Abstract

A growing proportion of individuals adopt family caregiving roles. Family caregivers are the primary providers of long-term care in the United States yet limited federal policy supports exist, despite the known negative impacts of caregiving. There is also limited information about the prevalence of youth/young adult caregivers and the impacts of caregiving at formative ages in the United States. Our objective is to estimate the prevalence of youth caregivers and examine the association of caregiving with educational investments. We use the American Time Use Survey (2013–2019) to identify and describe youth caregivers (aged 15–18) and young adult caregivers (aged 19–22) and compare them with non-caregiving peers. We estimate that there are approximately 1,623,000 youth caregivers and 1,986,000 young adult caregivers, corresponding to 9.2% and 12.7% of these age groups, respectively. However, there is a wide range in the estimated prevalence per year, from approximately 364,000 to 2.8 million youth caregivers and from 353,000 to 2.2 million young adult caregivers, depending on caregiver definition. Unlike adult caregivers, we find that young men and women were nearly equally likely to provide care. We also find that non-White individuals are disproportionately represented as youth caregivers. Compared with non-caregiving peers, both youth and young adult caregivers are less likely to be enrolled in school and, among those enrolled in school, spend significantly less time on educational activities. Considering the association of caregiving among youth/young adults and education, policies supporting youth and young adult caregivers are critical.

Introduction

A growing proportion of individuals provide unpaid care to family members and friends (i.e., are family caregivers) (AARP and National Alliance for Caregiving 2020; Schulz and Eden 2017). By 2050, projections indicate that 10% of individuals aged 20–64 will be providing care to an older adult (Mudrazija 2019). Caregivers perform a myriad of activities, including, but not limited to, assistance with activities of daily living (e.g., bathing, eating), instrumental activities of daily living (e.g., shopping, medication management), and supervision or support (AARP and National Alliance for Caregiving 2020; Schulz and Eden 2017). Family caregiving is associated with adverse outcomes that persist over time, such as worse mental and physical health, employment instability, social isolation, and greater financial burden (Bom et al. 2019; Heger 2017; Schmitz and Westphal 2015; Schulz and Eden 2017; van den Berg et al. 2014; Van Houtven et al. 2013).

Caregiving among youth 18 or younger and young adults aged 19 to 22 has been understudied in the United States (Armstrong-Carter et al. 2021; Joseph et al. 2020; Kavanaugh et al. 2016; Levine 2017). Much of the evidence on youth caregiving in the United States has been collected from small or nonrepresentative samples (Cohen et al. 2012; Greene et al. 2017; Shifren 2001). Currently, two national surveys provide prevalence estimates for the number of youth caregivers: a survey specifically of youth caregivers in 2005 led by the National Alliance for Caregiving and a national survey of adults led by AARP in collaboration with the National Alliance for Caregiving to estimate the prevalence of caregiving in the United States, which includes a question about whether the adult received assistance from youth in providing care, from which the expected number of youth caregivers was extrapolated. Both surveys provide insight into the prevalence and role of youth as caregivers but capture limited information about who youth caregivers are and their caregiving activities (AARP and National Alliance for Caregiving 2020; National Alliance for Caregiving 2005). Caregivers who are 18 or younger are largely excluded from existing national surveys; these surveys allow caregivers to self-report their activities and are often used to inform policy support for caregivers (e.g., National Study of Caregiving; Health and Retirement Study) (M. Skehan, personal communication, May 26, 2022; Weir 2018). The limited estimates of the prevalence of youth/young adult caregivers and their characteristics highlight the need for high-quality, national prevalence estimates to better understand the scope of youth caregiving and to provide responsive policy and targeted programmatic support for affected individuals and families.

