The course is intended to introduce central socioeconomic theories and methods from a multidisciplinary perspective. The topic of health is integrally treated from the perspective of different socioeconomic disciplines (such as sociology, economics, and demography). 

The following content areas will be covered:

• Health indicators
• Socioeconomic grading in health
• Health systems
• Health behaviors
• Health equity

The focus is on the application of these theories and methods. The course will include a progressive introduction to the statistical software for statistical analysis Stata, which the students will use to analyze survey data throughout the semester. In addition, the students will work in groups to develop and analyze their own research question under the guidance of the lecturers.

IMPORTANT

You will need to bring your own laptop to all sessions to be able to perform the in-class exercises and to take part in the mid-term examination.

After completing this course, students should be able to:

• Understand, classify and evaluate central socioeconomic theories and methods
• Recognize the multi-dimensionality of problem situations in health research
• Adapt socioeconomic theories and methods to specific fields of application and to apply them to specific socioeconomic questions
• Examine and develop integrative research designs

This course also supports the following skills:

• Analyze survey data using various Stata commands
• Apply relevant research designs to identify causal effects
• Work in a team environment and give oral presentations

Full attendance is expected in PI courses. A minimum of 80% attendance of contact hours is required. This is essential for continuous and in-depth exchange within your respective groups as well as for contributing to discussions across all projects. In case online units are scheduled, the same attendance requirements apply. If you are unable to fully attend a unit, please let the lecturer(s) know in advance.

• Interactive lectures with a critical reflection of relevant literature on theories and methods
• Computer-based exercises using survey data
• Group discussions to develop an integrative research design
• Student presentations

Assessment Components (relative weights in the final grade)

• Mid-term exam (40%)
• Final group presentation (40%)
• Participation (20%)

Grades (point ranges)

• 1: Excellent (90-100 points)
• 2: Good (80-89 points)
• 3: Satisfactory (65-79 points)
• 4: Sufficient (50-64 points)
• 5: Fail (0-49 points)

Please note:

• AI tools may be used for brainstorming and preparation for written assignments and presentations. The use of AI tools for results, discussion, and reflection is prohibited; these are the students' own work. AI output cannot be used as evidence for content-related claims; it must be substantiated with scientific literature.
•  All AI tools used must be listed in the resource directory. The entry in the resource directory must include: tool, search string, generated result string, date of search/interaction.
• The unauthorized use of AI tools or missing evidence is considered an attempt at fraud or plagiarism and triggers an oral re-examination.

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