The Experiences of Older Youth in and Aged Out of Foster Care

The Experiences of Older Youth in and Aged Out of

Foster Care During the COVID-19 Pandemic:

Material and Financial Well-Being by Foster Care

Status, Gender Identity, Sexual Orientation,

Ethnicity, and Race

Johanna K. P. Greeson

1, 2

, John R. Gyourko

1, 2

, Sara R. Jaffee

2, 3

, and Sarah Wasch

School of Social Policy & Practice, University of Pennsylvania

The Field Center for Children’s Policy, Practice, and Research, University of Pennsylvania

Department of Psychology, University of Pennsylvania

As a marginalized, underresourced population, older youth with foster care experience are

acutely vulnerable to the economic and social harms wrought by coronavirus disease 2019

(COVID-19). This study summarizes ﬁndings from an online survey deployed in April 2020 to

learn about the experiences of current and former foster youth (ages 18–23) during 1 month of

the COVID-19 crisis. Using snowball sampling and a cross-sectional design, the survey yielded

a ﬁnal analysis sample of 281 respondents from 32 states and 192 cities or districts. Findings

underscore the pervasive negative impacts of COVID-19 on respondents’ housing/living

situations, food security, employment, and ﬁnancial stability. Chi-square tests and post hoc

analyses revealed demographic disparities in respondents’ experiences during COVID-19.

Youth who aged out of care, cisgender females, nonstraight youth, and non-White youth were

signiﬁcantly more likely than demographic counterparts to experience pandemic-related

adversities. Implications for policy and practice are discussed.

Public Policy Relevance Statement

Older adolescents and young adults with foster care experience are at greater risk of poor

outcomes in early adulthood as compared to their peers in the general population. The

coronavirus disease 2019 (COVID-19) pandemic has exacerbated these risks for current and

former foster youth in the United States, and research is urgently needed to identify and

challenge pandemic-related harms for this vulnerable population. Analyzing survey re-

sponses collected in April 2020 from young people (ages 18–23) with history of foster care

placement, this study examines housing stability, food security, employment, ﬁnancial

stability, access to communications technology, and public beneﬁts receipt during COVID-

19, highlighting disparities between diverse demographic groups and leveraging data to

inform targeted disaster relief efforts and other state interventions.

aaa

evere acute respiratory syndrome coronavirus 2 (SARS-

CoV-2; coronavirus disease 2019 [COVID-19]) was ini-

tially detected in the United States in January 2020. By

March, the disease had been detected in all 50 states, prompting

nationwide emergency and major disaster declarations by federal

authorities (Federal Emergency Management Agency [FEMA],

2020a). The widespread and rapid community transmission of the

virus necessitated shelter-in-place mandates, quarantine protocols,

and social distancing, and by April, roughly 95% of the American

populace was under full or partial shelter-in-place orders issued by

state and local governments (Mervosh et al., 2020).

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

This article was published Online First February 24, 2022.

Johanna K. P. Greeson

https://orcid.org/0000-0002-5859-9517

John R. Gyourko

https://orcid.org/0000-0001-7025-5998

Sarah Wasch

https://orcid.org/0000-0003-2487-6392

Parts of these ﬁ ndings were presented as a poster at the 2021 Society for

Social Work & Research 25th Annual Conference, Online. The authors have

no conﬂicts of interest to disclose.

Correspondence concerning this article s hould be addressed to Johanna

K. P. Greeson, School of Social Policy & Practice, University of Penn-

sylvania, 3701 Locust Walk, Philadelphia, PA 19104, United States.

Email: jgre eson @up enn. edu

American Journal of Orthopsychiatry

https://doi.org/10.1037/ort0000615

334

Pandemic-re lated di srupti ons precipitated a sharp contraction

of the U.S. economy, leaving tens of millions unemployed. Job

losses have been particul arly seve re for women, non-White

workers, lower wage earners, and younger and less-educated

workers (i.e., those in the 16- to 24-year-old age range; Kochhar,

2020). These social groups and other historically marginali zed

and underresourced communities are among those experiencing

the gravest pandemic-related harms. COVID-19 has tended to

exacerbate longstanding challen ges such as ﬁnancial instabil ity,

high inciden ce of mental and physi cal health pr oblems, barriers to

health care ac cess, barriers to educational attainment, racial and

social discrimination, and food insecurity, with particularly acute

consequences for vulnerable social groups (Padilla & Thomson,

2021; Rollston & Galea, 2020; Stevenson, 2020).

Young people with a history of foster care placement comprise

one such social group. Even before COVID-19, these young people

were more likely than their counterparts in the general population to

experience a range of poor outcomes during early adulthood

(Courtney et al., 2009; Pecora et al., 2006). An emerging body

of evidence highlights the gravity of the COVID-19 disaster for

older youth with foster care experience, as the pandemic has

exacerbated risk of adverse outcomes in key life domains including

ﬁnancial stability, housing stability, food security, employment, and

physical and mental health (FosterClub, 2020; Greeson et al., 2020;

Ruff & Linville, 2021). Considerable additional research attention is

warranted to inform evidence-based responses.

The present study summarizes ﬁndings from an online survey of

current and former foster youth (ages 18–23) during the COVID-19

pandemic. The purpose of the study is to learn about the experiences

and ﬁnancial and material circumstances of older foster care youth

during an early moment in the pandemic’s trajectory, near the

beginning of the COVID-19 outbreak timeline in the United States.

In April 2020, few state or federal policies had yet been enacted to

support older foster care youth (Children’s Rights, 2020). Data

collected from this population during this period can be leveraged to

bolster contingency planning for future public health emergencies

and other disasters; to better understand the needs of diverse social

groups within the foster care population; and to inform targeted

resource allocations to better address the unique and ongoing needs

of these groups. As a longer term line of general research inquiry,

studies of this nature can empower public systems, private agencies,

and community stakeholder groups toward more effective and

compassionate models for the management of disaster relief efforts.

Background and Signiﬁcance

The Impact of Disasters

The United Nations (United Nations, Ofﬁce for the Coordination

of Humanitarian Affairs, 2008) characterizes disasters as severely

disruptive, collectively experienc ed e vents “causing wides pread

human material, economic, or environ mental losses,” which over-

whelm the coping capacities of affected communities (p. 22). Such

events may inclu de weather-re lated e mergencies (e.g., hurricanes,

tornadoes, ﬂoods), geological activity (e.g., earthquakes, eru p-

tions), humanitar ian emergencies ( e.g., armed conﬂict, refugee

crises, industrial accidents), and serious disease outbreaks such as

pandemic inﬂuenza (World Health Organization, n.d.). These

various eve nt types share a common potential for signiﬁca nt

ecological and psychosocia l disr uption at the individual, commu-

nity, and societal levels.

Compared to peers in other age groups, young people ages 16–24

face disproportionate risk of housing insecurity, job loss, persistent

unemployment, and ﬁnancial distress in disaster and recession

contexts in the United States (Bell & Blanchﬂower, 2011;

Kochhar, 2020). Low-income individuals, people with disabilities,

members of the LGBTQ+ (lesbian, gay, bisexual, transgender,

queer) community, single parents, women, immigrants, and minor-

ity race individuals are likewise at comparatively high risk of

disaster-related harms (Federal Emergency Management Agency

[FEMA], 2020b; Pérez-Escamilla et al., 2020). As noted in Federal

Emergency Management Agencies (FEMA)’s National Prepared-

ness Report (2020b), vulnerable populations “with less of a ﬁnancial

safety net” (p. 62) may struggle comparatively more than other

social groups to access adequate nutrition, transportation, and

critical news and information sources; maintain stable employment

and housing; and cope with ﬁnancial stress in disaster scenarios.

Disasters and Older Youth in and Recently

Aged Out of Care

Given the socioeconomic precarity commonly associated with

transitions from foster care to adulthood, older foster youth may be

uniquely vulnerable in disaster and postdisaster contexts. Compared

to their peers in the general population, young people transitioning

from foster care to emerging adulthood contend with greater risks of

under- and unemployment, poverty, and low educational attainment

(Rosenberg & Kim, 2018; Stewart et al., 2014). These interrelated

risks, which historically have contributed to high incidence of

homelessness and incarceration among former foster youth

(Cusick & Courtney, 2007), are during the pandemic exacerbating

threats to physical and socioeconomic health. Federal authorities

have advised that homelessness and housing instability may

increase individual risk of viral exposure (Centers for Disease

Control & Prevention, 2020b). So does incarceration, with many

of the largest known clusters of coronavirus outbreaks to date having

occurred in America’s jails and prisons (Hawks et al., 2020).