Given that the adverse effects of family caregiving observed among adults are well-established, it is critical to understand who is adopting caregiving roles across the life course. Youth/young adults who provide caregiving are doing so during a formative time for human capital investment, namely, their current and future schooling choices and achievement. Yet, the relationship between youth caregiving and schooling is unknown. If family caregiving negatively impacts their educational attainment and early employment, then there may be cumulative or exponential impacts on long-term economic well-being as the potential for lost wages over the life course may lead to earnings and wealth gaps attributable to family caregiving responsibilities (le Grand and Tåhlin 2002; Tamborini et al. 2015). The limited evidence on youth caregivers in the United States suggests that a greater proportion of younger caregivers, compared with older caregivers, are male, non-White, or Hispanic (National Alliance for Caregiving 2005). The interaction of systemic racism and potential adverse effects of youth caregiving may contribute to intergenerational health and economic inequities (Dean and Thorpe 2022). Notably, the division of family labor such as caregiving is typically gendered, with adult women disproportionately bearing the burden of caregiving and incurring the subsequent adverse economic consequences as a result of a range of nonexclusive reasons, including, but not limited to, familial responsibilities, personal preference, employment opportunities (or lack thereof), and financial constraints. However, evidence to date has primarily focused on this gender division in adults (Altintas and Sullivan 2017; England 2005; Folbre 2012; Glenn 2010; Grigoryeva 2017; Schulz and Eden 2017). Understanding who adopts family caregiver roles, the intensity of caregiving (e.g., time spent caregiving and types of tasks performed), and the association of caregiving with educational outcomes is a necessary precursor to examining long-term effects of caregiving and developing targeted caregiver supports.

Our objectives are to estimate the prevalence and characteristics of youth/young adult caregivers of adults and to examine differences in educational attainment and daily activities associated with caregiving. Using the American Time Use Survey (ATUS), we first estimate the numbers of caregivers aged 15–18 (hereafter referred to as youth caregivers) and aged 19–22 (hereafter referred to as young adult caregivers) and describe their time spent caregiving. We then describe the demographic characteristics of caregivers and their non-caregiving peers. Finally, we examine differences in school enrollment and time spent on education, work, socialization, and leisure among youth/young adult caregivers and their non-caregiving peers. We identify youth caregivers from their self-reported caregiving activities in a national sample, which does not require parental consent. Thus, our prevalence estimates of youth caregivers overcome prior estimates’ methodological limitations and provide key context about youth/young adult family caregivers in the United States.

Methods

Data and Sample

We employ two publicly available datasets. First, we use the Integrated Public Use Microdata Series (IPUMS) of ATUS for the years 2013–2019 (Flood et al. 2022). ATUS is administered over the phone in English or Spanish by the Census Bureau to collect a 24-hour time diary for each respondent. The diary captures the mix of time spent on various activities, such as working, socializing, providing care to children, and providing care to adults. For each activity reported, respondents describe the secondary activities, the time activity began and ended, the location, and who (if anyone) was also present during the activity. Respondents to ATUS must be at least 15 years old and living in the community; institutionalized and active military individuals are excluded. ATUS respondents are sampled from households who have completed the eighth survey in the Current Population Survey, in which households are surveyed for up to eight months. ATUS survey weights yield nationally representative estimates of how individuals aged 15 or older in the United States spend their time. Second, we link the ATUS to the eighth-month household survey in the Current Population Survey to capture additional household economic and social characteristics.

Definition of Caregivers of Adult(s)

Given the paucity of data on youth/young adult caregivers, we examine four primary definitions of a caregiver of adult(s) that are based on (1) the provision of assistance with activities of daily living (ADLs; e.g., bathing, assisting with medication, supervision) and with instrumental activities of daily living (IADLs; e.g., helping with managing finances, errands, shopping); (2) time spent providing care; and (3) whether caregiving is provided in response to a condition(s) related to aging.

We define caregivers of adults as individuals who report time spent:

  1. 1.

    Providing any assistance with ADLs/IADLs to adult(s).

  2. 2.

    Providing at least 15 minutes on average per day of assistance with ADLs/IADLs to adult(s).

  3. 3.

    Providing at least 30 minutes on average per day of assistance with ADLs/IADLs to adult(s).

