Financial Services Review, 33(1) 67 Resilient Personality or Financial Resilience Framework for Coping with Physical and Mental Health During the COVID-19 Pandemic Megan McCoy,1 Ives Machiz,2 Portia Johnson,3 Kenneth White,4 Kimberly Watkins,5 and Chet Bennetts6 Abstract Crises events such as the COVID-19 pandemic can have a profound impact on consumers’ financial, physical, and mental health. This study explores the role of two resilience frameworks, namely the financial resilience framework and the resilient personality, in coping with physical and mental health challenges during the pandemic. The financial resilience framework encompasses economic resources, access to financial resources, financial knowledge and behavior, and social capital, while the resilient personality focuses on cognitive flexibility and the ability to tolerate ambiguity. The study aims to investigate whether these frameworks act as complements or substitutes in promoting resilience. GLM ANOVA is employed in this research to examine the effects of financial resilience and a resilient personality on physical and mental health outcomes. Findings from this study indicate that both the financial resilience framework and resilient personality may contribute to one’s mental and physical health. However, the financial resilience framework is a stronger predictor of a positive self-assessment for both health factors than a resilient personality. Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License Recommended Citation McCoy, M., Machiz, I., Johnson, P., White, K., Watkins, K., & Bennetts, C. (2025). Resilient personality or financial resilience framework for coping with physical and mental health during the COVID-19 pandemic. Financial Services Review, 33(1), 67-84. Introduction The past two decades have witnessed a confluence of unprecedented global crises impacting not only financial well-being but also physical and mental health. Since the 2008 1 Corresponding author (meganmccoy@k-state.edu). Kansas State University, Manhattan, KS, USA 2 Arizona State University, Phoenix, AZ, USA. 3 Auburn University, Auburn, AL, USA. 4 University of Arizona, Tucson, AZ, USA. 5 University of Georgia, Athens, GA, USA. 6 Kansas State University, Manhattan, KS, USA. housing bubble financial crisis, coupled with the emergence of cyber threats and geopolitical instability, individuals have faced heightened levels of uncertainty. These factors have had ripple effects on economic activity and public https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/ Financial Services Review, 33(1) 68 health (Burgard & Kalousova, 2015; Shandler et al., 2023). Most notably, the COVID-19 pandemic strongly illustrates how a global health crisis can have cascading economic and psychological consequences. Although the pandemic has ended, the ripple effects continue to be significant. In terms of physical health, there was not only increased morbidity and mortality stemming from COVID-19 infections but also reduced access to healthcare services for other conditions (Shadmi et al., 2020). This resulted in the subsequent years marked by an increase in chronic health conditions resulting from delayed or canceled medical appointments and decreased use of preventive services (Bambra et al., 2021; Patel et al., 2021). Moreover, physical distancing measures and social isolation spawned reductions in physical activity, increased sedentary behaviors, and changes in dietary patterns, all of which can negatively impact physical health outcomes today (Ahmed et al., 2021; Meyer et al., 2020). Additionally, the pandemic has also resulted in significant mental health challenges that have not subsided as quickly as COVID-19 infection rates (Gruber et al., 2023). Research shows that the pandemic had a negative impact on mental health outcomes, with increased rates of anxiety, depression, and substance abuse symptomatology and diagnosis (Gao et al., 2020; Pfefferbaum & North, 2020). The emotional stress caused by the COVID-19 pandemic (Salari et al., 2020; Tsamakis et al., 2020) was compounded by the financial stress that lockdown policies, unemployment, layoffs, and furloughs facilitated (Coibion et al., 2020; Crayne, 2020; Faria-e-Castro, 2021; Kochhar, 2020; Pappas, 2020; Tran et al., 2020). The adverse outcomes of the pandemic did not have a homogenous effect on all. Although many people struggled with the effects of the pandemic, others demonstrated resilience in light of stressors and have experienced an increase in financial, physical, and mental health during the endemic (Prati & Mancini, 2021). The purpose of this study is to identify protective factors that allowed some to be resilient in light of the COVID-19 crisis. Two key theories of resilience propose the protective factors necessary to be resilient: (a) the financial resilience framework (Morrow, 2008; Salignac et al., 2019) and (b) the resilient personality (Asendorpfet al., 2001). The financial resilience framework is composed of four multidimensional components: economic resources, access to financial resources, financial knowledge and behavior, and social capital (Morrow, 2008; Salignac et al., 2019). It posits that individuals are best equipped to cope with adversity when they have knowledge of an adverse event and the resources to adapt successfully (Morrow, 2008; Salignac et al., 2019). In comparison, a resilient personality is characterized by cognitive flexibility and an ability to tolerate ambiguity well (Asendorpf et al., 2001). An individual with this personality type has the inner vision, calmness, intelligence, maturity, and self-esteem needed to see a challenge not as a threat but as a time to gather internal resources to enact positive and effective resistance. Individuals with a resilient personality are often seen as assertive, verbally expressive, energetic, personable, open-minded, smart, and self-confident (Asendorpfet al., 2001). The overarching research question guiding this study is whether the financial resilience framework and the resilient personality are complements (e.g., have an additive effect) or substitutes (have the same impact and it is not cumulative) as they relate to resilience in one’s physical and mental health in light of COVID-19. The examination used GLM ANOVA to analyze the effects of the financial resilience framework and a resilient personality on physical and mental health. Through insights into resiliency, the hope is the findings will be generalizable to other stressors and crises. Theoretically Informed Literature Review Biopsychosocial Model The biopsychosocial model (Engel, 1977) proposes that health and disease are determined by the interaction of biological, psychological, and social factors. The state of a person’s biological condition (e.g., organs, tissue, cells) is strongly influenced by psychological factors (e.g., cognition, emotions, motivation) and social interactions (e.g., society, community, family; Serafino, 2011). The biopsychosocial model has McCoy et al. 69 been extensively adopted in medical research. Findings from these studies have led to the development of a more comprehensive approach to healthcare to include mental health professionals, patients, families, and support systems. The theory was foundational to the study of COVID-19’s short-term and long-term impacts across many domains. For example, Kop (2021) found that attention to psychological and social factors is 74% higher in COVID-19-related articles compared to all other physical health- related scientific articles published during the same period. The biopsychosocial model can be applied to