Access to Employer Benefits and Financial Insecurity Among Frontline Healthcare Workers

Abstract

Concern is growing about financial stress among U.S. workers, many of whom experience financial insecurity (FIS) as they struggle to make ends meet, manage debt, and save. Benefits comprise almost a third of total compensation and affects hiring and retention, which is important with respect to the shortage of frontline healthcare workers (FHWs). We present results from a survey of 2321 FHWs, finding that FHWs without college degrees and working in home health and private duty settings have lower access to benefits and greater FIS compared to those with college degrees and who work in facility-based settings. Among all FHWs, access to benefits has a strong association with FIS, even while controlling for income. Our findings suggest that employers consider improving benefits to help address FIS and within healthcare, address issues of compensation equity based on educational attainment. Still, addressing worker FIS may take strengthening the public social safety net.

Keywords

benefits occupational status healthcare financial difficulties frontline workers essential workers COVID-19 financial insecurity savings emergency savings

Introduction

The U.S. is facing a crisis of financially stressed-out workers. PricewaterhouseCoopers (PwC) has been tracking this phenomenon since 2013. In its most recent survey, PwC found that at 57% of employees, finances were the top source of stress while 59% say pay is not keeping pace with the rising costs of basic needs such as food and housing. Among employees with financial stress, 44% say their financial worries are a distraction at work and report lower levels of work engagement compared to non-financially stressed employees (PwC, 2023). A similar study of employees of mid-sized and large U.S. companies found that financial concerns were employees’ top source of stress affecting 58% of workers while among those with financial stress, 78% say it distracts them at work (Financial Health Network, 2019).

U.S. workers have good reasons to experience financial stress. Based on our calculations of data from the 2021 National Financial Capability Study survey, 41% of those who are working full-time say it is difficult to cover their usual expenses in 2021 while 38% had not set aside at least 3 months’ worth of usual expenses in emergency savings. Over half (51%) of full-time workers were spending more than their incomes or just breaking even while only 58% said they regularly paid their credit card balances in full (FINRA Investor Education Foundation, 2022). In a different study of U.S. workers, 44% and 41% said it is difficult to pay for housing and food, respectively (Orbe et al., 2022). Workers also struggle with debt, as 47% and 42% said they have trouble paying down debt and making credit card payments, respectively (Orbe et al., 2022). Many workers are also ill-prepared for emergencies, as 44% did not have enough in emergency savings to cover at least 3 months’ worth of expenses and only 35% could cover an emergency expense of $1500 using cash or money in bank accounts (Orbe et al., 2022).

For the reasons outlined above, employers are increasingly concerned about employees’ financial stress and insecurity and how it may affect productivity and retention (Despard et al., 2020, 2021; Frank-Miller et al., 2019; Kim & Garman, 2004; Verne, 2014). The healthcare sector is an especially important case as the U.S. is facing a crisis among its frontline healthcare workforce, a fifth of which left their jobs during the COVID-19 pandemic (Galvin, 2021) amidst illness, concerns about getting COVID-19, family obligations, and financial challenges (McCall, 2021). Entering a post-pandemic era, the healthcare industry is struggling to fill positions, which jeopardizes the quality of care for patients. For example, in November 2022, job exits in healthcare were 33% higher than prior to the pandemic, while healthcare job openings increased by 70% since February 2020 (Telesford et al., 2023). In September 2022, the job openings rate in healthcare was 9.2%, representing over two million jobs, compared to an overall openings rate of 6.5% (Bureau of Labor Statistics, 2023). As the elderly population rises and the non-elderly working age population faces declines, shortages among frontline healthcare workers (FHWs)—nursing assistants, nurses, home health aides, and other staff providing direct care to patients will worsen (Cardoza, 2021).

Given that compensation is related to the hiring and retention of FHWs (e.g., Charlie, 2017; Nei et al., 2015) and that benefits comprise 31% of total employee compensation (Bureau of Labor Statistics, 2021), healthcare employers should be concerned about the benefits they offer and how these benefits may affect employee financial stress and insecurity. The healthcare industry also faces challenges of internal equity. FHWs without college degrees working in positions like home health aide have the lowest pay and the worst job quality of FHWs (McCall & Scales, 2022) and may be especially prone to experiencing financial insecurity and stress. The median wage among FHWs like home health aides was $28,955 in 2021 compared to $77,600 for Registered Nurses, and RNs are twice as likely to have retirement benefits and almost twice as likely to have employer-based health insurance compared to home health aides and other FHWs in positions that do not require a college degree (Bureau of Labor Statistics, 2022).

Improving access to and the quality of benefits like health insurance and paid time off (PTO) may lessen the financial stress and insecurity employees experience which may improve their work engagement. Yet the link between benefits access and financial insecurity among U.S. workers has not been well studied. Employers and benefit providers have an incomplete picture of the financial insecurities facing employees and what might be done, including the types of benefits that may help alleviate these insecurities.

Concerning healthcare, this is an important knowledge gap to fill for two key reasons. First, understanding how employers might improve benefits may help with retention and mitigate FHW shortages. Second, understanding differences between FHWs in positions that do and do not require college degrees may help promote greater equity with respect to pay and benefits. This is particularly important given that women of color disproportionately occupy FHW positions that do not require college degrees (McColl & Scales, 2022) and in general are at greater risk for financial insecurity (Watson & Biu, 2022).

The purpose of this study is to understand access to benefits among FHWs and how benefits access is related to employees’ financial insecurity, job satisfaction, and intent-to-leave. We define financial insecurity (FIS) as difficulties households experience in (1) consistently covering expenses for basic needs; (2) managing debt; and (3) saving money. To explore these topics, we use results from a survey of 2321 FHWs, devoting attention to differences between FHWs with and without college degrees and FHWs in large facility-based settings compared to those in home health agencies and in private duty. Findings from this study can help inform the efforts of executives and human resource (HR) managers in the healthcare industry and benefits providers to mitigate the financial stress FHWs may be experiencing, which may improve worker engagement and help address the FHW shortage.

Access to and Use of Employer Benefits among FHWs

Findings from the 2007 National Home Health Aide Survey (NHHAS) indicated that 73% of home health aides had access to health insurance, 59% PTO, 51% paid sick leave, 49% retirement benefits, and 56% dental, vision, and/or prescription drug benefits. In a different study of Certified Nursing Assistants (CNAs), 90% had access to health insurance, and 71% to paid leave (Squillace et al., 2009). Benefits access and use is related to employment setting as access was higher among public health nurses (i.e., employed by local or state government) compared to school and home health nurses. Access was also higher among FHWs in hospice care compared to home health agencies (Charlie, 2017), while access was higher in large versus small and medium sized healthcare organizations (Franzosa, 2016; Temple et al., 2011; National Center for Health Statistics, 2011). Also, union membership is associated with greater access to benefits among FHWs (Kim et al., 2020). Concerning FHW characteristics, benefits access was lower among Black and other race/ethnicity workers compared to White workers (National Center for Health Statistics, 2011; Price-Glynn & Rakovski, 2012; Sullivan et al., 2019).

In the NHHAS study, almost half of home health aides did not enroll in their employer’s health insurance plan and 19% were uninsured (Squillace et al., 2009). Enrollment in employer-sponsored health insurance was much lower among workers making under $20,000, who are more likely to enroll in public health insurance compared to higher paid workers (National Center for Health Statistics, 2011). Among direct care workers (DCWs) like home health aides, 43% have Medicaid, Medicare, or other public coverage—more than coverage through their employer or union (37%) (PHI, 2021). Enrollment in employer-sponsored retirement plans among FHWs is half that of all workers, and especially low among FHWs in private duty settings (Fremstad, 2011). Among nurses in community-based settings, 42% and 51% were dissatisfied with their health insurance and retirement benefits, respectively (Charlie, 2017). Squillace et al. (2009) found that 42% of CNAs who were uninsured said they turned down their employers’ health insurance plan because it was too expensive.

