{'fraction_non_alphanumeric': 0.0389413988657845, 'fraction_numerical': 0.023818525519848772, 'mean_word_length': 5.631578947368421, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Analysis of Commute Times and Neurobehavioral Performance Capacity in Aviation Cabin Crew

Fatigue-induced impairments in neurobehavioral performance capacity may compromise safety in 24-hr operational environments, and a potential contributing factor of special interest in commercial aviation is the influence of commute times prior to reporting for duty. However, no systematic field data exist regarding actual commute times in commercial aviation or the relationship between commute times and objective neurobehavioral performance capacity. To address these issues, the present study analyzed data from 807 one-way commute episodes and corresponding performances on standardized 5-min Psychomotor Vigilance Test (PVT) sessions by 160 active cabin crew from the 2009-2010 US Civil Aerospace Medical Institute-sponsored Flight Attendant Field Study (Roma et al., 2010). All eligible pre-work commute events were categorized as commutes originating from home at the start of a work trip (“Home,” n=444) or commutes while away on a work trip (“Trip,” n=363). Commute times from home were more widely distributed and positively skewed than commute times during a trip, and a univariate Analysis of Covariance (ANCOVA) controlling for reserve status, gender, and age confirmed that Home commutes were significantly longer than Trip commutes (mean±SEM: 81±3 vs. 31±3 min, p 120 min; Trip: 90 min) and utilized separate ANCOVAs as above to evaluate the relationships between commute times and mean performances of various PVT metrics. In addition, they assessed the relationship between commute times and mean predicted effectiveness scores rendered by the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE™) model, which accounted for sleep history and circadian factors based on each participant’s actual sleep/wake/location patterns receding each commute/PVT pairing. Analysis of Home commutes revealed no significant relationships between commute times and PVT reaction times, speed, lapses, false starts, or “effectiveness” (speed as % of individual baseline; F(4,436)s .20), although a trend in SAFTE predicted effectiveness (F(4,436)=2.36, p=.052) suggested a potential “recovery” effect of sleep obtained during commutes >120 min. Analysis of Trip commutes revealed no significant relationships between commute times and PVT reaction times, speed, lapses, false starts, effectiveness, or SAFTE predicted effectiveness (F(3,356)s .30). The apparent lack of effects on neurobehavioral performance capacity at the start of and during trips reveals the limited value of commute times per se as a significant predictor of fitness for duty.