No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Psychological Attributes Critical to the Performance of MQ-1 Predator and MQ-9 Reaper U.S. Air Force Sensor Operators
Abstract
Remotely Piloted Aircraft (RPA) operations in Iraq, Afghanistan, and other areas of operation are escalating as the force protection capabilities of such aircraft are fully realized in surveillance, reconnaissance, and precision-strike operations. Never in the history of warfare have uninhabited vehicles assumed such a critical role in such a vast array of theater operations. As a result, the aircrew of RPA aircraft work around the clock to provide support capabilities, flying one of the world's most advanced aerial weapons systems. However, there is minimal research on the assessment and selection of enlisted aircrew (i.e., Sensor Operators, SOs) who fill a critical role. At the present time, there are no published studies on the critical attributes of successful MQ-1 Predator and MQ-9 Reaper SOs. The purpose of this study was to consolidate data from several subject matter experts regarding the attributes needed to successfully complete training and adapt to operational demands. The results of the study aim to increase understanding of specific psychological attributes critical to performance, and to improve aeromedical assessment and selection procedures.
... Within cognitive ability, SMEs perceived that SOs with high levels of the following aptitudes performed well and adapted more readily to the rigors and unique demands of UAS platforms, Cognitive Proficiency, Visual Perception, Attention, Spatial Processing, Memory, and Reasoning. It was perceived that SOs without adequate levels of these aptitudes struggled with timely skills acquisition, task management and prioritization, situational awareness, channelized attention, and general problem solving (Chappelle, McDonald et al., 2010). ...
... With regard to personality traits, the SMEs identified the following non-cognitive capabilities and traits which they perceived affected SO duty performance and adaptation to the unique nature of UAS operations, Composure, Resilience, Self-Certainty, Conscientiousness, Success Orientated, Perseverance, Decisiveness, Humility, Cohesiveness, Assertiveness, and Adaptability (Chappelle, McDonald et al., 2010). ...
... Overall, the personality traits of the UAS Student sample display a high degree of congruency with traits documented among other aviation students and professionals. This tendency to be calm, even-tempered, and relaxed, as well as the ability to face stress without becoming upset is also well aligned with the attributes composure and resilience identified by Chappelle, McDonald, et al. (2010) as traits affecting duty performance and adaptation to the unique nature of UAS operations. ...
... A recent review of US Air Force RPAS job analyses (Paullin et al. 2011) identified 47 SAOCs relevant to RPAS pilot and SO performance. Research reviewed included Mission Essential Competencies (MECs) for Predator, Reaper, and Global Hawk RPAS platforms/missions (Paullin et al. 2011), studies conducted by the USAF School of Aerospace Medicine (Chappelle et al. 2010(Chappelle et al. , 2011, front end analysis of Predator Pilot and SO job requirements Duma 2008a, 2008b;Nagy, Kalita et al. 2006), and results from studies on RPAS operator qualifications (US Air Force 2008) and skill sets (Tvaryanas 2006). The list was further modified based on input from 17 RPAS SMEs and on-site observations of RPAS pilots and SOs, to arrive at a final list of 21 critical SAOCs. ...
... For example, results of job analyses have shown spatial and symbolic reasoning, perceptual and psychomotor abilities, central information processing (e.g. timesharing), situational awareness, and working memory to be essential for sensor operator and RPAS pilot performance (Bailey 2008;Chappelle et al. 2010;Paullin et al. 2011). ...
... Qualification for SO training requires an ASVAB General 6 composite percentile score greater than or equal to 64 or an Electronics composite percentile score greater than or equal to 54. After correction for multivariate range restriction (Lawley, 1943) Although the ASVAB demonstrated an acceptable level of predictive validity for SO training, results of RPAS job/task analyses (Bailey 2008;Crumley and Bailey 1979;Chappelle et al. 2010Chappelle et al. 2011Howse 2011;Paullin et al. 2011) identified several critical SO SAOCs not measured by the ASVAB. These include assertiveness, control precision, perceptual speed, stress tolerance, spatial and symbolic reasoning, situational awareness, timesharing, verbal communication, and working memory. ...
The jobs of Remotely Piloted Aircraft System (RPAS) pilot and that of sensor operator are relatively new in aviation, and viewpoints on who is best suited to fill these positions are evolving. This chapter is organized into eight parts. Part one focuses on why RPAS operator selection is important and the relations between selection, training, and human-system integration. Part two provides an overview of the RPAS operator selection and training process for the US military and civil aviation. Part three introduces the concept of "validity" and the steps involved in conducting personnel selection studies including the role of job/task analysis to identify critical skills, abilities, and other characteristics (SAOCs) and the identification of selection methods and performance criteria. In: part four we review the literature on RPAS job/task analyses and compare RPAS SAOCs to those for other related jobs (e.g., manned aircraft pilot), determine whether there are any unique SAOCs for RPAS operators, and the differences in requirements for RPAS pilots and sensor operators. Part five reviews results of predictive validation studies in military training. Part six speculates about changes in SAOC requirements as the capabilities of RPA systems change with advancements in technology (e.g., increased automation and autonomy, adaptive automation, multiple-RPA control). Part seven examines future trends in the measurement of RPAS operator aptitude. Finally, part eight provides recommendations for researchers and practitioners.
... More recently, research and development efforts have intensified as new technologies have rendered UAVs more practical and effective for several civilian (Coifman, McCord, Mishalani, & Redmill, 2004;Rango et al., 2006) and military applications (Bone & Bolkcom, 2003;Haddal & Gertler, 2010;Haulman, 2003). UAVs offer numerous advantages to military operations, notably force multiplication (Chappelle, McDonald, & King, 2010) and elimination of risk to operator's lives (Gertler, 2012;Stulberg, 2007). Whereas conventional aircraft are limited by the endurance of on-board pilots, UAV operators can work in shifts to support prolonged operations (Barnes & Matz, 1998;. ...
... Whereas conventional aircraft are limited by the endurance of on-board pilots, UAV operators can work in shifts to support prolonged operations (Barnes & Matz, 1998;. This makes them especially useful for intelligence, surveillance, and reconnaissance (ISR) missions (Chappelle et al., 2010;Gertler, 2012;Haulman, 2003). ...
... Reports of UAV operation attest that the infrequency of signals and lack of interaction make it difficult for operators to maintain alertness and predispose them to "hazardous states of awareness" (Pope & Bogart, 1992;Tvaryanas, 2006;. UAV operators working continuous shifts report boredom, and their performance shows significant loss of sustained attention and vigilance, decreased performance accuracy, and slowed response times (Chappelle et al., 2010;Cummings et al., 2013;Ouma et al., 2011;. ...
