The author(s) shown below used Federal funds provided by the U.S. 

Department of Justice and prepared the following final report: 

Document Title: Crime during the Transition to Adulthood: How 

Youth Fare as They Leave Out-of-Home Care 

Author: Gretchen Ruth Cusick, Mark E. Courtney, Judy 

Havlicek, Nathan Hess 

Document No.: 229666 

Date Received: February 2010 

Award Number: 2005-IJ-CX-4031 

This report has not been published by the U.S. Department of Justice. 

To provide better customer service, NCJRS has made this Federallyfunded grant final report available electronically in addition to 

traditional paper copies. 

 

Opinions or points of view expressed are those 

of the author(s) and do not necessarily reflect 

the official position or policies of the U.S. 

Department of Justice. 
Crime during the Transition to 

Adulthood 

How Youth Fare as They Leave Out-of-Home Care 

Gretchen Ruth Cusick 

Mark E. Courtney 

Judy Havlicek 

Nathan Hess 

2010 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Acknowledgments 

The authors wish to thank our three state partners, the Illinois Department of Children and Family 

Services, the Wisconsin Department of Health and Family Services, and the Iowa Department of 

Human Services. The study would not have been possible without their cooperation and financial 

support. We also want to recognize our other funders of the Midwest Study, the William T. Grant 

Foundation, the National Institute of Justice, and the National Institute of Mental Health. We also 

thank the University of Wisconsin Survey Center in Madison, Wisconsin, for their invaluable 

contribution to this study. We thank the Illinois Criminal Justice Information Authority and the 

Iowa Division of Criminal and Juvenile Justice Planning and Statistical Analysis Center for 

providing criminal history data. 

We also thank our colleagues Noel Bost, for his help with the literature review and conceptual 

design, and Wayne Osgood, for his insightful comments on earlier drafts of this work. 

This project was supported by Grant No. 2005-IJ-CX-0031/2005-IJ-CX-4031 awarded by the 

National Institute of Justice, Office of Justice Programs, and US Department of Justice. Points of 

view in this document are those of the author and do not necessarily represent the official position 

or policies of the US Department of Justice. 

 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table of Contents 

Introduction ...........................................................................1

Review of Relevant Literature ..........................................2

The Impact of Maltreatment and Child Welfare 

Experiences on Offending.............................................2

The Importance of Social Bonds at the Transition to 

Adulthood .....................................................................7

Contributions of the Current Study.............................10

Research Questions .........................................................12

Methods ...............................................................................15

Data and Sample .............................................................15

Survey Instruments .........................................................17

Analytic Methods............................................................18

Variables .........................................................................21

Dependent Variables...................................................21

Independent Variables ................................................24

Missing Data ...............................................................30

Findings ...............................................................................31

Offending Patterns ..........................................................31

Sample Comparisons ..................................................33

Variation in Offending by Gender ..............................37

Offending Over Time among Foster Youth................41

Predictors of Criminal Behavior .....................................48

Descriptive Statistics...................................................48

Results of the Poisson/Negative Binomial Models.....51

Predictors of Criminal Justice Involvement: The Risk for 

Arrest...............................................................................59

Descriptive Statistics...................................................59

Results of the Hazard Model.......................................60

Limitations of the Study..................................................68

Policy and Practice Implications .........................................71

References ...........................................................................77

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
List of Figures 

Figure 1. Self Reported Criminal Behavior: Midwest Study 

vs. Add Health (17-18 year olds).........................................34

Figure 2. Self Reported Criminal Behavior: Midwest Study 

vs. Add Health (19 year olds)..............................................35

Figure 3. Self Reported Criminal Behavior: Midwest Study 

vs. Add Health (21 year olds)..............................................36

Figure 4. Cumulative Probability of First Arrest.................60

Figure 5. Conditional Probability of First Arrest.................61

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
List of Tables 

Table 1. Self Reported Arrests: Midwest Study vs. Add 

Health Study ........................................................................37

Table 2. Percentage Engaging in Selected Offenses (17-18 

year olds) .............................................................................38

Table 3. Percentage Engaging in Selected Offenses (19 year 

olds) .....................................................................................39

Table 4. Percentage Engaging in Selected Offenses (21 year 

olds) .....................................................................................40

Table 5. Percentage of Foster Youth Engaging in Selected 

Offenses Over Time (n=438)...............................................42

Table 6. Profiles of Latent Classes (n=438) ........................44

Table 7. Characteristics of Latent Classes (n=438).............47

Table 8. Descriptive Statistics: Dependent Variables..........48

Table 9. Descriptive Statistics: ............................................50

Table 10. Estimates from Poisson Regression of Violent 

Criminal Behavior on Covariates (n=504) ..........................52

Table 11. Estimates from Poisson Regression of Violent 

Crime on Covariates with....................................................54

Table 12. Estimates from Negative Binomial Regression of 

Non-Violent Criminal Behavior ..........................................56

Table 13. Estimates from Poisson Regression of NonViolent Crime on Covariates with .......................................58

Table 14. Descriptive Statistics: Covariates in Hazard 

Models Predicting Arrest (n=728)......................................59

Table 15. Estimates from Cox Proportional Hazard 

Regression of Time to First Arrest on .................................62

Table 16. Estimates from Cox Proportional Hazard 

Regression of Time to First Arrest on Covariates By Gender

.............................................................................................67

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Introduction 

While the transition to adulthood has arguably become a more ambiguous and 

complex period for all youth (Furstenberg, Rumbaut, and Settersten, 2005), it may be 

particularly difficult for youth aging out of the child welfare system. Many youth placed 

under the care of the child welfare system have grown up in high risk families and 

neighborhoods. They enter adulthood with low educational status, little employment 

experience, mental health problems, high rates of homelessness, and limited social and 

financial resources (Collins, 2001). On top of these disadvantages, the transition to 

adulthood may be more abrupt for foster youth than for youth more generally. Whereas 

many young people move gradually toward independent adulthood, while continuing to 

rely on the support and guidance of families, foster youth “aging out”1

 of care lose the 

support of the child welfare system that has assumed the role of parent or guardian when 

they reach a particular age of majority. Although formal independent living services 

exist to help youth formerly in out-of-home2

 care move into adulthood, these youth are 

often on their own when making the transition (Courtney and Hughes-Heuring, 2005). 

In making the transition, youth in out-of-home care may be particularly at risk for 

engagement in crime or involvement with the criminal justice system (see Barth, 1990; 

 

1 Aging out refers to the process of being discharged from the child welfare system due to age ineligibility 

rather than being discharged due to adoption or reunification with one’s family of origin. 

2 We use the term “out-of-home care” to describe all youth placed under the supervision of the child 

welfare system for reasons of abuse or neglect rather than delinquent behavior. This includes youth placed 

in relative (kinship care) and non-relative foster homes, group homes/residential treatment facilities, 

adoptive placements, and independent living arrangements. 

1 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Courtney et al., 2001; Cusick and Courtney, 2007; Jones and Moses, 1984; Zimmerman, 

1982). Yet not all former foster youth end up in trouble. Many follow pathways into 

adulthood marked by more success than failure (Hines, Merdinger, and Wyatt, 2005). 

However, very little is known about the factors associated with adaptive functioning, and 

avoidance of criminal behavior or criminal justice contact in particular, of former foster 

youth. 

In this study, we examine criminal behavior and criminal justice system 

involvement among youth making the transition from out-of-home care to independent 

adulthood. We consider the importance of earlier experiences with maltreatment and 

within the child welfare system on criminal behavior during the transition to adulthood. 

In addition, we examine whether social bonds predict criminal behavior and the risk for 

criminal justice involvement among former foster youth. 

The results of this research are intended to provide a theoretically and empirically 

driven basis for future efforts at reducing negative outcomes for youth formerly in out-ofhome care as they become adults and for preventing crime among a particularly high risk 

population that has received limited attention by criminal justice researchers. 

Review of Relevant Literature 

The Impact of Maltreatment and Child Welfare Experiences on Offending 

The link between childhood experiences of maltreatment and later delinquency 

represents an area of growing interest among researchers and child welfare practitioners. 

Although heavily debated due to methodological issues, studies generally show a positive 

2 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
association between maltreatment, including physical abuse and neglect, and crime 

(McCord, 1983; Widom, 1989; Smith and Thornberry, 1995; Maxfield and Widom, 

1996). While such research examines the link between the childhood experiences of 

maltreatment, which if detected may lead to involvement with the child welfare system, 

and later crime, few studies look at experiences within the system that may influence 

offending. Youth who are placed in out-of-home care are exposed to a system of services 

that impact behavior. There is, however, considerable variation across individuals in the 

duration, number, and type of placements they experience (Courtney and Wong, 1996; 

Wulczyn, Kogan, and Harden, 2003). For example, the length of stay in out-of-home 

care across all children who exited care in 2001 varied from less than 1 month (19 

percent) to greater than 5 years (9 percent), with a median duration of 12 months (U.S. 

Department of Health and Human Services, 2003). Of the 542,000 children in out-ofhome care in 2001, 48 percent were in non-relative foster family homes, 24 percent were 

in relative family homes, 18 percent were in group homes or institutions, 4 percent were 

in pre-adoptive homes, and 6 percent were in other placement types (U.S. Department of 

Health and Human Services, 2003).3 

It is in relation to varying placement experiences such as these that a small 

number of child welfare researchers have examined the role of youths’ placement 

experiences on offending behaviors. An early study by Runyan and Gould (1985) found 

that number of foster home placements was positively correlated with criminal behavior 

 

3

 These figures are based on all children in foster care in 2001, and therefore, these figures may differ from our sample 

based on differences in age distribution. The median age at entry and exit of all foster youth in 2001 was 8.7 and 10.2, 

respectively. We expect that placement experiences of our sample, containing only youth between the ages of 17-21, 

will differ from the total population of foster children. For example, older foster children are much less likely to live in 

a foster family setting than younger children (see Wertheimer, 2002). 

3 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
among youth aged 11 to 18 at a bivariate level. The authors attribute this relationship, 

however, to earlier behavior problems; children were removed from homes, and therefore 

experienced additional placements due to their behavior problems. Widom (1991) 

suggests a similar pattern. More specifically, she found that children with a lower 

number of placements and for whom the first placement was longer than ten years had 

the lowest rates of delinquency and adult criminality. Similarly, Jonson-Reid and Barth 

(2000) found that children with multiple placements had a higher risk of incarceration 

during adolescence. 

By viewing offending among former foster youth through a life course 

perspective (Elder, 1985), we recognize that the path one takes during the transition 

adulthood is largely dependent on earlier life events. For youth leaving out-of-home 

care, behavior during the transition may be partially explained by earlier experiences of 

abuse or neglect as well as unstable or negative experiences within the child welfare 

system. It may be that these negative experiences decrease child well being and result in 

greater behavior problems among youth. It may also be that instability or placement in a 

group home setting is an indicator of a difficult case; a youth already showing significant 

problem behavior, a parent, caregiver, or household environment with problems, or both. 

Independent Living Services 

In addition to experiences with out-of-home care placements, specific services 

provided by the child welfare system to assist in the transition to adulthood may be 

important for later behavior. In response to the needs of youth once they leave care, the 

federal government has, since 1986, provided funding for independent living programs 

intended to assist in the transition to adulthood. In 1985, the Independent Living 

4 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Initiative (Public Law 99-272), under title IV-E of the Social Security Act, provided 

states federal funds to help youth develop the skills needed to live independently after 

leaving care. In 1993, funding for the Independent Living Program (ILP) was 

reauthorized (Public Law 103-66), which allowed for longer-term planning of state 

programs. Services included outreach programs to attract eligible youth, training in daily 

living skills, education and employment assistance, counseling, case management, and a 

written transitional independent living plan. As an amendment to Title IV-E, The Foster 

Care Independence Act (FCIA) of 1999 (Public Law 106-169) doubled federal funding to 

$140 million per year and provides states greater flexibility in the use of these funds, 

extends age restrictions, and provides funding for education and training vouchers. 

Despite these legislative efforts, the number of youth who actually benefit from 

independent living services as they transition to adulthood is unknown. A report by the 

United States General Accounting Office (GAO) found that only about 60 percent of all 

eligible youth received some type of independent living service in 1998 (GAO, 1999). 

Moreover, the efficacy of independent living services is, as of yet, uncertain. Although 

Collins (2001) suggests that there is empirical evidence that youth who receive 

independent living services have greater success transitioning to adulthood, she cautions 

that the sparse and methodologically flawed state of research precludes a definitive 

statement of service usefulness. No study to date has examined how variation in receipt 

of independent living services affects criminal behavior during early adulthood. 

Race, Placement, and Crime 

A neglected aspect in research noted above on the link between out-of-home care 

experiences and delinquency or crime is racial disparity. Studies of delinquency show 

5 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
that African American youth have higher rates of both official and self-reported 

offending than Caucasian youth (Elliot and Ageton, 1980; Hawkins et al., 2000), 

particularly for serious violent behaviors (McNulty and Bellair, 2003). In addition to 

higher rates of criminal behavior, African American children are disproportionately 

represented within the child welfare system (Shyne and Schroeder, 1978; Stehno, 1982; 

Lu et al., 2004). A recent volume of works on the overrepresentation of African 

American children in the child welfare system reports that although African American 

children comprised 15 percent of the U.S. child population in 1999, they constituted 45 

percent of the children in out-of-home care. Conversely, white children, who comprised 

60 percent of the child population, accounted for only 36 percent of children in out-ofhome care (Derezotes, Poertner and Testa, 2004). 

Of those children requiring out-of-home care, experiences within the system also 

differ by race. In an extensive review of the literature, Courtney et al (1996) found that 

African American children received fewer services from the child welfare system and 

experienced poorer case outcomes, including longer stays in care, greater reentry rates, 

less placement stability, and lower adoption rates. Moreover youth who are placed in 

kinship care, an arrangement that is predominantly composed of African American youth 

(Testa, 1997), typically remain separated from their parents, and linger in the child 

welfare system longer than those who are not placed with kin. 

Although African American youth are both more likely to engage in criminal 

behaviors and to have more negative experiences within the child welfare system, few 

studies to date have examined how the potential variation in specific placement 

experiences by race is, or is not may, related to crime during the transition to adulthood. 

6 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Given the disparities between the experiences of African Americans and other groups in 

the child welfare system, it is important to consider the possibility that placement 

experiences may differentially influence later criminal behavior and justice system 

involvement of these groups. 

The Importance of Social Bonds at the Transition to Adulthood 

Drawing on the literature noted above, we recognize that experiences, both from 

being abused or neglected and from involvement with the child welfare system, are 

unique to youth placed in out-of-home care and variation in these experiences may 

predict later offending. Yet, maltreatment histories and foster care experiences alone 

likely do not explain why some former foster youth engage in criminal behavior into 

adulthood while others do not. To more fully understand offending within this 

population, we turn to what is known to set youth toward a successful transition to 

adulthood and to avoid engagement in crime more specifically. 

