ArticleProceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences2020
Objective Measurement of Physician Stress in the Emergency Department Using a Wearable Sensor.
Article in Proceedings of the ... Annual Hawaii International Conference on System Sciences. Annual Hawaii International Conference on System Sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Mental health monitoring in the workplace using artificial intelligence: A scoping review.PLOS digital health · 2026Article
- Reliability Assessment of Wearable Technologies for Physiological Measurements: An Evaluation of Shimmer3 GSR+, Empatica E4, EmbracePlus, and Pixel Watch 2 Across Cognitive, Affective and Physical Activity Tasks.Sensors (Basel, Switzerland) · 2026Article
- Electrocardiogram-Based Mental Stress Detection Amid Everyday Activities Using Machine Learning: Model Development and Validation Study.Journal of medical Internet research · 2026Article
- Article
- Stress and Emotion Open Access Data: A Review on Datasets, Modalities, Methods, Challenges, and Future Research Perspectives.Journal of healthcare informatics research · 2025Review
- From lab to real-life: A three-stage validation of wearable technology for stress monitoring.MethodsX · 2025Article
- Article
- Physician Burnout: Evidence-Based Roadmaps to Prioritizing and Supporting Personal Wellbeing.Journal of healthcare leadership · 2024Review
- Effect of music therapy intervention on anxiety and pain during percutaneous renal biopsy: a randomized controlled trial.Clinical kidney journal · 2023Article
- A Method for Stress Detection Using Empatica E4 Bracelet and Machine-Learning Techniques.Sensors (Basel, Switzerland) · 2023Article
- Applying machine learning to explore the association between biological stress and near misses in emergency medicine residents.PloS one · 2022Article
- Pain and Stress Detection Using Wearable Sensors and Devices-A Review.Sensors (Basel, Switzerland) · 2021Review
- Digital Health Interventions for Mental Health, Substance Use, and Co-occurring Disorders in the Criminal Justice Population: A Scoping Review.Frontiers in psychiatry · 2021Article
- Job Demands and Resources among Healthcare Professionals during Virus Pandemics: A Review and Examination of Fluctuations in Mental Health Strain during COVID-19.Applied psychology = Psychologie appliquee · 2021Article
- Article
- Wearable sensor-based detection of stress and craving in patients during treatment for substance use disorder: A mixed methods pilot study.Drug and alcohol dependence · 2020Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Physician stress, and resultant consequences such as burnout, have become increasingly recognized pervasive problems, particularly within the specialty of Emergency Medicine. Stress is difficult to measure objectively, and research predominantly relies on self-reported measures. The present study aims to characterize digital biomarkers of stress as detected by a wearable sensor among Emergency Medicine physicians. Physiologic data were continuously collected using a wearable sensor during clinical work in the emergency department, and participants were asked to self-identify episodes of stress. Machine learning algorithms were used to classify self-reported episodes of stress. Comparing baseline sensor data to data in the 20-minute period preceding self-reported stress episodes demonstrated the highest prediction accuracy for stress. With further study, detection of stress via wearable sensors could be used to facilitate evidence-based stress research and just-in-time interventions for emergency physicians and other high-stress professionals.
Identifiers
32015695PMC6996921What OpenQuestion holds
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.