The objective of this research is to inform the design of dynamic interfaces to optimize unmanned aerial vehicle (UAV) operator reliance on automation. A broad goal of the U.S. military is to improve the ratio of UAV operators to UAVs controlled. Accomplishing this goal requires the use of automation; however, the benefits of automation are jeopardized without appropriate operator reliance. To improve reliance on automation, this effort sought to accomplish several objectives organized into phases. The first phase aimed to validate metrics that could be used to gauge operator fatigue online, to understand how the reliability of automated systems influences subjective and objective responses, and to understand how the impact of automation reliability changes with different levels of fatigue. To that end, this study employed a multiple UAV simulation containing several tasks. Findings for a challenging Image Analysis task indicated a decrease in accuracy and reliance with time. Both accuracy and reliance were lower with an unreliable automated decision making aid (60% reliability) than with a reliable automated decision making aid (86.7% reliability). Further, a significant interaction indicated that reliance diminished more quickly when the automated aid was less reliable. Concerning the identification of possible eye tracking measures for fatigue, metrics for percentage of eye closure (PERCLOS), blinks, fixations, and dwell time registered changes with time on task. Fixation metrics registered reliability differences. The second phase sought to use outcomes from the first phase to build two algorithms, based on eye tracking, to drive continuous diagnostic monitoring, one simple and another complex. These algorithms were intended to diagnose the passive fatigue state of UAV operators and used subjective task engagement as the dependent variable. The simple algorithm used PERCLOS and total dwell time within the automated tasking area. The complex algorithm added percent of cognitive fixations and frequency of express fixations. The complex algorithm successfully predicted task engagement, primarily on the strength of percentage of cognitive fixations and express fixation frequency metrics.
... Recently the Air Force Research Laboratory 711 th Human Performance Wing (Chappelle, McDonald, & King, 2010) conducted a study to identify critical personal attributes relevant to training success and career performance for RPA sensor operators. The authors approached their work through structured interviews conducted in five venues. ...
... Therefore, it becomes difficult to compare these with attributes listed in other works. Table 9 presents 21 attributes identified by Chappelle at al. (2010) for MPO positions, including seven Abilities and 14 Other characteristics. Although the authors reported that Knowledge and Skill attributes had been identified, their screening process eliminated them. ...
... Attribute list fromChappelle et al., 2010. ...
... Other human performance attributes such as psychomotor processing, spatial processing, composure, and perseverance are important to improve the team cohesion through human performance enhancement. Overall personal (physiological, cognitive, and psychological) attributes have been classified into five subdomains after a detailed study by several defense agencies and are summarized in Table II [75][76][77][78]. ...
... For common human metrics, we eliminated all the metrics that are invasive and only subjective to make the measurement practical. In additions to the selection criteria defined above, we focused on measurement methods for human metrics because relating activity measures to human performance is difficult [75][76][77][78]. Our research also agrees with that of several researchers in presenting trust, cognitive load, and human fatigue as important HMT metrics. ...
A significant amount of work is invested in human-machine teaming (HMT) across multiple fields. Accurately and effectively measuring system performance of an HMT is crucial for moving the design of these systems forward. Metrics are the enabling tools to devise a benchmark in any system and serve as an evaluation platform for assessing the performance, along with the verification and validation, of a system. Currently, there is no agreed-upon set of benchmark metrics for developing HMT systems. Therefore, identification and classification of common metrics are imperative to create a benchmark in the HMT field. The key focus of this review is to conduct a detailed survey aimed at identification of metrics employed in different segments of HMT and to determine the common metrics that can be used in the future to benchmark HMTs. We have organized this review as follows: identification of metrics used in HMTs until now, and classification based on functionality and measuring techniques. Additionally, we have also attempted to analyze all the identified metrics in detail while classifying them as theoretical, applied, real-time, non-real-time, measurable, and observable metrics. We conclude this review with a detailed analysis of the identified common metrics along with their usage to benchmark HMTs.
... Traditionally, RPVs employed by the defence force are operated by a three-person crew, including a pilot, a mission intelligence coordinator and a sensor operator (Chappelle, McDonald, & King, 2010). The sensor operator is largely responsible for the search and identification of ground targets using various visual displays, such as camera images of the landscape (Chappelle et al., 2010). ...
... Traditionally, RPVs employed by the defence force are operated by a three-person crew, including a pilot, a mission intelligence coordinator and a sensor operator (Chappelle, McDonald, & King, 2010). The sensor operator is largely responsible for the search and identification of ground targets using various visual displays, such as camera images of the landscape (Chappelle et al., 2010). The performance of the operator is integral to the success of any mission, but especially where a RPV is used to acquire information and/or locate targets such as occurs during search and rescue (Guznov, Matthews, Warm, & Pfahler, 2017). ...
Remotely piloted vehicles or ‘drones’ have become ubiquitous both privately and commercially. One of the numerous applications for drones involves the search and rescue for specified targets. The use of ‘cues’ during target detection has been shown to improve performance and reduce cognitive demands in many environments. This study examined the relationship between cue utilization and level of target detail during a high-fidelity simulated drone search and rescue task. Seventy-six undergraduate students from an Australian University operated a payload (long range camera) to detect a ‘target’ (a bus driver stranded in the Utah desert) while flying on a pre-programmed flight path. The results indicated that the provision of detailed target information was associated with greater rates of target detection. Further, participants with higher cue utilization were more likely to locate the target. Finally, participants with higher cue utilization, and provided with basic target information, were more likely to locate the target than participants with lower cue utilization. The practical and theoretical implications of the outcomes are discussed.
... Other human performance attributes such as psychomotor processing, spatial processing, composure, and perseverance are important to improve the team cohesion through human performance enhancement. Overall personal (physiological, cognitive, and psychological) attributes have been classified into five subdomains after a detailed study by several defense agencies and are summarized in Table II [75][76][77][78]. ...
... For common human metrics, we eliminated all the metrics that are invasive and only subjective to make the measurement practical. In additions to the selection criteria defined above, we focused on measurement methods for human metrics because relating activity measures to human performance is difficult [75][76][77][78]. Our research also agrees with that of several researchers in presenting trust, cognitive load, and human fatigue as important HMT metrics. ...
A significant amount of work is invested in human-machine teaming (HMT) across multiple fields. Accurately and effectively measuring system performance of an HMT is crucial for moving the design of these systems forward. Metrics are the enabling tools to devise a benchmark in any system and serve as an evaluation platform for assessing the performance, along with the verification and validation, of a system. Currently, there is no agreed-upon set of benchmark metrics for developing HMT systems. Therefore, identification and classification of common metrics are imperative to create a benchmark in the HMT field. The key focus of this review is to conduct a detailed survey aimed at identification of metrics employed in different segments of HMT and to determine the common metrics that can be used in the future to benchmark HMTs. We have organized this review as follows: identification of metrics used in HMTs until now, and classification based on functionality and measuring techniques. Additionally, we have also attempted to analyze all the identified metrics in detail while classifying them as theoretical, applied, real-time, non–real-time, measurable, and observable metrics. We conclude this review with a detailed analysis of the identified common metrics along with their usage to benchmark HMTs.
