implemented generic instruments for evaluating health-related quality of life (HRQoL) and generating preference-based health state utilities. Developed by the international, multidisciplinary EuroQol Group in the late 1980s, the instrument captures health across five core domains: Mobility, Self-Care, Usual Activities, Pain/Discomfort, and Anxiety/Depression. It exists in two primary adult versions: the original three-level version (EQ-5D-3L), which defines 243 theoretically possible health states, and the refined five-level version (EQ-5D-5L), introduced to mitigate significant ceiling effects and enhance measurement sensitivity across 3,125 distinct health profiles. In addition to the five-dimensional descriptive system, both versions feature the EQ Visual Analogue Scale (EQ-VAS), a vertical, continuous rating thermometer ranging from 0 (“the worst health you can imagine”) to 100 (“the best health you can imagine”), which captures a respondent’s holistic self-assessment of health status today.

The psychometric properties of the EQ-5D have undergone extensive empirical scrutiny across diverse clinical, general, and epidemiological populations in dozens of countries. The instrument demonstrates strong convergent validity with disease-specific and broader generic scales (such as the SF-36 and SF-12), robust discriminative validity across functional impairment strata, and acceptable-to-high test-retest reliability, with intraclass correlation coefficients (ICCs) generally ranging from 0.70 to 0.90 for summary index scores. The index scores, derived through population-based preference elicitation protocols utilizing time trade-off (TTO) and discrete choice experiments (DCE), yield country-specific health utility values anchored at 1.0 (full health) and 0.0 (a state equivalent to dead), permitting negative values for states evaluated as worse than dead. Consequently, the EQ-5D serves as an indispensable tool in clinical trials, population health surveillance, health technology assessments (HTA), and the calculation of Quality-Adjusted Life Years (QALYs) for health economic evaluations worldwide.

2. Keywords

EQ-5D, EuroQol, health-related quality of life, EQ-5D-5L, EQ-5D-3L, EQ-VAS, health utility, Quality-Adjusted Life Year, psychometrics, cost-utility analysis, patient-reported outcome measures, health economics, descriptive system, time trade-off

3. Authors

The EQ-5D was conceptualized and developed collaboratively by the EuroQol Group, an international, independent, non-profit network of multidisciplinary researchers founded in 1987. The founding investigators represented health economics, public health, sociology, psychology, and medicine across institutions in the Netherlands, the United Kingdom, Sweden, Finland, and Norway.

• Key Founding & Contributing Researchers:
  • Paul Kind – Centre for Health Economics, University of York, York, United Kingdom.
  • Rosalind Brooks – Senior Research Fellow and long-standing EuroQol Group coordinator, United Kingdom.
  • Frank de Charro – Erasmus University Rotterdam, Rotterdam, The Netherlands.
  • Gudrun Gudex – University of York, York, United Kingdom.
  • Alan Williams (Late) – Professor of Economics, Department of Economics and Related Studies, University of York, United Kingdom.
  • John E. Brazier – School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, United Kingdom.
  • Jan J. V. Busschbach – Department of Psychiatry and Psychology, Erasmus University Medical Center, Rotterdam, The Netherlands.
  • A. Simon Pickard – Department of Pharmacy Systems, Outcomes and Policy, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, USA.
  • M. F. (Mark) Janssen – EuroQol Research Foundation, Rotterdam, The Netherlands.
• Institutional Affiliation & Oversight: The copyright, intellectual property, scientific coordination, and global distribution of the instrument are managed by the EuroQol Research Foundation, Marten Meesweg 107, 3068 AV Rotterdam, The Netherlands (Website: https://euroqol.org).

4. Purpose

The primary purpose of the EuroQol EQ-5D Quality of Life Scale is to provide a standardized, simple, generic, non-disease-specific instrument for describing and valuing health-related quality of life. Unlike long, clinically detailed inventories designed to capture diagnostic nuance within a single specialty, the EQ-5D was explicitly engineered to be brief enough to supplement comprehensive battery protocols without inducing respondent fatigue, yet robust enough to permit comparisons across vastly divergent diagnostic categories, chronic conditions, and public health interventions.

