Poly-Victimization Among Girls in the Justice System

Abstract

Life History Calendars and the Juvenile Victimization Questionnaire were used to collect data from 100 delinquent girls to (a) examine range and co-occurrence of different types of violence over the life span, (b) examine independent and cumulative trajectories of risk for varied types of victimization, and (c) examine the relationship of victimization to girls’ offending. Risk trajectories demonstrate critical risk periods for different forms of violence exposure. Cox regression was used to examine the predictive value of different forms of violence exposure for the onset of delinquent and criminal behavior. Findings illuminate the need for programs addressing substance use and alternative coping mechanisms.

Keywords

delinquency girls poly-victimization

Introduction

Increased awareness among researchers, practitioners, and policy makers regarding violence exposure has led to a need to explore range and consequences of different forms of exposure for children living in varied contexts of risk. The present project focused on girls adjudicated delinquent, a population plagued by high levels of exposure to violent events. Exposure within this population is of particular interest not only because these girls experience numerous other health risks (e.g., poverty, mental disorders) but also because of the socio-behavioral risk that victimization may pose according to emerging theory on girls’ and women’s crime. Because crime and delinquency are among the most feared consequences of violence exposure, and because girls face escalating risk for exposure once involved in delinquency, focusing on this population has great potential for theory as well as practice and policy.

Children Exposed to Violence

Exposure to violence ranges from direct exposure to physical, sexual, or psychological abuse to witnessing violence in the family or community. Although researchers note difficulties in establishing prevalence estimates of childhood exposure to violence (Fantuzzo & Mohr, 1999; Salcido, Welthorn, & Behrman, 1999), they indicate that it is commonplace, particularly for children in urban environments. The literature on effects of exposure largely derives from research on direct abuse and witnessing intimate partner violence. Fantuzzo and Mohr (1999) provide an overview of effects of child witnessing violence, including findings from review articles spanning decades (Fantuzzo & Lindquist, 1989; Kolbo, Blakely, & Engleman, 1996; Margolin, 1998). Children from violent (vs. non-violent) homes are said to display greater levels of externalizing, such as aggression and behavior problems in schools and communities; internalizing, such as depression, anxiety, fearfulness, suicidal ideation, sleep problems, bedwetting, and low self-esteem; cognitive difficulties, including trouble concentrating and lower test scores; and social competence problems, including lack of empathy and impaired problem solving. Adverse effects vary across developmental stages and are more likely when witnessing co-occurs with direct abuse or ecological risk factors (e.g., family conflict, parental addiction). Other research indicates that, as children grow older, effects of exposure are more likely to include risky and delinquent behavior such as sexual promiscuity, substance abuse, truancy, running away, and property crime (Thornberry, Huizinga, & Loeber, 2004; Widom, 1995a, 1995b).

Trickett, Negriff, Ji, and Peckins (2011) review more recent work on child maltreatment, including physical abuse, sexual abuse, emotional maltreatment, and neglect. These researchers identify maltreatment’s association with a range of internalizing and externalizing behaviors and conclude that all types of maltreatment negatively affect formation of friendships and increase peer rejection. They note that this, in conjunction with aggression and poor emotion regulation, can lead to further behavior problems, emphasizing persistence of effects into adolescence and adulthood. They also emphasize the differing and interactive effects of varied types of maltreatment. Similarly, Iwaniec (1997) underscores the enmeshment of varied types of maltreatment, stating that emotional maltreatment is “the core of all major forms of abuse and neglect” and that “it requires special attention to disentangle emotional from physical acts of maltreatment” (p. 370). Margolin and Gordis (2000) cite co-occurrence of different types of violence exposure as one of the major methodological challenges in the literature on effects of violence.

Accordingly, a prominent gap in the research literature pertains to associations between different types of violence exposure. Finkelhor, Ormrod, Turner, and Hamby (2005) examined “poly-victimization”—simultaneously experiencing several different kinds of victimization in separate incidents (e.g., bullying, witnessing violence, sexual abuse). These researchers examined methods of operationally defining poly-victimization using the Juvenile Victimization Questionnaire (JVQ) and found that no matter how poly-victimization was operationalized, children who experienced multiple victimizations were at high risk of additional victimization and trauma symptomatology (e.g., anger, depression, anxiety) relative to other children. In fact, sheer number of victimizations was a better predictor of children’s symptomatology than any particular type of victimization.