... Examples of abilities associated with SOs include multitasking, spatial processing, and memory [4]. These abilities refer to intellectual mental functions and information processing abilities essential to SO job accomplishment [11]. TABLE I provides an overview of six core cognitive abilities related to SO job performance. ...
... TABLE I provides an overview of six core cognitive abilities related to SO job performance. These include cognitive proficiency, visual perception, attention, spatial processing, memory, and reasoning [4] [11]. ...
In this paper we report on our study of the performance of Deep Reinforcement Learning (DRL) agents in performing tasks that are illustrative for human Sensor Operators (SOs) in Remotely Piloted Aircraft Systems (RPASs). Our hypothesis is that the descriptive and predictive qualities of the agent's learning process potentially allow us to identify human task requirements, training needs, selection criteria and cutoff benchmarks. We present DRL results on tasks that cover different cognitive abilities required for an SO, using games as a method for learning.
... Some US Air Force RPAs have sustainable loiter times greater than 20 hours (Chappelle et al, 2010). Therefore, operational RPA squadrons typically operate multiple shifts to provide the necessary aircrew coverage. ...
... On a larger note, in terms of researching SA with respect to RPA operations, greater emphasis must be placed on the role of the CO. While the pilot, and to a lesser extent the sensor operator roles have received moderate study (see Schneider & McGrogan, 2011;Chappelle et al, 2010;Ouma et al, 2011), little has been done with a focus on the CO position despite its criticality to complex operations. It should be understood that the paradigm stemming from manned aircraft of the pilot having the most critical SA needs does not typically hold in modern egocentric medium and high-altitude RPA operations. ...
... USAF and UK Royal Air Force studies also have found overlap in the entry-level SAOCs required for RPA pilots and SOs (e.g., see Carretta et al., in press;Howse, 2011, for a review). For example, results of job analyses have shown central information processing (e.g., time sharing), perceptual and psychomotor abilities, spatial and symbolic reasoning, situational awareness, and working memory to be essential for RPA pilot and SO performance (Bailey, 2008;Chappelle, McDonald, & King, 2010;Chappelle, McDonald, & McMillan, 2011;Paullin, Ingerick, Trippe, & Wasko, 2011). ...
... Results of UAS/RPA job and task analyses (Bailey, 2008;Crumley & Bailey, 1979;Chappelle et al., 2010;Chapelle et al., 2011;Howse, 2011;Paullin et al., 2011) have identified several critical sensor operator SAOCs not adequately measured by the ASVAB. Critical skills and abilities not measured by the ASVAB include logic, perceptual and psychomotor, spatial and symbolic reasoning, situation awareness, verbal communication, and working memory. ...
U.S. Air Force sensor operators (SOs) are enlisted aviators who work side-by-side with unmanned aerial systems/remotely piloted aircraft (UAS/RPA) pilots, providing assistance with all aspects of aircraft employment and sensor management. SO training qualification includes medical, citizenship, and security standards and aptitude requirements. The current study examined the validity of the Armed Services Vocational Aptitude Battery (ASVAB) for predicting grades of students in three SO courses. The ASVAB composites used for SO training qualification (General and Electronics) demonstrated good predictive validity for all three courses (corrected for range restriction and criterion unreliability): Basic Sensor Operator Course, n = 461, r = .541 and .535; MQ-1 Initial Qualification/Requalification Training, n = 430, r = .583 and .553; MQ-9 Initial Qualification/Requalification Training, n = 249, r = .357 and .334). Although current selection methods are effective, based on results of UAS/RPA job/task analyses, the Air Force is examining the utility of other measures to supplement the ASVAB.
... The NATO doctrine of Continuous Operations (CONOPS) envisages continuous 24-hour combat missions (Krueger 2012). In addition to conventional surveillance activities, the modern warfighter may engage in computer-controlled monitoring tasks associated with the control of missiles (Hawley 2006), remotely piloted vehicles (RPVs; Chappelle, McDonald, and King 2010) and counter-terrorism (Hancock and Hart 2002). Selection of exceptionally vigilant individuals may be important for such tasks. ...
... Short-range prediction is the evaluation of whether the soldier is fit to perform an immediate mission. These include traditional sentry duty (MacBride et al. 2007), extended training sessions (Harris, Hancock, and Harris 2005), detection of improvised explosive devices (IEDs; Szalma et al. 2011) and operation of RPVs (Chappelle, McDonald, and King 2010). Long-range prediction refers to assessing the soldier's general fitness to perform vigilance tasks in relation to periods of months or years (e.g. a tour of duty). ...
Technological innovation increasingly requires operators in various applied settings to maintain vigilance for extended periods. However, standard psychometric tests typically predict less than 10% of performance variance. The present study (N = 462) aimed to apply the resource theory of sustained attention to construct a multivariate test battery for predicting battlefield vigilance. The battery included cognitive ability tests, a high-workload short vigilance task and subjective measures of stress response. Four versions of a 60- min simulated military battlefield monitoring task were constructed to represent different operational requirements. The test battery predicted 24-44% of criterion variance, depending on task version, suggesting that it may identify vigilant operators in military and other applied contexts. A multiple-groups path analysis showed that relationships between ability and vigilance were moderated by working memory demands. Findings are consistent with a diffuse theoretical concept of 'resources' in which performance energisation depends on multiple, loosely coupled processes.
... Значимість цієї ролі пов'язана з тим, що сприйняття, переробка, аналіз та узагальнення інформації та вироблення на цій основі рішення складають саму суть операторської діяльності. Під час управління польоту безпілотного літального апарату (БпЛА) головним джерелом одержання інформації оператором є візуальні та звукові сигнали, що надходять з наземної станції управління БпЛА, проте існує безліч додаткових джерел (телефон, колеги, робоче середовище, погодні явища та ін.), на які може переключатися увага оператора БпАК, в наслідок чого значно підвищується ймовірність виникнення аварій [10,11] та невизначеність ситуацій, дефіцит або великий об'єм інформації, порушення ритму надходження інформації, вплив дефіциту часу, вплив високого темпу роботи, відволікаючі чинники в роботі). Ці питання були сформульовані нами на основі власного досвіду контентаналізу службової діяльності зовнішніх пілотів та вивчення наявних публікацій із зазначених питань. ...
