Supportive Fintech for Individuals with Bipolar Disorder: Financial Data Sharing Preferences for Longitudinal Care Management

Document Title

Supportive Fintech for Individuals with Bipolar Disorder: Financial Data Sharing Preferences for Longitudinal Care Management

Document Information

• Research Domain: Interdisciplinary study of fintech and mental health, focusing on financial data sharing preferences of individuals with Bipolar Disorder (BD) and its impact on longitudinal care management.
• Keywords: Fintech, privacy, mental health, bipolar disorder, data sharing, long-term care, financial stability

Research Background and Issues

• Problems and Challenges:

  • Individuals with bipolar disorder often exhibit impulsive spending or other risky financial behaviors during episodes, leading to financial instability and even bankruptcy risks.
  • Worsening financial issues can further lower self-esteem and exacerbate mental health problems.
  • While existing fintech solutions can support mental health management, little is known about the privacy preferences of individuals with bipolar disorder regarding financial data sharing.

• Significance:

  • Bipolar disorder is the sixth leading cause of disability worldwide, with significant psychological, social, and economic impacts.
  • Long-term financial stability is a critical component of managing the condition for individuals with bipolar disorder.

• Research Motivation and Related Work:

  • Financial data can be accessed in high granularity through Open Banking technology, enabling data-driven tools for managing long-term care.
  • Previous studies have explored the relationship between disease management and financial management, but there remains a research gap regarding privacy needs in different contexts.

Solution

• Research Methodology:

  • The authors designed a factorial experiment based on the Contextual Integrity (CI) framework and conducted an online survey to collect financial data sharing preferences from 480 individuals with bipolar disorder.
  • Three contextual variables were established: data recipients (self, family, clinicians), data usage (e.g., relapse prediction, analysis of mood and spending behavior), and data granularity (e.g., transaction time and amount, category).
  • The survey also included qualitative analysis of participants' current financial management strategies and their social support networks.

• Innovative Approach:

  • Systematically measured privacy preferences using the Contextual Integrity framework, revealing differences in acceptance of financial data sharing across contexts for individuals with bipolar disorder.
  • Combined quantitative and qualitative data to explore how privacy preferences vary across demographic groups (age, gender, marital status, etc.) and diagnostic categories.

• Implementation Steps:

  1. Participants completed questionnaires assessing comfort levels with financial data sharing in hypothetical scenarios.
  2. Collected descriptions of participants' financial management strategies.
  3. Applied quantitative statistical and qualitative analysis to identify key patterns in sharing preferences and demographic differences.

Research Findings

• Key Discoveries:

  • Overall, individuals with bipolar disorder showed openness to using financial data to support long-term management, particularly in self-management scenarios.
  • Data recipients significantly influenced privacy preferences, with participants most comfortable sharing data with themselves, followed by clinicians, and lastly family members.
    • Women were significantly less willing than men to share financial data with family, potentially due to risks related to financial control and gender dynamics.
  • Data granularity also affected sharing preferences, with de-identified data (e.g., only amount and time) being more acceptable.
  • Individuals with BD II were more willing to share data with clinicians compared to BD I patients; the lower willingness among BD I patients may be linked to paranoia.

• Individual Differences:

  • Younger and unmarried participants were more likely to refuse sharing data with family.
  • Married participants with children were more willing to share data with family members.

• Supplementary Qualitative Analysis:

  • Financial collaboration ranged from complete delegation to others to merely accepting financial advice, with collaboration methods often dynamically adjusted based on condition and context.
  • Collaboration involving family members frequently involved conflicts or negative emotions, such as the pressure of being monitored or loss of privacy.

• Design Implications:

  • Fintech designs should support flexible adjustments to meet patients' dynamically changing privacy needs and collaboration intentions.
  • Introduce features like data visualization and layered permissions, allowing patients to define data sharing scopes and usage goals.
  • Prioritize tools focused on self-management while providing tailored solutions for specific long-tail needs of different groups.

• Limitations and Future Directions:

  • The study population was primarily from high-income regions such as Europe and North America, potentially excluding the needs of individuals in low- and middle-income countries or those without linked financial accounts.
  • As the survey method was exploratory, future research should investigate clear causal relationships through further experiments.
  • Ethical challenges in financial collaboration need attention, particularly balancing assistance with avoiding potential financial misuse or control.