If, indeed, children who experience high levels of exposure to violence also carry the bulk of emotional and behavioral symptomatology, this may lend insights to the recurring social question of why some abused individuals commit crimes while others do not (i.e., different volumes and/or intersecting impacts of victimization). Given such considerations regarding the aggregate impact of victimization, the field would benefit from an understanding that takes into account not only different types of exposure but also factors such as the trajectory of risk over the life span, dependence of different forms of exposure, and ways that cumulative impacts influence life outcomes.

Examining childhood violence exposure from a methodological viewpoint, past research is based largely on adults’ perceptions of children’s experiences. As users of services, children require interventions tailored to their levels of understanding, developmental capacities, and unique circumstances (Mullender et al., 2002). Researchers and funders are thereby beginning to recognize the need for studies tapping views of children (McGee, 2000; Mullender et al., 2002). Furthermore, most studies of violence exposure focus on past-year or lifetime prevalence, without detailed consideration of changing risks and co-occurrence of violence over the life span (Yoshihama & Gillespie, 2002). As we will explain, our event-history methods were innovative in garnering both qualitative and quantitative data with events mapped over children’s life spans.

Girls in the Juvenile Justice System

Rates of delinquency are rising among girls, and detention units are struggling with chronic overcrowding (Snyder & Sickmund, 1999). Experts argue that the disproportionate growth of the population of girl offenders is, in part, due to “fundamental systemic failure” to understand girls’ needs, noting girls’ “invisibility” in the justice system with regard to abuse histories, pregnancy, and other gendered issues (American Bar Association [ABA] & National Bar Association [NBA], 2001; Chesney-Lind & Shelden, 1992). Recent studies (Salisbury & Van Voorhis, 2009; Wright, Salisbury, & Van Voorhis, 2007; Wright et al., 2012) have emphasized the importance of gender responsiveness in the assessment and processing of female offenders, noting that factors such as child and adult victimization, family stress and support, and mental health disorders appear to significantly contribute to the prediction of justice-related outcomes for women. This and other research (e.g., Belknap & Holsinger, 2006; Topitzes, Mersky, & Reynolds, 2011; Zahn et al., 2010) are contributing to an ever-growing body of knowledge regarding gendered pathways to offending, with victimization as a key consideration in women’s and girls’ crime and delinquency.

Indeed, there is considerable evidence that victimization is pervasive in the backgrounds of delinquent girls. In interviews with nearly 100 female juvenile offenders, Cauffman, Feldman, Watherman, and Steiner (1998) found that more than 70% had been exposed to trauma such as molestation or witnessing violence. About three quarters of those interviewed had been badly hurt or in danger of being hurt, three quarters had witnessed someone being severely injured or killed, and 60% had been raped or nearly raped. Similarly, Wood and associates (Wood, Foy, Goguen, Pynoos, & James, 2002; Wood, Foy, Layne, Pynoos, & Boyd, 2002) found that, relative to boys, their sample of 100 girls in the juvenile system experienced high levels of physical punishment, sexual violence, exposure to community violence, and psychological distress associated with exposure. Other research on incarcerated youth (Belknap & Holsinger, 2006; Steiner, Garcia, & Matthews, 1997) also found rates of direct victimization to be higher among girls. Artz (1998) found victimization rates and fear of revictimization to be higher among violent versus non-violent girls. Finally, in a study of nearly 1,000 case files and 193 interviews with girl offenders, Acoca (1998) found strong correlations between violence exposure and risk behaviors, such as poly-drug use and gang membership. Once involved in delinquency, girls face heightened risk of re-exposure to violence in association with crime-involved peer networks and high-risk hangouts or activities (Widom, 2000), as well as in group homes and detention settings (Acoca & Dedel, 1998). Such girls may be reluctant to report or to use services due to their marginalized social position and precarious legal status (Richie, 2000).

