Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Aug 21.
Published in final edited form as: Ment Health Prev. 2026 Aug 1;43:200547. doi: 10.1016/j.mhp.2026.200547

Money and the Mind: Financial Well-Being, Mental Health, and Loneliness in a Large Cohort of Emerging Adults

Daniel Siconolfi a, Joan S Tucker b, Rachana Seelam b, Wendy Troxel a, Elizabeth J D’Amico b
PMCID: PMC13484321  NIHMSID: NIHMS2200441  PMID: 42614734

Abstract

Objective:

Financial challenges are common during emerging adulthood (ages 18–29) and may have implications for mental health and social relationships. Research with adults more generally indicates that debt and financial distress are associated with a range of poor health and social outcomes. However, most research has not addressed emerging adulthood, an important developmental period. Additionally, research with emerging adults has focused on debt burden rather than the broader concept of financial well-being which reflects a more holistic assessment of capabilities, future opportunities, and security. We examined financial well-being as a predictor of subsequent changes in mental health and loneliness among emerging adults.

Methods:

A community sample of emerging adults (N=2,157) completed surveys in 2021–22 (mean age=25) and 2022–23 (mean age=26) measuring financial well-being, depression symptoms, anxiety symptoms, and loneliness. We used longitudinal multivariable linear regression models to examine financial well-being and perceived debt burden, both independently and simultaneously, as predictors of change in outcomes one year later.

Results:

Lower financial well-being was prospectively associated with greater depression symptoms, anxiety symptoms, and loneliness. Debt burden had no independent prospective association with any of the three mental health outcomes.

Conclusion:

Broader measures of financial well-being may be more relevant than debt burden or understanding mental health outcomes. Assessing financial well-being may help identify individuals at risk for psychological distress. In addition to upstream efforts to reduce drivers of debt and poor financial well-being, there is a need for greater attention to links between economic circumstances and outcomes during this critical developmental period.

Keywords: financial stress, mental health, loneliness, emerging adults, young adult

1. Introduction

Emerging adulthood (ages 18–29) is a distinct developmental stage during which individuals typically are exploring identities and possibilities, often characterized by instability and transitions into greater independence from families of origin (Arnett, 2007; Arnett et al., 2014). It is also a period of life when many individuals struggle with unmet mental health needs. In the U.S., about 1 in 10 emerging adults (9.8%) report moderate or severe anxiety symptoms, with identical prevalence (9.8%) for moderate or severe depression symptoms (Terlizzi & Zablotsky, 2024). Further, about 1 in 4 emerging adults (24%) report significant loneliness (Witters, 2023). In addition to the more general contributors to poor mental health (e.g., hereditary risk factors), myriad antecedents and correlates of mental health problems during emerging adulthood have been documented. These span early life adversities, difficulties in peer and social relationships, increases in substance use, and delays or deficits in the development of skills and supports that may otherwise help buffer a period characterized by instability, and gaps between youth versus adult systems of care (Anderson et al., 2022; Arnett et al., 2014; Winzer et al., 2014; Wood et al., 2018).

As emerging adults in the United States (U.S.) navigate this important period between adolescence and established adulthood, many face challenges to achieving financial independence and security, which is a key developmental task for this period (Arnett, 2007; Wood et al., 2018). For example, U.S. college graduates with student loans had borrowed $29,417 on average, with average student debt increasing 8% from 2012 to 2022 (Wood, 2023). Another national U.S. study found that nearly 1 in 5 emerging adults with a credit record had debt in collections, suggesting an inability to meet their current financial obligations such as credit card, auto loan, medical, and student debt (Martinchek et al., 2022). One study of over 3,000 emerging adults in the U.S. found that 1 in 3 were financially precarious, characterized by relatively few financial socialization opportunities, limited access to banking services, low financial literacy, and high use of alternative financial services (e.g., payday loan stores) (Sinha et al., 2018). Compounding these challenges, the economic downturn that accompanied the COVID-19 pandemic particularly affected emerging adults (Gould & Kassa, 2020) and may continue to have reverberating effects on employment opportunities and financial security for some time.

Given the significant financial challenges facing many emerging adults, it is important to understand how these experiences may influence mental health. To date, evidence from the general population and historical cohorts of young adults has linked debt burden and financial problems with poor health outcomes (Bialowolski et al., 2021; Nykiforuk et al., 2023; Walsemann et al., 2015). For example, one study using data from the National Longitudinal Study of Adolescent Health found that high financial debt relative to available assets was cross-sectionally associated with higher perceived stress and depression, even after controlling for prior socioeconomic status, psychological and physical health, and other demographic factors (Sweet et al., 2013). Among young adults in the Transition into Adulthood Study, increases of $1,000 in student loan and credit card debt have been associated with 6% and 4% greater odds of psychological distress (Zhang & Kim, 2018). Other analyses with the Transition into Adulthood Study have found similar results (Kim & Chatterjee, 2021). Further, two studies using data from the National Longitudinal Survey of Youth (NLSY) found that greater cumulative student loan amounts were associated with poorer mental health (Qian & Fan, 2023; Walsemann et al., 2015), although this association was limited to young men in one of the studies (Qian & Fan, 2023).

