Long COVID presents a wide variety of symptoms, making it challenging for patients to understand and manage their condition. Self-reflection enables patients to gain insight into their situation, allowing them to identify patterns and correlations that could help them maintain their well-being. However, effective self-reflection depends on the ability to collect sufficient and relevant data, which can be realized with self-tracking. For long COVID patients, maintaining motivation to consistently track their symptoms can be challenging.

Although numerous self-tracking apps are available, few are specifically tailored to the needs of long COVID patients. This thesis addresses this gap by proposing a design concept for a self-tracking application specifically for long COVID patients.

A Human Centered Design (HCD) approach is employed, gathering firsthand perspec- tives from patients, integrating these insights into the app design, and evaluating the concept with experts. The findings, the resulting design concept and the evaluation results are presented, providing a foundation for future work in enhancing self-tracking and self-reflection solutions for long COVID patients.