Benefits and Turnover

Turnover among the frontline healthcare workforce is high. Gandhi et al. (2021) found a median turnover rate of 94% among nursing staff from a sample of 15,645 long-term care facilities. Among CNAs in long-term care facilities, the turnover rate was 55% (Kennedy et al., 2020), while Luo et al. (2013) found 3-month turnover rates ranging from 10% to 13% among different types of FHWs.

Numerous studies have found that a lack of benefits is a predictor of job satisfaction and turnover among FHWs, with most studies examining this association among CNAs working in long-term care facilities (Charlie, 2017; Ejaz et al., 2008; Rosen et al., 2011; Stone et al., 2017; Temple et al., 2011; Wiener et al., 2009; Yoon et al., 2016). Nonetheless, access to benefits is only one factor predicting job satisfaction and turnover among FHWs. Numerous studies link pay with job satisfaction and turnover intent, yet other factors include staff empowerment (Berridge et al., 2018), insufficient staffing levels (Mittal et al., 2009), workload (Dill et al., 2013), lack of leadership support (McGilton et al., 2014), difficult work conditions (Delp et al., 2010), and procedural justice (Gillet et al., 2013).

Negative Effects of Financial Insecurity on Workers

Various aspects of financial insecurity negatively affect workers and their families in important ways that may affect their overall wellbeing and productivity. Difficulty paying for basic needs is linked to mental health (Anvari-Clark & Frey, 2019; Heflin & Iceland, 2009) including among workers in frontline service occupations (McCarthy et al., 2018), and health (Huang et al., 2021; Neckerman et al., 2016). A lack of emergency savings leaves workers and their families vulnerable to financial shocks such as a hospitalization or major car repair and increases the chances people cannot meet their basic needs (Despard et al., 2018; Gjertson, 2016; Rodems & Pfeffer, 2021). Problems managing debt are linked to poor health and mental health (Bialowolski et al., 2019; Richardson et al., 2013). Using our own analysis of data from the 2021 National Financial Capability Study survey, difficulties paying for basic needs was greater among households with medical and student debt.

Financial insecurity may negatively affect workers’ productivity because of diminished mental and physical health. Workers whose debt problems are linked to depression may have trouble focusing and may struggle with motivation to perform tasks. Physical health problems linked to financial insecurity may make it difficult to perform physical tasks and result in work absences. Financial insecurity also is also very destabilizing for workers and their families. Problems covering expenses may lead to eviction and utility cutoffs, while a lack of emergency savings to pay for a car repair may result in work absences or tardiness due to a lack of reliable transportation.

Financial Insecurity Among FHWs

While much research has been conducted concerning the FIS of U.S. households and to a lesser degree, workers in the U.S., little research has focused on the frontline healthcare workforce. Almost half (44%) of FHWs, such as home health aides who provide care in the home themselves, are members of a low-income household and 45% receive some form of public assistance (PHI, 2021). Similarly, nearly half of home health aides had household incomes under $30,000 and 52% were receiving public benefits (National Center for Health Statistics, 2011). Many FHWs felt the need to continue to work during the COVID-19 pandemic despite the risk of coronavirus infection to avoid losing income (Sterling et al., 2020). Indeed, workers in general who lost jobs or income during the pandemic experienced greater rates of FIS than those who did not (Despard et al., 2020).

Among all healthcare workers, less than 10% experienced food insecurity within the past month. However, the odds of experiencing food insecurity were more than five times higher among FHWs such as home health aides and CNAs (Srinivasan et al., 2021). Among employees of a large health system, 11% experienced food insecurity, 12% financial strain, and 10% difficulty paying for housing or utilities. However, among clinical support staff such as medical assistants, these rates were two to three times greater (Seeholzer et al., 2022).

Study Purpose

Prior research has assessed FHWs’ access to and use of benefits, identifying some factors that explain variation in access, and how benefits access is related to turnover. The authors were able to find only two studies concerning FHWs. The purpose of this study is to examine benefits access among FHWs and how access is related to FIS, job satisfaction, and intent to leave one’s job. While wage levels affect FHWs’ ability to meet basic needs and save for emergencies, benefits may also play a role. For example, having paid leave means FHWs can avoid losing a day’s pay when they must stay home with a sick child, while health insurance can limit FHWs’ out-of-pocket healthcare expenses. Other types of benefits like tuition assistance and student loan repayment assistance can have a direct impact on FIS by reducing FHWs’ expenses. We also examine how FHWs’ educational attainment and employment setting relate to FIS and benefits access and whether FIS and benefits access relate to job satisfaction and intent to leave. Our research questions are:

1. To what degree does access vary across types of benefits? By educational attainment? By employment setting?

2. Is benefits access related to financial insecurity (FIS) among frontline healthcare workers (FHWs)?

3. How interested are FHWs in an emergency savings benefit in the workplace? Does interest vary based on program characteristics?

4. Is benefits access related to job satisfaction and intent to leave among FHWs?

Amidst a growing concern among companies and organizations about financial challenges affecting employees, our findings shed light on the importance of benefits, including traditional benefits like health insurance and newer benefits marketed as mitigating FIS like pay advances and loans. Our findings can also describe benefits access as an equity issue in the healthcare industry with respect to educational attainment. FHWs without college degrees—who are disproportionately women of color—may face the “double jeopardy” of lower wages and lower benefits access compared to FHWs with degrees.

Methods

Sample

We used a convenience sample of FHWs who completed an online survey over a 3-week period in September and October of 2021. FHWs were recruited through (blinded organization), a national advocacy organization for direct care workers, which shared the online survey opportunity among a group of affiliate organizations representing FHWs. The online survey was hosted on Qualtrics and study participants received a $25 Amazon gift card. After using a review process to exclude invalid survey responses (e.g., foreign Internet Protocol (IP) address, repeat IP addresses from locations different than the residence), we arrived at a final sample of 2321 FHWs. The study received Institutional Review Board approval from a university in the Midwest.

Measures

All measures used for this study came from the online survey which was developed based on extensive feedback from several content experts. An advisory committee of FHWs also reviewed and provided feedback about the survey. The final version included 100 questions and took about 15 minutes to complete. Major categories of survey items included employment arrangements and decisions, access to, use of, and perception of benefits, work experiences and job satisfaction, FIS, and demographic and household characteristics.

Educational attainment was measured as a dichotomous variable—with a value of 1 assigned for holding a 4-year college degree or higher and a value of 0 assigned for having less than a 4-year college degree, including having an associate degree, some college, a high school diploma, and less than high school. We dichotomized educational attainment as having a 4-year college degree or not based on prior research that shows that wages and access to and enrollment in benefits are lower among FHWs in positions that do not require a college degree (e.g., home health aide) (Bureau of Labor Statistics, 2022; McCall & Scales, 2022) while food insecurity is higher (Srinivasan et al., 2021) than for other types of FHWs. Employment setting was measured by asking FHWs about the setting for their primary job, with a value of 1 assigned to indicate working in a facility-based setting (hospital or long-term care facility) and a value of 0 to indicate working in a community-based (home health agency or private duty) setting.

To measure access to benefits, we asked FHWs whether their employer offered certain benefits and if so, whether they were eligible to receive the benefit and if they used the benefit. The list of benefits included health insurance, retirement benefits, PTO, dental benefits, expense reimbursement, tuition assistance, financial counseling, pay advances or loans, student loan repayment assistance, and child care assistance. FHWs were also asked how important it was to have access to each benefit, irrespective of access. Response options were “very,” “somewhat,” and “not at all” important. Counts of all benefits, including four major and common benefits (health insurance, retirement benefits, PTO, and dental benefits)¹ and excluding child care assistance and were used in models where benefits access was used as independent or dependent variable. Child care assistance was examined separately because it is the only benefit that is contingent on family structure whereas all other benefits are not and could potentially be used by all FHWs.