Similar transmission risks are present in group homes and other

congregate settings where older adolescents are more likely than

other age groups to be placed before aging out of foster care (Centers

for Disease Control & Prevention, 2020a; Kids Count Data Center,

2011). Unstable or crowded living conditions may also increase

vulnerabilities to abuse and exploitation as young people couch-surf

or seek refuge at emergency shelters to avoid homelessness

(Suriano, 2020).

Economic shock intensiﬁes these vulnerabilities, and the

pandemic-stricken labor market has been particularly bleak for

young adult workers and those without postsecondary degrees.

COVID-19 precipitated steep declines in the U.S. labor force

participation rate, with job losses concentrated in hospitality, leisure,

entertainment, and other service-based sectors of the economy

(Kochhar, 2020)—areas where many foster care alumni have tradi-

tionally found employment. Young people have described these

service industries as vital sources of employment and income during

the ﬁnancially precarious transition from state custody to indepen-

dent adulthood (Peters et al., 2012). Moreover, most young adults

with foster care experience lack the postsecondary degrees that

potentially confer protection against job instability and improve

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CURRENT AND FORMER FOSTER YOUTH EXPERIENCES DURING COVID 335

hiring prospects during recessions (Kochhar & Passel, 2020;

Rosenberg & Kim, 2018).

Foster Youth Experiences and Needs

During COVID-19

Think of Us, a Washington, DC-based nonproﬁt foster care

advocacy organization, hosted a virtual town hall event in March

2020 and asked older foster youth to identify their most pressing

needs during the COVID-19 crisis (Think of Us, 2020). On the basis

of responses from more than 1,400 young people, Think of Us

compiled a critical needs list in order of response frequency. Food

was the single-most urgent need, followed by housing and health

care. Financial assistance, employment assistance, and technology

resource needs were frequently reported as well.

In March 2020, the Oregon-based nonproﬁt organization Foster-

Club conducted a national poll of 613 young adults (ages 18–24)

currently or formerly in foster care. Nearly 65% of respondents who

had been employed prior to the COVID-19 outbreak reported

layoffs, lost gig work, or shift reductions resulting from the pan-

demic. Half of those who applied for unemployment had not

received any beneﬁts. Fifty-one percent of youth reported that

COVID-19 had impacted their food security, and nearly one in

ﬁve youth had run out of food altogether. Nearly one in four

respondents faced unstable housing or living situations.

Risk for adverse outcomes is not distributed evenly among

members of the foster care population. Studies prior to COVID-

19 show that marginalized or minoritized gender, sexual orientation,

and race/ethnicity youth are at comparatively higher risk of adverse

outcomes, both while they remain in care and when they transition to

adulthood (Dworsky, 2013; Shpiegel & Simmel, 2016; Watt & Kim,

2019). More recent studies indicate that these intersecting vulner-

abilities have intensiﬁed risks for foster youth during the COVID-19

pandemic. Surveys of current and former foster youth—such as

those conducted by FosterClub (2020), Greeson et al. (2020), and

Ruff and Linville (2021)—represent important steps toward identi-

fying and challenging pandemic-related harms. Given the pan-

demic’s severe social and economic disruption, including the

largest global recession since the Great Depression and more

than half the world’s population being under some form of lock-

down by the ﬁrst week of April 2020, research that prioritizes the

viewpoints of older foster youth and foster care alumni during such

crises is needed. It can and should inform the development of

interventions to mitigate pandemic-related harms where risk is

highest and need is greatest among young adults with foster care

experience. The extant literature on the impact of COVID-19 among

current and former foster youth is limited to just a handful of studies,

and additional work is required to develop a more comprehensive

picture of this population’s unique needs and risk proﬁles within the

macroeconomic, social, and health contexts of COVID-19.

The Present Study

With the goal of providing a more comprehensive picture of the

experiences of young people in and aged out of foster care during the

pandemic, this exploratory study presents results from an online

survey administered throughout April 2020 to current and former

foster youth. Other surveys, such as the national poll conducted by

FosterClub in March 2020, have similarly assessed the experiences

of current and former foster youth during the COVID-19 pandemic.

Our study contributes to this body of research by describing the

housing, food security, employment, personal ﬁnance, and techno-

logical experiences reported by current and former foster youth

during a 30-day period in April 2020. This monthlong period

comprises a unique moment in the early trajectory of the

COVID-19 pandemic in the United States. Survey data offer

important windows into the experiences and needs of older foster

youth during this critical juncture. As well, to our knowledge no

studies to date have investigated relationships between demographic

variables (i.e., foster care status, gender identity, sexual orientation,

ethnicity, and/or race) and the material and ﬁnancial circumstances

reported by foster care youth during the survey period, or during the

COVID-19 crisis generally.

The purpose of our study is to learn about the experiences of

young people in and aged out of foster care (ages 18–23) at the

beginning of the COVID-19 pandemic. Our study was guided by the

following research questions:

• To what extent do older youth in and recently aged out of

foster care in April 2020, during 1 month of the COVID-19

crisis in the United States report experiencing housing, food

security, employment, ﬁnancial, and technological hardships?

• To what extent are survey respondents’ demographic charac-

teristics (i.e., foster care status, gender identity, sexual orienta-

tion, ethnicity, and/or race) associated with their housing, food

security, employment, ﬁnancial, and technological hardships?

Method

Design and Overview

Data for this study come from our online survey of young people

from multiple states in the United States with foster care experience.

Administered by the Field Center for Children’s Policy, Practice,

and Research, this survey was open to eligible participants for a

30-day period in April 2020. Youth between the ages of 18 and 23

and currently in or aged out of foster care in the United States were

eligible to complete the survey.

Although the age at which young people age out of foster care

varies between states, formal support typically ceases between 18

and 21 years of age (Fernandes-Alcantara, 2019). Because we

wanted to capture the experiences of older youth still in foster

care as well as those on the verge of emancipation from care, we set

the lower bound for survey eligibility at age 18. Additionally,

because 18-year-olds have reached the age of legal majority in

most states, prospective respondents of this age who wished to

participate in our survey study could consent for themselves. The

upper bound for sample inclusion (age 23) corresponds to the age at

which a young person becomes ineligible to receive key sources of

extended foster care funding and services. This upper age limit

aligns with the maximum limit of eligibility for most Chafee

program funds (Family First Prevention Services Act, 2018).

Our survey questions are based in part on questions included in

FosterClub (2020) national online poll of current and former foster

youth, which asked respondents about the impacts of COVID-19 in

key life domains including ﬁnancial, material, social, and physical

and mental health. Our ﬁnal survey instrument had a total of 46

questions and incorporated a mix of Likert scale, multiple choice,

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336 GREESON, GYOURKO, JAFFEE, AND WASCH

and open-ended items. Data were collected using snowball sampling

and a cross-sectional survey design.

Recruitment

We recruited participants by leveraging our personal and profes-

sional connections to approximately ﬁve to ten different networks

including child welfare researchers, child welfare practitioners, and

higher education service providers, and asking “gatekeepers” to

disseminate our survey link to young people and service providers.

Examples of networks include Fostering Academic Achievement

Nationwide, the Child Maltreatment Researchers’ List Serve, Child

Welfare League of America, and the Pennsylvania Foster Care to

College Network. A recruitment email was also sent to individual

professional colleagues across the country who work within child

welfare systems, and/or who have connections to youth in foster care

or foster care alumni. We also posted information about the study on

our social media accounts including Facebook, Twitter, Instagram,

and LinkedIn. A social media post with our recruitment ﬂyer and

survey link was shared in Facebook groups speciﬁcally focused on

services to youth in foster care or foster care alumni. Individual

Facebook users also had the ability to share the post with their own

networks. Paid Facebook and Instagram ads were used to share the

post promoting the survey. Ads targeted young adults ages 18–23 in

10 U.S. cities, selected for their size and/or economic and geograph-

ical diversity: New York, Los Angeles, Chicago, Washington DC,

Detroit, New Orleans, Phoenix, Houston, Miami, and Dallas. The ad

ran for 3 weeks with a budget of $700.

