[en] Objective This proof-of-concept shows how the process of therapeutic change can be supported by personal electronic devices. By following the daily ups and downs of symptom strength and mood-related variables, we demonstrate the feasibility of constructing an idiographic psychological system model in the case of an adolescent outpatient of a day treatment clinic. Method We created an R-based shiny application that directly analyses the incoming data of key psychosomatic and psychological symptoms of the patient. Both patient and therapist have access to the visualized results of the online-analysis and use the application for therapeutic feedback sessions (e.g. Schiepek et al. (2016)). Result We compare the results of network models that are based on classical vector-auto regression to recurrence quantification analysis and evaluate their use in supporting the therapeutic change process. We also conduct online p-factor analysis and show, how the cross-lagged relationships of the latent factors can be valuable feedback to the patient. Conclusion By making subsequent use of daily online monitoring patient and therapist gained new insights into the mental network structure and the relating state-dynamics. The case study shows how the analysis of time-series data can provide a plausible insight into the mental structure of a patient and how the developed open source application can be used to relate to the patients’ state, cognitions, emotions and behaviour.