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Journal Article
Research Support, Non-U.S. Gov't
Adjusting for cross-cultural differences in computer-adaptive tests of quality of life.
Quality of Life Research 2018 April
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.
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.
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