Physiological Resonance in Empathic Stress: Insights from Nonlinear Dynamics of Heart Rate Variability

Abstract

Because most humans live and work in populated environments, researchers recently took into account that people may not only experience first-hand stress, but also second-hand stress related to the ability to empathically share another person's stress response. Recently, researchers have begun to more closely examine the existence of such empathic stress and highlighted the human propensity to physiologically resonate with the stress responses of others. As in case of first-hand stress, empathic stress could be deleterious for health if people experience exacerbated activation of hypothalamic-pituitary-adrenal and autonomic nervous systems. Thus, exploring empathic stress in an observer watching someone else experiencing stress is critical to gain a better understanding of physiological resonance and conduct strategies for health prevention. In the current study, we investigated the influence of empathic stress responses on heart rate variability (HRV) with a specific focus on nonlinear dynamics. Classic and nonlinear markers of HRV time series were computed in both targets and observers during a modified Trier social stress test (TSST). We capitalized on multiscale entropy, a reliable marker of complexity for depicting neurovisceral interactions (brain-to-heart and heart-to-brain) and their role in physiological resonance. State anxiety and affect were evaluated as well. While classic markers of HRV were not impacted by empathic stress, we showed that the complexity marker reflected the existence of empathic stress in observers. More specifically, a linear model highlighted a physiological resonance phenomenon. We conclude on the relevance of entropy in HRV dynamics, as a marker of complexity in neurovisceral interactions reflecting physiological resonance in empathic stress.

Keywords: complexity; empathic stress; heart rate variability; multiscale entropy; resonance.

Figure 1

Flowchart of the experimental protocol.

Figure 2

Anxiety (A) and negative affect (B) scores in reference (Ref) and speech/rest situations for the targets, observers and control (Ctrl) participants.

Figure 3

RR_mean (A), RMSSD (B), LF (C), HF (D), LF/HF (E) and complexity marker (F) mean values during reference (Ref), cognitive task (CT), speech preparation (Prepa) and speech/rest situations for targets, observers and control (Ctrl) participants. Significant differences correspond to the pairwise comparisons (Tukey post hoc) following the ANOVA results. **** p < 0.0001, *** p < 0.001, ** p < 0.01, * p < 0.05 for differences between experimental situations. $$ p < 0.01 for differences between experimental situations only for targets and observers. ### p < 0.001 for differences between situations only for Ctrl participants. £ p < 0.05 for differences between Ctrl participants and, respectively, targets and observers. RMSSD: root mean square of successive differences, LF: low-frequency power, HF: high-frequency power.