Existing studies have provided a valuable foundation regarding the prevalence of victimization and other risks among delinquent girls. However, the studies typically use limited concepts of victimization (e.g., one or two types of exposure) and a focus on the identification of mental disorders. There is a lack of research specifically to gather information on frequency and co-occurrence of different forms of violence exposure, its trajectory over the girls’ life spans, and relationship of violence exposure to juvenile offending. The current study addressed these gaps in the literature.

Method

Research Measures

Archival data

For each participant, we had access to juvenile justice admissions data, including basic demographics and offense history with justice contacts and sanctions.

Life History Calendar method

The Life History Calendar (LHC; Freedman, Thornton, Camburn, Alwin, & Young-DeMarco, 1988) is an established research tool designed to optimize accuracy in the collection of event timing/sequencing data. The LHC method uses a calendar-like matrix, providing visual cues said to enhance both interviewee and interviewer performance. Column headings typically denote years or ages, whereas row headings denote categories of life events. At the outset of the interview, the interviewer explains the calendar and, with the respondent’s help, maps memorable life experiences (e.g., schools, grades, living arrangements, neighborhoods). These salient cues then provide a temporal context for recalling events that may be less salient in time (e.g., “The abuse happened when I was in third grade living with my aunt”). The LHC’s rows and columns encourage recall at both thematic and temporal levels and thereby increase autobiographical memory (Axinn, Pearce, & Ghimire, 1999; Belli, 1998).

Criminologists have used the LHC method with populations including incarcerated offenders, with calendar timeframes ranging from a single month to a 40-year period; findings indicate strong test–retest reliability and validity, as well as responsiveness to administration needs of those with unstable lives and cognitive difficulties (Sutton, 2010; Sutton, Bellair, Kowalski, Light, & Hutcherson, 2011). Here, as in that research, the LHC was used in conjunction with lifetime victimization measures, that is, we administered items verbatim from the victimization measure, with each item denoted as a calendar row. Girls then assisted as we mapped each event to the columns of the calendar (i.e., ages/grades from birth up to current age), and girls were encouraged to elaborate in their own words to describe each event (e.g., “Can you tell me a bit about that?”). A simplified sample of a completed LHC is provided in the appendix.

JVQ

Our measure of exposure to violence was the JVQ, one of the most rigorously constructed measures of exposure to violence (Hamby & Finkelhor, 2004). The JVQ includes items on child maltreatment, gang violence, dating violence, sexual victimization, and witnessing/indirect victimization, among other things. (Table 1 includes breakdowns of subtypes of exposure within major categories.) For girls’ interviews, we adapted the child self-report version of the JVQ with items orally administered in sequence. Based on input from a consultant experienced in the extensive use of the JVQ (Heather Turner, personal communication, January 10, 2007), we did not use the scale in its entirety given the need to keep interviews to a manageable length. We also made minor wording changes for suitability for our intended audience. We used lifetime retrospective administration, an option provided in the full manual (Hamby, Finkelhor, Ormrod, & Turner, 2004). Girls were asked the first time they remembered each event happening and about subsequent times if it happened more than once. Follow-up prompts addressed number of times the child was victimized, relationship to perpetrator, whether the child was hurt, and questions specific to the victimization.

Table 1.

Prevalence of Self-Reported Victimization for Girls.

Girls’ victimization experiences	% girls^a (N = 100)
Any caregiver violence	69
Physical abuse	50
Psychological abuse^b	46
Neglect	23
Parental kidnapping or custodial interference	10
Gang or group attacks	31
Dating violence	42
Any sexual violence	81
Assaults by known adults	36
Assaults by unknown adults	14
Assaults by peers	20
Attempted rape	20
Flashing	14
Verbal sexual harassment	11
“Consensual” sex with adults^c	69
Any witnessed violence	90
Witnessed assault of the caregiver	45
Witnessed assault of a sibling by the caregiver	23
Witnessed a bad attack with a weapon	55
Witnessed a bad attack without a weapon	36
Had a close friend/family who was murdered	46
Witnessed a murder	35
Seen or heard community shootings or riots	57

Categories are not mutually exclusive.

We coded caregivers’ provision of alcohol or illicit drugs to girls—behavior sometimes referred to as “missocializing” or “corruption” (American Professional Society on the Abuse of Children, 1995; Hart, Germain, & Brassard, 1987)—as a form of psychological abuse.

