Pilot age and error in air taxi crashes.
BACKGROUND
The associations of pilot error with the type of flight operations and basic weather conditions are well documented. The correlation between pilot characteristics and error is less clear. This study aims to examine whether pilot age is associated with the prevalence and patterns of pilot error in air taxi crashes.


METHODS
Investigation reports from the National Transportation Safety Board for crashes involving non-scheduled Part 135 operations (i.e., air taxis) in the United States between 1983 and 2002 were reviewed to identify pilot error and other contributing factors. Crash circumstances and the presence and type of pilot error were analyzed in relation to pilot age using Chi-square tests.


RESULTS
Of the 1751 air taxi crashes studied, 28% resulted from mechanical failure, 25% from loss of control at landing or takeoff, 7% from visual flight rule conditions into instrument meteorological conditions, 7% from fuel starvation, 5% from taxiing, and 28% from other causes. Crashes among older pilots were more likely to occur during the daytime rather than at night and off airport than on airport. The patterns of pilot error in air taxi crashes were similar across age groups. Of the errors identified, 27% were flawed decisions, 26% were inattentiveness, 23% mishandled aircraft kinetics, 15% mishandled wind and/or runway conditions, and 11% were others.


CONCLUSIONS
Pilot age is associated with crash circumstances but not with the prevalence and patterns of pilot error in air taxi crashes. Lack of age-related differences in pilot error may be attributable to the "safe worker effect."
Rebok
George W
GW
Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205-1901, USA. grebok@jhsph.edu
Qiang
Yandong
Y
Baker
Susan P
SP
Li
Guohua
G
D000060:Accidents, Aviation / Q000523:psychology / Q000706:statistics & numerical data*; D000062:Accidents, Occupational / Q000523:psychology / Q000706:statistics & numerical data*; D000328:Adult; D000367:Age Factors; D000375:Aging / Q000523:psychology*; D005260:Female; D006304:Health Status; D006801:Humans; D008297:Male; D008396:Maryland / Q000453:epidemiology; D008875:Middle Aged; D015995:Prevalence; D012307:Risk Factors