Material hardship and sources of support for autistic adolescents and their families

Abstract

This exploratory study used the Future of Families and Child Wellbeing Study (FFCWS) to compare the financial well-being of families of adolescents with and without autism. Recognizing the gap in autism research, which predominantly measures financial well-being through household income, this study employed a multidimensional approach, including indicators of assets, material hardships, and both formal and informal safety net access. We found that families with autistic adolescents experienced greater financial instability, including a higher likelihood of substantial income drops and bankruptcy. Despite similar access to food assistance programs, food insecurity was notably higher among these families, especially in the lowest income brackets where nearly all families utilized food assistance. Furthermore, material hardship prevalence (46.4%) exceeded income poverty (29.8%), among families with autistic adolescents. A substantial proportion of middle- to high-income families also experienced hardships, had no assets, and lacked connection to safety net programs, suggesting that income-based metrics may not fully capture the financial challenges families face. The findings highlight the need for policies that acknowledge the broader financial needs of families with autistic adolescents, underscoring the inadequacies of current support systems.

Lay abstract

Our study looks at how families with autistic teenagers manage financially compared with families with teenagers who do not have autism. We know that money matters are a big part of life’s overall quality and that autistic individuals and their families often face more financial challenges. These challenges can affect their health, social connections, and access to needed services. What our research adds is a closer look at these financial difficulties by considering not just how much money a family has but also what they own, their struggles to meet basic needs, and the help they get from both government programs and their own social circles. We found that families with autistic teenagers often deal with more financial problems, including not having enough food, even though they might be using available support programs. This is important because it shows us that the current ways of helping may not be enough. Our findings suggest we need to think more broadly about how to support these families. This could mean making policies that better address their unique needs or coming up with new ways to help them that go beyond just looking at income. Understanding these challenges better can help us make life better for autistic individuals and their families.

Financial well-being significantly impacts the quality of life (Pellicano et al., 2024; Weida et al., 2020) and is particularly critical for families with autistic adolescents, who face unique economic challenges (Anderson, Rast, et al., 2020). National data shows that families with autistic children are more likely to encounter financial problems and require additional income to cover medical expenses compared with families of children with other disabilities (Kogan et al., 2008; Vohra et al., 2014). These families often experience lower employment rates and incomes and are more likely to leave their jobs to provide care, compared with families without health limitations (Montes & Halterman, 2008). The financial challenges are particularly severe for those caring for autistic children with co-occurring conditions or more severe symptoms, with associated costs significantly exceeding those of families without co-occurring health limitations (Matin et al., 2022).

Low-income families are particularly vulnerable to challenges such as care-related expenses, reduced earnings from caregiving-related work absences, and limited access to services and support (Liao & Li, 2020; Pickard & Ingersoll, 2016). In addition to having fewer economic resources, children from low-income households are also more likely to exhibit behavioral problems and have poorer health, resulting in the need for more extensive and intensive care (Assing-Murray & Lebrun-Harris, 2020; Flouri et al., 2015; Midouhas et al., 2013). Recent data indicates that half of autistic children reside in low-income households, with a significant portion living below the poverty line, highlighting the pervasive impact of financial hardship (Anderson et al., 2022).

While income is a crucial indicator of financial well-being, it often fails to capture the full extent of financial challenges faced by these families (Parish, Rose, et al., 2008). Many researchers contend that fully grasping and addressing the economic realities of families with autistic children requires a broader perspective that encompasses the individual’s ability to meet essential needs across economic, social, and other well-being domains (Ouellette et al., 2004). Yet there is no universally accepted definition or measurement approach for financial well-being, leading to varied focus in research (de Oliveira Cardoso et al., 2023; Taylor, 2011; Weida et al., 2020).

Dimensions of financial well-being

The multidimensional nature of financial well-being generally encompasses economic resources, material hardship, and safety nets, each contributing uniquely to the overall financial well-being of families (Anderson, Rast, et al., 2020; Radey et al., 2024; Weida et al., 2020). Economic resources include not only income but also assets and savings, which offer insights into long-term financial stability (Palmer, 2011). Material hardship, on the contrary, directly reflects the immediate challenges families face in meeting basic needs such as food, housing, and healthcare (Health Resources and Services Administration [HRSA], 2023). Safety nets, both formal (e.g., government-issued programs, like food stamps) and informal (e.g., support from family and friends), play a vital role in mitigating these hardships by providing necessary financial support during times of need (Sohn, 2023).

While these three dimensions often overlap, they are distinct and may manifest independently of one another. For instance, a family might have a low income yet possess significant assets or savings that buffer against material hardship. Conversely, a family could exhibit substantial material hardship or have limited assets despite their income being above the poverty line. Studies have shown that, even among wealthier households of autistic children, families need help paying for their child’s medical care (Parish et al., 2015). Further, many of the factors that influence one dimension of financial well-being also covary (or predict) other dimensions. For instance, the factors that predispose families to use formal safety net programs (such as being a single parent or having children from minoritized racial or ethnic backgrounds) are also associated with greater odds of material hardship and fewer economic resources among families with autistic children (Anderson et al., 2024) and other developmental disabilities (Parish et al., 2012). Socioeconomic status is related to race as well, with a greater proportion of autistic children of color, particularly Black and Hispanic/Latino children, living in low-income households (Anderson et al., 2022).

Research gaps and study aims

Although research acknowledges the distinct and complementary nature of the three dimensions of financial well-being, studies exploring their interplay and distinctions among families with autistic members are scarce. Most research has predominantly focused on income poverty; frequently implying that this single metric sufficiently represents financial well-being (Anderson et al., 2018; Shattuck et al., 2020). Meanwhile, investigations into other economic resources, such as assets, are less common and typically focus on adult populations (Cai et al., 2022, 2023; Pellicano et al., 2024). Recent research has explored the financial support that families with autistic individuals receive from government programs (Anderson et al., 2024; Karpur et al., 2021; Vasudevan et al., 2021) and, to a lesser extent, from friends and family (Pellicano et al., 2024). However, these studies are few. Recognizing the multidimensional nature of financial well-being is crucial for crafting policies that effectively help these families achieve and maintain economic stability.

This study employs a multidimensional approach to financial well-being, focusing on economic resources, material hardship, and safety nets to address the complex needs of families with autistic adolescents. By integrating these dimensions, we aim to provide a comprehensive analysis of the financial landscapes of families with and without autistic adolescents. Utilizing the underexplored Future of Families and Child Wellbeing Study (FFCWS) dataset, which includes a wide range of financial indicators such as assets, material hardship, and informal safety nets, our research offers an extensive view of the financial needs and support systems for these families. This comprehensive perspective is crucial for informing policy decisions that rely on nuanced assessments of financial needs and the accessibility of safety nets, enhancing our understanding of the financial challenges and resources available to these groups. In addition, our study seeks to identify potential risk factors for material hardship, pinpointing critical intervention points and identifying the most vulnerable subgroups. This targeted approach ensures that safety net programs and policies are finely tailored to those who stand to benefit the most, thereby optimizing support and improving the financial well-being and overall quality of life for families facing significant challenges.