To accommodate variations in age of consent from age 14 to 18 across different U.S. states (Norman-Eady, Reinhart, & Martino, 2003), the category “consensual” sex with adults (i.e., statutory rape) includes events for which any girl under the age of 18 stated that she willingly engaged in sexual intercourse with an adult 18 years of age or older.

Other prompts

To assess general family history, offense history, contacts with services or systems, and social supports, we adapted additional prompts from our previous study of incarcerated women (DeHart, 2008). For purposes of this article, we focus on offenses including alcohol and drug use, stealing (e.g., shoplifting, burglary), running away, fighting or physical assaults, and prostitution.¹

Recruitment and Interview Procedures

Our sample consisted of 100 girls adjudicated delinquent and housed at either the primary long-term commitment facility for girls or one of the two main group homes for girls within a Southeastern state. One group home was for girls who, because of offense history or personal characteristics, were deemed by the agency as in need of “moderate” management, and the other was for those deemed in need of “high” management. (These differentiations have since been done away with in practice.) Prospective participants were identified via the juvenile justice database and met individually with the interviewer in a private room at the juvenile facility. A single interviewer performed all 100 interviews. Assent forms were presented both in written form and read aloud to the child. If the child assented, we conducted the interview at that time. Girls who chose to participate received a $20 cash deposit to the facility spending account. We conducted exhaustive sampling of incoming girls over a multi-year period to obtain our sample of 100 girls from the three facilities.

Data Transfer and Analysis

Field notes and calendar mapping

We chose to use field notes in conjunction with life calendar mapping to document child interviews. Given our success with shorthand-style field notes (EasyScript; Levin, 2001), we felt that benefits of audiotaping were outweighed by the elevated risk to participants. Interviewer training included mock interviews with performance to a benchmark of limited errors and omissions. To promote the integrity of data, the interviewer transcribed speedwritten notes into interview transcripts and translated life calendar data into electronic format within 24 hours of each interview. Within transcripts, we attempted to be as accurate as possible in representing each girl’s thoughts and to use the words and language she used, as well as to honor veracity of her account (i.e., omitting outsider inferences about plausibility). We chose to transcribe using third-person perspective to underscore that these are not direct quotes, in that thoughts have been necessarily filtered through the interviewer.

Quantitative analyses

SPSS was used to conduct all quantitative analyses. Descriptive statistics were performed to attest to characteristics of our sample and their self-reported experiences of victimization. Key victimization and offending constructs from girls’ interviews were conceptualized in several ways, including (a) binary presence/absence coding of whether the girl experienced the event in question, (b) time-to-onset coding to indicate age at which the girl first experienced the event, and (c) frequency coding to indicate the number of incidents of the event.² We used survival analyses and Cox regression for time-to-onset dependent variables and standard parametric techniques (e.g., Pearson correlation) for continuous dependent variables. For any multiple comparisons, we adjusted significance thresholds using the Bonferroni method.

Qualitative analyses

Qualitative interview transcripts were coded and analyzed using ATLAS.ti software. Passages can be tagged with commentary or labeled with codes (e.g., “sexual abuse”). Passages, codes, and commentaries can be sorted into hierarchies, and participant files can be grouped into “families” or categories (e.g., “group homes”). For purposes of the present article, we used a first-cycle coding method with provisional top-down coding based on categories of items in girls’ interviews. This approach allowed us to identify specific exemplars to illustrate findings revealed in quantitative analysis of girls’ interview data. In this way, we bring ATLAS.ti’s powerful capabilities to bear upon inferences as these emerge from the quantitative data, which thereby helps us to understand manifest associations between variables.

Results

Participants

In total, 98% of girls who were invited to participate did so. Our sample of 100 committed girls ranged in age from 12 to 18, with the mean, median, and modal age being 16 years old. In all, 63% of girls were African American, 35% were White, and 2% were Hispanic; 58 girls were sampled from the long-term commitment facility, and the remaining girls were from the moderate-management (n = 22) and high-management (n = 20) group homes. Exploratory analyses indicated no differences between girls sampled from the long-term facility and those sampled from group homes for key variables, so groups were aggregated for analyses.