Вступ. В сучасних умовах надмірна кількість інформації може заплутати операторів і ускладнити процес прийняття обґрунтованих рішень, виникнення непередбачених ситуацій і як наслідок аварій. Ці аварії можуть мати серйозні наслідки, включаючи матеріальні збитки, втрату життя та збитки для навколишнього середовища. Тому для забезпечення надійності та ефективності роботи людини важливо, щоб обсяг інформації що надходить знаходився в оптимальних межах. Отже, успішність праці напряму залежить від функціонального стану оператора, його емоційного піднесення, яке, зокрема, регулюється результатом професійної діяльності. Таким чином, дослідження впливу змістовних складових інформаційного навантаження на емоційно забарвлені враження від дії того чи іншого інформаційного фактору має незаперечний пріоритет. Мета. Вивчити вплив факторів інформаційного навантаження на функціональний стан зовнішніх пілотів БпАК І класу «Легкі» в їхньому професійному середовищі. Матеріали та методи. Досліджено 41 військовослужбовців - чоловіків 20-35 років, які мали досвід управління БпАК І класу «Легкі» та залучались до виконання широкого спектру професійних завдань. За спеціально розробленою анкетою, що віддзеркалювала питання щодо інформаційного навантаження зовнішніх пілотів під час їх професійної діяльності, було проведено оцінювання їх впливу за 100 бальною шкалою на функціональний стан. Статистичний аналіз даних було проведено з залученням методів параметричної (t-критерій Стьюдента) статистики, кластерного та факторного аналізу з допомогою пакету програм STATISTICA 13.3. Результати. Обстежений контингент операторів з допомогою кластерного аналізу (метод k-середніх) було розділено на дві більш однорідні групи з кількісним складом 50% на 50% (по 20 осіб в кожній групі). З допомогою покрокового дискримінантного аналізу було отримано рівняння, які складаються з інформативних показників, що високовірогідно сприяють розділенню аналізованих даних на дві групи. Побудовані розв’язувальні правила для віднесення операторів до тієї чи іншої групи. Для проведення подальшого аналізу використовувались тільки ті показники, які надійно ділили досліджуваний контингент на дві групи. З допомогою факторного аналізу (метод головних компонент) для осіб обох груп було виділено приховані фактори, що впливають на формування емоційного стану та показана структура зав’язків цих факторів з компонентами інформаційних впливів. Висновки. Виділено дві групи операторів БпАК більш однорідних за своїми враженнями від дії компонентів інформаційного фактору праці, виконуючи одну і ту ж роботу для першої групи операторів притаманне інформаційне навантаження високого рівня (перевантаження), а для інших – низький рівень навантаження (група 2) та побудовані розв’язувальні правила для визначення приналежності до тієї чи іншої групи. Виділено два прихованих фактори, що впливають на формування емоційного стану операторів БпАК групи 1 (перевантажені), які сумарно пояснюють 54,0% дисперсії вихідних даних. Перший з них – фактор «механізму охоронного гальмування» пояснює (34,9%) і складається з двох компонентів: рівень невизначеності ситуації та рівень дефіциту інформації. Другий прихований фактор «формування адекватного управління» – пояснює 19,1% дисперсії аналізованих даних і формується за рахунок одного компонента. Виділено два прихованих фактори, що впливають на формування емоційного стану операторів БпАК групи 2 (недовантажені), які сумарно пояснюють 55,3% дисперсії вихідних даних. Перший прихований фактор «інформаційного навантаження» сумарно пояснює 36,1% дисперсії і має в своєму складі п’ять компонентів інформаційних впливів. Другий прихований фактор «нерозв'язності завдань» пояснює 19,2% загальної дисперсії вихідних даних і складається тільки з одного компонента.
... Additional support to these findings can be found in a study of over 800 UAV operators [12]. This study highlighted an additional factor challenging the performance of the UAV operators: the need to maintain high levels of visual and auditory alertness for extended periods of time. ...
Background: The exposure to war scenes via screens, despite offering a degree of detachment, can be stressful for
the operator. The aim of the current study is to examine the existence of anxiety, depression, and post traumatic stress
disorder (PTSD) symptoms among unmanned aerial vehicle (UAV) Israeli operators.
Methods: Participants comprised 41 UAV operators (87.2% male), aged 22–38 (Mage = 26.05, SD = 3.54). Most (78.0%)
reported having viewed battlefield scenes. All participants completed a total of five questionnaires: Beck Depression
Inventory, State-Trait Anxiety Inventory, and three questionnaires of PTSD: Post Trauma Questionnaire (CAPS), the Post�Traumatic Cognition Inventory (CTPI), and the Post-Traumatic Symptom Scale (PSS).
Results: Mean scores of depression and anxiety were found significantly lower than diagnosis cut-off points
(p < .001). Senior operators showed higher means for depression (5.69 vs. 2.58, p = .040), of stress level (PSS; 3.17 vs.
0.25, p = .020) and for distress intensity (3.79 vs. 0.57, p = 0.041) than less-experienced operators.
Conclusions: Investigating and monitoring the impact of battlefield exposure in UAV operators are highly beneficial
for preventing psychopathology.
Keywords: UAV, Unmanned aerial vehicle, Anxiety, Depression, Post-traumatic stress disorder, PTSD
... RPA sensor operators are responsible for the manual control of airborne sensors to acquire, track, and monitor enemy assets, combatants, and objects of interest. 3 RPA intelligence operators, who typically work in concert with RPA crews, also play a vital role by providing real-time situational awareness and continuous support to RPA crews and other military efforts in zones of heavy conflict. ...
Introduction
U.S. Air Force remotely piloted aircraft (RPA) operators perform a variety of around-the-clock global intelligence, surveillance, and reconnaissance (ISR) missions that are considered critical to operational effectiveness. The growing need for ISR operations has led to significant increases in operational tempo and workload, resulting in elevated operational stress, burnout, and psychological distress. These negative outcomes are linked to conditions such as long hours, low manning, lack of sleep, and communication issues. Through regular assessments and the implementation of additional resources (i.e., embedded health care providers), Air Force leadership is working to alleviate the stressors and maintain psychological well-being. Thus, the purpose of this study is to compare the levels of stress, and prevalence of burnout and psychological distress across RPA career fields within two major commands.
Materials and Methods
Assessments were completed by 571 RPA operators from 2 major commands: Air Force Special Operations Command (n = 158) and Air Combat Command (n = 413). RPA career fields included pilots (n = 331), sensor operators (n = 137), and intelligence operators (n = 103).
Results
Results revealed that high stress levels from an array of sources continue to result in increased risk of burnout and psychological distress for RPA operators. Several significant differences in sources of high stress across career fields and major commands are identified and discussed.
Conclusions
Overall, the results of this study highlight specific problem areas unique to certain subsets of the RPA community in need of targeted intervention and clarify several avenues for future research.
... 2-3), "The "dull" missions are the ones that require long loiter time and constant surveillance of a target (e.g., days to weeks) too tedious for a crew in a manned aircraft to execute without significant degradations in performance." Conversely, workload demands spike when pilots must handle high volumes of communication from multiple sources, and support combat missions involving intense, unpredictable activity (Chappelle et al., 2010). The vulnerability of operators to fatigue may be exacerbated by occupational factors such as long operational hours and shift work, combined with various stressors ( Current RPVs typically require a small team of operators, including a pilot and sensor operator. ...
