Login / Signup

Unlocking stress and forecasting its consequences with digital technology.

Sarah Margaret GooddayStephen Friend
Published in: NPJ digital medicine (2019)
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.
Keyphrases
  • artificial intelligence
  • machine learning
  • healthcare
  • big data
  • primary care
  • randomized controlled trial
  • heat stress
  • heart rate
  • social media
  • human health