Several mechanisms explain these connections between debt or financial problems and mental health outcomes, including behavioral, physiological, social, and economic pathways. Most broadly, links between financial problems, mental health outcomes, and loneliness can be understood as a stress process; if an individual lacks intra- and interpersonal resources that may otherwise buffer this stress, they are at risk for negative outcomes (Pearlin et al., 1981). Extensive research also shows that socioeconomic disadvantage and financial distress are associated with physiological stress responses, unmet needs and barriers to care, and inadequate social support (Bialowolski et al., 2021; Ryu & Fan, 2023). For example, financial strain may contribute to hopelessness about the future, a sense of helplessness and unfairness in current financial circumstances, and a sense of worthlessness and a negative view of the self, which comprise a triad of negative affect in depression (Beck et al., 1979; Marchetti & Possel, 2023). Financial strain may also cause or exacerbate anxiety, especially with regard to chronic worries about an uncertain future, a perceived lack of safety in the external world and daily circumstances, and hypervigilance toward potential threats (Portman, 2009). Debt and financial strain can also impede access to treatment, with studies finding that about 2 in 5 adults ages 18–25 (43%) and about 1 in 5 adults ages 26 to 49 (29%) with any mental illness reported unmet treatment needs, and more than half of all adults with unmet mental health needs endorsed cost as a barrier (Substance Abuse and Mental Health Services Administration, 2023). Although less research has focused on social consequences, financial problems may also impede social activities (e.g., participation in shared activities with friends), which may contribute to greater loneliness and isolation (Kung et al., 2022). In turn, loneliness and social isolation are associated with a wide range of adverse health outcomes (Office of the Surgeon General, 2023).

Many emerging adults also report stress and pessimism about their finances, for example, with regard to living comfortably, paying bills, affording housing, absorbing shocks, and attaining a better standard of living than their parents (Gallup, 2023). These concerns extend beyond a relatively narrow focus on debt and instead reflect a more holistic concept of financial well-being: “a state of being wherein a person can fully meet current and ongoing financial obligations, can feel secure in their financial future, and is able to make choices that allow enjoyment of life” (Consumer Financial Protection Bureau, 2015a, p. 18). Emerging adults tend to have lower financial well-being scores than midlife or older adults, reflecting potential difficulties, insecurity, and barriers to quality of life (Consumer Financial Protection Bureau, 2017).

As a more holistic indicator than debt burden, financial well-being may be more sensitive to associations between financial experiences and mental health outcomes. Financial well-being may also have unique pathways to mental health (e.g., hope, mastery, safety and security). However, virtually all research with emerging adults, including the studies cited above, has focused on the narrower concept of debt burden, or other factors like financial literacy, rather than examining how financial well-being may affect health and functional outcomes (Sorgente & Lanz, 2017). Financial difficulties and mental health problems during emerging adulthood can have lasting implications for lifecourse health and well-being across a range of domains including education and career, health and well-being, relationships, and important life skills (Wood et al., 2018). Given these long-term implications, it is critical to understand whether and how debt and financial well-being may influence health and functional outcomes for this age group.

To address these gaps, we examined longitudinal associations between financial well-being and mental health (depression symptoms, anxiety symptoms) and loneliness in a large, diverse, contemporary sample of emerging adults. We hypothesized that greater financial well-being would be associated with better mental health and less loneliness at one-year follow-up. We also hypothesized that financial well-being, as a more holistic concept, would maintain a statistically significant association with these outcomes even after controlling for debt burden.

2. Methods

2.1. Sample

Briefly, members of a longitudinal cohort completed self-administered online surveys that were scheduled one year apart. Study procedures and detailed information about the sample are freely available in PubMed Central-indexed publications (D’Amico et al., 2020; D’Amico et al., 2016). All procedures were approved by the institutional review board at RAND.

Participants were originally from two cohorts of middle school students recruited in 2008–2009 from 16 schools across three school districts in Southern California as part of a cluster randomized trial evaluating a voluntary after-school substance use prevention program (D’Amico et al., 2012). Parental consent forms were distributed across all 16 schools; 71% of parents provided consent and 94% of these students completed the baseline survey. The trial sample’s demographics were comparable to the school populations’ demographics, baseline rates of substance use were comparable to national estimates, and study retention did not vary between intervention and control schools (89% and 88%, respectively) (D’Amico et al., 2012). Intervention effects dissipated by the third assessment wave (2009). Over time, the cohort has continued to participate in self-administered online surveys, with 15 annual waves completed through 2023. Participants who miss a given survey wave are not “dropped” from the study and are invited to each future wave, and wave-to-wave retention rates average 87%.

