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Identification of resilient individuals and those at risk for performance deficits under stress.

Winslow BD, Carroll MB, Martin JW, Surpris G, Chadderdon GL - Front Neurosci (2015)

Bottom Line: Here we measure the effects of stress on physiological response and performance through behavior, physiological sensors, and subjective ratings, and identify which individuals are at risk for stress-related performance decrements.Stress response was effectively captured via electrodermal and cardiovascular measures of heart rate and skin conductance level.Outliers were identified in the experimental group that had a significant mismatch between self-reported stress and salivary cortisol.

View Article: PubMed Central - PubMed

Affiliation: Design Interactive, Inc. Orlando, FL, USA.

ABSTRACT
Human task performance is affected by exposure to physiological and psychological stress. The ability to measure the physiological response to stressors and correlate that to task performance could be used to identify resilient individuals or those at risk for stress-related performance decrements. Accomplishing this prior to performance under severe stress or the development of clinical stress disorders could facilitate focused preparation such as tailoring training to individual needs. Here we measure the effects of stress on physiological response and performance through behavior, physiological sensors, and subjective ratings, and identify which individuals are at risk for stress-related performance decrements. Participants performed military-relevant training tasks under stress in a virtual environment, with autonomic and hypothalamic-pituitary-adrenal axis (HPA) reactivity analyzed. Self-reported stress, as well as physiological indices of stress, increased in the group pre-exposed to socioevaluative stress. Stress response was effectively captured via electrodermal and cardiovascular measures of heart rate and skin conductance level. A resilience classification algorithm was developed based upon physiological reactivity, which correlated with baseline unstressed physiological and self-reported stress values. Outliers were identified in the experimental group that had a significant mismatch between self-reported stress and salivary cortisol. Baseline stress measurements were predictive of individual resilience to stress, including the impact stress had on physiological reactivity and performance. Such an approach may have utility in identifying individuals at risk for problems performing under severe stress. Continuing work has focused on adapting this method for military personnel, and assessing the utility of various coping and decision-making strategies on performance and physiological stress.

No MeSH data available.


Related in: MedlinePlus

Left panel: Stress score by group plotted during the baseline, TSST, and throughout the 5 scenarios. Center panel: Decision boundaries of stochastic gradient descent linear classifier of resilience group using baseline cortisol and baseline STAI. Right panel: Performance by resilience group, showing a decrease in performance over the first 4 scenarios for the resistant group compared to much less variability in performance for the resilience and recovery groups.
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Figure 6: Left panel: Stress score by group plotted during the baseline, TSST, and throughout the 5 scenarios. Center panel: Decision boundaries of stochastic gradient descent linear classifier of resilience group using baseline cortisol and baseline STAI. Right panel: Performance by resilience group, showing a decrease in performance over the first 4 scenarios for the resistant group compared to much less variability in performance for the resilience and recovery groups.

Mentions: Given that the above results indicated the scenarios did not provoke significant increases in physiological stress indices and served as more of a recovery phase than additional stressors, the pattern of these stress scores over the course of the experiment (baseline, socio evaluative stressor, VBS2 scenarios) was then analyzed to assess individuals' resilience to stress. Based on the responsivity of electrodermal and cardiovascular measures, a physiological stress score was defined for the experimental group only using a combination of heart rate and SCL, normalized by the mean control group values (Figure 6). As only the addition of the TSST in the experimental group provoked significant increases in physiological stress indices, only the experimental groups were used for the definition of resilience groups. Subjects were grouped by how their heart rate and skin conductance changed in response to the TSST and scenarios into the resistant, resilient, and recovery trends. (Norris et al., 2009) provided the basis for our definitions of the trends. One participant was removed due to loss of EDA. In the remaining participants, the majority of the individuals fell within the resilience phenotype (12/19), with 3 individuals in the resistant phentoype and 4 in the recovery.


Identification of resilient individuals and those at risk for performance deficits under stress.

Winslow BD, Carroll MB, Martin JW, Surpris G, Chadderdon GL - Front Neurosci (2015)

Left panel: Stress score by group plotted during the baseline, TSST, and throughout the 5 scenarios. Center panel: Decision boundaries of stochastic gradient descent linear classifier of resilience group using baseline cortisol and baseline STAI. Right panel: Performance by resilience group, showing a decrease in performance over the first 4 scenarios for the resistant group compared to much less variability in performance for the resilience and recovery groups.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4584989&req=5

Figure 6: Left panel: Stress score by group plotted during the baseline, TSST, and throughout the 5 scenarios. Center panel: Decision boundaries of stochastic gradient descent linear classifier of resilience group using baseline cortisol and baseline STAI. Right panel: Performance by resilience group, showing a decrease in performance over the first 4 scenarios for the resistant group compared to much less variability in performance for the resilience and recovery groups.
Mentions: Given that the above results indicated the scenarios did not provoke significant increases in physiological stress indices and served as more of a recovery phase than additional stressors, the pattern of these stress scores over the course of the experiment (baseline, socio evaluative stressor, VBS2 scenarios) was then analyzed to assess individuals' resilience to stress. Based on the responsivity of electrodermal and cardiovascular measures, a physiological stress score was defined for the experimental group only using a combination of heart rate and SCL, normalized by the mean control group values (Figure 6). As only the addition of the TSST in the experimental group provoked significant increases in physiological stress indices, only the experimental groups were used for the definition of resilience groups. Subjects were grouped by how their heart rate and skin conductance changed in response to the TSST and scenarios into the resistant, resilient, and recovery trends. (Norris et al., 2009) provided the basis for our definitions of the trends. One participant was removed due to loss of EDA. In the remaining participants, the majority of the individuals fell within the resilience phenotype (12/19), with 3 individuals in the resistant phentoype and 4 in the recovery.

Bottom Line: Here we measure the effects of stress on physiological response and performance through behavior, physiological sensors, and subjective ratings, and identify which individuals are at risk for stress-related performance decrements.Stress response was effectively captured via electrodermal and cardiovascular measures of heart rate and skin conductance level.Outliers were identified in the experimental group that had a significant mismatch between self-reported stress and salivary cortisol.

View Article: PubMed Central - PubMed

Affiliation: Design Interactive, Inc. Orlando, FL, USA.

ABSTRACT
Human task performance is affected by exposure to physiological and psychological stress. The ability to measure the physiological response to stressors and correlate that to task performance could be used to identify resilient individuals or those at risk for stress-related performance decrements. Accomplishing this prior to performance under severe stress or the development of clinical stress disorders could facilitate focused preparation such as tailoring training to individual needs. Here we measure the effects of stress on physiological response and performance through behavior, physiological sensors, and subjective ratings, and identify which individuals are at risk for stress-related performance decrements. Participants performed military-relevant training tasks under stress in a virtual environment, with autonomic and hypothalamic-pituitary-adrenal axis (HPA) reactivity analyzed. Self-reported stress, as well as physiological indices of stress, increased in the group pre-exposed to socioevaluative stress. Stress response was effectively captured via electrodermal and cardiovascular measures of heart rate and skin conductance level. A resilience classification algorithm was developed based upon physiological reactivity, which correlated with baseline unstressed physiological and self-reported stress values. Outliers were identified in the experimental group that had a significant mismatch between self-reported stress and salivary cortisol. Baseline stress measurements were predictive of individual resilience to stress, including the impact stress had on physiological reactivity and performance. Such an approach may have utility in identifying individuals at risk for problems performing under severe stress. Continuing work has focused on adapting this method for military personnel, and assessing the utility of various coping and decision-making strategies on performance and physiological stress.

No MeSH data available.


Related in: MedlinePlus