Digital Support for Detection and Treatment of Depression

Thesis (BA/MA)

Advisor(s): Philipp Reindl-Spanner (philipp.spanner@tum.de) / Barbara Prommegger (barbara.prommegger@tum.de)

CONTEXT

With an ageing society and the increasing prevalence of multimorbidity (two or more chronic conditions occurring simultaneously in a patient), the prevalence and complexity of mental illness are increasing. Depression is the most common diagnosis. General practitioners (GPs) play an important role in the care of patients with depression, as they make the initial diagnosis and are responsible for treatment. The detection and treatment of depression presents GPs with special challenges. Somatic comorbidities (presence of one or more additional conditions with a primary condition in a patient) can mask a depression and make it difficult to select a suitable therapy and implementation, endangering both the success of the therapy and the safety of the depression treatment.

The main goal of this study is to find ways of supporting GPs and patients through the usage of IT systems to improve the diagnosis and treatment of depression. From this context several questions arise which can be addressed in theses. What is the current state of scientific literature regarding this topic (especially regarding data usage)? What are current IT enabled solutions that monitor patients’ mental health? Which Stakeholders arise in a digital patient-practitioner-environment? What are possible solutions to help visualize patient generated data for GPs?

The aforementioned as well as several similar questions can serve as a foundation for your student thesis (BA/MA/Guided Research). The activities during the preparation of the work include literature analysis, the compilation of research questions, conduction of the research, deriving the findings and creation and evaluation of digital artifacts.

TASK(S)

  • Literature analysis
  • Qualitative analysis (interviews, case study research etc.) or quantitative analysis (survey research, archive data, public data, etc.).

REQUIREMENTS

  • High degree of autonomy and responsibility
  • Interest in current IS topics with medicinal related focus
  • Experience in & willingness to learn about scientific writing
  • Structured, reliable & self-motivated work style

FURTHER INFORMATION

The thesis can be written in English or German. The topic can also be adapted to your interests. If you have further questions, please do not hesitate to contact me directly. Please send your application including our specific application form, a current transcript of records and your CV to philipp.spanner@tum.de. Please also note that we can only consider applications with complete documents.