ResultsPerformanceThe correct detection and false alarm rates for each participant were used to compute signal detection theory measures of sensitivity (d’) and response bias (c). Sensitivity and response bias scores were analyzed using a 2 (noise) by 3 (task) ANOVA.

•Sensitivity: Significant main effect for task, F(2,69)=5.79, p<.01, η²=0.12. Post-hoc comparisons revealed that observers were significantly more sensitive in the temporal-only task (M=3.02) than in the combined task (M=2.51; see Figure 2). •Response Bias: Significant main effect for noise, F(1,42)=6.42, p<.05, η²=0.13, with observers in the noise condition (M=-0.05) being significantly more lenient in responding than their cohorts in the quiet condition (M=0.13; See Figure 3).

NoiseFor the noise group an 85 dBA intermittent white noise was presented via headphones during the task performance. Observers in the quiet condition also wore headphones to control for the effects of additional stimulation. The ambient sound level in the quiet condition was 64.5 dBA.

Self Reports of Workload and StressPerceived workload was assessed using the NASA Task Load Index (Hart & Staveland, 1988) and the Dundee Stress Questionnaire (Matthews et al., 2002). Following the instructions for the first task, participants completed the pre-DSSQ, after which they began the first task. Upon completion of each task, participants were administered the post-DSSQ and the NASA-TLX in a randomly assigned, counterbalanced order. This order was repeated after the second and third tasks.

Performance, Workload, and Stress Correlates of Temporal and Spatial Task Demands J.M. Ross, J.L. Szalma, J. Thropp, & P.A. Hancock Abstract

Increased understanding of the mechanisms by which stress impacts performance is essential to the design and operation of complex information systems. This study represents a test of the hypothesis that attentional narrowing observed under stressful conditions results from spatial and temporal perception drawing on common resource capacities. Although the present results were unable to resolve the specific issue to a satisfactory degree, a novel finding was observed that intermittent noise increases leniency in responding. The impact of noise on performance depends on the characteristics of the task to be performed, with spatial uncertainty exerting a significant influence on perceived workload and self reports of stress states.

ReferencesBroadbent, D.E., (1971). Decisions and stress. England: Medical Research Council.Broadbent, D.E., (1978). The current state of noise research: Reply to Poulton. Psychological Bulletin, 85(5), 1052-1067.Cornsweet, D.M., (1969). Use of cues in the visual periphery under conditions of arousal. Journal of Experimental Psychology, 80(1), 14-18.Dirkin, G.R., & Hancock, P.A. (1984). Attentional narrowing to the visual periphery under temporal and acoustic stress. Aviation, Space and Environmental Medicine, 55, 457.Easterbrook, J.A. (1959). The effect of emotion on cue utilization and the organization of behavior. Psychological Review, 66, 183-201.Hancock, P.A. (1986). Stress and adaptability. In: G.R.J. Hockey, A.W.K. Gaillard, & M.G.H. Coles, (Eds.). Energetics and Human Information Processing. (pp. 243-251), Dordrecht, the Netherlands: Martinus Nijhoff.Hancock, P.A., Szalma, J.L, & Weaver, J.L. (2002). Distortion of perceptual space-time under stress. Paper presented at the 23rd Army Science Conference, Orlando, FL, December.Hancock, P.A., & Warm, J.S., (1989). A dynamic model of stress and sustained attention. Human Factors, 31, 519-537.Hancock, P.A., & Weaver, J.L. (2003). On time distortion under stress. Theoretical Issues in Ergonomic Science, in press.Hart, S.G., & Staveland, L.E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In P.A. Hancock & N. Meshkati (Eds.), Human mental workload (pp139-183). Amsterdam: North-Holland.Helton, W.S., Warm, J.S., Matthews, G., Corcoran, K.J., & Dember, W.N. (2002). Further tests of an abbreviated vigilance task: Effects of signal salience and jet aircraft noise on performance and stress. Proceedings of the Human Factors and Ergonomics Society, 46, 1546-1550.Hockey, R., & Hamilton, P. (1983). The cognitive patterning of stress states. In G.R.J. Hockey (Eds.), Stress and fatigue in human performance (pp331-362). New York, NY: John Wiley & Sons Ltd.Matthews, G., Campbell, S.E., Falconer, S., Joyner, L.A., Huggins, J., Gilliland, K., et al. (2002). Fundamental dimensions of subjective state in performance settings: Task engagement, distress, and worry. Emotion, 2(4), 315-340.Milosevic, S., (1983). Effects of noise on signal detection. Ergonomics, 26(10), 939-946.Poulton, E.C., (1978). A new look at the effects of noise: A rejoinder. Psychological Bulletin, 85(5), 1068-1079.Szalma, J.L. (2002). Workload and stress of configural displays in vigilance tasks. Proceedings of the Human Factors and Ergonomics Society, 46, 1002-1006.Warm, J.S., Dember, W.N., & Hancock, P.A. (1996). Vigilance and workload in automated systems. In: R. Parasuraman and M. Mouloua. (Eds.). Automation and human performance: Theory and applications. (pp 183-200), Erlbaum, Hillsdale, N.J.Welford, A.T., (1973). Stress and performance. Ergonomics, 16, 567-580.

