Challenges in supporting social practices around personal data for long-term mental health management

Abstract

We discuss the importance of designing self-tracking technologies for serious mental illness (SMI) that allow individuals with SMI to collect, share, and sense-make over data with a dynamic set of support system members. Our collaborative work with individuals diagnosed with bipolar disorder has suggested the following design and technical challenges for supporting social practices around personal data in long-term mental health management: allowing for fine-grained control over data disclosure by individuals with SMI, supporting dynamism in relationships and roles over long-term use of a system, and allowing individuals flexibility in the variables that they self-track. We discuss these challenges and how they relate to the goals of predictive modelling and intervention in mental health personal informatics systems.