The financial well-being and debt burden items of focus for this analysis were first assessed at Wave 14. The current analysis uses all available data from participants who completed surveys at both Wave 14 (W14; 2021–2022, mean age = 24.7) and Wave 15 (W15; 2022–2023, mean age = 25.8; 92% of those present at Wave 14) and who were not missing data on financial well-being (n = 19). The final analytic sample included n = 2,157 emerging adults.

A dataset is available through the National Institute of Mental Health Data Archive (NDA). However, data for the full sample in this paper are not publicly available due to human subject protections and participant opt-in consent procedures for inclusion of individual participant data in the public dataset. Analytic code is available upon request by contacting the corresponding or senior authors.

2.2. Measures.

Demographic control variables at Wave 14.

Participants reported their current age (years), sex assigned at birth (male/female), race and ethnicity, sexual and gender diverse identity (no/yes, based on responses to questions about sexual orientation and gender identity), and educational attainment (having completed a 2- or 4-year degree vs. not). We also controlled for intervention status at Wave 1 in 2008 to be conservative, although intervention effects on substance use were no longer significant by Wave 3.

Debt burden and financial well-being at Wave 14.

Perceived debt burden was assessed with a single item from the National Financial Capability Study (Lin et al., 2022): “I have too much debt right now” (1 = strongly disagree to 7 = strongly agree).

Financial well-being was assessed with the abbreviated 5-item version of the Consumer Financial Protection Bureau (CFPB) Financial Well-Being Scale (Consumer Financial Protection Bureau, 2015b; α = 0.78). The scale is designed to assess four elements of financial well-being with regard to security (control over daily finances; capacity to absorb a financial shock) and freedom of choice (the ability to make choices to enjoy life; being on track to meet one’s financial goals). Respondents rate how well a given statement describes them or their situation for three items (e.g., “I am concerned that the money I have or will save won’t last.” [Completely; Very well; Somewhat; Very little; Not at all]), and how often a statement applies to them for two items (e.g., “My finances control my life.” [Always; Often; Sometimes; Rarely; Never]). One item (“I have money left over at the end of the month”) is reverse-scored and then all item responses are summed and crosswalked to population normalized scores that are publicly available in the measure user’s guide (Consumer Financial Protection Bureau, 2015b). Normed scores range from 19 to 82 and higher scores reflect greater well-being.

Mental health at Waves 14 and 15.

Depression symptoms in the past two weeks were measured with the Patient Health Questionnaire-8 (Kroenke et al., 2009; α = 0.93 at Wave 15). Anxiety symptoms in the past two weeks were measured using the Generalized Anxiety Disorder-7 (Spitzer et al., 2006; α = 0.95 at Wave 15). Responses are summed and higher scores indicate greater depression and anxiety symptoms, respectively, with continuous scores used for the analysis.

Loneliness at Waves 14 and 15.

Loneliness was assessed using the Three-Item Loneliness Scale (Hughes et al., 2004; α = 0.88 at Wave 15). Responses were summed such that higher scores indicate greater loneliness, with continuous scores used for the analysis.

2.3. Analytic approach.

We calculated univariate descriptive statistics to characterize the sample. We also used Pearson correlations to examine associations between debt burden and financial well-being, and between depression symptoms, anxiety symptoms, and loneliness symptoms. We used multivariable linear regression models to test for longitudinal associations between financial well-being and debt burden and the outcomes (depression, anxiety, and loneliness), controlling for initial levels of these outcomes at Wave 14. For each of the outcomes, we constructed three models: 1) financial well-being as the only predictor; 2) debt burden as the only predictor, and 3) financial well-being and debt burden as simultaneous predictors. All models also controlled for age, sex at birth, having completed a 2- or 4-year college degree, race and ethnicity, SGD identity, and childhood intervention condition (see 2.1.). Missing data for models were addressed with pairwise deletion. Analyses were conducted in SAS 9.4 (SAS Institute Inc., 2023) and Figure 1 was created in Stata 19.5 (StataCorp, 2025) using the vioplot package (Winter & Nichols, 2012).

Figure 1. Distribution of financial wellbeing scores by perceived debt burden, 2014.

Figure 1.

Open in a new tab

CFPB = Consumer Financial Protection Bureau. Higher financial well-being scores reflect greater well-being. Central dots indicate medians, bold black lines indicate the interquartile range, and violins reflect the probability density of financial well-being scores across subjective debt burden strata.

3. Results

The mean age of the sample at Wave 14 was 24.7 (SD = 0.8). Slightly more participants were female (56.2%) than male (43.8%). The majority had completed a 2- or 4-year degree (66.3%). Most identified as Hispanic (46.6%), followed by non-Hispanic White (23.6%) or non-Hispanic Asian (22.7%), and non-Hispanic Black, multiracial, or another racial identity (7.1%). Detailed demographics are shown in Table 1. Correlations between depression symptoms, anxiety symptoms, and loneliness are shown in Supplemental Table 1; briefly, loneliness was moderately correlated with depression symptoms (r = 0.53; r = 0.53) and anxiety symptoms (r = 0.48; r = 0.48) at Waves 14 and 15, respectively.