Consent

We used the Qualtrics CoreXM online software platform to create

and administer our survey. Before entering the survey, an electronic

consent form was provided at the beginning. Agreement to take the

survey was then obtained by participants completing a CAPTCHA

veriﬁcation at the bottom of the consent form. After clicking on

the CAPTCHA, participants were taken to the ﬁrst set of survey

questions.

Data Integrity

We carefully reviewed open-ended question text input to ensure

that responses matched what an eligible survey participant might say

and were congruent with their previous answers. These strategies

were implemented to increase the likelihood that respondents

completing the survey were human and not programmed “bots”

(Gabrielli et al., 2020). To further ensure the integrity of our data,

we used Qualtrics’“Prevent Ballot Box Stufﬁng” function that

prevents multiple responses from the same device and web browser.

Each submitted survey was reviewed by a member of the research

team to determine if the amount of time it took the respondent to

complete the survey was reasonable.

In appreciation for their time, participants were invited to click a

link to visit a new form to enter into a random drawing to win one of

twelve $25 Target gift cards. These data were collected and stored

separately from the research data. Research shows that such lottery-

based incentive systems are effective in making surveys less appeal-

ing to bot interference (Borodovsky et al., 2018; Gabrielli et al.,

2020).

Human Subjects Protections

The University of Pennsylvania’s Institutional Review Board

approved all aspects of the study. IP address tracking was disabled

to ensure participant anonymity, and the primary survey link was

separated from the link to opt-in for the incentive drawing.

Sample

Of the 478 young people who logged on to the online survey

website, roughly two thirds (n = 304) completed the CAPTCHA

veriﬁcation and entered the survey. During data cleaning, we

eliminated 23 participants who were either under age 18, over

age 23, or who entered a noninteger value when reporting their

age. Our ﬁ nal analysis sample thus includes responses from a total of

281 survey participants.

Demographic Measures

Participants were asked to report their age; time in foster care; city

and state of residence; foster care status; gender identity; sexual

orientation; ethnicity; race; and highest educational degree/certiﬁ-

cation. Table 1 displays the response categories associated with each

nominal-level demographic measure, and in the following sections,

we describe coding and analysis methods for selected measures.

Foster Care Status. This dichotomous variable had two

mutually exclusive categories: in foster care (i.e., in a foster home,

kinship care, group home, or other foster care placement) and aged

out of foster care (i.e., not receiving direct support from the foster

care system).

Gender Identity. Gender identity consisted of ﬁve mutually

exclusive categories. Given the small sample sizes for noncisgender

categories (e.g., trans male, trans female), we excluded these

categories from Chi-square analyses to focus on assessing differ-

ences between cisgender females and cisgender males, who together

comprised 96.4% of respondents in the study sample.

Sexual Orientation. To facilitate statistical tests, we col-

lapsed ﬁve mutually exclusive sexual orientation categories into a

dichotomous variable coded as nonstraight (i.e., bisexual or pan-

sexual; gay or lesbian; asexual; or another identity) or straight.

Ethnicity. During analysis, we collapsed ﬁve mutually exclu-

sive ethnicity categories into a dichotomous variable coded as

Hispanic/Latinx/Spanish (including Mexican, Mexican American,

Chicano; Puerto Rican; Cuban; or other Hispanic/Latinx/Spanish

origin) or non-Hispanic/Latinx/Spanish.

Race. Respondents reported their race as American Indian or

Alaska Native, Asian, Black or African American, Native Hawaiian

or Other Paciﬁc Islander, and/or White. During analysis, we created

an additional category (“multiracial”) to represent respondents who

reported two or more racial categories. Further, we combined the

original race categories into a recoded categorical variable with

values assigned as “non-White” (i.e., American Indian or Alaska

Native; Asian; Black or African American; multiracial; and/or

Native Hawaiian or Other Paciﬁc Islander); White (i.e., participants

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CURRENT AND FORMER FOSTER YOUTH EXPERIENCES DURING COVID 337

who identiﬁed their race only as White); or unknown/decline to

answer. Respondents who identiﬁed as White in combination with

additional race categories were considered to be multiracial and

were therefore coded as non-White for analysis purposes.

Outcome Measures

The survey asked participants to indicate their living situation/

housing status, employment status, educational status, and receipt of

public beneﬁts prior to the outbreak of COVID-19 in the United

States. The survey also asked participants about the impact of

COVID-19 on their living situation/housing status, food security,

employment, ﬁnancial stability, access to communications technol-

ogy, and applications for public beneﬁts. Table 1 displays the response

categories associated with each prepandemic outcome measure, and

Table 2 displays the response categories associated with items con-

cerning respondents’ experiences and statuses during COVID-19.

Living Situation/Housing Status. Participants reported

their prepandemic housing/living situation by selecting one of nine

preformatted response categories (see Table 1). In a separate

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Table 1

Sociodemographic Proﬁle of Survey Respondents (N = 281)

Variable n (%)

Age (M = 19.86, SD = 1.62)

18 years 66 (23.5)

19 years

68 (24.2)

20 years

57 (20.3)

21 years

35 (12.5)

22 years 31 (11.0)

23 years

24 (8.5)

Time in foster care (M = 5.76, SD = 4.22)

≤1 year

29 (10.3)

2–3 years 74 (26.3)

4–5 years

66 (23.5)

6–7 years

41 (14.6)

8–9 years

22 (7.8)

10+ years 49 (17.4)

Foster care status

Aged out

148 (52.7)

In care

133 (47.3)

Gender identity

Cisgender female

213 (75.8)

Cisgender male

58 (20.6)

Trans female

2 (0.7)

Trans male 3 (1.1)

Other

5 (1.8)

Sexual orientation

Straight

169 (60.1)

Bisexual or pansexual 69 (24.6)

Gay or lesbian

20 (7.1)

Asexual

12 (4.3)

Another identity

5 (1.8)

Decline to answer 6 (2.1)

Ethnicity

Not of Hispanic/Latinx/Spanish origin

198 (70.5)

Mexican, Mexican American, Chicano

30 (10.7)

Puerto Rican 19 (6.8)

Cuban

4 (1.4)

Other Hispanic/Latinx/Spanish origin

12 (4.3)

Unknown

12 (4.3)

Decline to answer 6 (2.1)

Race

White

109 (38.8)

Black/African American

90 (32.0)

Multiracial (2+ races) 37 (13.2)

American Indian/Alaska Native

6 (2.1)

Asian

3 (1.1)

Unknown

17 (6.0)

Decline to answer 19 (6.8)

U.S. region

Northeast

96 (34.2)

Midwest

75 (26.7)

West 71 (25.3)

South

39 (13.9)

Highest education level achieved

Still in high school

39 (13.9)

High school diploma 177 (63.0)

GED

8 (2.8)

Vocational certiﬁcate or license

8 (2.8)

Associate degree

23 (8.2)

Bachelor’s degree 16 (5.7)

Decline to answer

10 (3.6)

Education status prior to COVID-19

In high school

44 (15.7)

Attending GED classes 9 (3.2)

Attending vocational training

8 (2.8)

Attending college or university full-time

97 (34.5)

Attending college or university part-time

37 (13.2)

Table 1 (continued)

Variable n (%)

Not attending any classes or trainings

82 (29.2)

Other

4 (1.4)

Living situation/housing status prior to COVID-19

Own house or apartment 95 (33.8)

Traditional (nonkinship) foster home

42 (14.9)

Living with parent, relative, or other adult

(not in foster care)

38 (13.5)

College or dorm housing 36 (12.8)

Group home or residential facility

34 (12.1)

Kinship home

9 (3.2)

Couch-surﬁng

8 (2.8)

Experiencing homelessness 4 (1.4)

Other

15 (5.3)

Employment status prior to COVID-19

Employed full-time

69 (27.7)

Employed part-time 101 (40.6)

Gig or informal worker

12 (4.8)

Not working but looking for work

47 (18.9)

Not working, not looking for work

17 (6.8)

Other 3 (1.2)

Public beneﬁts received prior to COVID-19

b,c

None

176 (70.7)

SNAP (Supplemental Nutrition Assistance

Program)

55 (22.1)

WIC (Special Supplemental Nutrition

Program for Women, Infants, and

Children)

15 (6.0)

Housing voucher 11 (4.4)

TANF (Temporary Assistance for Needy

Families)

7 (2.8)

Unemployment beneﬁts

2 (0.8)

Note. Unless otherwise noted, a total of 281 survey participants responded to

each survey item. Percentages are rounded to the nearest tenth. COVID-19 =

coronavirus disease.