Prevalence of Victimization

Descriptive statistics were performed to examine frequencies for self-reported violence exposure. As can be seen in Table 1, victimization was pervasive. On average, girls experienced about three of these five major categories of violence and about 7 of the 20 subtypes of violence within their lifetimes (M = 3.13 and M = 6.72, respectively). Only 2% of girls reported no victimization.

Associations Among Types of Victimization

Table 2 shows Pearson correlations for associations among categories of victimization. For each of the five categories of victimization, we used the variable indicating the number of victimizations within that category. We have also included a variable indicating the count of each of the 20 subtypes of victimization reported by the girl. Of the five major categories of victimization, witnessing violence demonstrated the most consistent associations with other categories, and gang attacks showed the least consistency. As one would expect given the literature on poly-victimization, the number of subtypes of victimization experienced was highly correlated with all categories of victimization.

Table 2.

Pearson Correlations Among Victimization Categories.

	Gang violence	Dating violence	Sexual violence	Witnessing violence	No. of types of victimization experienced
Caregiver violence	.34*	.26	.22	.38*	.57*
Gang violence		.17	.25	.44*	.47*
Dating violence			.34*	.35*	.45*
Sexual violence				.41*	.64*
Witnessing violence					.74*

p < .003, Bonferroni-adjusted criterion.

Risk Trajectories for Victimization

Survival analyses were used to examine risk trajectories for each category of violence. The median time for which girls were exposed to risk (e.g., age at interview) was 16 years. Figure 1 illustrates the trajectory of risk for each category of victimization and for poly-victimization. These hazard functions graphically illustrate the proportion of those girls who were exposed to risk and experienced a given event. For example, the hazard function for caregiver violence shows that approximately one quarter of the 100 girls experienced caregiver violence by age 4. These girls have “terminated” (experienced onset for this category of violence) and are removed from the remaining calculations. At age 5, another girl experiences caregiver violence and is removed from the sample, 5 more terminate at age 6, 1 terminates at age 7, 3 at age 8, and so on. The dots on the graph indicate the number of those terminating relative to the number left in the sample at that step, and this is a measure of the “riskiness” of that particular age. At age 14, for instance, 7 of the remaining 34 girls experience caregiver violence, resulting in a 20% hazard rate; that is, if a girl had not already experienced violence by this age, she has a 7 out of 34 chance of experiencing it. It should be noted that because fewer cases remain in analyses at later stages, estimates at these stages might be viewed as less stable than those based on a greater number of cases. For instance, by the final caregiver violence interval representing girls at age 16, only 5 girls remained in the sample (i.e., exposed to risk), but 1 of these 5 experienced caregiver violence, resulting in the relatively high 1-in-5 hazard rate.

Figure 1.

Interpolated hazard for categories of victimization.

As can be seen by the interpolated hazard functions, risk for caregiver violence (Mdn age of onset = 12) peaks prior to school age and shows sporadic increases thereafter. Risk for gang attacks (Mdn = 17) begins in pre-pubescence and peaks in early adolescence, with risk declining in later adolescence. Risk for dating violence (Mdn = 16) begins around pubescence and rises dramatically thereafter. Girls face some risk of sexual violence (Mdn = 13) throughout childhood, with risk increasing around pubescence and peaking sharply in early adolescence, then declining thereafter. Risk for witnessing violence (Mdn = 8) begins before school age, rises throughout pubescence, and peaks in late adolescence. Poly-victimization (as operationalized by experiencing four or more subtypes of victimization³; Mdn = 15) presents some risk throughout childhood, with risk rising throughout adolescence. Median ages indicate that girls tend to risk witnessing violence at an earlier age than other categories of violence, followed by caregiver violence, sexual violence, dating violence, and gang violence.