Table 1.

Demographic Characteristics and Health Outcomes (N = 2,157).

Demographics Wave 14 Mean (SD) or % (n)
Age in years 24.7 (SD = 0.8)
Female sex 56.2% (n = 1211)
Race and ethnicity
Hispanic 46.6% (n = 1006)
Asian 22.7% (n = 490)
Non-Hispanic White 23.6% (n = 509)
Black/Multiracial/other 7.1% (n = 152)
Sexual and gender diverse (SGD) identity 21.8% (n = 471)
Higher education (2- or 4-year) degree completion 66.3% (n = 1430)
Debt burden and financial well-being
 Debt burden (range: 1–7) 3.2 (SD = 2.2)
 Financial well-being (range: 19–82) 55.3 (SD = 12.2)
Outcomes Wave 14 Mean (SD) Wave 15 Mean (SD)
Anxiety symptoms (GAD-7; range: 0–21) 5.2 (SD = 5.5) 4.5 (SD = 5.5)
Depression symptoms (PHQ-8; range: 0–24) 5.6 (SD = 5.7) 4.7 (SD = 5.5)
Loneliness (UCLA-3; range: 3–9) 4.9 (SD = 1.9) 4.8 (SD = 1.9)
Open in a new tab

Note. Higher scores indicate greater depression symptoms, anxiety symptoms, and loneliness. Scores of ≥ 10 on the PHQ-8 and GAD-7 indicate moderate or greater levels of depression and anxiety.

Overall, 28% of participants at W14 agreed that they had too much debt (M = 3.2; SD = 2.2). Mean financial well-being at W14 was 55.3 (SD = 12.2) and ranged from 19 to 82. The correlations between debt burden and financial well-being at Waves 14 and 15 were r = −0.39 and r = −0.46, respectively, suggesting that these are related but conceptually distinct constructs. This is shown with greater nuance in Figure 1, which depicts the distribution of debt burden and financial well-being using violin plots. Although there was a trend suggesting that median financial well-being increased at lower levels of debt burden (a moderate negative association), the financial well-being scores were widely distributed across levels of self-rated debt burden, suggesting substantial variability in financial well-being within and across the seven strata of subjective debt burden.

Multivariable model results are shown in Table 2. In Model 1, greater financial well-being at the previous wave was associated with lower anxiety symptoms (−0.047 [95% CI: −0.064, −0.030], p < .001), lower depression symptoms (−0.055 [95% CI: −0.073, −0.038], p < .001), and less loneliness (−0.015 [95% CI: −0.021, −0.009], p < .001) at the subsequent wave.

Table 2.

Multivariable models examining Wave 14 financial well-being and debt burden as predictors of change in Wave 15 mental health and loneliness.

W15 Anxiety Symptoms W15 Depression Symptoms W15 Loneliness
Estimate 95% CI p-value Estimate 95% CI p-value Estimate 95% CI p-value
Model 1
 W14 Financial well-being −0.047‡ −0.064, −0.030 <.001 −.055‡ −0.073, −0.038 <.001 −.015‡ −0.021, −0.009 <.001
Model 2
 W14 Debt burden 0.114* 0.025, 0.203 .012 0.142† 0.051, 0.232 .002 .044† 0.013, 0.075 .006
Model 3
 W14 Financial well-being −0.045‡ −0.063, −0.027 <.001 −0.053‡ −0.071, −0.034 <.001 −0.014‡ −0.020, −0.008 <.001
 W14 Debt burden 0.033 −0.062, 0.128 .494 0.044 −0.052, 0.141 .365 0.017 −0.016, 0.050 .314
Open in a new tab

Models adjust for middle school intervention condition, age, sex, 2- or 4-year degree completion, race and ethnicity, sexual and gender minority identity, and corresponding mental health variable at the previous wave (e.g., W15 anxiety symptoms are adjusted for W14 anxiety symptoms).

*

p < .05.

†

p < .01.

‡

p < .001.

In Model 2, debt burden at the previous wave was associated with greater anxiety symptoms (0.114 [95% CI: 0.025, 0.203], p = .012), greater depression symptoms (0.142 [95% CI: 0.051, 0.232], p = .002), and greater loneliness (0.044 [95% CI: 0.013, 0.075], p = .006) at the subsequent wave.

Finally, Model 3 included both financial well-being and debt burden. Only financial well-being was associated with the outcomes. Specifically, prior wave financial well-being was associated with lower anxiety symptoms (−0.045 [95% CI: −0.063, −0.027], p < .001), lower depressive symptoms (−0.053 [95% CI: −0.071, −0.034], p < .001) and less loneliness (−0.014 [95% CI: −0.020, −0.008], p < .001) at the subsequent wave.

