Measuring outcomes for loneliness research: examining the appropriateness of the EQ-5D-5 L and EQ-HWB

Loneliness is a recognized global public health concern and significantly impacts overall well-being. This study aims to determine utility values associated with different loneliness levels and assess the performance of the EQ-5D-5D and EQ-HWB measures in capturing loneliness. Data from an online survey comprising a nationally representative cross-sectional sample of Australian adults was used. The survey included information on demographics, the 20-item Revised UCLA Loneliness Scale (R-UCLA-RS), EQ-5D-5 L, and EQ-HWB. The Kruskal-Wallis test was used to assess the statistical differences in utility scores from the EQ-5D-5 L and EQ-HWB-9, as well as the EQ-HWB sum score, across three levels of loneliness (Low/Medium/High) as measured by the R-UCLA-LS. Exploratory factor analysis (EFA) was used to explore the conceptual overlap between the EQ-5D-5 L and EQ-HWB with the R-UCLA-LS item measure. Additionally, ordinary least squares (OLS) regression was conducted to identify predictors of loneliness from the items that overlapped with the R-UCLA-LS.v 2072 respondents completed the survey. Both the EQ-5D-5 L and EQ-HWB measures significantly differentiated between loneliness levels (p < 0.001). The mean EQ-5D-5 L utility scores were 0.89 for low loneliness, 0.81 for moderate loneliness, and 0.72 for moderate to high loneliness. The EQ-HWB-9 utility scores were 0.88, 0.75, and 0.58, respectively, showing greater sensitivity to the burden of loneliness. EFA revealed no overlap between EQ-5D-5 L items and the R-UCLA-LS, while five EQ-HWB items overlapped with the R-UCLA-LS, including the “feel lonely” item, which is also part of the EQ-HWB-9. Regression analysis explained 53.58% of the variance in loneliness scores (F(10, 1463) = 168.87, p < 0.001), with “feeling lonely” and “feeling unsupported” contributing most to the prediction. While the EQ-5D-5 L shows moderate sensitivity to loneliness, the EQ-HWB and EQ-HWB-9 demonstrate stronger associations with loneliness measures. The EQ-HWB-9, in particular, shows promise as a brief yet sensitive tool for capturing loneliness-related burden and may be especially useful in interventions targeting loneliness.

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Publication Details

Journal
The European Journal of Health Economics
Published
2026-03-21
DOI
https://doi.org/10.1007/s10198-026-01904-9
Primary Topic
Health disparities and outcomes
Type
article
Field-Weighted Citation Impact
0.00
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article

Measuring outcomes for loneliness research: examining the appropriateness of the EQ-5D-5 L and EQ-HWB

May Lim, Ishani Majmudar, Mohammadreza Mohebbi, Cathrine Mihalopoulos et al.
The European Journal of Health Economics
Health disparities and outcomes
article

Measuring outcomes for loneliness research: examining the appropriateness of the EQ-5D-5 L and EQ-HWB

May Lim, Ishani Majmudar, Mohammadreza Mohebbi, Cathrine Mihalopoulos, Lidia Engel, Julie Abimaniyi-Ochom, Lan Gao
article en

Abstract

Loneliness is a recognized global public health concern and significantly impacts overall well-being. This study aims to determine utility values associated with different loneliness levels and assess the performance of the EQ-5D-5D and EQ-HWB measures in capturing loneliness. Data from an online survey comprising a nationally representative cross-sectional sample of Australian adults was used. The survey included information on demographics, the 20-item Revised UCLA Loneliness Scale (R-UCLA-RS), EQ-5D-5 L, and EQ-HWB. The Kruskal-Wallis test was used to assess the statistical differences in utility scores from the EQ-5D-5 L and EQ-HWB-9, as well as the EQ-HWB sum score, across three levels of loneliness (Low/Medium/High) as measured by the R-UCLA-LS. Exploratory factor analysis (EFA) was used to explore the conceptual overlap between the EQ-5D-5 L and EQ-HWB with the R-UCLA-LS item measure. Additionally, ordinary least squares (OLS) regression was conducted to identify predictors of loneliness from the items that overlapped with the R-UCLA-LS.v 2072 respondents completed the survey. Both the EQ-5D-5 L and EQ-HWB measures significantly differentiated between loneliness levels (p < 0.001). The mean EQ-5D-5 L utility scores were 0.89 for low loneliness, 0.81 for moderate loneliness, and 0.72 for moderate to high loneliness. The EQ-HWB-9 utility scores were 0.88, 0.75, and 0.58, respectively, showing greater sensitivity to the burden of loneliness. EFA revealed no overlap between EQ-5D-5 L items and the R-UCLA-LS, while five EQ-HWB items overlapped with the R-UCLA-LS, including the “feel lonely” item, which is also part of the EQ-HWB-9. Regression analysis explained 53.58% of the variance in loneliness scores (F(10, 1463) = 168.87, p < 0.001), with “feeling lonely” and “feeling unsupported” contributing most to the prediction. While the EQ-5D-5 L shows moderate sensitivity to loneliness, the EQ-HWB and EQ-HWB-9 demonstrate stronger associations with loneliness measures. The EQ-HWB-9, in particular, shows promise as a brief yet sensitive tool for capturing loneliness-related burden and may be especially useful in interventions targeting loneliness.

The European Journal of Health Economics
The University of Sydney (AU), Deakin University (AU), Monash Health (AU), Monash University (AU), Swinburne University of Technology (AU)
Openalex Percentile: Top 18%
Health disparities and outcomes
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