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Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off

OBJECTIVE: The aim of this study was to compare online, unsupervised and face-to-face (F2F), supervised valuation of EQ-5D-5L health states using composite time trade-off (cTTO) tasks. METHODS: The official EuroQol experimental design and valuation protocol for the EQ-5D-5L of 86 health states were...

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Autores principales: Jiang, Ruixuan, Shaw, James, Mühlbacher, Axel, Lee, Todd A., Walton, Surrey, Kohlmann, Thomas, Norman, Richard, Pickard, A. Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068705/
https://www.ncbi.nlm.nih.gov/pubmed/33247810
http://dx.doi.org/10.1007/s11136-020-02712-1
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author Jiang, Ruixuan
Shaw, James
Mühlbacher, Axel
Lee, Todd A.
Walton, Surrey
Kohlmann, Thomas
Norman, Richard
Pickard, A. Simon
author_facet Jiang, Ruixuan
Shaw, James
Mühlbacher, Axel
Lee, Todd A.
Walton, Surrey
Kohlmann, Thomas
Norman, Richard
Pickard, A. Simon
author_sort Jiang, Ruixuan
collection PubMed
description OBJECTIVE: The aim of this study was to compare online, unsupervised and face-to-face (F2F), supervised valuation of EQ-5D-5L health states using composite time trade-off (cTTO) tasks. METHODS: The official EuroQol experimental design and valuation protocol for the EQ-5D-5L of 86 health states were implemented in interviewer-assisted, F2F and unsupervised, online studies. Validity of preferences was assessed using prevalence of inconsistent valuations and expected patterns of TTO values. Respondent task engagement was measured using number of trade-offs and time per task. Trading patterns such as better-than-dead only was compared between modes. Value sets were generated using linear regression with a random intercept (RILR). Value set characteristics such as range of scale and dimension ranking were evaluated between modes. RESULTS: Five hundred one online and 1,134 F2F respondents completed the surveys. Mean elicited TTO values were higher online than F2F when compared by health state severity. Compared to F2F, a larger proportion of online respondents did not assign the poorest EQ-5D-5L health state (i.e., 55555) the lowest TTO value ([Online] 41.3% [F2F] 12.2%) (p < 0.001). A higher percentage of online cTTO tasks were completed in 3 trade-offs or fewer ([Online] 15.8% [F2F] 3.7%), (p < 0.001). When modeled using the RILR, the F2F range of scale was larger than online ([Online] 0.600 [F2F] 1.307) and the respective dimension rankings differed. CONCLUSIONS: Compared to F2F data, TTO tasks conducted online had more inconsistencies and decreased engagement, which contributed to compromised data quality. This study illustrates the challenges of conducting online valuation studies using the TTO approach. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11136-020-02712-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-80687052021-05-05 Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off Jiang, Ruixuan Shaw, James Mühlbacher, Axel Lee, Todd A. Walton, Surrey Kohlmann, Thomas Norman, Richard Pickard, A. Simon Qual Life Res Article OBJECTIVE: The aim of this study was to compare online, unsupervised and face-to-face (F2F), supervised valuation of EQ-5D-5L health states using composite time trade-off (cTTO) tasks. METHODS: The official EuroQol experimental design and valuation protocol for the EQ-5D-5L of 86 health states were implemented in interviewer-assisted, F2F and unsupervised, online studies. Validity of preferences was assessed using prevalence of inconsistent valuations and expected patterns of TTO values. Respondent task engagement was measured using number of trade-offs and time per task. Trading patterns such as better-than-dead only was compared between modes. Value sets were generated using linear regression with a random intercept (RILR). Value set characteristics such as range of scale and dimension ranking were evaluated between modes. RESULTS: Five hundred one online and 1,134 F2F respondents completed the surveys. Mean elicited TTO values were higher online than F2F when compared by health state severity. Compared to F2F, a larger proportion of online respondents did not assign the poorest EQ-5D-5L health state (i.e., 55555) the lowest TTO value ([Online] 41.3% [F2F] 12.2%) (p < 0.001). A higher percentage of online cTTO tasks were completed in 3 trade-offs or fewer ([Online] 15.8% [F2F] 3.7%), (p < 0.001). When modeled using the RILR, the F2F range of scale was larger than online ([Online] 0.600 [F2F] 1.307) and the respective dimension rankings differed. CONCLUSIONS: Compared to F2F data, TTO tasks conducted online had more inconsistencies and decreased engagement, which contributed to compromised data quality. This study illustrates the challenges of conducting online valuation studies using the TTO approach. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11136-020-02712-1) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-11-28 2021 /pmc/articles/PMC8068705/ /pubmed/33247810 http://dx.doi.org/10.1007/s11136-020-02712-1 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Jiang, Ruixuan
Shaw, James
Mühlbacher, Axel
Lee, Todd A.
Walton, Surrey
Kohlmann, Thomas
Norman, Richard
Pickard, A. Simon
Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off
title Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off
title_full Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off
title_fullStr Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off
title_full_unstemmed Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off
title_short Comparison of online and face-to-face valuation of the EQ-5D-5L using composite time trade-off
title_sort comparison of online and face-to-face valuation of the eq-5d-5l using composite time trade-off
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8068705/
https://www.ncbi.nlm.nih.gov/pubmed/33247810
http://dx.doi.org/10.1007/s11136-020-02712-1
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