Although there are many pathways into adulthood (Maow, 2005; Osgood, Ruth 

Eccles, Jacobs, and Barber, 2005; Shanahan, 2000) successfully navigating the transition 

is largely a function of the support, guidance, and resources offered by families. More so 

than in a previous generation, transitioning to adulthood now requires parental assistance 

(Furstenberg, Rumbaut, and Settersten, 2005). Young people rely on their families for a 

range of emotional and tangible support (Schoeni and Ross, 2005). Young people may 

also receive a “patchwork of institutional support as they leave adolescence” 

(Furstenberg, Rumbaut, and Settersten, 2005, p. 20). Education and employment 

institutions are two common institutions. Completing high school and pursuing a college 

education increase employment opportunities in adulthood. Similarly, employment 

7 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
opportunities nurture the development of work related skills and set the stage for future 

responsibilities and careers as adults. 

Social bond theory (Hirschi, 1969) suggests that attachments to adults and 

commitment to and involvement with conventional social institutions reduce crime and 

delinquency by acting as agents of informal social control (Sampson and Laub, 1990). 

Bonds to parents or school discourage delinquency during adolescence (Cernkovich and 

Giordano, 1992; Felson and Staff, 2006; Hirshi, 1969; Sampson and Laub, 1993) while 

bonds to spouses and jobs discourage offending during adulthood (Horney et al.,1995; 

Laub et al., 1998; Sampson and Laub, 1993). Attachment and commitment to and 

involvement with families and educational or employment institutions are in many ways 

the building blocks to a successful transition to adulthood because they facilitate the 

exploration and gradual movement toward independence that has increasingly come to 

define the transition to adulthood. However, they also may play a role in discouraging 

negative behavior more specifically. 

Here we review detail the many social bonds that may be related to crime, with a 

focus on the notion that establishing these bonds at the transition to adulthood may be 

particularly difficult for foster youth. 

Parents and Caregivers 

By being placed in out-of-home care, foster youth all have had disrupted family 

relationships, which could lead to weaker social bonds to families during the transition to 

adulthood. In spite of this, many former foster youth report have ongoing contact with 

their families of origin, including parents (Barth, 1990; Cook et al., 1991; Courtney et al., 

2001; Courtney and Dworsky, 2006; Festinger, 1983; Frost and Jurich, 1983; Harai, 

1980; Jones and Moses, 1984; Zimmerman, 1992). However, compared to a general 

8 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
population, foster youth are less likely to report being close to parents (Perry, 2006). A 

recent study of foster youth found that only 52 percent reported being somewhat or very 

close to mothers and only 28 percent reported being somewhat or very close to fathers 

during the transition to adulthood (Courtney et al., 2001). 

For youth placed in out-of-home care, a parent can include individuals beyond 

biological parents. Foster parents, a group home worker, or even the larger child welfare 

system that has legally assumed guardianship may play an important role for foster youth. 

Yet, as with biological parents, not all youth feel attached to these parental figures. 

Former foster youth generally report feeling satisfied with their experiences in foster care 

(Chapman, Wall, and Barth, 2004; Courtney et al., 2001; Courtney and Dworsky, 2006) 

and some report close relationships with foster parents or other caregivers. In this study, 

we examine attachment not only to biological parents, but also this range of individuals 

that play a parental role to foster youth. 

Education and Employment 

 Education and work are also central to the lives of young people during the 

transition to adulthood. Although changes in federal legislation increased the funding 

provided for education and training opportunities for former foster youth making the 

transition to adulthood4

, studies suggest that many former foster youth are disconnected 

 

4 The Education and Training Voucher (ETV) Program resulted from the passage of child welfare 

legislation which provided states with greater funding and flexibility to assist youth during the transition to 

adulthood. The Foster Care Independence Act of 1999 (Public Law 106-169), which established the John 

H. Chafee Foster Care Independence Program, doubled the funding provided to states for concrete living 

needs, such as housing, and extended that age youth can remain in foster care from 18 to 21 years (Kessler, 

2004; Massinga and Pecora, 2004). The Promoting Safe and Stable Families Amendment of 2001 provided 

the federal dollars for Education and Training Vouchers (ETV). 

9 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
from educational and employment pursuits. Studies show that individuals formerly 

placed in out-of-home care have fewer years of education and many foster youth do not 

graduate from high school (Barth, 1990; Cook et al., 1991; Courtney et al., 2001; 

Courtney and Dworsky, 2007; Festinger, 1983; Frost and Jurich, 1983; Jones and Moses, 

1984; Zimmerman, 1992). A study by Courtney et al. (2001) found that 37 percent of 

former foster youth had not completed high school or obtained a GED, and only 9 percent 

had taken any college courses within 12 to 18 months of discharge from care. 

Unemployment rates are higher among former foster youth than the general population of 

young people (Cook et al., 1991; Goerge et al., 2001; Jones and Moses, 1984; 

Zimmerman, 1982) and having serious financial trouble during the transition to adulthood 

is common among this population (Dworsky, 2005). 

Contributions of the Current Study 

Of course, not all former foster youth have weak bonds to parents or educational 

and employment institutions. Some have ongoing, close relationships with biological or 

foster families, attend college, and obtain full-time, stable employment as they leave the 

child welfare system and enter adulthood. The focus of this study is to examine which 

factors, above and beyond maltreatment and out-of-home care placement experiences are 

predictive of criminal behavior and criminal justice involvement among these young 

people. 

This study contributes to the knowledge base on crime among foster youth 

transitioning to adulthood in a number of ways. The first concerns our study design and 

data sources. We use data from largest longitudinal study of young people aging out of 

foster care and transitioning to adulthood since the passage of the John Chafee Foster 

10 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Care Independence Act in 1999. The use of both official and self-reported data allows us 

to examine behaviors that may not come to the attention of authorities as well as those 

which elicit legal action. The use of both data sources also allows us to examine 

offending for the full sample, including those leaving the study over time. Although 

relevant recent work (see Ryan, Testa, and Zhai, 2008) examines crime among male 

foster youth only, our study includes both males and females. We feel this is another 

important contribution of our study as all too often crime among females and, in 

particular among female foster youth, is given less attention because it is less common, 

although no less troubling, than among males. 

Second, out study expands on prior research that has examined the link between 

experiences with the child welfare system and outcomes. For example, previous studies 

have examined the relationship between placement instability and offending (see Runyan 

and Gould, 1985; Jonson-Reid and Barth, 2000; Ryan, Testa, and Zhai, 2008). Yet these 

studies focused on outcomes during childhood and adolescence rather than during the 

transition to adulthood, as is the focus of our study. In addition, our study is the first to 

examine the link between receipt of independent living services from the child welfare 

system and criminal behavior. 

Third, our study contributes substantively to the growing body of research on both 

social bonds and crime during the transition to adulthood more generally and social 

bonds and crime among foster youth more specifically. Although studies have examined 

the effect of social bonds on crime during the transition to adulthood (Piquero, Brame, 

Mazerolle, and Haapanen, 2002), the focus has tended to be on job stability and marriage 

in the mid- to-late 20’s and early 30’s rather than factors that may be more salient in the 

11 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
very early transition years. Less is known about the influence of bonds to families, 

particularly parents or caregivers, education, and early employment, on crime as one 

prepares for the transition to adulthood. In addition, although recent work has examined 

the relationship between social bonds and crime among foster youth (see Ryan, Testa, 

and Zhai, 2008), such work is limited by focusing on adolescence rather than the 

transition to adulthood and considers only bonds to foster caregivers rather than to 

biological parents. 

Research Questions 

1) Are offending patterns during the early transition to adulthood (ages 17-22) 

among youth formerly in out-of-home care different from those of the general 

population? 

 Before examining what predicts variations in criminal behavior or criminal justice 

involvement, we first identify whether offending patterns during the early transition to 

adulthood among foster youth are the same or differ from those seen in the general 

population. The early transition to adulthood marks an important stage in the life course 

to examine offending patterns as it is during this period from the end of high school 

through the early twenties that offending, on average, declines. Data show that offending 

increases during adolescence, reaches a peak around age 16 (for property offenses) and 

18 (for violent offenses) and then declines thereafter (Hirschi and Gottfredson, 1983; 

Farrington, 1986). We examine whether foster youth display this same general pattern. 

2) Do experiences in out-of-home care, including number of placements, placement 

type, age at entry, and receipt of independent living services predict later criminal 

12 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
behavior or criminal justice involvement during the transition to adulthood among 

youth aging out of the child welfare system? Is the relationship between out-ofhome care experiences and crime moderated by race? 

The limited body of prior literature on the relationship between placement 

experiences and criminal behavior suggests that youth who experience more “negative” 

placements are those who are more likely to offend. Similarly, it has been hypothesized, 

but never examined, that youth who receive aid from the child welfare system in making 

the transition to adulthood will have fewer negative outcomes. It could be that the 

relationship between out-of-home care experiences and subsequent offending is spurious, 

and that both are influenced by already existing problem behaviors. Those youth who 

exhibit problem behaviors may be moved into and out of placements, placed in group 

homes, have strained relationships with caregivers, and not receive the support of the 

child welfare system. Controlling for prior delinquency as well as background individual 

and family demographic factors and maltreatment history, we examine how foster care 

experiences are related to criminal behavior during the transition to adulthood. 

In addition, we examine whether the relationship between placement experiences 

and criminal behavior varies by race. As noted earlier, African American youth have 

different experiences in out-of-home care than youth of other races. Negative effects of 

placement experiences may be greater among African American youth. Therefore, we 

test for statistical interactions between placement experiences and race. 

3) Above and beyond prior experiences with maltreatment and within the child 

welfare system, do the bonds to parents or caregivers, education, or employment 

13 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
that foster youth have as they approach the transition to adulthood predict later 

criminal behavior or criminal justice involvement? 

With this final research question, we examine whether social bonds that youth 

have as they approach the transition to adulthood predict criminal behavior or criminal 

justice involvement during the transition. Because our focus is on the early part of the 

transition, we examine social bonds that we hypothesize may be most important at this 

point in the life stage. In particular, we examine bonds to parents or caregivers, school, 

work, and the child welfare system, while controlling for earlier experiences with 

maltreatment and out-of-home care, background risk factors, and demographic 

characteristics. 

14 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Methods 

Data and Sample 

Data for this project come from The Midwest Study of the Adult Functioning of 

Former Foster Youth, which is a longitudinal panel study that is part of a collaborative 

effort of the state public child welfare agencies in Illinois, Iowa, and Wisconsin, Chapin 

Hall at the University of Chicago, and the University of Washington. The larger purpose 

of the Midwest Study is to gather information about services provided to selected youth 

served in participating states and the adult self-sufficiency outcomes achieved by the 

youth. The participating states fund and/or operate the full range of services supported 

by the Chafee Foster Care Independence Program (e.g., life skills training, mentoring, 

tutoring, employment services, transitional housing), but these services vary considerably 

in availability between and within the states. In addition, the policy regimes differ across 

the three states in ways that affect the supports available to youth who age out of care. 

For example, at the time of this study, youth in Illinois were legally permitted to remain 

in care until age 21, while youth in Iowa and Wisconsin remained in care until 

approximately age 18. 

 Youth from the three states who met the following basic criteria were eligible for 

inclusion in the original sample: (1) they reached the age of 17 years old while in out-ofhome care, (2) they had been in care for at least one year prior to their 17th birthday, and 

3) they were placed in out-of-home care for reasons of abuse or neglect rather than 

delinquency. In the states of Iowa and Wisconsin, the sample reflects the universe of 

15 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
youth in out-of-home care who fit these criteria. In Illinois, a random sample of youth 

were selected, who represent two-thirds of those youth in out-of-home care that fit the 

sampling criteria. A group of 767 youths who met the sample selection criteria was 

identified. 

Survey data were collected directly from the youth in the sample over three 

waves. Respondents participated in in-person interviews that were approximately ninety 

minutes long. The interview schedule was made up almost entirely of fixed response 

questions. During the first wave of interviews, conducted between May 2002 and March 

2003, 732 interviews were completed, for a response rate of approximately 95 percent. 

Youth were between the ages of 17 and 18 when they were first interviewed. The second 

interview took place in March through December 2004, between respondents’19th and 

20th birthdays. At Wave 2, 603 youth were located, for a follow-up response rate of 83 

percent. The third wave of interviews, conducted between March 2006 and January 

2007, took place as soon as possible after their 21st birthday. At Wave 3, 590 of the 

original sample took part, for a response rate of 81 percent. 

To supplement the survey data, we accessed official arrest5

 data from each state 

for this study. Youth were matched to arrest records based on identifying information 

such as name, date of birth, social security number, gender, and race. In each of the three 

state databases, we included all criminal arrests that occurred between respondents’ Wave 

1 interview and August 31, 2007, by which time all of the study participants were at least 

 

5

 We note that only data on arrests are used in this study; not all arrests result in a conviction. 

16 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
21 years old.6

 Official arrest information was obtained for 728 of the original 732 

sample.7

 

Survey Instruments 

A main source of information for this research comes from survey data collected 

over three waves. As will be discussed further, independent variables examined in this 

study come largely from the Wave 1 interview. The survey instrument at Wave 1 

targeted a number of areas that prior research suggests might be related to later offending 

for this population, including: family background, experiences prior to and during out-ofhome care, maltreatment history, health status, mental health status, delinquency, 

substance abuse and other high risk behaviors, teen parenthood, receipt of independent 

living services, and social support systems. In developing the survey, emphasis was 

placed on using standardized measures that have been employed in other large-scale 

studies of youth (e.g., the National Longitudinal Study of Adolescent Health). Questions 

about respondents’ experiences in out-of-home care including ongoing relations with 

foster care providers and the youth’s family of origin were taken from Dr. Courtney’s 

earlier study in Wisconsin. Questions about independent living services were based on 

the range of potential services identified by the Service Standards and Outcome Measures 

Workgroup appointed by the U.S. Children’s Bureau to help create implementation 

regulations for the John Chafee Foster Care Independence Program. Hence, these 

questions reflect current practice in the field. 

 

6

 We chose August 31, 2007 as the end of the study period in order to maximize the amount of time post-wave 1 

interview in which to measure arrests that were available in the data. 

7

 Four respondents did not provide permission to access administrative records. 

