Design and implementation of a mobile application for data collection to identify early warning signs of relapse in patients diagnosed with schizophrenia

This paper explores the use of mHealth technologies to support the treatment of schizophrenia. Its main goal is to design and implement the frontend part of the ITAREPS (Schizophrenia Relapse Prevention System) on an iOS platform that will be used to collect subjective data from schizophrenia patients, which is crucial for recognizing early warning signs indicating relapse. The MMSP methodology for smaller software projects was chosen as the initial methodological framework. The MVVM architecture and the SwiftUI user interface were used for the actual implementation of the application. Validation of the implemented application was performed in the form of user testing with the target users, i.e., patients diagnosed with schizophrenia, in combination with the completion of a satisfaction questionnaire regarding the tested application and its functionalities. The user testing resulted in positive feedback on the graphical design of the application and the intuitiveness of using its functions, along with the discovery of minor shortcomings related to the UX of the application.