Numerous studies have shown: Mobile apps can help detecting mental health disorders and increase well-being. Together with several well-known universities and high-level partners, we started our own research projects in order to validate and constantly improve our digital product Moodpath.
Moodpath is based on the concept of cognitive behavioral therapy and was developed with experienced therapists and doctors. Additionally, researchers from the fields of psychology and psychotherapy conduct clinical studies to continuously validate the app.
Not only do we validate Moodpath from its professional and technical point of view, we also make sure that it is easily integrated into the everyday life of the users. To achieve that, we work closely with design and product experts and listen carefully to the feedback of users, patients and therapists.
"The open research platform, which is created with the help of Moodpath users, provides scientists with new insights into individual courses of depression and connections between experienced situations, emotions, and symptoms."
Prof. Dr. Johannes Zimmermann Psychologische Hochschule Berlin
Our primary research focus is the detection of depressive episodes. These are some of our current studies:
We collaborated with members of the chair for Clinical Psychological to validate a pilot version of the app. The study was conducted with a clinical sample and with a second sample consisting of students. The encouraging results regarding the intensity of usage and specificity were presented at a conference for clinical psychology and psychotherapy in 2017. Furthermore, we work together with other partners to validate the Moodpath screening.
In cooperation with Prof. Henrik Walter, we are planning a study on risk factors of mental disorders in which the concept of resilience will be investigated at different levels.
With Prof. Sandra Matz, we are planning to conduct a research project that examines if sensor data of smartphones can be helpful to detect symptoms of depression as well as to evaluate and individualize psychological interventions. The collected data is supposed to be used – assisted by machine learning algorithms – in order to improve the detection and alleviation of symptoms.
In collaboration with Prof. Johannes Zimmermann, we constantly optimize our depression screening. We want to improve its sensitivity and specificity as well as the methodical foundation to build better structure models. The improved models are supposed to facilitate insights from various symptoms and symptom classes with regards to the structural composition of a depression.
Our aim is to evaluate our products scientifically and to improve research on depression. Therefore, we have established our own online research platform that provides scientists with our anonymized data. Are you interested in the platform and our research? Then write to us: email@example.com