17 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Analytic Methods 

 To answer our research questions, we used a combination of statistical methods, 

including bivariate and multivariate approaches. To address the first research question, 

we first compared the prevalence of offending across a range of criminal behaviors from 

our sample at ages 17-18, when offending should be at it’s peak, through ages 19 and 21, 

when offending should be declining, to those from the Add Health study8. We also 

compared self reported arrest rates of our sample to the national sample. We also 

examined changes in offending within our sample of foster youth that participated in all 

three interviews and responded to questions about criminal behavior (n=438). T-tests for 

differences in proportions are used to compare foster youth to the Add Health sample and 

within the Midwest Study sample over time. We next identified groups of foster youth 

who appear on different offending or desisting paths as they enter adulthood. Previous 

research has identified categories of offenders (Moffitt, 1993; Chung et al., 2002) and 

developed methods to predict different offending trajectories (see Nagin and Land, 1993; 

Nagin and Trenblay, 1999; Bushway et al., 2001). Based on the notion that there are 

different categories of offenders, we conducted a latent class analysis to determine 

whether our sample of foster youth consist of distinct classes of offenders during the 

early transition to adulthood. These descriptive analyses are helpful in providing a 

picture of the overall pattern of offending during the early transition to adulthood for 

 

8

 This research uses data from Add Health, a program project designed by J. Richard Udry, Peter S. Bearman, and 

Kathleen Mullan Harris, and funded by a grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of 

Child Health and Human Development, with cooperative funding from 17 other agencies. Special acknowledgment is 

due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Persons interested in obtaining data 

files from Add Health should contact Add Health, Carolina Population Center, 123 W. Franklin Street, Chapel Hill, NC 

27516-2524 (addhealth@unc.edu). No direct support was received from grant P01-HD31921 for this analysis. 

18 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
former foster youth, as well as identifying the proportion of the sample that appear to be 

continuing or desisting from crime. 

To address the second and third research questions, we used two multivariate 

approaches, First, we estimated a series of Poisson and negative binomial regression 

models to examine Wave 1 predictors of self-reported criminal behavior (violent and 

non-violent) at age 21 (Wave 3). We conducted Poisson and negative binomial 

regression analyses because the dependent variables for criminal behavior, described 

below, had a large number of zero (no criminal behavior) values and a positive skew. 

However, rather than use a logistic regression which would treat all levels of offending 

the same (no criminal behavior vs. any criminal behavior), the Poisson and negative 

binomial analyses allow us to model variation among “high” and “low” offenders. When 

the deviance statistic for a Poisson model indicated over dispersion (when the true 

variance is bigger than the mean), the negative binomial model was favored. We 

controlled for background risk factors and demographic characteristics and tested for 

statistical interactions between race and placement experiences. Our sample included 

504 youth who responded to questions about criminal behavior during the Wave 3 

interview. 9

 

 

9 Of those 590 youth interviewed at Wave 3, 86 youth refused or did not respond to the questions on 

criminal behavior. Because some of the questions in the interview dealt with sensitive topics that study 

participants might not have felt comfortable talking with the interviewer about, a portion was administered 

using Audio Computer Aided Self Interviewing (ACASI). Study participants listened to a recording of 

these questions through headphones and entered their responses into a computer. Questions about criminal 

behavior were part of the ACASI. Therefore, not taking the ACASI explains the majority (n=53) of those 

86 who did not respond to the criminal behavior questions. This included 35 youth who were interviewed 

by telephone and 18 who refused to complete the ACASI or were unable to do so (e.g. they were unable to 

read). Although being incarcerated did not necessarily preclude youth from taking the ACASI (7 

incarcerated youth did not complete the ACASI), 29 of the remaining 33 youth who did complete the 

ACASI but did not respond to criminal behavior questions were incarcerated during the Wave 3 interview. 

Twelve of these youth had been incarcerated for more than 12 months. 

19 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Second, we estimated Cox proportional hazard models, or “survival models” to 

examine whether out-of-home care experiences and social bonds predict the risk for 

arrest during the early transition to adulthood. Compared to the survey data analyses, in 

which self reported criminal behavior is the outcome, these hazard models offer three 

benefits. First, all survey respondents can be included in the models, rather than only 

those who participated in the Wave 3 interview. Second, we are able to measure official 

arrests for a longer period than was available with the survey data. Third, these models 

allow us to examine the timing of arrest, rather than simply the occurrence of an arrest. 

Such models are useful for examining time to event data, such as the time to a first arrest, 

because they allow for censored observations of the experiences of individual s that do 

not experience the event (Allison, 1995). The model estimated is a semi-parametric 

survival model that does not require specification of a baseline hazard function.10 The 

hazard can be thought of as the instantaneous risk of experiencing an arrest at time t, 

given that an arrest has not already occurred prior to time In our analyses, t = 0 represents 

the time at which the Wave 1 interview was conducted. The general form of the Cox 

proportional hazard regression equation is 

exp()()( )... 0 i 2211 i i i kk = thth β χ + β χ + + β χ , 

 

10 Prior research on time to arrest as a measure of re-arrest or recidivism suggest the use of a parametric estimates 

which allows for the risk for arrest to be highest immediately following release and then decrease, or to be highest 

immediately following release, to then decrease, and subsequently increase again. Although we are examining arrest as 

an outcome, we are not examining arrest as an indicator of recidivism, as was the focus of these earlier studies. 

Therefore, we have no theoretical reason to hypothesize that the hazard function follows a particular parametric 

distribution. The age crime curve would suggest that the hazard function of arrests from late adolescence into early 

adulthood might take a functional form that is monotonically decreasing, thus following a Weibull distribution. We 

found that our data more closely follows a Weibull distribution than the log-normal distribution that has been used in 

recidivism studies. Regression analyses specifying a Weibull distribution and using a Cox model, however, produced 

the same results. Because our interest is in the theoretical relationship between covariates and the risk for arrest rather 

than the specific form of the duration dependency, we chose to present results of the Cox model which is less sensitive 

to the functional form of the model (Box-Steffensmeier and Jones, 2004). 

20 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
and the hazard rate for the ith individual is 

 ) exp()()( 0 i = β′xthth , 

where is the baseline hazard function. Once an individual experiences an arrest, 

they are removed from the risk set. We present model results for the full sample and 

separately by gender. 

( ) 0 th

Variables 

Dependent Variables 

Our main outcomes are self-reported criminal behavior and official arrest. First, 

self reported criminal behavior was measured during each wave of the survey, based on 

questions from the National Longitudinal Study of Adolescent Health (Add Health). For 

the bivariate analyses, we examined ten items, coded as ‘yes’ if the respondent reported 

engaging in the behavior during the past 12 months and ‘no’ if they had not reported the 

behavior. These include a range of criminal behaviors from stealing something worth 

less than $50, to vandalism, to using or threatening to use a weapon to get something. 

For multivariate (negative binomial) regression analyses, we examined two selfreported criminal behavior dependent variables: 1) any violent behavior, and 2) any nonviolent behavior,11 following the example of LaGrange and Silverman (1999) and 

Haynie and Giordano (2005) who each used a similar self-reported crime outcomes. 

Respondents were asked a series of questions at Wave 3 about their criminal behavior. 

 

11 We also estimated models for an outcome of any criminal behavior, which combined violent and non-violent 

behavior, and determined that the model using the full criminal behavior scale was not as informative as the models 

that looked at violent and non-violent crime separately. Therefore, separate violent and non-violent scales are 

presented as outcomes in this report. 

21 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Each item was measured on a scale of zero to three for incidence frequency, with zero 

indicating they had never engaged in the activity and 3 indicating they had engaged in the

activity more than 5 times.

rime 

stealing 

 

12 Questionnaire items were grouped into non-violent and 

violent scales; items were summed to create outcome measures for any non-violent crime 

(8 items, alpha = .703) and any violent crime (4 items, alpha = .736). Non-violent c

included deliberately damaging property, stealing something worth less than $50, 

something worth more than $50, going into a building or house to steal something, selling 

marijuana or other drugs, buying, selling, or holding stolen property, writing a bad check, 

and using someone else’s credit card, bank card, or automatic teller card without their 

permission or knowledge. The violent crime scale included using or threatening to use a 

weapon to get something, taking part in a group physical fight, using a weapon in a fight, 

and hurting someone badly enough in a physical fight that he/she needed medical 

attention. Outliers were recoded to help reduce skew. As noted above, of the 590 

respondents who participated in the Wave 3 survey, only 504 responded to items about 

criminal behavior. Therefore, these regression analyses were conducted on these 504 

respondents with valid outcome data. 

To estimate the risk for arrest, we used official criminal arrest records to measure 

the dependent variable. For these analyses, our outcome of interest is the first arrest13,14

12 0 = never, 1 = 1 or 2 times, 2 = 3 or 4 times, 3 = more than 5 times. 

13 Forty-two respondents were arrested for minor offenses, mainly traffic offenses such as speeding or driving without 

a valid license, or public order offenses, such as disorderly conduct. We did not include such arrests in this study as 

these minor offenses may be systematically recorded differently across the three states. 

14 Only arrests that occurred in the state in which respondents were residing during the wave 1 interview are included. 

Therefore, our data do not contain arrests that occurred outside of the residing state at Wave 1. An arrest in another 

state is possible, particularly if an individual moved out of state. As noted by Schmidt and Witte (1988), covariates that 

correlate positively with mobility may therefore have a spurious correlation with the outcome, yet data limitations for 

such analyses do not permit an easy solution and the use of arrest data from only one state in survival analyses is 

22 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
during the transition from adolescence to adulthood. We assume that all of the 

respondents are at-risk for arrest at the time of their first interview and estimate a hazard 

model that predicts when that first arrest occurs. Hazard models utilize two dependent 

variables to capture both the occurrence and timing of an event. First, the survival time 

reflects the duration of time between the beginning of the observation period (i.e., the 

date of the Wave 1 interview15) and either the date of first arrest or the end of the 

observation period (i.e., August 31, 2007). A second variable indicates whether an arrest 

occurred during the observation period, or in other words, if the respondent “failed”. 

This variable is coded ‘1’if the respondent was arrested and ‘0’ if he/she was not. As all 

respondents were 17 or 18 years old at the Wave 1 interview, our dependent variable 

captures arrests that occurred during the early transition to adulthood, between age 17 at 

the Wave 1 interview to nearly 24 years at the end of the observation period16. Unlike 

survey data analyses, which only included respondents who were interviewed at Wave 3, 

these analyses included all respondents for which official arrest records were available 

(n=728). 

 

common (see recidivism studies by Bottcher and Ezell, 2005; Schmidt and Witte, 1988; Visher, Lattimore, and Linster, 

1991). However, out-of-state mobility is low among this population. We found that at least 30 individuals in our 

sample moved out of state at some point after their first interview, although the date is unknown. Analyses excluding 

these individuals resulted in no differences across survival models, suggesting that our substantive results are not 

impacted by unobserved out-of-state arrests. 

15 Wave 1 interviews were conducted throughout 2002 and early 2003. 

16 At the end of the observation period (8/31/2007) the mean age was 22.7, with ages ranging from 21.8 to 23.6 years. 

23 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Independent Variables 

 In both the Poisson/negative binomial regression and proportional hazard 

regression analyses, independent variables were measured from the Wave 1 survey. 

Measurement of all independent variables is described below. 

Social Bonds 

We measured bonds to parents as the degree of closeness respondents reported 

feeling toward parents, based on a 4-point ordinal scale (‘1’= not at all close; ‘2’ = not 

very close; ‘3’ = somewhat close; ‘4’ = very close). Separate measures were included for 

closeness to mother (biological or step-mother) and closeness to father (biological or 

step-father).17 Because young people placed in out-of-home care also have parental or 

family figures in the form of their out-of-home caregiver, we also created a measure of 

closeness to caregiver (non-relative foster parents, relatives in kinship care placements, or 

adults working in group homes in which the respondent was placed during the Wave 1 

interview), also coded on the same 4-point ordinal scale. 18 

We measured bonds to educational and employment institutions through three 

variables. First, school enrollment was measured as a dichotomous variable coded ‘1’ if 

the respondent was enrolled in some form of school (high school, vocational school, or 

college) at the time of the Wave 1 interview and ‘0’ otherwise. We measured 

commitment to educational pursuits through a dichotomous variable of educational 

 

17 We also tested the effect of closeness to grandparents, which was not significant in any models, and therefore, not 

included in the final models reported here. 

18 Respondents without a living mother or father or who did not know if their parent was alive did not receive questions 

about closeness to biological parent. For these cases systematically missing a value, we coded the closeness to mother 

or closeness to father variables as ‘not at all close’ to represent the lack of this connection. In regression models, we 

included an indicator variable coded ‘1’ if the respondent did not have the specified parental figure on the item and ‘0’ 

otherwise. Similarly, respondents in independent living settings were coded as ‘not at all close’ to caregiver because no 

parental figure or guardian is present in this type of placement. 

24 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
expectations, coded ‘1’ if the respondent reported that he/she would like to graduate from 

college or beyond and ‘0’ otherwise. Having bonds to employment was measured 

through employment status at Wave 1, coded ‘1’ if the respondent was employed and ‘0’ 

otherwise.19 

In addition to the measures of social bonds noted above, we used a global 

measure of perceived social support20, which captures support across emotional, tangible, 

positive social interaction, and affectionate domains. This measure is based on the MOS 

Social Support Survey (Sherbourne and Stewart, 1991). Respondents were asked to 

indicate on a 5-point scale how often each type of support was available to them (i.e., ‘1’ 

= none of the time; ‘2’ = a little of the time; ‘3’ = some of the time; ‘4’ = most of the 

time; ‘5’ = all of the time). Each of 19 items were summed and converted to a score on a 

scale of 0-10021, with higher scores indicating greater social support.22 The alpha 

reliability score for these 19 items is .96. 

In addition to attachment to parents, school, and employment, we measured 

attachment to the child welfare system. We asked respondents how likely they were to 

turn to the child welfare system for assistance with personal, employment, family, 

housing, health, or other problems or for financial help after being discharged. 

 

19 In analyses not shown, we examined the effect working more than 20 hours per week, as prior research has found 

that high intensity employment is related to offending among adolescents. We found no relationship between this 

measure and the risk for arrest. 

20 Although empirical support is limited, scholars have argued that social support, both expressive and instrumental, 

may reduce an individual’s likelihood of offending (Colvin, Cullen, and Vander, 2002; Cullen, 1994). 

21 Documentation on this social support scale can be found in Sherbourne and Stewart, 1991 and at 

http://www.rand.org/health/surveys_tools/mos/mos_socialsupport_scoring.html. 

22 In addition to the global measure, we also tested the effect of each social support sub-scale (emotional, tangible, 

positive social interaction, and affectionate). We found similar effects of each sub-scale on the outcome, and therefore 

opted to include only the full social support scale in the final models. 

25 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Responses for each of the seven types of assistance were coded on a 4-point ordinal scale 

(‘1’ = very unlikely; ‘2’ = unlikely; ‘3’ = likely; ‘4’ = very likely). We created an overall 

scale of the likelihood of turning to the child welfare system for assistance after discharge 

as the mean of these seven items. The alpha reliability score for these seven items is .92. 