Method

Data source

The FFCWS was initiated in 1998–2000 to investigate unmarried mothers’ (and fathers’) conditions and experiences from their child’s birth (Reichman et al., 2001). It has served as a principal source of national-level information on family relationships and the broader social environment during children’s development (Geller et al., 2018). The baseline FFCWS sample comprised 4898 infants born between 1998 and 2000, with parents drawn from 20 major U.S. cities with populations exceeding 200,000. The FFCWS oversampled births to unmarried parents to investigate at-risk households, rendering it ideal for studying safety nets as it represents a relatively economically disadvantaged sample. The dataset currently includes six waves of data collection, starting with baseline interviews conducted shortly after the child’s birth, followed by subsequent surveys at 1, 3, 5, 9, and 15 years later. This study used Wave Five data collected from 2014 to 2017, incorporating caregivers’ responses about their 15-year-old adolescent participants. Among the 4663 eligible families (95% of the baseline sample) for the Year 15 follow-up survey, 3580 caregivers (77%) completed the interviews (Office of Population Research, Princeton University, 2018). The use of this dataset received exempt approval from the Institutional Review Board at Florida State University

Participants

This study’s primary focus was on the subgroup of households in which the focal child had autism, or families with autistic adolescents, hereafter. Adolescents were considered to have autism if parents/caregivers affirmed to the survey question: “Has a doctor or health professional ever told you that your child has Autism or Asperger’s Syndrome?” We excluded one case in which the parent did not know, resulting in a total of 84 families with autistic adolescents. The comparison group consisted of 3495 adolescents of the same age who did not have autism.

Measures

Economic resources

Household income was measured using an imputed income measure created by the FFCWS staff, based on the official poverty thresholds published by the U.S. Census (Office of Population Research, Princeton University, 2018). We segmented household income into three poverty level categories: poor—below or equal to 100% of the federal poverty level (FPL), low—income—between 101% and 199% FPL, and middle—to high—income—200% FPL or above. Assets included measures of home ownership, credit card access, any savings, and savings for 2 months of expenses. We also examined whether caregivers (a) experienced a large drop in household income and (b) filed for bankruptcy in the past 7 years.

Material hardship

Caregivers responded to nine dichotomous items that indicated whether they had experienced various material hardships over the past 12 months. Families were coded as having food insecurity if they responded affirmatively to the question, “In the past 12 months, were you ever hungry, but did not eat because you could not afford enough food?” Medical hardship occurred if there was anyone in the household who “needed to see a doctor or go to the hospital but couldn’t because of the cost.” Housing hardship included caregivers who “moved in with other people even for a little while because of financial problems,” “stayed in a shelter, in an abandoned building, an automobile or any other place not meant for regular housing, even for one night,” or was “evicted from their home or apartment for not paying the rent or mortgage.” Bill-paying hardship referred to caregivers who either skipped a rent or mortgage payment in the past 12 months or did not pay utility bills in full. Utility hardship occurred if caregivers had their telephone disconnected or utilities shut off because there was not enough money. We also calculated depth of hardship, by summing the values from the five hardship dimensions mentioned above.

Safety nets

The formal safety net encompassed six programs categorized into four main groups: cash assistance, food assistance, rental assistance, and public health insurance. For cash assistance, we used yes/no responses to two survey questions inquiring about income received from: (a) Welfare or Temporary Assistance for Needy Families (TANF) or General Assistance; or (b) Supplemental Security Income (SSI) or Social Security Disability Insurance (SSDI) in the past 12 months. Food assistance involved the use of the Supplemental Nutrition Assistance Program (SNAP) in the past 12 months and the current use of the National School Breakfast/Lunch program (NSBLP). Rental assistance referred to the receipt of government help (federal, state, or local) in paying rent, including benefits like public housing or Section 8 vouchers. Public health insurance included adolescents currently covered by Medicaid or another public program for medical care (e.g., Children’s Health Insurance Program (CHIP)). All programs were measured at the household level except for the NSBLP and public health insurance, which were measured at the adolescent level. The count of formal benefits ranged from zero to six, considering the adolescent’s or household’s enrollment in the measured formal safety net program (TANF, SSI/SSDI, SNAP, NSBLP, rental assistance, and public health insurance). Table 1 provides more information about each program and its eligibility requirements.

Table 1.

Overview of formal safety net programs.

Program	Description	Funding	Eligibility
Cash assistance
Temporary Assistance for Needy Families (TANF)	Federal program that provides time-limited financial assistance and support services (like job preparation or childcare subsidies) to needy families with children under 18 years.	Federally funded, state-operated (states receive block grants to design and operate programs).	Eligible Unit: Household. Note: The household must comprise at least one 1dependent child and their parent(s) or caretaker relatives. Means-tested based on income, assets, and composition.
Supplemental Security Income (SSI) Program	Federal program that provides monthly cash benefits to individuals or couples with limited income and resources who have a disability, are blind, or are 65 years or older.	Federally funded by general tax revenues, with optional state financial supplementation.	Eligible unit: Individuals or couples. Means-tested based on income and assets, with categorical eligibility for elders, those who are blind, or those with disabilities.
Social Security Disability Insurance (SSDI) Program	Provides financial assistance to individuals wh are unable to work due to a medically determinable physical or mental disability expected to last at least 1 year or result in death.	Federally funded through payroll taxes under the Social Security Act.	Eligible unit: Individual Based on (a) work history—the applicant has worked and paid into the Social Security system for a certain number of years, with the amount of work required depending on the individual’s age at the time of disability and (b) disability status.
Food assistance
Supplemental Nutrition Assistance Program (SNAP)	Federal program offering nutrition assistance, such as vouchers for food purchases, to eligible, low-income individuals and families.	Federally funded, state operated.	Eligible unit: All individuals that live together and purchase or prepare food together. Low-income individuals and families. Means-tested based on income and household size.
National School Breakfast or Lunch Program (NSBLP)	Provides nutritious free or reduced-price lunches and breakfasts to eligible children in schools and residential childcare institutions.	Federally funded.	Eligible Unit: Individual students. Children in schools from low-income families; eligibility is means-tested or categorical based on SNAP participation.
Rental assistance
Section 8 Housing Vouchers	Offers rental housing assistance to low-income families through vouchers that subsidize a portion of their rent in privately owned housing.	Federally funded.	Eligible unit: Household. Low-income families, elders, and individuals with disabilities. Eligibility is means-tested, based on income and family size.
Public housing	Offers affordable housing options to low-income families, elders, and people with disabilities through federally funded and locally managed public housing developments. Can include public housing and private sector aid.	Federal, state, and local funding.	Eligible unit: Household. Low-income families, elders, and individuals with disabilities. Eligibility varies, generally means-tested.
Public health insurance
Medicaid	Entitlement program that provides health coverage to low-income individuals and families, including many with disabilities. Covers a broad range of health services.	Jointly funded by state and federal government.	Eligible unit: Individual. Low-income individuals and families, including those with disabilities. Eligibility is means-tested, with some categorical eligibility (can be based on disability, SSI, or TANF). Eligibility varies by state.
CHIP	Offers health coverage to children in families with incomes too high to qualify for Medicaid but too low to afford private coverage.	Jointly funded by state and federal government.	Eligible Unit: Individual. Note—Children up to age 19. Eligibility is based on family income that can lie above Medicaid thresholds but within CHIP limits.