To measure FIS, we used nine measures to indicate the presence of distinct types of financial insecurity experienced by workers with respect to covering expenses for basic needs, managing debt, and saving. Concerning problems covering expenses (five measures), we measured food insufficiency by asking workers whether in the prior 6 months: “We worried whether our food would run out before we got money to buy more” and “The food that we bought just didn’t last, and we didn’t have money to get more.” Responses of “sometimes” or “often” to both questions were assigned a value of 1 to indicate food insufficiency while all other responses to the two questions were assigned a value of 0. These two questions were taken from the USDA household food insecurity survey module (U.S. Department of Agriculture, 2012). Also, we asked four questions concerning distinct types of material hardship; workers were asked whether in the prior 6 months they had difficulty paying for rent or mortgage, household bills, medical care, and prescription medications.

We included two measures concerning saving, including whether workers had any money in emergency savings and if so, for how long this savings would last. Responses of having less than 1 month of emergency savings were assigned a value of 1 to indicate a low level of emergency savings and a value of 0 for having savings of 1 month or more. Workers were also asked whether they had any retirement savings, with responses of “no” coded as 1 to indicate a lack of retirement savings and responses of “yes” coded as 0. To measure managing debt, workers were asked “Thinking about any credit cards and loans you have, which of the following best describes your ability to make monthly payments?” Responses of “We are behind on our payments,” “We have stopped making some payments,” or “We have stopped making all payments” were coded as 1 to indicate having credit card problems and 0 if the response was “We are usually able to pay on time.”

Lastly, we included a single measure of subjective financial security to assess FHWs’ general sense of how they are doing financially by asking “Overall, which one of the following best describes how well you are managing financially these days.” Responses of “Just getting by” and “Finding it difficult to get by” were coded as 1 indicating problems getting by and 0 for responses of “Living comfortably” and “Doing okay.” This measure reflects an aspect of subjective financial well-being defined by Brüggen et al. (2017) as “the perception of being able to sustain current and anticipated desired living standards” (p. 229).

The nine measures of financial insecurity were measured separately as dependent variables and a FIS scale was created by creating a count of the nine types of financial insecurity experienced. The FIS scale was additive; scores ranged from zero to nine. Concerning child care, workers were asked, “In a typical month, how difficult is it for you to pay for child care?” with response choices of very, somewhat, not at all or not applicable. Responses were coded as 1 for very difficult and 0 for somewhat or not at all difficult and analyzed separately and not included in the FIS scale.²

Job satisfaction was measured by using select items from the Job Satisfaction Survey (JSS), which was originally designed for use in human services work settings (Spector, 1985). A lack of survey space precluded including the entire 36-item JSS, thus items were selected for relevance to the work conditions of FHWs. FHWs read eight statements concerning work conditions including “When I do a good job, I get the recognition I deserve,” “Communication seems good at my job,” “Most of our rules and procedures make it easy to do a good job,” “I usually feel like my job is meaningful,” “I like doing the things I do at work,” “People who do well on the job here have a good chance of being promoted,” “I feel I’m being paid a fair amount for the work I do,” and “The benefits I get are as good as what most other places offer.” Two of these items were slightly re-worded so all eight items were phrased in positive terms. Response options for each of these statements were Disagree very much = 1, Disagree moderately = 2, Disagree slightly = 3, Agree slightly = 4, Agree moderately = 5, and Agree very much = 6. For ease of interpretation, composite scores were calculated by summing all non-missing responses and dividing this number by the eight (the number of items).

Analysis

Benefits access was used as a dependent variable to answer Research Question 1 and as an independent variable predicting financial challenges to answer Research Question 2 and predicting job satisfaction and intent to leave to answer Research Question 4. Each financial challenge and the FIS scale were used as dependent variables to answer Research Question 2. Lacking at least 1 month of emergency savings was used as an independent variable for Research Question 3 to help explain variation in interest in a workplace savings benefit.

In addition to univariate descriptive statistics such as means, medians, and frequencies, bi- and multi-variate statistical analyses were used to answer research questions. Analysis of Variance (ANOVA) and Poisson and negative binomial regression (in instances of overdispersion) models were used to assess the number of benefits to which FHWs had access and the number of financial challenges they experienced as measured by the FIS scale³. Probit regression with the margins commands were used to estimate predicated probabilities of each of the financial insecurities. All regression models used covariance control and robust standard errors. Model covariates included age, income, gender identity, race/ethnicity, marital status, number of adults in the households, number of children under age 18 in the household, region, educational attainment, employment setting, and union membership. Income was a particularly important covariate in models where benefits access predicted financial insecurities (Research Question 2).

Results

Sample Description

Table 1 displays the characteristics of the frontline healthcare workers who completed the survey. Most survey respondents were women, white, married, had one or more children, did not have a college degree, and had household income of $50,000 and above. The average and median age of respondents was 35 years old with a range of 20–69 years old. Some demographic characteristics differed based on employment setting. Workers in facilities such as hospitals were more likely than workers in home health or private duty settings to have a college degree and household income of $50,000 or more. Concerning differences by race and ethnicity, White workers were more likely to have a college degree and to have higher incomes compared to Black and Hispanic—differences that were statistically significant (p < .001).

Table 1.

Sample Description (N = 2321).

	All	Facility	Home Health or Private Duty
Age	35.07 (5.53)	35.09 (5.05)	34.99 (7.05)
Gender identity
Female	57	58	53
Male	42	42	46
Other/non-binary	<1	<1	1
Race/Ethnicity
Non-Hispanic white	74	75	72
Non-Hispanic black	15	15	16
Hispanic	8	8	5
Other	3	2	6
Educational attainment
Less than a college degree	53	49	68
College degree or above	47	51	32
Income
Under $25,000	12	9	21
$25,001–$35,000	9	8	15
$35,001–$50,000	17	17	19
$50,001–$75,000	40	44	26
$75,001 or higher	21	22	19
Geographic area of residence
Northeast	10	10	10
Midwest	29	29	30
West	26	25	30
South	35	36	30

Note. Figures are frequency percentages or mean values with standard deviations in parentheses.

Employment Characteristics

Most study participants worked in a facility-based setting (79%) such as a hospital, followed by 12% in home health and 9% in private duty. Most (72%) worked 31–40 hours per week; 17% worked more than 40 hours and 10% worked 30 hours or less per week. Nearly all workers (97%) said they received bonuses, extra pay for being on call and/or for working in the evening or on weekends, and hazard pay related to COVID-19. Concerning monthly pay, 24% made less than $3,000, 50% made between $3000 and $4,999, and 27% make $5000 or more. FHWs in home health and private duty settings were more likely to earn less than $3000 a month compared workers in facility-based settings (p < .001).

Job changes were common as 59% of FHWs said they changed jobs at least once in the past year. Among those who changed jobs, 56% left their jobs due to concerns about COVID-19, while 34% of FHWs said they are somewhat or very likely to leave their current job in the next year. Nearly two-thirds came to work sick at least once in the past year and 40% said they did side or “gig” work in the past 6 months (e.g., pet sitting, Uber).

Access to and Use and Importance of Benefits

Access to the nine benefits which we asked about ranged from 13% (student loan repayment assistance) to 71% (health insurance). The take-up rate for benefits was uniformly high, ranging from 77% (tuition assistance) to 95% (PTO). FHWs ranked various benefits as very important in a similar order as access. For example, health insurance and student loan repayment assistance were the top and bottom benefit for access and importance, respectively. For dental benefits, expenses reimbursement, tuition assistance, financial counseling, pay advances or loans, and student loan repayment assistance, the proportion of FHWs who said this benefit was “very important” exceeded the proportion who had access to each of these benefits (Table 2).

