Major depression is the most prevalent mental disorder and one of the main reasons for disability. To be successful in treating depression, it is necessary to have early identification and intervention. Therefore, it is important to design more objective and more efficient depression screening techniques. Such interventions provided by mobile apps shows promise due to their capabilities to support people in their everyday lives. Until very recently, the design of mental health apps that works effectively in the context of diagnostics had not been widely explored. For this reason, we have investigated potentially significant depression-correlated parameters derived from self reports, smartphone usage pattern and sensor data to specify our concept. Following the results of the requirement analysis, we developed the Android app ‘Fine’. A feasibility check with a specific target audience has shown that the app can record most of the selected parameters reliably. It has also shown that the overall concept has been accepted positively with the target audience. Further work is planned to improve the functionalities and to adapt specific needs for depression attendance.