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Adjusting for cross-cultural differences in computer-adaptive tests of quality of life

PURPOSE: Previous studies using the WHOQOL measures have demonstrated that the relationship between individual items and the underlying quality of life (QoL) construct may differ between cultures. If unaccounted for, these differing relationships can lead to measurement bias which, in turn, can unde...

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Autores principales: Gibbons, C. J., Skevington, S. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5874271/
https://www.ncbi.nlm.nih.gov/pubmed/29204782
http://dx.doi.org/10.1007/s11136-017-1738-7
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author Gibbons, C. J.
Skevington, S. M.
author_facet Gibbons, C. J.
Skevington, S. M.
author_sort Gibbons, C. J.
collection PubMed
description PURPOSE: Previous studies using the WHOQOL measures have demonstrated that the relationship between individual items and the underlying quality of life (QoL) construct may differ between cultures. If unaccounted for, these differing relationships can lead to measurement bias which, in turn, can undermine the reliability of results. METHODS: We used item response theory (IRT) to assess differential item functioning (DIF) in WHOQOL data from diverse language versions collected in UK, Zimbabwe, Russia, and India (total N = 1332). Data were fitted to the partial credit ‘Rasch’ model. We used four item banks previously derived from the WHOQOL-100 measure, which provided excellent measurement for physical, psychological, social, and environmental quality of life domains (40 items overall). Cross-cultural differential item functioning was assessed using analysis of variance for item residuals and post hoc Tukey tests. Simulated computer-adaptive tests (CATs) were conducted to assess the efficiency and precision of the four items banks. RESULTS: Splitting item parameters by DIF results in four linked item banks without DIF or other breaches of IRT model assumptions. Simulated CATs were more precise and efficient than longer paper-based alternatives. DISCUSSION: Assessing differential item functioning using item response theory can identify measurement invariance between cultures which, if uncontrolled, may undermine accurate comparisons in computer-adaptive testing assessments of QoL. We demonstrate how compensating for DIF using item anchoring allowed data from all four countries to be compared on a common metric, thus facilitating assessments which were both sensitive to cultural nuance and comparable between countries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11136-017-1738-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-58742712018-03-30 Adjusting for cross-cultural differences in computer-adaptive tests of quality of life Gibbons, C. J. Skevington, S. M. Qual Life Res Article PURPOSE: Previous studies using the WHOQOL measures have demonstrated that the relationship between individual items and the underlying quality of life (QoL) construct may differ between cultures. If unaccounted for, these differing relationships can lead to measurement bias which, in turn, can undermine the reliability of results. METHODS: We used item response theory (IRT) to assess differential item functioning (DIF) in WHOQOL data from diverse language versions collected in UK, Zimbabwe, Russia, and India (total N = 1332). Data were fitted to the partial credit ‘Rasch’ model. We used four item banks previously derived from the WHOQOL-100 measure, which provided excellent measurement for physical, psychological, social, and environmental quality of life domains (40 items overall). Cross-cultural differential item functioning was assessed using analysis of variance for item residuals and post hoc Tukey tests. Simulated computer-adaptive tests (CATs) were conducted to assess the efficiency and precision of the four items banks. RESULTS: Splitting item parameters by DIF results in four linked item banks without DIF or other breaches of IRT model assumptions. Simulated CATs were more precise and efficient than longer paper-based alternatives. DISCUSSION: Assessing differential item functioning using item response theory can identify measurement invariance between cultures which, if uncontrolled, may undermine accurate comparisons in computer-adaptive testing assessments of QoL. We demonstrate how compensating for DIF using item anchoring allowed data from all four countries to be compared on a common metric, thus facilitating assessments which were both sensitive to cultural nuance and comparable between countries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11136-017-1738-7) contains supplementary material, which is available to authorized users. Springer International Publishing 2017-12-04 2018 /pmc/articles/PMC5874271/ /pubmed/29204782 http://dx.doi.org/10.1007/s11136-017-1738-7 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Gibbons, C. J.
Skevington, S. M.
Adjusting for cross-cultural differences in computer-adaptive tests of quality of life
title Adjusting for cross-cultural differences in computer-adaptive tests of quality of life
title_full Adjusting for cross-cultural differences in computer-adaptive tests of quality of life
title_fullStr Adjusting for cross-cultural differences in computer-adaptive tests of quality of life
title_full_unstemmed Adjusting for cross-cultural differences in computer-adaptive tests of quality of life
title_short Adjusting for cross-cultural differences in computer-adaptive tests of quality of life
title_sort adjusting for cross-cultural differences in computer-adaptive tests of quality of life
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5874271/
https://www.ncbi.nlm.nih.gov/pubmed/29204782
http://dx.doi.org/10.1007/s11136-017-1738-7
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