4. Discussion

Achieving financial independence is an important milestone during the transition to adulthood for emerging adults in the U.S., and financial resources during this time can affect important life decisions and milestones such as moving out, going to college, partnership and marriage, having children, and buying a home (National Endowment for Financial Education, 2014). Both of our hypotheses were supported by the findings. First, consistent with our hypothesis, financial well-being affected mental health and loneliness outcomes one year later. Emerging adults who reported greater financial well-being were more likely to report less depression, anxiety, and loneliness. Second, also consistent with our hypothesis, financial well-being was a more robust predictor of mental health than debt burden. This is likely because financial well-being is a broader and more holistic construct that subsumes subjective debt burden and is a construct that is likely to more fully capture the psychological experience of financial status. We note that debt burden and financial well-being were only moderately correlated, indicating that they are distinguishable and not multicollinear. This finding highlights the greater explanatory breadth of financial well-being; whereas debt burden is a single, specific financial marker, financial well-being is a more holistic appraisal spanning current and future states along with security and freedom of choice (Consumer Financial Protection Bureau, 2015b).

Our finding that debt burden alone was prospectively associated with poorer mental health is consistent with previous research (Bialowolski et al., 2021; Kim & Chatterjee, 2021; Nykiforuk et al., 2023; Qian & Fan, 2023; Walsemann et al., 2015; Zhang & Kim, 2018). However, our findings address gaps in the existing literature in several ways. First, most research with emerging adults has focused on debt burden (e.g., subjective burden, objective amounts), but the present study suggests that these debt-focused indicators may be insufficient measures of financial lived experience. This underscores the need for future research to incorporate broader appraisals of financial well-being. Second, few studies have focused on emerging adults, and this is especially true with regard to longitudinal design. Our one-year follow-up provides stronger evidence for the temporal ordering of financial well-being as a predictor of mental health and loneliness outcomes. Third, we incorporated loneliness as a social outcome, which has been almost completely neglected in existing research on the impacts of debt and financial well-being, despite the epidemic of loneliness and social isolation in the U.S. (Office of the Surgeon General, 2023).

From a prevention and policy perspective, financial well-being and its mental health correlates are important to address because experiences during this key developmental period can affect trajectories for subsequent adulthood years (Wood et al., 2018). Poor mental health during emerging adulthood can lead to limited opportunities across a wide range of domains. These include exploration and identity development, education, employment and careers, deepening social and romantic relationships, physical health and well-being, and finally, development of skills for thriving and environmental mastery that help individuals cope with inevitable stressors across the life course (Wood et al., 2018). Perceived cost and affordability are also significant barriers to accessing mental health treatment that might otherwise improve these symptoms. (Substance Abuse and Mental Health Services Administration, 2023). Although financial well-being is typically examined as a point-in-time characteristic, a life course perspective may be more appropriate given the lifelong dynamic between financial well-being and the socioecological context (Consumer Financial Protection Bureau, 2015a; Salignac et al., 2019).

These findings also highlight the potential utility of framing financial well-being as a public health issue (Bialowolski et al., 2021; Nykiforuk et al., 2023; Walsemann et al., 2015). For example, targeted policies aimed at protecting emerging adults from accumulating unmanageable debt are needed (Martinchek et al., 2022). Others have suggested the need for public mental health campaigns that could destigmatize financial-related psychosocial distress and provide education and referrals (Ryu & Fan, 2023).

This study also examined loneliness, which has been understudied in the literature on financial instability among young people and findings showed that emerging adults with greater financial well-being were less lonely. Further research is needed to understand the mechanisms underlying this association. For example, future research could explore the extent to which loneliness is due to having fewer resources to go out and socialize with friends, versus upward comparison of one’s own financial status to that of peers (e.g., on social media). Regardless of the underlying mechanism driving this association, our results highlight that greater attention to financial instability as a contributing factor is warranted in the nation’s efforts to tackle its epidemic of loneliness, including among emerging adults (Office of the Surgeon General, 2023). We note that loneliness is generally associated with poorer mental health, including depression and anxiety symptoms (Christiansen et al., 2021; Mann et al., 2022), although in this study the correlations were only moderate, suggesting that each of these are somewhat distinct experiences in this sample. Future research should examine whether loneliness may mediate prospective associations between financial well-being and mental health outcomes, which would require more robust multi-wave designs with appropriate temporal spacing between predictor, mediator, and outcome measures.

Finally, our findings align with the broader literature showing that subjective socioeconomic status is typically a stronger predictor of health and mental health outcomes than objective socioeconomic status and that subjective assessments likely reflect individuals’ perceptions of social comparisons, security and control, and future opportunities (Hoebel & Lampert, 2020; Quon & McGrath, 2014). These dynamics may be particularly salient during emerging adulthood, a developmental period characterized by transitions in financial independence and expectations for future economic stability, and the financial well-being measure is especially attuned to these specific experiences (e.g., feeling that money “controls my life,” that I am “just getting by,” and an expectation to never obtain “the things I want in life.”).

