Color Vision Testing, Standards, and Visual Performance of the U.S. Military

Author:

Gao Hong1,Kirkendall Cristina D2,Kinney Micah J3,Preston Adam M1,Reddix Michael D1

Affiliation:

1. Naval Aerospace Medical Research Laboratory, Naval Medical Research Unit Dayton , Wright Patterson AFB, OH 45433-7955, USA

2. Selection and Assignment Research Unit, U.S. Army Research Institute , Fort Belvoir, VA 22060, USA

3. Naval Air Warfare Center Aircraft Division , Patuxent River, MD 20670-1156, USA

Abstract

ABSTRACT Introduction Color vision deficiency (CVD) is a disqualifying condition for military special duty occupations. Color vision testing and standards vary slightly among the U.S. military branches. Paper-based pseudoisochromatic plates (PIPs) remain a screening tool. Computer-based color vision tests (CVTs), i.e., the Cone Contrast Test (CCT), the Colour Assessment and Diagnosis (CAD) test, and the Waggoner Computerized Color Vision Test (WCCVT), are now replacing the Farnsworth Lantern Test (FALANT) and its variants to serve as a primary or secondary test in the U.S. Armed Forces. To maintain consistency in recruitment, performance, and safety, the study objectives were to examine military color vision testing, passing criteria, and color discrimination performance. Methods Study participants were 191 (17% female) students, faculty, and staff of the U.S. Air Force Academy and the Naval Aerospace Medical Institute. All subjects performed six CVTs, and 141 participants completed two additional military relevant color discrimination tasks. Friedman non-parametric test and Wilcoxon signed-rank post hoc test with Bonferroni adjusted P values were used to compare CVTs and standards. Analysis of variance and Bonferroni adjusted post hoc test were used to describe effects on color discrimination performance. Results The Heidelberg Multicolor—Moreland and Rayleigh (HMC-MR) anomaloscope diagnosed 58 CVD (30.4%). There were no statistically significant differences in identifying red–green CVD by the HMC-MR, CCT, CAD, WCCVT, and PIP tests (P = .18), or classifying deutan, protan, and normal color vision (CVN) by the HMC-MR and the CVT (P = .25). Classification of tritan CVD was significantly different depending on which CVT was used (P < .001). Second, overall passing rates were 79.1% on the CAD (≤6 standard normal unit (SNU)), 78.5% on the combined PIP/FALANT, 78.0% on the CCT (≥55%), and 75.4% on the WCCVT (mild) military standards. The CVTs and the PIP/FALANT standards were not significantly different in number of personnel selected, but CAD and CCT passed significantly more individuals than WCCVT (P = .011 and P = .004, respectively). The previous U.S. Air Force standard (CCT score ≥75%) passed significantly fewer individuals relative the U.S. Navy pre-2017 PIP/FALANT or the current CVT standards (P ≤ .001). Furthermore, for those who failed the PIP (<12/14), the FALANT (9/9 or ≥16/18) agreed with the CVTs on passing the same CVN (n = 5); however, it also passed moderate-to-severe CVD who did not pass WCCVT (n = 6), CCT (n = 3), and CAD (n = 1). Lastly, moderate/severe CVD were significantly slower and less accurate than the “mild” CVD or CVN in the two color discrimination tasks (P < .001). In comparison to CVN in the in-cockpit display color discrimination task, mild CVD (CCT ≥55% and <75%) were significantly slower by 1,424 ± 290 milliseconds in reaction time (P < .001) while maintaining accuracy. Conclusions CVTs are superior to paper-based PIP in diagnosing, classifying, and grading CVD. Relative to the PIP/FALANT standard in personnel selection, the current U.S. military CVT passing criteria offer comparable passing rates but are more accurate in selecting mild CVD. Nevertheless, military commanders should also consider specific operational requirements in selecting mild CVD for duty as reduced job performance may occur in a complex color critical environment.

Funder

Bureau of Medicine and Surgery

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health,General Medicine

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