Maltreatment and Out-of-Home Care Experiences 

Although all the young people in the sample entered out-of-home care due to 

reasons of abuse or neglect, and therefore, represent a maltreated population, there was 

variation in the extent of respondents’ abuse history. Therefore, we included a measure 

of the number of different acts of physical abuse the respondent reported having 

experienced prior to entering care, as well as a measure of the number of different acts of 

neglect experienced.23 Prior sexual abuse or assault was also included as a dichotomous 

variable coded ‘1’ if the respondent ever experienced either type of victimization and ‘0’ 

otherwise. 

The goal of out-of-home care is to protect children and youth and assist in 

positive development, yet certain placement experiences may negatively affect 

individuals and impede a successful transition to adulthood, and more specifically, may 

 

23 Physical abuse includes being thrown or pushed, hit hard with a fist or kicked or slapped really hard, 

being beaten up (hit or kicked repeatedly), being attacked with a weapon, being tied up, held down, or 

blindfolded so that they could not protect themselves, attempted to be choked, strangled, or smothered, and 

being locked in a room or closet. Neglect includes that the respondent had a serious illness or injury or 

physical disability, but his/her caretakers ignored it or failed to obtain necessary medical or remedial 

treatment for it; caretakers failed to help respondent with washing and grooming so that he/she was often 

dirty, had uncombed hair, or wore dirty clothes; caretakers often failed to provide regular meals for 

respondent so that he/she had to go hungry or ask other people for food; respondent had to go without 

things that he/she needed because family's paycheck was spent on the adult's interests; respondent was 

required to do chores that were too difficult or dangerous; respondent was actually abandoned by a 

caretaker; respondent’s caretakers were physically or emotionally ill to the extent that he or she was unable 

to care for respondent or pay attention to respondent because of the illness; respondent missed school 

because he/she had to stay home to take care of a parent, grandparent, brother or sister, or to do chores; 

respondents caretakers failed to protect you from being physically harmed by someone else. 

26 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
be related to arrests. For example, arrest has been associated with multiple placement 

moves (Johnson-Reid and Barth, 2003; Runyan and Gould, 1985; Widom, 1989) and 

group home care. To control for these different experiences within the child welfare 

system, we included measures of out-of-home care experiences that reflect the stability 

and type of placements. First, we measured placement instability as the total number of 

out-of-home care placements the respondent had experienced to date. Second, we 

measured type of out-of-home care placement as one prepares for the transition to 

adulthood as the current placement type during the Wave 1 interview.24 Dummy 

variables for kinship care, group care, and independent living setting or other placements 

were compared to the reference placement of traditional foster care. Type of care that 

young people are placed in just before they begin the transition to adulthood may also 

indicate different access to support from caregivers. We also controlled for the age, in 

years, at which respondents first entered care. 

The John H. Chafee Foster Care Independence Program of 1999 provides states 

federal funds to help prepare young people during the transition from out-of-home care to 

independent living. These funds may be used for educational services, vocational 

training or employment services, budgeting and financial management services, health 

education services, housing services, or services to promote their positive youth 

development (Collins, 2001). We asked respondents if they received any training or 

services in preparation for independent living across domains of education (8 items), 

employment (11 items), financial management (7 items), housing (9 items), health 

 

24 Although we feel current placement is the best indicator of how different placements might impact behaviors 

following discharge, we also examined the effect of ever being placed in group care and ever being placed in kinship 

care. Neither of the lifetime placement variables was related to the risk for arrest. 

27 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
education (9 items), and youth development (3 items). We measured independent living 

services (ILS) support as a count of the number of services received across the six 

domains.25 The alpha reliability score for these 47 items is .96. 

Finally, because our sample consists of young people across three states that 

follow different child welfare practices that could impact behavior and in which three 

different reporting systems were utilized to measure arrests, we included two dummy 

variables to represent respondents who were placed in care in the states of Iowa and 

Wisconsin, with respondents from Illinois serving as the reference category. 

Demographic and Background Control Factors 

We controlled for several demographic characteristics, background risk factors, 

and out-of-home care placement experiences of respondents. Gender was included as a 

dichotomous variable with males coded ‘1’ and females coded ‘0’. We measured race of 

respondent through a series of dummy variables, with African American and other26

racial groups being compared to the reference category of White respondents. Although 

we attempted to interview all respondents near to their 17th birthday, the logistics of 

locating respondents and scheduling interviews resulted in variation in the timing of 

Wave 1 interviews. To account for age and potential developmental differences in 

respondents based on the timing of their first interview, we included a variable measuring 

respondents’ age (in years) at their Wave 1 interview. We also included a variable 

 

25 A small amount of data on independent living services was missing. For missing items, we imputed an individual’s 

mean score within the relevant domain. If all items in a domain were missing, we imputed the sample mean. 

26 Our decision to collapse all other racial groups was based on the distribution of race in the sample, with 

approximately 12% of respondents reporting a race other than White or African American (.5% “Asian/Pacific 

Islander”, 1.4% “American Indian/Native Alaskan”, 9.7% mixed, .5 “other”). In addition, we controlled for Hispanic 

ethnicity in earlier models (youth of Hispanic ethnicity comprised 8.6% of the sample). This measure had no 

relationship with the outcome and was subsequently removed from the final model presented in our results. 

28 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
indicating whether the respondent was a teen parent, coded ‘1’ if he/she had children and 

‘0’ if he/she did not have children at the Wave 1 interview. 

We also included background risk measures that are associated with crime. First, 

in negative binomial regression models where we predict self-reported criminal behavior, 

we controlled for prior self-reported delinquency, which we calculated as a summed scale 

based on 11 items that range from minor theft to using a weapon, each coded from zero 

(never) to three (5 or more times). In the hazard models where we predicted time to first 

arrest, we controlled for prior self-reported arrest. Prior arrest was coded ‘1’ if 

respondents reported that they had been arrested at any point prior to the Wave 1 

interview and ‘0’ otherwise.27 

We also included two measures of mental and behavioral health disorders. These 

measures were gathered using the Composite International Diagnostic Interview (CIDI; 

World Health Organization, 1998), which is a highly structured interview designed for 

use by non-clinicians that renders both lifetime and current psychiatric diagnoses 

according to definitions and criteria of the Diagnostic and Statistical Manual of Mental 

Disorders, Fourth Edition (DSM-IV). We distinguished between alcohol and drug related 

diagnoses and other mental health diagnoses through two measures taken from the CIDI. 

First, we measured whether respondents had any lifetime alcohol or substance 

dependence diagnosis. Second, we measured whether respondents had any other lifetime 

mental health disorder diagnosis, including major depression, panic disorder, social 

phobia, generalized anxiety disorder, or post-traumatic stress disorder. 

 

27 We chose to use the self reported measure of prior arrest because official arrest records for juveniles are not 

consistently available. 

29 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Missing Data 

Within each wave of data collection, respondents may have missing data for some 

items. For regression analyses, respondents were excluded from analyses in which the 

dependent variable was missing. We imputed the sample mean for missing values on 

independent variables.28 For scale items (e.g. independent living services or social 

support measure), we first imputed the respondent’s individual mean on those missing 

items before calculating the scale. For respondents missing values for all items in a scale, 

we imputed the sample mean. Missing data for independent variables was minor. For 

the full sample of 732 youth, no independent variable was missing on greater than 4 

percent of cases. 

For the analyses examining self reported offending within each of the three 

waves, only those youth with valid responses to the questions about delinquent and 

criminal behavior were included. Missing values were not imputed as these data were 

not missing at random. Rather this occurred either because youth did not participate in a 

particular interview or because youth did not participate in the ACASI portion of the 

interview. Also, when examining offending over time, for example in the latent class 

analysis, only those youth who participated in all three waves of data collection and had 

valid data on the crime measures were included. 

 

28 We note that the mean from the specific sample being used in each analysis was used for imputation. 

30 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Findings 

Offending Patterns 

1) Are offending patterns during the early transition to adulthood (ages 17-22) 

among youth formerly in out-of-home care different from those of the general 

population? 

In examining whether offending patterns during the early transition to adulthood 

among youth formerly in out-of-home care differ from those in the general population, 

we address three main issues: 1) how do youth in out-of-home care compare to youth 

more generally in terms of self-reported offending during the early transition to 

adulthood; 2) does offending decline overall between late adolescence and early 

adulthood among former foster youth as has been shown in previous research on general 

populations; and 3) is there variation in offending patterns during the early transition to 

adulthood among former foster youth, again as has been shown in previous research on 

general populations. 

To address these issues, we first compared self reported offending among 

respondents in the Midwest Study to same aged peers from in a national survey. We 

present data from each of the three waves of the Midwest Study. During the first 

interview when respondents were 17-18 years old, questions on self-reported offending 

were answered by all but two youth in the sample (n=730). After attrition, the sample 

during the second wave of interviews, at which point respondents were 19 years old, 

consisted of 603 respondents (82 percent of participants in the first interview), of which 

31 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
95 percent reported on criminal behavior (n=574). By the third wave at which point 

respondents were about 21 years old, 590 respondents were interviewed, of which 85 

percent reported on criminal behavior (n=504). 

 We compared self reported offending among foster youth to a sample of same 

aged peers from the National Longitudinal Study of Youth (Add Health). Add Health is a 

nationally representative study that examines the causes of health-related behaviors of 

adolescents and their outcomes in young adulthood.29 The data cited in this report were 

collected from the Add Health study participants in the core sample who were 17-18 

years old during the first wave of the study (n=1,938), and 19 (n=498) or 21 (n=740) 

years old at the time of a third interview in order to compare to our 17-18 year olds at 

Wave 1, 19 year olds at Wave 2, and 21 year olds at Wave 3, respectively. We note that 

the although Add Health is a longitudinal study, in order to select youth approximately 

the same age as those in our Midwest Study, the sample analyzed here does not include 

the same youth over time. 

The Midwest Study and the Add Health study had significantly different racial 

distributions at each of the time points, with the Midwest Study being represented by a 

higher proportion of African American and multiracial respondents.30 The high 

percentage of African American youth in the Midwest sample is not surprising, given that 

African American children are historically and currently overrepresented in the child 

welfare system (Shyne and Schroeder, 1978; Stehno, 1982; Lu et al., 2004). These 

different racial distributions, however, make comparing the samples on criminal behavior 

 

29 Several groups were over-sampled (e.g., African American youth from highly educated families or a 

parent with a college degree), but only youth in the core sample were included in our analyses. 30 For example, at age 17-18, 57% of the Midwest Study was African American and 10% multiracial 

compared to only 18% and 4% respectively in the Add Health Study. 

32 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
problematic because African American youth tend to have higher rates of both official 

and self-reported offending than Caucasian youth (Elliot and Ageton, 1980; Hawkins et 

al., 2000), particularly for serious violent behaviors (McNulty and Bellair, 2003). Given 

the differences in both the hypothesized crime rates and racial distributions of the two 

samples, it would be more appropriate to compare youth aging out of the child welfare 

system to a sample in the general population with a more similar racial distribution. In 

order to account for differences in the racial distributions of the two samples, we 

computed a case weight for youth in the Add Health sample by dividing the percentage of 

Midwest Study youth who identified themselves as belonging to a particular race by the 

percentage of Add Health youth who identified themselves as belonging to that same 

race.31 32

Sample Comparisons 

Figure 1 shows the percentage of youth in each sample who reported engaging in 

each of the delinquent or criminal behaviors during the last 12 months before the 

interview when youth were approximately 17-18 years old. This represents offenses 

committed when youth were about 16-17 years old. Behaviors ranged from minor 

property offenses, such as taking something from a store worth less than $50 to serious 

acts of violence, such as such using or threatening to use a weapon to get something from 

someone and shooting or stabbing someone. Using independent samples t-tests to 

 

31 For example, 57 percent of the Midwest Study youth were African American compared with 

approximately 19 percent of Add Health youth. The weight assigned to each African American youth in 

the Add Health sample was 57/19=3.00. 

32 Although by weighting for race we attempt to make the two samples more directly comparable, we recognize that the 

Add Health sample is not a formal comparison group. These two groups were sampled at different points in time, using 

different methods. Therefore, we cautiously use the Add Health sample to estimate a general population of youth, 

compared to a sample of foster youth. 

33 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
compare the proportions, we found that a significantly higher proportion of youth in the 

Midwest sample reported engaging in each offense. For most offenses, the proportion of 

youth in out-of-home care engaging in each offense was at least twice that found in the 

Add Health study. 

Figure 1. Self Reported Criminal Behavior: Midwest Study vs. Add Health (17-18 year olds) 

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Damaged

property*

Stole

something <

$50*

Stole

something >

$50*

Went into

house or

building to

steal

something*

Sold drugs* Hurt

someone

badly

enough to

need

medical

care*

Used or

threatened

to use a

weapon to

get

something* 

Participated

in a group

fight*

Pulled knife

or gun on

someone*

Shot or

stabbed

someone*

% of sample reporting behavior in past 12 months 

Midwest Study Add Health

We found fewer differences in offending between the youth in out-of-home care 

and their Add Health peers as reported at age 19 than found two years earlier. As shown 

in Figure 2, offending at about age 18 was lower in general for both foster youth and 

youth in general than offending at ages 16-17. Yet, a significantly higher proportion of 

youth in out-of-home care reported damaging property, stealing something worth more 

34 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
than $50, taking part in a group fight, and pulling a knife or gun on someone. Although 

the sample sizes are smaller during this second period, and thus, the power to detect 

variation across samples is reduced, it does not appear that this explains the lack of many 

statistically significant differences across the groups. Unlike the comparisons made 

during late adolescence, few offenses differed by more than two to three percent across 

the two groups. We note, however, that youth in out-of-home care are more likely to 

engage in some violent offenses, with nearly a quarter participating in a group fight and 

six percent having pulled a knife or gun on someone. 

Figure 2. Self Reported Criminal Behavior: Midwest Study vs. Add Health (19 year olds) 

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Damaged

property*

Stole

something <

$50

Stole

something >

$50*

Went into

house or

building to

steal

something

Sold drugs Hurt

someone

badly

enough to

need

medical care

Used or

threatened

to use a

weapon to

get

something* 

Participated

in a group

fight*

Pulled knife

or gun on

someone*

Shot or

stabbed

someone

% of sample reporting behavior in past 12 months 

Midwest Study Add Health

35 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
By Wave 3, when respondents were 21-22 years old, we found even fewer 

differences between foster youth and their peers more generally. The only significant 

differences between the two samples were for damaging property, going into a house to 

steal something, and pulling a knife or gun on someone. Respondents from the Midwest 

Study were more likely than their peers in Add Health to report engaging in these three 

criminal behaviors. 

Figure 3. Self Reported Criminal Behavior: Midwest Study vs. Add Health (21 year olds) 

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Damaged

property*

Stole

something <

$50

Stole

something >

$50

Went into

house or

building to

steal

something*

Sold drugs Hurt

someone

badly

enough to

need

medical care

Used or

threatened

to use a

weapon to

get

something 

Participated

in a group

fight

Pulled knife

or gun on

someone*

Shot or

stabbed

someone

% of sample reporting behavior in past 12 months 

Midwest Study Add Health

 

Large differences across the two groups are seen when comparing self reported 

arrests by age 19 and since age 18 for those interviewed at age 19.33 As shown in Table 

33 A comparable figure of self report arrest between the Midwest Study and Add Health Study was not available at age 

21. 

