Cognitive Change in Special Forces Personnel ...

PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 49th ANNUAL MEETING—2005

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COGNITIVE CHANGE IN SPECIAL FORCES PERSONNEL FOLLOWING STRESSFUL SURVIVAL TRAINING W. C. Harris, P. A. Hancock University of Central Florida C. A. Morgan III Yale University School of Medicine Understanding the deterioration in cognitive functioning produced by stress continues to gain in importance due to the increasing demands imposed by technologically sophisticated systems. Although the general deleterious effects of stress are well established, the relative sensitivity of different cognitive functions to stress and the pattern of cognitive recovery with rest have not been fully distinguished. In this paper, we examined the cognitive performance of Special Forces soldiers immediately prior to and immediately following one week of Survival, Evasion, Resistance and Escape (SERE) School training at Ft. Bragg, NC. Post-stress cognitive performance was characterized by significantly increased response time with minimal change in response accuracy. While response time increased for all tasks, memory appears to be most sensitive to stress. Performance returned to pre-stress levels the next morning following one night of sleep. The tasks affected most in the current study differed from changes which follow primarily upon physical stress, implying that the effects of combined psychological and physical stress on cognitive performance differ substantively from the effects of physical demand alone.

INTRODUCTION Modern day military forces are currently operating in a variety of stressful settings for extended periods of time (Scales, 2003). These chronic stress conditions can impair cognitive functioning which is the basis for the judgments these personnel take. Errors in such judgments can be personally and collectively catastrophic. As decisionmaking ability declines, we need to ensure that critical tasks can still be performed and that technological systems adjust to support this reduced level of operator functioning (Hancock & Szalma, 2003). Predicting performance change during stress requires our understanding of the function relating change in cognitive capacities to stress. The extended-U model (Hancock & Warm, 1989) provides a comprehensive description of this complex, non-linear relationship between stress level and operator performance. However, this general description does not specify the nature of change in any individual cognitive function as stress increases. Judgments, and the decisions which underlie those judgments, are the final product of a number of such basic cognitive functions (Wickens & Flach, 1988). The cognitive operations involved in decision-making include; i) obtaining relevant information, and/or retrieving relevant information from memory; ii) processing logical and spatial information as well as mathematical transformations; and iii) formulating a chain of appropriate response strategies. At present, we do not know whether stress affects the resources necessary to perform each of these functions equally or whether they are differentially altered by either stress or the inherent characteristics of the exposed individuals. Predicting impending overall

performance deterioration is of course important. However, if we are to provide technical support to such stressed individuals, we need to be able to anticipate which cognitive functions will deteriorate most. Cognitive changes during high stress portions of SERE training include dissociation and memory deficits (Morgan, et al., 2004). Previous field assessments, which have examined only a limited number of cognitive tasks following approximately 12 hours of high stress and a recovery period of approximately one hour, have detected little in terms of specific cognitive changes (DeJohn & Reams, 1992). However, the subsequent inclusion of Simple Response Time (SRT) and a more detailed analysis of within-session did find subtle cognitive changes following one week of high stress and only three hours of recovery (see Harris, Hancock, & Harris, 2005). Further, in some of our previous work, we have also found small changes in cognitive performance immediately following physically demanding work (Harris & Hancock, 2003). The present study examined the effect of high levels of combined physical and psychological stress immediately following SERE exposure and also monitored the recovery profile as it occurred during a twelve-hour, post-stress interval. The cognitive battery selected provides a profile of six cognitive functions critical for decision making in military settings. Previous studies (Harris et al., 2005; Harris & Hancock, 2003) found that SRT changes preceded response time change in more complex tasks and the number of milliseconds by which SRT increased, actually predicted the level of deterioration of the more complex tasks. The present study served to further evaluate this covariation of SRT-cognitive functioning.

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EXPERIMENTAL METHOD We assessed the performance of two classes at the Army SERE School at Ft. Bragg, NC using the ANAM Readiness Evaluation System (where ANAM is the acronym for the Automated Neuropsychological Assessment Metric) to evaluate soldier cognitive functioning. The major goal of the present experiment was to determine whether all types of cognitive functioning are affected equally by a common level of mission stress, namely one week of SERE training. We also examined the recovery of cognitive functioning after this period of stress. The results of each class were analyzed separately and compared.

Experimental Participants Two SERE classes were solicited as participants in the present study. During December 2003, twenty-seven enlisted Special Forces soldiers enrolled in the Army Survival, Evasion, Resistance, and Escape (SERE) School at Ft. Bragg, NC, and represented the first class. In January 2004, a second group of twenty-four Special Forces soldiers enrolled in the Army SERE School and participated as the second class. Twenty-two of the soldiers in the second group were enlisted personnel and two were officers.