States of residence are collapsed into geographical regions based on U.S.

Census Bureau (2019) classiﬁcations.

Category percents are based on the

total number of responses received for this survey item (n = 249). Thirty-two

cases with missing values were excluded from analysis.

Some

participants selected more than one type of public beneﬁt.

338 GREESON, GYOURKO, JAFFEE, AND WASCH

question, participants selected from among the same categories to

report their housing/living situation at the time of survey completion

(see Table 2).

Food Security. Participants reported their food security

status during COVID-19 by selecting one of ﬁve preformatted

response categories (see Table 2).

Employment. Participants reported their employment status

before COVID-19 by selecting one of six preformatted response

categories (see Table 1). In a separate question, participants reported

the impact of COVID-19 on their employment by selecting one of

seven preformatted response categories (see Table 2).

Financial Stability. Participants reported their ﬁnancial

status during COVID-19 by selecting one of ﬁve preformatted

response categories (see Table 2).

Public Beneﬁts. Participants indicated whether they

received any public beneﬁts (i.e., Temporary Assistance for Needy

Families [TANF], Supplemental Nutrition Assistance Program

[SNAP] and Women, Infants, and Children [WIC], housing

voucher, and/or unemployment beneﬁts; see Table 1) prior to

COVID-19. In a separate question, participants selected from among

the same response categories to report any new applications for

public beneﬁts (i.e., beneﬁts not already received prior to the

pandemic) since the outbreak of COVID-19. Both items permitted

participants to select multiple response options. Each type of public

beneﬁt was dichotomously coded as having been selected by the

respondent or not.

Access to Technology. Participants indicated whether dur-

ing COVID-19 they had reliable access to (a) cell phones, (b) personal

computers, and/or (c) internet connections. Each was dichotomously

coded as having been selected by the respondent or not.

Data Analysis

Data were analyzed with IBM SPSS Statistics (Version 26).

Similar to other survey studies, missing data were present for

some variables, resulting in modest decreases in sample size for

some analyses. Missing data ranged from 0% to 11.4% of cases

for any single survey item. Given the novel nature of the dataset, we

used all values observed for each variable of interest in order to

avoid loss of valuable data through listwise deletion.

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Table 2

Frequency Statistics for COVID-19 Impact Measures and Selected

Outcomes

Survey item stems and response sets n (%)

What best describes your current living situation/housing

status? (n = 281)

Own house or apartment

100 (35.6)

Living with parent, relative, or other adult (not

in foster care)

46 (16.4)

Traditional (nonkinship) foster home 42 (14.9)

Group home or residential facility

33 (11.7)

Couch-surﬁng

15 (5.3)

College or dorm housing

13 (4.6)

Kinship home 11 (3.9)

Experiencing homelessness

5 (1.8)

Other

16 (5.7)

What impact has COVID-19 had on your living

situation/housing status? (n = 281)

My living situation/housing is unchanged since

COVID-19

173 (61.6)

I fear being forced to leave my current living

situation/housing

43 (15.3)

I have been or am being forced to leave my

current living situation/housing

28 (10.0)

I’m experiencing homelessness/housing

instability due to a loss of housing since

COVID-19—I’m in crisis

18 (6.4)

Other

19 (6.8)

What best describes your current food security

status? (n = 281)

There is plenty of food where I live/I have

access to food

121 (43.1)

I have access to some food

106 (37.7)

My access to food is very low 46 (16.4)

I cannot access food—I’m in crisis

4 (1.4)

Other

4 (1.4)

What impact has COVID-19 had on your

employment? (n = 249)

I was laid off because of COVID-19

69 (27.7)

My hours/income have been severely cut

because of COVID-19

28 (11.2)

I no longer have reliable gig work because of

COVID-19

28 (11.2)

My employment status has not been impacted

by COVID-19

43 (17.3)

I am not sure yet of the impact of COVID-19 on

my employment

17 (6.8)

Does not apply—I was not working before

COVID-19

44 (17.7)

Other 20 (8.0)

What best describes your current ﬁnancial status? (n = 249)

I’m having a money crisis

54 (21.7)

My money situation is on a week-to-week basis

72 (28.9)

My money situation will be ﬁne for about a

month

54 (21.7)

My money situation feels stable for 3 months or

57 (22.9)

Other 12 (4.8)

Since COVID-19, have you applied for public beneﬁts

that you did not already have? (n = 249)

None

192 (77.1)

Unemployment 38 (15.3)

SNAP (Supplemental Nutrition Assistance

Program)

27 (10.8)

Housing voucher

11 (4.4)

TANF (Temporary Assistance for Needy

Families)

7 (2.8)

WIC (Special Supplemental Nutrition Program

for Women, Infants, and Children)

6 (2.4)

Table 2 (continued)

Survey item stems and response sets n (%)

Access to communication tools during COVID-19 (n = 249)

I have reliable access to a cell phone

227 (91.2)

I have reliable access to the internet

199 (79.9)

I have reliable access to a computer 165 (66.3)

None of the above

6 (2.4)

Note. Respondents reported their “current” living situations/housing

statuses, ﬁnancial statuses, and food security statuses when they

completed the online survey in April 2020. Percentages are rounded to

the nearest tenth. COVID-19 = coronavirus disease.

Thirty-two cases with missing values were excluded from analysis.

CURRENT AND FORMER FOSTER YOUTH EXPERIENCES DURING COVID

339

For de scriptive statis tics, we c alculate d frequencies and per-

centages for all categorical variables, and means and standard

deviations for all continuo us variable s. We conducted omnibu s

Chi-square tests to assess the statistical signiﬁcance of bivar iate

relationships bet ween demogr aphic varia bles and each outc ome

of interest. (Parti cipants who declined to identify their gender,

sexual orientation, ethnici ty, or race were excluded from signi ﬁ-

cance tes ts, as one of the prima ry pu rposes o f ou r stud y was to

investigate relationships between demographic variables and

respondent experiences during COVID-19.) For omnibus Chi-

square tests, we set the signiﬁcance level at α = .05. When an

omnibus test re turne d a p value lower than .05 , we procee ded wi th

post hoc pair wise co mparison s of contingency ta ble ce lls to

facilitate further interpretation of ﬁndings.

Our ﬁrst step in any given post hoc analysis was t o examine

standardized residual values to determin e which of the contin-

gency table cells made the greatest contributions to omnibus test

results (Sharpe, 2015). According to Agresti’s (2 007) rule of

thumb for po st hoc contingency table analysis, “a standardized

residual having absolute value that e xceeds about 2 ::: indicates

lack of ﬁtofH

in that cell” (p. 38). After each omnibus test, we

used this guid eline t o iden tify contingency table cells for p airwise

comparison. To evalua te differences between the id enti ﬁed cells

(i.e., those with standardize d residuals ≥ [2]), we conducted

pairwise z tests for equality of proportions. This procedure allowed

us to assess differences between demographic groups. We used

Bonferroni corrections to c ontrol the familywise error rate in post

hoc analyses, dividing the overall signiﬁcance le vel designated f or

the study (α = .0 5) by the number of cell pairs identi ﬁed for

comparison in each contingen cy ta ble. Because we did not for-

mulate a priori hypotheses concerning the nature or direction of

between-group d ifferen ces, and considering the number of out-

come va riables and demographic groups examined in our study,

we opted to use Bonferroni corrections to counte r α inﬂation

during t he post hoc ana lysis p hase ( Armstrong, 201 4). Finally, we

applied Yates’s (1934) continuity correction for comparisons

involving cell count(s) ≤ 5.

Results

Sample Demographics

Table 1 presents a summary of sociodemographic characteristics

for the total sample (N = 281). Survey participants were almost

evenly split between those still in care and those aged out of care.

Respondents were predominantly cisgender females. Although most

young people in the total sample identiﬁed as straight/heterosexual,

a considerable minority identiﬁed their sexual orientation as non-

straight (i.e., bisexual or pansexual, gay or lesbian, asexual, or

another identity; n = 106, 37.7%). Most participants had completed

high school, but only a small percentage had earned a Bachelor’s

degree. Participants hailed from 32 states (plus Washington, DC)

and 191 cities across the United States (see Figure 1). Collectively,

slightly more than half of the respondents lived in Pennsylvania

(14.9%), New Jersey (13.2%), California (11.4%), Indiana (6.8%),

or Illinois (6.4%) when they took the survey. Respondents were, on

average, 19.86 years of age (SD = 1.62) and had spent an average of

5.76 years in foster care (SD = 4.22).

