Kallio, J.; Vildjiounaite, E.; Kantorovitch, J.; Kinnula, A.; Bordallo López, M. Unobtrusive Continuous Stress Detection in Knowledge Work—Statistical Analysis on User Acceptance. Sustainability 2021, 13, 2003. https://doi.org/10.3390/su13042003
Unobtrusive continuous stress detection in knowledge work-statistical analysis on user acceptance
|Author:||Kallio, Johanna1; Vildjiounaite, Elena1; Kantorovitch, Julia2;|
1Knowledge Intensive Products and Services, VTT Technical Research Centre of Finland Ltd., Kaitoväylä 1, FI-90571 Oulu, Finland
2Data Intensive Economy, VTT Technical Research Centre of Finland Ltd., Tekniikantie 21, FI-02150 Espoo, Finland
3Faculty of Information Technology and Electrical Engineering, University of Oulu, Pentti Kaiteran katu 1, FI-90570 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021041910823
Multidisciplinary Digital Publishing Institute,
|Publish Date:|| 2021-04-19
Modern knowledge work is highly intense and demanding, exposing workers to long-term psychosocial stress. In order to address the problem, stress detection technologies have been developed, enabling the continuous assessment of personal stress based on multimodal sensor data. However, stakeholders lack insights into how employees perceive different monitoring technologies and whether they are willing to share stress-indicative data in order to sustain well-being at the individual, team, and organizational levels in the knowledge work context. To fill this research gap, we developed a theoretical model for knowledge workers’ interest in sharing their stress-indicative data collected with unobtrusive sensors and examined it empirically using structural equation modeling (SEM) with a survey of 181 European knowledge workers. The results did not show statistically significant privacy concerns regarding environmental sensors such as air quality, sound level, and motion sensors. On the other hand, concerns about more privacy-sensitive methods such as tracking personal device usage patterns did not prevent user acceptance nor intent to share data. Overall, knowledge workers were highly interested in employing stress monitoring technologies to measure their stress levels and receive information about their personal well-being. The results validate the willingness to accept the unobtrusive, continuous stress detection in the context of knowledge work.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
3141 Health care science
This research was funded by Business Finland under ITEA 18033 Mad@Work, grant number 2991/31/2019.
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).