The instrument fulfills three core applications across contemporary healthcare, research, and policy landscapes:

• Health Economic Evaluation and Cost-Utility Analysis: The EQ-5D provides standardized weights that convert self-reported multi-attribute health descriptions into a single summary index value (utility). These utilities represent societal or individual preferences for specific health states and serve as the critical denominator in calculating Quality-Adjusted Life Years (QALYs). Decision-making bodies such as the National Institute for Health and Care Excellence (NICE) in the UK, the Pharmaceutical Benefits Advisory Committee (PBAC) in Australia, and corresponding health technology assessment (HTA) agencies internationally routinely recommend or mandate the EQ-5D for evaluating the comparative cost-effectiveness of new pharmaceuticals, surgical interventions, and medical technologies.
• Clinical Trials and Comparative Effectiveness Research: Because it is generic, the EQ-5D allows researchers to track patient-reported outcomes (PROs) longitudinally over the course of clinical trials. It captures unintended collateral impacts of treatments—such as whether a chemotherapy regimen that controls physical disease progression produces unacceptable decrements in anxiety, depression, or functional mobility.
• Population Health Surveys and Health System Performance Tracking: National statistical agencies and ministries of health utilize the EQ-5D in large-scale national surveys to benchmark the health of the general public, identify disparities in vulnerable subpopulations, assess longitudinal epidemiologic trends, and evaluate the macro-level impact of healthcare policies and public health interventions.

From a theoretical perspective, the rationale behind the EQ-5D is rooted in the philosophy that healthcare systems exist not merely to extend the chronological length of human life, but crucially to optimize the functional and subjective quality of that survival. A metric must balance parsimony with validity to achieve high compliance, universal translation feasibility, and wide applicability across cultures and clinical contexts.

5. Psychological Construct

The overarching construct assessed by the EQ-5D is Health-Related Quality of Life (HRQoL), defined as the subjective perception of the impact of health status, illness, and therapeutic interventions on an individual’s physical, psychological, and social functioning and well-being. Rather than treating health as the simple absence of objective biomedical pathology, the EuroQol model aligns with the holistic paradigm conceptualized by the World Health Organization, incorporating both objective functioning and subjective somatic and affective experience.

The descriptive system evaluates five specific sub-dimensions:

• Mobility: Assesses gross motor functional capacity, ambulation, and physical independence. In the 3L version, it spans from having no problems walking about, to having some problems, to being confined to bed. In the 5L refinement, the dimension tracks progressive gradations: no problems, slight problems, moderate problems, severe problems, and being completely unable to walk about. This dimension directly indexes physical disability, musculoskeletal integrity, and cardiopulmonary endurance.
• Self-Care: Evaluates fundamental activities of daily living (ADLs), specifically washing and dressing oneself independently. It captures fine and gross motor competence, independence, and basic self-maintenance. Impairments in this dimension carry profound psychological implications, often signaling severe disability, loss of autonomy, and the necessity for formal or informal caregiver dependency.
• Usual Activities: Encompasses instrumental activities of daily living (IADLs), vocational duties, educational commitments, housework, family obligations, and leisure or social pursuits. This dimension serves as the primary bridge between somatic functioning and psychosocial role fulfillment. Deficits here indicate societal role disruption and life role limitations resulting from physical or emotional distress.
• Pain / Discomfort: Measures the somatic-sensory and affective burden of physical pain and bodily discomfort. It incorporates acute and chronic pain conditions, post-operative distress, neuropathies, and physical unease across a severity gradient (from no pain up to extreme pain). Because pain is inherently subjective, this dimension acknowledges the patient’s lived somatic reality regardless of whether underlying organic etiology is definitively established.
• Anxiety / Depression: Reflects psychological functioning, mood disturbance, emotional distress, and internalizing psychological symptoms. Capturing states from not anxious/depressed to extremely anxious/depressed, this dimension ensures that psychological morbidity is accorded parity with physical impairment. It recognizes that affective disruption is an indispensable constituent of overall health status.

Complementing these five functional domains is the EQ Visual Analogue Scale (EQ-VAS), which measures the overarching construct of global self-rated health. While the five-dimension profile breaks health down into discrete categorical domains, the EQ-VAS allows the respondent to cognitively integrate their physical, emotional, social, and existential state into a single global rating, capturing personal health evaluations that may transcend the specific five descriptive items.

6. Theoretical Framework

The theoretical framework underpinning the EQ-5D integrates principles from multi-attribute utility theory (MAUT), welfare economics, and cognitive measurement theory. The instrument’s structure operationalizes the concept that health can be conceptualized as a multi-attribute state comprised of independent, mutually exhaustive dimensions that collectively define an individual’s health profile.

