The interdisciplinary course "Digital Health Psychology" is designed for students of psychology and medical engineering. Current issues from the fields of digital health and stress research are addressed in groups. The goal of this research-oriented course is to strengthen the cooperation between the individual disciplines in order to make optimal use of mutual synergy effects.

Students will use their individual skills learned during their studies in interdisciplinary teams to benefit from each other. In addition to the planning and execution of a research question as well as analysis of the results in groups, there will also be teaching units of the different disciplines during the semester (psychology: theoretical models and biological basis of stress, hypothesis-driven planning and execution of experiments, collection of biomarkers and their evaluation in the laboratory, inferential statistics; medical engineering: data analysis in Python, acquisition and processing of physiological signals, basics of machine learning). In addition, fundamentals of scientific work and research data management are taught. Topics covered include:

• Overview of current issues in the field of machine learning and data analysis for stress research.
• Best practices for presenting and writing up scientific results
• Best practices for hypothesis-driven design and implementation of experimental and field studies