ArticleNPJ digital medicine2019
Unlocking stress and forecasting its consequences with digital technology.
Article in NPJ digital medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04713111 (Stress and Recovery in Frontline Healthcare COVID-19 Workers), which is not on this map. Cited by 20 papers.
What it found
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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.
Stress and Recovery in Frontline Healthcare COVID-19 Workers: A Feasibility Study Using Wearable and Smartphone Devices
Who cites it
20 citing papers in PubMed.
- Mental health monitoring in the workplace using artificial intelligence: A scoping review.PLOS digital health · 2026Article
- Digital Health Tools Embedded in a Cancer Genetics Clinic: Observational Study.JMIR formative research · 2026Observational
- Patient-centered modeling of the breast biopsy experience.Frontiers in artificial intelligence · 2025Article
- Novel Deep Learning-Based Vocal Biomarkers for Stress Detection in Koreans.Psychiatry investigation · 2024Article
- Facilitators of and Barriers to Teachers' Engagement With Consumer Technologies for Stress Management: Qualitative Study.Journal of medical Internet research · 2024Article
- Stress and cardiovascular disease: an update.Nature reviews. Cardiology · 2024Review
- Dissecting the heterogeneity of "in the wild" stress from multimodal sensor data.NPJ digital medicine · 2023Article
- Digital Phenotyping: Data-Driven Psychiatry to Redefine Mental Health.Journal of medical Internet research · 2023Article
- The promises and challenges of clinical AI in community paediatric medicine.Paediatrics & child health · 2023Article
- Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.JMIR mHealth and uHealth · 2022Article
- Inducing and Recording Acute Stress Responses on a Large Scale With the Digital Stress Test (DST): Development and Evaluation Study.Journal of medical Internet research · 2022Article
- Optimizing Social Support in Oncology with Digital Platforms.JMIR cancer · 2022Article
- Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum.NPJ digital medicine · 2022Review
- Article
- An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study.JMIR formative research · 2021Article
- Stress-related consequences of the coronavirus disease 2019 pandemic on symptoms of Crohn's disease.European journal of gastroenterology & hepatology · 2021Article
- The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2021Article
- Psychological stress in heart failure: a potentially actionable disease modifier.Heart failure reviews · 2021Review
- What Are We Measuring When We Evaluate Digital Interventions for Improving Lifestyle? A Scoping Meta-Review.Frontiers in public health · 2021Article
- Digital Phenotyping: an Epistemic and Methodological Analysis.Philosophy & technology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic stress is a major underlying origin of the top leading causes of death, globally. Yet, the mechanistic explanation of the association between stress and disease is poorly understood. This stems from the inability to adequately measure stress in its naturally occurring state and the extreme heterogeneity by inter and intraindividual characteristics. The growth and availability of digital technologies involving wearable devices and mobile phone apps afford the opportunity to dramatically improve measurement of the biological stress response in real time. In parallel, the advancement and capabilities of artificial intelligence (AI) and machine learning could discern heterogeneous, multidimensional information from individual signs of stress, and possibly inform how these signs forecast the downstream consequences of stress in the form of end-organ damage. The marriage of these tools could dramatically enhance the field of stress research contributing to impactful and empowering interventions for individuals bridging knowledge to practice, and intervention to real-world use. Here we discuss this potential, anticipated challenges, and emerging opportunities.
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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.