Table 2.

Employer Benefits: Access, Use, and Importance.

Benefit	Access	Use	Unsure	Importance of Benefits
Benefit	%	%	%	Very %	Somewhat %	Not at all %
Health insurance	71	94	8	54	35	11
Paid time off	61	95	17	44	41	15
Retirement benefits	54	84	13	49	38	13
Dental benefits	30	87	27	40	43	17
Expenses reimbursement	29	90	25	37	37	26
Tuition assistance	21	77	26	30	39	31
Financial counseling	21	82	27	29	40	31
Pay advances or loans	17	80	28	31	39	30
Student loan assistance	13	77	31	29	37	35

Note. All figures in the table represent response frequencies. Row totals may exceed 100 due to rounding. “Access”: the percentage of respondents who said they had access to the benefit. “Use”: the percentage of respondents who had access to the benefit and used or enrolled in the benefit. “Unsure”: the percentage of respondents who were uncertain about whether their employer offered the benefit or whether they were eligible. “Importance of benefits” reflects how important each benefit is to respondents, regardless of access.

Overall, FHWs had access to an average of 3.52 out of 9 possible benefits⁴ and 2.26 out of 4 major benefits (health insurance, retirement, PTO, and dental). Benefits access varied among FHWs by their educational attainment and work settings. Out of all 9 benefits, FHWs with college degrees had an average of 3.95 benefits compared to 3.08 benefits among FHWs without degrees, χ² (9, N = 1770) = 238.16, p < .001. FHWs in facilities had an average of 3.77 benefits compared to 2.63 benefits among FHWs in home health or private duty settings, χ² (9, N = 1771) = 262.89, p < .001. Results from Poisson regression controlling for factors such as age and income indicated an incidence rate ratio (IRR)⁵ of 1.14, z = 5.09, p < .001 among FHWs with a degree and an IRR of 1.39, z = 8.56, p < .001 among those working in facility-based settings, indicating greater access to benefits compared to FHWs without degrees and working in home health or private duty settings, respectively.

Health Insurance Use

Among FHWs using health insurance, those without a college degree were more likely to be enrolled in a high deductible health plan (HDHP⁶) (43%) and to pay $400 or more per month on health insurance (33%) than those with a college degree or higher (25% and 20%, respectively) (p < .001). Similarly, FHWs in home health (38%) and private duty (51%) settings were more likely to have HDHPs than FHWs in facilities (30%) (p < .001).

Financial Insecurity

FIS scale scores ranged from 0 to 9, with a mean of 2.70 (SD = 2.55) and a median of 2 types of financial insecurities.⁷ The nine challenges comprising the FIS scale had an internal consistency of α = .80. Financial insecurities were common as 45% of FHWs reported experiencing three or more of the types of insecurity while only 28% reported no insecurities. Examining specific insecurities, over a third of FHWs said they had experienced food insufficiency in the prior 6 months, had problems paying back credit cards or loans, and had emergency savings that would cover less than 1 month of usual household expenses.⁸

FHWs with and without college degrees had FIS scores of 1.54 and 3.67, respectively, χ² (9,2055) = 414.21, p < .001 while FHWs in facility-based and home health or private duty settings had FIS scores of 2.38 and 4.00, respectively, χ² (9,2056) = 169.08, p < .001. These differences remained true after controlling for factors like age and income. Results from negative binomial regression indicated an IRR of 0.52, z = 13.41, p < .001 among FHWs with a degree and an IRR of 0.72, z = 7.06, p < .001 and among those working in facility-based settings, indicating lessened risks of experiencing FIS.

Examining specific types of financial insecurity while controlling for age, income, and other factors, FHWs without degrees had statistically significant higher predicted probabilities than FHWs with degrees for 8 out of 9 insecurities, with a mean difference of 15 percentage points. A similar pattern held for work setting, with FHWs in home health or private duty settings having statistically significant higher predicted probabilities than FHWs in facility-based settings for 8 out of 9 financial insecurities, with a mean difference of 8 percentage points (Table 3)

Table 3.

Factors Predicting Financial Insecurities.

	Work Setting				Education Level
Financial Insecurity	All %	Facility %	HH/PD %	p	Degree %	No Degree %	p
Food insufficiency	34	32	41	***	25	42	***
Housing hardship	25	24	29	*	16	35	***
Problems paying bills	22	21	25	*	15	29	***
Medical care hardship	20	18	28	***	14	27	***
Prescription drug hardship	20	18	27	***	12	28	***
Credit card/loan problems	34	32	41	**	23	45	***
<1 month in emer. savings	34	31	45	***	25	43	***
No retirement savings	22	21	30	***	13	34	***
Problems getting by financially	26	25	27	--	26	25	--

Note. Figures represent the model-predicted probabilities (in percentages) of workers who experienced each financial insecurity using the margins command in Stata following probit regression models using covariance control. HH/PD = home health or private duty. *p < .05, **p < .01, ***p < .001.

Benefits Access and Financial Insecurity

Examining all nine benefits, benefits access was negatively correlated with the nine financial insecurities r (1595) = −.37, p < .001. Controlling for income, age, and other factors, benefits access was associated with a reduced likelihood of experiencing financial insecurity IRR = 0.85, z (1567) = 8.32, p < .001. That is, each additional workplace benefit was associated with a decreased risk of experiencing financial insecurity.

Concerning the four major benefits—health insurance, retirement, dental, and PTO, an increase in having access to an additional benefit predicted a statistically significant lower probability of experiencing all nine financial insecurities. For example, the probability of experiencing housing hardship (e.g., problems paying rent) dropped from 47% to 29% when having two major benefits rather than one. Declines in risk for financial insecurities were steepest going from two to three benefits, with an average percentage point decline of 18 percentage points. Certain benefits were particularly important. On average, having access to health insurance, a retirement plan, and PTO reduced the chances of having a financial insecurity by 24, 29, and 26 percentage points, respectively, (all differences p < .001). However, access to dental benefits was not a significant predictor of financial insecurity (Table 4)

Table 4.

Access to Major Benefits and Predicted Probabilities of Financial Insecurities.

	Number of Benefits
Financial Insecurity	One %	Two %	Three %	Four %	p
Food insufficiency	45	44	24	23	***
Housing hardship	47	29	12	9	***
Problems paying bills	36	32	14	13	***
Medical care hardship	36	28	10	8	***
Prescription drug hardship	33	26	13	6	***
Credit card/loan problems	58	55	15	9	***
<1 month in emer. savings	43	43	23	22	***
No retirement savings	41	34	16	22	***
Problems getting by financially	39	25	27	12	***

Note. Figures represent the model-predicted probabilities (in percentages) of workers who experienced each financial insecurity using the margins command in Stata following probit regression models using covariance control. Benefits counted included health insurance, retirement, dental, and paid time off. *p < .05, **p < .01, ***p < .001.

Child Care Assistance and Difficulty

Concerning child care, 41% of FHWs had access to assistance and of those with access, 86% used this benefit while 19% were unsure whether their employer offered assistance or whether they were eligible to receive it. Concerning child care costs, 11% said it was very difficult and an additional 51% said it was somewhat difficult to cover these expenses. Among FHWs who had access to and used child care assistance, 53% reported any difficulty covering child care costs compared to 64% who lacked access to this benefit χ² (1, N = 1427) = 12.27, p < .001.