36 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
1, a significantly higher proportion of youth in out-of-home care reported having ever 

been arrested by age 19 and having been arrested since age 18 when compared to youth 

in general. This is true for both males and females. For arrests since age 18, we found 

even larger differences between the Midwest and Add Health studies. Even more 

striking, the percentage of female foster youth ever experiencing an arrest was not only 

higher than females in the Add Health sample, but also higher than that for Add Health 

males. The higher levels of self-reported arrest among foster youth could reflect the 

tendency for youth in out-of-home care to engage in violent behaviors at higher rates than 

youth in general, as shown above, though the differences between the two groups in selfreported arrest are much higher that the differences in self-reported criminal behavior. 

Alternatively, higher arrest rates could be a result of greater scrutiny being applied to 

foster youth by child welfare authorities and the police. 

Table 1. Self Reported Arrests: Midwest Study vs. Add Health Study

Males Females 

Midwest 

Study 

Add Health 

Study 

Midwest 

Study 

Add Health 

Study 

Ever arrested by age 19 57.0% 20.1% 34.4% 2.8% 

Arrested since age 18 35.9% 1.9% 17.9% 1.1% 

Variation in Offending by Gender 

We next compared offending in the Midwest and Add Health samples by gender 

to determine if the differences noted above were true for both males and females 

separately. As shown in Table 2, we found a significantly higher proportion of female 

foster youth reported all offenses when compared to female youth in general at ages 17-

18. A higher proportion of male foster youth also reported most offenses. Exceptions 

included pulling a knife or gun on someone and shooting or stabbing someone, for which 

the two samples did not significantly differ. 

37 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 2. Percentage Engaging in Selected Offenses (17-18 year olds) 

Females Males 

Midwest 

Study 

Add 

Health 

Midwest 

Study 

Add 

Health 

Damaged property 15.7 8.0 * 26.6 17.8 * 

Stole something < $50 31.9 10.9 * 42.7 20.7 * 

Stole something > $50 5.0 3.0 14.9 6.5 * 

Went into house or building 

to steal something 5.8 2.4 * 16.9 6.5 * 

Sold drugs 14.1 4.7 * 27.9 14.7 * 

Hurt someone badly enough 

to need medical care 27.1 8.6 * 50.0 29.7 * 

Used or threatened to use a 

weapon to get something 5.9 3.2 

* 

14.7 6.9 * 

Participated in a group fight 28.5 12.1 * 42.4 28.6 * 

Pulled knife or gun on 

someone 9.0 3.1 * 16.7 13.9 

Shot or stabbed someone 4.0 .1 * 7.1 5.6 

 *p<.05; one-tailed test 

 

When comparing offending as reported at age 19 across the two samples by 

gender (see Table 3), we found fewer differences among males, while female foster youth 

continued to report more offending. A significantly higher proportion of female foster 

youth reported all offenses except stealing something worth less than $50, selling drugs, 

and shooting or stabbing someone. On the other hand, the only significant difference 

between male foster youth and male youth in general was for participating in a group 

fight. 

38 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 3. Percentage Engaging in Selected Offenses (19 year olds) 

Females Males 

Midwest 

Study 

Add 

Health 

Midwest 

Study 

Add 

Health 

Damaged property 17.6 4.2 * 25.8 20.7 

Stole something < $50 6.9 4.6 * 15.2 14.5 

Stole something > $50 4.7 1.0 * 10.2 8.3 

Went into house or building 

to steal something 1.9 .3 * 6.3 9.5 

Sold drugs 6.3 6.2 * 21.1 16.3 

Hurt someone badly enough 

to need medical care 8.5 2.9 * 23.1 22.6 

Used or threatened to use a 

weapon to get something 3.8 .5 * 5.9 6.2 

Participated in a group fight 14.8 4.5 * 34.4 19.6 * 

Pulled knife or gun on 

someone 4.4 .2 * 8.2 5.8 

Shot or stabbed someone 1.0 .0 3.1 4.1 

*p<.05; one-tailed test 

The gender differences at age 21 reflect those seen in the full sample (see Table 

4). By age 21, even the female differences in self-reported offending declined, with only 

one statistically significant difference. A higher percentage of female foster youth 

reported pulling a knife or gun on someone. Similarly, there was only one difference 

between males, with a higher percentage of male foster youth reporting going into a 

house or building to steal something. In both of these cases, however, percentages in 

each sample were low. 

39 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 4. Percentage Engaging in Selected Offenses (21 year olds) 

Females Males 

Midwest 

Study 

Add 

Health 

Midwest 

Study 

Add 

Health 

Damaged property 8.8 6.4 17.2 12.3 

Stole something < $50 3.5 3.8 11.3 10.7 

Stole something > $50 2.8 2.8 9.0 6.0 

Went into house or building 

to steal something 1.1 .9 3.6 1.9 * 

Sold drugs 4.9 4.0 14.5 13.5 

Hurt someone badly enough 

to need medical care 3.5 3.8 15.8 15.4 

Used or threatened to use a 

weapon to get something .4 .2 3.2 1.6 

Participated in a group fight 6.0 5.2 20.8 22.0 

Pulled knife or gun on 

someone 4.2 1.4 * 5.9 2.8 

Shot or stabbed someone 1.1 .7 .9 .3 

*p<.05; one-tailed test 

In comparing the samples over time, we note that the Add Health sample consists 

of different individuals at each time point. The Midwest Study sample, however, consists 

of individuals from the same base sample. Thus, it is possible that the Midwest Study 

loses individuals over the three waves that are most at risk for offending. If this is the 

case, offending at ages 19 and 21 among the Midwest Study may be underestimated. In 

turn, differences to Add Health at these ages could be masked here. 

To better gauge whether attrition in the Midwest Study results in underestimates 

of self-reporting offending, we compared offending at ages 17-18 (Wave 1) between 

those retained in the study and those not subsequently interviewed. Those who left the 

study after the first wave of interviews were not significantly more or less likely to report 

engaging in delinquent or criminal behaviors at Wave 1 than those who were 

subsequently interviewed at Waves 2 and/or 3. We also compared official arrests rates of 

those who were interviewed at Wave 3 to those who had left the study. Of those 

40 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
interviewed at Wave 3, 46 percent had an arrest recorded compared to 47 percent of those 

not interviewed (the difference is not statistically significant). These findings suggest 

that the study did not lose those youth most likely to offend. We also found that 43 

percent of those youth interviewed at all three waves had an official arrest. Again, this 

suggests study attrition did not result in the selective loss of those displaying the worst 

behavior. 

Offending Over Time among Foster Youth 

The analyses presented above suggest that like their peers more generally, 

offending among foster youth tends to decline during the early transition to adulthood, at 

least among those youth for whom offending information was available. Offending is 

likely to be high among foster youth during late adolescence because, in general, it is 

during this period that offending increases (Hirschi and Gottfredson, 1983; Farrington, 

1986). Yet, little is known about whether young people aging out of the child welfare 

system desist from offending as they transition to adulthood. The Midwest Study allows 

us to examine changes in offending behavior among the same sample of former foster. 

To do so, we compared self-reporting offending among respondents who completed all 

three interviews. First we compared offending of respondents at age 17-18 to offending 

at age 19, and then between offending of respondents at age 19 to offending at age 21. 

Paired samples t-tests revealed that offending generally decreased from one time point to 

the next (see Table 5). Exceptions included damaging property and stealing something 

worth more than $50, in which we found no significant declines between age 17-18 and 

19. Damaging property, selling drugs, hurting someone badly enough to need medical 

41 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
care, using or threatening to use a weapon, and participating in a group fight all 

significantly declined from age 19 to age 21. 

 

Table 5. Percentage of Foster Youth Engaging in Selected Offenses Over Time (n=438) 

17-18 Year Olds 19 Year Olds 21 Year Olds 

Damaged property 19.9 18.6 11.9*** 

Stole something < $50 35.4 9.6*** 7.1 

Stole something > $50 8.9 6.8 5.5 

Went into house or building 

to steal something 8.7 3.6*** 3.2 

Sold drugs 18.0 11.9** 7.5* 

Hurt someone badly enough 

to need medical care 34.7 15.3*** 8.5*** 

Used or threatened to use a 

weapon to get something 7.8 3.7** 1.6* 

Participated in a group fight 34.3 21.5*** 12.1*** 

Pulled knife or gun on 

someone 11.9 5.7*** 4.6 

Shot or stabbed someone 4.3 2.1* 1.0 

Note: *p<.05, **p<.01, ***p<.001; one-tailed test (19 year olds vs. 17-18 year olds; 21 year olds vs. 19 

year olds) 

These findings suggest that patterns of offending among youth aging out of care 

are similar to those seen in the general population, with offending peaking during late 

adolescence and appearing to decline into adulthood. They do not, however, highlight 

any possible variation in offending trends within our sample of foster youth. In other 

words, while overall offending among our sample declines during the early transition to 

adulthood, some youth may continue offending while others may even begin offending 

after adolescence. 

In order to further identify variations in offending patterns over time among our 

sample of foster youth, we conducted a latent class analyses for the Midwest Study 

respondents participating in all three interviews and who reported on criminal behavior 

(n=438). Latent class analysis, or LCA, is a method that presumes observed variables are 

42 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
indicators of a latent categorical variable that represents a mixture of distinct 

subpopulations within the data (McCutcheon 1987). The result is an empirical 

classification of individuals who share a common profile. In this case, we classify 

individuals who share common patterns of offending across the three waves of data. The 

analyses were conducted using Latent GOLD software (Vermunt and Magidson 2005). 

In this LCA, we included six indicators of self-reported offending that represent 

any violent offending and any non-violent offending at each wave. The analysis revealed 

a five class model best fit the data. For reporting the profiles of the classes on the 

indicators used in the analysis and for validating class distinctions across additional 

characteristics of interest, cases were assigned to membership in the single class for 

which they have the highest, or modal, probability. Profiles of the latent classes are 

presented in Table 6. The first row shows the relative proportion of the sample in each 

class. The remaining rows present the probabilities on the indicators used in the latent 

class analysis. 

43 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 6. Profiles of Latent Classes (n=438)

Rare or 

NonOffenders Adolescent 

Offenders 

Desisting 

Offenders 

Chronic 

Offenders 

Chronic 

NonViolent 

Offenders 

Class Size 34% 28% 19% 11% 8% 

Indicators 

Any violent offense - w1 

No 0.7686 0.3998 0.1504 0.0852 0.7328 

Yes 0.2314 0.6002 0.8496 0.9148 0.2672 

Any non-violent offense – w1 

No 0.8891 0.2593 0.4392 0.1422 0.3739 

Yes 0.1109 0.7407 0.5608 0.8578 0.6261 

Any violent offense – w2 

No 0.9898 0.9927 0.0166 0.1659 0.9935 

Yes 0.0102 0.0073 0.9834 0.8341 0.0065 

Any non-violent offense – w2 

No 0.9709 0.7169 0.6212 0.2351 0.0812 

Yes 0.0291 0.2831 0.3788 0.7649 0.9188 

Any violent offense – w3 

No 0.9212 0.9982 0.6725 0.2954 0.7496 

Yes 0.0788 0.0018 0.3275 0.7046 0.2504 

Any non-violent offense – w3 

No 0.9212 0.8864 0.9286 0.222 0.3518 

Yes 0.0788 0.1136 0.0714 0.778 0.6482 

 

“Rare or Non-Offenders” - The largest class, representing approximately 34 

percent of the sample, reported consistently low offending experiences across the three 

waves when compared to respondents in other classes. For example, respondents in this 

first class had only a .23 probability of reporting a violent offense and a .11 probability of 

reporting a non-violent offense at Wave 1. Over the next two waves, the probability of 

reporting either violent or non violent offenses dropped to below .10. Therefore, 

although some respondents in this class did report offending across each wave, the 

general pattern of this class, particularly compared to other classes, was to be nonoffenders. 

44 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
“Adolescent Offenders” – The second largest class, with about 28 percent of the 

sample, is distinguished from the other classes by relatively high levels of delinquent or 

criminal behaviors at age 17-18, but lower levels over time. By age 19 and 21, the 

probability of a violent offense dropped to almost zero. Non-violent offenses also 

become much less likely than seen during adolescence. Thus, this class of Adolescent 

Offenders appears similar to what Moffit (1993) referred to as “adolescent limited”, 

meaning that offending is limited to what may be thought of as normative adolescent 

behavior that decreases as youth enter adulthood. 

“Desisting Offenders” - The third largest class, with about 19 percent of the 

sample, is noteworthy for reporting delinquent and criminal behaviors at ages 17-18 and 

age 19, but reporting a decrease in these behaviors by age 21. Whereas the Adolescent 

Offenders limited their offending to adolescence, this group of Desisting Offenders 

continued offending into late adolescence/early adulthood at age 19, but appears to 

change, or desist from, their behavior as they enter their 20’s. 

“Chronic Offenders” – The fourth class includes only 11 percent of the sample. 

This class is distinguished from other classes by having the highest reported probability 

of violent and non-violent behaviors over time. This group, although small, was most 

likely to report engaging in both types of behavior at all three waves of the study. For 

example, although decreasing slightly over time, the probability of reporting any violent 

or non-violent offense remained above .70 at each of the three waves. Therefore, this 

class appears to describe chronic offenders. 

“Chronic Non-Violent” - The smallest class includes only about 8 percent of the 

sample. Like the Chronic Offenders, respondents in this last class had a high probability 

45 

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been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
of engaging in non-violent offenses at each of the three waves. However, unlike the 

Chronic Offenders and more similar to Non-Offenders, respondents in this class had a 

relatively low probability of engaging in violent offenses at any time point. Therefore, it 

appears that this class consists of chronic non-violent offenders. 

To further describe the latent classes found in the LCA, we examined 

demographic characteristics and background factors, foster care experiences, and social 

bond factors for each class. As shown in table 7, Non-Offenders and Adolescent 

Offenders were more likely than other classes to include females than males. With 

respect to race, higher proportions of African American youth are found among NonOffenders, Desisting Offenders, and Chronic Offenders than in the other classes. 

Respondents who reported experiencing childhood neglect were disproportionately 

represented among Chronic Offenders. Adolescent Offenders were more likely to 

include respondents who entered foster care as adolescents while Non-Offenders were 

more likely to include respondents who entered foster care at younger ages. Desisting 

Offenders were more likely to include respondents whose last placement was a relative 

home while Chronic Offenders were overrepresented by respondents who reported last 

placement was in a group home. Chronic Offenders were also overrepresented by 

respondents who reported experiencing high levels of placement instability in foster care. 