the study of personal finance, as financial resilience and financial well-being are also complex constructs influenced by biological, psychological, and social factors (Hughes, 2021). However, the relationship between biopsychosocial factors and financial well-being is largely unexplored (Kannadhasan et al., 2016). The model has been applied to some aspects of personal finance, namely financial risk-taking and tolerance (Fong, 2005; Grable & Joo, 2004; Grable & Webb, 2008; Kannadhasan et al., 2016), and oniomania or compulsive overbuying (Faber, 1992). Additional evidence for the complex relationship of the elements of the biopsychosocial model was found in a longitudinal study of married couples (Lee et al., 2021). Using Structural Equation Modeling (SEM), the authors discovered that during the middle years of adulthood, the existence of family financial hardships was associated with reduced marital stability, which was linked to heightened mental health difficulties. Moreover, the results reaffirmed the influential role of psychological distress in shaping subsequent physical health outcomes. Specifically, anxiety symptoms reported by both husbands and wives during their early middle years contributed to the decline of their physical health in later adulthood (Lee et al., 2021). While some results seem intuitive, further exploration of each nuanced component of the biopsychosocial model is in order. Biological Chou et al. (2016) established a connection between financial well-being, economic hardships, and adverse health outcomes including heightened physical pain, reduced pain tolerance, and an elevated risk of coronary heart disease. In another study, individuals who reported substantial financial debt experienced poorer self-reported general health and higher diastolic blood pressure (Sweet et al., 2013). These associations persisted even after controlling for previous socioeconomic status, psychological and physical health, and various demographic factors (Sweet et al., 2013). A meta-analysis found that being in debt was related to poor health behaviors including increases in smoking, problem drinking, and drug dependence (Richardson et al., 2013). These findings underscore the interplay between financial well- being and physical health, highlighting the importance of considering the biological implications of economic hardships and financial stress. Psychological Ryu and Fan (2023) find that financial stress greatly contributes to one’s psychological distress, and the relationship between financial stress and distress is moderated by socioeconomic factors such as gender, marital status, employment, income, and homeownership. The association between financial stress and psychological distress was significantly stronger among women, people who were separated, divorced, widowed, or never married, unemployed persons, those with a household income under $75,000, and those who rent versus own a home. A meta-analysis found statistically significant associations between debt and the presence of various mental health conditions, including but not limited to mental health disorders, suicide completion or attempt, as well as psychotic disorders. (Richardson et al., 2013). Depression and anxiety are widely studied psychological conditions associated with financial stress. A longitudinal study among cancer patients found that financial burden significantly predicted depressive symptoms and general anxiety. However, depressive symptoms and general anxiety during the initial survey did not predict subsequent financial burden, suggesting that financial difficulties are indicative of future distress (Jones et al., 2020). At the extreme end of psychological issues, after Financial Services Review, 33(1) 70 controlling for demographic and clinical covariates specific to the population of the study, results suggested that for each progressive increment in financial strain, the predicted probabilities of suicide attempts and suicidal ideation experienced significant escalation. Respondents who acknowledged all four financial strain variables measured exhibited a predicted probability of future suicide attempts that were 20 times higher in comparison to respondents who did not endorse any of the financial strain variables (Elbogen et al., 2020). In summary, there is a critical need to address financial well-being as a key factor in promoting and maintaining mental health. Sociological The sociological implications of financial resilience and financial well-being have been relatively well examined from the lens of several disciplines. Looking at many sociological elements, one study explored the relationship between financial wellness, personal well-being, and gender, finding that men scored higher in financial satisfaction and knowledge than women. However, women demonstrated higher levels of personal well-being, affirming the multi-dimensional aspect of financial wellness proposed by Joo (2008). This also underscored the mediating role of financial satisfaction in the relationship between financial satisfaction and knowledge (Gerrans et al., 2014). In another study, Kim et al. (2003) found that after accounting for the initial financial stressor score, age, and household income, credit counseling had a positive impact on reducing financial stressors for clients who remained in the program for 18 months. Although a person’s general degree of optimism can affect their resilience (Muir & Strnadova, 2014), the relationship between resilience and optimism is ambiguous, as the impact of one on the other remains unclear. While individuals' optimism levels may influence their ability to recover from adverse events, it is also plausible that their confidence in coping abilities influences their level of optimism (Salignac et al., 2019). Individuals classified as optimistic tend to have greater social capital (friends and family on whom they can rely for financial knowledge and assistance) and greater access to financial products and services (such as bank accounts, affordable credit and insurance products) than individuals classified as neutral or pessimistic (Salignac et al., 2019). They note that since those experiencing sociological limitations such as mental illness may have higher barriers to amass formal and informal social supports and community resources, they are in turn also likely to express lower financial resilience. The literature reviewed here highlights the sociological factors that can influence financial well-being, such as gender, social support, and community resources. Therefore, an approach based on the biopsychosocial model (Engel, 1977) is useful for understanding financial stress and financial resilience’s role in promoting financial well-being. Financial Resilience Framework The financial resilience framework (Morrow, 2008; Salignac et al., 2019) is intended to aid individuals and families in building financial resilience in the face of economic uncertainty and financial shocks, such as the period marked by COVID-19 (Norris, 2010). Morrow (2008) conceptualized financial resilience in the context of measuring financial inclusion/exclusion as dependent on one’s knowledge of events, ability to predict risks, access to and knowledge of available alternatives, and resources to adapt. Norris (2010) offered five essential financial elements of financial resilience: saving, budgeting, debt management, insurance, and investment. Sherraden (1991) added that acquiring assets (savings, investments, and property) is a precursor to household and individual financial resilience. Finally, Salignac et al. (2019) expanded on