Project
The Project
An overview of W-MIC — its background, aims and methodology
Overview
Preference-weighted generic instruments used in economic evaluations may provide a partial assessment of effects when the scope of an intervention extends beyond health. This is particularly relevant in non-curative care settings — such as social care, rehabilitation, or services for older adults — where the benefits of interventions are broader than what standard health measures capture.
Multiple wellbeing instruments have been developed to expand the scope of economic evaluations, but selecting the most appropriate one remains challenging. Instruments differ in their theoretical foundations, scope, target populations, and stage of development, meaning that using different instruments to assess the same technology or service may yield different conclusions about its benefits.
The W-MIC study was developed to address this methodological gap. Funded by ZonMw, it provides a large, open-access dataset and a systematic comparison of leading wellbeing instruments across diverse populations and care contexts.
Context & Motivation
Economic evaluations of health technologies and services typically rely on preference-weighted health measures such as the EQ-5D. While well-validated in curative care, these instruments may not adequately capture the full range of benefits in non-curative settings, where interventions aim to improve broader aspects of wellbeing rather than health per se. A growing number of wellbeing instruments have been proposed as alternatives, but the evidence base for their use in economic evaluation remains limited and fragmented. The W-MIC study was designed to fill this gap by generating comparable, large-scale evidence on multiple instruments simultaneously, using a harmonised dataset made openly available for secondary research.
Aims & Objectives
The W-MIC project has three overarching aims:
Dataset generation - Build a large, open-access dataset in health and wellbeing that can be leveraged for multiple research purposes by anyone.
Psychometric validation — Provide systematic evidence on the psychometric properties of multiple wellbeing instruments across different populations and non-curative care contexts, including their distributional properties, reliability, and construct validity.
Instrument comparison — Evaluate how these instruments perform relative to one another, and whether differences in their theoretical foundations, scope, or target populations lead to different conclusions when used to assess health technologies and services.
Together, these aims are intended to support researchers, health technology assessment (HTA) bodies, policy makers, and developers of health and social care technologies in selecting appropriate outcome measures for economic evaluations.
Study Design
The project is structured in two parts.
Part 1 — Cross-sectional survey. A large online survey was conducted in the Netherlands and the United States, targeting a sample of approximately 7,000 adults. The survey included seven wellbeing instruments — ASCOT-STC4, EQ-HWB-9, ICECAP-A/O, QOL-ACC, SWB-5D, WiX, and WOOP — alongside measures of general health (EQ-5D-5L, PHQ-15, self-reported overall health status and health satisfaction) and subjective wellbeing (SWLS, OECD eudaimonic questions, SPANE), as well as demographic information. The target sample included four subgroups: the general public, older adults, individuals with chronic health conditions, and social care users. A follow-up measurement was conducted in a subgroup of participants at two weeks and three months after the initial survey. Data quality was systematically assessed using a series of indicators targeting response inconsistency and careless responding.
Part 2 — Clinical case studies. Two case studies were conducted in non-curative care settings to evaluate the fit-for-purpose of the wellbeing instruments in applied clinical contexts. These involved participants with cognitive impairments and individuals undergoing physical rehabilitation.
Analyses draw on psychometric and statistical methods and will explore descriptive distributions, reliability, convergent and known-group validity across instruments and subgroups as well other advanted statistical methods such as factor analysis, latent profile analysis and psychometric network analysis.
Funding & Affiliations
The W-MIC project is funded by ZonMw (the Netherlands Organisation for Health Research and Development). It is based at the Erasmus School of Health Policy & Management (ESHPM), Erasmus University Rotterdam, in collaboration with the EuroQol Research Foundation.
Timeline
| Phase | Period | Description |
|---|---|---|
| Phase 1 | 2024–2025 | Instrument selection & survey design |
| Phase 2A | 2025–2025 | Online survey in the Netherlands and United States (N≈7,000); follow-up in a subgroup |
| Phase 2B | 2025–2027 | Case studies: Application of instruments in two clinical non-curative care settings |
| Phase 3 | 2025–2028 | Psychometric analyses: Validation and comparison of instruments across subgroups and contexts |
| Phase 4 | 2025–2028 | Dissemination: Publication of findings and open-access dataset release |