The other side of the curve: Examining the relationship between pre-stressor physiological responses and stress reactivity
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There is widespread consensus that stress induces dramatic physiological changes, but no agreement on the quantitative parameters that are appropriate to measure these responses. More importantly, the interpretation of various stress measurements, and how individual responses should be evaluated, has not been properly addressed. Even the definition of baseline, against which stress responses must be measured, is not clearly established. The current experiment sought to address these shortcomings by comparing the predictive value of different calculated parameters for psychosocial and physiological measures of stress across individuals. Subjects were 29 male and 59 female healthy undergraduate students with saliva samples collected over a 3-h interval that included a Trier Social Stress Test. Salivary cortisol and alpha-amylase response were analyzed using the absolute concentration, the percent change in concentration, the area under the curve (Pruessner et al., 2003), and the arrival index (change from arrival to 1h after arrival). The arrival index correlated with the subsequent stress response for both cortisol (r=0.76, p<0.01) and alpha-amylase (r=0.86, p<0.01). The arrival index for both cortisol and alpha-amylase was also related to subjective ratings of anxiety following the psychosocial stressor. A subset of individuals with high self-reported anxiety also displayed higher reactivity in response to the psychosocial stressor. Thus, the magnitude of the difference in cortisol and alpha-amylase between arrival and 1h after arrival was a predictor of subsequent stress reactivity. These findings suggest that different psychosocial profiles may be reflected in cortisol and alpha-amylase changes. For this reason: (1) a recovery period after arrival is essential to establish a baseline, (2) the difference between arrival and post-recovery period baseline should be included in experimental designs as a predictive variable, and (3) transformation of individual measures into proportional changes relative to the arrival sample is very likely to obscure important underlying individual differences.
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