the financial resilience framework by outlining four essential components: (a) economic resources, (b) financial resources and products, (c) financial knowledge and behaviors, and (d) social capital which serve as the operationalization of the financial resilience framework. The first component, economic resources, includes savings, income, and the ability to meet cost-of-living expenses. Resilience is influenced by one’s ability to meet their cost of living (Jacobs et al., 2014), and an inability to do so McCoy et al. 71 contributes to financial stress (Orthner et al., 2004). The economic resources component captures an individual’s ability to cope with adversity and deal with unexpected expenses given their monetary inputs (Demirgüç-Kunt et al., 2015). The second component, financial resources and products, measures access to financial products and services. Individuals may experience several different types of exclusion from financial products and services (Cnaan et al., 2012; Gomez-Barroso & Marban-Flores, 2013; Marron, 2013; Salignac et al., 2016). Financial exclusion arises from a confluence of factors. One key factor is condition mismatch, where the products and services offered simply don't align with the target population’s needs or interests. Another factor is access limitations, where individuals do not meet minimum requirements to qualify for desired products or services (Salignac et al., 2019; Kempson & Poppe, 2018). Physical and geographic barriers also play a role, as the absence of local branches or service availability can significantly hinder access. Price can be a significant hurdle as well, with costs exceeding the budgets of potential users. Self-selected exclusion can occur when individuals voluntarily choose not to participate due to cultural reasons, psychological factors, or lack of financial literacy. Finally, marketing gaps contribute to the problem when marketing strategies fail to effectively reach the target group, leading to a lack of awareness about available financial products and services. The third component, financial knowledge, builds on literature from financial literacy (Lusardi & Mitchell, 2014) and financial capability research (Kempson & Poppe, 2018; Serido et al., 2013). Given increasingly complex financial systems, an individual’s financial security is based on an adequate understanding of the system, along with positive financial skills and behaviors (Lusardi & Mitchell, 2014). This component of the financial resilience framework fills a necessary gap in the literature as neither financial literacy nor financial capability alone can well-explain one’s ability to cope with financial stressors or economic shocks (Salignac et al., 2022). The fourth component is social capital. Social capital is the connections among individuals— social networks and the norms of reciprocity and trustworthiness that arise from them (Putnam, 2000). Social capital depends on networks— specifically on the payoff from network membership—in terms of access to resources and opportunities that would be otherwise unavailable (Scrivens & Smith, 2013). Individuals draw on family, friends, and community as sources of financial support and information in times of emergency (Demirgüç- Kunt et al., 2015; Seccombe, 2002). The component of social capital theory integrates this framework into the biopsychosocial model (Engel, 1977) as it falls in the social domain of this model. Resilient Personality Personality is made up of behavioral predispositions (i.e., temperament), cognitive attributes, and emotional qualities (Skodol, 2010). Research on the resilient personality type, a concept developed by Werner & Smith (1982), involves the traits and qualities that help people deal well with problems, stress, and other life difficulties. Derived from the Big Five Personality dimensions (agreeableness, conscientiousness, extraversion, neuroticism, and openness to experience), this simplified approach to personality typology characterizes individuals as resilient, undercontrolled, or overcontrolled (Werner & Smith, 1982). Unlike under and overcontrolled personality types, resilient personality types can recover from difficult events or situations, adapt to changes, and maintain a positive attitude despite obstacles (Morrow, 2008). Resilient personality type ranges from having the skills to cope with adversity to being able to thrive in the face of adversity (Bonanno, 2004). Although one’s resilience is a dynamic internal process that changes and is affected by personal, familial, community, and cultural factors (Masten, 2014), the resilient personality type has internal developmental assets that promote stronger resilience despite external factors (Benson et al., 1999; Masten, 2001). A relationship may exist between the financial resilience framework factors and resilient Financial Services Review, 33(1) 72 personality; however, this examination is limited in the literature. Zahedi et al. (2022) propose that future studies explore the ways that financial resilience might be moderated by personality traits. This study aims to expand on these findings by better understanding how having a resilient personality is associated with coping with financial adversity. Methods Data The data were collected by the Qualtrics partner network of panel providers from November 17, 2021 to December 15, 2021 using several different avenues of recruitment (e.g., email, social media platforms). This data were part of a larger study that aimed to collect data on resilience in the aftermath of the COVID-19 pandemic. The targeted population included adults living in the United States (n = 3,598) with a particular emphasis on low and moderate income households and people of color, as this population was most negatively impacted by the pandemic (Kantamneni, 2020). The participants obtained through this data collection process were 51% White, 22% Black/African American, 10% Asian American, and 17% Other. Regarding ethnicity, 20% of the sample identifies as Hispanic. Also, among the respondents, approximately 30% have a high school diploma (or equivalent), 28% were some college, 31% were college degree holders (associate’s or bachelor's), 8% have earned graduate degrees, and 3% had less than high school educations. The majority (52%) were employed at least part-time, 24% were unemployed, and the remainder were self-employed, students, or other. The married or cohabiting respondents account for 58% of the sample. Demographic data is summarized in Table 1. Table 1. Client Demographic Data Total Sample Analyzed Cases N % N % Age (n = 3,597) 18 – 24 years 654 18.18 529 17.12 25 – 34 years 1,107 30.78 994 32.17 35 – 44 years 869 24.16 761 24.63 45 – 54 years 441 12.26 381 12.33 55 – 64 years 256 7.12 209 6.76 65 years or older 270 7.51 216 6.99 Gender Female 1,767 49.11 1,498 48.48 Male 1,753 48.72 1,527 49.42 Other 78 2.17 65 2.10 Race White 1,820 50.58 1,595 51.62 Black 799 22.21 697 22.56 Asian 362 10.06 290 9.39 Other 617 17.15 508 16.44 Hispanic No 2,879 80.02 2,464 79.74 Yes 719 19.98 626 20.26 McCoy et al. 73 Education (n = 3,596) Less than high school 124 3.45 90 2.91 High school graduate or equivalent 1,095 30.45 934 30.23 Some college, or degree or in progress 976 27.14 834 26.99 Associate degree 442 12.29 385 12.46 Bachelor's degree 682 28.97 603 19.51 Graduate degree (Master's, Professional, Doctorate) 277 7.70 244 7.90 Marital Status Married or cohabiting 2,085 57.95 1,741 56.34 Not married nor cohabiting 1,513 42.05 1,349 43.66 Employment Status (n = 3,597) Employed full-time (40 hours per week) 1,457 40.51 1,349 43.66 Employed