Emergency Savings Benefit Experiment

In the survey, we randomly assigned FHWs to one of four questions concerning a hypothetical workplace emergency savings program. Workers were told “Imagine if your employer offered a benefit where a certain portion of your paycheck went into a savings account so you can have money for emergencies. Under this program, (1) 3% of your paycheck would automatically go into a savings account; (2) $75 from your monthly pay would automatically go into a savings account; (3) 3% of your paycheck would automatically go into a savings account. Also, your employer would contribute an extra $500 if you completed a financial education program; and (4) 3% of your paycheck would automatically go into a savings account. Also, your employer would contribute an extra $500 after your account reached $500.” Participants saw one of these four statements and were asked to indicate on a scale of 0–10 how likely they would participate in the described savings program. These program scenarios were meant to test whether certain types of anchors (a percentage of one’s paycheck or a fixed amount) and/or incentives (employer matches under two scenarios) might make workers more or less likely to participate. Workers gave an average score of 6.87 (SD = 2.14) suggesting moderate interest in participating, yet there were no statistically significant differences among the four groups. That is, no hypothetical program structure garnered higher interest among FHWs than the others. However, FHWs who already had emergency savings stated a higher likelihood of participation than FHWs with no emergency savings, p < .001.

Access to Benefits, Job Satisfaction, and Intent to Leave

The eight-item abbreviated version of the JSS had good internal consistency, α = .77. Composite JSS scores ranged from 1.38 to 6.00 (scale of 1–6 from disagree very much to agree very much), with a composite mean score of 4.05 (SD = 0.83) and a composite median of 4, which reflect a response choice of “agree moderately” on the scale. Overall, 34% of workers said they were somewhat or very likely to leave their jobs within the next year, with job satisfaction associated with intention to leave one’s job F (1,2294) = 160.37, p < .001. Likely leavers had job satisfaction scores of 30 compared to 34 among those unlikely to leave. Job satisfaction was correlated with benefits access r = .25, p < .001 and benefits access was associated with intention to leave one’s job F (1,1765) = 5.70, p < .05 as workers likely to leave their jobs had access to an average of 3.37 benefits (out of 9) compared to 3.59 among those unlikely to leave. Controlling for factors like income and age, benefits access was not a significant predictor of intention to leave β = −.007, z (1723) = 0.29, p = .77. However, having access to four major benefits—health insurance, retirement, dental, and PTO—was a significant predictor of intention to leave β = −.28, z (1989) = 10.49, p < .001, a finding that remains true after including job satisfaction in the regression model β = −.22, z (1975) = 7.31, p < .001.

Discussion

In this study, we conducted a survey of 2321 FHWs concerning their access to and use of employer benefits and their financial insecurity (FIS). Concerning Research Question 1, we found that access to health insurance, PTO, and retirement benefits was higher than benefits specifically focused on mitigating FIS, such as financial counseling and pay advances or loans. This finding aligns with prior research that shows interest among employees in benefits like loans and financial counseling that surpasses availability (Financial Health Network, 2019). We also found a large disparity in benefits access by educational attainment and work setting. FHWs with college degrees who work in facility-based settings like hospitals have far greater benefits access than FHWs without degrees and who work in home health and private duty settings.

Concerning Research Question 2, we find that financial insecurities are common among FHWs and are much greater among those without degrees and working in home health or private duty. Most importantly, we find that access to four major benefits (health insurance, retirement, PTO, and dental benefits) is clearly and strongly associated with FIS—even after controlling for income and other demographic and household characteristics. Benefits access was significantly and negatively related to all nine financial insecurities and was a strong predictor of FIS scores. Among the four benefits, health insurance, retirement, and PTO had equally strong associations with the likelihood of experiencing FIS while dental benefits did not predict FIS. In addition, access to child care assistance was associated with less difficulty covering child care costs.

In answering Research Question 3, we find that FHWs had a moderate interest in using an emergency savings benefit in the workplace, with interest higher among FHWs who already have emergency savings. However, design features such as having a fixed amount or percentage of pay automatically deducted from one’s paycheck or receiving a conditional or unconditional employer contribution did not influence interest. Concerning Research Question 4, we find that benefits access was associated with job satisfaction and that access to the four major benefits was a significant predictor of intent to leave one’s job, even after controlling for job satisfaction.

Our study is the first of which we are aware that draws a link between benefits access and FIS while controlling for age, income, and other factors. What is especially compelling about these results is that the link between benefits access and FIS held for all nine types of financial insecurity. This pattern cannot be explained by differences in wages as we controlled for income. As such, employers who are concerned about employees’ financial stress and how it might affect productivity ought to look at the benefits they offer—especially health insurance, retirement, and PTO.

Also, only two prior studies of which we are aware examined FIS among FHWs (Seeholzer et al., 2022; Srinivasan et al., 2021). We build on this research by examining a broader array of insecurities and illustrating large gaps in benefits access and FIS between FHWs with and without college degrees and those working in facility-based settings like hospitals versus home health and private duty settings. With wages among FHWs that are much higher in positions that require a college degree, FHWs without degrees face “triple jeopardy”—lower wages, fewer benefits, and greater FIS, especially when they work in home health or private duty settings.

Our findings concerning how common FIS is among FHWs support the need for benefit providers and healthcare employers to offer new types of financial wellness benefits such as financial counseling and loans (Despard et al., 2020, 2021; Financial Health Network, 2019; Orbe et al., 2022). For example, nonprofit organizations like Neighborhood Trust, GreenPath Financial Wellness, and Working Credit partner with employers to offer financial counseling and coaching services while SaverLife offers savings programs. Financial technology companies like Employee Loan Solutions, Salary Finance, Even, and HoneyBee partner with banks and credit unions to offer personal financial management applications, loans, and access to financial counseling. Also, major benefit providers such as Prudential and MetLife have begun to build new product lines around financial wellness. Yet less than a quarter of FHWs in our study said they have access to these benefits, a similar finding from other studies (e.g., Financial Health Network, 2019).

Workplace loans can help employees with low or no credit scores access affordable credit and avoid high-cost products like payday loans to help cope with a major unexpected expense or to make large purchases. Because loan payments are payroll deducted, defaults are low (FINRA Investor Education Foundation and Filene Research Institute, 2017). Financial counseling can help employees address a range of financial challenges and goals, including improving credit health and scores (Despard et al., 2021). Financial counseling can also help employees access wage supports like the Earned Income Tax Credit (EITC) (Despard & Levy, 2022) and anticipate and navigate “benefits cliffs”—the loss of access to public benefits as wages rise (Despard, 2022).

Helping employees save for emergencies is especially important. Emergency savings may help decrease defined contribution plan (DCP) hardship withdrawals and lessen the chance that employees will experience destabilizing events like evictions and utility cut-offs or losing a means of transportation (Despard et al., 2018). The Secure Act 2.0 signed into law in December 2022 allows employers to auto-enroll employees into emergency savings accounts for up to 3% of pay and linked to DCPs, and to make DCP matches in lieu of employees’ student loan payments.

While it is important to consider financial wellness benefits, we found an especially strong association between having access to health insurance, retirement, and PTO and FIS. While we cannot infer that access to these benefits resulted in lessened FIS, employers should consider providing or improving these benefits before they consider new financial wellness benefits. For example, offering PTO would have a stronger effect on FIS than offering pay advances, particularly among lower-wage workers (Davison & Blackburn, 2023). Not missing a day’s pay due to a child’s illness will make it easier to buy food than a pay advance. Offering paid leave also has important implications for controlling the spread of communicable diseases (Marty Martin et al., 2021). For the third of FHWs without college degrees and other lower-wage employees who pay $400 or more per month on health insurance, employers can use wage-tiered employee premiums to make insurance more affordable. Alternatively, reliance on employers to provide health insurance could lessen (Lester et al., 2021) in favor of public options, such as allowing workers to opt-in to Affordable Care Act (ACA) marketplace subsidies if this meant lower premiums for comparable employer-sponsored plans. These considerations are important given that a fifth of all FHWs said they had trouble paying for medical care and prescription medications. Also, while many factors affect turnover, our findings suggest that improving access to benefits could lessen FHWs’ job leaving intentions.

