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We aimed to develop and evaluate the Computerized Glaucoma Visual Function Test (CoGVFT), among a cohort of glaucoma patients, and identify potential new items to optimize the test. A cross-sectional study involving 84 patients with open-angle glaucoma of varying severity and 18 controls without glaucoma were recruited. Better and worse eye visual field parameters, visual acuity, contrast sensitivity, 6-Part Cognitive Impairment Test (6CIT) and Glaucoma Activity Limitation-9 (GAL-9) questionnaire responses were recorded. The CoGVFT was administered to all participants. Rasch analysis was used to assess the psychometric properties of the CoGVFT, which was then evaluated with criterion, convergent, and divergent validity tests. Regression modeling determined factors predictive of CoGVFT performance. The 38-item CoGVFT demonstrated convergent validity with statistically significant differences in glaucoma severity groups (P < 0.001, analysis of variance). The correlation coefficient for CoGVFT person measures (logits) with GAL-9 person measures (logits) and better eye (BE) mean deviation was 0.528 (P < 0.001) and 0.762 (P < 0.001), respectively, demonstrating convergent validity. Divergent validity was suboptimal as the 6CIT score demonstrated moderate correlation (r = 0.463, P < 0.001) with CoGVFT person measures (logits). Multivariable analysis revealed that better BE contrast sensitivity, lower age, and better BE visual acuity were associated with better CoGVFT performance (P < 0.001). The CoGVFT retains most of the features of its predecessor to estimate vision-based activity limitation related to glaucoma. The CoGVFT is an easily accessible tool that can potentially be used in the community to help detect undiagnosed glaucoma in the population. Copyright 2020 The Authors.

Citation

Christopher Jong, Simon Edward Skalicky. The Computerized Glaucoma Visual Function Test: A Pilot Study Evaluating Computer-Screen Based Tests of Visual Function in Glaucoma. Translational vision science & technology. 2020 Nov;9(12):9

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PMID: 33200050

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