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Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching

BACKGROUND: Proxy respondent-someone who assists the intended respondent or responds on their behalf-are widely applied in the measurement of health-related quality of life (HRQL). However, proxies may not provide the same responses as the intended respondents, which may bias the findings. OBJECTIVE...

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Autores principales: Liang, Ying, Che, Tianle, Zhang, Haiyue, Shang, Lei, Zhang, Yuhai, Xu, Yongyong, Guo, Lingxia, Tan, Zhijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079393/
https://www.ncbi.nlm.nih.gov/pubmed/32188480
http://dx.doi.org/10.1186/s12955-020-01325-z
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author Liang, Ying
Che, Tianle
Zhang, Haiyue
Shang, Lei
Zhang, Yuhai
Xu, Yongyong
Guo, Lingxia
Tan, Zhijun
author_facet Liang, Ying
Che, Tianle
Zhang, Haiyue
Shang, Lei
Zhang, Yuhai
Xu, Yongyong
Guo, Lingxia
Tan, Zhijun
author_sort Liang, Ying
collection PubMed
description BACKGROUND: Proxy respondent-someone who assists the intended respondent or responds on their behalf-are widely applied in the measurement of health-related quality of life (HRQL). However, proxies may not provide the same responses as the intended respondents, which may bias the findings. OBJECTIVES: To determine whether the use of proxies is related to socio-demographic characteristics of the intended respondent, and to assess the possible proxy response bias of Chinese version of EQ-5D-3 L in general population. METHODS: A cross-sectional study based on a provincially representative sample from 2013 National Health Service Survey (NHSS) in Shaanxi, China was performed. HRQL was measured by Chinese version of EQ-5D-3 L. Propensity score matching (PSM) was used to get matched pairs of self-reports and proxy-reports. Before and after PSM, univariate logistic and linear models including the indicator of proxy response as the only independent variable, were employed to assess the possible proxy response bias of the dimensional and overall health status of EQ-5D-3 L respectively. RESULTS: 19.9% of the responses involved a proxy. Before PSM, the proxy-report group was younger in age and reported less unhealthy lifestyle, lower prevalence of disease, and less hospitalization than the self-report group. After PSM, it showed that the proxy-report group was statistically more likely to report health problem on each dimension of EQ-5D-3 L, with odds ratios larger than one comparing with self-report group. The means of EQ-5D-3 L index and EQ VAS of proxy-report group were 0.022 and 0.834 lower than self-report group. CONCLUSIONS: Significantly negative proxy response bias was found in Chinese EQ-5D-3 L in general population, and the magnitude of the bias was larger in physical dimensions than psychological dimensions after using PSM to control confounders.
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spelling pubmed-70793932020-03-23 Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching Liang, Ying Che, Tianle Zhang, Haiyue Shang, Lei Zhang, Yuhai Xu, Yongyong Guo, Lingxia Tan, Zhijun Health Qual Life Outcomes Research BACKGROUND: Proxy respondent-someone who assists the intended respondent or responds on their behalf-are widely applied in the measurement of health-related quality of life (HRQL). However, proxies may not provide the same responses as the intended respondents, which may bias the findings. OBJECTIVES: To determine whether the use of proxies is related to socio-demographic characteristics of the intended respondent, and to assess the possible proxy response bias of Chinese version of EQ-5D-3 L in general population. METHODS: A cross-sectional study based on a provincially representative sample from 2013 National Health Service Survey (NHSS) in Shaanxi, China was performed. HRQL was measured by Chinese version of EQ-5D-3 L. Propensity score matching (PSM) was used to get matched pairs of self-reports and proxy-reports. Before and after PSM, univariate logistic and linear models including the indicator of proxy response as the only independent variable, were employed to assess the possible proxy response bias of the dimensional and overall health status of EQ-5D-3 L respectively. RESULTS: 19.9% of the responses involved a proxy. Before PSM, the proxy-report group was younger in age and reported less unhealthy lifestyle, lower prevalence of disease, and less hospitalization than the self-report group. After PSM, it showed that the proxy-report group was statistically more likely to report health problem on each dimension of EQ-5D-3 L, with odds ratios larger than one comparing with self-report group. The means of EQ-5D-3 L index and EQ VAS of proxy-report group were 0.022 and 0.834 lower than self-report group. CONCLUSIONS: Significantly negative proxy response bias was found in Chinese EQ-5D-3 L in general population, and the magnitude of the bias was larger in physical dimensions than psychological dimensions after using PSM to control confounders. BioMed Central 2020-03-18 /pmc/articles/PMC7079393/ /pubmed/32188480 http://dx.doi.org/10.1186/s12955-020-01325-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Liang, Ying
Che, Tianle
Zhang, Haiyue
Shang, Lei
Zhang, Yuhai
Xu, Yongyong
Guo, Lingxia
Tan, Zhijun
Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching
title Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching
title_full Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching
title_fullStr Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching
title_full_unstemmed Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching
title_short Assessing the proxy response bias of EQ–5D-3 L in general population: a study based on a large-scale representative household health survey using propensity score matching
title_sort assessing the proxy response bias of eq–5d-3 l in general population: a study based on a large-scale representative household health survey using propensity score matching
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079393/
https://www.ncbi.nlm.nih.gov/pubmed/32188480
http://dx.doi.org/10.1186/s12955-020-01325-z
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