Living Situation/Housing Status: Before and

During COVID-19

As shown in Table 1, approximately one third of respondents (n =

95, 33.8%) were living in their own house or apartment prior to

onset of COVID-19 in the United States. Eighteen percent were in

foster care placements, including traditional (i.e., nonkinship) foster

family homes (14.9%) or kinship care settings (3.2%). Nearly 14%

of respondents were living with a parent, relative, or other adult (not

in a foster care placement); 12.8% were living in college/dorm

housing; and 12.1% were living in a group home or residential

facility. Nearly 3% of the respondents were couch-surﬁng and 1.4%

were experiencing homelessness before the pandemic. Roughly 5%

selected “Other.”

Respondents’ prepandemic living situations/

housing statuses differed signiﬁcantly by foster care status, χ

(8,

N = 281) = 82.02, p < .001, V = .540. Prepandemic living situation/

housing status did not vary by gender, sexual orientation, ethnicity,

or race.

Following the pandemic outbreak in early Spring 2020, the

percentages of respondents living in traditional family foster

home settings, kinship care, and group home/congregate care set-

tings remained relatively stable, with each of these categories

shifting <1 percentage point from reported prepandemic levels

(see Table 2). There were slight upticks in the percentages of

respondents living in their own apartment or house (35.6%) or

with parents, relatives, or other adults (16.4%). As compared to

prepandemic levels, the percentage of respondents living in college/

dorm housing (4.6%) dropped sharply during COVID-19, and the

percentage of respondents who were couch-surﬁng (5.3%) nearly

doubled. The percentage of respondents experiencing homelessness

ticked slightly up to 1.8% of the total sample. Respondents ’ living

situations/housing statuses during COVID-19 differed signiﬁcantly

by foster care status, χ

(8, N = 281) = 100.18, p < .001, V = .597.

Living situation/housing status during the pandemic did not vary by

gender, sexual orientation, ethnicity, or race.

Impact of COVID-19 on Living Situation/

Housing Status

Although most respondents (n = 173, 61.6%) indicated that their

housing status or living situation had not changed since the pan-

demic outbreak, 31.7% indicated that COVID-19 had some (any)

negative impact on their living situation (see Table 2). Collectively,

more than one quarter of respondents reported either that they feared

being forced to leave their current living arrangement (15.3%), or

that they were being forced to leave or had already been forced to

leave their living arrangement (10%). Roughly 1 in 15 respondents

(n = 18, 6.4%) were in crisis due to homelessness/housing instability

precipitated by the pandemic.

As shown in Tables 3 and 4, the impact of COVID-19 on

respondents’ living situations/housing statuses differed signiﬁcantly

by foster care status, χ

(4, N = 281) = 19.14, p < .001, V = .261,

gender, χ

(4, N = 271) = 12.14, p = .016, V = .212, and ethnicity,

(4, N = 263) = 10.29, p = .036, V = .198. The impact of COVID-

19 on housing did not vary by sexual orientation or race.

This document is copyrighted by the American Psychological Association or one of its allied publishers.

This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

For any survey item with a response set including the category “other,”

participants who selected “other” were permitted to input an open-ended text

response. To review selected excerpts, see Greeson et al.’s (2020) research

report featuring preliminary analyses of qualitative text responses.

340 GREESON, GYOURKO, JAFFEE, AND WASCH

Post hoc pairwise comparisons revealed that respondents in foster

care, as compared to respondents aged out of care, were less likely to

report being in crisis due to a loss of housing since COVID-19 (2.3%

vs. 10.1%; χ

= 6.00, p = .014). Respondents in foster care were less

likely to fear being forced to leave their housing/living situation

(9.8% vs. 20.3%; χ

= 5.95, p = .015), and were more likely to

report that their housing/living situation was unchanged since the

pandemic outbreak (70.7% vs. 53.4%; χ

= 8.86, p = .003).

Cisgender females, as compared to cisgender males, were less likely

to report that their housing/living situation was unchanged since

COVID-19 (57.3% vs. 79.3%; χ

= 9.39, p = .002).

Food Security During COVID-19

Most respondents reported either that they had access to plenty of

food (n = 121, 43.1%) or access to some food (n = 106, 37.7%). A

sizeable minority, however, indicated that they had experienced

some (any) food insecurity since the pandemic outbreak: 16.4%

reported that their access to food was very low, and 1.4% were in

crisis as they lacked access to any food (see Table 2).

As shown in Tables 3 and 4, food security during the pandemic

differed signiﬁcantly by foster care status, χ

(4, N = 281) = 17.53, p =

.002, V = .250, gender, χ

(4, N = 271) = 10.40, p = .034, V = .196,

sexual orientation, χ

(4, N = 275) = 13.10, p = .011, V = .218, and

race, χ

(4, N = 245) = 15.30, p = .004, V = .250. Food security did not

vary by ethnicity.

Respondents in foster care, as compared to those aged out of care,

were less likely to report having very low access to food during the

pandemic (9.8% vs. 22.3%; χ

= 8.02, p = .005). As well,

respondents in care were more likely to have access to plenty of

food during COVID-19 (53.4% vs. 33.8%; χ

= 10.98, p < .001).

Cisgender females were less likely than cisgender males to have

access to plenty of food during the pandemic (38% vs. 58.6%; χ

7.91, p = .005), as were nonstraight respondents as compared to

straight respondents (34.9% vs. 47.9%; χ

= 4.51, p = .034). Non-

White respondents were more likely than White respondents to have

very low access to food during COVID-19 (22.1% vs. 8.3%; χ

8.61, p = .003).

Employment Status Before COVID-19

A total of 32 cases were excluded from this analysis due to item

nonresponse. Of the 249 participants who responded to this survey

question, nearly three quarters (n = 182) reported either that they

worked part-time (40.6%), full-time (27.7%), or had gig or informal

jobs (4.8%) prior to COVID-19 (see Table 1). Roughly one in ﬁve

respondents (n = 47, 18.9%) were not employed but were looking for

work, and 6.8% were neither employed nor seeking employment.

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Figure 1

Location of Participants

Note. See the online article for the color version of this ﬁgure.

CURRENT AND FORMER FOSTER YOUTH EXPERIENCES DURING COVID

341

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Table 3

Frequency Statistics and Omnibus Chi-Square Results by Foster Care Status, Gender, and Sexual Orientation

Survey item stems and response sets

Foster care status Gender Sexual orientation

In care Aged out

Cisgender female Cisgender male

Nonstraight

Straight

Vn (%) n (%) n (%) n (%) n (%) n (%)

What impact has COVID-19 had on your living

situation/housing?

19.14

***

.261 12.14

.212 2.13 .088

My living situation/housing is unchanged

94 (70.7) 79 (53.4) 122 (57.3) 46 (79.3) 61 (57.5) 109 (64.5)

I’ve been forced to leave my current living

situation

17 (12.8) 11 (7.4) 26 (12.2) 2 (3.4) 12 (11.3) 16 (9.5)

I fear being forced to leave my current living

situation

13 (9.8) 30 (20.3) 39 (18.3) 3 (5.2) 18 (17.0) 24 (14.2)

I’m experiencing homelessness/housing

instability—I’m in crisis

3 (2.3) 15 (10.1) 13 (6.1) 3 (5.2) 6 (5.7) 11 (6.5)

Other

6 (4.5) 13 (8.8) 13 (6.1) 4 (6.9) 9 (8.5) 9 (5.3)

What best describes your current food security

status?

17.53

.250 10.40

.196 13.10

.218

I cannot access food—I’m in crisis

0 (0.0) 4 (2.7) 3 (1.4) 1 (1.7) 0 (0.0) 4 (2.4)

My access to food is very low

13 (9.8) 33 (22.3) 41 (19.2) 4 (6.9) 20 (18.9) 25 (14.8)

I have access to some food

48 (36.1) 58 (39.2) 84 (39.4) 19 (32.8) 45 (42.5) 59 (34.9)

I have access to plenty of food

71 (53.4) 50 (33.8) 81 (38.0) 34 (58.6) 37 (34.9) 81 (47.9)

Other

1 (0.8) 3 (2.0) 4 (1.9) 0 (0.0) 4 (3.8) 0 (0.0)

What impact has COVID-19 had on your

employment?