part-time (less than 40 hours per week) 397 11.04 326 10.55 Self-employed 301 8.37 250 8.09 Full-time student 201 5.59 168 5.44 Part-time student 67 1.86 56 1.81 Unemployed 878 24.41 730 23.62 Other 296 8.23 211 6.83 Resilient Personality No 2,037 56.61 1,748 56.57 Yes 1,561 43.39 1,342 43.43 N = 3,598 unless otherwise noted for the total sample; N = 3,090 for the analyzed cases Measures The two dependent variables were self-reported measures of physical and mental health. The physical health measure was a single question that asked respondents to rate their overall health. Respondents were then asked in a separate single question to rate their overall mental health. Responses for both questions range from 1 to 5, with 1 being “excellent” and 5 being “poor”. The independent variables of interest were the resilient personality typology and the financial resilience framework. To assess a resilient personality, respondents self-reported whether overcontrolled, undercontrolled, or resilient comes closest to their personality. Respondents were allowed to select only one typology. The financial resilience framework variable was a scale composed of 10 questions representing the four components of the framework. Seven of the ten resilience questions were given scores ranging from 0 to 1, with 0 representing the absence of a resilient feature and 1 indicating the highest level of resilience. Financial knowledge was coded on a scale ranging from 0 to 1. The survey had three financial knowledge questions, and the total number of correct answers for each respondent was calculated. The score was then recoded as follows: 0 correct = 0.00; 1 correct = 0.33; 2 correct = 0.67; and 3 correct = 1.00. By recoding the objective financial knowledge variable [0, 1] interval, the construct of objective financial knowledge was weighted the same as the other constructs in the financial resilience index. Social capital was measured by asking respondents to identify sources of financial Financial Services Review, 33(1) 74 support, as was done in similar articles (e.g., Scrivens & Smith, 2013). Respondents who identified a family member, friend, neighbor, faith-based community, service provider, institution, or organization as a source for urgently needed monetary support to face an emergency, were coded 1 indicating presence of social capital. If respondents said there was nobody they could ask if they urgently needed $1,000 for an emergency, then they were coded 0 to indicate no social capital. The total scores for the scale range from 0 to 8. Responses to the questions for the financial resiliency framework are summarized in Table 2. Several covariates (i.e., age, gender, race, ethnicity, education, marital status, employment status, and employment change during COVID- 19) were included in the analyses. Table 2. Financial Resilience Framework—Survey Results N % Annual Household Income Less than $15,000 643 18.37 $15,000 – $24,999 540 15.43 $25,000 – $34,999 539 15.40 $35,000 – $49,999 698 19.94 $50,000 – $74,999 360 10.29 $75,000 – $99,999 360 10.29 $100,000 – $149,999 360 10.29 Greater than $150,000 0 0.00 Savings Before COVID-19 Pandemic I had no savings 984 28.20 I had very little savings (1 month of income or less) 886 25.39 I had limited savings (1 to 2 months of income) 763 21.87 I had moderate savings (3 or more months of income) 856 24.53 Access To Any Form Of Credit Before COVID-19 Pandemic No access to any form of credit 808 22.46 Access to any form of credit 2,790 77.54 Access To Financial Accounts No access to financial accounts 82 2.28 Access to financial accounts 3,516 97.72 Before Making Major Financial Decisions… Almost no research 380 10.58 A little bit of research 996 27.72 Moderate amount of research 1,168 32.51 A great deal of research 1,049 29.20 Total Financial Literacy Questions Answered Correctly 0 895 24.87 1 1,294 35.96 McCoy et al. 75 2 854 23.74 3 555 15.43 Knowledge of Financial Products and Services No knowledge of financial products and services 422 11.75 Basic knowledge of financial products and services 1,749 48.68 Good knowledge of financial products and services 1,069 29.75 Very good knowledge of financial products and services 353 9.82 Could you ask someone if you urgently needed $1,000 for an emergency? No 981 27.27 Yes 2,617 72.73 Missing data handled by listwise deletion for each question Analysis GLM ANOVA was used to analyze the effects of the financial resilience framework and a resilient personality on physical and mental health. GLM ANOVA was chosen because it can account for continuous covariates and yet allow for greater interaction analysis than OLS. This is important for substitute/complement analysis. For analysis, responses to the financial resilience variables were summed, and the scores were grouped into three categories with one category comprising the lowest quartile, one representing the middle two quartiles (interquartile range), and one representing the highest quartile. The quartile cutoff scores were less than 4.00 for the lower quartile (n = 810), 4.00 to 5.76 for the middle two quartiles (IQR) (n = 1,770), and greater than 5.76 for the upper quartile (n = 824). Missing data on key variables reduced the number of complete cases to n = 3,090. Results For mental health, GLM ANOVA analysis indicated significant results for the main effects of both the financial resilience framework score (χ2[2] = 34.99, p < .001) and the resilient personality indicator (χ2[1] = 51.60, p < .001). The GLM ANOVA results for mental health are presented in Table 3. The interaction between resilient personality and the financial resilience framework score was also significant (χ2[2] = 11.24, p < .01). Table 4 summarizes the main and interaction effects for the model. All interactions with a resilient personality and a high quartile indicator of the financial resilience framework were significantly stronger than any other combination at p < .001. A resilient personality combined with the financial resilience framework in the IQR was also significant at p < .001 compared to the same financial resilience framework level without a resilient personality. Given a significant interaction, the analysis supports a resilient personality and the financial resilience framework as complements concerning their effect on mental health. Both are associated with a significant difference in mental health, and the two factors interact to associate with even greater change. Financial Services Review, 33(1) 2 Table 3. Mental Health—GLM ANOVA Results Factors df χ2 Significance Indicator of Resilience 2 34.99 *** Resilient Personality 1 51.60 *** INTERACTION 2 11.24 ** N = 3,090 * p < .05; ** p < .01; *** p < .001 For physical health, GLM ANOVA analysis showed significant main effects for both the financial resilience framework score (χ2[2] = 77.50, p < .001) and a resilient personality (χ2[1] = 15.76, p < .01). The GLM ANOVA results for physical health are presented in Table 5. However, the interaction term was not significant (χ2[2] = 4.21, p = 0.12). The main effects difference for a resilient personality was significant at p < .001, and all three possible main effects comparisons for the financial resilience framework score were also significant at p < .001. The main effects contrast is presented in Table 6. GLM ANOVA supports the financial resilience framework and a resilient personality as substitutes concerning physical health. Each factor is associated with a significant difference in physical health, with changes in the financial resilience framework associated with the greatest changes in physical health. The interaction