4.1. Limitations.

Several study limitations apply. First, results are based on a U.S.-based cohort predominantly based in California that was originally recruited for a middle school substance use intervention. Participants still largely reside in California, and results may not generalize to emerging adults in international settings or other parts of the U.S. (e.g., California has one of the highest costs of living in the country (MERIC, 2024). Data were also collected during the COVID-19 public health emergency, a time of significant social and economic instability and temporary policy influences (e.g., stimulus payments) which may have influenced financial status and mental health. Second, all data are self-reported and subject to social desirability bias. Third, the debt burden measure consisted of a single item and may not fully capture this construct. Fourth, financial well-being is an inherently subjective measure, and should not be interpreted as an objective measure of financial status (e.g., an individual with low income may still report high financial wellbeing). Fifth, reverse causality is a plausible explanation for the associations we found; for example, individuals with better mental health may perceive their financial situation more positively and report greater financial well-being. Finally, although our use of a longitudinal design is a strength, future research is needed to understand the extent to which financial well-being has longer-term impacts on functioning that may persist into adulthood.

4.2. Conclusions.

This study addresses gaps in knowledge regarding financial well-being and mental health and loneliness outcomes among contemporary emerging adults and suggests that financial well-being can contribute to better mental health and less loneliness among emerging adults. Findings highlight the importance of addressing upstream, structural efforts to reduce drivers of poor financial well-being and greater research and policy attention to the links between economic circumstances and health outcomes during this critical developmental period.

Supplementary Material

1

Acknowledgements:

We thank the study participants and districts and schools who participated and supported the CHOICE project. We also thank Jennifer Parker for survey administration. This research was supported by the National Institute on Alcohol Abuse and Alcoholism (R01AA016577, R01AA020883, R01AA025848, R01AA028812; PI: D’Amico). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This manuscript is the result of funding in whole or in part by the National Institutes of Health (NIH). It is subject to the NIH Public Access Policy. Through acceptance of this federal funding, NIH has been given a right to make this manuscript publicly available in PubMed Central upon the Official Date of Publication, as defined by NIH.

Footnotes

Declaration of competing interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

CRediT statement: DS: Conceptualization, Investigation, Methodology, Visualization, Writing - Original Draft, Writing - Review & Editing; JT: Conceptualization, Investigation, Methodology, Supervision, Writing - Original Draft, Writing - Review & Editing; RS: Data curation, Formal analysis, Methodology, Writing - Review & Editing; WT: Conceptualization, Investigation, Methodology, Writing - Review & Editing; ED: Conceptualization, Funding acquisition, Investigation, Methodology, Writing - Review & Editing.

AI Declaration: During the preparation of this work, the first author used Anthropic’s Claude 3.6 (Sonnet) for critical review of drafts and used Elicit to support the literature review. The first author reviewed and edited the output as needed and takes full responsibility for the content of the published article.