Cognitive Assessment Methodology The battery used to assess performance in the present study was the ANAM Readiness Evaluation System (ARES). The Automated Neuropsychological Assessment Metric (Reeves, et al., 1991) presents a wider spectrum of cognitive tasks on a desktop or laptop computer, making administration in the field problematic. The ARES is a selection of tests from the larger ANAM battery presented on a handheld computer. ARES tasks were selected that assess components of cognitive performance considered to be important in operational settings (Wickens & Flach, 1988). The battery included; Simple Reaction Time (SRT), Logical Reasoning, Mathematical Processing, Spatial Processing, Spatial Memory, and a 6-item Sternberg Memory task. The battery was always administered using a handheld, Handspring Visor Prism.

Experimental Procedure Training on the cognitive assessment battery (ARES) and subsequent baseline assessment occurred at approximately 1800h on the last day of SERE classroom instruction. During this pre-stress session, soldiers completed the battery four times. Collectively they exhibited high levels of accuracy during the first training trial and accuracy was maintained while response speed increased during training. Response time improved with practice and the fourth repetition of the respective ARES

tasks was used as baseline performance (see Benedetto, Harris, & Goernert, 2000). One week later, at approximately 1400h, soldiers completed the battery a fifth time as their final activity of the field training exercise. Meals were provided and snacks were available, and soldiers then slept in the barracks that night. The sixth and final ARES administration occurred at approximately 0715h the following morning.

EXPERIMENTAL RESULTS Although procedures were identical for both classes, results are presented separately to provide an estimate of the consistency of effects. We have divided the results initially on the basis of response accuracy and response time.

Response Accuracy Pairwise comparisons were conducted between the fourth performance trial (designated as the baseline), the fifth performance trial (designated as the immediate poststress condition) and the sixth performance trial (designated the recovery, or morning after trial). For Class 1, there was only one significant effect and that was the reduction in accuracy of Logical Reasoning for the morning after trial versus the baseline, see Table 1. These predominantly null results for accuracy follow our earlier finding of relative high stress resistance in the real-world. The results of Class 2 were a little different. Here, the accuracy of mathematical processing was impaired in both the immediate post-stress and morning after test conditions. Further, there was a transient effect on Letter Memory which showed a small, but significant drop immediately following stress. However, like the results for Class 1, the predominant pattern showed little or no substantive change in performance accuracy. Table 1. Accuracy by Task and Condition. Task

Class

Logical Reasoning

One Two One Two One Two One Two One Two

Mathematical Processing Spatial Processing Spatial Memory Letter Memory

*p< .05

Prestress 94.6 95.0 91.0 94.5 95.0 95.8 94.7 96.0 94.7 96.7

Poststress 94.2 94.3 90.5 88.2 * 91.2 92.3 92.2 93.9 92.2 93.6*

Morning after 91.2 * 94.1 92.5 89.8 * 91.7 92.6 94.7 96.7 94.7 97.9

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Response Time

Cognitive Function Sensitivity

While there appear to be few changes in response accuracy one cannot take this as a full portrait of performance since speed is symbiotic with accuracy and one cannot be veridically understood without the other. When we look at the results in Table 2, a very different and much fuller picture emerges. The first thing that must be mentioned is that the present results do not derive from a speed-accuracy trade-off. It is evident that when performance was less accurate it was also slower, implying a general deterioration, not a change in response strategy. For Class 1, there was a significant post-stress increase in response time for all tasks, with the exception of Spatial Processing which however did show a strong tendency for slower response. This post-stress effect was transient in that by the morning after, scores had all returned to baseline. For Class 2, the pattern was almost identical. However, in this group the exception was Logical Reasoning and not Spatial Processing. Again the trend for this one nonsignificant change was in the same direction as all of the others, namely an increase in response time. Combinatorial examination of both the time and accuracy data did not suggest any micro speed-accuracy trade-offs within any of the individual tasks tested.