  4. 4.

    Providing care or assistance (excluding financial assistance) to an adult because of a condition related to aging. Care includes assistance with activities such as driving, grooming, and taking medicine(s) that could be provided in the caregiver's home, recipient's home, or a care facility.

Notably, all definitions exclude household activities that are independent of assisting the adult (i.e., chores), as well as caregiving only for children. See online Appendix A for a complete list of activity codes and survey questions corresponding to each definition.

Demographic and Economic Characteristics

We describe the demographic and economic characteristics of youth/young adult caregivers of adults and of their non-caregiving peers. Specifically, we examine age, sex, race (White race or Black/African American, American Indian/Alaska Native, Asian, other races, multiple races), Hispanic ethnicity, marital status, highest level of education (less than 12th grade; 12th grade completed/GED; some college or associate's/vocational, bachelor's, or graduate degree), enrollment in school, rural residence, employment status (employed versus not), household size, year of survey, and household number of children. Household covariates (size and income) are drawn from the final Current Population Survey interview as harmonized by IPUMS.

Time-Use Measures

We examine time use of individuals aged 15–22 across multiple domains: caregiving; education; working; leisure; and organizational, volunteer, and religious activities. For all but caregiving, we used activity codes aligned with the Bureau of Labor Statistics definitions. See online Appendix B for a complete list of activity codes for each domain.

Time spent caregiving includes time spent on all activities used to define being a caregiver, as described earlier. See online Appendix A for a complete list of related activity codes.

Time spent on educational activities includes time attending classes, completing homework, conducting research, completing administrative tasks, and participating in extracurricular activities, except sports.

Time spent on work-related activities includes time at work, searching for jobs and interviewing, and any income-generating activities that are not included in the job description. Work-related activities could include self-employment and side businesses.

Time spent on leisure includes activities such as relaxing, socializing, sports, exercise, recreation, playing computer/card/board/video games, watching television, or recreational reading.

Time spent on organizational, civic, and religious activities includes religious and volunteer activities as well as civic obligations.

Statistical Analysis

First, we generate estimates of the average number of youth and young adult caregivers across all sample definitions by applying person-level survey weights to generate average national estimates from 2013–2019. Because the existing survey weights for ATUS yield nationally representative weights for the average number of minutes spent per day per person, we calculate person-level weights by dividing the weights for time-use variables by the number of days in a reported period to yield the weight per person (Bombyk 2022). To calculate the average number of caregivers per year, we divide the total number of estimated caregivers by the number of years of data observed (seven years). Second, we describe the demographic and household characteristics of youth/young adult caregivers providing assistance with ADLs or IADLs and their non-caregiving peers for context. Given the lack of data about youth caregivers to date, we present results using the definition of youth who provide any assistance to an adult with ADLs or IADLs. Third, we describe time spent on education, work, leisure, and socialization in the sample of caregivers and their non-caregiving peers. Finally, we estimate the association of being a caregiver with the probability of enrollment in school and time spent on education, work, leisure, and religious, volunteer, and civic activities.

For each outcome among each age group (15–18 and 19–22), we run two regressions, with the first including a binary indicator for providing assistance with ADLs or IADLs and the second including two binary indicators, one for providing assistance with ADLs and one for IADLs to tease out the differential effects of type of assistance, as shown in Eqs. (1) and (2). We use negative binomial regression to estimate time-use outcomes and logistic regression to estimate enrollment in school and calculate the differential association of being a caregiver using the method of recycled predictions. All descriptive and regression analyses include replicate weights to yield corrected standard errors adjusting for complex survey design. All regression models include covariates for sex, race, Hispanic ethnicity, marital status, rural residence, household size interacted with family income, number of children in the household, year of survey, weekend day, summer month (May–July), and region (represented as Xi in Eqs. (1) and (2)):
Yi=β1ADLorIADLCaregiveri+β2Xi+εi
(1)
Yi=β1ADLCaregiveri+β2IADLCaregiveri+β3Xi+εi.
(2)

