Managing Aviator Fatigue in a Deployed Environment: The

MILITARY MEDICINE, 174, 4:358, 2009

Managing Aviator Fatigue in a Deployed Environment: The Relationship Between Fatigue and Neurocognitive Functioning CPT Yaron G. Rabinowitz, MS USA*; MAJ Jill E. Breitbach, MS USA†; MAJ Christopher H. Warner, MC USA‡

INTRODUCTION Advances in modern warfare have resulted in military operational tempos that are increasingly rapid and unrelenting.1 Commanders and front line soldiers are required to synthesize vast amounts of information and to subsequently use that information to make critical battlefield decisions. The capacity of individuals to make accurate, split-second judgments will often have life-and-death consequences.2 This is particularly true during aviation missions, which often occur during the darkness of early morning hours, when visibility is low and aircrews are most susceptible to the effects of fatigue. Moreover, the complexities of the modern cockpit require pilots to negotiate multiple sources of complex visual and auditory information, placing a premium on information processing and multitasking capability. To ensure operational success and safety, factors which may impair cognitive performance, such as fatigue and sleep disruption, must be identified and mitigated. Sleep loss, whether because of poor sleep quality, restricted sleep opportunities, or prolonged sleep deprivation, has been linked with significant decrements in cognitive functioning3 to include cognitive slowing, increased attention lapses, memory impairment, decreased vigilance, and reduced capacity for *Department of Psychology, Texas A&M University, Corpus Christi, TX 78412. †Neuropsychology Fellow, Department of Psychology, Tripler Army Medical Center, Honolulu, HI 96859-5000. ‡Division Psychiatrist, 3rd Infantry Division, Fort Stewart, GA 31314. The views expressed in this manuscript are those of the authors and do not reflect the official policy of the Department of the Army, the Department of Defense, or the U.S. Government. This manuscript was received for review in April 2008. The revised manuscript was accepted for publication in July 2008.


sustained attention.4 It has been hypothesized that the brain regions involved in higher order complex mental operations (i.e., prefrontal cortex), and thus most critical to aviators, are those most affected by prolonged sleep deprivation, and those that have the greatest need for sleep-mediated recuperation.5 Aviators and aviation crews are at a profound risk for sleep deprivation and disturbance given the nature and requirements of their work. A recent study of U.S. Army aircrew suggests that most report significant fatigue and inadequate amounts of sleep per night.6 To support the pace of military aviation operations, aircrews often work on rotating shifts.6 Unfortunately, shift work can lead to circadian descynchrony which can have deleterious effects on functioning and performance.7 Although the circadian system can adapt to changes in sleep/wake schedule, individuals do not generally adapt fully to shift work. This may be attributable to a tendency to revert to a nighttime/sleep– daytime/wake schedule during their days off which effectively reverses any adaptation that may have previously occurred.8 Although the relationship between fatigue and performance in the aviation community is well documented, most studies on the subject have been conducted in a nondeployed environment, limiting their applicability to modern combat operations. Additionally, although some studies have examined the relationship between the fatigue and standardized neurocognitive functioning assessment tools,9,10 no studies have explored the relationship between the predicted effectiveness of pilots using the Fatigue Avoidance Scheduling Tool (FAST) and the standardized neurocognitive functioning assessment tool SynWin. This relationship is a worthy target of study given the measures’ potential for adaptation as screening and safety mechanisms in aviation units and organizations. Moreover, the use of actigraphy and the FAST software provides a more

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ABSTRACT The current military battlefield requires aviators to make split-second decisions that often have life-anddeath consequences, making identifying predictors of diminished cognitive performance a vital aeromedical and safety concern. The current study explored the relationship between aviator effectiveness, as determined by sleep–wake patterns, and neurocognitive functioning in a brigade-size rotary wing aviation element deployed in Iraq. Actigraphy and the Fatigue Avoidance Scheduling Tool (FAST) were used to assess the ratio of sleep–wake patterns over a 24-hour time period, and a computerized multitasking measure, which mimics the task demands of flying, was utilized to evaluate neurocognitive functioning during preflight operations. Results showed a significant positive association between level of effectiveness and neurocognitive functioning before flight operations. The reported sleep habits and trends in types of sleep difficulties are noted. The results speak to the potential efficacy of using actigraphy and software to evaluate a pilot’s effectiveness before flight operations, and suggest that flight surgeons and psychologists may be able to play a vital role in improving overall sleep patterns and enhancing the warfighting efforts of aviators in combat. They also suggest that mandated crew rest and evaluation of total reported sleep time may not be sufficient to ensure optimum performance levels.

