ArticleInternational journal of environmental research and public health2020
Protocol of the STRess at Work (STRAW) Project: How to Disentangle Day-to-Day Occupational Stress among Academics Based on EMA, Physiological Data, and Smartphone Sensor and Usage Data.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Psychological resilience as a bridge between academic work stress and work engagement: evidence from Arab university faculty.Frontiers in psychology · 2026Article
- Machine learning-based detection of workplace stress using wearable and multimodal data: a systematic literature review.Frontiers in artificial intelligence · 2026Review
- Using wearable technology to evaluate the electrodermal activity of therapists assessing challenging behavior.Journal of applied behavior analysis · 2026Article
- Real-time monitoring of military health and readiness: a perspective on future research.Frontiers in digital health · 2025Article
- The feasibility and acceptability of using EMA and physiological data to measure day-to-day occupational stress, musculoskeletal pain and mental health.BMC research notes · 2024Article
- The association between day-to-day stress experiences and work-life interference among office workers in academia: an ecological momentary assessment study.International archives of occupational and environmental health · 2023Article
- Using EMA and Physiological Data to Explore the Relationship between Day-to-Day Occupational Stress, Musculoskeletal Pain and Mental Health among University Staff: A Study Protocol.International journal of environmental research and public health · 2023Article
- Article
- Sources of Occupational Stress among Office Workers-A Focus Group Study.International journal of environmental research and public health · 2022Article
- Assessing the Current Integration of Multiple Personalised Wearable Sensors for Environment and Health Monitoring.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Several studies have reported on increasing psychosocial stress in academia due to work environment risk factors like job insecurity, work-family conflict, research grant applications, and high workload. The STRAW project adds novel aspects to occupational stress research among academic staff by measuring day-to-day stress in their real-world work environments over 15 working days. Work environment risk factors, stress outcomes, health-related behaviors, and work activities were measured repeatedly via an ecological momentary assessment (EMA), specially developed for this project. These results were combined with continuously tracked physiological stress responses using wearable devices and smartphone sensor and usage data. These data provide information on workplace context using our self-developed Android smartphone app. The data were analyzed using two approaches: 1) multilevel statistical modelling for repeated data to analyze relations between work environment risk factors and stress outcomes on a within- and between-person level, based on EMA results and a baseline screening, and 2) machine-learning focusing on building prediction models to develop and evaluate acute stress detection models, based on physiological data and smartphone sensor and usage data. Linking these data collection and analysis approaches enabled us to disentangle and model sources, outcomes, and contexts of occupational stress in academia.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.