between the two factors was not significant, indicating a substitution effect, where changing one factor alone would not be expected to affect the other factor’s impact on physical health. Discussion This study examined whether the financial resilience framework and the resilient personality work as complements or substitutes to impact one’s mental and physical health in light of the health and financial crisis created by the COVID- 19 pandemic. Findings from this study indicate that both the financial resilience framework and resilient personality may contribute to one’s mental and physical health. However, the financial resilience framework is a stronger predictor of both mental and physical health outcomes than a resilient personality. Findings from our study provide several essential contributions to the literature. First, the current study provides an important finding regarding mental health and resilience. The components that make up the financial resilience framework (Salignac et al., 2019) have been linked to mental health outcomes in prior research. For example, financial knowledge and behavior have been associated with lower levels of psychological distress and depression (Lim et al., 2019; Seay et al., 2019). Similarly, social capital has been linked to improved mental health outcomes, such as greater social support, reduced stress, and better overall well-being (Kim & Garman, 2019; Moksnes et al., 2018). Taken together, this study’s finding that the financial resilience framework is essential for mental health is important in designing personal finance interventions and policies that target financial health that can also aid a client’s mental health. McCoy et al. 1 Table 4. Mental Health - Contrasts (Main and Interactions) (Indicator Group, Personality Group) Contrast SE z Significance MAIN: Indicator 1 vs 0 0.1711 0.05 3.25 ** MAIN: Indicator 2 vs 0 0.3790 0.06 5.89 *** MAIN: Indicator 2 vs 1 0.2079 0.05 4.01 *** MAIN: Personality 1 vs 0 0.3174 0.04 7.18 *** (0, 1) vs (0, 0) 0.1341 0.09 1.56 (1, 0) vs (0, 0) 0.0917 0.06 1.43 (1, 1) vs (0, 0) 0.3845 0.07 5.56 *** (2, 0) vs (0, 0) 0.1834 0.08 2.17 * (2, 1) vs (0, 0) 0.7087 0.08 8.96 *** (1, 0) vs (0, 1) -0.0424 0.08 -0.54 (1, 1) vs (0, 1) 0.2541 0.08 3.05 ** (2, 0) vs (0, 1) 0.0493 0.10 0.52 (2, 1) vs (0, 1) 0.5746 0.09 6.35 *** (1, 1) vs (1, 0) 0.2929 0.05 5.13 *** (2, 0) vs (1, 0) 0.0917 0.07 0.04 (2, 1) vs (1, 0) 0.6170 0.07 9.25 *** (2, 0) vs (1, 1) -0.2012 0.08 -2.61 ** (2, 1) vs (1, 1) 0.3242 0.07 4.61 *** (2, 1) vs (2, 0) 0.5254 0.08 6.42 *** N = 3,090 * p < .05; ** p < .01; *** p < .001 Indicator Group: 0 = low quartile financial resilience, 1 = IQR financial resilience, 2 = high quartile financial resilience Personality Group: 0 = not resilient, 1 = resilient Table 5. Physical Health—GLM ANOVA Results Factors df χ2 Significance Indicator of Resilience 2 77.50 *** Resilient Personality 1 15.76 ** INTERACTION 2 4.21 N = 3,090 * p < .05; ** p < .01; *** p < .001 Financial Services Review, 33(1) 78 Table 6. Physical Health—Contrasts (Main Only) Main Group Contrast SE z Significance Indicator 1 vs 0 0.1621 0.05 3.56 *** Indicator 2 vs 0 0.4735 0.06 8.51 *** Indicator 2 vs 1 0.3114 0.04 6.96 *** Personality 1 vs 0 0.1517 0.04 3.97 *** N = 3,090 * p < .05; ** p < .01; *** p < .001 Indicator Group: 0 = low quartile financial resilience, 1 = IQR financial resilience, 2 = high quartile financial resilience Personality Group: 0 = not resilient, 1 = resilient Secondly, our findings support the link between factors related to the financial resilience framework (Salignac et al., 2019) and physical health. For example, economic resources have been associated with improved access to healthcare, better nutrition, and better overall physical health (Morrow, 2011; Zhu et al., 2019). Access to financial resources has also been linked to improved physical health outcomes, including lower levels of chronic disease and better overall health status (Kobayashi et al., 2015; Zhu et al., 2019). Social capital through informal networks can provide individuals with information, support, and motivation to engage in health- promoting behaviors such as exercise, healthy eating, and smoking cessation (Berkman et al., 2000). Similarly, our findings show the added benefit of increased physical health and higher levels of financial resilience. Furthermore, social networks can facilitate access to healthcare services and encourage compliance with medical treatments (Kim et al., 2017). Yet, to the authors’ knowledge, no study has directly examined how the entirety of the financial resilience framework impacts physical health domains, and the link is important to explore further in future studies. Finally, our study found that the financial resilience framework and resilient personality were complementary in explaining mental health but not the physical health results. The complementary nature of the resiliency factors and mental health is consistent with previous research that suggests that personality traits can moderate the relationship between financial stressors and mental health outcomes (Rothmann & Coetzer, 2003). For instance, individuals with a resilient personality may be better able to cope with financial stressors and maintain positive mental health outcomes (Windle, 2011). Interestingly, this study did not find support for a complementary relationship between the financial resilience framework and resilient personality traits when it came to physical health. This may be because financial factors are more directly related to physical health outcomes, particularly in the United States where medical care costs are high, financial resources become even more essential to access healthcare, purchase prescriptions, and buy healthy food options (Todorova et al., 2016). The impact of inner vision, calmness, intelligence, maturity, and self-esteem on financial setbacks will not overcome the need for financial resources to be physically healthy. However, more research is needed to gather deeper insights into why resilient personality did not have a complementary role when it came to physical health. These findings suggest that financial professionals should continue to highlight the importance of financial security and capability and the role of social support networks in promoting both mental and physical health to their clients. Moreover, the findings underscore the importance for financial professionals to advocate for increased access to mental and physical health resources so individuals can maintain a healthy lifestyle. Financial services McCoy et al. 79 providers should be trained on how to identify financial difficulties that may be linked to psychological and physical stressors to help these clients receive the proper care, thus increasing their ability to cope with financial shocks. Limitations There are several limitations to note. This study did not have a random selection of respondents, which can impact generalizability to the larger population. Next, none of the households sampled had an income greater than $150,000. This was an intentional decision as the study was designed to study at-risk households and oversample households based on race/ethnicity and income. Results from our study cannot be applied directly to households that were excluded based on the research design. Future research should focus on high-income groups to see if these findings will hold. Our study used a single- item question to measure a resilient personality. Future studies should consider using multi-item measure to improve robustness and possibly provide results for different levels