Risk Trajectories for Crime and Delinquency

Survival analyses were used to examine risk trajectories for each category of delinquency as well as for the onset of involvement with the justice system. Figure 2 illustrates the trajectory of risk for each category of delinquency and for juvenile justice involvement. As can be seen by the interpolated hazard functions, risk for substance use (Mdn = 13) begins prior to school age for a very small number of girls and increases sporadically in pre-pubescence, and then rises steadily throughout most of adolescence. There exists some risk for stealing (Mdn = 14) throughout childhood, with hazard rising markedly throughout adolescence. Risk for running away (Mdn = 14) begins in pre-pubescence and rises sharply throughout adolescence. Fighting (Mdn = 12) shows an early peak in risk prior to school age, followed by multiple subsequent peaks in adolescence. Prostitution risk (Mdn = 17) begins around pubescence and peaks sharply near age 15. Finally, first involvement in the justice system (Mdn = 14) shows a gradual slope, with risk beginning as early as school age and escalating throughout adolescence. Median ages indicate that girls tend to become involved in fighting slightly before becoming involved in substance use, followed by stealing and running away. Around that same age, girls may come to the attention of the justice system. Involvement in prostitution tends to occur later in adolescence. It is notable that the curve for justice involvement is more closely aligned with those for offenses such as stealing and running away than for those such as substance use or physical assaults.

Figure 2.

Interpolated hazard for delinquency and justice involvement.

Association of Victimization to Onset of Crime and Delinquency

Cox regression was used to examine how number of self-reported victimizations may predict the age of onset for each type of self-reported offense. Each regression equation included one of the five crime types as a dependent variable and the five victimization categories entered in one step as independent variables. Trimmed equations were then performed using only those independent variables that met a significance threshold of p < .10. For purposes of this article, we will focus only on significant findings.

For the age of first substance use, number of caregiver victimizations and number of witnessing victimizations met criteria for inclusion in the trimmed equation. The overall model was significant, χ²(2, N = 100) = 20.75, p < .001, and both categories of victimization contributed to the prediction of substance use onset. For the age of first fight, only number of witnessing victimizations contributed to prediction, χ²(1, N = 100) = 4.27, p < .05. For the age of first prostitution, number of sexual victimizations and number of witnessing victimizations contributed to prediction, χ²(2, N = 100) = 15.07, p < .001. Table 3 displays Cox regression coefficients and other relevant statistics for each equation.

Table 3.

Cox Regressions.

Variable	B	SE	Wald	df	p	β
Number of victimizations on the onset of substance use (N = 100)
Caregiver violence	0.241	.102	5.597	1	.018	1.272
Witnessing violence	0.430	.133	10.533	1	.001	1.538
Number of victimizations on the onset of fighting (N = 100)
Witnessing violence	0.216	.105	4.247	1	.039	1.241
Number of victimizations on the onset of prostitution (N = 100)
Sexual violence	1.411	.329	18.425	1	.000	4.101
Witnessing violence	−0.635	.268	5.633	1	.018	0.530

Qualitative Exploration of Patterns

To delve further into these associations, we examined girls’ narrative accounts of victimization and crime, specifically searching the qualitative data set for examples of a victimization–crime linkage. We attempted to choose quotes that were representative of the sample while still being illustrative of associations between constructs.

Substance use and victimization

In Cox regressions, substance use was associated with experiences of caregiver violence and witnessing violence. Examination of qualitative accounts revealed that the use of alcohol and drugs as a means of coping was an underlying theme across all three associations. Consider the following accounts:

Alice is still going to drink when she’s out of here. It makes you forget your problems for just one night—problems like past stuff from when her mom used child abuse and was on drugs . . . stuff like that never goes away.

Angie saw her mom beaten by her dad all of her life. . . . Every fight there was a bloody nose or busted lip, bruises. Lots of times her mom would have broken bones. Angie didn’t like it. Drugs helped her cope.

Corruption involving parents or other caregivers was also a factor in girls’ substance use:

Jenna did OxyContin with her mom the first time. That’s how Jenna’s mom found out that Jenna was doing it and snorting it because they sniffed it when they did it together. It was weird because her mom patted her on the back for snorting it. Like most kids get patted on the back by their moms for playing sports or something, and Jenna’s mom patted her on the back for snorting pills. It made Jenna feel like a badass, kinda cool.

Cynthia’s uncles used to sell drugs and that’s how Cynthia got exposed to all that. Her uncles knew that kids at school wanted it, and they asked Cynthia if she wanted to sell and earn some money.