Sources: Temporary Assistance for Needy Families (TANF): U.S. Department of Health and Human Services (n.d.-c); Supplemental Security Income (SSI): Social Security Administration (n.d.); Supplemental Nutrition Assistance Program (SNAP): U.S. Department of Agriculture (n.d.-b); National School Breakfast or Lunch Program (NSBLP): U.S. Department of Agriculture (n.d.-a); Medicaid: Medicaid.gov (n.d.-b); and Children’s Health Insurance Program (CHIP): Medicaid.gov (n.d.-a).

Informal safety net recipients included caregivers who reported receiving cash or housing assistance from family or friends (i.e., lived with family without paying rent or moved in with family due to need) in the past 12 months. We also assessed the perceived availability of in-kind and small financial support from family and friends, along with the perceived access to substantial financial support. Following the approach used in previous studies (Campbell et al., 2022; Pilkauskas et al., 2012; Radey & Brewster, 2013), perceived support was based on caregiver responses to three dichotomous items that indicated whether they could count on someone to (a) lend them $200, (b) provide them with a place to live, or (c) assist with emergency childcare during the next year if necessary. Caregivers affirming all three questions were considered to have perceived full support. If a caregiver could rely on someone to provide a $1000 loan and co-sign a $1000 bank loan, we considered them to have substantial financial support.

Demographics and health-related characteristics

Adolescent demographics included race, ethnicity, and sex. Adolescent health and healthcare characteristics included: overall health, diagnosis of attention-deficit/hyperactivity disorder (ADD/ADHD), depression or anxiety, and/or other learning disabilities, prescribed medication use, and whether the adolescent was seen by a professional for illness in the past year. We also included a three-category measure of adolescent’s type of health insurance coverage (uninsured, Medicaid, and private insurance). At the caregiver level, we examined overall health, education, and current work status. Among those who were currently working, we also reported weekly work hours and occupation type. We included diagnosed depression based on Major Depressive Episode questions from the Composite International Diagnostic Interview—Short Form (CIDI-SF), Section A.19 (Kessler et al., 1998), which past studies indicate acceptable to high reliability and validity (Olsen et al., 2003). For the evaluation of caregiver-related measures, Cronbach’s alpha was calculated to assess the internal consistency of the composite scales derived from caregivers of autistic adolescents’ responses. The resulting alpha of 0.79 indicates good reliability, affirming the consistency and suitability of these measures for our analysis.

Analysis

We began by presenting background information on the sample’s demographic characteristics, along with descriptions of adolescent health and healthcare (Table 2). Then, we provided information concerning the economic resources, material hardships, and support sources within households with autistic adolescents, relative to those of adolescents without autism (Tables 3 and 4). We also explored the relationship between household income with other indicators of financial well-being by calculating the percentage of families in each income category who reported specific assets, material hardships, or safety nets for adolescents with and without autism (Table 5). We analyzed differences among study covariates by calculating univariate percentages and counts and used logistic regression with dummy coding to identify significant disparities in characteristics and outcomes between adolescents with and without autism. Finally, we employed bivariate analyses among the subpopulation of families with autistic adolescents to compare the distributions of families who reported at least one material hardship to those who did not, along with separate analyses to investigate factors related to any material hardship (Table 6). We calculated crude odds ratios to quantify the association’s magnitude between variables and used an alpha level of 0.05 for tests of statistical significance. Following Olivier and Bell’s (2013) guidelines, an odds ratio of 1.22, 1.86, or 3.0 corresponded to small, medium, and large effect sizes, respectively. We conducted an a priori power analysis for bivariate logistic regression with a type I error rate of 0.05 and a power of 0.80 (Faul et al., 2009). The power analysis indicated a minimum sample size of 204 to detect a medium effect (odds ratio of 1.5 or less). Missing data rates among our sample of families with autistic adolescents ranged from 0.0% to 6.0% (single-parent household). About 3.6% of participants had missing data on occupation type and 2.4% did not have a value for household education. All other study variables had a missing rate under 1.2%.

Table 2.

Demographic and health-related characteristics, by autism diagnosis: tests of significance versus no autism, counts and percentages n (%).

	No autism (n = 3495)		Autism (n = 84)
	n	(%)	n	(%)
Adolescents
Race and ethnicitya
White	593	(17)	30	(35.7)***
Black	1,767	(50.6)	30	(35.7)**
Other or multicultural	107	(3.1)	2	(2.4)
Hispanic/Latino	1,022	(29.3)	22	(26.2)
Male	1,786	(51.1)	68	(81)***
Disabilities/mental health disorders
ADD/ADHD	541	(15.5)	47	(56)***
Depression or Anxiety	221	(6.3)	20	(23.8)***
Learning disability	370	(10.6)	33	(39.8)***
Takes prescribed medications	956	(27.4)	51	(60.7)***
Has regular source of healthcare	3303	(94.6)	80	(95.2)
Healthcare coverage
None	127	(3.6)	0	(0)
Medicaid	2104	(60.4)	54	(64.3)
Private insurance	1250	(35.9)	30	(35.7)
Caregivers
Single parentb	1461	(44)	34	(43)
Number of kids (<18) in household
One	913	(26.1)	25	(25)
Two	1065	(30.5)	28	(28)
Three or more	1516	(43.4)	31	(31)
Education level
High school or less	1301	(37.5)	26	(31.7)
Some college	1519	(43.8)	37	(45.1)
College graduate	650	(18.7)	19	(23.2)
Currently works for pay	2460	(70.7)	55	(65.5)
Among those who currently work
Work hours
Part-time (<35 hours/week)	532	(21.9)	17	(31.5)+
Full-time (35+ hours/week)	1899	(78.1)	37	(68.5)+
Occupation typec
Professional/executive	727	(31.3)	14	(26.4)
Administrative	516	(22.3)	9	(17)
Sales and related	162	(7)	6	(11.3)
Machine operators/laborers	187	(8.1)	3	(5.7)
Service	678	(29.2)	17	(32.1)
Unspecified/Otherd	49	(2.1)	4	(7.5)*
Fair/Poor health	680	(19.5)	21	(25)
Depressione	420	(12)	20	(23.8)**

ADHD, attention-deficit/hyperactivity disorder.

