Gregory J. Funke

Emotional intelligence, personality, and task-induced stress

Emotional intelligence (EI) may predict stress responses and coping strategies in a variety of applied settings. This study compares EI and the personality factors of the Five Factor Model (FFM) as predictors of task-induced stress responses. Participants (N = 200) were randomly assigned to 1 of 4 task conditions, 3 of which were designed to be stressful. Results confirmed that low EI was related to worry states and avoidance coping, even with the FFM statistically controlled. However, EI was not specifically related to task-induced changes in stress state. Results also confirmed that Neuroticism related to distress, worry, and emotion-focused coping, and Conscientiousness predicted use of task-focused coping. The applied utility of EI and personality measures is discussed.

Vehicle automation: A remedy for driver stress?

The present study addressed the effects of stress, vehicle automation and subjective state on driver performance and mood in a simulated driving task. A total of 168 college students participated. Participants in the stress-induction condition completed a ‘winter’ drive, which included periodic loss of control episodes. Participants in the no-stress-induction condition were not exposed to loss of control. An additional, independent manipulation of vehicle speed was also conducted, consisting of two control conditions requiring manual speed regulation and a third in which vehicle speed was automatically regulated by the simulation. Stress and automation both influenced subjective distress, but the two factors did not interact. Driver performance data indicated that vehicle automation impacted performance similarly in the stress and no-stress conditions. Individual differences in subjective stress response and performance were also investigated. Resource theory provides a framework that partially but not completely explains the relationship between vehicle automation and driver stress. Implications for driver workload, safety and training are discussed.

Conceptualization and Measurement of Team Workload A Critical Need

Objective: The purpose of this article is to present and expand on current theories and measurement techniques for assessing team workload. Background: To date, little research has been conducted on the workload experienced by teams. A validated theory describing team workload, which includes an account of its relation to individual workload, has not been articulated. Method: The authors review several theoretical approaches to team workload. Within the team research literature, attempts to evaluate team workload have typically relied on measures of individual workload. This assumes that such measures retain their validity at the team level of measurement, but empirical research suggests that this method may lack sensitivity to the drivers of team workload. Results: On the basis of these reviews, the authors advance suggestions concerning a comprehensive theory of team workload and methods for assessing it in team settings. The approaches reviewed include subjective, performance, physiological, and strategy shift measures. Theoretical and statistical difficulties associated with aggregating individual-level workload responses to a team-level measure are discussed. Conclusion: Conception and measurement of team workload have not significantly matured alongside developments in individual workload. Application: Team workload remains a complex research area without simple measurement solutions, but as a research domain it remains open for contributions from interested and enterprising researchers.

Measuring workload in collaborative contexts: trait versus state perspectives.

Objective: In the present study, we explored the state versus trait aspects of measures of task and team workload in a disaster simulation. Background: There is often a need to assess workload in both individual and collaborative settings. Researchers in this field often use the NASA Task Load Index (NASA-TLX) as a global measure of workload by aggregating the NASA-TLX’s component items. Using this practice, one may overlook the distinction between traits and states. Method: Fifteen dyadic teams (11 inexperienced, 4 experienced) completed five sessions of a tsunami disaster simulator. After every session, individuals completed a modified version of the NASA-TLX that included team workload measures. We then examined the workload items by using a between-subjects and within-subjects perspective. Results: Between-subjects and within-subjects correlations among the items indicated the workload items are more independent within subjects (as states) than between subjects (as traits). Correlations between the workload items and simulation performance were also different at the trait and state levels. Conclusion: Workload may behave differently at trait (between-subjects) and state (within-subjects) levels. Application: Researchers interested in workload measurement as a state should take a within-subjects perspective in their analyses.

Effect of Active and Passive Fatigue on Performance Using a Driving Simulator

The present study investigated the effects of active fatigue (e.g., elevated distress) and passive fatigue (e.g., decreased task engagement) on driving performance. The study used similar manipulations developed by Saxby et al. (2007), which were shown to induce active and passive fatigue states. 168 undergraduates participated. There were 3 conditions (active, passive, control) and 2 durations (10, 30 minutes). The active condition used simulated wind gusts to increase the required number of steering and acceleration changes, while the passive condition was fully automated. In the control condition, drivers were in full control of steering and acceleration. Data confirmed that, over time, passive fatigue is expressed as decreasing task engagement. Furthermore, drivers in the passive condition had slower response times to an unexpected event and were more likely to crash than those in the active and control conditions. Theoretical and practical implications are discussed.