The impacts of fatigue on the vehicle driver may change with technological advancements including automation and the increasing prevalence of potentially distracting in-car systems. This article reviews the authors' simulation studies of how fatigue, automation, and distraction may intersect as threats to safety. Distinguishing between states of active and passive fatigue supports understanding of fatigue and the development of countermeasures. Active fatigue is a stress-like state driven by overload of cognitive capabilities. Passive fatigue is produced by underload and monotony, and is associated with loss of task engagement and alertness. Our studies show that automated driving reliably elicits subjective symptoms of passive fatigue and also loss of alertness that persists following manual takeover. Passive fatigue also impairs attention and automation use in operators of Remotely Piloted Vehicles (RPVs). Use of in-vehicle media has been proposed as a countermeasure to fatigue, but such media may also be distracting. Studies tested whether various forms of phone-based media interacted with automation-induced fatigue, but effects were complex and dependent on task configuration. Selection of fatigue countermeasures should be guided by an understanding of the form of fatigue confronting the operator. System design, regulation of level of automation, managing distraction, and selection of fatigue-resilient personnel are all possible interventions for passive fatigue, but careful evaluation of interventions is necessary prior to deployment.
... As a relatively new job function, new training and selection methods are required to address human factor challenges in order to improve job performance and safety [22]. A serious game in this domain focuses on (1) relevant SO tasks which include controlling sensors and detecting, identifying and tracking targets and (2) relevant cognitive abilities which include amongst others visual scanning, tracking and discrimination, spatial memory, and divided attention and vigilance to multiple sources [23]. ...
In military simulations, software agents are used to represent individuals, weapon platforms or aggregates thereof. Modeling the behavioral capabilities and limitations of such agents may be time-consuming, requiring extensive interaction with subject matter experts and complicated scripts, but nevertheless resulting in rigid, predictable performance.
Autonomous agents that learn desired behaviors themselves using Machine Learning (ML) techniques can overcome these shortcomings. However, such techniques are not yet widely used and perhaps underappreciated. In this context, the latin expression “multum in parvo” (“much in little”) denotes that ML agents are able to yield a large variety of behavior, despite their compactness in terms of code and usage of physical memory. This paper attempts to provide some background on applicable Machine Learningsolutions and their potential military application. The paper is
based on the work of the NATO Research Task Group IST- 121 Machine Learning Techniques for Autonomous Computer Generated Entities.
... For example, the aircraft crew of a UAV must search for and detect targets and make mission-appropriate decisions (e.g., take photos, deploy a weapon, or call for an air strike). Current MQ-1 Predator and MQ-9 Reaper UAVs are controlled by three-person crews, which include a pilot, a sensor operator, and a mission intelligence coordinator (Chappelle, McDonald, & King, 2010). Search for ground targets is performed primarily by the sensor operator using a variety of displays, including direct camera images of the terrain . ...
Objective:
The goal for this study was to evaluate several visual search training techniques in an unmanned aerial vehicle (UAV) simulated task environment.
Background:
Operators controlling remote unmanned vehicles often must perform complex visual search tasks (e.g., target search). These tasks may pose substantial demands on the operator due to various environmental factors. Visual search training may reduce errors and mitigate stress, but the most effective form of training has not been determined.
Methods:
Participants were assigned to one of four training conditions: target, cue, visual scanning, or control. After the training, the effectiveness of the training techniques was tested during a 30-minute simulated UAV flight. A secondary task manipulation was included to further simulate the demands of a realistic UAV control and target search task. Subjective stress and fatigue were also assessed.
Results:
Target training produced superior target search performances in more hits and fewer false alarms (FAs) when compared to the control condition. The visual scanning and cue trainings were moderately effective. Only target training performance was vulnerable to the secondary task load. The task was stressful, but training did not mitigate stress response.
Conclusion:
Training participants on the target and the cue appearance as well as active scanning of the visual field is promising for promoting effective target search for this simulated UAV environment.
Application:
These training techniques could be used in preparation for intelligence, surveillance, and reconnaissance (ISR) missions that involve target search, especially where target appearance change is likely.
... Third, severe time pressure can drastically decrease task performance by limiting time to gain situational awareness [4] and formulate a response. Fourth, decisionmaking is often conducted under fatigue, which may degrade task performance [5], [6], and in related military cases has been found to cause operator " burnout " [7], [8]. Automated decision support systems (DSS) for C2 must be tailored to counteract the above tendencies and augment human performance under these unique cognitive demands. ...
... Additional support to these findings can be found in a study of over 800 UAV operators [12]. This study highlighted an additional factor challenging the performance of the UAV operators: the need to maintain high levels of visual and auditory alertness for extended periods of time. ...
Background
The exposure to war scenes via screens, despite offering a degree of detachment, can be stressful for the operator. The aim of the current study is to examine the existence of anxiety, depression, and post traumatic stress disorder (PTSD) symptoms among unmanned aerial vehicle (UAV) Israeli operators. Methods
Participants comprised 41 UAV operators (87.2% male), aged 22–38 (Mage = 26.05, SD = 3.54). Most (78.0%) reported having viewed battlefield scenes. All participants completed a total of five questionnaires: Beck Depression Inventory, State-Trait Anxiety Inventory, and three questionnaires of PTSD: Post Trauma Questionnaire (CAPS), the Post-Traumatic Cognition Inventory (CTPI), and the Post-Traumatic Symptom Scale (PSS). ResultsMean scores of depression and anxiety were found significantly lower than diagnosis cut-off points (p < .001). Senior operators showed higher means for depression (5.69 vs. 2.58, p = .040), of stress level (PSS; 3.17 vs. 0.25, p = .020) and for distress intensity (3.79 vs. 0.57, p = 0.041) than less-experienced operators. Conclusions
Investigating and monitoring the impact of battlefield exposure in UAV operators are highly beneficial for preventing psychopathology.
... Moreover, "the monotonous nature of the work (…) is interrupted by unpredictable and intense moments of combat (that) can be both mentally and physically fatiguing. Despite the potential for fatigue, the SO must quickly and efficiently monitor and respond to multiple visual and auditory sources of the communication (…) without degradation in performance" (Chappelle et al., 2010). ...
The FAF decided to offer the possibility for various NCO (Non Commissionned Officers) specialists to apply for the position of Sensor Operators (SO) for the Reaper RPA (Remotely Piloted Aircraft) through an internal FAF assessment. The approach aims at both enhancing some career pathways and allowing people to know the new RPA's job better.
