Robin Gulseth
PhD fellow at University of Bergen
Robin Gulseth has an academic background in political science. He holds a Bachelor in comparative politics from the University of Bergen and a Master of Science in political science with specialization in international relations, diplomacy and conflict studies from Copenhagen University. Gulseth has professional experience as an analyst in market research and a research consultant in the health sector. He is now working on a three-year PhD project intended to investigate predictive models of treatment outcomes within the context of internet-based cognitive behavioral therapy (iCBT) in mental health care, using digital phenotyping as a guiding framework.
Tell us about your project!
The project has a planned three-stage development. The proposal is to first review and synthesize current evidence and practices of digital phenotyping within the field of digital mental health. Second, the project aims to determine which digital features, and methodological approaches can predict treatment outcomes at an early stage in digital mental health interventions using existing empirical retrospective data. In this process, key behavioral and clinical predictors of treatment response will be identified, which again will be used to develop empirically grounded models. Thirdly, the project will apply developed models on prospective naturalistic intervention data for validation to ensure predictions are accurate and fair in unseen data. In the future such models have the potential to enhance personalization, improving clinical decision support, and guiding policy decisions on the implementation of digital mental health services.
“ I am working on a three-year PhD project intended to investigate predictive models of treatment outcomes within the context of internet-based cognitive behavioral therapy (iCBT) in mental health care, using digital phenotyping as a guiding framework.”
— Robin Gulseth on his PhD project “Digital phenotyping in mental health care: Developing predictive models to inform personalized digital treatment”