学术文献库

In this paper, we present novel research methods for collecting and analyzing personal financial data alongside mental health factors, illustrated through a N=1 case study using data from one individual with bipolar disorder. While we have not found statistically significant trends nor our findings are generalizable beyond this case, our approach provides an insight into the challenges of accessing objective financial data. We outline what data is currently available, what can be done with it, and what factors to consider when working with financial data. More specifically, using these methods researchers might be able to identify symptomatic traces of mental ill health in personal financial data such as identifying early warning signs and thereby enable preemptive care for individuals with serious mental illnesses. Based on this work, we have also explored future directions for developing interventions to support financial wellbeing. Furthermore, we have described the technical, ethical, and equity challenges for financial data-driven assessments and intervention methods, as well as provided a broad research agenda to address these challenges. By leveraging objective, personalized financial data in a privacy-preserving and ethical manner help lead to a shift in mental health care.