of the resilient personality trait. Similarly, where data allowed, we included the individual’s position before the stressor event (savings before Covid and access to credit before Covid), but longitudinal data would improve the reliability and validity of this study. Lastly, nearly one-fourth of respondents were unemployed. Although this employment status is overrepresented, it aligns with the situation at hand during the height of the pandemic. The unemployment rate for Black and Hispanic/Latino communities was significantly higher than the rate for White communities during the COVID-19 pandemic. According to data from the Bureau of Labor Statistics (BLS), the unemployment rate for Black Americans peaked at 16.8% in April 2020. By March 2021, this rate gradually declined to 7.8%. Similarly, the unemployment rate for Hispanic/Latino Americans peaked at 18.9% in April 2020 and declined to 7.9% by March 2021. In comparison, the unemployment rate for White Americans peaked at 14.2% in April 2020 and declined to 5.4% by March 2021. It is worth noting that these unemployment rates do not account for individuals who dropped out of the labor force due to pandemic-related factors, such as caregiving responsibilities or health concerns. Thus, the true impact of the pandemic on employment may be even greater than these statistics suggest. Implications Results from this study provide an opportunity to re-examine the biopsychosocial model (Engel, 1977) as the model originally incorporated basic financial aspects (e.g., socioeconomic status and household income) within the social component construct. However, the intersection between more nuanced financial health factors, as described in the financial resilience framework (i.e., economic resources, access to financial resources, financial knowledge and behavior, and social capital; Salignac et al., 2019) suggests there is potential for the biopsychosocial model to include a separate financial component. Adding a separate financial component will allow research to examine the unique contributions of social health (e.g., friends and community) and one’s overall well-being, including financial health. This is consistent with previous research that has emphasized the need for a more comprehensive understanding of the factors that contribute to overall well-being, including financial factors (Moffitt et al., 2018). As stated by Kannadhasan et al. (2016), “There is no specific theory on the role of biopsychosocial factors in the financial services domain” (p. 118). Our findings suggest that this is an oversight in the theorizing of the connection between pillars of well-being. This may be especially true in the United States, where the costs of medical care are staggering relative to other countries around the world (Papanicolas et al., 2018), and one’s physical and mental health may be even more directly dictated by one’s financial health (Todorova et al., 2016). This study has several practical implications for various personal finance and mental health stakeholders across education, advising, coaching, planning, and counseling domains. For mental health professionals, interventions that increase resilience could help clients better cope with mental health issues such as trauma, depression, and anxiety. For financial professionals, understanding the traits that make Financial Services Review, 33(1) 80 people resilient can help identify individuals at risk for mental health problems. The findings of this study suggest that financial professionals should persist in highlighting to their clients the critical role of financial stability, financial literacy, and social support networks in promoting both mental and physical health. Moreover, the findings underscore the importance for financial professionals to advocate for increased access to services and resources that influence mental and physical well-being, thereby supporting individuals in maintaining a healthy lifestyle. It is crucial for financial professionals to acknowledge and address financial difficulties that may be linked to psychological and physical stressors among their clients. Finally, financial professionals can utilize the insights from this study to enrich discussions with clients about how personality factors contribute to their overall well-being. Our study provides several reasons for the inclusion of resilience methods in financial and mental health interventions. First, findings from this study support the idea that interventions should include complementary mechanisms that focus on helping clients enhance their financial resiliency. The need for holistic and multifaceted interventions is evident given that those in this study with a resilient personality and the multiple components of the financial resilience framework may have better mental and physical health. By creating interventions that address resilience across the five elements (saving, budgeting, debt management, insurance, and investment; Norris, 2010) and incorporating strategies that support the four financial resilience framework components (economic resources, financial resources, and products, financial knowledge and behaviors, and social capital; Salignac et al., 2019), practitioners and researchers will strengthen their effectiveness in helping individuals cope and have better overall well- being. Second, lingering chronic stress, secondary to adverse COVID-19 pandemic related outcomes, is an issue that many mental health and personal finance practitioners are still helping their clients manage. Resources have been made available from federal and state agencies, professional organizations (e.g., AFCPE, FPA), financial institutions, and nonprofits. For example, the Consumer Financial Protection Bureau (CFPB, n.d.) developed web-based and printed materials to inform consumers on how they can protect and manage their finances during COVID-19. These resources focus on financial management, mortgage and housing assistance, avoiding fraud, and student loan relief. Practitioners can familiarize themselves with such resources and incorporate them as tools to help their clients build a mindset to better endure future economic downturns and protect their mental and financial health. For personal finance practitioners, these results also hint at the importance of financial planners incorporating the biopsychosocial model when working with clients. This inclusion may provide a more thorough assessment of a client’s physical and mental health, particularly for financial planning components such as cash flow, estate planning, and insurance planning. Given the difficulty many practitioners experience getting their clients to implement recommendations, the biopsychosocial model coupled with assessing financial resilience could help planners and counselors better assist their clients with meeting their goals. More research should be conducted to test these interventions in hopes of informing professional practice. Finally, the findings support an intersectional approach to research that could potentially expand our understanding of how people cope during economic uncertainty in times of crisis and the tools they need to cope and recover. Future studies can focus on examining how having financial resilience is associated with other outcomes of well-being, such as parenting, environmental, or relationship health. To do this, measures that capture resilient personalities and the financial resilience framework could be included in data collection. Additionally, the findings suggest a need for empirically based interventions that are inclusive of targeted