4.5 Article

Initial Cognitive Performance Predicts Longitudinal Aviator Performance

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/geronb/gbr031

关键词

Age; Aviation expertise; Cognitive performance; Executive function; Flight simulator performance; Processing speed

资金

  1. Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development
  2. National Institute on Aging at the National Institutes of Health [R37 AG12713]
  3. Office of Academic Affiliations, Department of Veteran Affairs
  4. Medical Research Service of the Veterans Affairs Palo Alto Health Care System
  5. Department of Veterans Affairs Sierra-Pacific Mental Illness Research, Education, and Clinical Center

向作者/读者索取更多资源

Objectives. The goal of the study was to improve prediction of longitudinal flight simulator performance by studying cognitive factors that may moderate the influence of chronological age. Method. We examined age-related change in aviation performance in aircraft pilots in relation to baseline cognitive ability measures and aviation expertise. Participants were aircraft pilots (N = 276) aged 40-77.9. Flight simulator performance and cognition were tested yearly; there were an average of 4.3 (+/- 2.7; range 1-13) data points per participant. Each participant was classified into one of the three levels of aviation expertise based on Federal Aviation Administration pilot proficiency ratings: least, moderate, or high expertise. Results. Addition of measures of cognitive processing speed and executive function to a model of age-related change in aviation performance significantly improved the model. Processing speed and executive function performance interacted such that the slowest rate of decline in flight simulator performance was found in aviators with the highest scores on tests of these abilities. Expertise was beneficial to pilots across the age range studied; however, expertise did not show evidence of reducing the effect of age. Discussion. These data suggest that longitudinal performance on an important real-world activity can be predicted by initial assessment of relevant cognitive abilities.

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