19.06

.277 7.43 .176 11.01

†

.212

My employment has not been impacted

16 (14.2) 27 (19.9) 28 (15.1) 13 (24.1) 12 (12.6) 31 (20.8)

I was laid off

32 (28.3) 37 (27.2) 55 (29.6) 12 (22.2) 34 (35.8) 34 (22.8)

I no longer have reliable gig work

11 (9.7) 17 (12.5) 25 (13.4) 2 (3.7) 9 (9.5) 15 (10.1)

My work hours and/or income were severely cut

8 (7.1) 20 (14.7) 20 (10.8) 7 (13.0) 15 (15.8) 13 (8.7)

I’m not sure yet

7 (6.2) 10 (7.4) 13 (7.0) 4 (7.4) 4 (4.2) 13 (8.7)

Does not apply—I wasn’t working before

COVID-19

32 (28.3) 12 (8.8) 30 (16.1) 12 (22.2) 14 (14.7) 30 (20.1)

Other

7 (6.2) 13 (9.6) 15 (8.1) 4 (7.4) 7 (7.4) 13 (8.7)

What best describes your current ﬁnancial status?

6.24 .158 8.01

†

.183 16.79

.262

I’m experiencing a money crisis

21 (18.6) 33 (24.3) 42 (22.6) 8 (14.8) 23 (24.2) 29 (19.5)

My money situation is on a week-to-week basis

30 (26.5) 42 (30.9) 53 (28.5) 17 (31.5) 36 (37.9) 35 (23.5)

My money situation will be ﬁne for about a

month

23 (20.4) 31 (22.8) 45 (24.2) 7 (13.0) 23 (24.2) 30 (20.1)

My money situation will be stable for 3+ months

34 (30.1) 23 (16.9) 37 (19.9) 19 (35.2) 10 (10.5) 47 (31.5)

Other

5 (4.4) 7 (5.1) 9 (4.8) 3 (5.6) 3 (3.2) 8 (5.4)

Since COVID-19, have you applied for public

beneﬁts you did not already have?

7.22

.170 10.25

.219 1.00 .064

Applied for one or more new beneﬁts

17 (15.0) 40 (29.4) 51 (27.4) 3 (5.6) 25 (26.3) 31 (20.8)

Did not apply for any new beneﬁts

96 (85.0) 96 (70.6) 135 (72.6) 51 (94.4) 70 (73.7) 118 (79.2)

Note. V = Cramer’s V effect size measurement for Chi-square tests of independence. Table reports conditional relative frequencies and omnibus test results for selected survey items and the associated categorical response

sets, with column percents reported by demographic subgroup. χ

values in bold text denote signi ﬁcance of the test statistic. Frequency/percent values in bold text convey that a post hoc pairwise comparison returned a p

value below the Bonferroni-adjusted α. Participants who declined to identify their gender or sexual orientation were excluded from analyses. SNAP = Supplemental Nutrition Assistance Program; TANF = Temporary

Assistance for Needy Families; Women, Infants, and Children = WIC; COVID-19 = coronavirus disease.

Participants who identiﬁed their sexual orientation as bisexual or pansexual; gay or lesbian; asexual; or another identity.

Thirty-two cases with missing values were excluded from analysis. Conditional relative

frequencies and column percents describe the distribution of n = 249 complete responses received for the survey item.

SNAP, TANF, WIC, housing vouchers, and/or unemployment beneﬁts the participant was not

already receiving prior to COVID-19.

†

p < .10.

p < .05.

p < .01.

***

p < .001.

342 GREESON, GYOURKO, JAFFEE, AND WASCH

Prepandemic employment status differed signiﬁcantly by foster

care status, χ

(5, N = 249) = 14.85, p = .011, V = .244. Respondents

in foster care, as compared to those who aged out of care, were less

likely to have been employed full-time prior to COVID-19 (16.8%

vs. 36.8%; χ

= 12.26, p < .001). Prepandemic employment status

did not vary signiﬁcantly by gender, sexual orientation, ethnicity,

or race.

Impact of COVID-19 on Employment

A total of 32 cases were excluded from this analysis due to item

nonresponse. Of the 249 participants who responded to this item,

slightly more than half (n = 125, 50.2%) reported some (any)

negative impact of the pandemic on their employment status:

27.7% had been laid off from their job, 11.2% had their income/

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Table 4

Frequency Statistics and Omnibus Chi-Square Results by Ethnicity and Race

Survey item stems and response sets

Respondent demographic

Ethnicity Race

Latinx Non-Latinx

Non-White White

Vn (%) n (%) n (%) n (%)

What impact has COVID-19 had on your living

situation/housing?

10.29

.198 2.15 .094

My living situation/housing is unchanged

42 (64.6) 119 (60.1) 88 (64.7) 66 (60.6)

I’ve been forced to leave my current living

situation

3 (4.6) 25 (12.6) 12 (8.8) 12 (11.0)

I fear being forced to leave my current living

situation

13 (20.0) 28 (14.1) 19 (14.0) 15 (13.8)

I’m experiencing homelessness/housing

instability—I’m in crisis

0 (0.0) 14 (7.1) 11 (8.1) 7 (6.4)

Other 7 (10.8) 12 (6.1) 6 (4.4) 9 (8.3)

What best describes your current food security

status?

2.50 .098 15.30

.250

I cannot access food—I’m in crisis

1 (1.5) 2 (1.0) 2 (1.5) 1 (0.9)

My access to food is very low 12 (18.5) 29 (14.6) 30 (22.1) 9 (8.3)

I have access to some food

25 (38.5) 75 (37.9) 51 (37.5) 37 (33.9)

I have access to plenty of food

25 (38.5) 90 (45.5) 53 (39.0) 58 (53.2)

Other

2 (3.1) 2 (1.0) 0 (0.0) 4 (3.7)

What impact has COVID-19 had on your

employment?

2.59 .105 5.31 .156

My employment has not been impacted

11 (19.3) 30 (16.7) 19 (15.7) 16 (16.7)

I was laid off

13 (22.8) 55 (30.6) 33 (27.3) 30 (31.3)

I no longer have reliable gig work 7 (12.3) 17 (9.4) 17 (14.0) 5 (5.2)

My work hours and/or income were

severely cut

8 (14.0) 19 (10.6) 13 (10.7) 12 (12.5)

I’m not sure yet

5 (8.8) 11 (6.1) 9 (7.4) 6 (6.3)

Does not apply—I wasn’t working before

COVID-19

9 (15.8) 33 (18.3) 20 (16.5) 20 (20.8)

Other

4 (7.0) 15 (8.3) 10 (8.3) 7 (7.3)

What best describes your current ﬁnancial

status?

.073 .055 6.82 .177

I’m experiencing a money crisis

10 (17.5) 37 (20.6) 33 (27.3) 14 (14.6)

My money situation is on a week-to-week

basis

18 (31.6) 52 (28.9) 36 (29.8) 26 (27.1)

My money situation will be ﬁne for about a

month

13 (22.8) 40 (22.2) 23 (19.0) 23 (24.0)

My money situation will be stable for 3+

months

14 (24.5) 41 (22.8) 23 (19.0) 27 (28.1)

Other 2 (3.5) 10 (5.6) 6 (5.0) 6 (6.3)

Since COVID-19, have you applied for public

beneﬁts you did not already have?

0.01 .005 1.79 .091

Applied for one or more new beneﬁts

13 (22.8) 42 (23.3) 32 (26.4) 18 (18.8)

Did not apply for any new beneﬁts 44 (77.2) 138 (76.7) 89 (73.6) 78 (81.3)

Note. V = Cramer’s V effect size measurement for Chi-square tests of independence. Table reports conditional relative frequencies and omnibus test results for

selected survey items and the associated categorical response sets, with column percents reported by demographic subgroup. χ

values in bold text denote

signiﬁcance of the test statistic (α = .05). Frequency/percent values in bold text convey that a post hoc pairwise comparison returned a p value below the

Bonferroni-adjusted α. Participants who declined to identify their ethnicity or race were excluded from analyses. SNAP = Supplemental Nutrition Assistance

Program; TANF = Temporary Assistance for Needy Families; WIC = Women, Infants, and Children; COVID-19 = coronavirus disease.

