The quantified self in health

Health problems and the accompanying costs (healthcare, social, economic) are an ever increasing problem. The extremely high demands on the current care system ask for a new approach towards health. Sensor technology and smartphone applications offer novel opportunities to monitor and quantify physiological and psychological states over prolonged periods of time in the natural context of everyday life. This allows the generation of insights into the temporal dynamics in health (across days, weeks, months and years) and the antecedents of disturbances in health. Moreover, these technologies enable better diagnostics as well as the development of preventive measures or user-tailored interventions to promote health. In this course, we will particularly zoom into three domains: health in context, methodologies to monitor, model, and predict health in everyday-life situations, and ethical implications of these possibilities. The course offers lectures combined with assignments to provide students with advanced knowledge on - and hands-on experiences with - quantified self approaches. Quantified self approaches refer to the quantitative methods of obtaining self-knowledge through numbers by means of self-tracking, via mobile sensors or self-reports. In the current course, we will apply these methods to the health domain.

At the end of the course, students should be able to:

• explain the Quantified Self approach and data collection methodologies
• explain health concepts frequently studied with the Quantified Self approach
• explain statistical analyses for experience sampling data on a conceptual level and apply these analyses in Quantified Self research
• develop a proposal to apply Quantified Self methods in research
• understand and apply (basic) Machine Learning (ML) analyses on Quantified Self data
• make a critical assessment of Quantified Self research designs and outcomes, including ethical considerations

You must meet one of the following collections of requirements

• Collection 1
• Completed Final examination Bsc program
• Collection 2
• Completed Pre-Master

• Selected articles
• Mehl & Conner (2012) Handbook of Research Methods for Studying Daily Life
• Stata http://www.dpc-software.nl/ (Stata Corp LP)