Pregnancy and the postpartum experiences represent transformative stagesof a woman’s life that, in some cases, are accompanied by mental health challenges. In the transition from pregnancy to postpartum, the focus shifts from the mother to the baby, potentially leaving the woman to feel alone andoverlooked in navigating the complex emotional and physical challenges of recovering from childbirth and caring for a small human. In this study, we argue that the mental health and well-being of a pregnant or postpartum woman is shaped by the level and type of supportive relationships they have(i.e, interpersonal versus healthcare provider) because such supportive relationships promote psychological energy required for their task. Using data from the 2025 Pregnancy Journey Survey, this study examines the association between having supportive interpersonal and healthcare provider relationships and the woman’s mental health, and whether these associations are mediated by the satisfaction of their basic psychological needs for competence, autonomy, and belonging.
Drawing on stress buffering and amplification frameworks, we used data from the Health and Retirement Study, a nationally representative population-based longitudinal survey of U.S. older adults to evaluate (1) the extent to which older adults experiencing financial hardship differ with respect to depressive symptoms; (2) whether these associations are buffered or amplified by partner/spouse support and strain, respectively; and (3) whether the purported stress buffering and amplifying roles of romantic relationships vary by sense of purpose in life. Analyses were adjusted for demographic and socioeconomic status indicators, and health conditions that are well-established correlates of financial hardship and depressive symptoms. Understanding these dynamics may inform interventions that leverage relational and psychological resources to protect mental health under financial stress.
This study investigates the relationship between material hardship and population-level mental health outcomes, focusing on depression and frequent mental distress (FMD). Drawing on the stress process framework, we examine whether risky health behaviors—smoking, binge drinking, and physical inactivity—mediate these associations. We constructed a geo-coded dataset by merging tract-level estimates from the 2024 CDC PLACES release with sociodemographic indicators from the 2022 American Community Survey. Structural Equation Models (SEMs) were estimated with a latent construct of material hardship composed of housing instability, utility threats, transportation barriers, SNAP reliance, and lack of insurance. Results show that material hardship is associated with higher prevalence of depression and FMD. Smoking emerges as a key mediator, exerting a large and positive indirect effect, while binge drinking and physical inactivity exhibited negative effects that modestly attenuate overall associations. These findings highlight smoking as a critical behavioral pathway linking hardship to mental health burdens. This study calls for coupling economic supports with integrated behavioral health interventions and expanding smoking cessation and physical activity programs to reduce the mental health effects of economic hardship.
Author(s): Youngjoo Choung, Swarn Chatterjee, Tae-Young Pak
This study examines the effect of livelihood benefits on household consumption in South Korea. Government support is provided as cash. Using data from the Korean Welfare Panel, the analysis compares the effect of adjusted gross income and livelihood benefits on food and non-food expenditures. Measures of elasticity, average propensity to consume (APC), and marginal propensity to consume (MPC) are applied. Results indicate food spending is unresponsive to either income source. Non-food expenditures increase; a larger increase is observed from livelihood benefits. The findings establish that households do not differentiate between livelihood benefits and other income sources. Cash transfers contribute to overall welfare but do not directly achieve the policy objective of increasing food expenditure.
Licensed payday lender operations have declined nearly 90% over the past decade in Wisconsin, even in absence of interest rate limits and relatively high limits on the maximum amount one can borrow in payday loans. Yet, Wisconsin has relatively generous income limits for food and energy assistance sans any limit limits. Considering that utilities are a common reason consumers borrow payday loans, I examine the effects of payday lender vacancy on energy assistance participation by leveraging cross-county variation in licensed payday lender vacancies by year. I employ unique administrative data on licensed payday lender branch operations in Wisconsin since 2011, which I merge to publicly available administrative data on counties’ energy assistance participation, demographics, socioeconomic characteristics, and business censuses. I preliminarily find that licensed payday lender vacancies increase energy assistance participation, although such effects are delayed. Results have policy implications for financial regulations conditional on statically generous safety net parameters.
Assistant Professor, University of Wisconsin-Madison
I am a postdoctoral fellow at the Institute for Research on Poverty and an incoming assistant professor in the Department of Consumer Science (effective Fall 2020), both at the University of Wisconsin-Madison. I study the impacts of consumer policies on economically vulnerable populations... Read More →
Tuesday April 14, 2026 10:15am - 11:45am PDT Pacific II
This study, based on original data collection and the creation of tailored educational videos specifically produced for this research, investigates the effectiveness of short consumer education videos in shaping students’ intentions to increase fruit and vegetable consumption. The interventions included a control group and varied in framing: neutral (informational), positive (gains), and negative (losses). Cultural orientations, measured by Hofstede’s dimensions, were also tested as potential moderators. Data were collected from over 400 students at a large public university using a randomized between-subjects design. Results show that positively framed videos significantly increased intentions compared to control, while neutral and negative framings had little effect. Cultural orientations, particularly long-term orientation and uncertainty avoidance, strongly predicted higher intent, and female students reported greater likelihood than males. These findings highlight the importance of message framing and cultural context in promoting healthier eating intentions. By linking consumer education, culture, and nutrition, this study offers evidence for scalable, low-cost interventions that resonate with diverse student populations and support ACCI’s mission to enhance consumer and family well-being.
