Using the R programming language and the Shiny Framework, I developed a web application for the dynamic assessment of psychopathology. Using daily questionnaires concerning a person’s disorder, highly individualized disorder models can be derived. These models can help practitioners get a more in-depth understanding of their patients’ symptom dynamics. Also, interventions can be matched to the symptom structure so that they achieve maximum efficiency. A publication on these tools is available at JMI Medical Informatics.
Recently, other researchers expressed interest in using DynAMo for their research projects. While I am always happy about this, it is important to note that DynAMo can not be installed and maintained without knowledge in Unix/Linux server administration. It relies on running CRON jobs and reverse-forwarding to get SSL encryption. A tutorial on how to install and use the system will be published to this page in fall or winter of 2018. The code in its current state of development can be obtained from my GitHub repository.
The development of the data assessment module is nearly complete and currently undergoing a pilot phase. Features include:
The assessment module will also process the data acquired automatically so that the correlational and time-dependent structure of the psychopathology is uncovered. The steps are:
These steps prepare the data so that they can be processed by the data analysis module. It is be able to plot time-series data from day-to-day questionnaires, including additional plots that show phases of critical instability. Also, the treatment planning module will offer an overview over a patient’s symptom structure based on the models generated by an automated treatment planning algorithm called DATA. The aim is to offer a guideline to plan interventions that are fit to the patient’s individual psychopathology and promise maximum efficacy. It is currently undergoing empirical examination.