REFERENCES

  1. Anderson JK, Newlove-Delgado T, & Ford TJ. (2022). Annual research review: A systematic review of mental health services for emerging adults - moulding a precipice into a smooth passage. Journal of Child Psychology and Psychiatry, 63(4), 447–462. 10.1111/jcpp.13561 [DOI] [PubMed] [Google Scholar]
  2. Arnett JJ. (2007). Emerging adulthood: What is it, and what is it good for? Child Development Perspectives, 1(2), 68–73. 10.1111/j.1750-8606.2007.00016.x [DOI] [Google Scholar]
  3. Arnett JJ, Žukauskienė R, & Sugimura K. (2014). The new life stage of emerging adulthood at ages 18–29 years: Implications for mental health. The Lancet Psychiatry, 1(7), 569–576. 10.1016/s2215-0366(14)00080-7 [DOI] [PubMed] [Google Scholar]
  4. Beck A, Rush J, Shaw B, & Emery G. (1979). Cognitive therapy of depression. Guilford Press. [Google Scholar]
  5. Bialowolski P, Weziak-Bialowolska D, Lee MT, Chen Y, VanderWeele TJ, & McNeely E. (2021). The role of financial conditions for physical and mental health. Evidence from a longitudinal survey and insurance claims data. Social Science and Medicine, 281, 114041. 10.1016/j.socscimed.2021.114041 [DOI] [PubMed] [Google Scholar]
  6. Christiansen J, Qualter P, Friis K, Pedersen SS, Lund R, Andersen CM, Bekker-Jeppesen M, & Lasgaard M. (2021). Associations of loneliness and social isolation with physical and mental health among adolescents and young adults. Perspectives in Public Health, 141(4), 226–236. 10.1177/17579139211016077 [DOI] [PubMed] [Google Scholar]
  7. Consumer Financial Protection Bureau. (2015a). Financial well-being: The goal of financial education. https://www.consumerfinance.gov/data-research/research-reports/financial-well-being/
  8. Consumer Financial Protection Bureau. (2015b). Measuring financial well-being: A guide to using the CFPB Financial Well-Being Scale. https://files.consumerfinance.gov/f/201512_cfpb_financial-well-being-user-guide-scale.pdf
  9. Consumer Financial Protection Bureau. (2017). Financial well-being in America. https://www.consumerfinance.gov/data-research/research-reports/financial-well-being-america/
  10. D’Amico EJ, Rodriguez A, Tucker JS, Dunbar MS, Pedersen ER, Shih RA, Davis JP, & Seelam R. (2020). Early and late adolescent factors that predict co-use of cannabis with alcohol and tobacco in young adulthood. Prevention Science, 21(4), 530–544. 10.1007/s11121-020-01086-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. D’Amico EJ, Tucker JS, Miles JN, Ewing BA, Shih RA, & Pedersen ER. (2016). Alcohol and marijuana use trajectories in a diverse longitudinal sample of adolescents: Examining use patterns from age 11 to 17 years. Addiction, 111(10), 1825–1835. 10.1111/add.13442 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. D’Amico EJ, Tucker JS, Miles JN, Zhou AJ, Shih RA, & Green HD Jr. (2012). Preventing alcohol use with a voluntary after-school program for middle school students: Results from a cluster randomized controlled trial of CHOICE. Prevention Science, 13(4), 415–425. 10.1007/s11121-011-0269-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Gallup. (2023). Americans remain discouraged about personal finances. https://news.gallup.com/file/poll/506081/20230518PersonalFinances.pdf
  14. Gould E, & Kassa M. (2020). Young workers hit hard by the COVID-19 economy: Workers ages 16–24 face high unemployment and an uncertain future. https://files.epi.org/pdf/203139.pdf
  15. Hoebel J, & Lampert T. (2020). Subjective social status and health: Multidisciplinary explanations and methodological challenges. Journal of Health Psychology, 25(2), 173–185. 10.1177/1359105318800804 [DOI] [PubMed] [Google Scholar]
  16. Hughes ME, Waite LJ, Hawkley LC, & Cacioppo JT. (2004). A short scale for measuring loneliness in large surveys: Results from two population-based studies. Research on Aging, 26(6), 655–672. 10.1177/0164027504268574 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kim J, & Chatterjee S. (2021). Financial debt and mental health of young adults. Journal of Financial Counseling and Planning. 10.1891/jfcp-18-00048 [DOI] [Google Scholar]
  18. Kroenke K, Strine TW, Spitzer RL, Williams JB, Berry JT, & Mokdad AH. (2009). The PHQ-8 as a measure of current depression in the general population. Journal of Affective Disorders, 114(1–3), 163–173. 10.1016/j.jad.2008.06.026 [DOI] [PubMed] [Google Scholar]
  19. Kung CSJ, Pudney SE, & Shields MA. (2022). Economic gradients in loneliness, social isolation and social support: Evidence from the UK Biobank. Social Science and Medicine, 306, 115122. 10.1016/j.socscimed.2022.115122 [DOI] [PubMed] [Google Scholar]
  20. Lin JT, Bumcrot C, Mottola G, Valdes O, Ganem R, Kieffer C, Lusardi A, & Walsh G. (2022). Financial capability in the United States: Highlights from the FINRA Foundation National Financial Capability Study (5th edition). www.FINRAFoundation.org/NFCSReport2021 [Google Scholar]
  21. Mann F, Wang J, Pearce E, Ma R, Schlief M, Lloyd-Evans B, Ikhtabi S, & Johnson S. (2022). Loneliness and the onset of new mental health problems in the general population. Social Psychiatry and Psychiatric Epidemiology, 57(11), 2161–2178. 10.1007/s00127-022-02261-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Marchetti I, & Possel P. (2023). Cognitive triad and depressive symptoms in adolescence: Specificity and overlap. Child Psychiatry & Human Development, 54(4), 1209–1217. 10.1007/s10578-022-01323-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Martinchek K, Andre J, & Santillo M. (2022). What can policymakers do to help young adults cope with debt? Credit health among adults ages 18 to 24. https://www.urban.org/sites/default/files/2022-12/What%20Can%20Policymakers%20Do%20to%20Help%20Young%20Adults%20Cope%20with%20Debt.pdf