Thirty-two cases with missing values were excluded from analysis. Conditional relative frequencies and column percents describe the distribution of n = 249

complete responses received for the survey item.

SNAP, TANF, WIC, housing vouchers, and/or unemployment beneﬁts the participant was not already

receiving prior to COVID-19.

p < .05.

p < .01.

CURRENT AND FORMER FOSTER YOUTH EXPERIENCES DURING COVID

343

work hours severely cut, and 11.2% lost reliable gig work (see

Table 2).

The impact of COVID-19 on employment varied signiﬁcantly by

foster care status, χ

(6, N = 249) = 19.06, p = .004, V = .277. As

well, there was a marginally signiﬁcant association between

employment impact and sexual orientation, χ

(6, N = 244) =

11.01, p = .088, V = .212. Employment impact did not vary by

gender, ethnicity, or race (see Tables 3 and 4).

Respondents in foster care, as compared to those aged out of

care, were more likely to rep ort that the pa ndemic ha d not

impacted their employment because they had not been working

prior to COVID-19 (28.3% vs. 8.8%; χ

= 16.12, p < .001).

Nonstraight respondents were more likely than straight respon-

dents to report being laid off during the pan demic (35.8% vs.

22.8%; χ

= 4.86, p = .028).

Financial Stability During COVID-19

A total of 32 cases were excluded from this analysis due to item

nonresponse. Of the 249 participants who responded to this item,

slightly more than half (n = 126, 50.6%) were e xperien cing some

(any) lev el of personal ﬁnancial inst ability following the pan-

demic ou tbrea k: 21.7% w ere in ﬁnancial crisis, and 28.9%

reported that their ﬁna nces were on a w eek-to- week basis ( see

Table 2).

Financial stability during the pandemic varied signiﬁcantly by

sexual orientation, χ

(4, N = 244) = 16.79, p = .002, V = .262. As

well, there was a marginally signiﬁcant association between ﬁnan-

cial stability and gender, χ

(4, N = 240) = 8.01, p = .091, V = .183.

Financial stability did not vary by foster care status, ethnicity, or race

(see Tables 3 and 4).

Nonstraight respondents, as compared to straight respondents,

were more likely to report that their personal ﬁnancial stability

was on a week-to-week basis during the pandemic (37.9% vs.

23.5%; χ

= 5.84, p = .016). Nonstraight respondents were less

likely to report that their pers onal ﬁnances w ould re main stabl e

for 3 mon ths or longer (10.5% vs . 31.5%; χ

= 14.31, p < .001).

Cisgender females were less likely than cisgender males to report

that their personal ﬁnances would r emain stable f or 3 months o r

longer (19.9% vs. 35.2%; χ

= 5.47, p = .019).

Receipt of Public Beneﬁ ts Prior to COVID-19

A total of 32 cases were excluded from this analysis due to item

nonresponse. Of the 249 participants who responded to this item,

most (n = 176, 70.7%) had not received public beneﬁts prior to

COVID-19 (see Table 1). Slightly less than one quarter (n = 55,

22.1%) participated in SNAP, 6% received WIC (Women, Infants,

and Children) beneﬁts, 4.4% were housing voucher recipients, 2.8%

participated in TANF, and less than 1% received unemployment

beneﬁts.

Respondents in foster care, as compared to those aged out of

care, were le ss likely to report that they received any publi c

beneﬁt s prior to the pandem ic, 16.8% versus 39.7%; χ

(1, N =

249) = 15.61, p < .001. Pre pandemic receipt of public bene ﬁts

did not vary by g ender, sexual orientation, ethnicity , or race.

New Applications for Public Beneﬁts

During COVID-19

A total of 32 cases were excluded from this analysis due to item

nonresponse. Of the 249 participants who responded to this item,

most (n = 192, 77.1%) indicated that they had not applied for any

new beneﬁts since the pandemic began (see Table 2). Roughly one

in seven (n = 38, 15.3%) applied for unemployment beneﬁts, and

roughly 1 in 10 (n = 27, 10.8%) applied for SNAP beneﬁts.

Comparatively fewer respondents applied for housing vouchers

(4.4%), TANF (2.8%), or WIC (2.4%). A total of 20 respondents

indicated that they applied for multiple different types of public

beneﬁts.

New applications for public beneﬁts (i.e., respondent applications

for beneﬁts they had not received prior to COVID-19) differed

signiﬁcantly by foster care status and by gender. Respondents in

foster care, as compared to those who aged out of care, were less

likely to report having newly applied for beneﬁts during the

pandemic, 15% versus 29.4%; χ

(1, N = 249) = 7.22, p = .007.

Cisgender females were more likely than cisgender males to report

having newly applied for beneﬁts, 27.4% versus 5.6%; χ

(1, N =

240) = 10.25, p = .001. New applications for public beneﬁts did not

vary by sexual orientation, ethnicity, or race (see Tables 3 and 4).

Access to Technology During COVID-19

A tot al of 32 cases were excluded from this analysis due to item

nonresponse. Of the 249 participants who responded to this item,

91.2% had reliable access to a cell phone, 79.9% had reliable

access to the internet, 66.3% had reliable access to a computer,

and 2.4% lacked access to any of th ese during th e pandemic ( see

Table 2).

Respondents in foster care, as compared to those who aged out of

care, were signiﬁcantly more likely to have reliable access to a cell

phone during COVID-19, 73.5% versus 60.3%; χ

(1, N = 249) =

4.78, p = .029. Non-White youth were marginally less likely than

White youth to have reliable access to a computer during the

pandemic, 62.0% versus 74.0%; χ

(1, N = 217) = 3.49, p =

.062. Cisgender females were marginally more likely to have reliable

access to a cell phone, 93.0% versus 85.2%; χ

(1, N = 240) = 3.21,

p = .073, and were marginally more likely to have reliable access to

the internet, 83.9% versus 72.2%; χ

(1, N = 240) = 3.73, p = .054,

than were cisgender males. There were no signiﬁcant differences in

cell phone, internet, or computer access by sexual orientation or

ethnicity.

Discussion

This study uses data collected from 281 current and former foster

youth (ages 18–23) who participated in an online survey in April

2020. Respondents reported their experiences during COVID-19

and their appraisals of the impact of the pandemic in key outcome

domains including housing, food security, employment, ﬁnancial

stability, and access to technology.

Our ﬁndings suggest that respondents experienced substantial

challenges related to these aspects of their safety and well-being in

early 2020, following the emergence of COVID-19 in the United

States. Respondents were also asked whether they had submitted

any new applications for public beneﬁts since the pandemic

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

344 GREESON, GYOURKO, JAFFEE, AND WASCH

outbreak. Although majorities or considerable minorities of respon-

dents experienced ﬁnancial instability, employment-related adver-

sities, housing instability, and/or food insecurity during the

pandemic, most indicated that they had not applied for any new

public beneﬁts. We additionally assessed whether there were any

differences by foster care status, gender, sexual orientation, ethnic-

ity, or race. As reviewed below, respondents who had aged out of

foster care, cisgender females, nonheterosexual youth, and non-

White youth were more likely than their demographic counterparts

to report ﬁnancial and material distress during the pandemic. The

timing of our study is particularly important as it documents how the

patterns of results emerged early, which speaks to the need for rapid

assistance in the case of public health and other emergencies.

Foster Care Status

Young adults who aged out of foster care were more likely than

their peers in care to report challenges related to their living

situation/housi ng, to experience food insecurity, and to ap ply for

public beneﬁts during COVID-19. Thi s is unders tandabl e, as

youth who are accessing extended foster care services are pre-

sumably residing in monitored pla cements where, at a min imum,

their basic needs should be met. Additionally, youth still in foster

care may not be eligi ble for the sam e public be neﬁts as youth who

have aged out of foster care, and so applications for new beneﬁt

programs are more likely to be complet ed by young adults who

were formerly in care.

Gender Identity

Participants who identiﬁed as cisgender female were more likely

than cisgender males to report negative impacts on their living

situation/housing, and more likely to apply for public beneﬁts

during COVID-19. As well, cisgender females were less likely to

report that they had access to plenty of food during the pandemic,

and less likely to report that their personal ﬁnances would remain

stable for 3 months or longer. Previous studies examining the role of

gender as a factor inﬂuencing outcomes for transition-age youth

have yielded inconclusive results (Courtney et al., 2012; Pecora

et al., 2003). Further research on the impact of gender identity on

postcare functioning is warranted, especially in light of the ongoing

COVID-19 public health crisis.