AcknowledgementThis work was supported by the Department of Defense Multidisciplinary University Research Initiative (MURI) program administered by the Army Research Office under grant DAAD19-01-1-0621. P.A. Hancock, Principle Investigator. The views expressed in this work are those of the authors and do not necessarily reflect official Army policy. The assistance of the Psychology Department at University of Central Florida is also gratefully acknowledged.

IntroductionThe operation of modern complex systems induces considerable stress in operators, who must then devote cognitive and physical resources to adapt to the stressor and maintain adequate performance levels. Design of systems that mitigate these effects requires development of theoretical models articulating the mechanism of stress effects. Toward that end, Hancock and Warm (1989) described a dynamic model of maximal adaptability. A major contribution of this model is the explicit recognition that tasks themselves represent the proximal stressor in operational settings. They identified two task dimensions that influence adaptive processes and performance. The first is information structure, which refers to the meaning extracted from the task and is often represented in a spatial format (e.g., visual displays). The second is the information rate, or the temporal flow of the task elements. Operators need to maintain an optimum state by seeking to modify perceptions along these dimensions. They noted that such a strategy is manifested in attentional narrowing under stress, originally articulated by Easterbrook (1959) as a restriction in the range of cue utilization with increased arousal. While the notion of unitary arousal has slowly dissolved (e.g. see Hancock, 1986; Matthews et al., 2002; Hockey & Hamilton, 1983), evidence for the narrowing of attention under stress has been experimentally validated (e.g., see Cornsweet, 1969; Dirkin & Hancock, 1984). Recently, Hancock and Weaver (2003) have argued that the distortion in the perception of time results from the same mechanism as narrowing of spatial perception, and that this narrowing is therefore a general effect of stress on perception of space-time. It was further argued by Hancock, Szalma, and Weaver (2002) that the common narrowing mechanism results from perceptions (and distortions of those perceptions) of spatial and temporal information drawing on common resource capacities. One way to test this hypothesis is to use conjunctions of task characteristics that vary in their spatial-temporal emphasis. Specifically, if temporal and spatial task characteristics draw on similar resource capacities, combining these elements into a task should debilitate performance relative to tasks in which only one of the characteristics is dominant. Further, these effects should be exacerbated in the presence of an external stressor such as noise. One goal for the present study was to test these possibilities.In addition to performance, task-based and external sources of stress also induce high levels of perceived workload and stress in observers. It has been well established that experimental manipulations that impact performance in target detection tasks also influence perceived workload and self-reports of stress in those tasks (e.g., Warm, Dember, & Hancock, 1996). Performance decrements are often associated with increases in workload, and contexts in which performance declines occur are associated with increases in self-reports of stress (e.g. Matthews et al., 2002; Szalma, 2002). If processing spatial and temporal elements of a task requires common resource capacities, one might expect higher workload ratings and increased stress in operators after a task that combines these elements relative to tasks that emphasize only one of these characteristics. A second goal for this study was to test this hypothesis.

