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

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.

Adaptive vocational interest diagnostic: Informing and improving the job assignment process.

The history of vocational interests shows that these measures have great promise for use in job assignment, suggesting that individuals will be more satisfied and successful in their job when they are doing work that interests them. Recent research has provided empirical support for these predictions and demonstrated that the match between an individual's interests and his or her work activities is positively related to job performance and negatively related to attrition. Building on these positive empirical findings, the U.S. Army Research Institute is investigating vocational interest measures for personnel job assignment. Person-job fit is very important in a context such as the U.S. Army, where applicants have over 140 military occupational specialties from which to choose. This paper begins by reviewing evidence for the validity of interests and discussing how vocational interest measures may be used for assigning Soldiers in a military context followed by our recent research to develop a new measure of vocational interests to improve the process of matching Soldiers to military occupational specialties. We will conclude with the next steps for this research and potential paths of implementation.