Sexual Orientation

Nonstraight respondents were more likely than straight respon-

dents to experience a negative impact on their employment due to

COVID-19, more likely to experience ﬁnancial instability, and less

likely to report that they had access to plenty of food during the

pandemic. Prior research shows that even before the pandemic,

sexual minority youth with a history of foster care placement were at

greater risk for poor employment and ﬁnancial stability outcomes in

early adulthood as compared to their heterosexual peers (Shpiegel &

Simmel, 2016). As well, research by Dworsky (2013) indicates that

transition-age nonheterosexual youth are signiﬁcantly more likely to

be food insecure. Findings from the present study suggest that

sexual minority youth are particularly vulnerable to pandemic-

related adversities in key outcome domains and may therefore

beneﬁt from more intensive supports during disaster scenarios.

Further research should examine the interrelationships between

prepandemic risk factors and the experiences and needs of nonhet-

erosexual current and former foster youth during COVID-19.

Practice and Policy Recommendations

Considering the major ities or sizeable minorities of diverse

youth gro ups in this sample who experienced hardsh ips in critical

ﬁnancial and material doma ins at the outset o f COVID-19, we

suggest that child we lfare organizations enhan ce opportunities to

ensure that young people ’s basic needs are met. S ystemic inter -

ventions m ust be implemented to ensure tha t older foster youth

maintain stable housing, and to allow youth who a ged out to

reenter care and/or receive housing s ervices. Altho ugh the p assage

of the foster care-speciﬁc provisions of the Supporting Foster

Youth and Families through the P andemic Act (20 20) in the

Consolidated Appropriations Act provid ed a temporary mora to-

rium on discharges from fos ter care du e to age or nonc ompliance,

these protections expire d in S eptember 2021. In co nsideration of

ongoing pandemic-rela ted cha llenges, state and county child

welfare systems should seek to re instate or continue providing

resources to older youth in foster ca re as ther e is no reason t o

believe that these young people would no t beneﬁt from a continu-

ation of resources while the COVID-19 pandemic continues to

impact communitie s. The Supporting Foste r You th and Familie s

through the Pandemic Act (2020) is one way the system cou ld

permanently be changed for the better for older youth in and aged

out of care. At the state level, California i s working to pass a

measure to continue a pilot universal basic income program th at

gave youth aged out of fo ste r care $1,000 per month to help them

get through the pandemic (J ones, 2021).

Concrete reso urces such as gift car ds, bags of groceries, laptops,

and/or WiFi hotspots must be disseminated directly to vulnerable

young people to alleviate ﬁn ancial and material concerns and to

ensure contin ued access t o information. This study showed that the

negative impacts of COVID-1 9 were signi ﬁcantly worse for young

people who had alre ady age d out of foster care. It is therefore

critical that child welfar e agencies and other youth-serving s ys-

tems work to locate these individuals and in addition to providing

immediate resources, assist them with applying for any public

beneﬁts that they may be newly eligible for, including TANF,

SNAP, W IC, or u nemplo yment due to changes in work on school

schedules.

For older youth still in foster care, innovative approaches must be

adopted to ensure that basic needs are met and to avoid dangerous

gaps in service provision. Every older youth in care should be

equipped with access to the internet and a personal smartphone or

computer. Technology is critical to facilitate access to educational

programming, employment, food, and housing. For the nearly 25%

of respondents still in foster care who either were forced to leave

their current living situation, feared being forced to leave their

current living situation, or experienced homelessness or a housing

crisis, child welfare agencies should not only ensure an adequate

pool of foster homes in preparation for emergency situations, but

reassure youth in care that continued h ousing is guar anteed. One

strategy to achieve this incl udes adopting a ﬂexible or increased

foster parent per diem stipend, as an increased payment could

serve as an incentive, particularly during times of extreme need

(Mari nescu et al., 2019).

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This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

CURRENT AND FORMER FOSTER YOUTH EXPERIENCES DURING COVID 345

Finally, we note that COVID-19 underscores and exacerbates

deep ﬂaws in America’s social safety net. The challenges reported

by young adults exiting foster care are shared by many Americans

who were already living near or below the poverty line or who were

otherwise vulnerable when the pandemic began. Although we

suggest concrete actions child-serving agencies can take to promote

positive outcomes for young adults exiting foster care during and

after the pandemic, the difﬁculties reported by our survey respon-

dents go well beyond what the child welfare system alone can

address. Ensuring adequate basic income, employment and housing

stability, food security, and other measures of well-being are the

responsibilities of multiple agencies which must work in tandem to

ensure that all Americans have the opportunities and resources

required to survive and thrive in the 21st century.

Limitations

The limitations of this study are important to note. First, similar to

other survey studies and because we used snowball sampling, it is

unclear how well our sample represents the population. Nonprob-

ability sampling lays our results open to selection bias and error.

Further, advertisements of our survey were delivered via social

media platforms and targeted to young people in large metropolitan

areas. Our ﬁndings may have differed if more rural-located youth

were targeted for sample inclusion. Research suggests that support-

ive resource availability, behavioral and environmental risks, and

foster care experiences of youth vary to some extent depending on

urbanicity (e.g., Barth et al., 2006; McGuinness, 2009; Okpych

et al., 2015).

Two features of our study design limit our ability to make causal

inferences about how study respondents were affected by COVID-

19. We did not have pre-COVID-19 information on respondents. It

is not always clear how much their circumstances changed as a result

of COVID-19, although in some cases we asked respondents to

report retrospectively on their circumstances before COVID-19. We

also did not include a demographically matched comparison group

of young people impacted by COVID-19, but who did not have any

history of foster care. We are therefore unable to determine to what

extent our ﬁndings are causally related to the experiences of foster

care and aging out of care, although ongoing nationally representa-

tive surveys of similarly aged youth during COVID-19 may even-

tually allow us to make some comparisons.

Relatedly, we did not have a way of tracking how each participant

learned about the research study. There is the possibility that

participants who learned of the study through Facebook or Insta-

gram or Twitter represent a similar subgroup of the population of

young adults in, or recently exited from, foster care. Although

targeted social media advertising often results in an oversampling

of particular subgroups (Borodovsky et al., 2018), we attempted to

simultaneously utilize a variety of recruitment methods to limit the

possibility of an idiosyncratic respondent pool. Lastly, the timing of

our study has provided an early “snapshot” of the experiences of a

sample of older youth in care and recently aged out of care during

COVID-19. It is possible that this population could have experi-

enced additional harms, like greater illness, as the pandemic con-

tinued to rage, which we have not documented. More research is

needed to understand how the experience of youth in and aging out

of foster care has changed over the duration of the pandemic.

Conclusion

This survey study examines the experiences of older youth in care

and recently aged out of care during the COVID-19 pandemic. This

is the ﬁrst peer-reviewed study to explore between-group differ-

ences in the ﬁnancial and material circumstances reported by older

foster care youth during an early moment in the pandemic’s

trajectory. As such, this research considerably advances our under-

standing of the associations between older foster youths’ demo-

graphic characteristics and the ﬁnancial and material challenges

reported by youth at the outset of the pandemic.

Findings suggest cause for serious concern. Pandemic-related

adversity exacerbates the already-challenging material and ﬁnancial

hardships common among members of this vulnerable community

in emerging adulthood. Majorities or sizeable minorities of the

respondents reported difﬁculties related to their living situations/

housing statuses, access to food, employment, and personal ﬁ-

nances. One in ﬁve young people did not have reliable access to

the internet during the early months of the pandemic, and one in

three young people lacked reliable access to a computer. Analyses

revealed disparate pandemic-related impacts across foster care

status, gender, sexual orientation, and race groups, with youth

who aged out of care, cisgender females, nonstraight youth, and

non-White youth more likely to report pandemic-related material

and ﬁnancial challenges.

Current service structures lack the requisite ﬂexibility to ade-

quately respond to the COVID-19 crisis and its sequelae for older

youth in and recently aged out of care. More research is needed to

further understand what happens to marginalized young people, like

those with foster care experiences, during disasters. This study is an

important ﬁrst step in building and leveraging this knowledge to

inform policy and practice changes so that when disaster strikes

again, our systems can more effectively respond to the safety, health,

and well-being needs of youth with foster care experiences.

Keywords: COVID-19, foster care, housing stability, employment,

financial stability

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