First, we determined the SO's profile in terms of abilities. These are based on litterature review (such as Chappelle, McDonald & King, 2010; Coton, Chappelle, Heaton & Salinas, 2011; Duvillard-Monternier, Donnot & Gilles, 2015) but also on interviews with the first SO in the FAF. Then, we docused on several FAF job analyses, ralized with SME (Subjects-Matter Experts) (e.g., Weapon System Officiers, N=60; RPA Intelligence Imagery Operator, N= 8; Air Traffic Controller, N=52; Forward Air Controller, N=11; Flight Simulator Instructors, N=16; Air-to-Ground missile Operator, N=133). We used an adaptation of Fleishman Fob Analysis Survey in order to make comparisons and links between these profiles and the SO's profiles.
This communication aims at explaining 1) the main resultst of these comparative analyses, and recommendations to assess NCO SO applicants that we made, 2) the first selection process of SO in the FAF used since the end of 2014, 3) the directions for future researches and propects needed for RPA operators in the FAF.
... UAVs are useful tools for intelligence, surveillance, and reconnaissance missions because they reduce the threat to human operators, enable operators to work in shifts to support prolonged operations, and can potentially serve as force multipliers (Chappelle, McDonald, & King, 2010). Recent technology promises to allow single operators to control many UAVs with the help of automation designed to increase operator efficiency, enhance flexibility of operations, and lower workload (Cummings, Brzezinski, & Lee, 2007). ...
Reliability of automation is known to influence operator reliance on automation. What is less understood is how the influence of reliability and the effects of operator fatigue might interact. The present study investigated the impact of automation reliability on accuracy and reliance and how this impact changes with level of fatigue during simulated multiple unmanned aerial vehicle (UAV) operation. Participants (N = 131) completed a two-hour simulated multi-UAV mission assisted by an automated decision making aid of either high or low reliability. A decrease in subjective task engagement and performance over time marked the induction of passive fatigue by the mission. Participants were more trusting in the high reliability condition than in the low reliability condition. Finally, reliance decreased with time at any reliability, but a significant interaction between reliability and time on task indicated that the decrease was of smaller magnitude when the automation was reliable.
... Similar to military intelligence imagery analysts, such military personnel are tasked with directly observing and interacting with ground troops or enemy combatants through high-definition digital media in real time to track, target, and destroy enemy combatants and assets; provide force protection to ground troops; and survey postbattle damage and large-scale catastrophes. As a result, USAF Predator/Reaper RPA operators also operate in a continuously deployed, in-garrison fashion with high exposure to events involving human casualties (Chappelle, McDonald, & King, 2010;Chappelle, McDonald, & McMillan, 2011). Studies were conducted that solicited USAF Predator/ Reaper RPA operators to participate in a comprehensive and confidential occupational health survey that included the military version of the PTSD Checklist-Military (PCL-M; Chappelle, McDonald, Thompson, & Swearingen, 2012). ...
Imagery analysts are critical to the intelligence capabilities of the United States Air Force (USAF) and are known as the "eyes" of the USAF. The purpose of this study was to assess for posttraumatic disorder (PTSD) symptoms among this cohort. Of the 498 imagery analysts who participated, a total of 4.22% met provisional diagnostic criteria for PTSD as outlined in the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; American Psychiatric Association, 2000) which was lower than established rates of PTSD (up to 18%) among military personnel returning from deployment. Implications of subclinical PTSD symptoms on occupational functioning and overall diagnostic picture are discussed. (PsycINFO Database Record
(c) 2015 APA, all rights reserved).
... Given the sensitive, high-demand nature of USAF Predator/ Reaper drone operations, 29,30 it is important military commanders gauge the prevalence rates of distress among officer and enlisted airmen engaged in such operations. Results of the study indicate 1 out of every 10 Predator/Reaper drone operators self-reported high levels of distress. ...
The goal of this study is to repeat a survey administered in 2010 to assess for changes in mental health among United States Air Force aircrew operating Predator/Reaper remotely piloted aircraft, also commonly referred to as "drones." Participants were assessed for self-reported sources of occupational stress, levels of clinical distress using the Outcome Questionnaire-45.2, and symptoms of post-traumatic stress disorder (PTSD) using the PTSD Checklist-Military Version. A total of 1,094 aircrew responded to the web-based survey composed of the commercially available standardized instruments mentioned above. The survey also contained nonstandardized items asking participants to report the main sources of their occupational stress, as well as questions addressing demographics and work-related characteristics. The estimated response rate to the survey was 49%. Study results reveal the most problematic self-reported stressors are operational: low manning, extra duties/administrative tasks, rotating shift work, and long hours. The results also reveal 10.72% of operators self-reported experiencing high levels of distress and 1.57% reported high levels of PTSD symptomology. The results are lower than findings from the 2010 survey and from soldiers returning from Iraq and Afghanistan. Implications of the study and recommendations for United States Air Force line leadership and mental health providers are discussed.
... Job analysis studies also indicate that even higher validities could be achieved through expansion of the constructs measured in current selection procedures (e.g., Chappelle, McDonald, & King, 2010;Chappelle, McDonald, & McMillan, 2011;Kalita & Duma, 2008a, 2008bNagy, Eaton, & Muse, 2006;Nagy, Kalita, & Eaton, 2006;Tvaryanas, 2006). For example, measures of communication and teamwork skills, initiative, judgment and decision making, critical thinking, and person-environment fit, and improved measures of timesharing/multitasking, have been identified as having strong potential for augmenting current selection practices (Paullin et al., 2011). ...
This review examines evolving personnel selection practices for unmanned aircraft systems/remotely piloted aircraft (UAS/RPA) across the U.S. Air Force, U.S. Naval Services, and U.S. Army. Findings across services revealed several themes, including strengths (e.g., strong predictive validities, consistency in operator profiles), weaknesses (e.g., small number of predictive validation studies, small sample sizes), and gaps (e.g., need for further investigation of noncognitive predictors). Ongoing and proposed research, including development and implementation of new instruments and methodologies, are discussed, followed by suggestions to facilitate enhanced UAS/RPA selection practices across the services. (PsycINFO Database Record (c) 2013 APA, all rights reserved)
... It is important to note that the two latest military research reports into drone operator stress focus on what they call ''burnout'' (Chappelle et al. 2010;Ouma et al. 2011). The sub-clinical diagnosis of burnout has emerged as a psychological condition which lies between the normal ''stress'' of day-to-day military work and the clinical diagnosis of PTSD, which entails possible medical interventions, loss of duty assignment, discharge from the military, and the lifelong impacts of a mental health disorder including strained social relations, medical treatments and expenses, and limited employment opportunities in civilian life. ...
As the military's armed surveillance drones have become the iconic weapon of the early twenty-first century, they have also introduced radical transformations in the traditional labor of those who operate them – the pilots, crew, analysts, and commanders. In so doing, these transformations have engendered new kinds of subjectivity, with new ways of experiencing the work of surveillance and killing. This paper investigates the nature of these new subjectivities, how they are constructed through new technologies that combine surveillance with remote agency, the bureaucratization of killing, and the psychological implications for operators. It examines how scientific management strategies from Taylorism to business process re-engineering have contributed to reconstituting the subjectivity of drone pilots and sensor operators through decomposing their labor practices and reconstituting them within professionalized careers and technological systems of supervision and management. It also looks at how the decisions to use lethal force are themselves decomposed and distributed among individuals designated as responsible agents within the chain-of-command. In light of the creation of these new subjectivities, the paper examines the psychological stress experienced by those who occupy these new subject positions through an examination of several recent military studies, journalistic accounts, and a recent short film based upon an interview with a drone pilot, Omer Fast's 5,000 Feet is the Best (2011).