audiences (e.g., gender, race, culture) and lead to valid and reliable outcomes. Resilience may also help expand insights regarding factors associated with other research areas such as consumer decision-making and behavioral economics. McCoy et al. 81 References Ahmed, O., Hossain, K. N., Siddique, R. F., & Jobe, M. C. (2021). COVID-19 fear, stress, sleep quality and coping activities during the lockdown, and personality traits: A person-centered approach analysis. Personality and Individual Differences, 178, 110873. Asendorpf, J. B., Borkenau, P., Ostendorf, F., & Van Aken, M. A. G. (2001). Carving personality description at its joints: Confirmation of three replicable personality prototypes for both children and adults. European Journal of Personality, 15, 169–198. https://doi.org/10.1002/per.408. Bambra, C., Riordan, R., Ford, J., & Matthews, F. (2021). The COVID-19 pandemic and health inequalities. Journal of Epidemiology and Community Health, 75(6), 461-463. Benson, P. L., Scales, P. C., Leffert, N., & Roehlkepartain, E. C. (1999). A Fragile Foundation: The State of Developmental Assets among American Youth. Minneapolis, MN: Search Institute. Berkman, L. F., Glass, T., Brissette, I., & Seeman, T. E. (2000). From social integration to health: Durkheim in the new millennium. Social Science & Medicine, 51(6), 843-857. Bonanno, G. A. (2004). Loss, trauma, and human resilience: Have we underestimated the human capacity to thrive after extremely aversive events? American Psychologist, 59(1), 20–28. https://doi.org/10.1037/0003- 066X.59.1.20 Burgard, S. A., & Kalousova, L. (2015). Effects of the Great Recession: Health and well- being. Annual Review of Sociology, 41, 181-201. Chou, E. Y., Parmar, B. L., & Galinsky, A. D. (2016). Economic insecurity increases physical pain. Psychological Science, 27(4), 443–454. https://doi.org/10.1177/0956797615625 640 Cnaan, R. A., Moodithaya, M. S., & Handy, F. (2012). Financial inclusion: Lessons from rural South India. Journal of Social Policy, 41, 183–205. Coibion, O., Gorodnichenko, Y., & Weber, M. (2020). Labor Markets During the COVID-19 Crisis: A Preliminary View (NBER Working Paper 27017). National Bureau of Economic Research. https://10.3386/w27017 Consumer Financial Protection Bureau. (n.d.). Protecting your finances during the coronavirus pandemic. https://www.consumerfinance.gov/coron avirus/ Crayne, M. P. (2020). The traumatic impact of job loss and job search in the aftermath of COVID-19. Psychological Trauma: Theory, Research, Practice, and Policy, 12(S1), S180–S182. https://doi.org/10.1037/tra0000852 Elbogen, E. B., Lanier, M., Montgomery, A. E., Strickland, S., Wagner, H. R., & Tsai, J. (2020). Financial strain and suicide attempts in a nationally representative sample of us adults. American Journal of Epidemiology, 189(11), 1266–1274. https://doi.org/10.1093/aje/kwaa146 Engel, G. L. (1977). The need for a new medical model: A challenge for biomedicine. Science, 196(4286), 129-136. Faber, R. J. (1992). Money changes everything: Compulsive buying from a biopsychosocial perspective. American Behavioral Scientist, 35(6), 809-819. Faria-e-Castro, M. (2021). Fiscal policy during a pandemic. Journal of Economic Dynamics and Control, 125, Article 104088. https://doi.org/10.1016/j.jedc.2021.1040 88 Fong, T. W. (2005). The biopsychosocial consequences of pathological gambling. Psychiatry, 2(3), 22–30. https://doi.org/10.1037/0003-066X.59.1.20 https://doi.org/10.1037/0003-066X.59.1.20 https://doi.org/10.1037/tra0000852 https://doi.org/10.1037/tra0000852 https://doi.org/10.1037/tra0000852 https://doi.org/10.1016/j.jedc.2021.104088 https://doi.org/10.1016/j.jedc.2021.104088 https://doi.org/10.1016/j.jedc.2021.104088 https://doi.org/10.1016/j.jedc.2021.104088 Financial Services Review, 33(1) 82 Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., Wang, W., Fu., H. & Dai, J. (2020). Mental health problems and social media exposure during the COVID-19 outbreak. PLoS One, 15(4), e0231924. Gerrans, P., Speelman, C., & Campitelli, G. (2014). The relationship between personal financial wellness and financial well-being: A structural equation modeling approach. Journal of Family and Economic Issues, 35(2), 145–160. https://doi.org/10.1007/s10834-013- 9358-z Gomez-Barroso, J. L., & Marban-Flores, R. (2013). Basic financial services: A new service of general economic interest? Journal of European Social Policy, 23, 332–339. Grable, J. E., & Joo, S.H. (2004). Environmental and biopsychosocial factors associated with financial risk tolerance. Journal of Financial Counseling and Planning, 15(1), 73–82. Grable, J., Britt, S., & Webb, F. (2008). Environmental and biopsychosocial profiling as a means for describing financial risk-taking behavior. Journal of Financial Counseling and Planning, 19(2). Gruber, J., Hinshaw, S. P., Clark, L. A., Rottenberg, J., & Prinstein, M. J. (2023). Young adult mental health beyond the COVID-19 ERA: Can enlightened policy promote long-term change? Policy insights from the behavioral and brain sciences, 10(1), 75-82. Hughes, C. (2021). The impact of creditworthiness on financial well-being, anxiety, depression, hopelessness, and suicide. Journal of Accounting & Finance (2158-3625), 21(3), 143–160. https://doi.org/10.33423/jaf.v21i3.4400 Jacobs, D., Perera, D., & Williams, T. (2014). Inflation and the cost of living. Bulletin. Reserve Bank of Australia. Joo, S. (2008). Personal financial wellness. In J. J. Xiao (Ed.), Handbook of Consumer Finance Research (pp. 21–33). Springer. Kannadhasan, M., Aramvalarthan, S., Mitra, S. K., & Goyal, V. (2016). Relationship between biopsychosocial factors and financial risk tolerance: An empirical study. Vikalpa, 41(2), 117-131. Kantamneni, N. (2020). The impact of the COVID-19 pandemic on marginalized populations in the United States: A research agenda. Journal of Vocational Behavior, 119, 103439. Kempson, E., & Poppe, C. (2018). Understanding financial well-being and capability - a revised model and comprehensive analysis. Oslo Metropolitan University. Kim, H., & Garman, E. T. (2019). Financial socialization and the role of social capital in reducing financial stress. Journal of Financial Counseling and Planning, 30(2), 239-253. Kim, J., Han, Y., & Lee, H. (2017). Social network types and health status among elderly Koreans. Journal of Community Health Nursing, 34(4), 173-182. Kobayashi, L. C., Wardle, J., Wolf, M. S., & von Wagner, C. (2015). Aging and functional health literacy: A systematic review and meta-analysis. Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 71(3), 445-457. Kochhar, R. (2020, June 11). Unemployment rose higher in three months of COVID-19 than it did in two years of the Great Recession. Pew Research Center. https://www.pewresearch.org/fact- tank/2020/06/11/unemploymentrose- higher-in-three-months-of-COVID-19- than-it-did-intwo-years-of-the-great- recession/ Kop, W. J. (2021). Biopsychosocial processes of health and disease during the COVID-19 pandemic. Psychosomatic Medicine, 83(4), 304-308. McCoy et al. 83 Lee, S., Wickrama, K. K. A. S., Lee, T. K., & O’Neal, C. W. (2021). Long-term physical health consequences of financial and marital stress in middle-aged couples. Journal of Marriage and Family, 83(4), 1212–1226. https://doi.org/10.1111/jomf.12736 Lim, V. K., Teo, T. S., & Loo, G. L. (2019). Effects of financial knowledge, behavior, and well-being: An exploratory study of individuals in Singapore. Journal of Financial Counseling and Planning, 30(1), 110-124. Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52, 5–44. Marron, D. (2013). Governing poverty in a neoliberal age: New labour and the case of financial exclusion. New Political Economy, 18, 785. Masten, A. S. (2001). Ordinary magic: Resilience in development. American Psychologist, 56(3), 227-238. doi: 10.1037/0003- 066X.56.3.227 Masten, A. S. (2014). Global perspectives on resilience in children and youth. Child Development, 85(1), 6-20. doi: 10.1111/cdev.12205 Meyer, J., McDowell, C., Lansing, J., Brower, C., Smith, L., Tully, M., & Herring, M. (2020). Changes in physical activity and sedentary behavior in response to COVID-19 and their associations with mental health in 3,052 US adults. International Journal of Environmental Research and Public Health, 17(18), 6469. Moksnes, U. K., Lazarewicz, M., & Løvgren, M. (2018). Social support and mental health among young Norwegian adults. Scandinavian Journal of Psychology, 59(6), 623-629. Morrow, S. L. (2008). Conceptualizing financial resilience. Journal of Family and Economic Issues, 29(2), 612-623. Morrow, S. L. (2011). Financial capability and asset holding in later life: A life course perspective. Journal of Gerontological Social Work, 54(8), 815-829. Muir, K., & Strnadova, I. (2014). Whose responsibility? Resilience in families of children with developmental disabilities. Disability and Society, 29(6), 922–937. Norris, F., (2010). Behavioural science perspectives on resilience. CARRI Research Paper, 11, Community and Regional Resilience Institute Oak Ridge: Tennessee, USA, 50 pp. Orthner, D. K., Jones-Sanpei, H., & Williamson, S. (2004). The resilience and strengths of low-income families. Family Relations, 53, 129–167. Papanicolas, I., Woskie, L. R., & Jha, A. K. (2018). Health care spending in the United States and other high-income countries. Journal of the American Medical Association, 319(10), 1024- 1039. Pappas, S. (2020). How will people react to the new financial crisis? American Psychological Association. Patel, J. A., Nielsen, F. B. H., Badiani, A. A., Assi, S., Unadkat, V. A., Patel, B., Ravindrane, R. & Wardle, H. (2021). Poverty, inequality and COVID-19: The forgotten vulnerable. Public Health, 183, 110-111. Pfefferbaum, B., & North, C. S. (2020). Mental health and the COVID-19 pandemic. New England Journal of Medicine, 383(6), 510-512. Prati, G., & Mancini, A. (2021). The psychological impact of COVID-19 pandemic lockdowns: A review and meta-analysis of longitudinal studies and natural experiments. Psychological Medicine, 51(2), 201–211. https://doi .org/10.1017/S0033291721000015 Putnam, R. (2000). Bowling alone: The collapse and revival of American community. Simon and Schuster. Financial Services Review, 33(1) 84 Richardson, T., Elliott, P., & Roberts, R. (2013). The relationship between personal unsecured debt and mental and physical health: A systematic review and meta- analysis. Clinical Psychology Review, 33(8), 1148–1162. https://doi.org/10.1016/j.cpr.2013.08.00 9 Rosenström, T., & Jokela, M. (2017). A parsimonious explanation of the resilient, undercontrolled, and overcontrolled personality types. European Journal of Personality, 31(6), 658-668. Rothmann, S., & Coetzer, E. P. (2003). The big five personality dimensions and job performance. SA Journal of Industrial Psychology, 29(1), 68-74. Ryu, S., & Fan, L. (2023). The relationship between financial worries and psychological distress among US adults. Journal of Family and Economic Issues, 44(1), 16-33. Salari, N., Hosseinian-Far, A., Jalali, R., Vaisi- Raygani, A., Rasoulpoor, S., Mohammadi, M., Rasoulpoor, S., & Khaledi Paveh, B. (2020). Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: A systematic review and meta-analysis. Globalization and Health, 16(1), Article 57. https://doi.org/10.1186/ s12992-020- 00589-w Salignac, F., Hanoteau, J., & Ramia, I. (2022). Financial resilience: A way forward towards economic development in developing countries. Social Indicators Research, 160(1), 1-33. Salignac, F., Marjolin, A., Reeve, R., & Muir, K. (2019). Conceptualizing and measuring financial resilience: A multidimensional framework. Social Indicators Research, 145(1), 17–38. https://doi.org/10.1007/s11205-019- 02100-4 Salignac, F., Muir, K., & Wong, J. (2016). Are you really financially excluded if you choose not to be included? Insights from social exclusion resilience and ecological systems. Journal of Social Policy, 45(2), 269–286. https://doi.org/10.1017/S004727941500 0677 Scrivens, & Smith, C. (2013). Four interpretations of social capital. (OECD Statistics Working Papers, No. 2013/6). Seay, M. C., Kubik, M. Y., & Grymes, M. R. (2019). Financial education, financial behavior, and psychological distress: An examination of the mediating influence of financial behaviors. Journal of Financial Counseling and Planning, 30(1), 86-99. Serido, J., Shim, S., & Tang, C. (2013). A developmental model of financial capability: A framework for promoting a successful transition to adulthood. International Journal of Behavioural Development, 37, 287–297. Shadmi, E., Chen, Y., Dourado, I., Faran-Perach, I., Furler, J., Hangoma, P., Piya Hanvoravongchai, Obando, C., Petrosyan, V., Rao, K.D., Ruano, A.L., Shi, L. de Souza, L.E., Spitzer-Shohat, S., Sturgiss, E., Suphanchaimat, R., Uribe, M.V., Willems, S. & Shi, L. (2020). Health equity and COVID-19: Global perspectives. International Journal for Equity in Health, 19(1), 1-16. Shandler, R., Gross, M. L., & Canetti, D. (2023). Cyberattacks, psychological distress, and military escalation: An internal meta- analysis. Journal of Global Security Studies, 8(1), ogac042. Sherraden, M. (1991). Assets and the Poor: A new American welfare policy. Armonk, NY: M.E. Sharpe. Skodol, A.E. The resilient personality. Handbook of Adult Resilience; Guilford Press: New York, NY, USA, 2010; Volume 112 Sweet, E., Nandi, A., Adam, E. K., & McDade, T. W. (2013). The high price of debt: Household financial debt and its impact on mental and physical health. Social McCoy et al. 85 Science & Medicine, 91, 94–100. https://doi.org/10.1016/j.socscimed.201 3.05.009 Todorova, I. L., Tucker, K. L., Jimenez, M. P., Lincoln, A. K., Arevalo, S., & Falcón, L. M. (2013). Determinants of self-rated health and the role of acculturation: Implications for health inequalities. Ethnicity & Health, 18(6), 563-585. Tran, B. X., Nguyen, H. T., Le, H. T., Latkin, C. A., Pham, H. Q., Vu, L. G., Le, X., Nguyen, T. T., Pham, Q. T., Ta, N., Nguyen, Q. T., Ho, C., & Ho, R. (2020). Impact of COVID-19 on economic well- being and quality of life of the Vietnamese during the national social distancing. Frontiers in Psychology, 11, Article 565153. https://doi .org/10.3389/fpsyg.2020.565153 Tsamakis, K., Triantafyllis, A. S., Tsiptsios, D., Spartalis, E., Mueller, C., Tsamakis, C., Chaidou, S., Spandidos, D.A., Fotis, L., Economou, M., & Rizos, E. (2020). COVID‑19 related stress exacerbates common physical and mental pathologies and affects treatment. Experimental and Therapeutic Medicine, 20(1), 159-162. Werner, E. E., & Smith, R. S. (1982). Vulnerability and resiliency in children: A longitudinal study. American Journal of Orthopsychiatry, 52(4), 559-567. doi: 10.1111/j.1939-0025.1982.tb01456.x Windle, G. (2011). What is resilience? A review and concept analysis. Reviews in Clinical Gerontology, 21(2), 152-169. https://doi.org/10.1017/S095925981000 0420. Zahedi, J., Salehi, M., & Moradi, M. (2022). Identifying and classifying the contributing factors to financial resilience. Foresight, 24(2), 177-194. Zhu, H., Luo, X., & Wang, D. (2019). How does financial access affect health outcomes? Evidence from China. Applied Economics Letters, 26(10), 825-831. https://doi.org/10.1017/S0959259810000420 https://doi.org/10.1017/S0959259810000420