Non-Offenders were more likely to report being enrolled in school at ages 19 and 21 than 

respondents in the other classes. Finally, Chronic Offenders were overrepresented by 

respondents who reported lower social support. We found no statistically significant 

difference in the state (Illinois, Iowa, or Wisconsin) in which foster youth were placed 

across the latent classes. 

46 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 7. Characteristics of Latent Classes (n=438) 

Class 1 Class 2 Class 3 Class 4 Class 5 Total Χ2

Rare or 

Non 

Offenders 

(n=155) 

Adolescent 

Offenders 

(n=124) 

Desisting 

Offenders 

(n=89) 

Chronic 

Offenders 

(n=41) 

Chronic 

NonViolent 

Offenders 

(n=29) (n=438) 

% % % % % % 

Demographics 

Female 70.3 66.9 44.9 26.8 31.0 57.5 44.8*** 

Race: 24.7** 

White 32.3 44.4 16.9 31.7 48.3 33.6 

Black 56.8 41.9 62.9 53.7 48.3 53.0 

Other 11.0 13.7 20.2 14.6 3.4 13.5 

State: 10.5 

Wisconsin 28.4 33.1 31.5 29.3 24.1 30.1 

Illinois 64.5 54.0 64.0 65.9 58.6 61.2 

Iowa 7.1 12.9 4.5 4.9 12.2 8.7 

Physical abuse 31.0 39.5 27.0 48.8 44.8 35.2 9.4* 

Neglect 53.5 62.1 49.4 73.2 65.5 57.8 9.3* 

Age at entry: 12 and older 51.0 66.1 48.3 53.7 31.0 57.3 15.2** 

Foster Care Experiences 

Last placement type: 44.2*** 

Kinship care 39.4 23.4 42.7 17.1 27.6 32.6 

Foster care 41.9 37.9 33.7 26.8 34.5 37.2 

Group care 5.2 18.5 14.6 34.1 27.6 15.1 

Independent living/Other 13.5 20.2 9.0 22.0 10.3 15.1 

5 or more placements 28.4 54.0 38.2 58.5 51.7 42.0 25.4*** 

At-risk behaviors 

Prior arrest 29.0 54.8 56.2 70.7 62.1 47.9 37.8*** 

Substance abuse diagnosis 9.0 28.2 18.0 39.0 24.1 20.1 26.6 

Mental health diagnosis 21.9 30.6 22.5 17.1 24.1 24.2 4.5 

Teen parenthood 19.4 9.7 12.4 17.2 14.2 14.2 11.4 

Social Bonds 

Social support (MOS) 58.7 41.1 48.3 31.7 48.3 48.4 13.8** 

Close to maternal caregiver 59.4 62.9 68.5 63.4 58.6 62.6 2.2 

Close to paternal caregiver 43.9 45.2 44.9 36.6 27.6 42.7 3.9 

Close to foster caregiver 78.7 69.4 82.0 68.3 79.3 75.8 6.9 

Wave One: 

 In school 85.8 82.3 79.8 78.0 79.3 82.4 2.4 

Employed 40.6 42.7 34.8 29.3 32.9 38.8 3.2 

Wave Two: 

In school 56.8 37.9 39.3 43.9 41.4 45.7 12.4 * 

Employed 47.1 45.2 36.0 36.6 44.8 43.2 3.8 

Wave Three: 

In school 32.2 23.4 16.9 12.2 13.8 23.5 13.2** 

Employed 59.4 56.9 58.4 35.0 69.0 56.9 10.0* 

*p<.05, **p<.01, ***p<.001 

47 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Predictors of Criminal Behavior 

Descriptive Statistics 

Descriptive statistics for the criminal behavior dependent variables are presented 

in Tables 8. Most respondents did not report engaging in any of the non-violent or 

violent behaviors at Wave 3. Again, 8 items, measured from 0 (never) to 3 (more than 

five times), were used to construct the non-violent scale. This could result in a maximum 

possible score of 24 for someone who reported engaging in every behavior more than five 

times. Four items were used to construct the violent scale, for a maximum possible score 

of 12. However, as shown in Table 8, the maximum score for each outcome was 5. 

These statistics indicate that most respondents did not report engaging in the targeted 

behaviors.34 

Table 8. Descriptive Statistics: Dependent Variables 

N Mean 

Standard 

Deviation Max 

Non-violent Criminal Behavior 504 0.66 1.33 5 

Violent Criminal Behavior 504 0.37 1.00 5 

Descriptive statistics for independent variables included in the models predicing 

non-violent and violent criminal behavior are shown in Table 9. Respondents reported 

closer relationships with out-of-home caregivers than with either mothers or fathers. 

Most of the sample was enrolled in some type of educational setting and nearly threequarters reported plans to graduate from college. Only 38 percent were employed at 

Wave 1. Perceived social support was relatively high among the sample, with a mean 

social support score of 73.15 out a possible 100. Attachment to the child welfare system, 

 

34 Although the scales skewed toward zero, our analytic models (Poisson and negative binomial) do account for 

variation beyond “yes” vs. “no” as would be the case in a binomial distribution. 

48 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
however, appeared limited. For example, the average score on a scale indicating 

likelihood to ask the child welfare system for help after discharge was only 2.4, on a scale 

from 1-4. On average, respondents received 13.68 independent living services. 

Considering 47 independent living services were potentially available, this figure 

suggests that young people aging out of care receive limited preparation for making the 

transition from adolescence to independent adulthood. 

49 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 9. Descriptive Statistics: 

Independent Variables in Violent and Non-Violent Criminal Behavior Models (n=504) 

Males 

(n=221) 

Females 

(n=283) 

Total 

(N=504) 

Mean s.d. Mean s.d. Mean s.d. Min Max 

Controls and Risk Factors 

 African American .52 .50 .55 .50 .54 .50 0 1 

 White .37 .48 .30 .46 .33 .47 0 1 

 Other race .12 .32 .14 .35 .13 .34 0 1 

 Teen parenthood .06 .24 .20 .40 .14 .35 0 1 

 Prior delinquency scale 5.16 3.82 3.42 3.28 4.18 3.62 0 11 

 Physical abuse .92 1.53 1.14 1.79 1.04 1.69 0 7 

 Neglect 1.56 2.00 1.80 2.14 1.69 2.08 0 9 

 Sexual abuse/assault .16 .37 .39 .49 .29 .45 0 1 

 Substance abuse diagnosis .23 .42 .17 .38 .20 .40 0 1 

 Mental health diagnosis .13 .34 .31 .46 .23 .42 0 1 

Out-of-Home Care Experiences 

 Age at entry (in years) 10.71 3.87 10.92 4.04 10.83 3.96 0 16 

 Number of placements 6.10 6.39 5.12 5.10 5.55 5.72 1 42 

 Type of placement at wave 1 

 Foster care .38 .49 .35 .48 .36 .48 0 1 

 Kinship care .32 .47 .34 .47 .33 .47 0 1 

 Group care .19 .40 .13 .34 .16 .36 0 1 

 Independent living/Other .12 .32 .19 .39 .16 .36 0 1 

 Number of independent 

 living services received 14.53 12.11 13.01 11.87 13.68 11.99 0 47 

Social Bonds 

 Closeness to mother 2.69 1.23 2.66 1.21 2.67 1.22 1 4 

Missing mother indicator .16 .37 .10 .30 .13 .33 0 1 

 Closeness to father 2.11 1.23 2.12 1.22 2.11 1.23 1 4 

Missing father indicator .30 .46 .21 .41 .25 .44 0 1 

 Closeness to foster caregiver 3.15 1.06 2.92 1.23 3.02 1.16 1 4 

 Social support 71.47 21.73 74.46 22.26 73.15 22.05 0 100 

 In school .85 .36 .80 .40 .82 .39 0 1 

 College plans .68 .47 .75 .43 .72 .45 0 1 

 Employed .36 .48 .39 .49 .38 .48 0 1 

 Likely to ask child welfare 

 system for help 2.39 .72 2.43 .80 2.41 .77 1 4 

State 

 Illinois .56 .50 .65 .48 .61 .49 0 1 

 Iowa .09 .28 .09 .28 .09 .28 0 1 

 Wisconsin .35 .48 .27 .44 .30 .46 0 1 

50 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Results of the Poisson/Negative Binomial Models 

Violent Crime 

A Poisson distribution was chosen to model violent crime (deviance = 1.08). The 

results for the full model can be seen in Table 10. As expected, there is a large and 

statistically significant difference in delinquency by gender. Exponentiation of the 

parameter estimate for males, β = 0.98, reveals that boys have an average level of violent 

crime over 2.5 times the average for females. Youths who reported delinquency in Wave 

1 also have higher criminal behavior in Wave 3, about 18 percent higher for each 1 unit 

increase in Wave 1 delinquency. 

Out-of-home care experiences were also significantly related to violent crime. 

High numbers of foster care placements contributed to an increase of about 3 percent in 

violent offending for each placement, and youths in group care at Wave 1 are expected to 

report about 80 percent more crime than the average for youths in traditional foster care. 

Youths who access independent living services however, have decreases in violent 

behavior of about 2 percent for each service used. 

Finally, we found that having college plans at Wave 1 decreases violent behavior 

by about one-third compared to those without college aspiration. Being a victim of 

sexual abuse is also related to a decrease of more than 50 percent in violent crime 

reported. 

51 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
 

Table 10. Estimates from Poisson Regression of Violent Criminal Behavior on Covariates 

(n=504)

Variables Β SE Exp(β)

Demographic and Background Risk Factors 

 Male (vs. female) .980*** .199 2.66 

 African American (vs. white) .206 .205 1.23 

 Other race (vs. white) -.188 .284 0.83 

 Prior delinquency .161*** .024 1.18 

 Neglect .064 .044 1.07 

 Physical abuse -.011 .056 0.99 

 Sexual abuse/assault -.808** .245 0.45 

 Substance abuse diagnosis -.231 .198 0.79 

 Mental health diagnosis -.068 .213 0.93 

 Teen parenthood .251 .236 1.29 

 Iowa (vs. Illinois) -.180 .388 0.84 

 Wisconsin (vs. Illinois) -.538** .198 0.58 

Out-of-Home Care Experiences 

 Age at entry .013 .022 1.01 

 Number of placements .025* .012 1.03 

 Type of placement at wave 1 

 (vs. traditional foster care) 

 Kinship care .125 .214 1.13 

 Group care .582** .214 1.79 

 Independent living/other .471 .399 1.60 

 Number of independent living services -.019** .007 0.98 

Social Bonds 

 Closeness to mother -.018 .087 0.98 

 Missing mother indicator .776** .255 2.17 

 Closeness to father .001 .081 1.00 

 Missing father indicator -.129 .211 0.88 

 Closeness to caregiver .166 .117 1.18 

 Social support .007 .004 1.01 

 In school .053 .209 1.05 

 College plans -.403* .160 0.67 

 Employed -.003 .166 0.99 

 Likely to ask child welfare system for help -.038 .108 0.96 

*p<.05, **p<.01, ***p<.001 (two-tailed tests) 

52 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Violent Crime by Race 

To test the hypothesis that the relationship between out-of-home care placement 

experiences and crime differ by race, we included interaction terms between a dummy 

variable for race (African American = 1, white = 0) and each out-of-home care placement 

variable35. Results for the interactions are shown in Table 11. 

Contrary to our hypothesis, we did not find much evidence that the relationship 

between out-of-home care placement experiences and violent criminal behavior was 

moderated by race, specifically when comparing white and African American youth. 

Only two interactions were significant – being in group care versus traditional foster care 

and being in independent living or other care settings versus traditional foster care. 

Being in group care is associated with a higher rate of violent behavior for African 

Americans than for whites. In addition, being in an independent living or other 

arrangement versus traditional foster care was associated with an increase in violent 

crime for white youth, but not for African Americans. However, we note this finding 

with caution due to the small number of youth who were living independently (or “other” 

placement) in Wave 1. 

 

35 Because the interaction of interest was white versus African American youth, we limited the sample to only white 

and African American youth (n=438) for the model testing interactions between race and placement experiences. 

53 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 11. Estimates from Poisson Regression of Violent Crime on Covariates with 

 Interaction between Race (African American vs. White) and Out-of-Home 

 Placement Experiences (n=438) 

Variables Β SE Exp(β)

Demographic and Background Risk Factors 

 Male (vs. female) 1.134*** .226 3.11 

 African American (vs. white) 1.074 .739 2.93 

 Prior delinquency .156*** .028 1.17 

 Neglect .021 .049 1.02 

 Physical abuse -.016 .069 .98 

 Sexual abuse/assault -.656* .274 .52 

 Substance abuse diagnosis -.421 .233 .66 

 Mental health diagnosis .239 .233 1.27 

 Teen parenthood .165 .286 1.18 

 Iowa (vs. Illinois) -.519 .417 .60 

 Wisconsin (vs. Illinois) -.552* .219 .58 

Out-of-Home Care Experiences 

 Age at entry .063 .048 1.07 

 Number of placements .010 .020 1.01 

 Type of placement at wave 1 

 (vs. traditional foster care) 

 Kinship care .513 .426 1.67 

 Group care -.397 .494 .67 

 Independent living/other 1.466** .497 4.33 

 Number of independent living services -.002 .014 1.00 

Social Bonds 

 Closeness to mother -.124 .076 .88 

 Missing mother indicator .560 .418 1.75 

 Closeness to father .062 .078 1.06 

 Missing father indicator .826* .334 2.28 

 Closeness to caregiver .273* .126 1.31 

 Social support .003 .004 1.00 

 In school .068 .234 1.07 

 College plans -.406* .175 .67 

 Employed .195 .191 1.22 

 Likely to ask child welfare system for help .088 .116 1.09 

Interactions (with African American vs. white) 

 Age at entry*race -.051 .055 .95 

 Number of placements*race .030 .025 1.03 

 Type of placement at wave 1 

 (vs. traditional foster care 

 Kinship care*race -.404 .495 .67 

 Group care*race 1.163* .566 3.20 

 Independent living/other*race -1.776* .731 .17 

 Number of independent living services*race -.030 .016 .97 

*p<.05, **p<.01, ***p<.001 (two-tailed tests) 

54 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Nonviolent Crime 

We estimated non-violent criminal behavior through negative binomial 

regression, the results of which can be seen in Table 12. As seen in the violent crime 

model, gender and Wave 1 delinquency are both significant and positive in the nonviolent crime model. Males are estimated to engage in 68 percent more non-violent 

criminal behavior than females, a much less dramatic difference than seen in the violent 

crime model. The effect of Wave 1 delinquency was also smaller, though still 

significant, contributing a 12 percent increase in expected nonviolent crime for each 1 

unit increase in prior delinquency. Study particpants with multiple foster care placements 

are predicted to have higher levels of crime, as each placement is associated with a 4 

percent increase in average criminal behavior. No social bonds variables were found to be 

significant in the nonviolent model. 

