Multi-trajectory analysis uncovers latent associations between psychological and physiological acute stress response patterns.

Encounter with an acute stressor elicits multiple physiological and psychological response trajectories that spread at different times-scales and directions. Associating a single physiological response trajectory with a specific psychological response has remained a challenge, due to putative interactions between the different stress response pathways. Hence, multidimensional analysis of stress response trajectories may be better suited to account for response variability. To test this, 96 healthy female participants underwent a robust acute laboratory stress induction procedure while their psychological [positive and negative affect (PANAS)] and physiological [heart rate (HR), heart rate variability (HRV), saliva cortisol (CORT)] responses were recorded before, during and after stress. Combining these data using unsupervised group-based multi-trajectory modelling uncovered three latent classes that best accounted for variability across psychological and physiological stress response trajectories. These classes were labelled based on their psychological response patterns as: A prototypical response group that depict a moderate increase in negative and decrease in positive affect during stress, with both patterns recovering after stress offset (n = 55); A heightened response group that depict excessive affective responses during stress that recover after stress offset (n = 24); and a lack of recovery group that depict a moderate increase in negative and decrease in positive affect during stress, with both patterns not recovering after stress offset (n = 17). With respect to physiological acute stress trajectories, all three groups exhibited comparable increases in HR and CORT during stress that recovered after stress offset, yet only the prototypical group expressed the expected stress-induced reduction in HRV, while the other two groups exhibited blunted HRV response. Critically, focusing on a single physiological stress response trajectory, including HRV, did not account for psychological response variability and vice versa. Taken together, a multi-trajectory approach may better account for the multidimensionality of acute stress response and uncover latent associations between psychological and physiological response patterns. Compared to the other two groups, the prototypical group also exhibited significantly lower overall stress scores based on the DASS-21 scale. This, alongside the uncovered response patterns, suggest that latent psycho-physiological associations may shed light on stress response adaptivity or lack thereof.

Predicting Chronic Stress among Healthy Females Using Daily-Life Physiological and Lifestyle Features from Wearable Sensors.

Background: Chronic stress is a highly prevalent condition that may stem from different sources and can substantially impact physiology and behavior, potentially leading to impaired mental and physical health. Multiple physiological and behavioral lifestyle features can now be recorded unobtrusively in daily-life using wearable sensors. The aim of the current study was to identify a distinct set of physiological and behavioral lifestyle features that are associated with elevated levels of chronic stress across different stress sources. Methods: For that, 140 healthy female participants completed the Trier inventory for chronic stress (TICS) before wearing the Fitbit Charge3 sensor for seven consecutive days while maintaining their daily routine. Physiological and lifestyle features that were extracted from sensor data, alongside demographic features, were used to predict high versus low chronic stress with support vector machine classifiers, applying out-of-sample model testing. Results: The model achieved 79% classification accuracy for chronic stress from a social tension source. A mixture of physiological (resting heart-rate, heart-rate circadian characteristics), lifestyle (steps count, sleep onset and sleep regularity) and non-sensor demographic features (smoking status) contributed to this classification. Conclusion: As wearable technologies continue to rapidly evolve, integration of daily-life indicators could improve our understanding of chronic stress and its impact of physiology and behavior.

Parsing inter- and intra-individual variability in key nervous system mechanisms of stress responsivity and across functional domains.

Exposure to stressful events is omnipresent in modern human life, yet people show considerable heterogeneity in the impact of stress exposure(s) on their functionality and overall health. Encounter with stressor(s) is counteracted by an intricate repertoire of nervous-system responses. This narrative review starts with a brief summary of the vast evidence that supports heart rate variability, cortisol secretion, and large-scale cortical network interactions as kay physiological, endocrinological, and neural mechanisms of stress responsivity, respectively. The second section highlights potential sources for inter-individual variability in these mechanisms, by focusing on biological, environmental, social, habitual, and psychological factors that may influence stress responsivity patterns and thus contribute to heterogeneity in the impact of stress exposure on functionality and health. The third section introduces intra-individually variability in stress responsivity across functional domains as a novel putative source for heterogeneity in the impact of stress exposure. Challenges and future directions are further discussed. Parsing inter- and intra-individual variability in nervous-system mechanisms of stress responsivity and across functional domains is critical towards potential clinical translation.