Our study highlights larger structural problems with the healthcare labor market. The occupational stratification by educational attainment that exists within healthcare concerning wages extends to benefits access and FIS. Healthcare employers should lessen pay gaps between employees in jobs that require and do not require college degrees to promote greater internal equity. Employers should also examine reasons why FHWs without degrees may have lower access to benefits, such as due to part-time status, and then in response lower the number of weekly hours for benefits eligibility and/or increase work hours for FHWs who want this. In addition, employers should examine the robustness of their career ladders, such as from Certified Nursing Assistant (CNA) to Licensed Practical Nurse (LPN) and consider offering benefits like tuition assistance and flexible scheduling to help FHWs develop their careers.

Yet part of the educational attainment disparity we found is related to a higher proportion of FHWs without college degrees working in home health and private duty settings. Increasing third party reimbursements for home health such as through the Medicaid Home and Community-Based Services (HCBS) program could enable home health employers to increase spending on benefits. Private duty FHWs are in a different situation as independent contractors who must secure their own benefits. Several states are taking steps to improve benefits access for self-employed workers, such as the Oregon Saves retirement savings program for workers who lack access to a defined benefit or contribution plan through the workplace. Yet other challenges remain among private duty FHWs who, like other self-employed workers, face greater economic insecurity compared to FHWs who work for an employer (Auguste et al., 2022)including responsibility for the employer share of Social Security and Medicare taxes (Veliotis & Steve, 2022).

Lastly, a broader question concerns what might be expected of employers in offering benefits with respect to the role of a public safety net. Undoubtedly, the FIS FHWs and other workers experience is due to broader challenges in society, such as food and transportation inflation, unaffordable housing, and child care. Given wide variation across industries and firm sizes in the cost of offering benefits as a proportion of revenue or expenses, it may be unrealistic to expect substantial changes in benefits spending sufficient to meaningfully impact workers’ FIS. As a result, workers in various parts of the labor market will regularly be at a disadvantage unless the public social safety net is strengthened. We find that difficulties paying for child care are lower when FHWs have access to child care assistance as a benefit. Yet most employers do not provide this benefit. A more efficient way to ensure workers can afford child care and experience fewer work disruptions would be to offer universal child care and pre-kindergarten through strategies such as converting the Child Care and Development Block Grant from a discretionary to entitlement program.

Study Limitations

A key limitation of our study is that our findings are not generalizable to the population of FHWs in the U.S. as the sample drawn was non-probabilistic. We did not ask FHWs to identify their job title and instead used educational attainment as a proxy for occupational status. Thus, we cannot say for certain that all FHWs without college degrees in our study are part of the direct care workforce comprised of home health aides, nursing assistants, and personal care aides. Still, our finding that FHWs without degrees had an average of 3.67 benefits (counting all 10 benefits) is similar to Yoon et al.’s (2016) finding of an average of 4.29 benefits among home health aides. While we found a strong association between access to benefits and FIS while controlling for income and other factors, the relationship is correlational, not causal. There are other unobserved factors that may help explain this relationship. Furthermore, we only measured whether workers said they had access to the benefit; we did not ask about any characteristics of the benefit such as financial value. Thus, we are unable to offer findings concerning the quality of benefits employers offer.

Lastly, it is important to note that we surveyed FHWs about a year and a half into the COVID-19 pandemic. FHWs and their families had access to direct financial supports including a third round of Economic Impact Payments in March 2021, additional unemployment insurance payments through early September 2021, and additional monthly Child Tax Credit payments from July 2021 through December 2021. FHWs might also have benefited from the suspension of federal student loan payments and eviction moratoriums. Thus, the FIS we observe may be greater as we enter a post-pandemic period absent these financial supports. In addition, FHWs were working in exceedingly difficult conditions during the pandemic. Thus, our findings concerning job satisfaction and intent to leave might have been different in a pre- or post-pandemic context.

Conclusion

Frontline healthcare workers (FHWs) play especially important roles in caring for sick and vulnerable individuals, the care of whom is in jeopardy due to current and projected labor shortages. One way to better support FHWs is to offer benefits that may mitigate FIS. Indeed, we draw a strong link between benefits access and FIS in many respects. Yet this access is unequal; FHWs without college degrees and working in home health and private duty settings have lower benefits access and higher FIS than FHWs with degrees working in facility-based settings like hospitals. Employers and the public sector both play a role in improving benefits access and lowering FIS among the frontline healthcare workforce.

Footnotes

Acknowledgments

We are grateful to the Prudential Foundation whose support made this research project possible and for the support and insights offered by Prudential’s Samuel Diaz, Manager, Inclusive Solutions and Paula D’Ambrosa, Director, Inclusive Solutions. We would also like to thank Kezia Scales and Stephen McCall with PHI for their feedback, guidance, and assistance with study recruitment and Najjuwah Walden of Washington University in St Louis for feedback concerning research design and the following graduate research assistants at the Social Policy Institute for their support Emma Nordmeyer, Shanice Fezeu Meyou, and Selina Miller. Lastly, we wish to thank the frontline healthcare workers themselves who participated in this study and the Building on Benefits Advisory Council for their thoughtful feedback and engagement in the project.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Prudential Foundation.

ORCID iD

Mathieu R. Despard

Notes

Author Biographies

Mathieu R. Despard is an Associate Professor in the Department of Social Work at UNC Greensboro, a Visiting Scholar with the Social Policy Institute at Washington University in St. Louis, and an Adjunct Assistant Professor with the Kenan-Flagler Business School at UNC Chapel Hill. He conducts research on financial health and economic mobility with a focus on low- and moderate-income households. Dr. Despard advises PhD students in a joint program with North Carolina A&T State University and teaches graduate courses in social work management, financial inclusion and social innovation, and intervention design.

Haotian Zheng is a Research Assistant with the Social Policy Institute and a PhD in Social Work student in the Brown School at Washington University in St. Louis.

Sophia Fox-Dichter is a Data Analyst II with the Social Policy Institute at Washington University in St. Louis and a PhD student at the Edward J. Bloustein School of Planning and Public Policy at Rutgers, State University of New Jersey focusing on rental household stability and policies that impact it.

References

Anvari-Clark

Frey

J. J.

(2019). Financial capability and behavioral health. The Routledge handbook on financial social work (pp. 61–72). Routledge.

Auguste

Roll

Despard

(2022). The precarity of self-employment and gig work among low- and moderate-income households. Social Forces, 101(3), 1081–1115. https://doi.org/10.1093/sf/soab171

Berridge

Tyler

D. A.

Miller

S. C.

(2018). Staff empowerment practices and CNA Retention: Findings from a nationally representative nursing home culture change survey. Journal of applied gerontology: the official journal of the Southern Gerontological Society, 37(4), 419–434. https://doi.org/10.1177/0733464816665204

Białowolski

Węziak-Białowolska

VanderWeele

T. J.

(2019). The impact of savings and credit on health and health behaviours: An outcome-wide longitudinal approach. International Journal of Public Health, 64(4), 573–584. https://doi.org/10.1007/s00038-019-01214-3

Brüggen

E. C.

Hogreve

Holmlund

Kabadayi

Löfgren

(2017). Financial well-being: A conceptualization and research agenda. Journal of Business Research, 79, 228–237. https://doi.org/10.1016/j.jbusres.2017.03.013

Bureau of Labor Statistics . (2021). Employer costs for employee compensation. (News Release). Author. https://www.bls.gov/news.release/pdf/ecec.pdf

Bureau of Labor Statistics . (2022). Occupational outlook handbook. Author. https://www.bls.gov/ooh/

Bureau of Labor Statistics . (2023). 2.1 million job openings in health care and social assistance in September 2022. Author. https://www.bls.gov/opub/ted/2022/2-1-million-job-openings-in-health-care-and-social-assistance-in-september-2022.htm

Cardoza

(2021, September 28). There’s a shortage of home health aides for the elderly, and it’s getting worse. National Public Radio. https://www.npr.org/2021/09/28/1031651663/shortage-home-health-aides-elderly

10.