55 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
 

Table 12. Estimates from Negative Binomial Regression of Non-Violent Criminal Behavior 

 on Covariates (n=504) 

Variables Β SE Exp(β)

Demographic and Background Risk Factors 

 Male (vs. female) .519* .227 1.68 

 African American (vs. white) -.305 .272 0.74 

 Other race (vs. white) -.196 .330 0.82 

 Prior delinquency .115*** .030 1.12 

 Neglect .031 .056 1.03 

 Physical abuse .056 .073 1.06 

 Sexual abuse/assault -.417 .256 0.66 

 Substance abuse diagnosis .108 .262 1.11 

 Mental health diagnosis -.043 .271 0.96 

 Teen parenthood -.314 .392 0.73 

 Iowa (vs. Illinois) .019 .392 1.02 

 Wisconsin (vs. Illinois) .013 .239 1.01 

Out-of-Home Care Experiences 

 Age at entry -.015 .030 0.99 

 Number of placements .037* .017 1.04 

 Type of placement at wave 1 

 (vs. traditional foster care) 

 Kinship care -.428 .267 0.65 

 Group care .554 .309 1.74 

 Independent living/other .387 .494 1.47 

 Number of independent living services -.012 .009 0.99 

Social Bonds 

 Closeness to mother .149 .107 1.16 

 Missing mother indicator .362 .359 1.44 

 Closeness to father -.150 .101 0.86 

 Missing father indicator -.249 .272 0.78 

 Closeness to caregiver .147 .151 1.16 

 Social support -.003 .005 0.99 

 In school -.235 .269 0.79 

 College plans .109 .222 1.12 

 Employed -.165 .211 0.85 

 Likely to ask child welfare system for help -.074 .134 0.93 

*p<.05, **p<.01, ***p<.001 (two-tailed tests) 

56 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Non-violent Crime by Race 

As with the violent criminal behavior model, we tested for statistical interactions 

between placement experiences and race. The regression results for the interaction terms 

are shown in Table 13. Again, we found little support for the hypothsis that the 

relationship between out-of-home care experiences and non-violent crime differs between 

African American and white youth. Only one interaction term, number of placements by 

race, was significant, such that more out-of-care placements increased non-violent crime 

for African Americans. Conversely, non-violent crime was similar for white youth with 

different numbers of placements. This suggests that moving through many out-of-home 

care placements may be more detrimental for African American youth. 

57 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 13. Estimates from Poisson Regression of Non-Violent Crime on Covariates with 

 Interaction between Race (African American vs. White) and Out-of-Home 

 Placement Experiences (n=438) 

Variables β SE Exp(β)

Demographic and Background Risk Factors 

 Male (vs. female) .805** .247 2.24 

 African American (vs. white) -.428 .815 .65 

 Prior delinquency .100** .034 1.11 

 Neglect .089 .061 1.09 

 Physical abuse -.058 .083 .94 

 Sexual abuse/assault -.179 .283 .84 

 Substance abuse diagnosis .188 .283 1.21 

 Mental health diagnosis .146 .302 1.16 

 Teen parenthood -.544 .359 .58 

 Iowa (vs. Illinois) .124 .418 1.13 

 Wisconsin (vs. Illinois) .229 .253 1.26 

Out-of-Home Care Experiences 

 Age at entry .019 .050 1.02 

 Number of placements .005 .028 1.01 

 Type of placement at wave 1 

 (vs. traditional foster care) 

 Kinship care -.909 .553 .40 

 Group care .362 .458 1.44 

 Independent living/other .679 .625 1.97 

 Number of independent living services -.031* .015 0.97 

Social Bonds 

 Closeness to mother .077 .097 1.08 

 Missing mother indicator .126 .737 1.13 

 Closeness to father -.115 .099 .89 

 Missing father indicator -.133 .532 .88 

 Closeness to caregiver .140 .164 1.15 

 Social support -.006 .005 .99 

 In school .106 .305 1.11 

 College plans -.022 .238 .98 

 Employed -.198 .234 .82 

 Likely to ask child welfare system for help -.120 .148 .89 

Interactions (with African American vs. white) 

 Age at entry*race -.076 .062 .93 

 Number of placements*race .075* .036 1.08 

 Type of placement at wave 1 

 (vs. traditional foster care 

 Kinship care*race .703 .641 2.02 

 Group care*race .496 .614 1.64 

 Independent living/other*race .102 .635 1.11 

 Number of independent living services*race .030 .019 1.03 

*p<.05, **p<.01, ***p<.001 (two-tailed tests) 

58 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Predictors of Criminal Justice Involvement: The Risk for Arrest 

Descriptive Statistics 

Descriptive statistics for the covariates predicting time to first arrest are presented 

in Table 14. Results are similar to those presented in Table 9 for the Wave 3 sample. 

Table 14. Descriptive Statistics: Covariates in Hazard Models Predicting Arrest (n=728) 

Males 

(n=352) 

Females 

(n=376) 

Total 

(N=728) 

Mean s.d. Mean s.d. Mean s.d. Min Max 

Controls and Risk Factors 

 African American .56 .50 .58 .49 .57 .49 0 1 

 White .32 .47 .30 .46 .31 .46 0 1 

 Other race .12 .32 .12 .33 .12 .33 0 1 

 Teen parenthood .07 .26 .20 .40 .14 .35 0 1 

 Age at wave 1 17.9 .34 17.9 .37 17.9 .36 17.1 18.8 

 Prior arrest .62 .49 .41 .49 .51 .50 0 1 

 Physical abuse (sum) .39 .49 .40 .49 1.06 1.71 0 7 

 Neglect (sum) .60 .49 .65 .48 1.75 2.06 0 7 

 Sexual abuse/assault .14 .34 .40 .49 .30 .46 0 1 

 Substance abuse diagnosis .23 .42 .16 .37 .20 .40 0 1 

 Mental health diagnosis .13 .34 .32 .47 .23 .42 0 1 

Out-of-Home Care Experiences 

 Age at entry 10.5 4.0 10.9 4.07 17.9 .36 17.1 18.8 

 Number of placements 6.3 6.4 5.3 5.4 5.8 5.9 0 42 

 Type of placement (wave 1) 

 Foster care .36 .48 .36 .48 .36 .48 0 1 

 Kinship care .29 .45 .32 .47 .31 .46 0 1 

 Group care .21 .41 .15 .36 .18 .38 0 1 

 Independent living/Other .07 .25 .09 .28 .08 .27 0 1 

 Number of independent 

 living services received 

14.29 12.13 13.0 11.9 13.6 12.0 0 47 

Social Bonds 

 Closeness to mother 2.65 1.2 2.69 1.2 2.67 1.2 1 4 

 Closeness to father 2.12 1.2 2.11 1.2 2.12 1.2 1 4 

 Closeness to foster caregiver 3.10 1.1 2.95 1.2 3.03 1.2 1 4 

 Social support 72.2 22.4 74.2 23.14 73.2 22.8 0 100 

 In school .83 .38 .82 .39 .82 .38 0 1 

 College plans .69 .46 .75 .43 .72 .45 0 1 

 Employed .32 .47 .38 .48 .35 .48 0 1 

 Likely to ask child welfare 

 system for help 

2.36 .74 2.42 .74 2.39 .79 1 4 

State 

 Illinois .61 .49 .68 .47 .65 .48 0 1 

 Iowa .08 .49 .09 .29 .09 .28 0 1 

 Wisconsin .31 .46 .23 .42 .27 .44 0 1 

59 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Results of the Hazard Model 

We first examined the time that young people aging out of care survived, on 

average, before experiencing an arrest. Forty-six percent of the sample was arrested 

between the Wave 1 interview (from 2002-2003) and the end of the study period (August 

31, 2007), which is about 5.3 years. This figure is not surprising, given the high risk for 

offending for maltreated youth in general (Maxfield and Widom, 1996; McCord, 

McCord, and Thurber, 1983; Smith and Thornberry, 1995; Widom, 1989) and 

considering that over half of the sample reported a previous arrest before the Wave 1 

interview. Over the period, the probability of arrest reaches almost .50, as shown in 

Figure 4 (the cumulative probability of first arrest). 

Figure 4. Cumulative Probability of First Arrest 

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Duration in Quarters

Cumulative Probability

60 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Figure 5 illustrates the conditional hazard probabilities of first arrest following the 

Wave 1 interview. This is expressed as the proportion of individuals at risk who are 

arrested during each time point, shown in 3-month, or quarterly, intervals. As shown in 

Figure 5 the conditional probability of experiencing an arrest generally decreases over the 

study period. 

Figure 5. Conditional Probability of First Arrest 

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Duration in Quarters

Conditional Probability 

Next, we examined the relationship of covariates to the timing of first arrest. 

Results of the Cox proportional hazards model for the full sample are presented in Table 

15. A significant coefficient indicates the covariate is predictive of the time to first 

arrest. Positive coefficients are associated with earlier time to first arrest (earlier failure), 

while negative coefficients are associated with later time to first arrest (longer survival). 

Hazard ratios are also provided. These hazard, or risk, ratios indicate how the risk of 

61 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
arrest varies with a change in the value of a covariate relative to a reference value (for 

categorical covariates) or with increasing values of a continuous covariate. Values over 

one indicate an increase in the hazard rate and values less than one indicate a decrease in 

the hazard rate. If one is subtracted from the hazard ratio and the remainder is multiplied 

by 100, the result is equal to the percentage change in the hazard of arrest. 

Table 15. Estimates from Cox Proportional Hazard Regression of Time to First Arrest on 

 Covariates: Full Sample (n=728) 

Variables β SE 

Hazard 

Ratio 

Demographic and Background Risk Factors 

 Age at wave 1 in years -.053 .200 .95 

 Male (vs. female) .692*** .133 2.00 

 African American (vs. white) .719*** .155 2.05 

 Other race (vs. white) .322 .197 1.37 

 Prior arrest .814*** .135 2.26 

 Neglect -.005 .035 1.00 

 Physical abuse .047 .043 1.05 

 Sexual abuse/assault .025 .153 1.02 

 Substance abuse diagnosis .425** .139 1.53 

 Mental health diagnosis -.334* .159 .72 

 Children .055 .176 1.06 

 IA -.054 .279 .95 

 WI -.107 .155 .90 

Out-of-Home Care Experiences 

 Age at entry .015 .016 1.01 

 Number of placements .035*** .009 1.04 

 Type of placement at wave 1 

 (vs. traditional foster care) 

 Kinship care .194 .154 1.21 

 Group care .458** .168 1.58 

 Independent living/other .295 .265 1.34 

 Number of independent living services .002 .005 1.00 

Social Bonds 

 Closeness to mother .098 .061 1.10 

 Missing mother indicator .495* .205 1.64 

 Closeness to father -.017 .058 .98 

 Missing father indicator -.042 .164 .96 

 Closeness to caregiver .034 .079 1.03 

 Social support .005 .003 1.00 

 In school .036 .153 1.04 

 College plans -.270* .123 .76 

 Employed -.378** .126 .68 

 Likely to ask child welfare system for help -.048 .078 .95 

*p<.05, **p<.01, ***p<.001 (two-tailed tests) 

62 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
We found that being male versus female and African American versus White 

increased the hazard rate for arrest by about 100 percent. In other words, the time to first 

arrest was significantly shorter for males and African American respondents. The time to 

first arrest was also significantly shorter among those with a prior arrest and those with a 

history of alcohol or drug abuse diagnosis. That young people with substance abuse 

problems would have a greater risk of arrest is not surprising given the association 

between drug use and arrests among juveniles (National Institute of Justice, 2003). These 

findings were independent of out-of-home care experiences. Having a history of one or 

more of the mental health disorders we assessed was associated with a reduced hazard of 

arrest. Since the most common diagnoses among the disorders we assessed were 

depression and PTSD, in other words, disorders not normally reflective of externalizing 

behavior problems, the negative association is not necessarily surprising. 

The risk for arrest was significantly associated with out-of-home care placement 

experiences.36 Being in group home care versus traditional foster care at the time of the 

Wave 1 interview led to significantly higher hazard rates, with a group care placement at 

the time of the Wave 1 interview resulting in a 58 percent increase in the hazard rate 

when compared to a traditional foster care placement. The need for a highly restrictive 

placement setting at the onset of the transition may represent an important marker of risk 

for criminal justice system involvement. Young people who experienced multiple 

placements also had a higher hazard rate for arrest. Results show that each additional 

placement after the first resulted in a 4 percent increase in the hazard rate. This finding is 

 

36 As we did in the criminal behavior models, we tested for statistical interactions between race and placement 

experiences. None of the relationships were significant and therefore were not included in the final model presented 

here. 

63 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
particularly salient given that over 50 percent of the respondents experienced four or 

more placements during foster care. 

We found some support for the hypothesis that having bonds as one approaches 

the transition to adulthood reduces the risk of arrest. With respect to our measures of 

connections to family and caregivers, however, the results indicate that contrary to our 

expectations there appears to be little relationship with being close to one’s mother, father 

or foster caregiver and crime. However, not having a mother was related to an increase 

in the hazard rate. There was a 64 percent increase in the risk for arrest among those 

youth coded as not having a mother. 

Bonds to education and employment did predict timing to arrest in general, but 

again, results were mixed. Having plans to graduate from college and being employed at 

Wave 1 reduced the hazard rate by 24 and 32 percent respectively. Thus, those with 

plans to attend college and those employed before the onset of the transition to adulthood 

survived longer without experiencing an arrest during the transition than those 

unemployed or without college plans. Being enrolled in some form of school just prior to 

the transition, however, was not significantly related to the timing of arrest. These 

findings suggest that commitment to one’s education may be more important than simply 

the status of being in school for the timing to first arrest. However, a high percentage of 

respondents (83 percent) were enrolled in some form of education at Wave 1. It may be 

that we found no relationship between education status and the timing of arrest due to the 

limited variation in this covariate. The likelihood of turning to the child welfare system 

for assistance was not related to the hazard of first arrest. 

64 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Time to Arrest by Gender 

We also examined the hazard models separately by gender. The mean time to 

first arrest differed for males and females. For males, the mean time to first arrest, for 

those arrested, was 1040 days, or approximately 2.9 years. Over the observed range of 

data (1927 days, or about 5.3 years) the probability of being arrested is .61 for males. For 

females, the mean time to first arrest was longer, at 1408 days, or approximately 3.9 

years. Over the observed range of data, the probability of being arrested is .32 for 

females. 

Results of the Cox proportional hazards model by gender are presented in Table 

16. To determine whether the regression coefficients significantly differed across the 

models, we calculated a Z-score using the formula 2

2

2

1

21

SEbSEb

bb Z

+

− = (see Clogg, 

Petkova, and Haritou, 1995; Paternoster, Brame, Mazerolle, and Piquero, 1998), which is 

included in Table 16. Based on this test, we found little evidence of differences in the 

factors predicting time to arrest between males and females. However, we note that there 

may not be enough power to detect such differences. Therefore, although we discuss 

these gender specific models, we note that we cannot be sure that the factors examined 

here differentially predict the risk for arrest for males and females. 