... I should also note that it is difficult to examine what exactly happened when UAVs were introduced, because much remains classified about US unmanned operations. Nevertheless, a few reports shed some light on the new landscape of activities and networks of human actors and technologies involved in the unmanned operations, including accident reports and research reports on operators of drones (see for example Manning et al. 2004;Williams 2004;USFOR 2010;Chappelle et al. 2010). Based on these reports, I will first look more closely at the delegation of tasks to unmanned systems. ...
The prospect of increasingly autonomous military robots has raised concerns about the obfuscation of human responsibility. This papers argues that whether or not and to what extent human actors are and will be considered to be responsible for the behavior of robotic systems is and will be the outcome of ongoing negotiations between the various human actors involved. These negotiations are about what technologies should do and mean, but they are also about how responsibility should be interpreted and how it can be best assigned or ascribed. The notion of responsibility practices, as the paper shows, provides a conceptual tool to examine these negotiations as well as the interplay between technological development and the ascription of responsibility. To illustrate the dynamics of responsibility practices the paper explores how the introduction of unmanned aerial vehicles has led to (re)negotiations about responsibility practices, focusing particularly on negotiations within the US Armed Forces.
... Results of recent job analyses of Remotely Piloted Aircraft (RPA) pilots and sensor operators indicate that the factors related to pilot performance are also needed to be successful in these emerging career fields (Bailey, 2008;Chappelle, McDonald, & King, 2010;Chappelle, McMillan, Novy, & McDonald, 2010). Efforts have begun to examine the applicability of the PCSM composite and its components to these emerging career fields. ...
In 1993, the US Air Force implemented the Pilot Candidate Selection Method (PCSM) as an additional indicator of pilot training aptitude. PCSM scores have been shown to be related to several pilot training criteria including graduation/elimination, flying grades, class rank, and number of flight hours needed to complete training (Carretta & Ree, 2003). The PCSM composite is still in use today, but the scores that contribute to it have changed. The study reported here examined the predictive validity of the current composite versus several training performance measures for 883 students attending Specialized Undergraduate Pilot Training (SUPT). Results indicated that the PCSM composite remained predictive of flying training performance despite changes in test content and flying training. After correction for multivariate range restriction and dichotomization of the graduation/elimination criterion, the correlation between the PCSM composite and T-6 completion was .53. This is consistent with the value of .46 reported by Carretta and Ree (2003) for an earlier version of the PCSM composite. Its predictiveness can be attributed to the measurement of factors that have consistently shown a relation to flying performance: cognitive ability, aviation job knowledge/experience, and psychomotor ability. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Building on emerging literature, a new self-report inventory was developed to assess multiple psychological attributes relevant to adaptability in remote warriors. Literature search backed by surveys of military and psychological experts identified 32 attributes for self-report scale development. Items were sorted reliably into targeted dimensions (67.5% vs. 1.6% random) in support of content validity. Item analysis of responses from 255 U.S. Air Force remote operations Airmen (74.5% sensor operators) narrowed the set to 25 empirically distinct scales demonstrating overall strong internal consistency reliability (Mdn alpha = .83), unidimensionality per scale, convergent and discriminant validity in relations with the NEO Personality Inventory-3 (e.g. Stress Tolerance r = -.50 with NEO Neuroticism and r = .00 with NEO Openness), and criterion validity in relations with burnout (e.g., Coping Flexibility r = -.43 with Exhaustion) and psychological distress (e.g., Hardiness r = -.62). Results support the continued development of the measure for advancing understanding of the psychology of remote warfare and engagement in similarly demanding occupations.
Future unmanned aerial systems (UAS) operations will require control of multiple vehicles. Operators are vulnerable to cognitive overload, despite support from system automation. This study tested whether attentional resource theory predicts impacts of cognitive demands on performance measures, including automation-dependence and stress. It also investigated individual differences in response to demands. One-hundred and 1 university student participants performed a multi-UAS simulation mission incorporating 2 surveillance tasks. Cognitive demands and level of automation (LOA) of key tasks were manipulated between-subjects. Results were partially consistent with predictions. Higher task demands impaired performance and elevated distress and workload, as expected. Higher LOA produced greater dependence on automation, but failed to mitigate workload. It was expected that, as the automation was quite reliable, participants would attempt to conserve resources by depending more on automation under high demand. In fact, the opposite tendency was observed. Individuals high in conscientiousness were especially likely to override the automation under high demand, apparently taking charge personally. Neuroticism and distress were also associated with performance, but results did not fit a resource theory interpretation. Thus, understanding impacts of overload in the multi-UAS context requires understanding operator strategy as well as resource insufficiency. Findings have implications for system design, and operator selection and training. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
The technology touted for keeping humans out of harm's way, may work for physical harm, but not necessarily psychological harm, which may even be exacerbated by Remotely Piloted Aircraft Systems (RPAS) technology. In this chapter we focus on factors associated with psychological and social effects (i.e., psychosocial) for those operating RPAS with an emphasis on the military operations. Psychosocial effects that include stress reactions, fatigue, feelings of guilt, and social conflict are important considerations for Human Systems Integration (HSI). RPAS operations are unique and at the same time challenging for a number of reasons including remote sensing, remote acting, the erratic pace of work, lack of social support, and technological usability issues. We reason that only the first two are essential features of the RPAS environment. The other features are contingent and are thus prime targets for improving the RPAS and mitigating some of the negative psychosocial effects.
The aim of this study was to systematically review the existing research on the health and well-being of military drone operators and intelligence analysts in order to provide an overview of research and identify gaps in this area. Six literature databases and 2 databases containing unclassified military reports were searched for relevant papers produced between January 1996 and May 2016. The search criteria were broad to allow for the identification of all relevant studies on the topic. Fifteen studies met the inclusion criteria; all of which were conducted in the U.S. with the U.S. Air Force personnel. The main sources of occupational stress reported by participants across the studies were operational. The rates of mental health diagnoses, including PTSD, were low, but levels of psychological distress were higher in drone and intelligence operators than in comparison groups. Fatigue emerged as a significant concern. It is important that future studies examine a variety of mental and physical health outcomes. The health and well-being of drone operators and intelligence analysts should be studied not just in the U.S., but also in other countries that are using drones for military purposes.