  24. MERIC. (2024). Cost of living data series. https://meric.mo.gov/data/cost-living-data-series
  25. National Endowment for Financial Education. (2014). Money and milestones: The impact of debt on young adults’ financial life transitions. https://www.nefe.org/_images/research/Financial-Behavior-Debt-Early-Life-Transitions/Financial-Behavior-Debt-Early-Life-Transitions-Executive-Summary.pdf
  26. Nykiforuk CIJ, Belon AP, de Leeuw E, Harris P, Allen-Scott L, Atkey K, Glenn NM, Hyshka E, Jaques K, Kongats K, Montesanti S, Nieuwendyk LM, Pabayo R, Springett J, & Yashadhana A. (2023). An action-oriented public health framework to reduce financial strain and promote financial wellbeing in high-income countries. International Journal for Equity in Health, 22(1), 66. 10.1186/s12939-023-01877-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Office of the Surgeon General. (2023). Our epidemic of loneliness and isolation: The U.S. Surgeon General’s Advisory on the healing effects of social connection and community. https://www.hhs.gov/sites/default/files/surgeon-general-social-connection-advisory.pdf [PubMed]
  28. Pearlin LI, Menaghan EG, Lieberman MA, & Mullan JT. (1981). The stress process. Journal of Health and Social Behavior, 22(4). 10.2307/2136676 [DOI] [PubMed] [Google Scholar]
  29. Portman ME. (2009). Conceptual Models. In Generalized anxiety disorder across the lifespan (pp. 31–39). 10.1007/978-0-387-89243-6_3 [DOI] [Google Scholar]
  30. Qian Y, & Fan W. (2023). Student loans, mental health, and substance use: A gender comparison among US young adults. Journal of American College Health, 71(3), 930–941. 10.1080/07448481.2021.1909046 [DOI] [PubMed] [Google Scholar]
  31. Quon EC, & McGrath JJ. (2014). Subjective socioeconomic status and adolescent health: a meta-analysis. Health Psychology, 33(5), 433–447. 10.1037/a0033716 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Ryu S, & Fan L. (2023). The relationship between financial worries and psychological distress among U.S. adults. Journal of Family and Economic Issues, 44(1), 16–33. 10.1007/s10834-022-09820-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Salignac F, Hamilton M, Noone J, Marjolin A, & Muir K. (2019). Conceptualizing financial wellbeing: An ecological life-course approach. Journal of Happiness Studies, 21(5), 1581–1602. 10.1007/s10902-019-00145-3 [DOI] [Google Scholar]
  34. SAS Institute Inc. (2023). SAS/STAT® 15.3 User’s Guide. In SAS Institute Inc. [Google Scholar]
  35. Sinha G, Tan K, & Zhan M. (2018). Patterns of financial attributes and behaviors of emerging adults in the United States. Children and Youth Services Review, 93, 178–185. 10.1016/j.childyouth.2018.07.023 [DOI] [Google Scholar]
  36. Sorgente A, & Lanz M. (2017). Emerging adults’ financial well-being: A scoping review. Adolescent Research Review, 2(4), 255–292. 10.1007/s40894-016-0052-x [DOI] [Google Scholar]
  37. Spitzer RL, Kroenke K, Williams JB, & Lowe B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. 10.1001/archinte.166.10.1092 [DOI] [PubMed] [Google Scholar]
  38. StataCorp. (2025). Stata Statistical Software: Release 19.5. In StataCorp LP. [Google Scholar]
  39. Substance Abuse and Mental Health Services Administration. (2023). Key substance use and mental health indicators in the United States: Results from the 2022 National Survey on Drug Use and Health (PEP23-07-01-006). https://www.samhsa.gov/data/report/2022-nsduh-annual-national-report
  40. Sweet E, Nandi A, Adam EK, & McDade TW. (2013). The high price of debt: Household financial debt and its impact on mental and physical health. Social Science and Medicine, 91, 94–100. 10.1016/j.socscimed.2013.05.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Terlizzi EP, & Zablotsky B. (2024). Symptoms of anxiety and depression among adults: United States, 2019 and 2022 (National Health Statistics Reports, Issue. https://www.cdc.gov/nchs/data/nhsr/nhsr213.pdf [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Walsemann KM, Gee GC, & Gentile D. (2015). Sick of our loans: Student borrowing and the mental health of young adults in the United States. Social Science and Medicine, 124, 85–93. 10.1016/j.socscimed.2014.11.027 [DOI] [PubMed] [Google Scholar]
  43. Winter N, & Nichols A. (2012). vioplot. In http://fmwww.bc.edu/RePEc/bocode/v
  44. Winzer R, Lindblad F, Sorjonen K, & Lindberg L. (2014). Positive versus negative mental health in emerging adulthood: A national cross-sectional survey. BMC Public Health, 14, 1238. 10.1186/1471-2458-14-1238 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Witters D. (2023). Loneliness in U.S. Subsides From Pandemic High. https://news.gallup.com/poll/473057/loneliness-subsides-pandemic-high.aspx
  46. Wood D, Crapnell T, Lau L, Bennett A, Lotstein D, Ferris M, & Kuo A. (2018). Emerging adulthood as a critical stage in the life course. In Halfon N, Forrest CB, Lerner RM, & Faustman EM. (Eds.), Handbook of Life Course Health Development (pp. 123–143). Springer. 10.1007/978-3-319-47143-3_7 [DOI] [PubMed] [Google Scholar]
  47. Wood S. (2023). How much student loan debt does the average college graduate have? https://www.usnews.com/education/best-colleges/paying-for-college/articles/see-how-student-loan-borrowing-has-changed
  48. Zhang Q, & Kim H. (2018). American young adults’ debt and psychological distress. Journal of Family and Economic Issues, 40(1), 22–35. 10.1007/s10834-018-9605-4 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS2200441-supplement-1.pdf (170.5KB, pdf)

RESOURCES