Disentangling the Relationship Between Stress and Sleep: A Data Fusion Project with Wearables and Ecological Momentary Assesment
Method Stream: Longitudinal Intensive Methods
ECs: Only 14 EC (standard, no new/own data collection. Applicable in case of a clinical internship)
Description:
Disentangling the causal relationship between sleep and stress remains a complex challenge, despite numerous studies showing strong correlations between the two. Does stress trigger sleep disturbances, or does poor sleep exacerbate stress? In this project, you will use Ecological Momentary Assessment, unobtrusive sleep monitoring via smartwatch, and cutting-edge statistical methods to explore this question. You will work with an existing dataset collected from medical residents in an intensive care unit, where participants were monitored over a three-week period and exposed to various acute stressors.
Who are we looking for?
We are looking for data-driven students eager to elevate their analytical skills and tackle complex real-world questions and data-fusion challenges.
What do we offer?
You will receive guidance on applying advanced statistical techniques and data processing methods. Due to the project’s complexity, you’ll collaborate closely with your supervisors and a fellow student who will also be working on the project.