This study systematically compared the psychometric properties of 6 of the 5-level and 3-level EQ-5D bolt-ons (vision, breathing, tiredness, sleep, social relationships, and self-confidence).
Population Norms Study (POP-UP) is a longitudinal survey collecting general population data from United States, Canada, United Kingdom, Italy, Spain, Germany, the Netherlands, and Belgium. Respondents entered demographics and health conditions data and completed the EQ-5D-5L/3L with bolt-ons, Myasthenia Gravis Activities of Daily Living (MG-ADL), and Health Utility Index-3 (HUI-3). Psychometric properties included ceiling/floor, informativity, divergent and convergent validity, reliability, known-groups validity, and responsiveness.
A total of 9,758 respondents completed the survey in 2021, and 4,839 respondents in 2023. The 5-level bolt-ons reduced ceiling effects by 35% and floor effects by 55% compared with the 3-level, with the largest reductions for vision and sleep (42%/57%) and the smallest for breathing (29%/44%). Informativity was higher for the 5-level bolt-ons (3%-11%) than 3-level (2%-9%), except for breathing (−2%). Most bolt-ons showed weak to moderate correlations with EQ-5D dimensions, except for social relationships, which correlated strongly with anxiety/depression (r = 0.61). Both measures showed strong convergent validity for breathing (5-level r = 0.68; 3-level r = 0.66) and lower for vision (5-level r = 0.37; 3-level r = 0.32). EQ-5D + 5-level and EQ-5D-5L + 3-level bolt-ons had excellent reliability (Intraclass Correlation Coefficients = 0.92-0.97). Adding bolt-ons did not significantly improve known-groups validity, except for breathing (relative efficiency EQ-5D + 5-level = 1.12; EQ-5D-5L + 3-level = 1.10). The 5-level bolt-ons improved responsiveness, detecting 47.1% more improvements and 55.7% more worsening over time.
All 6 of the 5-level EQ-5D bolt-ons outperformed the 3-level bolt-ons by reducing ceiling and floor, enhancing informativity, demonstrating divergent validity, and improving responsiveness.
What is it about? The study investigates the effectiveness of adding extra questions, called "bolt-ons," to a health-related quality of life measurement tool known as EQ-5D. These bolt-ons come in 2 versions: one with 3 answer levels, and one with 5. So far, it has been unclear which version provides better insights into people’s health. This study fills the gap by comparing both versions in a general population across several countries. The paper suggests that the 5-level bolt-ons offer improved measurement accuracy and enhance the understanding of health-related quality of life.
How was the research conducted? The research compared the 2 versions of 6 bolt-ons to assess their performance. Data analysis methods were applied in a large survey involving participants from 8 countries: United States, Canada, United Kingdom, Italy, Spain, Germany, The Netherlands, and Belgium. The study focused on people from the general population rather than specific patient groups to ensure a comprehensive analysis across diverse demographics. Researchers collected data by having participants fill out surveys, which included questions on various health aspects and the EQ-5D tool with bolt-ons.
What were the results? The main finding is that all 6 5-level bolt-ons outperform the 3-level versions, reducing ceiling effect (when too many people score at the top) by 35 percent and floor effect (when too many score at the bottom) by 55 percent, with the largest reduction for the bolt-ons vision and sleep and the smallest for bolt-on breathing. Five-level versions generally captured more information and showed stronger relationships to related measures. Reliability was excellent, whereas only the breathing bolt-on could distinguish between people with breathing problems. A notable surprise was how strongly social relationships aligned with the mood dimension, suggesting overlap that may need careful handling.
Why are the results important? For health technology assessment agencies, these results indicate that using 5-level bolt-ons can provide more accurate data on health assessment. Practically, this could lead to better health evaluations and treatment decisions in clinical settings. Patients and healthcare providers benefit from the more precise measurement of health-related quality of life, potentially leading to improved care and outcomes. In the long term, these findings could influence the design of new health assessment tools and contribute to more effective health policy making.
What are the strengths and weaknesses of this study? A major strength of this study is its large, representative sample from multiple countries, which enhances the generalizability of the findings. However, a limitation is the potential for cultural differences not fully accounted for in the analysis. Future research could expand on these findings by examining how bolt-ons perform in specific patient populations and explore differences between countries in more detail.
Note: This content was created with assistance from artificial intelligence (AI) and has been reviewed and edited by ISPOR staff. For more information or for inquiries on ISPOR’s AI policy, click here or contact us at info@ispor.org.