^aThe FFCWS used race and ethnicity equivalently.

^bVersus married or cohabitating; restricted to primary caregivers who were biological parents of the adolescent (N = 79).

^cBased on three-digit codes from the U.S. Bureau of Labor Statistics’ May 2016 Major Occupation Groups, as detailed in their Occupation Profile (https://www.bls.gov/oes/current/oes_stru.htm).

^dThis refers to categories with fewer than 10 cases, as defined by the FFCWS to maintain participant confidentiality, or when a response was either not provided or was unclear.

^eCaregivers met conservative estimate of diagnosis for major depression in the past year based on Major Depressive Episode questions from the Composite International Diagnostic Interview—Short Form (CIDI-SF), Section A.19.

^***p < 0.001,

^**p < 0.01,

^*p < 0.05,

⁺p < 0.10.

Table 3.

Economic resources and material hardships, by autism diagnosis: tests of significance versus no autism, counts and percentages n (%).

	No autism (n = 3495)		Autism (n = 84)
	n	(%)	n	(%)
Assets and debt
Household income
Poor (under 100% FPL)	1,068	(30.6)	25	(29.8)
Low income (100–199% FPL)	984	(28.2)	26	(31)
Middle to high income (>200% FPL)	1435	(41.2)	33	(39.3)
Home ownership	1159	(33.3)	29	(34.5)
Has credit card	1620	(46.7)	37	(44)
Has (any) savings	1592	(46.1)	37	(44)
Has savings for 2 months of expenses	846	(24.6)	17	(20.5)
Large drop in income in past 7 years	1074	(31.2)	33	(39.8)+
Filed for bankruptcy in past 7 years	236	(6.8)	11	(13.1)*
Material hardships
Food	514	(14.7)	23	(27.4)**
Medical	154	(4.4)	8	(9.5)*
Housing	195	(5.6)	7	(8.3)
Bill-paying	1109	(31.8)	26	(31)
Utilities	692	(19.9)	18	(21.4)
Depth of hardshipa
None	2018	(57.7)	45	(53.6)
1	722	(20.7)	16	(19)
2 or more categories	755	(21.6)	23	(27.4)

FPL, federal poverty level.

^aSum of hardship domains (food, medical, housing, bill-paying, and utilities).

^***p < 0.001,

^**p < 0.01,

^*p < 0.05,

⁺p < 0.10.

Table 4.

Formal and informal safety net use, by autism diagnosis: tests of significance versus no autism, counts and percentages n (%).

	No autism (n = 3495)		Autism (n = 84)
	n	(%)	n	(%)
Formal safety net
TANF	376	(10.8)	10	(11.9)
SSI/SSDI	824	(23.7)	40	(48.2)***
SNAP	1491	(42.8)	33	(39.3)
NSBLP	2168	(62.6)	46	(54.8)
Rental assistancea	612	(17.6)	15	(17.9)
Medicaidb	2104	(60.5)	54	(64.3)
Number of programsc
None	800	(22.9)	17	(20.2)
1	576	(16.5)	13	(15.5)
2	566	(16.2)	12	(14.3)
3	682	(19.5)	19	(22.6)
4	575	(16.5)	14	(16.7)
5	255	(7.3)	6	(7.1)
6	41	(1.2)	3	(3.6)+
Informal safety net
Received money from family/friends	1254	(36)	34	(40.5)
Received housing from family/friends	286	(8.2)	9	(10.7)
Perceived Support
Full supportd	2498	(71.7)	53	(63.1)+
Access to $200	2935	(84.2)	66	(78.6)
Access to place to live	2801	(80.3)	65	(77.4)
Access to childcare	2983	(85.6)	73	(86.9)
Large financial supporte	1657	(47.5)	28	(33.3)*
Access to $1,000	1956	(56.1)	41	(48.8)
Co-signer for $1,000 loan	2061	(59.1)	38	(45.2)*

NSBLP, National School Breakfast/Lunch Program; SNAP, Supplemental Nutrition Assistance Program; SSI/SSDI, Supplemental Security Income or Social Security Disability Insurance; TANF, Temporary Assistance for Needy Families.

^aReceipt of government help in paying rent, including public housing or Section 8 vouchers.

^bIncludes adolescents currently covered by Medicaid or another public program for medical care (e.g., Children’s Health Insurance Program (CHIP)).

^cSum of programs (TANF, SSI/SSDI, SNAP, NSBLP, rental assistance, Medicaid).

^d(Yes) to $200, a place to live, and access to childcare.

^e(Yes) to $1000 and cosigner for $1000 loan.

^***p < 0.001,

^**p < 0.01,

^*p < 0.05,

⁺p < 0.10.

Table 5.

Economic resources, material hardships, and safety nets by household income and autism status: tests of significance versus no autism, counts and percentages n (%).

