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. 2017 May 31;6(3):12.
doi: 10.1167/tvst.6.3.12. eCollection 2017 May.

Optimizing the ULV-VFQ for Clinical Use Through Item Set Reduction: Psychometric Properties and Trade-Offs

Affiliations

Optimizing the ULV-VFQ for Clinical Use Through Item Set Reduction: Psychometric Properties and Trade-Offs

Gislin Dagnelie et al. Transl Vis Sci Technol. .

Abstract

Purpose: We examine the dimensionality of the 150-item visual functioning questionnaire for individuals with ultralow vision (ULV-VFQ) and develop representative abbreviated versions, facilitating clinical use, while retaining compatibility with a 17-item performance assessment.

Methods: Subsets with 50 and 23 items covering the full difficulty range were selected, with evenly spaced item measures (IMs) and good representation of visual aspects and functional domains. Person measures (PMs) for the anchored subsets were derived through Rasch analysis of data from 80 respondents.

Results: Fit statistics for the reduced item sets were similar to those for the full set, with reliabilities at or above 95%. Mean PMs in the reduced sets were within 0.8 standard errors (SEs) of those in the full set. SEs of the PMs increased from the SE for 150 items, roughly in inverse proportion with the square root of the set size. Unexplained variance levels (24%-27%) and variance of the first unexplained factor (3.3%-3.9%) were close to those (30% and 2.6%) for 150 items. Differential item functions for omitted items were negligible. Aspects and domains are adequately represented in the reduced sets.

Conclusions: Self-reported visual ability can be measured accurately using appropriately chosen anchored subsets of the ULV-VFQ. Functional ability of individuals with ULV is characterized adequately by a single dimension.

Translational relevance: The ULV-VFQ50 and ULV-VFQ23, using anchored IMs from the 150-item ULV-VFQ, provide an efficient and reliable self-report assessment of visual ability in individuals whose visual impairment is too severe for assessment with VFQs currently in use.

Keywords: low vision rehabilitation; patient-reported outcomes; prosthetic vision; ultralow vision; visual functioning questionnaire.

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Figures

Figure 1
Figure 1
Person (leftward) – Item (rightward) plots along a common logit axis, for the four ULV-VFQ versions, with item anchoring used in analyses for the reduced item sets. Item difficulty and person ability increase from bottom to top. Notice minor shifts and reduced resolution in PMs with decreasing item set size, especially for those with lowest visual ability.
Figure 2
Figure 2
SE (top), statistical information ([N × SE2]−1; bottom) gained, as a function of PM, for administration of 4 versions of the ULV-VFQ. The maximum amount of information gained is only slightly higher with 150 items than with lower item numbers. Information is gained even for PMs well outside the IM range (−3.39–2.70; −2.71–1.80 for the 17-item version), but SE rises sharply in this region, especially for 17 items. Notice the shift in the peak of the distribution for the smaller item sets: As the median item measure shifts, so does the person measure for which SE is smallest, and for which the highest information is gained.
Figure 3
Figure 3
IMs and reliability Z-scores for the ULV-VFQ IMs (anchored; top) and PMs (unanchored; bottom). As indicated in the top legend, Items represented by dark blue circles are included in all four versions of the instrument, others only in the versions indicated by their markers. The 4 sets in the bottom do not coincide, since PMs were not anchored. Dot size in either panel is proportional to the SE of the Measure estimate, and, thus, lowest in the center of the vertical range (both panels) and for the largest item set (bottom).
Figure 4
Figure 4
Scree plot of the explained (persons, items) and 5 largest unexplained variance components, for each of the 4 data sets, on a logarithmic scale. Total unexplained variance ranged from 30% (150 items) to 24% (23 items).
Figure 5
Figure 5
Person measure estimates for item groups governed by different visual aspects (top) and domains (bottom) projected onto the first two Principal Components derived from the PMs estimated for these item groups. The left shows projected vectors independent of item group size; the right shows the same vectors scaled according to item group size. Note the expanded vertical scale in the right.

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