Utilization of a Virtual Patient Model to Enable Tailored Therapy for Depressed Patients

Major depression is a prominent mental disorder that has significant impact upon the patient suffering from the depression as well as on the society as a whole. Currently, therapies are offered via the Internet in the form of self-help modules, and they have shown to be as effective as face-to-face counseling. In order to take automated therapies a step further, models which describe the development of the internal states associated with depression can be of great help to give dedicated advice and feedback to the patient e.g. by means of making predictions using the model. In this paper, an existing computational model for states related to depression (e.g. mood) is taken as a basis in combination with models that express the influence of various therapies upon these states. These models are utilized to give dedicated feedback to the patient, tailor the parameters towards the observed patient behavior, and give an appropriate advice regarding the therapy to be followed.