	Poor (under 100% FPL)				Low-income (100–199% FPL)				Middle- to high-income (≥200% FPL)
	No autism (n = 1068)		Autism (n = 25)		No autism (n = 984)		Autism (n = 26)		No autism (n = 1435)		Autism (n = 33)
	ss	(%)	n	(%)	n	(%)	n	(%)	n	(%)	n	(%)
Assets and debt
Home ownership	121	(11.4)	0	(0)	224	(22.8)	9	(34.6)	812	(56.7)	20	(60.6)
Has credit card	218	(20.5)	6	(24)	406	(41.6)	10	(38.5)	995	(70)	21	(63.6)
Has (any) savings	188	(17.7)	4	(16)	386	(39.6)	11	(42.3)	1,016	(72)	22	(66.7)
Has savings for 2 months of expenses	73	(6.9)	0	(0)	170	(17.5)	4	(15.4)	602	(42.7)	13	(40.6)
Large drop in income in past 7 years	461	(44.2)	12	(48)	310	(31.8)	10	(38.5)	303	(21.4)	11	(34.4)+
Filed for bankruptcy in past 7 years	43	(4)	2	(8)	86	(8.8)	5	(19.2)+	107	(7.5)	4	(12.1)
Material hardships
Food	283	(26.5)	15	(60)***	161	(16.4)	5	(19.2)	70	(4.9)	3	(9.1)
Medical	61	(5.7)	3	(12)	50	(5.1)	4	(15.4)*	43	(3)	1	(3)
Housing	119	(11.2)	4	(16)	52	(5.3)	2	(7.7)	24	(1.7)	1	(3)
Bill-paying	451	(42.4)	9	(36)	366	(37.3)	9	(34.6)	291	(20.3)	8	(24.2)
Utilities	343	(32.2)	8	(32)	218	(22.2)	7	(26.9)	130	(9.1)	3	(9.1)
Any hardshipa	629	(58.9)	18	(72)	484	(49.2)	13	(50)	363	(25.3)	8	(24.2)
Formal safety net
Any cash assistance	540	(50.9)	19	(76)*	331	(33.8)	14	(56)*	198	(13.9)	8	(24.2)+
TANF	247	(23.2)	6	(24)	89	(9.1)	3	(11.5)	40	(2.8)	1	(3)
SSI/SSDI	388	(36.6)	19	(76)***	266	(27.1)	13	(52)**	169	(11.8)	8	(24.2)*
Any food assistance	1,006	(94.5)	24	(96)	821	(83.9)	24	(92.3)	531	(37.3)	8	(24.2)
SNAP	839	(78.8)	20	(80)	481	(49)+	8	(30.8)	167	(11.7)	5	(15.2)
NSBLP	915	(86.5)	19	(76)	756	(77.5)	21	(80.8)	492	(34.6)	6	(18.2)+
Rental assistanceb	381	(35.8)	11	(44)	179	(18.2)	2	(7.7)	52	(3.6)	2	(6.1)
Medicaidc	958	(89.9)	23	(92)	734	(74.8)	22	(84.6)	406	(28.5)	9	(27.3)
Disconnectedd	21	(2)	0	(0)	66	(6.7)	1	(3.8)	711	(49.5)	16	(48.5)
Informal safety net
Received money from family/friends	499	(46.9)	15	(60)	390	(39.7)	10	(38.5)	362	(25.3)	9	(27.3)
Received housing from family/friends	138	(13)	3	(12)	78	(7.9)	4	(15.4)	69	(4.8)	2	(6.1)
Full supporte	600	(56.3)	12	(48)	678	(69)	16	(61.5)	1,215	(84.9)	25	(75.8)
Access to $200	781	(73.3)	16	(64)	810	(82.4)	22	(84.6)	1,337	(93.4)	28	(84.8)+
Access to place to live	728	(68.3)	17	(68)	777	(79.1)	18	(69.2)	1,290	(90)	30	(90.9)
Access to childcare	810	(76)	21	(84)	830	(84.5)	22	(84.6)	1,337	(93.4)	30	(90.9)
Large financial supportf	271	(25.4)	3	(12)	413	(42.1)	5	(19.2)*	970	(67.7)	20	(60.6)
Access to $1,000	356	(33.4)	7	(28)	506	(51.5)	11	(42.3)	1,090	(76.2)	23	(69.7)
Co-signer for $1,000 loan	425	(39.9)	7	(28)	535	(54.5°	8	(30.8)*	1,095	(76.4)	23	(69.7)

FPL, federal poverty level; NSBLP, National School Breakfast/Lunch Program; SNAP, Supplemental Nutrition Assistance Program; SSI/SSDI, Supplemental Security Income or Social Security Disability Insurance; TANF, Temporary Assistance for Needy Families.

^aAt least one of the following hardship types: food, medical, housing, bill-paying, and utilities.

^bReceipt of government help in paying rent, including public housing or Section 8 vouchers.

^cIncludes adolescents currently covered by Medicaid or another public program for medical care (e.g., Children’s Health Insurance Program (CHIP)).

^dDid not receive any of the six formal safety net programs (TANF, SSI/SSDI, SNAP, NSBLP, rental assistance, and Medicaid).

^e(Yes) to $200, a place to live, and access to childcare.

^f(Yes) to $1000 and cosigner for $1000 loan.

^***p < 0.001,

^**p < 0.01,

^*p < 0.05,

⁺p < 0.10.

Table 6.

Predictors of any material hardship among 84 families of autistic adolescents: n (%) and unadjusted OR and 95% CI.