Charlie

(2017). Ensuring the continuation of the public health nurses workforce: Comparison of work outcomes with nurses in other sectors of healthcare. Doctoral dissertation. University of Pennsylvania (ProQuest Dissertation and Theses Global.

11.

Davison

H. K.

Blackburn

A. S.

(2023). The case for offering paid leave: Benefits to the employer, employee, and society. Compensation & Benefits Review, 55(1), 3–18. https://doi.org/10.1177/08863687221131728

12.

Delp

Wallace

S. P.

Geiger‐Brown

Muntaner

(2010). Job stress and job satisfaction: Home Care Workers in a consumer‐directed model of care. Health Services Research, 45(4), 922–940. https://doi.org/10.1111/j.1475-6773.2010.01112.x

13.

Despard

(2022). Benefits cliffs: Effects on worker and the role of employers. U.S. Chamber of Commerce Foundation. https://www.uschamberfoundation.org/sites/default/files/USCCF_BenefitsCliffsBrochure_Digital.pdf

14.

Despard

Frank-Miller

Fox-Dichter

Germain

Conan

(2020). Employee financial wellness programs: Opportunities to promote financial inclusion? Journal of Community Practice, 28(3), 219–233. https://doi.org/10.1080/10705422.2020.1796878

15.

Despard

Frank-Miller

Zeng

Fox-Dichter

Germain

Grinstein-Weiss

Covington

(2020). Employee financial wellness programs: Promising new benefit for frontline workers? Compensation and Benefits. Review, 52(4), 156–174. https://doi.org/10.1177%2F0886368720942371

16.

Despard

Grinstein-Weiss

Chun

Roll

(2020, July 13). COVID-19 job and income loss leading to more hunger and financial hardship. Brookings Institution. https://www.brookings.edu/blog/up-front/2020/07/13/covid-19-job-and-income-loss-leading-to-more-hunger-and-financial-hardship/

17.

Despard

Guo

Grinstein-Weiss

Russell

Oliphant

de Ruyter

(2018). The mediating role of assets in explaining hardship risk among households experiencing financial shocks. Social Work Research, 42, 147–158. https://doi.org/10.1093/swr/svy012

18.

Despard

Levy

(2022). Offering free tax assistance and promoting the EarnedIncome Tax Credit through the workplace: A pilot evaluation with Goodwill Industries. U.S. Chamber of Commerce Foundation. https://www.uschamberfoundation.org/sites/default/files/EITC%20Goodwill%20Pilot%20Evaluation.pdf

19.

Despard

Zeng

Fox-Dichter

Frank-Miller

Grinstein-Weiss

(2021). Can workplace financial counseling help lower-income workers improve credit outcomes? Journal of Financial Counseling and Planning, 32(3), 432–448. https://doi.org/10.1891/JFCP‐19‐00081

20.

Dill

J. S.

Morgan

J. C.

Marshall

V. W.

Pruchno

(2013). Contingency, employment intentions, and retention of vulnerable low-wage workers: An examination of nursing assistants in nursing homes. The Gerontologist, 53(2), 222–234. https://doi.org/10.1093/geront/gns085

21.

Ejaz

F. K.

Noelker

L. S.

Menne

H. L.

Bagaka’s

J. G.

(2008). The impact of stress and support on direct care workers’ job satisfaction. The Gerontologist, 48 Spec No 1(suppl_1), 60–70. https://doi.org/10.1093/geront/48.supplement_1.60

22.

Financial Health Network . (2019). Better for employees, better for business: The case for employers to invest in employee financial health. Author. https://s3-amazonaws-com-443.web.bisu.edu.cn/cfsi-innovation-files-2018/wp-content/uploads/2019/05/24163214/FHN-MorganStanley-Infographic-FINAL.pdf

23.

FINRA Investor Education Foundation & Filene Research Institute . (2017). Employer-sponsored small-dollar loan: Feasibility study report. https://filene.org/do-something/programs/employer-sponsored-small-dollar-loans

24.

FINRA Investor Education Foundation . (2022). National financial capability study (5th Edition). Author. https://finrafoundation.org/knowledge-we-gain-share/nfcs

25.

Frank-Miller

Despard

Germain

Grinstein-Weiss

Covington

(2019). Financial wellness programs in the workplace: Employer motivations and experiences. Journal of Workplace Behavioral Health, 34, 241–264. https://doi.org/10.1080/15555240.2019.1594851

26.

Franzosa

(2016). The effects of job characteristics on home care workers’ well-being and job performance: Understanding the psychosocial effects of relational care. Doctoral dissertation. City University of New York (ProQuest Dissertation and Theses Global.

27.

Fremstad

(2011). Maintaining and improving social security for direct care workers. Center for Economic and Policy Research. https://www.cepr.net/report/maintaining-and-improving-social-security-for-direct-care-workers/

28.

Galvin

(2021, October 4). Nearly 1 in 5 health care workers have quit their jobs during the pandemic. Morning Consult. https://morningconsult.com/2021/10/04/health-care-workers-series-part-2-workforce/

29.

Gandhi

Grabowski

D. C.

(2021). High nursing staff turnover in nursing homes offers important quality information: Study examines high turnover of nursing staff at U.S. nursing homes. Health Affairs, 40(3), 384–391. https://doi.org/10.1377/hlthaff.2020.00957

30.

Gillet

Colombat

Michinov

Pronost

A. M.

Fouquereau

(2013). Procedural justice, supervisor autonomy support, work satisfaction, organizational identification and job performance: The mediating role of need satisfaction and perceived organizational support. Journal of Advanced Nursing, 69(11), 2560–2571. https://doi.org/10.1111/jan.12144

31.

Gjertson

(2016). Emergency saving and household hardship. Journal of Family and Economic Issues, 37, 1–17. https://doi.org/10.1007/s10834-014-9434-z

32.

Heflin

C. M.

Iceland

(2009). Poverty, material hardship, and depression. Social Science Quarterly, 90(5), 1051–1071. https://doi.org/10.1111/j.1540-6237.2009.00645.x

33.

Huang

Heflin

C. M.

Validova

(2021). Material hardship, perceived stress, and health in early adulthood. Annals of Epidemiology, 53, 69–75.e3. https://doi.org/10.1016/j.annepidem.2020.08.017

34.

KennedyApplebaumBowblis

K.R.J. R.

Applebaum

Bowblis

J. R.

(2020). Facility-level factors associated with CNA turnover and retention: Lessons for the long-term services industry. The Gerontologist, 60(8), 1436–1444. https://doi.org/10.1093/geront/gnaa098

35.

Kim

Garman

E. T.

(2004). Financial stress, pay satisfaction and workplace performance. Compensation & Benefits Review, 36(1), 69–76. https://doi.org/10.1177/0886368703261215

36.

Kim

LinLunaMa

Y. G. J.

Stiehl

E. G.

Stiehl

(2020). Certified nursing assistants’ barriers and facilitators to accessing and using worksite health promotion programs. Journal of Occupational and Environmental Medicine, 62(11), 943–952. https://doi.org/10.1097/JOM.0000000000002007

37.

Lester

G. V.

Brock Baskin

M. E.

Clinton

M. S.

(2021). Employer-sponsored benefits in the United States: The past, present, and future. Compensation and benefits review, 53(1), 24–42. https://doi.org/10.1177/0886368720947609

38.

Luo

Lin

Castle

N. G.

(2013). The correlates of nursing staff turnover in home and hospice agencies: 2007 National Home and Hospice Care Survey. Research on Aging, 35(4), 375–392. https://doi.org/10.1177/0164027512443072

39.