During the last few years the use of armed remotely piloted aircraft, most often referred to as drones, has caused extensive debate on the morality in warfare. This chapter will argue that drones have been humanized (attributed both intent and purpose) by being labeled e.g., as “killer-drones” while the pilot is often portrayed as a victim. It is possible that this humanized perception of drones has led to them being criticized specifically for violating universal legal and ethical principles. The humanization of drones together with the occupational stress seen in drone pilots as a result of organizational shortcomings indicates that technology has developed faster than the human ability to fully comprehend that progress. In conclusion, several aspects for successful integration of future autonomous systems in military organizations are discussed.
Unmanned aerial vehicles (UAVs) have become increasingly valuable military assets, and reliance upon them will continue to increase. Despite lacking an onboard pilot, UAVs require crews of up to three human operators. These crews are already experiencing high workload levels, which is a problem that will be likely compounded as the military envisions a future where a single operator controls multiple UAVs. To accomplish this goal, effective scheduling of UAVs and human operators is crucial to future mission success. We present a mathematical model for simultaneously routing UAVs and scheduling human operators, subject to operator workload considerations. This model is thought to be the first of its kind. Numerical examples demonstrate the dangers of ignoring the human element in UAV routing and scheduling.
The U.S. Air Force remotely piloted aircraft MQ-1 Predator and MQ-9 Reaper sensor operators (SOs) represent a group of enlisted airmen in a high-demand, high-precision, aviation-related position where they have a pivotal role in precision-strike aerial operations. This study evaluated psychological baseline test scores from the NEO Personality Inventory-Revised (NEO PI-R) on enlisted airmen who became operational Predator/Reaper SOs in an effort to assess how key personality traits (e.g., neuroticism, extraversion, openness, agreeableness, conscientiousness) distinguished them from peers in the civilian, general population as well as AC-130 gunship SOs. This study also developed occupationally specific normative data and distribution of personality scores for use in aeromedical evaluations of Predator/Reaper SO training applicants and incumbents. The results of the study shed light on objective personality traits and differences and assist military psychologists and flight surgeons with the interpretation of NEO PI-R test scores when evaluating the suitability and fitness for duty of training applicants and incumbents for such a unique and demanding career field. A case study and clinical vignette are provided to illustrate the practical application of study findings.
The increasing operational demand for MQ-1 Predator and MQ-9 Reaper remotely piloted aircraft (RPA) in support of intelligence, surveillance, and reconnaissance missions as well as precision-strike operations in theaters of conflict has led to a substantial rise in operational hours, shift work, and exposure to combat-related events (e.g., destruction of enemy assets and combatants) for operators. As a result of the continual need to sustain a high operational tempo, there are concerns among line commanders and aeromedical leadership regarding the prevalence of occupational burnout. There is also concern that there are differences across units for risk of occupational burnout and that active duty crew members are at higher risk when compared with National Guard/Reserve operators. This study surveyed 426 officer and enlisted operators (pilots and sensor operators). Although a wide range of stressors may contribute to elevated levels of burnout, the majority of occupational stress was reported to stem from operational stress and not exposure to combat (e.g., live video feed regarding the destruction or death of enemy combatants and ground forces). In general, the results revealed that active duty operators are more than twice as likely to suffer from the facets of occupational burnout involving emotional exhaustion and cynicism. Active duty as well as National Guard/Reserve operators attributed shift work, shift changes, hours worked, and simultaneously serving as a warfighter in theater while returning home and managing domestic roles and responsibilities at home to their burnout levels.
This study investigated the relation of the "Big Five" personality di- mensions (Extraversion, Emotional Stability, Agreeableness, Consci- entiousness, and Openness to Experience) to three job performance criteria (job proficiency, training proficiency, and personnel data) for five occupational groups (professionals, police, managers, sales, and skilled/semi-skilled). Results indicated that one dimension of person- ality. Conscientiousness, showed consistent relations with all job per- formance criteria for all occupational groups. For the remaining per- sonality dimensions, the estimated true score correlations varied by occupational group and criterion type. Extraversion was a valid pre- dictor for two occupations involving social interaction, managers and sales (across criterion types). Also, both Openness to Experience and Extraversion were valid predictors of the training proficiency criterion (across occupations). Other personality dimensions were also found to be valid predictors for some occupations and some criterion types, but the magnitude of the estimated true score correlations was small (p < .10). Overall, the results illustrate the benefits of using the 5- factor model of personality to accumulate and communicate empirical findings. The findings have numerous implications for research and practice in personnel psychology, especially in the subfields of person- nel selection, training and development, and performance appraisal.
Remotely piloted aircraft (RPA) with long endurance allow near-continuous operations, necessitating the implementation of shift work for crewmembers to provide the necessary manning of ground control stations. Shift work has a well-known association with fatigue, degraded work performance, and an increased risk for errors and accidents. This study presents the results of a follow-up survey of a particular population of shift-working RPA crewmembers 1 yr after modification of their shift work schedule.
A cross-sectional survey of 66 RPA crewmembers was conducted using a collection of validated fatigue scales. This data was compared to survey data collected a year prior from the same population and from a reference group of non-shift-working aircrew. Shift system features and individual and situational differences associated with fatigue were explored. Additionally, several alternative types of shift schedules were assessed through modeling and simulation.
The study found no significant reduction in reported fatigue despite prior modifications to the shift work schedule to increase opportunities for recovery. Months shift working, sleep quality, and disturbances in family and social activities were associated with overall fatigue scores. Approximately half of those surveyed met criteria for occupationally significant fatigue. Months shift working, use of on-duty napping, and fatigue scores were predictive of those with occupationally significant fatigue. Modeling of feasible variants of the current shift work schedule failed to reveal a significantly improved alternative schedule.
Collectively, the results demonstrate a persistent problem with chronic fatigue in this study population, likely reflective of continued inadequate opportunities for recovery and restorative sleep.
Critical psychological attributes of AC-130 gunship sensor operators according to subject matter experts
- W Chappelle
- J Patterson
- T Sowin
- B Randall
Chappelle, W., Patterson, J., Sowin, T., & Randall, B. (2009). Critical psychological attributes of AC-130 gunship sensor operators according to subject matter experts. USAF Technical Report, AFRl-SA-BR-TR-2009-001S; Brooks City Base, TX
The development and initial validation of the unmanned aerial vehicle (UAV) external pilot selection system Meta-anlaysis of personality assessment as predictors of military aviation training success
- S Biggerstaff
- D J Blower
- C A Portman
- A D Chapman
Biggerstaff, S., Blower, D. J., Portman, C.A., & Chapman, A.D. (1998). The development and initial validation of the unmanned aerial vehicle (UAV) external pilot selection system. Technical Report, Naval Aerospace Medical Research laboratory; Pensacola, FL Campbell, J.5., castaneda, M., & Pulos, S. (2010). Meta-anlaysis of personality assessment as predictors of military aviation training success. International Journal of Aviation Psychology, 20(1), 92- 109