Sensitivity Analysis

We conduct multiple sensitivity analyses. First, we examine educational outcomes among caregivers across all definitions of youth caregiver. Second, we consider educational outcomes among caregivers aged 15–17 and their non-caregiving peers across caregiver definitions to elucidate whether the effects on educational outcomes are driven by 18-year-old individuals who have completed high school and have not started college. Third, we examine educational outcomes among caregivers while adjusting for maximum year of required attendance for schooling (i.e., compulsory attendance laws) using data from 2017 as compiled by the National Center for Education Statistics (2018). Fourth, we conduct all analyses using Poisson regression. Finally, we examine all outcomes after excluding interviews conducted during the summer months.

Results

Estimated Prevalence

On average per year, we estimate that the number of youth caregivers aged 15–18 ranges from approximately 364,000 to 2.8 million and the number of young adult caregivers aged 19–22 ranges from 353,000 to 2.2 million, depending on the definition of caregiver. The estimated number of caregivers providing assistance with ADLs or IADLs to adults, on average per year, is approximately 1,623,000 youth and 1,986,000 young adult caregivers, corresponding to approximately 9.2% and 12.7% of the sample in these age groups, respectively (Table 1).

Descriptive Statistics

Youth caregivers aged 15–18 are more likely than their non-caregiver peers to be female and non-White (Table 2). Twenty-seven percent of such caregivers are not enrolled in full-time or part-time school, compared with 18% of non-caregiving peers.

Among individuals aged 19–22, caregivers are less likely to be employed (63% vs. 67%) or enrolled in full-time or part-time school (42% vs. 46%) than non-caregivers.

Time Use of Caregivers

When examining time use among individuals aged 15–18, youth caregivers spend approximately 25 minutes per day providing care. Youth caregivers spend fewer minutes on educational and work activities and more time on leisure activities relative to their non-caregiving peers (Figure 1). Among 15–18-year-olds enrolled in full-time school, caregivers spend approximately 42 and 31 fewer minutes on educational activities and time in class per day, respectively, compared with their non-caregiving peers.

Similar trends were seen among individuals aged 19–22 (Figure 1). Young adult caregivers spend approximately 26 minutes per day providing care. These caregivers spend approximately 38 fewer minutes on educational activities per day than their non-caregiving peers. Among 19–22-year-old individuals enrolled in full-time school, caregivers spend approximately 71 and 15 fewer minutes on educational activities and time in class per day, respectively, compared with their non-caregiving peers. See online Appendix C for a complete table of time-use descriptive statistics by caregiver status.

Association Between Caregiving and Education

Compared with non-caregiving peers, caregivers are less likely to be enrolled in school full-time after adjusting for demographic, regional, and economic characteristics. The same is true for time spent on educational activities among those enrolled full-time. Panels a and b of Figure 2 show the predicted outcomes for non-caregiving youth and youth providing assistance with ADLs and IADLs. Table 3 provides the corresponding differential associations of providing ADL or IADL care, ADL care only, and IADL care only. Among 15–18-year-olds, caregivers have lower predicted probability of being enrolled full-time than non-caregiving youth, and this is consistent across the type of care provided (Figure 2, panel a). For this age group, being a caregiver is associated with an 8.1-percentage-point decrease in the probability of being enrolled in school full-time or part-time (p < .001), after controlling for all other variables in the model. Providing ADL assistance is associated with a 13.9-percentage-point decrease in enrollment probability, while providing IADL assistance is associated with a 7.0-percentage-point decrease (p < .001). Among youth enrolled full-time, being a caregiver is associated with spending 44 fewer minutes on educational activities per day (p < .001; panel b). Among those enrolled full-time, providing ADL assistance is associated with 50.7 fewer minutes on educational activities (p < .05) while providing IADL assistance is associated with 43 fewer minutes (p < .05).