MethodsParticipantsParticipants in this experiment were twenty-two females and twenty-two males at the University of Central Florida (Mean age=21.27). TasksThree seven minute tasks were employed in the present study. In each task participants were required to discriminate a 2mm diameter O from a D and a “backwards-D,” which were presented on a background mask of .4 mm diameter white circles on a black background for 500msecs unless otherwise stated (see Figure 1). The three tasks differed according to spatial and temporal properties of target detection.

•The ‘spatial-only’ task required observers to detect an O of brighter illumination that appeared in any one of nine locations on a screen (see Figure 1). •The ‘temporal-only’ required observers to detect an O of shorter duration (300 msecs), which always appeared in the center of the screen. •The ‘combined’ task the combined the spatial uncertainty with the temporal discrimination task. Thus, observers were required to detect an O of shorter duration that could appear in any one of nine locations on the screen.

Event rate was twenty-four events per minute with a signal probability=0.17. The order of task performance was counterbalanced across participants.

WorkloadGlobal TLX workload ratings for each task and noise condition are presented in Figure 4, and were analyzed using a 2 (noise) by 3 (task) ANOVA.

•Significant main effect for task, F(2, 82)=3.43, p<.05, η²=0.75. Post-hoc comparisons indicated that the temporal task (M=49.34) induced significantly less global workload than the spatial-only task (M=55.41) and the combined task (M=55.37).

Weighted ratings on the subscales of the TLX were obtained and analyzed using a 2 (noise) by 3 (task) by 5 (subscale) mixed ANOVA with repeated measures on the last two factors.

•Significant main effect for noise, F(1, 42)=4.30, p<.05, η²=0.09. Noise Induced significantly higher workload (M=167.71) relative to the quiet condition (M=140.97) across the five scales. •Significant main effect for scales, F(3, 124)=9.72, p<.001, η²<0.01.•Significant task by scales interaction, F(6,242)=2.45, p<.05, η²=0.55.

Separate ANOVA’s for task for each scale were computed to further explore the task by scale interaction. Weighted ratings for the three subscales that showed significant task effects are shown in Figure 5.

•Weighted Temporal Demand•Significant effect for task, F(2, 83)=5.90, p< .01, η²=0.12. Post-hoc comparisons indicated that the combined task induced more temporal demand (M=169.30) than the spatial-only task (M=118.75).

•Weighted Performance•Significant main effect for task, F(2, 78)=3.61, p<.05, η²=0.08. Post-hoc tests revealed that the combined task (M=89.43) induced significantly less Performance Workload than the spatial-only task (M=127.57).

StressParticipant’s responses on the pre- and post-DSSQ were used to calculate scores on eleven scales using the formula (post-score–pre-score/SD). Separate 2 (Noise) by 3 (Task) ANOVAs were computed for each scale. Standardized DSSQ change scores are plotted as a function of task type and noise condition for three of the DSSQ scales in Figure 6.

•Energetic Arousal•Significant main effect for task, F(2, 75)=5.82, p<.01, η²=0.12. The temporal-only task (M=-0.44) induced a significantly larger drop in Energetic Arousal relative to pre-task state as compared to the spatial only (M=-0.16) and combined (M=-0.15) tasks.

•Tense Arousal•Significant main effect for noise, F(1, 42)=3.98, p=.05, η²=0.09.Oservers in the noise condition (M=0.74) were significantly more tense than those in the quiet condition (M=0.20).