Multi-Attribute Utility Theory (MAUT) and Health State Decomposition

Under MAUT, any complex health state $H$ can be decomposed into a vector of attributes $(x_1, x_2, dots, x_n)$, where each attribute represents a functional or subjective domain. In the EQ-5D-3L, each of the 5 dimensions has 3 levels, defining $3^5 = 243$ unique composite health states (e.g., state 11111 represents perfect health; state 33333 represents the most severe impairment across all domains). In the EQ-5D-5L, with 5 levels per dimension, the system defines $5^5 = 3,125$ discrete health states (ranging from 11111 to 55555).

The theoretical model posits that individuals (or representative societal panels) possess an underlying preference function $U(H)$ that maps these multi-attribute categorical profiles onto a continuous cardinal utility scale normalized between 1.0 (full health) and 0.0 (death). This valuation function typically takes the additive or multiplicative form:

$$U(H) = 1 – \sum_{j=1}^{5} \beta_j (x_j) – \theta(X)$$

where $\beta_j(x_j)$ denotes the disutility weight associated with level $x$ on dimension $j$, and $\theta(X)$ represents an interaction term (such as the N3 term in the classic Dolan 1997 UK valuation model) that accounts for non-linear disutility when extreme problems occur on at least one dimension.

Welfare Economics and Preference Elicitation

Unlike purely psychometric scales that generate sum scores or z-scores, the EQ-5D index is explicitly anchored in the theoretical principles of normative welfare economics and expected utility theory. Health utility values are not arbitrarily assigned by clinicians; rather, they are elicited from representative general population samples using rigorous decision-analytic valuation methodologies:

• Time Trade-Off (TTO): Respondents are asked to determine the amount of time in full health ($x$ years) they consider equivalent to living a longer period ($t$ years, typically 10 years) in a specified compromised health state. The utility is calculated as $U = x / t$. For states judged worse than dead ($x < 0$), composite TTO (cTTO) designs are utilized to establish continuous negative bounds.
• Discrete Choice Experiments (DCE): Respondents choose between hypothetical health profiles (Option A vs. Option B), with or without duration attributes, allowing economists to model relative attribute importance and marginal substitution rates using multinomial logit or probit frameworks.

Cognitive Model of Self-Report

From a cognitive psychometric standpoint, the EQ-5D relies on Tourangeau’s four-stage model of questionnaire response: comprehension of the domain prompt, retrieval of relevant autobiographical health memories (anchored to “today”), judgment/integration of those somatic and psychological sensations against internal subjective thresholds, and selection of the corresponding response category. The evolution from the 3L to the 5L version was theoretically motivated by the need to lower cognitive threshold barriers, expand discrimination at the mild-to-moderate interface, and resolve the pervasive ceiling effect observed when healthy or mildly ill individuals completed the 3L version.

7. Validity

The psychometric validity of both the EQ-5D-3L and EQ-5D-5L has been established across hundreds of clinical trials, general population cohorts, and disease registers globally. The literature provides robust evidence supporting construct, convergent, discriminant, and predictive validity.

Convergent Validity

Convergent validity has been repeatedly demonstrated through systematic comparisons with established generic instruments, most notably the Medical Outcomes Study 36-Item Short Form Survey (SF-36), the SF-12, and the WHOQOL-BREF. In foundational validation research, Brazier, Jones, and Kind (1993) demonstrated high correlations between corresponding physical and psychological domains of the EQ-5D and the SF-36:

• The EQ-5D Mobility and Self-Care dimensions exhibit strong negative correlations with the SF-36 Physical Functioning subscale ($r = -0.65$ to $-0.82$, where lower EQ-5D level codes reflect better health).
• The EQ-5D Pain/Discomfort dimension correlates strongly with the SF-36 Bodily Pain subscale ($r = -0.70$ to $-0.85$).
• The EQ-5D Anxiety/Depression dimension correlates moderately to strongly with the SF-36 Mental Health dimension ($r = -0.58$ to $-0.74$) and with psychiatric screening tools such as the Hospital Anxiety and Depression Scale (HADS) and the PHQ-9.

