Title
Dynamical systems modeling of day-to-day signal-based patterns of emotional self-regulation and stress spillover in highly-demanding health professions
Abstract
As hospital workers face a growing number of patients and have to meet increasingly rigorous standards of care, their ability to successfully modulate their emotional reactions and flexibly handle stress presents a significant challenge. This paper examines a multimodal signal-driven way to quantify emotion self-regulation and stress spillover through a dynamical systems model (DSM). The proposed DSM models day-to-day changes of emotional arousal, captured through speech, physiology, and daily activity measures, and its interplay with daily stress. The parameters of the DSM quantify the degree of self-regulation and stress spillover, and are associated with work performance and cognitive ability in a multimodal dataset of 130 full-time hospital workers recorded over a 10-week period. Linear regression experiments indicate the effectiveness of the proposed features to reliably estimate individuals' work performance and cognitive ability, providing significantly higher Pearson's correlations compared to aggregate measures of emotional arousal. Results from this study demonstrate the importance of quantifying oscillatory behaviors from longitudinal ambulatory signals and can potentially deepen our understanding of emotion self-regulation and stress spillover using signal-driven measurements, which complement self-reports and provide estimates of the psychological constructs of interest in a fine-grained time resolution.
Year
DOI
Venue
2020
10.1109/EMBC44109.2020.9175604
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Keywords
DocType
Volume
Activities of Daily Living,Emotional Regulation,Emotions,Health Occupations,Humans,Speech
Conference
2020
ISSN
ISBN
Citations 
2375-7477
978-1-7281-1991-5
0
PageRank 
References 
Authors
0.34
3
7