Cyber Vigilance: Effects of Signal Probability and Event Rate

Cyber security operators in the military and civilian sector face a lengthy repetitive work assignment with few critical signal occurrences under conditions in which they have little control over what transpires. In this sense, their task is similar to vigilance tasks that have received considerable attention from human factors specialists in regard to other operational assignments such as air traffic control, industrial process control, and medical monitoring. Accordingly, this study was designed to determine if cyber security tasks can be linked to more traditional vigilance tasks in regard to several factors known to influence vigilance performance and perceived mental workload including time on task, the probability of critical signal occurrence, and event rate (the number of stimulus events that must be monitored in order to detect critical signals). Consistent with the results obtained in traditional vigilance experiments, signal detection on a 40-minute simulated cyber security task declined significantly over time, was directly related to signal probability, and inversely related to event rate. In addition, as in traditional vigilance tasks, perceived mental workload in the cyber task, as reflected by the NASA Task Load Index, was high. The results of this study have potential meaning for designers of cyber security systems in regard to psychophysical factors that might influence task performance and the need to keep the workload of such systems from exceeding the information processing bounds of security operators.

The Sustained Attention to Response Task (SART) Does Not Promote Mindlessness During Vigilance Performance

Objective In this study, we evaluated the validity of the Sustained Attention to Response Task (SART) as a means for promoting mindlessness in vigilance performance. Background Vigilance tasks typically require observers to respond to critical signals and to withhold responding to neutral events. The SART features the opposite response requirements, which supposedly leads it to promote a mindless, nonthoughtful approach to the vigilance task. To test that notion, we compared the SART to the traditional vigilance format (TVF) in terms of diagnostic accuracy assessed through decision theory measures of positive and negative predictive power (PPP and NPP), perceived mental workload indexed by the Multiple Resource Questionnaire, and oculomotor activity reflected in the Nearest Neighbor Index and fixation dwell times. Method Observers in TVF and SART conditions monitored a video display for collision flight paths in a simulated air traffic control task. Results Diagnostic accuracy in terms of NPP was high in both format conditions. While PPP was poorer in the SART than in the TVF, that result could be accounted for by a loss of motor control rather than a lack of mindfulness. Identical high levels of workload were generated by the TVF and SART tasks, and observers in both conditions showed similar dynamic scanning of the visual scene. Conclusion The data indicate that the SART is not an engine of mindlessness. Application The results challenge the widespread use of the SART to support a model in which mindlessness is considered to be the principal root of detection failures in vigilance.

Use of the RoboFlag synthetic task environment to investigate workload and stress responses in UAV operation

Use of unmanned aerial vehicles (UAVs) is an increasingly important element of military missions. However, controlling UAVs may impose high stress and workload on the operator. This study evaluated the use of the RoboFlag simulated environment as a means for profiling multiple dimensions of stress and workload response to a task requiring control of multiple vehicles (robots). It tested the effects of two workload manipulations, environmental uncertainty (i.e., UAV’s visual view area) and maneuverability, in 64 participants. The findings confirmed that the task produced substantial workload and elevated distress. Dissociations between the stress and performance effects of the manipulations confirmed the utility of a multivariate approach to assessment. Contrary to expectations, distress and some aspects of workload were highest in the low-uncertainty condition, suggesting that overload of information may be an issue for UAV interface designers. The strengths and limitations of RoboFlag as a methodology for investigating stress and workload responses are discussed.

A Comparison of Cerebral Hemovelocity and Blood Oxygen Saturation Levels During Vigilance Performance

This study compared measures of cerebral blood flow velocity (CBFV) and blood oxygen saturation (rSO2), during the performance of a 40-min vigilance task. Observers monitored a simulated air-traffic control display for flight path deviations which occurred in a unidirectional or a multidirectional context. CBFV and rSO2 measures were secured from the medial cerebral arteries in the left and right cerebral hemispheres and from the corresponding frontal lobes, respectively. Performance efficiency was greater in the unidirectional than the multidirectional condition and declined over time in both conditions, more so in the multidirectional condition. This pattern of results was paralleled in different ways by the two hemodynamic measures. A result of this sort challenges the assumption of a close tie between cerebral blood flow and oxygen saturation (Siesjo, 1978) and supports recent findings (Mintun et al., 2001) that cerebral blood flow and oxygen levels are not tightly coupled in active brain states.

Development of the Team Workload Questionnaire (TWLQ)

In the present paper we developed the Team Workload Questionnaire (TWLQ). Despite extensive workload studies, little research has been conducted on the workload experienced by teams. Team workload has largely been ignored by research with no validated theory constructed or dedicated team workload measures available to researchers and practitioners. The TWLQ items were generated based on the NASA-TLX and team workload theory. We examined 216 members of sports team completing a team workload measure after games or practice. Principal Axis Factoring method with Direct Oblimin rotation indicated three separate factors for the TWLQ with the factors classified as Task Workload, Team Workload, and Task-Team Balancing. The TWLQ may be a useful subjective measure that can be used to assess the workload demand in team tasks. It provides researchers a tool to advance the understating of team workload and gives practitioners the means to assess the workload demands of team tasks.