A Visual Analytics Dashboard for Mental Health Therapists

Abstract

Mental health disorders are a significant problem throughout the western world. Cognitive Behavioral Therapy (CBT) is a common treatment form for these disorders. Internet-based Cognitive Behavioral Therapy (iCBT) provides higher efficiency than face-to-face CBT, without reducing the efficacy of the treatment. While iCBT has been shown to work well on a small scale, the amount of data each therapist need to consider, grows rapidly with the number of patients. This thesis examines the data used for iCBT, and presents possible solutions for gaining overview of this data through visual analytics and dashboard techniques. We designed and developed an artifact through the design science methodology, in order to implement these techniques. The main evaluation of the artifact consisted of semi-structured interviews with experts in psychology and psychiatry. We present methods for automatic processing of standardized mental health screening questionnaires, as well as a novel way of visualizing these questionnaires over time. We also discuss the scalability of a dashboard application using the HL7 FHIR standard for representing screening questionnaires and numerical observational data. Finally, we present identified problems and further work on structuring data for analytics in iCBT.