Aviator Fatigue And Cognitive Functioning

comprehensive and thorough picture of fatigue levels and actual effectiveness than can be achieved by self-report measures. The current study explored the relationship between a pilot’s level of effectiveness, determined by sleep–wake patterns and predicted fatigue levels, and neurocognitive functioning in military rotary wing aviators in a combat setting.

The sleep history questionnaire was composed of 19 items developed for the purposes of the current study. It asked participants about sleep quality, quantity, preferences, and correlates. Most items were dichotomous ( yes or no), however some items were continuous (e.g., “How many caffeinated beverages do you consume in a day?”).



Measures Demographics and Sleep History Questionnaire

Upon entry into the study, all participants were asked to complete demographics and sleep history questionnaires. Basic demographic data were collected (e.g., sex, age, education).

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The actigraph is a wrist-worn device, similar to a wrist watch, which objectively estimates sleep quantity and quality by measuring wrist movements. An actigraph consists of an accelerometer as well as a filter, which filters out everything except the 2- to 3-Hz band, thereby ensuring external vibrations are ignored. From wrist movements, the actigraph makes a determination of whether the participant is asleep or awake. Sleep and wake information can then be used to predict overall level of effectiveness. Fatigue Avoidance Scheduling Tool (FAST)

FAST is a fatigue forecasting system developed for the U.S. Army and Air Force with the support of the Department of Transportation.11 Fatigue predictions are derived from the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) model.12 The FAST scheduling tool was utilized to ascertain level of pilot effectiveness at the time of SynWin administration on the basis of data obtained via actigraphy (over a 24-hour period before SynWin administration) regarding the sleep/wake ration of pilots. SynWin

SynWin,13 has been demonstrated to have good reliability coefficients (0.67–0.89) between repeated administrations using composite score for reliability comparisons.13 SynWin consists of a simultaneous computerized representation of four screens that must be manipulated in some manner to receive a positive score. The first screen requires the subject to memorize six random letters from the alphabet, which are presented for 5-second intervals. After a 5-second delay a letter, known as the “probe letter,” is presented requiring the subject to confirm whether it was one of the initial six letters. A second box consists of a fuel management gauge; the subject must constantly right click on the fuel icon to keep the needle in the green area. The subject loses points if the needle goes into the red region or is pointing to zero. The third box is a math problem that must be completed during the test. Once the subject completes the problem, he must right click the “Done” button. If the problem is completed correctly, the subject receives a positive score; if the subject completes the problem incorrectly, he or she loses points. Math problems continue to regenerate until the test is complete. The final box plays an aural tone while the subject negotiates the three other boxes. Although a constant beep is played every 3 to 4 seconds throughout the entire test, the “ALERT” button must be right clicked when the subject hears a tone that is higher than the normal established tone. Results for each test and each session


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Procedures This study is a retrospective analysis of findings from 63 aviators assigned to a brigade-size rotary wing aviation element. The aviators were identified by Command for monitoring of sleep and neurocognitive status given their high flight hours in a combat theater of operations. This program involved a periodic assessment of sleep history and cognitive performance. Aviators’ sleep–wake patterns were monitored via actigraphy, and individual effectiveness was predicted utilizing the Fatigue Avoidance Scheduling Tool (FAST),11 derived from a validated mathematical model called the Sleep, Activity, Fatigue, and Task Effectiveness model (SAFTE).12 Neurocognitive functioning was assessed using SynWin,13 which was designed to evaluate simultaneous multitasking of visual memory, complex information processing, visual monitoring, and auditory attention. Overall level of effectiveness at time of cognitive test administration (operationalized as FAST scores), was hypothesized to be predictive of neurocognitive functioning (operationalized as SynWin scores). Data were analyzed in theater by the brigade flight surgeon, who provided feedback to Command. Participants were given an informational briefing where they were advised of the nature of the program. Each participant then completed the Demographics and Sleep History Questionnaire, and was provided with an actigraph watch designed to measure sleep/wake data. Participants were required to wear the actigraph watch continuously for the duration of the study. At the informational briefing, participants were given one familiarization trial to orient to the novel nature of the SynWin task (coded as time 1). All subsequent trials were considered to be reflective of neurocognitive functioning and were administered during preflight operations. SynWin was administered in a secure environment in all trials, each with a 5-minute run time. Actigraphy data for the previous 24-hour period were downloaded at the time of SynWin testing (for trials other than the familiarization trial), and the FAST algorithm was run on the data to determine effectiveness scores. Testing of subjects was monitored by an aeromedically trained psychologist, and test data were consolidated into an SPSS database.

