publications

2026

1. Following the Money: How Financial Data Can Transform Mental Health Research and Care

   Saeed Abdullah, Mark Matthews, Jeff Brozena, and 5 more authors

   Psychiatric Services, 2026

   Abs

   Money is deeply intertwined with mental health, yet financial behavior remains largely absent from mental health assessment and interventions. The authors argue that financial data represents an untapped opportunity for mental health support. Toward this vision, this article addresses three questions: Can financial behavior be measured objectively? Would patients share such data? Are there clinically meaningful signals? Recent studies involving over 1,000 individuals with bipolar disorder demonstrate feasibility through open banking, broad acceptability, and preliminary evidence linking spending to mood states. Building on these findings, the authors discuss the potential for clinical integration and interventions while outlining responsible development of this emerging field.

2. A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health

   Oluwadara Adedeji, Michael Mayowa Farayola, Jeff Brozena, and 3 more authors

   2026

   Abs

   Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory requirements and system-level verification. This challenge is particularly acute in digital phenotyping, where continuous behavioural data raises concerns around consent, privacy, and fairness. In this paper, we propose a computational ethical framework for AI-driven digital phenotyping system in which ethical requirements are formalised as deontic temporal logic constraints, alongside a conceptual ethical agent that oversees the system and ensures that any supervised system satisfies the specified constraints. Using a case study involving financial data and mental health, we model key ethical properties and verify them using the Z3 Satisfiability Modulo Theories (SMT) solver. Our evaluation shows that the framework is logically consistent and that violations of the specified ethical properties are ruled out within the formal model through counterexample-based verification. This presents early research enabling continuous, machine-verifiable ethical checking, moving beyond retrospective compliance based on static documentation. We discuss limitations, including the need for real-world verification with data, the challenge with subjectivity and contextual sensitivity, the need for human oversight, and outline how such approaches can support the development of AI systems with continuous and auditable ethical guarantees.

3. Money and Mental Health: A Scoping Review of Financial Variables, Data Sources, and Analytical Methods

   Oluwadara Adedeji, Andreas Balaskas, David Coyle, and 2 more authors

   Frontiers in Public Health, 2026

   Abs

   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 characterise 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. 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. 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. 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). 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.

4. Manifestations of Mood in Money: Unravelling Financial Behaviours for Passive Assessment in Bipolar Disorder

   Oluwadara Adedeji, John Olusegun, Keith Gaynor, and 1 more author

   2026

   Abs

   Mood and money are closely intertwined in bipolar disorder (BD), yet it remains unclear whether financial behaviour provides reliable mood-contingent signals, and it is largely absent from digital phenotyping research. Advances in open banking enable objective, passive measurement of financial behaviour at scale. We conducted semi-structured interviews with 19 (11 UK, 4 Ireland, 4 Nigeria) adults with BD to examine how mood manifests in financial behaviour, identify potential financial mood markers, and explore data-sharing preferences. Participants reported distinct mood-related changes in spending and reciprocal effects of money on mood. Three themes emerged: (i) symptomatic drivers shaped by credit access, seasonality, and social context; (ii) candidate markers such as transaction frequency, timing, category, and amount; and (iii) conditional willingness by most participants to share data influenced by privacy, anonymity, and granularity. High-mood spending reflected goal pursuit, generosity, and insomnia, while depression involved both reduced spending and retail therapy, challenging simple bidirectional assumptions. These findings provide empirical insight into financial data as a potential mood marker and inform future research and privacy-sensitive data collection.

2025

1. Money and Mental Health: Spending as a Mental Health Indicator - Psychological, Behavioral, Economic Perspectives and Data Collection

   Oluwadara Adedeji, John Olusegun, and Mark Matthews

   2025

   Abs

   Symptomatic financial behavior in bipolar disorder can increase stress, worsen symptoms, and hinder recovery. While spending sprees signal high mood states, research on personal experiences remains limited. This study explores mood-spending dynamics through semi-structured interviews in Ireland and Nigeria (N=5, projected N=10), assessing geo-economic influences and data-sharing preferences for future research. Participants reported varied impulsive spending patterns and emphasized privacy, security, and transparency in financial data sharing. These findings highlight the need for protective financial technologies for vulnerable individuals.

2022

1. Image Augmentation for Satellite Images

   Oluwadara Adedeji, Peter Owoade, Opeyemi Ajayi, and 1 more author

   2022

2021

1. 6G Enabled Smart Infrastructure for Sustainable Society: Opportunities, Challenges, and Research Roadmap

   Agbotiname Lucky Imoize, Oluwadara Adedeji, Nistha Tandiya, and 1 more author

   Sensors, 2021

   Abs

   The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications. To address this problem, researchers are developing cutting-edge technologies for the envisioned 6G wireless communication standards to satisfy the escalating wireless services demands. Though some of the candidate technologies in the 5G standards will apply to 6G wireless networks, key disruptive technologies that will guarantee the desired quality of physical experience to achieve ubiquitous wireless connectivity are expected in 6G. This article first provides a foundational background on the evolution of different wireless communication standards to have a proper insight into the vision and requirements of 6G. Second, we provide a panoramic view of the enabling technologies proposed to facilitate 6G and introduce emerging 6G applications such as multi-sensory–extended reality, digital replica, and more. Next, the technology-driven challenges, social, psychological, health and commercialization issues posed to actualizing 6G, and the probable solutions to tackle these challenges are discussed extensively. Additionally, we present new use cases of the 6G technology in agriculture, education, media and entertainment, logistics and transportation, and tourism. Furthermore, we discuss the multi-faceted communication capabilities of 6G that will contribute significantly to global sustainability and how 6G will bring about a dramatic change in the business arena. Finally, we highlight the research trends, open research issues, and key take-away lessons for future research exploration in 6G wireless communication.