TY - JOUR
T1 - Are long-haul truck drivers unusually alert? A comparison with long-haul airline pilots
AU - Sallinen, Mikael
AU - Pylkkönen, Mia
AU - Puttonen, Sampsa
AU - Sihvola, Maria
AU - Åkerstedt, Torbjörn
N1 - Funding Information:
We would like to thank all participants, the collaborating transport companies as well as the data managing, medical, and nursing personnel of the Finnish Institute of Occupational Health for their valuable contribution to this study. The study was funded by the Finnish Work Environment Fund grant no. 109378 , the SalWe Research program for Mind and Body by Business Finland , Finnair, Nordic Programme on Health and Welfare grant no. 74809 , and the Finnish Institute of Occupational Health .
Publisher Copyright:
© 2020
PY - 2020/3
Y1 - 2020/3
N2 - Background: Recent studies suggest heavy vehicle drivers self-estimate their sleepiness unexpectedly low during night duties. The present study compared sleepiness ratings of long-haul truck drivers with those of long-haul airline pilots during night and non-night duties. In addition, the correspondence between self-rated manifest and predicted latent sleepiness was examined in the two groups. Methods: Twenty-two drivers and 33 pilots participated. Their working hours, sleep, on-duty sleepiness, and use of sleepiness countermeasures were measured in naturalistic conditions. Predictions of latent sleepiness were based on the measurements of working hours and sleep using the Sleep/Wake Predictor modelling tool. Results: Drivers rated lower levels of sleepiness than pilots during both duty types, though predicted latent sleepiness levels were very similar among the two groups. Neither the results of sleep nor those of sleepiness countermeasures explained the difference in self-rated sleepiness. Discussion: The results raise the possibility that long-haul truck drivers are actually sleepier than they report, and thus are at an increased risk for not responding to sleepiness in a timely manner. A potential explanation for this behavior is lack of education and training on sleepiness among truck drivers as compared with airline pilots. Alternatively, long-haul truck drivers may be exceptionally tolerant to soporific working conditions. The first reported results do not, however, support this hypothesis.
AB - Background: Recent studies suggest heavy vehicle drivers self-estimate their sleepiness unexpectedly low during night duties. The present study compared sleepiness ratings of long-haul truck drivers with those of long-haul airline pilots during night and non-night duties. In addition, the correspondence between self-rated manifest and predicted latent sleepiness was examined in the two groups. Methods: Twenty-two drivers and 33 pilots participated. Their working hours, sleep, on-duty sleepiness, and use of sleepiness countermeasures were measured in naturalistic conditions. Predictions of latent sleepiness were based on the measurements of working hours and sleep using the Sleep/Wake Predictor modelling tool. Results: Drivers rated lower levels of sleepiness than pilots during both duty types, though predicted latent sleepiness levels were very similar among the two groups. Neither the results of sleep nor those of sleepiness countermeasures explained the difference in self-rated sleepiness. Discussion: The results raise the possibility that long-haul truck drivers are actually sleepier than they report, and thus are at an increased risk for not responding to sleepiness in a timely manner. A potential explanation for this behavior is lack of education and training on sleepiness among truck drivers as compared with airline pilots. Alternatively, long-haul truck drivers may be exceptionally tolerant to soporific working conditions. The first reported results do not, however, support this hypothesis.
KW - Commercial aviation
KW - Professional drivers
KW - Road transportation
KW - Sleepiness
KW - Working hours
U2 - 10.1016/j.aap.2020.105442
DO - 10.1016/j.aap.2020.105442
M3 - Article
C2 - 32007780
AN - SCOPUS:85078519650
SN - 0001-4575
VL - 137
JO - Accident Analysis and Prevention
JF - Accident Analysis and Prevention
M1 - 105442
ER -