From work stress to disease: A computational model
Publication year
2022Number of pages
27 p.
Source
PLoS One, 17, 2, (2022), article e0263966ISSN
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
SW OZ BSI OLO
SW OZ BSI AO
Journal title
PLoS One
Volume
vol. 17
Issue
iss. 2
Languages used
English (eng)
Subject
Learning and Plasticity; Work, Health and PerformanceAbstract
In modern society, work stress is highly prevalent. Problematically, work stress can cause disease. To help understand the causal relationship between work stress and disease, we present a computational model of this relationship. That is, drawing from allostatic load theory, we captured the link between work stress and disease in a set of mathematical formulas. With simulation studies, we then examined our model's ability to reproduce key findings from previous empirical research. Specifically, results from Study 1 suggested that our model could accurately reproduce established findings on daily fluctuations in cortisol levels (both on the group level and the individual level). Results from Study 2 suggested that our model could accurately reproduce established findings on the relationship between work stress and cardiovascular disease. Finally, results from Study 3 yielded new predictions about the relationship between workweek configurations (i.e., how working hours are distributed over days) and the subsequent development of disease. Together, our studies suggest a new, computational approach to studying the causal link between work stress and disease. We suggest that this approach is fruitful, as it aids the development of falsifiable theory, and as it opens up new ways of generating predictions about why and when work stress is (un)healthy.
This item appears in the following Collection(s)
- Academic publications [244127]
- Electronic publications [131105]
- Faculty of Social Sciences [30028]
- Open Access publications [105145]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.