This study explores the relationship between financial independence and mental health among emerging adult college students, focusing on two key psychological indicators: anxiety and flourishing. Drawing on data from college students across two U.S. universities, the research examines how varying levels of financial responsibility - measured through funding sources, itemized expenses, and self-reported motivation - relate to scores on the Generalized Anxiety Disorder Scale (GAD-7) and the Flourishing Scale (FS).
Author(s): Nilton Porto, Jing Jian Xiao, Ashley LeBaron-Black, Mariyam Abbas
In this study, we used data collected from college students at five universities in the U.S. to explore personal finance topics demanded by college students. Budgeting, cash management, the financial planning process, and investing are the four topics most frequently chosen by the surveyed students as helpful topics in financial education. We also explored if there are differences in personal finance topics demanded by college students in terms of four sets of financial independence factors: independence level, independence motivation, funding source, and financial responsibility. The results indicate that comparatively, financial responsibility and funding source show more differences in personal finance topics demanded by college students than the other two sets of variables: independence level and independence motivation. The findings indicate that when designing personal finance courses for college students, differences in financial independence and motivation may not be effective predictors. Students across various levels of financial independence and motivation may benefit equally from these topics, though their reasons for engaging with them may differ.
Dr. Jing Jian Xiao is a consumer economics professor at University of Rhode Island. He is also the editor of Journal of Financial Counseling and Planning and the co-guest editor for the special issue on “Consumer Wellbeing in Asia” of Journal of Consumer Affairs.
Tuesday April 14, 2026 2:15pm - 3:45pm PDT Pacific II
This study examined the relationships between digital access, digital literacy, and psychological well-being among adults aged 50 and older using nationally representative data from the 2022 Health and Retirement Study. Digital literacy was modeled as a multidimensional construct encompassing functional, social-communicative, and leisure/productivity skills. Using Structural equation modeling, we found that digital literacy was closely associated with psychological well-being, reflected in purpose in life and depressive symptomatology. Digital access showed a modest direct association with psychological well-being, but its relationship through digital literacy was more pronounced, highlighting the relevance of digital engagement. These findings suggested that variations in digital literacy were linked with differences in well-being among older adults. The study contributed to consumer interest research by identifying digital literacy as an important correlate of psychological well-being and informing programs and policies that promote digital skills, inclusion, and healthy aging in a technology-driven society.
The purpose of this study was to explore the link between personality profiles and the ownership of annuities to increase our understanding of the psychological phenomena that may help explain the annuity puzzle. Two weighted, inferential analyses were conducted. Personality profiles representing unique combinations of the Big Five personality trait variables were identified using latent profile analysis. These variables were then used as predictors of annuity income ownership in a binary logistic regression. Personality profiles were found to be statistically significant predictors. Implications for research, policy, and practice were discussed.
Robert O. Herrmann Outstanding Dissertation Award Winner
Financial well-being in later life is shaped by far more than income and assets. This award-winning dissertation applies Engel's (1977) Biopsychosocial (BPS) Model to financial well-being for the first time, examining how biological, psychological, and sociological factors interact to predict financial outcomes among older adults. Using five waves (2010–2018) of the Health and Retirement Study (HRS) and structural equation modeling with over 35,000 respondents, the study operationalizes physical health, mental health, and social connection as higher-order latent constructs and tests their direct, indirect, and combined effects on a multidimensional measure of financial well-being. Results reveal that the integrated BPS model explains up to 99% of variance in the financial well-being construct, with mental health emerging as the dominant predictor. Physical health exerts positive but variable direct effects and meaningful indirect effects through psychological pathways, while social connection shows a surprising negative direct association, suggesting that maintaining social ties may carry financial costs even as those ties bolster mental health. Findings challenge purely economic models of financial wellness and offer actionable intervention points for financial planners, policymakers, and health professionals working with aging populations.