Results are robust when restricting the sample to individuals younger than 18 and robust across multiple definitions of caregiving. Conditional on the definition of caregiving, we find that being a youth caregiver is associated with a decrease of 2.4–11.4 percentage points in the probability of being enrolled in school (p < .05) and with 22–89 fewer minutes spent on educational activities (p < .05). Results are also consistent after adjusting for maximum year of required attendance for schooling (i.e., compulsory attendance laws), when using Poisson regression instead of negative binomial, and after excluding interviews conducted during the summer months. See online Appendix D for complete results from all models.

Among individuals aged 19–22, the predicted probability of being enrolled in school and predicted time spent on education varied by whether an individual provided help with ADLs or IADLs. Panels c and d of Figure 2 show the predicted outcomes for non-caregiving youth and young adult caregivers. Table 4 provides the corresponding differential associations of providing ADL or IADL care, ADL care only, and IADL care only. In this age group, being a caregiver providing assistance with ADLs only is associated with an 11.7-percentage-point decrease in the probability of being enrolled in school (p < .05). Among those enrolled full-time, providing assistance with ADLs or IADLs is associated with spending 78 fewer minutes on educational activities overall compared with non-caregiving peers (p < .001). Providing ADL assistance only is associated with 78.8 more minutes on educational activities, while providing IADL assistance only is associated with 94.6 fewer minutes (p < .05). The difference in time spent on education, conditional on full-time enrollment, among ADL versus IADL caregivers is statistically significant.

Association Between Caregiving and Employment

Among individuals aged 15–18, being a caregiver is associated with 10 fewer minutes per day on work-related activities compared with non-caregiving peers (p < .05). Among those aged 19–22, being a caregiver is associated with 44 fewer minutes per day on work-related activities compared with non-caregiving peers (p < .001).

Association Between Caregiving and Social Activities and Leisure

When examining time spent on religious, volunteer, civic, and leisure activities, we find mixed results. Among 15–18-year-olds, being a caregiver is associated with nearly 7 more minutes per day spent on such activities; providing assistance with ADLs is associated with a larger decrease in time spent socializing relative to caregivers providing IADL help. We also find an increase of 33 minutes per day in time spent on leisure activities (p < .001). Among those aged 19–22, being a caregiver is not associated with time spent on leisure or religious, volunteer, and civic activities.

Discussion

We estimate that there are approximately 1.6 million youth caregivers and nearly 2.0 million young adult caregivers in the United States per year over the period 2013–2019. For context, our estimates of youth and young adult caregivers correspond to 9% and 13% of these age groups, respectively, while an estimated 19% of adults in the United States provide care to an adult for health or functional needs (AARP and National Alliance for Caregiving 2020). We also find that non-White youth are more likely to be caregivers than individuals of other races, and that youth caregivers spend substantially less time in educational activities than their non-caregiving peers; the last finding holds across multiple definitions of caregiver. This investigation is the first nationally representative study based on self-reported activities to estimate the prevalence of youth caregiving for adults and to examine the relationship between caregiving and educational involvement. These results collectively raise questions about the role of children as caregivers and the implications for their future economic and health outcomes.

Our findings contribute prevalence estimates of youth and young adult caregivers of adults. We expand on existing evidence by using a general public survey on time use that includes those younger than 18. Given the paucity of data defining optimal thresholds for time spent caregiving to identify youth caregivers, we present a range of estimates. Our estimated prevalence of youth caregivers is higher than that in the 2005 report released by the National Alliance for Caregiving, which estimated approximately 1.3–1.4 million caregivers divided evenly among individuals aged 8–11, 12–15, and 16–18 (Levine 2017; National Alliance for Caregiving 2005). This difference could reflect how youth caregivers are identified or changes in the number of such caregivers over time. Our results are not directly comparable with the more recently estimated 5.4 million youth caregivers from the Caregiving in the United States 2020 report, as their estimate includes no age bounds (i.e., individuals could be younger than 15) (AARP and National Alliance for Caregiving 2020). Future work is needed to examine the trends in the prevalence of youth caregivers over time to understand if the share of youth providing care is growing, decreasing, or remaining constant in the United States. For example, our estimates may be undercounting youth/young adult caregivers in more recent years because the COVID-19 pandemic increased disability and comorbidities and decreased nursing home use (Al-Aly et al. 2021; Briggs and Vassall 2021; Logue et al. 2021; National Institute for Health and Care Research 2020). In 2020, school enrollment rates for children and college enrollment precipitously decreased in the United States (U.S. Census Bureau 2021). Future research should assess whether some youth/young adults who left school during the pandemic adopted family caregiving roles, as well as explore caregiving to other children in the household; an increase in the latter may further exacerbate existing health and economic disparities.