Marty Martin

Lopez

Flannery

T. P.

Dixon

(2021). Infectious disease: Protecting workers and organizations-the role of compensation & benefits. Compensation and benefits review, 53(1), 43–55. https://doi.org/10.1177/0886368720947332

40.

McCall

(2021, April 12). Will COVID-19 change direct care employment? New data offers clues. PHI. http://phinational.org/will-covid-19-change-direct-care-employment-new-data-offer-clues/

41.

McCall

Scales

(2022). Direct care worker disparities: Key trends and challenges (Issue Brief). PHI. http://www.phinational.org/wp-content/uploads/2022/02/Direct-Care-Worker-Disparities-2022-PHI.pdf

42.

McCarthy

Carter

Jansson

Benoit

Finnigan

(2018). Poverty, material hardship, and mental health among workers in three front-line service occupations. Journal of Poverty, 22(4), 334–354. https://doi.org/10.1080/10875549.2017.1419532

43.

McGilton

K. S.

Boscart

V. M.

Brown

Bowers

(2014). Making tradeoffs between the reasons to leave and reasons to stay employed in long-term care homes: Perspectives of licensed nursing staff. International Journal of Nursing Studies, 51(6), 917–926. https://doi.org/10.1016/j.ijnurstu.2013.10.015

44.

Mittal

Rosen

Leana

(2009). A dual-driver model of retention and turnover in the direct care workforce. The Gerontologist, 49(5), 623–634. https://doi.org/10.1093/geront/gnp054

45.

National Center for Health Statistics . (2011). An overview of home health aides: United States, 2007. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. https://www.cdc.gov/nchs/data/nhsr/nhsr034.pdf

46.

Neckerman

K. M.

Garfinkel

Teitler

J. O.

Waldfogel

Wimer

(2016). Beyond income poverty: Measuring disadvantage in terms of material hardship and health. Academic Pediatrics, 16(3 Suppl), S52–S59. https://doi.org/10.1016/j.acap.2016.01.015

47.

Nei

Snyder

L. A.

Litwiller

B. J.

(2015). Promoting retention of nurses: A meta-analytic examination of causes of nurse turnover. Health Care Management Review, 40(3), 237–253. https://doi.org/10.1097/HMR.0000000000000025

48.

Orbe

Synderman

Sprick

Akabas

(2022). New BPC survey underscores Americans’ financial fragility, demand for workplace and policy innovation. Bipartisan Policy Center. https://bipartisanpolicy.org/blog/new-bpc-survey-underscores-americans-financial-fragility-demand-for-workplace-and-policy-innovation/

49.

PHI . (2021). U.S. home care workers: Key facts. Author. https://phinational.org/resource/direct-care-workers-in-the-united-states-key-facts-2/

50.

Price-Glynn

Rakovski

(2012). Who rides the glass escalator? Gender, race and nationality in the national nursing assistant study. Work, Employment and Society, 26(5), 699–715. https://doi.org/10.1177/0950017012451634

51.

PwC . (2023). PwC’s 2023 employee financial wellness survey. https://www.pwc.com/us/en/services/consulting/business-transformation/library/employee-financial-wellness-survey.html

52.

Richardson

Elliott

Roberts

(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.2013.08.009

53.

Rodems

Pfeffer

F. T.

(2021). Avoiding material hardship: The buffer function of wealth. Journal of European Social Policy, 31(5), 517–532. https://doi.org/10.1177/09589287211059043

54.

Rosen

Stiehl

E. M.

Mittal

Leana

C. R.

(2011). Stayers, leavers, and switchers among certified nursing assistants in nursing homes: A longitudinal investigation of turnover intent, staff retention, and turnover. The Gerontologist, 51(5), 597–609. https://doi.org/10.1093/geront/gnr025

55.

Seeholzer

E. L.

Santiago

Thomas

DeAngelis

Scarl

Webb

Woods

Sehgal

A. R.

(2022). Prevalence of social determinants of health among health system employees. Journal of Primary Care & Community Health, 13, 21501319221113956. https://doi.org/10.1177/21501319221113956

56.

Spector

P. E.

(1985). Measurement of human service staff satisfaction: Development of the job satisfaction survey. American Journal of Community Psychology, 13(6), 693–713. https://doi.org/10.1007/BF00929796

57.

Squillace

M. R.

Remsburg

R. E.

Harris-Kojetin

L. D.

Bercovitz

Rosenoff

Han

(2009). The national nursing assistant survey: Improving the evidence base for policy initiatives to strengthen the certified nursing assistant workforce. The Gerontologist, 49(2), 185–197. https://doi.org/10.1093/geront/gnp024

58.

Srinivasan

Cen

Farrar

Pooler

J. A.

Fish

(2021). Food insecurity among health care workers in the US: Study examines food insecurity among health care workers in the United States. Health Affairs, 40(9), 1449–1456. https://doi.org/10.1377/hlthaff.2021.00450

59.

Sterling

M. R.

Tseng

Poon

Cho

Avgar

A. C.

Kern

L. M.

Ankuda

C. K.

Dell

(2020). Experiences of home health care workers in New York City during the coronavirus disease 2019 pandemic: A qualitative analysis. JAMA Internal Medicine, 180(11), 1453–1459. https://doi.org/10.1001/jamainternmed.2020.3930

60.

Stone

Wilhelm

BishopBryantHermer

C.N. S.L.

Squillace

M. R. S.

Hermer

Squillace

M. R.

(2017). Predictors of intent to leave the job among home health workers: analysis of the National Home Health Aide Survey. The Gerontologist, 57(5), 890–899. https://doi.org/10.1093/geront/gnw075

61.

Sullivan

Meschede

Shapiro

Kroeger

Escobar

(2019). Not only unequal paychecks: Occupational segregation, benefits, and the racial wealth gap. Institute on Assets and Social Policy. https://heller.brandeis.edu/iasp/pdfs/racial-wealth-equity/asset-integration/occupational_segregation_report_40219.pdf

62.

Telesford

Wager

Hughes-Cromwick

Amin

Cox

(2023). How has health sector employment recovered since the pandemic?. Peterson-KFF Health System Tracker. https://www.healthsystemtracker.org/chart-collection/what-impact-has-the-coronavirus-pandemic-had-on-healthcare-employment/

63.

Temple

Dobbs

Andel

(2011). Exploring correlates of turnover among nursing assistants in the National Nursing Home Survey. The Journal of nursing administration, 41(7-8 Suppl), S34–S42. https://doi.org/10.1097/NNA.0b013e318221c34b

64.

U.S. Department of Agriculture . (2012). U.S. household food insecurity survey module: Three-stage design, with screeners. https://www.ers.usda.gov/media/8271/hh2012.pdf

65.

Veliotis

Steve

(2022). The tax cuts and jobs act of 2017 and the gig economy: Why the employee vs. contractor debate matters more than ever. Compensation & Benefits Review, 54(2), 85–92. https://doi.org/10.1177/08863687211060242

66.

Verne

(2014). Financial wellness programs to reduce employee stress. Compensation & Benefits Review, 46(5-6), 304–308. https://doi.org/10.1177/0886368714566150

67.

Watson

Biu

(2022). You can’t improve black women’s economic well-being without addressing both wealth and income gaps. Urban Institute. https://www.urban.org/urban-wire/you-cant-improve-black-womens-economic-well-being-without-addressing-both-wealth-and

68.

Wiener

J. M.

Squillace

M. R.

Anderson

W. L.

Khatutsky

(2009). Why do they stay? Job tenure among certified nursing assistants in nursing homes. The Gerontologist, 49(2), 198–210. https://doi.org/10.1093/geront/gnp027

69.

Yoon

Probst

DiStefano

(2016). Factors affecting job satisfaction among agency-employed home health aides. Home Health Care Management & Practice, 28(1), 57–69. https://doi.org/10.1177/1084822315603195