Aviator Fatigue And Cognitive Functioning

are automatically written to a file, identified by the session number and user ID code.

RESULTS To determine sample characteristics, means and standard deviations were calculated for continuous study variables, and frequencies and percentages were calculated for dichotomous and categorical study variables (Table I). The sample consisted primarily of men (62 of 63 participants were men) who TABLE I.

Descriptive Characteristics of Study Variables

Variable Age Years in School Self Report of Sleep (hrs/night) No. Problem Sleep Behaviors/night Self Report of No. Naps/Week FAST Effectiveness Score Composite SYNWIN Score Gender Male Female Daytime Sleepiness Doing Shift Work Trouble Falling Asleep Trouble Staying Asleep Nicotine User Ever Taken Sleep Aids? >2 Caffeinated Drinks Per Day




32.39 14.71 7.02 1.38 0.80 94.36 455.22

6.03 2.01 1.41 1.31 1.38 7.64 183.14



62.00 1.00 11.00 48.00 40.00 31.00 27 16 33

98.40 1.60 17.20 75.00 62.50 48.40 43.5 25.8 53.9

DISCUSSION The Fatigue Avoidance Scheduling Tool (FAST) has been used previously to ascertain levels of effectiveness based on sleep–wake data derived via actigraphy. However, no studies to date have examined the relationship between FAST scores and a computerized measure of neurocognitive functioning in a deployed combat environment. In the current study, it was hypothesized that level of pilot effectiveness (FAST scores) would be positively associated with an aviator’s neurocognitive functioning just before combat flight operations. The intent TABLE II.

Time 2 FAST Score Regressed on Time 2 SynWin Composite Score

Independent Variable Familiarization SynWin Score Time 2 FAST Score





0.10 7.18

0.28 0.32

0.04 2.76

2.29* 2.61*

Note: *p < 0.05; B, unstandardized coefficient; SE, standard error.

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Analytic Plan Preliminary data screening was conducted to assess for the presence of missing values, outliers, and to test for normality. Only one case was observed to have missing SynWin values. Scatterplots were used to detect univariate outliers, and no cases were identified. The distribution of data was inspected to assess for normality. Skewness statistics were calculated and converted to z-scores by dividing the skewness statistic by its standard error. Variables whose z-scores had absolute values greater than “2.0” were considered to be nonnormally distributed. The FAST scores were observed to be negatively skewed and were transformed using square root transformation with reflection. To preserve the original directionality of the variable, the transformed variable was multiplied by “−1.” The a priori hypothesis was tested using linear regression analysis. The FAST scores served as the independent variable and time 2 SynWin composite score was the dependent variable (time 1 was the familiarization trial). Time 1 SynWin composite scores were entered into the regression equation as a covariate to control for time 1 performance variability. To minimize problems associated with multicollinearity in regression analysis, the independent variable and covariate were centered at the mean (by subtracting the grand mean from individual scores on each variable).

were in their early thirties (the average age of the sample was 32 years) and who had some college education (the average education was just under 15 years). Although most participants reported sleeping at least 7 hours per night, 62.5% of the sample reported difficulties falling asleep, 48% reported difficulties staying asleep, 17.5% reported daytime sleepiness to be a problem, and 53.9% of the sample drank more than 3 or more caffeinated beverages per day. The participants who had 2 or more caffeinated beverages per day comprised 78.1%. Moreover, the average sleeprelated problems reported was 1.38 per night, and 75% of the sample was involved in shift work. Of participants who reported either difficulty initiating or maintaining sleep, a significant number reported difficulty with both (n = 24 out of 63, 38%), and a high correlation existed between the two groups (r = 0.36, p < 0.01). The data suggest that there may be a high-risk subgroup of individuals with multiple sleep problems, for whom intervention is most appropriate. There were minimal differences in reported sleep across individuals with sleep problems and those without. There were also minimal differences across type of sleep disturbance or problem. For instance, pilots who had difficulty falling asleep but had no difficulties sustaining sleep reported 6.6 hours of sleep per night whereas pilots who reported experiencing no difficulties in either initiating or maintaining sleep reported 7.06 hours. Likewise, pilots who reported having difficulty initiating sleep, but reported no difficulty maintaining sleep, reported 6.67 hours per night and pilots who had both initiation and maintenance difficulties reported 7.3 hours per night. The a priori hypothesis posited that FAST scores at the time of SynWin administration would be significantly associated with SynWin composite scores when controlling for the practice effects of the familiarization trial. The findings confirmed these hypotheses as FAST scores significantly predicted SynWin composite scores (t = 2.61, p < 0.05). Results from the regression analysis can be found in Table II.

