Cortisol and salivary alpha-amylase trajectories following a group social-evaluative stressor with adolescents.Psychoneuroendocrinology. 2017 Dec; 86:8-16.P
Intraindividual variability in stress responsivity and the interrelationship of multiple neuroendocrine systems make a multisystem analytic approach to examining the human stress response challenging. The present study makes use of an efficient social-evaluative stress paradigm - the Group Public Speaking Task for Adolescents (GPST-A) - to examine the hypothalamic-pituitary-adrenocortical (HPA)-axis and Autonomic Nervous System (ANS) reactivity profiles of 54 adolescents with salivary cortisol and salivary alpha-amylase (sAA). First, we account for individuals' time latency of hormone concentrations between individuals. Second, we use a two-piece multilevel growth curve model with landmark registration to examine the reactivity and recovery periods of the stress response separately. This analytic approach increases the models' sensitivity to detecting trajectory differences in the reactivity and recovery phases of the stress response and allows for interindividual variation in the timing of participants' peak response following a social-evaluative stressor. The GPST-A evoked typical cortisol and sAA responses in both males and females. Males' cortisol concentrations were significantly higher than females' during each phase of the response. We found no gender difference in the sAA response. However, the rate of increase in sAA as well as overall sAA secretion across the study were associated with steeper rates of cortisol reactivity and recovery. This study demonstrates a way to model the response trajectories of salivary biomarkers of the HPA-axis and ANS when taking a multisystem approach to neuroendocrine research that enables researchers to make conclusions about the reactivity and recovery phases of the HPA-axis and ANS responses. As the study of the human stress response progresses toward a multisystem analytic approach, it is critical that individual variability in peak latency be taken into consideration and that accurate modeling techniques capture individual variability in the stress response so that accurate conclusions can be made about separate phases of the response.