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    Rights statement: This is the author’s version of a work that was accepted for publication in Social Science & Medicine. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Social Science & Medicine, 190, 2017 DOI: 10.1016/j.socscimed.2017.08.033

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Differential item functioning in quality of life measurement: an analysis using anchoring vignettes

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<mark>Journal publication date</mark>10/2017
<mark>Journal</mark>Social Science and Medicine
Volume190
Number of pages9
Pages (from-to)247-255
Publication StatusPublished
Early online date26/08/17
<mark>Original language</mark>English

Abstract

Systematic differences in the ways that people use and interpret response categories (differential item functioning, DIF) can introduce bias when using self-assessments to compare health or quality of life across heterogeneous groups. This paper reports on an exploratory analysis involving the use of anchoring vignettes to identify differential item functioning (DIF) in a commonly used measure for assessing health-related quality of life - namely the EQ-5D. Using data from a bespoke (i.e. custom) survey that recruited a representative sample of 4300 respondents from the general Australian population in 2014 and 2015, we find that the assumptions of response consistency (RC) and vignette equivalence (VE) hold in a sub-sample of respondents aged 55–65 years (n = 914), which demonstrates that vignettes can appropriately identify DIF in EQ-5D reporting for this age group. We find that the EQ-5D is indeed subject to DIF, and that failure to account for DIF can lead to conclusions that are misleading when using the instrument to compare health or quality of life across heterogeneous groups. We also provide several important insights in terms of the identifying assumptions of RC and VE. We conclude that the implications of DIF could be of considerable importance, not only for outcomes research, but for funding decisions in healthcare more broadly given the strong reliance on patient-reported outcome measures in economic evaluations for health technology assessment.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Social Science & Medicine. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Social Science & Medicine, 190, 2017 DOI: 10.1016/j.socscimed.2017.08.033