For males and females, having a prior arrest and experiencing placement 

instability were significantly associated with a higher hazard rate for arrest. The high rate 

of subsequent criminal system involvement among those with previous legal system 

involvement suggests the need to take a closer look at the ways in which juvenile 

criminal system involvement intersects with foster placement experiences in ways that 

may influence subsequent criminal activity. 

65 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
For males, being employed at the onset of the transition was associated with a 

lower hazard rate of arrest; being employed resulted in a 31 percent decrease in the 

hazard rate of arrest for males. Having plans to enroll in college also resulted in a 31 

percent decrease in the hazard rate of arrest suggesting the protective effects of planning 

for the future and a commitment to education. Given the uncertainty associated with 

being in long-term foster care, the ability to plan likely reflects an important protective 

factor for young males in meeting future goals. Being enrolled in school, however, was 

not significantly related to the time to first arrest among males or females. 

With regard to bonds to parents and caregivers, we found for females that a close 

relationship with a biological mother resulted in a 24 percent increase in the hazard rate 

of arrest. For males, not having a mother resulted in a 58 percent increase in the hazard 

rate of arrest, suggesting that males who are without a mother experienced a shorter time 

to first arrest. Again, differences for these coefficients were not statistically significant 

suggesting the relationship between closeness to mother and arrest may be similar for 

males and females. 

66 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table 16. Estimates from Cox Proportional Hazard Regression of Time to First Arrest on 

Covariates By Gender 

Males Females 

Variables b SE 

Hazard 

Ratio B SE 

Hazard 

Ratio 

Z-score 

for diff 

Demographic and Background 

Risk Factors 

 Age at wave 1 -.199 .264 .82 .123 .327 1.13 -.76 

 African American .931*** .192 2.54 .338 .292 1.40 1.69 

 Other race .213 .265 1.24 .434 .321 1.54 -.53 

 Prior arrest .610** .182 1.84 1.07*** .217 2.91 -1.62 

 Neglect .043 .043 1.04 -.116 .064 .89 2.06*

 Physical abuse .044 .055 1.04 .055 .072 1.06 -.12 

 Sexual abuse/assault -.094 .237 0.91 .028 .224 1.03 -.37 

 Substance abuse diagnosis .460** .173 1.58 .382 .268 1.47 .24 

 Mental health diagnosis -.674** .241 .51 -.120 .234 .89 -1.64 

 Children .470 .265 1.60 -.086 .246 .92 1.53 

 IA -.186 .386 .83 -.000 .431 1.00 -.32 

 WI -.028 .184 .97 -.308 .324 .74 .75 

Out-of-Home Care Experiences 

 Age at entry .027 .021 1.03 -.025 .025 .98 1.59 

 Number of placements .029* .012 1.03 .060*** .016 1.06 -1.55 

 Type of placement at wave 1 

 Kinship care .166 .196 1.18 .215 .262 1.24 -.15 

 Group care .443 * .223 1.56 .441 .290 1.56 .01 

 Independent living/other .106 .352 1.11 .167 .435 1.18 -.10 

 Number of independent 

 living services .009 .006 1.01 -.008 .008 .99 1.70 

Social Bonds 

 Closeness to mother .036 .079 1.04 .213* .102 1.24 -1.37 

 Missing mother indicator .681** .255 1.98 .060 .398 1.06 1.31 

 Closeness to father .018 .078 1.02 -.022 .091 .98 .33 

 Missing father indicator -.067 .200 .93 -.031 .295 1.03 -.10 

 Closeness to caregiver -.076 .109 .93 -.024 .129 .98 -.30 

 Social support .004 .003 1.00 .004 .005 1.00 .00 

 In school .188 .206 1.21 .032 .258 1.03 .47 

 College plans -.373* .156 .69 .015 .221 1.02 -1.43 

 Employed -.399* .163 .67 -.390 .220 .68 -.03 

 Likely to ask child 

 welfare system for help -.078 .106 .92 .060 .133 1.06 0.81 

*p<.05, **p<.01, ***p<.001 (two-tailed tests) 

67 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Limitations of the Study 

In presenting our findings, we note the following limitations to the study. First, 

although this is the largest study of foster youth aging out of care since the Foster Care 

Independence Act to date, youth from only three Midwestern states are represented. 

While findings may not be generalizable to foster youth in other states, it is worth 

comparing the Midwest Study sample to the characteristics on the foster care population 

nationally. There are no readily available national data on older youth in foster care, 

however, data provided by states to the Federal government in 2001 indicate that the 

Midwest Study sample was comparable to the national foster care population in terms of 

gender, but not race and ethnicity (U.S. Department of Health and Human Services, 

2003). In 2001, just over half (52%) of children and youth in foster care nationally were 

male, compared to 49 percent of the Midwest Study sample. African Americans made up 

a larger percentage of the Midwest Study population (57%) than they did of the foster 

care population nationally (37%), whereas Hispanics made up a smaller percentage of the 

Midwest Study sample (9%) than they did of the overall foster care population (17%). 

Because the sampling frame of the Midwest Study excluded youth under the care of the 

child welfare system who were in psychiatric hospitals, incarcerated, or on runaway 

status over the course of the study field period, the study might understate to some extent 

crime outcomes for the overall population of older youth in care. 

Second, although our study benefits from a longitudinal design with high 

retention, some analyses are limited to only those youth interviewed at certain or all 

waves. For example, only those youth with information on criminal behavior at Wave 3 

were included in analyses predicting crime at age 21. Similarly we limited our latent 

class analysis to only those youth present in all three waves and who answered questions 

68 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
about their criminal behavior. There is the possibility that youth not interviewed and, 

therefore, not included in these analyses engage in more criminal behavior than those 

interviewed. Statistical checks on the data (e.g. comparing data at Wave 1 and official 

arrest records over time) as described earlier do not suggest attrition of those most likely 

to offend. However, we note this as a possible limitation. 

Third, the purpose of our study was to examine whether social bonds one has as 

he/she approaches the transition to adulthood predicts offending during the early 

transition period. Therefore, we used social bond measures at Wave 1 to predict 

subsequent behavior. It may be that the strength and type of social bonds change over 

time. Future research would benefit from examining changes in social bonds and those 

that are contemporaneous to the outcomes. 

Fourth, our social bonds measures, while noteworthy for addressing attachment to 

a variety of caregivers and for focusing on those bonds we hypothesize to be most critical 

during the early transition to adulthood, have limitations. In particular, our measures of 

attachment to parents and caregivers use only one question regarding closeness to the 

specified individual. In addition, we have no measure of parental monitoring, which is a 

focal measure in Hirschi’s theory. Again, although we hypothesized that certain social 

bonds, notably attachment to parents and caregivers and commitment to education and 

employment, would be most critical as one approaches the transition to adulthood, we 

recognize that other bonds may important as well. For example, although marriage was 

very rare among our sample, attachment to a romantic partner is a possible bond that may 

predict criminal behavior. Future research, particularly that addresses youth as they 

69 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
move further into the transition period, may benefit from considering the importance of 

romantic partners. 

Finally, future research would benefit from the use of multi-methods, possibly 

including qualitative interviews, to gain a deeper understanding of the life course 

experiences of youth aging out of foster care and their associated involvement in crime. 

70 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Policy and Practice Implications 

Since 1985, federal policy has long grappled with how to parent children in aging 

out of foster care and help them to grow up to be productive adults. There have been 

successive pieces of legislation which have attempted to address the needs of older 

children in the child welfare system, including the Independent Living Program in 1985, 

the Adoption and Safe Families Act of 1997, and the John Chaffee Foster Care 

Independence Act in 1999. More recently, the Fostering Connections to Success and 

Increasing Adoptions Act of 2008 (to be implemented in 2011) amended the Social 

Security Act to provide states who extend the age at which youth may remain in foster 

care past the age of 18 with federal funding. 

Our findings have several implications for policy, practice, and research. First, 

comparison of the Midwest Study and Add Health data on self-reported crime and arrest 

provide reason for both optimism and concern. On the one hand, youth self reports 

suggest that foster youth, like their peers, engage in less crime over time as they move 

into adulthood. In fact, while foster youth report more criminal behavior than their peers 

as they approach the age of majority, at age 19 and 21 there are few differences between 

the groups in self-reported crime. Findings from our latent class analysis indicate that 

only about one-fifth of the foster youth (19 percent; latent classes 4 and 5 combined) are 

chronic offenders, with somewhat less than half of these being nonviolent chronic 

offenders (8 percent of the sample). In other words, at least according to their own 

reports, as a group foster youth in transition pose little threat to community safety. On 

71 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
the other hand, in spite of these relatively small differences in self-reported criminal 

behavior, foster youth remain much more likely than their peers to be arrested as they 

make the transition to adulthood. These conflicting findings call for research designed to 

better understand the circumstances that lead to foster youth in transition to being 

arrested. Do their self reports mask behavior that understandably leads to arrest, or might 

they be under more scrutiny than their peers or receive less sympathy from law 

enforcement authorities? 

Second, the finding that race is a significant predictor of arrest, but not selfreported crime37, is disturbing and calls for further investigation and explanation. That 

race did not predict self reported non-violent nor violent crime in our sample when 

controlling for other factors suggests that the racial difference in official arrest versus 

self-reported outcomes may not simply be an artifact of a self reported crime measure 

that reflects trivial and non-serious offenses (see Elliot and Ageton, 1980). In other 

words, our findings are inconsistent with past work that finds significant race differences 

when examining more serious self reported crime measures (Elliot and Ageton, 1980). If 

our self-reported crime measures are not differentially valid by race (e.g. .if African 

Americans are not less likely to report engaging in certain offenses38), then our finding 

that African American youth experience greater arrests but do not reporting engaging in 

more crime suggests a possible bias in police response. Foster youth already face 

considerable challenges making the transition to adulthood and African American foster 

 

37 We note that our bivariate analyses showed a higher proportion of African American youth to be classified using 

self-report data as chronic offenders as well as non-offenders. However, multivariate analyses did not reveal racial 

differences in self reported offending. 

38 See Hindelang, Hirschi, and Weis (1981) for a discussion on this methodological issue. 

72 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
youth appear to face the added burden of heightened risk of arrest that may not reflect a 

heightened engagement in crime. 

Third, our findings suggest that greater attention is needed to ensure that older 

foster youth are provided with opportunities, both before and after reaching the age of 

majority, to become better connected to larger structures that traditionally support the 

transition to adulthood, including employment and education. Presently, there are no 

guidelines or practice standards that ensure foster youth are provided with opportunities 

to gain skills to use in the work force. Yet, the limited research that has been done on 

young adults who “aged out” of foster care has found that their labor market outcomes 

are generally quite poor, which suggests that the employment-related needs of foster 

youth are not currently being met (Courtney, Dworsky, Ruth Cusick, Keller, Havlicek, 

and Perez, 2007). Similarly, educational outcomes for foster youth are generally poor 

(Courtney and Hughes-Heuring, 2005). While the associations identified in our study 

should not be regarded as causal, the fact that prior employment and plans to attend 

college are associated with reductions in later crime argues for greater attention to 

improving the education and employment experiences of foster youth. Given the lack of 

evidence regarding the effectiveness of independent living programs directed towards 

improving education and employment outcomes, resources should be devoted to rigorous 

evaluation of interventions targeting these outcomes for foster youth (Montgomery et al, 

2006). 

Fourth, our findings on the relationships between the placement experiences of 

foster youth and later crime have implications for child welfare practice. Our findings 

suggest that it is not simply the case that youth with more difficult cases experience 

73 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
multiple placements or are placed in group settings. Placement in group care near the 

point of transition from care and a history of placement instability are strong predictors of 

criminal behavior and arrest, even after controlling for prior problem behavior, 

suggesting that placement instability and group care placement are not merely indicators 

of existing problem behavior.39 Although our analyses cannot confirm a causal 

relationship between placement instability or group care and crime, our findings do point 

to a possible opportunity for the child welfare system to act on these specific cases. The 

child welfare system may consider providing extra supports in an attempt to mitigate the 

possible detrimental impact of these particular placement experiences or those other 

external factors that may be associated with placement instability or placement in group 

care that were not examined here. Our findings suggest that efforts to prevent crime 

among foster youth making the transition to adulthood are well targeted at those in group 

care. That placement instability is associated with later crime may not be surprising, but 

it calls for renewed efforts to minimize the instability that all too often characterizes the 

lives of children and youth in care. Developing research on the effectiveness of treatment 

foster care and training of foster parents to better cope with externalizing behavior should 

help guide efforts to develop alternatives to group care and help reduce placement 

mobility of foster youth (Chamberlain et al, 2008; Leve and Chamberlain, 2005). 

 

39 We also note that we included a measure of caregiver problems and reentry to the child welfare system after a failed 

attempt at reunification in previous models not shown in this report to control for the possibility that negative 

placement experiences were indicators of antisocial behaviors of parents and continued difficulties with home 

environments. Neither was significant predictors of the outcomes and the inclusion did not change our findings for 

number of placements or group home placement. 

74 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Fifth, although we found limited support for our hypothesis that greater receipt of 

independent living services is related to less crime, our findings do suggest that these 

services are meaningful. In particular, greater receipt of independent living services was 

related to a reduction in violent behavior. This finding highlights the need for further 

research on the nature of these services, including the quality and types of programs 

being offered, availability of services, and program uptake (Naccarato and DeLorenzo, 

2008; Montgomery et al, 2006). 

Finally, our findings suggest that more attention ought to be given to 

understanding the ways in which child welfare agencies assist older foster children to 

navigate relationships with their biological parents and extended families. Contrary to 

findings for vulnerable populations which have suggested that having a close and caring 

relationship with at least one adult is an important protective factor for youth at risk, this 

study suggests that greater understanding of the multiple bonds former foster youth have 

with individuals and their communities is needed. While we found limited support for 

the hypothesis that closeness of foster youth to their parents was related to crime, we 

found stronger evidence that the absence of a parent increased the risk of self-reported 

crime and arrest. Research consistently suggests that a large percentage of these young 

people return to their families at discharge from the child welfare system (Wulcyzn and 

Hislop, 2001). It may then follow that these young people will be better served by an 

approach that attempts to minimize the risks presented by their caregivers, even when 

youth are not reunified with their caregivers. A related issue has to do with the relatives 

caring for these young people. Although the Fostering Connections to Success and 

Increasing Adoptions Act will facilitate more permanent placements with relatives, there 

75 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
is some evidence to suggest that helping relative caregivers to navigate relationships with 

biological parents may go a long way in stabilizing placements (Beeman and Boisen, 

1999) and potentially decrease familial obstacles facing foster youth during the transition 

to adulthood. 

76 

This document is a research report submitted to the U.S. Department of Justice. This report has not 

been published by the Department. Opinions or points of view expressed are those of the author(s) 

and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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