Generative Artificial Intelligence (GenAI) tools powered by Large Language Models have captured widespread attention of many. There are, however, many unanswered questions about its use. This paper’s goal is to evaluate the use of seven GenAI tools to provide financial advice in three situations: 1) The appropriate amount of emergency savings to hold, 2) The optimal withdrawal rate from retirement funds, and 3) The recommended composition of an investment portfolio. The authors wrote prompts for each situation and provided the same prompt for each situation to each of the seven GenAI tools. In a second step, the race or gender of the individual described in the prompt was changed to learn if the GenAI recommendations would change. This paper reports the outcomes and concludes with recommendations for practice, policy, and research.
Author(s): Brenda Cude, Gianni Nicolini, Swarn Chatterjee
I am a Professor of Finance from the University of Rome (Italy) and my main research interests are on consumer finance, financial literacy, and financial education.
Wednesday April 15, 2026 9:45am - 11:15am PDT Pacific II
The COVID-19 pandemic triggered a surge of new investors, with 21% of US investors in 2021 having joined markets within the past two years. These investors were younger, lower-income, and more likely to invest in risky assets like cryptocurrencies while often relying friends and family and social media for information. However, 2024 findings reveal a significant shift: new investor flow dropped dramatically to 8%, while young adult participation fell from 32% to 26%. Still, 2024 new investors continue exhibiting high-risk behaviors, including trading options and investing in crypto. Beyond a decreased flow of new investors, time series data suggests many pandemic investors may have exited the market, indicating the pandemic investor surge has also ebbed.
Artificial Intelligence (AI) has become increasingly influential, making it crucial to understand what determines public acceptance of AI. Moral foundation theory predicts responses to morally contentious acts, and acceptance of an AI’s decisions is influenced if people feel their moral foundations are considered. While previous research has examined how moral foundations predict awareness and perceptions about AI, public acceptance of AI also needs to be understood in everyday contexts. To address this gap, this research explores the role of moral foundations in shaping acceptance of AI across diverse domains of daily life, using survey data from 614 U.S. participants. Results show that when AI is perceived as causing vulnerability or excluding certain groups and opportunities, people are less likely to accept it in the context of hiring, criminal sentencing, and the automation of jobs. It also suggests that individuals who place a high value on social norms are more likely to accept AI in contexts such as hiring, criminal sentencing, and marketing. This study highlights the importance of considering moral psychology in predicting public acceptance of AI. It suggests stakeholders consider moral foundations in AI design and use, which may address ethical conflicts and guide policy.
This study investigates fintech use and its applications to households' emergency savings, specifically with attention to financial literacy and debt levels. Using weighted logistic regression from the 2024 National Financial Capability Study, the analysis estimates the factors that increase or decrease the likelihood of maintaining three months of emergency savings. The results show that fintech use alone is not associated with emergency savings. However, financial literacy is strongly associated positively with savings, while debt reduces the likelihood of savings by 14% to 33% as respondents' debt sources increased. Interaction effects show that fintech benefits households with low financial literacy and high debt burdens.
This study investigates how family financial socialization (FFS) unfolds within immigrant-heritage families, drawing on the experiences of first-generation college students. Existing research has largely focused on parent–child dynamics within White, middle-class samples, overlooking the ways migration histories, cultural traditions, and systemic barriers shape financial learning. Through a Photovoice project, participants submitted images and reflections capturing formative financial experiences. Thematic Analysis revealed ten central themes that showed how financial lessons were communicated explicitly—through direct guidance—and implicitly—through observation, necessity, and responsibility. Critical Discourse Analysis further demonstrated how students’ narratives both reproduced and resisted racialized, classed, and cultural discourses about money. Findings highlight that FFS extends beyond parent–child interactions to include peers, extended kin, cultural values, and encounters with institutions. Participants often served as cultural and financial intermediaries, translating, advocating, and navigating financial systems on behalf of their families, experiences that deeply informed their values and behaviors. These insights underscore the need to refine FFS frameworks to incorporate cultural and structural contexts and to design culturally responsive financial education that acknowledges the lived realities of immigrant and first-generation communities.
Author(s): Miguel Quiñones, Yesenia Alvarez Padilla
Artificial intelligence (AI) is rapidly transforming personal finance by offering affordable financial advice. While these tools have the potential to expand access to guidance and improve decision-making, little is known about which consumers are most receptive to AI-driven financial advice. Identifying these groups is critical for understanding how technology can be leveraged to enhance consumer and family economic well-being. This study examines sociodemographic, financial, and psychological characteristics and digital engagement variables that are related to having an interest in getting financial advice from AI. The analysis focuses on whether characteristics such as age, gender, race/ethnicity, household income, financial literacy, financial anxiety, and frequency of digital behaviors are associated with openness to AI-based financial guidance. By clarifying who is most likely to adopt AI-driven financial advice, the study provides insights into how emerging financial technologies can reduce barriers to professional guidance and promote household financial security, inclusion, and long-term consumer welfare.
