OBJECTIVES: We report on the relationship between CogScreen-Aeromedical Edition (AE) factor scores and flight simulator performance in aircraft pilots aged 50-69. METHODS: Some 100 licensed, civilian aviators (average age 58+/-5.3 yr) performed aviation tasks in a Frasca model 141 flight simulator and the CogScreen-AE battery. The aviation performance indices were: a) staying on course; b) dialing in communication frequencies; c) avoiding conflicting traffic; d) monitoring cockpit instruments; e) executing the approach; and f) a summary score, which was the mean of these scores. The CogScreen predictors were based on a factor structure reported by Kay (11), which comprised 28 CogScreen scores. Through principal components analysis of Kay's nine factors, we reduced the number of predictors to five composite CogScreen scores: Speed/Working Memory (WM), Visual Associative Memory, Motor Coordination, Tracking, and Attribute Identification. RESULTS: Speed/WM scores had the highest correlation with the flight summary score, Spearman r(rho) = 0.57. A stepwise-forward multiple regression analysis indicated that four CogScreen variables could explain 45% of the variance in flight summary scores. Significant predictors, in order of entry, were: Speed/WM, Visual Associative Memory, Motor Coordination, and Tracking (p<0.05). Pilot age was found to significantly improve prediction beyond that which could be predicted by the four cognitive variables. In addition, there was some evidence for specific ability relationships between certain flight component scores and CogScreen scores, such as approach performance and tracking errors. CONCLUSIONS: These data support the validity of CogScreen-AE as a cognitive battery that taps skills relevant to piloting.
OBJECTIVES: We report on the relationship between CogScreen-Aeromedical Edition (AE) factor scores and flight simulator performance in aircraft pilots aged 50-69. METHODS: Some 100 licensed, civilian aviators (average age 58+/-5.3 yr) performed aviation tasks in a Frasca model 141 flight simulator and the CogScreen-AE battery. The aviation performance indices were: a) staying on course; b) dialing in communication frequencies; c) avoiding conflicting traffic; d) monitoring cockpit instruments; e) executing the approach; and f) a summary score, which was the mean of these scores. The CogScreen predictors were based on a factor structure reported by Kay (11), which comprised 28 CogScreen scores. Through principal components analysis of Kay's nine factors, we reduced the number of predictors to five composite CogScreen scores: Speed/Working Memory (WM), Visual Associative Memory, Motor Coordination, Tracking, and Attribute Identification. RESULTS: Speed/WM scores had the highest correlation with the flight summary score, Spearman r(rho) = 0.57. A stepwise-forward multiple regression analysis indicated that four CogScreen variables could explain 45% of the variance in flight summary scores. Significant predictors, in order of entry, were: Speed/WM, Visual Associative Memory, Motor Coordination, and Tracking (p<0.05). Pilot age was found to significantly improve prediction beyond that which could be predicted by the four cognitive variables. In addition, there was some evidence for specific ability relationships between certain flight component scores and CogScreen scores, such as approach performance and tracking errors. CONCLUSIONS: These data support the validity of CogScreen-AE as a cognitive battery that taps skills relevant to piloting.
Authors: Joy L Taylor; Quinn Kennedy; Maheen M Adamson; Laura C Lazzeroni; Art Noda; Greer M Murphy; Jerome A Yesavage Journal: Psychol Aging Date: 2011-06
Authors: Jerome A Yesavage; Booil Jo; Maheen M Adamson; Quinn Kennedy; Art Noda; Beatriz Hernandez; Jamie M Zeitzer; Leah F Friedman; Kaci Fairchild; Blake K Scanlon; Greer M Murphy; Joy L Taylor Journal: J Gerontol B Psychol Sci Soc Sci Date: 2011-05-17 Impact factor: 4.077
Authors: Maheen M Adamson; Viktoriya Samarina; Xu Xiangyan; Virginia Huynh; Quinn Kennedy; Michael Weiner; Jerome Yesavage; Joy L Taylor Journal: J Int Neuropsychol Soc Date: 2010-03-02 Impact factor: 2.892