Developing a recommender system artifact for patient tailored therapy in the COPE project

Abstract

Mental health disorders affect people from all over the world of all ages. Depression is of the most common mental health problems and is commonly experienced by women during and after breast cancer treatment. Cognitive Behavioral Therapy (CBT) is a therapy form that has been proven effective in treating symptoms of depression. While CBT has traditionally been given face-to-face with a therapist, Internet-based CBT (iCBT) has shown higher efficiency, without the cost of efficacy. Self-guided iCBT provides an inexpensive alternative of treatment as it does not require a therapist involved, leading to better scaling. It has not shown the same effectiveness and user adherence. This project is part of a larger research project called COPE aiming at providing self-guided iCBT to breast cancer patients in a patient tailored and more efficacious manner. This thesis examines the possibility of integrating the advantages of a therapist guided iCBT into a self-guided iCBT application. An artifact was designed and developed through the method of design science, in an effort to make self-guided iCBT personalized. The artifact is a recommender system that uses content and patient data to recommend the most suited therapy content, as well as a simulation tool for insight and evaluation.