Money and mental health: a scoping review of financial variables, data sources, and analytical methods

Background The relationship between financial circumstances and mental health is well-established. New financial data sources such as bank transactions and digital payments offer new opportunities to better characterize this relationship. However, the prior financial data sources and analytical approaches have not been systematically reviewed. Understanding these is essential to guide future research and inform integrated interventions that address both financial and mental health outcomes. Objective This scoping review systematically maps the research on money and mental health, examining: (1) the financial variables and data sources used, (2) modeling methods employed, and (3) methodological gaps that novel objective data might address. Methods We systematically searched PubMed, PsycINFO, IEEE Xplore, ACM Digital Library, and Scopus. Papers were screened against predefined inclusion/exclusion criteria, and data extracted using a standardized spreadsheet. Analysis employed deductive coding guided by our research questions, refined iteratively through engagement with the data. PRISMA Extension for Scoping Reviews (PRISMA-ScR) was followed for reporting. Results Of the 43 included studies, most ( n = 34, 79%) examined mental health in connection with financial factors such as financial difficulty or financial strain, while a small number focused on predictive modeling with financial behavioral data ( n = 5, 12%), macroeconomic indicators ( n = 2, 5%), or intergenerational support between parent and child ( n = 2, 5%). Depression was the most common outcome ( n = 24, 56%), followed by anxiety, psychological distress, and bipolar disorder. Statistical methods dominated (77%), with 19% employing machine learning or deep learning. Ground truths relied predominantly on self-reported questionnaires—only four studies used objective financial data (three gambling records, one bank transaction). Conclusion This review reinforces the complex, bidirectional relationship between financial circumstances and mental health. Most studies examined how financial difficulty affects mental health, while only a few explored how mental illness influences financial behavior, indicating a clear research gap. There is substantial opportunity to use objective financial data and more diverse analytical methods, particularly machine learning, to deepen understanding of the relationship and interactions between money and mental health and inform targeted interventions.