•Hedonic Tone•Significant main effect for noise, F(1, 42)=6.84, p<.05, η²=0.14.Observers in the noise condition reported larger declines in Hedonic Tone (M=-0.90) compared to their cohorts in the quiet condition (M=-0.20). •Significant main effect for task, F(2, 83)=3.07, p=.05, η²=0.07. Hedonic Tone was significantly lower after the temporal-only task (M=-0.67) than after the combined task (M=-0.46).

DiscussionDue to a potential ceiling effect (average detection scores above 87% and false alarm rates below 13%) in the detection and false alarm rates, performance data did not provide unequivocal information either for or against the hypothesis of Hancock et al. (2002) regarding the covariation of temporal and spatial distortion. Thus, the only difference in performance was observed in the expected superiority of a task without spatial uncertainty.

However, dissociations were observed between performance and self reports of workload and stress.

•In the combination and spatial only tasks performance was similar but the combination task induced higher Weighted Temporal Demand and lower Performance Workload relative to the spatial-only task.•Although observers achieved higher d’ scores in the temporal-only task relative to tasks with spatial uncertainty, there is a cost for such performance as reflected in decreased Energetic Arousal and Hedonic Tone.

Current experimental work will investigate whether these effects extend to a task in which spatial and temporal discriminations are combined rather than temporal discrimination and spatial uncertainty.

In this study, noise did not impact sensitivity, but it significantly decreased response bias, indicating a more lenient response bias in the presence of noise. These results are consistent with the general view that stress lowers response criteria (Welford, 1973), but not with the literature on the impact of noise on target detection performance, which indicates that the criterion should increase (e.g. see Broadbent, 1971) or remain stable (Milosevic, 1983). The consensus, based upon the work of Broadbent (1971; 1978; see also Poulton, 1978), has been that in long duration tasks continuous noise induces a rise in conservatism, particularly for responses of intermediate confidence. Further, in short duration tasks noise may serve to enhance performance. However, in this study, which employed a short duration task, no performance enhancement (in terms of increased correct detections and lower false alarm rates) was observed, and response bias decreased, indicating increased responding in the presence of intermittent noise. Note that in a short duration vigil using similar stimuli to those employed in this study, (Helton, Warm, Matthews, Corcoran, & Dember, 2002) found that continuous jet engine noise improved detections without changing the false alarm rate. A crucial difference between the study of Helton and his colleagues and the current study was the format of noise. In their study, noise was continuous presentation of jet engine noise, while in the current study intermittent noise of variable duration and random presentation times was used. Thus, participants experienced a greater degree of uncertainty regarding when and for how long noise would be present. It may be that it is uncertainty as a source of stress that induces leniency in responding.

The impact of noise on observers’ state was more pronounced in self reports of stress, with participants who experienced noise reporting greater Tense Arousal and lower Hedonic Tone. These effects differ from those of Helton and his colleagues (2002), who observed that noise decreased the symptoms of stress after a difficult vigilance task. These results represent trends opposite to those observed in this study, despite the fact that the task demands placed upon operators by Helton et al. were substantially greater than those in this study. For instance, the event rate in their study was 57.5 events per min, while an event rate of 24 events per minute was employed herein. It may be that whether noise exerts a negative effect on stress and performance depends on how the difficulty level of the task interacts with the form of noise presented to operators.

Practical ApplicationsThe finding that intermittent noise may induce leniency in responding differs from results of prior studies showing a rise in conservatism, indicating that willingness to identify a stimulus as signal varies as a function of noise format. Further, task parameters may impact the perceived workload and stress associated with task performance. These results underscore the importance of understanding how task- and environmentally-based stressors impact the performance, workload, and stress associated with performance. As increased leniency in responding can have a direct impact on target detection, these issues assume greater importance for tasks requiring detection of threat or friend/foe identification. Further research should examine how spatial-temporal task parameters interact with noise format to influence target detection and operator state.

Figure 3. Response bias as a function of task type for each noise condition.

Note. Error bars are standard error.

Figure 2. Perceptual sensitivity as a function of task.

Note. Error bars are standard error.