	At least one material hardshipa				Unadjusted OR predicting at least one material hardshi
	No (n = 45)		Yes(n=39)
	n	(%)	n	(%)	OR	[95% CI]
Adolescents
Race and ethnicitb
White or Other	24	(53.3)	8	(20.5)	Ref
Black	12	(26.7)	18	(46.2)	4.50**	[1.52–13.30]
Hispanic/Latino	9	(20)	13	(33.3)	4.33*	[1.35–13.92]
Male	33	(73.3)	35	(89.7)	3.18+	[0.93–10.86]
Disabilities/mental health disorders
ADD/ADHD	23	(51.1)	24	(61.5)	1.53	[0.64–3.65]
Depression or anxiety	9	(20)	11	(28.2)	1.57	[0.57–4.31]
Learning disability	16	(35.6)	17	(44.7)	1.47	[0.61–3.55]
Takes prescribed medications	31	(68.9)	20	(51.3)	0.48	[0.20–1.16]
Has regular source of healthcare	44	(97.8)	36	(92.3)	0.27	[0.03–2.74]
Careaivers
Single parentc	13	(32.5)	21	(53.8)	2.42+	[0.97–6.04]
Number of kids (<18) in household
One	10	(22.2)	15	(38.5)	Ref
Two	15	(33.3)	13	(33.3)	0.58	[0.19–1.72]
Three or more	20	(44.4)	11	(28.2)	0.37+	[0.12–1.09]
Education level
High school or less	11	(25.6)	15	(38.5)	Ref
Some college	19	(44.2)	18	(46.2)	0.69	[0.25–1.91]
College graduate	13	(30.2)	6	(15.4)	0.34+	[0.10–1.17]
Currently works for pay	34	(75.6)	21	(53.8)	0.38*	[0.15–0.95]
Among those who currently work	13	(30.2)	6	(15.4)	0.34+	[0.10–1.17]
Work hours	34	(75.6)	21	(53.8)	0.38*	[0.15–0.95]
Part-time (<35 hours/week)	9	(27.3)	8	(38.1)	Ref
Full-time (35+ hours/week)	24	(72.7)	13	(61.9)	0.63	[0.23–1.70]
Occupation typed
Professional/Executive	9	(28.1)	5	(23.8)	Ref
Administrative	7	(21.9)	2	(9.5)	0.62	[0.15–2.59]
Sales and related	2	(6.2)	4	(19)	2.00	[0.39–10.31]
Machine operators/laborers	3	(9.4)	0	(0)	0.33	[0.03–3.77]
Service	7	(21.9)	10	(47.6)	1.50	[0.43–5.25]
Unspecified/othere	4	(12.5)	0	(0)
Fair/poor health	6	(13.3)	15	(38.5)	4.06*	[1.39–11.90]
Depressionf	4	(8.9)	16	(41)	7.13**	[2.13 – 23.88]
Assets and debt
Household income
Poor (under 100% FPL)	7	(15.6)	18	(46.2)	Ref
Low income (100–199% FPL)	13	(28.9)	13	(33.3)	0.39	[0.12–1.24]
Middle to high income (≥200% FPL)	25	(55.6)	8	(20.5)	0.12***	[0.04–0.41]
Home ownership	22	(48.9)	7	(17.9)	0.23**	[0.08–0.62]
Has credit card	26	(57.8)	11	(28.2)	0.29**	[0.12–0.72]
Has (any) savings	25	(55.6)	12	(30.8)	0.36*	[0.14–0.87]
Has savings for 2 months of expenses	14	(31.1)	3	(7.9)	0.19*	[0.05–0.72]
Large drop in income in past 7 years	13	(29.5)	20	(51.3)	2.51*	[1.02–6.19]
Filed for bankruptcy in past 7 years	5	(11.1)	6	(15.4)	1.45	[0.41–5.20]
Formal safety net
Any cash assistance	15	(34.1)	26	(66.7)	3.87**	[1.55–9.63]
TANF	3	(6.7)	7	(17.9)	3.06	[0.73–12.78]
SSI/SSDI	14	(31.8)	26	(66.7)	4.29**	[1.71–10.75]
Any food assistance	21	(46.7)	35	(89.7)	10.00***	[3.05–32.83]
SNAP	10	(22.2)	23	(59)	5.03***	[1.95–13.00]
NSBLP	18	(40)	28	(71.8)	3.82**	[1.53–9.56]
Rental assistanceg	6	(13.3)	9	(23.1)	1.95	[0.63–6.08]
Medicaidh	23	(51.1)	31	(79.5)	3.71**	[1.40–9.80]
Disconnectedi	15	(33.3)	2	(5.1)	0.11**	[0.02–0.51]
Number of programs (Mean, SD)	3.2	(1.5)	1.6	(1.6)	1.84***	[1.34–2.52]
Informal safety net
Received money from family/friends	10	(22.2)	24	(61.5)	5.60***	[2.16–14.54]
Received housing from family/friends	3	(6.7)	6	(15.4)	2.55	[0.59–10.95]
Full supportj	35	(77.8)	18	(46.2)	0.24**	[0.10–0.63]
Access to $200	39	(86.7)	27	(69.2)	0.35+	[0.12–1.04]
Access to place to live	39	(86.7)	26	(66.7)	0.31*	[0.10–0.91]
Access to childcare	39	(86.7)	34	(87.2)	1.05	[0.29–3.74]
Large financial supportk	22	(48.9)	6	(15.4)	0.19**	[0.07–0.54]
Access to $1000	30	(66.7)	11	(28.2)	0.20***	[0.08–0.50]
Co-signer for $1000 loan	27	(60)	11	(28.2)	0.26**	[0.10–0.66]

ADHD, attention-deficit/hyperactivity disorder; CI, confidence interval; FPL, federal poverty level; NSBLP, National School Breakfast/Lunch program; OR, odds ratio; SNAP, Supplemental Nutrition Assistance Program; SD, standard deviation; SSI/SSDI, Supplemental Security Income or Social Security Disability Insurance; TANF, Temporary Assistance for Needy Families.

^aAt least one of the following hardship types: food, medical, housing, bill-paying, and utilities.

^bThe FFCWS used race and ethnicity equivalently.

^cVersus married or cohabitating; restricted to primary caregivers who were biological parents of the adolescent (N = 79).

^dBased on three-digit codes from the U.S. Bureau of Labor Statistics’ May 2016 Major Occupation Groups, as detailed in their Occupation Profile (https://www.bls.gov/oes/current/oes_stru.htm).

^eThis refers to categories with fewer than 10 cases, as defined by the FFCWS to maintain participant confidentiality, or when a response was either not provided or was unclear.

^fCaregivers met conservative estimate of diagnosis for major depression in the past year based on Major Depressive Episode questions from the Composite International Diagnostic Interview—Short Form (CIDI-SF), Section A.19.

^gReceipt of government help in paying rent, including public housing or Section 8 vouchers.

^hIncludes adolescents currently covered by Medicaid or another public program for medical care (e.g., Children’s Health Insurance Program (CHIP)).

ⁱDid not receive any of the six formal safety net programs (TANF, SSI/SSDI, SNAP, NSBLP, rental assistance, and Medicaid).

^j(Yes) to $200, a place to live, and access to childcare.

^k(Yes) to $1000 and cosigner for $1000 loan.

^***p < 0.001,

^**p < 0.01,

^*p < 0.05,

⁺p < 0.10.

Community involvement

The study was co-authored by an autistic researcher (N.A.), who participated heavily in the interpretation, drafting, and revision of the project.

Results

Demographics and health-related characteristics

Table 2 illustrates the distribution of demographics and health-related characteristics of adolescents and caregivers by autism status. Autistic adolescents were generally more likely to be male (81%) and white (35.7%) than their peers without autism. In addition, 26.2% of adolescents in the autism group were Hispanic/Latino, 35.7% were Black, and a small portion (2.4%) identified as Multicultural or belonging to other races. Autistic adolescents faced significant health challenges, with 60.7% requiring prescription medication. In addition, they were more likely than their non-autistic peers to have multiple diagnoses, including ADD/ADHD, depression, anxiety, and learning disabilities. Despite these health-related challenges, most (95.2%) autistic adolescents had access to a usual source of care, and none were uninsured. Due to the FFCWS sampling design overrepresenting unmarried births, the sample was more socioeconomically disadvantaged than point estimates presented in other population-based datasets. Notably, about 43% of autistic adolescents lived in single-parent homes and 31.7% of caregivers had an education of high school or less (Table 2). Over half (65.5%) of caregivers in the autism group were employed, with the majority holding full-time positions. The most common occupations among these caregivers included service and professional/executive roles, and administrative positions. Characteristics of caregivers were generally similar between groups, with the notable exception of depression, which was markedly higher among caregivers of autistic adolescents compared with those without autism.