We also find important differences in demographic characteristics among youth/young adult caregivers relative to their non-caregiving peers. Unlike adult caregivers, young men and women are nearly equally likely to provide care, and non-White individuals are disproportionately represented as youth caregivers, similar to what was found in research on youth/young adult caregivers in international settings (Di Gessa et al. 2022; King et al. 2021; Xue et al. 2024; Xue et al. 2023). The lack of a sex divide in caregiving in this sample may reflect generational changes, birth order (with the oldest child taking on caregiving tasks), or lack of care alternatives, such that the need for caregiving overrides typical gender norms. For example, we find that youth caregivers report 1.5 children in the household on average, which may include the caregiver; this is aligned with the declining family size in the United States. The smaller number of children in the household obviously results in fewer potential caregivers for adults requiring care. Notably, the division of labor in eldercare is informed by the gender of the caregiver, the gender of any siblings of the caregiver, and the gender of the individual receiving care (Grigoryeva 2017). Thus, we may expect to observe gender inequities among larger families, but we may also observe differences in caregiving when taking into account the gender of the care recipient and siblings of the caregiver. Moreover, it is notable that even if men and women are equally likely to become caregivers, inequities in time investment and care activities may exist (Altintas and Sullivan 2017; England 2005; Folbre 2012; Glenn 2010). Consider the case of childcare: approximately 40% of men provide any childcare, but they spend less time providing such care than women (Altintas and Sullivan 2017). Similarly, unlike evidence from adult caregivers, we find few youth and young adult caregivers providing both ADL and IADL assistance, but rather ADL or IADL assistance. Future research is needed to explain families’ needs and experiences that may drive these findings.

While we do not present causal estimates owing to insufficient information to address selection into caregiving or to match caregivers with non-caregivers, the magnitude of the associations between being a caregiver and decreased school enrollment and time spent on school suggests impaired long-term economic and health consequences for these youth caregivers. We find that youth caregivers are 8 percentage points less likely to be enrolled in school than non-caregiving peers, and this significant, negative association persists when using more conservative definitions of a caregiver. Among youth and young adult caregivers enrolled in school, they spend less time on work and educational activities. To place our findings in context, 44 fewer minutes spent on education per day for those enrolled in school corresponds to 15.5% less time spent on education than non-caregiving peers or missing 11% of the standard in-school time each day, assuming 6.64 hours per school day. Lower educational attainment, such as disenrolling from high school or forgoing higher education, is strongly associated with negative effects on employment and lifetime earnings and worse long-term health outcomes, including increased mortality (De Ridder et al. 2013; Lleras-Muney 2005). Notably, young adults who provide ADL assistance spend more time on educational activities, while youth caregivers spend more time socializing. Collectively, these findings are notable given that caregiving by older adults is associated with adverse mental health, physical health, and economic outcomes, and young adult caregiving is associated with worse mental health outcomes (Arora and Wolf 2014; Bom et al. 2019; Grenard et al. 2020; Heger 2017; Schmitz and Westphal 2015; Schulz and Eden 2017; van den Berg et al. 2014; Van Houtven et al. 2013). Adverse outcomes, such as lower educational levels, associated with caregiving among youth/young adults may influence their short- and long-term outcomes. Therefore, caregiving acts as a structural barrier to their well-being. Overall, these findings highlight a critical need to develop and implement targeted policies to support youth/young adult caregivers to mitigate the potential adverse effects on long-term economic and health outcomes.

