Attention Control Measures Improve the Prediction of Performance in Navy Trainees

We present a theoretical framework and empirical data from a sample of 490 U.S. Navy trainees (air traffic controllers, student naval aviators, and student naval flight officers) exploring the use of attention control tests in personnel selection. Current military selection tests leave room for improvement when predicting individual differences in work-relevant outcomes and reducing adverse impact. We tested whether measures of attention control, working memory capacity, and fluid intelligence improved the prediction of training success above and beyond composite scores currently used by the U.S. Military. For air traffic controllers in training, commonality analyses revealed that attention control explained 9.1% of the unique variance in academic performance, whereas the Armed Forces Qualification Test explained 5.2% of the unique variance. For student naval aviators, incremental validity estimates were generally small and non-significant. For student naval flight officers, commonality analyses revealed that attention control measures explained 11.8% of the unique variance in aviation preflight indoctrination training performance and 4.3% of the unique variance in flight performance. Although these point estimates are based on relatively small samples, they provide preliminary evidence that attention control measures might improve training outcome classification accuracy in real-world samples of military personnel.