Discriminant and Known-Groups Validity

The EQ-5D exhibits powerful known-groups validity, successfully differentiating between cohorts stratified by age, chronic morbidity count, socio-economic status, and clinical severity markers. In studies involving musculoskeletal disorders (e.g., total hip and knee arthroplasty), the descriptive system and utility index clearly discriminate between pre-operative patients and healthy normative controls (mean pre-op index $\approx 0.35$ vs. general population norm $\approx 0.86$). Similarly, in oncology, cardiology (NYHA functional classes I through IV), and neurology (e.g., Expanded Disability Status Scale in multiple sclerosis), the EQ-5D utility index displays statistically significant monotonic declines corresponding to worsening disease severity ($p < 0.001$).

Predictive and Longitudinal Validity (Responsiveness)

Predictive validity has been confirmed in epidemiological and clinical prospective studies where baseline EQ-5D utility and EQ-VAS scores independently predict long-term clinical endpoints, including all-cause mortality, unplanned hospital readmissions, institutionalization, and return-to-work rates. In terms of responsiveness (sensitivity to change over time), longitudinal studies demonstrate substantial effect sizes (Cohen’s $d > 0.80$; Standardized Response Mean $[SRM] > 0.90$) following successful therapeutic interventions, such as joint replacement, revascularization, or effective pharmacological management of major depressive disorder.

Comparative Validity: EQ-5D-3L vs. EQ-5D-5L

Comparative validation trials (e.g., Janssen et al., 2013; Pickard et al., 2007) confirm that the EQ-5D-5L significantly outperforms the 3L version by reducing ceiling effects (the proportion of respondents scoring 11111) by an absolute 10% to 25% across diverse cohorts. The Shannon Index ($H’$) and Shannon Evenness Index ($J’$), which measure informational efficiency, demonstrate that the 5L version captures substantially richer discriminative information across all five dimensions without degrading semantic comprehension.

8. Reliability

Because the EQ-5D descriptive system consists of single-item categorical indicators representing distinct functional domains, classical internal consistency metrics such as Cronbach’s alpha must be interpreted with caution. However, across various validation studies, Cronbach’s alpha for the five items typically ranges between 0.72 and 0.86, indicating acceptable internal consistency despite the broad spectrum of constructs measured.

Test-Retest Reliability

Test-retest stability is the primary reliability metric for multi-attribute health status classifications. Across clinical and general population samples evaluated under stable medical conditions over intervals ranging from 24 hours to 2 weeks, the EQ-5D displays excellent stability:

• EQ-5D Index Scores: Intraclass Correlation Coefficients (ICCs) for the continuous summary utility index consistently fall between 0.78 and 0.92, reflecting high reproducibility.
• EQ-VAS: The ICC for the continuous visual analogue thermometer ranges between 0.73 and 0.86.
• Individual Dimensions: Agreement for individual categorical dimensions, evaluated via Cohen’s weighted kappa ($\kappa_w$), demonstrates moderate-to-almost-perfect concordance:
  • Mobility: $\kappa_w = 0.75 – 0.90$
  • Self-Care: $\kappa_w = 0.70 – 0.88$
  • Usual Activities: $\kappa_w = 0.61 – 0.79$
  • Pain/Discomfort: $\kappa_w = 0.65 – 0.81$
  • Anxiety/Depression: $\kappa_w = 0.58 – 0.76$

Lower kappa values for Anxiety/Depression and Usual Activities are widely recognized in psychometric literature as reflecting the genuine temporal fluctuation of affective states and daily schedules rather than measurement instability of the instrument itself.

9. Factor Analysis

Structural evaluations of the EQ-5D using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) consistently elucidate the underlying latent dimensional architecture of the instrument across global populations.

Factor Structure and Dimensionality

Unconstrained EFA across large multinational general population datasets routinely extracts either a one-factor global HRQoL solution or a distinct two-factor solution depending on the analytical extraction criteria (eigenvalues > 1.0 vs. parallel analysis):

• Two-Factor Oblique Model: This is the most psychometrically and theoretically coherent model:
  • Factor 1: Physical Functioning / Somatic Health: Defined by high primary factor loadings from Mobility ($lambda = 0.78 – 0.89$), Self-Care ($lambda = 0.72 – 0.85$), and Usual Activities ($lambda = 0.65 – 0.78$), with moderate secondary cross-loading from Pain/Discomfort ($lambda = 0.45 – 0.58$).
  • Factor 2: Mental / Affective Health: Dominated by a heavy loading from Anxiety/Depression ($lambda = 0.82 – 0.92$), with a secondary loading from Pain/Discomfort ($lambda = 0.40 – 0.52$) and mild loading from Usual Activities ($lambda = 0.35 – 0.45$).
  • The inter-factor correlation between Physical and Mental dimensions is typically moderate ($r \approx 0.45 – 0.55$), validating that while physical and affective domains covary as components of overall health, they maintain distinct conceptual identities.

