Department of Mathematics and Computer Science

Personalized medicine is transforming medical counseling by introducing the need for effective communication of evolving, individualized risks (1). Tools like iKNOW (2, 3), an evidence-based digital counseling tool, are designed to support women with hereditary cancer risks, particularly those with an increased likelihood of developing breast and ovarian cancer. Unlike one-time measures for therapy decisions, personalized risks evolve over a lifetime, requiring different actions at various stages. Physicians must clearly explain these dynamic risks, while patients need to understand when and which measures are recommended to mitigate their risk of illness.

The design of user interfaces that communicate risk graphics can play a crucial role in helping both physicians and patients understand and address these evolving risks. This ultimately supports preference-sensitive health decisions and advances personalized medicine.

Therefore, the goal of this thesis is to investigate how cumulative risks, which change over time, can be effectively communicated. While icon arrays are validated for static risks, there is currently no evidence supporting their use for dynamic, time-evolving risks. Would a timeline diagram, icon arrays at specific time points, or a combination of both be the most effective way to convey these risks?

General Research Process

• Understand the Research Context and Objectives
  Conduct a thorough review of the research domain, focusing on cumulative risk visualization and its challenges. Clearly define the goals and scope of the thesis.
• Develop Approaches for Cumulative Risk Visualizations
  Based on existing research and best practices, design multiple approaches for visualizing cumulative risks. Ensure the designs align with the principles of effective risk communication.
• Create a High-Fidelity Prototype
  Develop a high-fidelity prototype of the existing user interface and incorporate the newly designed risk visualizations. Ensure the prototype is functional and user-friendly, ready for testing.
• Conduct a Between-Subjects Design Study
  Design and execute an empirical study using a between-subjects design to evaluate the effectiveness of the different visualization approaches. Recruit participants and ensure ethical guidelines are followed.
• Analyze Results
  Perform qualitative and quantitative analyses of the study results to assess the impact of the visualizations on users’ understanding, trust, and decision-making. Identify key insights and implications for future research.

References

1. Speiser, D., Heibges, M., Besch, L., Hilger, C., Keinert, M., Klein, K., Rauwolf, G., Schmid, C., Schulz-Niethammer, S., Stegen, S., Westfal, V., Witzel, I., Zang, B., Kendel, F., & Feufel, M. (2023). Paradigmatic approach to support personalized counseling with digital health (iKNOW). JMIR Formative Research, 7, e41179. https://doi.org/10.2196/41179
2. Feufel, M. A., Rauwolf, G., Hartmann, T., Kendel, F., & Speiser, D. (2023). Personalisierte Risiken verständlich kommunizieren: Wie digitale Formate die Kommunikation unterstützen können. Forum, 38(5), 393–396. https://doi.org/10.1007/s12312-023-01243-3
3. Feufel, M. A., Speiser, D., Schüürhuis, S., Neumann, K., Keinert, M., Stegen, S., Rauwolf, G., Heibges, M., Westfal, V., Besch, L., Olbrich, C., Klein, K., Witzel, I., & Kendel, F. (2024). iKNOW—Supporting the counseling of women with hereditary risk of breast and ovarian cancer with digital technologies: A randomized controlled trial. Genetics in Medicine Open, 2(Suppl 2), 101892. https://doi.org/10.1016/j.gimo.2024.101892
4. Fansher, M., Walls, L., Hao, C., Subramonyam, H., Boduroglu, A., Shah, P., & Witt, J. K. (2025). Narrative visualizations: Depicting accumulating risks and increasing trust in data. Cognitive Research: Principles and Implications, 10(7). https://doi.org/10.1186/s41235-025-00613-w