Aviator Fatigue And Cognitive Functioning

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of flying, suggesting that there may be a convergence between SynWin scores and an aviator’s potential flight performance. Thus, the observed relationship between FAST scores and SynWin scores indicate that actigraphy and data analysis with FAST software may be a viable tool for aviation units to employ so that true effectiveness determinations can be made before flight operations. Alternatively, SynWin may hold promise in aviation selection programs. SynWin may not only identify individuals whose neurocognitive functioning may be temporarily impaired because of sleep restriction or deprivation, but those who possess an inherent aptitude for the task demands of flying. This would afford psychologists and other medical professionals involved in selection programs greater insight into pilot trainability and suitability than current paper-and-pencil tests, which typically explore only IQ factors and personality characteristics. Given the current findings, it would be helpful to determine points after which pilot effectiveness is compromised to such an extent that the risks of undertaking the mission outweigh foreseeable benefits. SynWin, and other automated neurocognitive measures, have the potential to be used as indicators of cognitive status once an aviator’s baseline cognitive functioning has been measured (presumably during selection programs, at the start of an aviator’s career). For instance, if an aviator is experiencing fatigue or sleep deprivation, SynWin may help determine if the aviator is safe to fly by ascertaining the degree to which neurocognitive functioning is temporarily compromised by using the baseline score as a comparative criterion. Furthermore, following injury, baseline measures of neurocognitive functioning may prove more valuable than normative scores derived postinjury, which only allow for inferences to be made about changes in cognitive functioning. The current findings need to be interpreted in light of certain study limitations. First, the sample itself limits generalizabilty to other populations. The sample was a convenience sample of primarily male, rotary wing aviators from the Army. Whether the findings apply to female aviators, fixed wing aviators, aviators from other military branches, and civilian aviators, remains to be seen. It is possible that the additional information processing in combat environments and sustained military operations may place a greater premium on divided attention than would be found in other settings. Further, the study was cross-sectional in nature. Longitudinal studies should be developed to validate whether the relationship between FAST scores and cognitive performance observed in the current study are maintained across time and in replication studies. Future studies should endeavor to elucidate the complex relationship between FAST scores and cognitive performance as a means of understanding when an aviator is too compromised to fly safely. Finally, other indicators of flight performance, such as check-ride performance, self-evaluations of performance, and mission success should be incorporated into future studies with the FAST software. The current findings provide insight into the complex dynamics of aviator fatigue and effectiveness and speak to the importance of instituting pilot safety precautions which


