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ReQoL-UI (Recovering Quality of Life - Utility Index)

Methodpeer-reviewed✓ Source-grounded

ReQoL-UI is a method designed to measure quality of life in people receiving mental health care. It converts responses from the ReQoL-10 questionnaire into a single number (utility) that reflects how much someone values their health state, which can be used to calculate quality-adjusted life years (QALYs) for comparing treatments.

At a glance

Use when

Evaluating mental health interventions where generic measures may miss important benefits; when QALYs are required for economic evaluation in mental health; when patient-centered recovery outcomes are prioritized

Avoid when

Assessing non-mental health conditions; when a generic measure is sufficient or required for cross-condition comparison; when only clinical symptom change (not quality of life) is of interest

Inputs

Responses to the ReQoL-10 questionnaire, which describes a health state across 7 dimensions (6 mental health, 1 physical health)

Outputs

A single utility score ranging from -0.195 to 1.0, suitable for use in QALY calculations

How it works

The ReQoL-UI is a preference-based index derived from the ReQoL-10 measure using psychometric methods including confirmatory factor analysis and item response theory to develop a 7-dimensional health state classification system (6 mental health domains, 1 physical health domain). Utility weights were elicited via time-trade-off (TTO) valuation with a representative UK general population sample (n=305), and a random effects regression model was used to generate the scoring algorithm. The resulting index produces utility values ranging from -0.195 (worse than dead) to 1.0 (full health), enabling QALY calculation for economic evaluation in mental health.

HTA domains
Clinical Effectiveness, Patient and Social Aspects
Categories
HRQoLPROMs
Assumptions
The ReQoL-10 items adequately capture dimensions of quality of life important in mental health recovery; general population TTO responses reflect societal values for mental health states; the random effects model appropriately captures variance in utility preferences
Strengths
Developed specifically for mental health populations using patient-reported input,Based on robust psychometric methods (IRT, CFA) for item selection and classification,Uses general population valuation for societal perspective in economic evaluation,Generates utilities compatible with QALY framework
Limitations
Limited to 64 directly valued states, with others being modeled,May not capture all aspects of mental health recovery relevant to specific subpopulations,Relies on TTO method, which can be challenging for mental health states
Also known as
ReQoL Utility Index, ReQoL-10 Utility Index

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Beta record. Generated from the primary source via AI extraction and independent audit, pending final human review.