Confirmatory Factor Analysis (CFA) and Goodness-of-Fit

When evaluated via structural equation modeling using polychoric correlation matrices (essential for ordinal categorical data), the two-factor specification yields excellent model fit indices across clinical samples:

• Comparative Fit Index (CFI): $> 0.98$
• Tucker-Lewis Index (TLI): $> 0.97$
• Root Mean Square Error of Approximation (RMSEA): $< 0.05$ (90% CI: $0.035 – 0.062$)
• Standardized Root Mean Square Residual (SRMR): $< 0.03$

Item Response Theory (IRT) and Rasch Modeling

Application of the graded response model (GRM) and Rasch analysis confirms that the EQ-5D-5L offers superior item information curves (IIC) compared to the EQ-5D-3L. Item thresholds ($\eta_1$ to $\eta_4$) in the 5L version are ordered monotonically across all five dimensions, confirming that the five response levels represent progressive increases in functional impairment without category reversal. The discrimination parameters ($lpha$) are highest for Mobility and Anxiety/Depression, reflecting strong latent trait measurement precision.

10. Instrument / Measurement Tool

• Instrument Name: EuroQol EQ-5D (incorporating EQ-5D-3L, EQ-5D-5L, and EQ-VAS).
• Target Population: Adults aged 18 and older (a youth version, EQ-5D-Y, is independently validated for children and adolescents aged 4–15).
• Administration Modality: Self-administered paper-and-pencil, digital/web-based, smartphone app, tablet, face-to-face clinical interview, or proxy/caregiver interview.
• Completion Time: Approximately 2 to 5 minutes, placing virtually zero cognitive burden on the respondent.
• Structure of the Instrument:
  • Part 1: The Descriptive System: Five categorical items, each assessing a distinct dimension: (1) Mobility, (2) Self-Care, (3) Usual Activities, (4) Pain/Discomfort, and (5) Anxiety/Depression.
  • Part 2: EQ Visual Analogue Scale (EQ-VAS): A 20-centimeter vertical continuous scale graduated from 0 to 100, where 0 represents “The worst health you can imagine” and 100 represents “The best health you can imagine.”
• Response Formats:
  • EQ-5D-3L Format: 3-point ordinal scale per item:
    • 1 = No problems
    • 2 = Some / moderate problems
    • 3 = Confined to bed / unable / extreme problems
  • EQ-5D-5L Format: 5-point ordinal scale per item:
    • 1 = No problems
    • 2 = Slight problems
    • 3 = Moderate problems
    • 4 = Severe problems
    • 5 = Extreme problems / Unable to
• Scoring and Index Calculation:
  • Health Profile Code: Responses are combined into a 5-digit string representing the level chosen on each dimension in order (e.g., 11111 = full health; 21232 = slight/moderate impairments; 55555 = worst state on 5L).
  • Country-Specific Value Sets (Utility Index): The 5-digit profile is converted into a cardinal health state utility score using country-specific mathematical preference algorithms (value sets). These algorithms are generated from general population samples via Time Trade-Off (TTO) and Discrete Choice Experiment (DCE) valuation studies (e.g., standard value sets for the US, UK, Canada, Germany, Japan, France, etc.).
  • Crosswalk / Mapping: For jurisdictions without an established EQ-5D-5L value set, the van Hout et al. (2012) crosswalk methodology permits mapping 5L response data back onto established 3L value sets.
  • VAS Score: Recorded directly as an integer value from 0 to 100.