Economic resources and material hardship

Table 3 reports economic resources and material hardships among families of adolescents with and without autism. Families were evenly distributed along federal poverty thresholds for both groups with 29.8% of autistic adolescents living in poor households, 31% living in low-income households, and the remaining 39.3% of living in middle- to high-income households.

Asset accumulation was low for both groups. Overall, less than half of families with autistic adolescents had access to savings or credit, and just over one-third of families owned their home. Income and assets were distributed similarly between groups, yet families with autistic adolescents filed for bankruptcy at almost double the rate of those without autism (13.1% vs 6.8%), likely because over one-third of these families faced a significant income drop.

In this study, the prevalence of any material hardship (46.4%) was higher than the prevalence of income poverty (29.8%) among families with autistic adolescents. The most common material hardships among families with autistic adolescents were bill-paying hardship (31%), followed by food insecurity (27.4%), and utility disconnection (21.4%). Medical and housing hardships were much less common. Although these patterns generally persisted for both groups, families with autistic adolescents reported significantly higher levels of food insecurity relative to families of adolescents without autism and were over twice as likely to forego medical care due to cost.

Formal and informal safety nets

Table 4 summarizes formal and informal safety nets. More than two-thirds (79.8%) of families with autistic adolescents received support from at least one of the following six formal safety net programs (TANF, SSI/SSDI, SNAP, NSBLP, rental assistance, and Medicaid). In terms of individual programs, Medicaid was the most common program among autistic adolescents with 64.3% receiving coverage, followed by the NSBLP (54.8%), SSI/SSDI (48.2%), SNAP (39.3%), rental assistance (17.9%), and TANF (11.9%). Despite having higher rates of food insecurity, families with autistic adolescents were no more likely to receive SNAP or NSBLP benefits than families of adolescents without autism. They were, however, much more likely to receive SSI/SSDI. That said, receivers’ SSI/SSDI benefit amount (in dollars) was, on average, less than those of adolescents without autism. The median annual payment amount among autistic SSI/SSDI recipients was $7350 (M =$6287, SD =$4371) relative to $7800 (M =$7840, SD =$7411) among recipients without autism (data not shown). This contrasts with national studies of working-age SSI recipients, which found higher annual payments among autistic adults relative to adults with intellectual disabilities or other mental health disorders (Anderson, Hemmeter, et al., 2020). Most families drew support from multiple safety net programs, regardless of autism status. Roughly half of all families with autistic adolescents participated in three or more formal safety net programs.

Families with autistic adolescents accessed the informal safety net at similar rates as other households: 40.5% of families received cash assistance from family or friends in the past 12 months and 10.7% received housing assistance. Most families with autistic adolescents could count on someone to lend them $200 (78.6%), to provide housing (77.4%), and to offer emergency childcare (86.9%) when necessary. Yet we found that families with autistic adolescents had lower perceived access to large financial support (i.e., ability to access $1000 and get a cosigner on a $1000 loan) than families of adolescents without autism.

Economic resources, material hardships, and safety net indicators by household income

Table 5 presents income-based differences in economic resources, material hardships, and safety nets between families of adolescents with and without autism. We found that one-third (33.3%) of autistic families in middle- to high-income households did not have any savings, 39.4% did not own their home, and 36.4% did not have access to a credit card. Roughly a quarter of these families reported some type of material hardship, and over one-third experienced a large drop in income. Despite these challenges, nearly half (48.5%) of middle- to high-income autistic families were disconnected from the formal safety net. We also found that autism-based differences in food insecurity were most pronounced among the poorest income category, with the proportion of autistic families experiencing food insecurity being more than twice that of families without autistic adolescents (60% vs 26.5%). Despite having higher levels of food insecurity, however, autistic families were not significantly more likely than non-autistic families to receive any formal food supports, at any income level.

Factors associated with material hardship

Table 6 displays the distribution of study variables, cross-classified by any material hardship, as well as unadjusted odds ratios from bivariate analysis. Overall, about 46.4% of families with autistic adolescents reported at least one material hardship in the past 12 months. Among them, the majority (more than 50%) were single parents, had two or more children, and currently worked for pay. Child demographics and health-related characteristics were generally not associated with material hardship. One exception was race and ethnicity, in which Black and Hispanic/Latino adolescents had over a four times greater likelihood of reporting any material hardship compared with white or Other adolescents. Caregiver health was also significantly associated with the odds of any material hardship among autistic families. The odds of any hardship were over four times higher among caregivers with fair or poor health and seven times higher among caregivers with depression relative to their counterparts with better health and no depression. Families with autistic adolescents experiencing any material hardship faced a different set of financial challenges compared with their counterparts with no material hardship, such as income poverty, limited assets, and perceived access to support from family and friends. For example, among families reporting material hardship, 46.2% had incomes below the poverty line, and 33.3% earned between 100% and 200% of the FPL. In contrast, 44.5% of families without reported hardship had incomes below 200% of the FPL. Although material hardship primarily affected poor and low-income families, about one in five middle- to high-income families also experienced some form of hardship. Access to savings or credit and homeownership were significantly associated with reduced hardship, while large drops in income significantly increased the risk of hardship. Likewise, formal and informal safety net use significantly increased the odds of material hardship whereas perceived support from friends and family reduced them. All indicators of formal and informal safety net receipt yielded medium to large effect sizes in unadjusted analyses.

Discussion

This exploratory descriptive study highlights significant disparities in financial well-being outcomes among families with autistic adolescents, revealing the limitations of formal safety net programs in addressing their comprehensive needs. Our findings indicate that while formal safety nets effectively address healthcare needs for autistic adolescents, they fall short in meeting broader social needs. Despite high insurance coverage and minimal disparities in healthcare access, families with autistic adolescents faced substantial material hardships. Consistent with findings from previous research (Karpur et al., 2021, 2022; Tahech et al., 2023), food insecurity was notably higher among autistic families compared with non-autistic ones, despite similar access to formal food assistance programs like SNAP and NSBLP. This discrepancy is alarming, as such programs have been proven to alleviate poverty and food insecurity in general child populations (de Cuba et al., 2019; Rogers et al., 2022; Sonik et al., 2023). Furthermore, the most significant disparities in food insecurity appear within the lowest income brackets, where nearly all families utilize food assistance. This persistent vulnerability highlights a significant gap in the effectiveness of existing programs and suggests a pivotal opportunity to optimize formal safety nets. By improving how these programs identify and address the specific needs of high-risk families, particularly those with autistic adolescents, we can enhance their impact, ensuring interventions are not only accessible but also finely attuned to the unique challenges these families face.

