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Robert P. Finger, Karsten Kortuem, Eva Fenwick, Bettina von Livonius, Jill E. Keeffe, Christoph W. Hirneiss; Evaluation of a Vision-Related Utility Instrument: The German Vision and Quality of Life Index. Invest. Ophthalmol. Vis. Sci. 2013;54(2):1289-1294. doi: 10.1167/iovs.12-10828.
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© ARVO (1962-2015); The Authors (2016-present)
Multi-attribute utility instruments (MAUIs), which contain a descriptive system, including several health dimensions with associated levels of increasing severity, are used commonly to measure utilities. However, the validity of the descriptive systems rarely is examined using modern psychometric theory. Therefore, we evaluated the psychometric properties of the German version of the Vision and Quality of Life Index (VisQol), a six-item vision-related MAUI.
The German VisQol was self-administered to 340 patients and 280 controls. All subjects underwent a full ophthalmologic examination, including best-corrected visual acuity (VA) testing. The psychometric properties of the VisQoL were assessed using Rasch analysis.
The VisQoL's descriptive system did not function in controls. In patients, after collapsing response categories to resolve disordered thresholds and omitting misfitting persons, the measurement properties (i.e., precision, unidimensionality, and targeting) of the German VisQoL were satisfactory. Most person misfit related to unexpected responses to item 4 (“organizing assistance”). Rasch-generated person estimates were not different between age categories, sex, or underlying ocular condition, but decreased significantly with presence of visual impairment in the better eye (LogMAR ≥ 0.5, 1.20 ± 4.62 compared to 3.46 ± 3.52, P < 0.001).
The German VisQoL's descriptive system displayed adequate fit to the Rasch model after removal of a large proportion of patients with poor fit statistics. However, the wording of item four should be revised to reduce respondent confusion and measurement “noise.” The scale's descriptive system does not function in a sample of visually unimpaired persons, most likely due to a lack of variance in the measured trait.
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