Endometriosis is a chronic disease characterized by the presence of uterine lining (endometrial)-like tissue outside the uterus. Endometriosis-related complaints, such as pain, have a huge impact on the quality of life of these women. There is a need for a reliable way of assessing symptoms with co-occurring factors as a large number of women continue to suffer from chronic pain despite medical treatment. This thesis describes the development of an endometriosis-specific smartphone app that is based on the experience sampling method (ESM) for real-time symptom assessment over time. The ESM provides real-life insight into physical, mood-related, and environmental factors, and measuring fluctuations of these symptoms could provide insight into sickness behaviour. Analysing direct associations could give clues for individualized treatment options which could reduce symptom burden. Furthermore, ESM is highly suitable to accurately evaluate the effect of new treatment options and behavioural therapies. In this thesis it is hypothesized that giving self-insight in symptoms could induce patient empowerment in clinical care in the future and will improve health outcomes.
|Award date||21 Apr 2022|
|Place of Publication||Maastricht|
|Publication status||Published - 2022|
- experience sampling method