This analysis is subject to several limitations. First, because of the small sample size, we cannot examine how the prevalence of youth caregivers has changed over time or the level of detail of the demographic information, even after pooling multiple years of data. Thus, we are only able to derive average estimates over pooled years of data. Second, we can only compare White and non-White races and Hispanic and non-Hispanic ethnicities, which can mask important differences among historically marginalized populations. However, this remains a useful first step in documenting characteristics of youth/young adult caregivers. Our findings demonstrate the need to assemble larger samples for further study. Third, we are unable to determine how long an individual has been a caregiver or to whom. A higher proportion of 19–22-year-olds relative to 15–18-year-olds may have a sibling with a disability who is over 18, which may impact who is identified as a caregiver. We focus on youth caregivers providing care to individuals aged 18 or older and do not examine youth providing care to siblings with disabilities who are younger than 18. An important consideration for future research is to expand on the understanding of youth caregivers’ experiences and roles across different definitions of care recipients. Fourth, there is no single agreed-upon definition of caregiving or threshold for identifying youth/young adults as caregivers, thus we report a range of estimates of caregivers with varied definitions based on their reported time use. Fifth, measurement error in self-reported time diaries may exist with respect to caregivers versus non-caregivers, but also between youth and young adults. Relatedly, it is ambiguous whether home-schooled children are captured as enrolled in school, but this is unlikely to be a dominant factor given the low percentage of students who are homeschooled (e.g., 2.8% in 2019) (National Center for Education Statistics 2022). However, we still find reductions in time spent on school regardless of school enrollment. Finally, we examine data prior to the COVID-19 pandemic. The COVID pandemic could be increasing caregiving among youth and young adult populations disproportionately. However, because of small sample size, we are unable to reliably estimate youth caregivers in 2020.

Family caregivers are the primary providers of long-term care in the United States. Yet family caregivers of all ages have been widely neglected by systematic federal policy supports despite the fact that the Centers for Disease Control and Prevention recognized caregiving as a public health concern in 2019. Moreover, the increased focus on moving health care to home- and community-based settings may have unintended consequences in increasing burden on family caregivers (Konetzka 2014). The few existing policies for caregivers exclude family caregivers younger than 18. For example, the Pennsylvania Caregiver Support Program and California Family Caregiver Services only allow family caregivers aged 18 or older to receive respite, training, and financial assistance (California Department of Aging n.d.; Pennsylvania Department of Aging n.d.). Additionally, little research in the United States has documented the experiences and needs of youth caregivers, thereby preventing the development and implementation of responsive policies. Moreover, the existing quality of care provided by youth caregivers and their potential training needs are unknown. While traditional interventions of support, for example, respite through home- and community-based services, may be helpful, the needs of youth/young adult caregivers and their families may differ from the needs of spouses or adult children caring for an aging parent. Similarly, to ensure high-quality care for care recipients, policies expanding training and support to youth caregivers are needed. The overarching lack of a comprehensive long-term care system in the United States, combined with the exclusion of youth caregivers from existing policy supports and most caregiving research, renders children adopting caregiving roles particularly vulnerable to adverse effects of caregiving with little to no evidence-based interventions to mitigate any negative caregiving effects.

The United States has limited systematic support for family caregivers of any age. Caregivers who are younger than 18 have been excluded from the few existing policies that support caregivers. Considering the potentially negative long-term and sweeping effects of caregiving, which may compound during the life course for youth, understanding the causal pathways of caregiving and educational attainment and future earnings, as well as positive aspects of caregiving, is necessary to inform policies to minimize negative outcomes for youth caregivers. Additional data and future research are critical to better understand the experiences and needs of youth and young adult caregivers and their families to inform policy and create novel structural supports for affected individuals and families.

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