One of our prime concerns was to estimate the magnitude of stress effects on specific information processing elements. To generate a first pass perspective on this, we reasoned that Simple Response Time (SRT) was involved in all tasks and so we have extracted SRT changes from all other members of the task battery. (This assumes a simple additive effect of SRT which we are willing to make at this juncture). This being so, the response time changes are presented in Table 3. Similar changes in both classes on four of the five tasks suggest that the effect of stress varies with largely the task and is somewhat loss contingent upon the individual. The size of post-stress change varied with the cognitive demands of the task. Memory tasks were affected most. For Spatial Memory this change was 53% and 35% for Class 1 and Class 2 while the respective reduction in Letter Memory was 28% and 43% respectively. The Logic Reasoning task was affected least (7% and 5%). Mathematical Processing also exhibited similar, but more moderate changes in both classes (21% and 23%). The only task not exhibiting similar changes in both classes was Spatial Processing (i.e., 10% and 26%). Performance on the Spatial Processing task stabilizes slowly (Harris et al., 2005) and the class difference may reflect that performance had not stabilized during training in one or both classes.

Table 2. Response Time by Task and Condition. Task

Class

Simple Response Time Logical Reasoning

Mathematical Processing

Spatial Processing

Spatial Memory

Letter Memory

One

Prestress 215.4

Poststress 236.1***

Morning After 213.2

Two

224.8

247.1*

224.0

One

1761.7

1898.3*

1801.1

Two

2106.4

2224.7

1915.8

One

1866.8

2234.3***

1829.3

Two

2124.8

2590.8***

2306.6

One

2073.8

2284.4

2000.0

Two

2407.0

2997.5*

2239.0

One

1168.9

1692.0***

1180.0

Two

1287.8

1681.6**

1429.4

One

690.0

845.5***

721.2

Two

778.8

1039.9***

780.9

p< .05, ** p< .01, *** p< .001

Table 3. Response Time Change by Task and Condition. Task

Class

Prestress

Poststress

Change (ms)

Change (%)

One Two Mathematical One Processing Two Spatial One Processing Two Spatial One Memory Two Letter One Memory Two

1547 1881 1652 1900 1859 2182 954 1063 475 554

1662 1978 1998 2344 2048 2751 1456 1435 610 793

115 97 346 444 189 569 502 372 135 239

7 5 21 23 10 26 53 35 28 43

Logical Reasoning

DISCUSSION The present study reports consistent findings that accord with the model proposed in the extended-U. (Hancock & Warm, 1989) The current results indicate that cognitive performance change varies between an apparent insensitivity to stress during initial stress exposure to the catastrophic collapse that has been described during realworld disasters (Morgan, 1995; Leach, 2004). Assessment of cognitive functioning after one week of psychological and physical stress indicated slower than baseline responding with minimal accuracy change. Completion of items was self-paced, and soldiers elected to increase the


time they expended on each item in order to maintain accuracy as cognitive functioning declined. Had items been externally paced, increased error rates may well have occurred as the available time approached its limit. Memory tasks deteriorated most. This pattern differs from previous studies which found Logical Reasoning was most sensitive to the stress of physically demanding simulated combat (Harris & Hancock, 2003). Replication of Class 1 changes in Class 2 indicates a strong consistency in the cognitive processing changes produced by SERE training. The difference in the pattern of cognitive tasks affected by stress suggests that the effects of physical and psychological stress do differ. Physical effort, discomfort, and sleep deprivation are high during simulated combat, but only rarely is the level of psychological threat elevated. In contrast, the SERE training had lower physical demands but included significant levels of psychological stress. The appearance of decrements in complex cognitive task performance at the point at which SRT increased by approximately 20 ms is consistent with our previous studies that have found SRT diagnostic and that complex cognitive performance changes can be predicted by SRT changes (Harris et al., 2005; Harris & Hancock, 2003). The consistent appearance of cognitive performance deficits when SRT increases reach 20 ms suggests that SRT may provide an effective fitness for duty test. Memory deficits are consistent with cognitive changes during SERE training (Morgan, et al., 2004) and suggest that post SERE assessments are indicative of changes during stress. Furthermore, changes in the present study indicate that the information processing deficits found in the present study are likely to be present during stress. The cognitive performance return to baseline in the present study further delineates the speed of recovery of cognitive functioning in military personnel but the minimum time for complete recovery still needs to be determined. Almost complete recovery occurred here after 12 hours of rest, but three hours was insufficient for complete recovery in an earlier group of Navy SERE students (Harris et al., 2005). We conclude that optimal recovery time lies between this three and twelve hour interval. Future research is needed to determine the relationship between cognitive function changes and operational performance.

ACKNOWLEDGEMENTS This work was supported by the DoD Multidisciplinary University Research Initiative (MURI) program administered by the Army Research Office under Grant DAAD19-01-1-0621, P.A. Hancock, Principal

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Investigator. The views expressed in this work are those of the authors and do not necessarily reflect official Army policy.

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