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.
翻译:在本文中,我们介绍了利用来自患有双极障碍的个人的数据进行N=1案例研究,用N=1案例研究来说明的个人财务数据收集和分析个人财务数据以及精神健康因素的新研究方法。虽然我们尚未发现具有统计意义的趋势,而且我们的调查结果除此案例之外也没有普遍适用,但我们的方法提供了对获取客观财务数据的挑战的洞察力。我们概述了目前可获得哪些数据,可用哪些数据来做哪些工作,以及在处理财务数据时需要考虑哪些因素。更具体地说,使用这些方法,研究人员也许能够在个人财务数据中发现精神疾病症状的症状,例如确定预警信号,从而能够对患有严重精神疾病的人进行预防性护理。基于这项工作,我们还探索了制定支持财务福利的干预措施的未来方向。此外,我们还介绍了金融数据驱动评估和干预方法的技术、伦理和公平挑战,并提供了应对这些挑战的广泛研究议程。通过利用客观、个人化的财务数据来保护隐私和道德,有助于心理健康的转变。