11. Permissions & Fee and Test Year

• Year of Initial Publication:
  • Original EQ-5D-3L: 1990 (EuroQol Group, Health Policy).
  • Refined EQ-5D-5L: 2005 / 2009 (formally released following methodological consensus; comprehensive multi-country valuation protocols launched 2011–2013).
• Copyright & Intellectual Property: The EuroQol instruments, including all language translations, digital adaptations, and value sets, are copyrighted worldwide by the EuroQol Research Foundation.
• Licensing and Fee Structure:
  • Academic & Non-Commercial Research: Free of charge. Academic researchers, clinicians, post-graduate students, non-profit healthcare institutions, and public health agencies may register and obtain licenses without user fees, provided registration is completed prior to study initiation via the EuroQol User Registration Portal.
  • Commercial Use: Requires a paid user license agreement. Pharmaceutical companies, contract research organizations (CROs), medical device manufacturers, and for-profit entities conducting sponsored clinical trials must pay licensing fees based on study scale, number of administrations, and language requirements.
• Registration & Official Portal: Formal permission, registration, approved user guides, scoring algorithms, and authorized official language translations (available in >170 languages) must be obtained directly through the EuroQol Foundation website: https://euroqol.org.

12. References

Brazier, J. E., Jones, N., & Kind, P. (1993). Testing the validity of the Euroqol and comparing it with the SF-36 health survey questionnaire. Quality of Life Research, 2(3), 169–180. https://doi.org/10.1007/BF00435221

Brazier, J. E., Walters, S. J., Nicholl, J. P., & Kohler, B. (1996). Using the SF-36 and Euroqol on an elderly population. Quality of Life Research, 5(2), 195–204. https://doi.org/10.1007/BF00435967

Brooks, R. (1996). EuroQol: The current state of play. Health Policy, 37(1), 53–72. https://doi.org/10.1016/0168-8510(96)00822-6

Dolan, P. (1997). Modeling valuations for EuroQol health states. Medical Care, 35(11), 1095–1108. https://doi.org/10.1097/00005650-199711000-00002

EuroQol Group. (1990). EuroQol: A new facility for the measurement of health-related quality of life. Health Policy, 16(3), 199–208. https://doi.org/10.1016/0277-9536(90)90221-D

Greiner, W., Weijnen, T., Nieuwenhuizen, M., Oppe, M., Badia, X., Busschbach, J., Buxton, M., Dolan, P., Kind, P., Krabbe, P., Leidl, R., Parkin, D., Perneger, T., Rathouz, P., Scalone, L., & de Charro, F. (2003). A single European currency for EQ-5D health states. Results from a six country study. The European Journal of Health Economics, 4(3), 222–231. https://doi.org/10.1007/s10198-003-0182-5

Herdman, M., Gudex, C., Lloyd, A., Janssen, M. F., Kind, P., Parkin, D., Bonsel, G., & Badia, X. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20(10), 1727–1736. https://doi.org/10.1007/s11136-011-9903-x

Janssen, M. F., Pickard, A. S., Golicki, D., Gudex, C., Niewada, M., Scalone, L., Swinburn, P., & Busschbach, J. (2013). Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: A multi-country study. Quality of Life Research, 22(7), 1717–1727. https://doi.org/10.1007/s11136-012-0322-4

McDowell, I. (2006). Measuring health: A guide to rating scales and questionnaires (3rd ed.). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195165678.001.0001

Pickard, A. S., De Leon, E. P., Kohlmann, T., Cella, D., & Rosenbloom, S. (2007). Psychometric evaluation of the 5-level EQ-5D in cancer patients. Medical Care, 45(3), 259–263. https://doi.org/10.1097/01.mlr.0000254514.85711.15

Roset, M., Badia, X., & Mayo, N. E. (1999). Sample size calculations in studies using the EuroQol 5D. Quality of Life Research, 8(6), 539–549. https://doi.org/10.1023/A:1008985227845

Shaw, J. W., Johnson, J. A., & Coons, S. J. (2005). US valuation of the EQ-5D health states: Development and testing of the D1 valuation model. Medical Care, 43(3), 203–220. https://doi.org/10.1097/01.mlr.0000151513.79197.8e

van Hout, B., Janssen, M. F., Feng, Y. S., Kohlmann, T., Busschbach, J., Golicki, D., Lloyd, A., Scalone, L., Kind, P., & Pickard, A. S. (2012). Interim scoring for the EQ-5D-5L: Mapping the EQ-5D-5L to EQ-5D-3L value sets. Value in Health, 15(5), 708–715. https://doi.org/10.1016/j.jval.2012.02.008

13. Items of the Scale (Questionnaire)