Comparing Color Vision Testing Using the Farnsworth-Munsell 100-Hue, Ishihara Compatible, and Digital TCV Software

摘要

It is crucial that eye care professionals be able to provide quick, accurate, and complete testing of color vision, both to enhance the lives of patients and to satisfy the requirements laid out by industry standards. With the growing popularity of the use of digital equipment in offices, there is a natural progression to digital color vision screening tests, which have the advantage of being fast, inexpensive, and readily portable with automated scoring for greater consistency. Few studies have sought to validate specific digital tests. The aim of this study is to compare two traditionally accepted manual tests for detecting congenital color vision deficiency (CCVD) with analogous digital versions. Thirty-five individuals (11 male, 24 female, mean age 25.1 years) with normal color vision and six individuals (all male, mean age 40.0 years) with congenital red-green deficiency were asked to perform the following four tests for detecting CCVD: Ishihara Compatible Pseudoisochromatic Plate (Ishihara); Waggoner Computerized Color Vision Test by Konan Medical USA (TCV); Farnsworth-Munsell 100-Hue Color Cap Rearrangement Test (100-Hue); and an online version of the Farnworth-Munsell 100-Hue (Online 100-Hue) available for free at color-blindness.com. The administration time for each test was recorded along with test scores. The Ishihara and TCV had sensitivities of 83.3% and 100% and specificities of 100% and 94.3%, respectively. The manual 100-Hue and the online 100-Hue had sensitivities of 66.7% and 83.3% and specificities of 88.6% and 85.7%, respectively. The average test time was 2.3 minutes for the Ishihara and 3.4 minutes for the TCV. The geometric mean completion time for the manual 100-Hue was 15 minutes; for the Online 100-Hue it was 7.5 minutes, thus reducing the test time by 50%. A Bland-Altmann analysis shows that the Online 100-Hue tends to give higher scores than the manual 100-Hue; however, there are several outliers that lead to a wide range and wide variability. Each of the tests included in this study has specific strengths and weaknesses. An understanding of these can aid the clinician in selecting the ideal test for a given situation as well as guide research and development of future digital color vision tests. There are still concerns about consistency and accuracy of digital color tests due to the variations in screens, but so far, results are promising.