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was to elucidate the relationship between a pilot’s level of effectiveness, on the basis of actual sleep data, collected by actigraphy (rather than self-report) and analyzed via validated software, and cognitive performance. The overarching goal was to explore the potential benefits of utilizing FAST software as a tool to enhance aviation safety in deployed environments. This study is particularly important when viewed in the context of the extreme cognitive demands inherent in military aviation and the high likelihood for fatigue inherent on both shift work and modern combat operations. The findings demonstrate that an aviator’s cognitive functioning, and, by extension, capacity to successfully negotiate the task demands of flying, are significantly associated with a pilot’s alertness/effectiveness before flight operations. Although this finding is not unanticipated, the implication is that a pilot’s cockpit performance may be markedly compromised when a pilot is fatigued (and effectiveness is low). This, in turn, is likely to result in an increased likelihood for pilot mishaps. The findings also suggest that in aviation units, fatigue, and its negative sequelae, may be a pervasive problem not necessarily identifiable by examining quantity of sleep alone. Indeed, the mean hours of sleep reported by the pilots belies the fact that the assessed aviators reported a myriad of sleep difficulties and disturbances. For instance, a significant portion reported daytime sleepiness and relied upon caffeinated beverages to stay awake. In addition, most pilots in the study reported difficulty either falling asleep or staying asleep, with a significant proportion experiencing both. The subsample with difficulties both initiating and maintaining sleep may be at particularly high risk for fatigue-related problems and may warrant targeted intervention. Possible interventions include work/rest plan modifications developed for units in conjunction with the brigade or battalion flight surgeon. For instance, the flight surgeon may provide quantitative data from actigraphy about the actual quantity of sleep, which can help aviators identify methods for improving overall sleep quality and/or enhancing adjustments to rotating work cycles. Also of note was the fact that there were negligible differences in reported sleep duration across subcategories of individuals who reported having trouble initiating or sustaining sleep. Additionally, there were no substantial differences in reported sleep between individuals reporting sleep problems and those who did not. Thus, efforts to track sleep or mandate crew down time may not be sufficient to mitigate potential safety risks associated with pilot fatigue. Programs designed to minimize the impact of fatigue on pilot performance and safety should consider using multiple levels of intervention and assessment. A prudent risk management program for aviation units may include integrating tools for quantitatively measuring alertness/effectiveness into Fighter Management programs and preflight operations. FAST may enable commanders to evaluate pilots’ readiness with greater precision and ease, thereby facilitating more sound and accurate safety decisions. The measure of neurocognitive functioning utilized in the present study (SynWin) closely resembles the actual demands

Aviator Fatigue And Cognitive Functioning

go beyond merely evaluating sleep duration or down time. The findings also highlight the potential efficacy of the FAST program as a measure of pilot effectiveness in a deployed environment. The ease of use of both FAST and SynWin, demonstrated by their successful and minimally invasive use in the current project, make these viable tools for use in theater and in pilot selection programs. REFERENCES

Chairman of the Board of Managers, Maj Gen Jerry Sanders USAF (Ret.) shown with Maj Gen Bruce Green, Deputy AFSG

Head Table at Annual Dinner

Lt Gen Louis Lillywhite, Surgeon General of the United Kingdom expresses appreciation on behalf of the International Delegates. 362

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1. Richard LS, Huffman AH: The impact of commuter war on military personnel. Milit Med 2002; 167: 602–5. 2. Ramsey CS, Mcglohn SE: Zolpidem as a fatigue countermeasure. Aviat Space Environ Med 1997; 68(10): 926–31. 3. Belenky G, Wesensten NJ, Thorne DR, et al: Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study. J Sleep Res 2003; 12(1): 1–12. 4. Himashree G, Banerjee PK, Selvamurthy W: Sleep and performance: recent trends. Indian J Physiol Pharmacol XXX; 46(1): 6–24. 5. Harrison Y, Horne JA: The impact of sleep deprivation on decision making: a review. J Exp Psychol Appl 2000; 6: 236–49.

6. Caldwell JL, Gilreath SR: Work and sleep hours of U.S. Army aviation personnel working reverse cycle. Milit Med 2001; 166: 159–66. 7. Luna TD: Air traffic controller shiftwork: what are the implications for aviation safety? A review. Aviat Space Environ Med 1997; 68(1): 69–79. 8. Sack RL, Lewy AJ: Melatonin as a chronobiotic: treatment of circadian desynchrony in night shift workers and the blind. J Biol Rhythms 1997; 12: 595–603. 9. Petrilli RM, Roach GD, Dawson D, Lamond N: The sleep, subjective fatigue, and sustained attention of commercial airline pilots during and international pattern. Chronobiol Int 2006; 23(6): 1357–62. 10. Thomas F, Hopkins RO, Handrahan DL, Walker J, Carpenter J: Sleep and cognitive performance of flight nurses after 12-hour evening versus 18-hour shifts. Air Med J 2006; 25(5): 216–25. 11. Hursh SR, Balkin TJ, Miller JC, Eddy DR: The fatigue avoidance scheduling tool: modeling to minimize the effects of fatigue on cognitive performance. SAE Transactions 2004; 113(1): 111–9. 12. Hursh SR, Redmond DP, Johnson ML, et al: Fatigue models for applied research in warfighting. Aviat Space Environ Med 2004; 75(Suppl.): A44–53. 13. Elsmore TF: SYNWORK1: A PC-based tool for assessment of performance in a simulated work environment. Behav Res Methods Instrum Comput 1994; 26: 421–6.


Managing Aviator Fatigue in a Deployed Environment: The

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