Accepted for/Published in: JMIR Formative Research
Date Submitted: Apr 7, 2022
Date Accepted: Sep 22, 2022
Date Submitted to PubMed: Oct 20, 2022
Stressors and De-stressors in Working from Home based on Context and Physiology from Self-reports and Smartwatch Measurements: International Observational Study Trial
ABSTRACT
Background:
Stress levels among the global population have been rising for years. With the COVID-19 pandemic, this level has risen further with the addition of teleworking to the normal way of working. To manage stress levels in employees working from home, we need to gain insights into the stressors and de-stressors in a home office. We present an international remote study in employees working from home by making use of the advanced technology (smartwatches and questionnaires through smartphones) from this era.
Objective:
The main objective of this study was to determine the stressors and de-stressors in people working from home. The secondary objective was to determine smartwatch measurements that could represent these stressors and de-stressors.
Methods:
Employees working from home from 3 regions of the world (United States, United Kingdom, and Hong Kong) were asked to wear a smartwatch continuously for 7 days, fill in 5 daily questionnaires during this week and two additional questionnaires before and after the measurement week. The entire study was done remotely.
Results:
A total of 202 people participated, with 198 participants finishing the experiment. Stressors found are other people and daily life getting in the way of work (P=.05), job intensity (P=.007), a history of burn-out (P=.03), anxiety towards the pandemic (P=.04) and environmental noise (P=.008). De-stressors found are access to sunlight (P=.02) and fresh air (P<.001) during the workday and going outdoors (P<.001), having breaks (P<.001), exercising (P<.001), and having social interactions (P<.001). The smartwatch measurements positively related to stress were number of active intensity periods (P<.001), number of highly active intensity periods (P=.04), steps (P<.001) and the standard deviation in heart rate (P<.001). Stress prediction models based on questionnaire data had similar performance (F1=.51) than models based on automatic measurable data alone (F1=.47).
Conclusions:
The results show that there are stressors and de-stressors when working from home that should be taken into account when managing stress in employees. Some of these stressors and de-stressors are (in)directly measurable with unobtrusive sensors, and prediction models based on this data show promising results for the future of automatic stress detection and management. Clinical Trial: trialregister.nl NL9378
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.