Our study found significant financial instability in families with autistic adolescents, who faced a higher likelihood of substantial income drops and were almost twice as likely to declare bankruptcy compared with families with non-autistic adolescents. Challenges uniquely exacerbated by the demands of autism care, including employment disruptions and high service expenditures, may contribute to the greater risk of experiencing substantial income drops and increased likelihood of bankruptcy, especially for single-parent households (McAuliffe et al., 2017). Despite these challenges, these families reported less access to liquid assets, such as the ability to secure loans or cosigners, compared with their counterparts. This economic volatility underscores the critical need for policies focused on asset accumulation and strengthening informal support networks to better support these families’ financial stability. Interestingly, while high food insecurity remains a severe issue, families with autistic adolescents do not face greater risks regarding bill-paying and utility hardships compared with other families. This difference may be linked to the higher rates of SSI/SSDI receipt among autistic adolescents compared with those without autism, despite families of autistic adolescents receiving lower annual payments than their non-autistic counterparts. However, the high prevalence of food insecurity amid low bill-paying hardships suggests a targeted need for programs specifically enhancing food access.

The study also highlights the compounded effect of race, ethnicity, and family structure on hardship within autistic families. Our findings indicate that adolescents from single-parent and minority backgrounds face increased risks of material hardship, exacerbated by systemic reliance on safety net programs. These findings mirror those presented in other research studies of children with disabilities (Parish, Rose, et al., 2008) and have also been shown to predict other financial indicators. For instance, results from nationally representative samples of autistic children reveal that children from single-parent households and from minority backgrounds are more likely to live in low-income households and to report higher rates of formal safety program use than their counterparts (Anderson, Rast, et al., 2022; Anderson et al., 2023). Single parents of autistic children are also much more likely to feel the impact of reduced employment than their married counterparts (Brewer, 2018; Gnanasekaran et al., 2016; McAuliffe et al., 2017). The compounded effects of race, ethnicity, and single parenthood intensify material hardships among families with autistic adolescents, highlighting the critical need for safety net programs to refine their targeting mechanisms to better serve these vulnerable groups. Future research could investigate how race, ethnicity, and family structure combine with household income to affect financial well-being outcomes among autistic adolescents and their families.

In addition, caregiver depression’s significant correlation with material hardship emphasizes the necessity for integrated support that addresses both economic stability and mental health, although our use of cross-sectional data does not provide insight into the direction of the relationship. Previous research points to a bidirectional relationship where financial strain can exacerbate mental health issues and vice versa (Fuller et al., 2024; Heflin & Iceland, 2009; Parish, Magaña, et al., 2008). On one hand, financial insecurity can impair a caregiver’s ability to manage stress, leading to potential social isolation and depression. This can also erode self-esteem and sense of control, further exacerbating hardship. Conversely, depression can reduce a caregiver’s job performance due to symptoms like fatigue and decreased concentration. The risk of employment disruptions and reduced work hours is especially high among parents of children with disabilities due to intensive caregiving demands, directly impacting their income and increasing financial strain, a known risk factor for depression (Bourke-Taylor et al., 2011; Cidav et al., 2012). In addition, the emotional and physical toll of caregiving can heighten stress levels, potentially leading to depression, while the extensive effort required to navigate health care and special education systems can add to this stress (Cohrs & Leslie, 2017; Parish, Magaña, et al., 2008). This cyclical relationship underscores the need for integrated support addressing both mental health and economic stability. Future research employing longitudinal data and advanced modeling could elucidate the complex interactions between caregiver health and financial well-being, guiding more effective interventions.

Finally, our study demonstrates that reliance solely on income-based measures may misrepresent the resources available to families to get their basic needs met and prohibit the adequate identification of financially disadvantaged groups. Notably, families in our study drew from a wide range of resources, including government programs and social supports, and there were many instances in which income-poor families had assets like home ownerships, credit card access, and savings. Likewise, many middle- to high-income households reported hardship and limited assets in our study. Despite having higher income, middle- to high-income families may experience elevated needs, elevated costs for care, and reduced work hours and earnings. Further, we found that many higher-income households of autistic adolescents had limited access to formal safety net programs to counterbalance the increased demands on their time and resources. The broad array of resources that income-poor families might possess coupled with the presence of hardship among families with higher income suggests that current measures may not fully capture the nuances of financial well-being. These findings also indicate that means-tested eligibility criteria might not be the best metric to establish the need for safety net benefits among families with adolescents with autism. Expanding our understanding of financial well-being allows for a deeper grasp of the unique challenges autistic families face and improves interventions like SNAP. Our study underscores the need for more focused research that explores specific types of material hardship and calls for future studies to examine these distinctions more closely.

Our study provides novel insights into the financial well-being of autistic adolescents and their families, shedding light on potential risk factors for material hardship. Notably, the FFCWS dataset offers more detailed data on financial needs and safety nets than other population-based datasets, making it particularly well-suited for these analyses. Despite the valuable insights gained from this study, several limitations must be acknowledged, which may affect the generalizability and comprehensiveness of our findings. First, due to our cross-sectional design and focus on bivariate relationships, we cannot establish causal relationships between variables, nor can we determine the duration or depth of key measures (like material hardship). Second, the reliance on self-reported data introduces the potential for response bias, inaccurate respondent perceptions, and common method variance (Campbell & Fiske, 1959). Third, our analyses of differences in material hardship among families with autism were based on a composite measure (at least one reported material hardship), which, while a useful starting point, may obscure important distinctions among various challenges that families face. Fourth, our analysis differentiated households based on the autism status of the focal child; data about siblings or other household children were not available. Furthermore, the significant gender imbalance in our sample, with a preponderance of boys, may limit the representativeness of our findings to the broader autistic population, as it does not adequately capture the experiences and challenges faced by autistic girls, whose conditions and needs might differ. Finally, due to data limitations, our evaluation of safety net programs is not exhaustive and excludes certain in-kind assistance programs, such as energy assistance. These limitations point to the need for future research that accounts for confounding effects, validates reported safety net receipts, examines risk factors for specific material hardship domains separately, and incorporates a broader range of safety net measures and interventions.

Conclusion

This study highlights significant disparities in the financial well-being and material hardship experienced by families with autistic adolescents, revealing a notable inefficacy in formal safety net programs to adequately address their unique social and financial challenges. This study highlights the urgent need for a comprehensive understanding of financial well-being that extends beyond income, emphasizing the significance of assets, material hardships, and safety nets in shaping the quality of life for autistic adolescents and their families. Our findings support a multidimensional approach to assessing financial well-being to inform more effective policy and practice. By broadening the scope of what constitutes financial well-being and dissecting different types of material hardships, we can better understand and address the specific challenges faced by families with autistic adolescents.