Once involved in substance use, girls’ presence in risky situations was sometimes associated with witnessed violence:

Jenna saw a murder in tenth grade. Jenna was with the lady to go get drugs . . . She saw it . . . The lady spoke Spanish, and she and the man were arguing in Spanish. He took a gun out of his back pocket . . . There was brain everywhere. That image . . . it was terrifying. It takes your breath away, when the life of someone is taken. It’s powerful in a weird, creepy way.

Fighting and victimization

The association between witnessing violence and engaging in fighting or assaults was often a function of girls’ use of retaliatory or protective violence, as is illustrated in the following examples:

The whole time Sandy lived with her grandmother, she used to see her grandmom beat Sandy’s sister. That’s when Sandy started beating on her grandmom. Sandy and her sister didn’t call DSS because they knew their grandmom would get locked up.

When Alice was 16 she jumped her cousin’s baby’s daddy because he spit in her face . . . Alice beat him with her brothers. They were kicking him and all. Alice still has blood on the shoes she was wearing when she came in here to DJJ from that.

Prostitution and victimization

Involvement in prostitution was typically associated with girls’ sexual relationships with exploitative men:

Amber had a sugar daddy in tenth and eleventh grade. She would have sex with him for money and other stuff. He was in his 60s. He was on the news this year because he got busted.

Emily was tricking when she ran away at 16 and 17. She probably did it 20 times . . . [A crackhead she knew] suggested it as a way they could get money. Emily has lots of flashbacks about it. She wonders why she ever did it, how she even got in that position. She gets pictures of it happening in her head.

Prostitution activity was, in turn, associated with dating violence from pimps as well as witnessed violence associated with risky situations:

Corretta was attacked a lot by the dude she was with. He would pistol whip her and drag her down the strip by her hair . . . He used to say he did it because he loved her. It would happen because Corretta didn’t do what she was told . . . He’d drag her off the fire escape back inside, beat her, and make her have sex—with him and with other people. He’d do it even if she was bleeding—then he’d make her have oral sex. Corretta has dreams about it, and sometimes if she’s thinking about it, she’ll break down and cry.

Discussion

These girls committed to juvenile facilities reported very high levels of victimization, particularly caregiver violence, sexual violence, and witnessing violence. Many girls experienced multiple types of violence exposure. Examining the hazard function for different categories of victimization and isolating time periods with steep slope changes is a way to identify risky time periods for girls (Singer & Willett, 1991), periods during which prevention or risk reduction may take on heightened importance. Within this sample of delinquent girls, risk trajectories indicated susceptibility to caregiver violence and witnessed violence starting prior to school age, with a second peak in risk during adolescence. Thus, early childhood and adolescence may be times to target trauma-informed interventions to specifically address these risks and provide support that may mitigate impacts of violence exposure. This might be integrated into school-based programs, after-school programs, or community-based mentoring or membership organizations (e.g., Big Sisters, Girl Scouts). In contrast, risk for gang or group attacks began rising just before pubescence, and dating violence risk logically escalated after pubescence. Sexual violence was a risk for girls throughout their lives, but was particularly prevalent during adolescence. Thus, early preventive education on such risks might be supplemented with skill-building around adolescence to bolster girls’ resilience to these threats. The early onset of violence exposure, as well as recurring exposure to risk throughout childhood and adolescence, indicates that the assessment for victimization and trauma should occur early and frequently in girls’ lives. Furthermore, programs or services to address multiple, co-occurring forms of violence exposure might be implemented throughout girls’ lives, and especially during the teen years, as the likelihood of poly-victimization increases. Several recent publications provide excellent resources for practitioners who work with victims of multi-abuse trauma in delivery of trauma-informed care (e.g., Edmund & Bland, 2011; Jennings, 2011).

Hazard functions for crime and delinquency evinced assaultiveness and substance use as risks that emerge relatively early in girls’ lives, prior to their involvement with justice agencies. Thus, it may be advisable to raise awareness about the origins and consequences of externalizing and internalizing behaviors among youth. For instance, school administrators and school social workers might benefit from specific education regarding the association of trauma with behavioral problems such as fighting and substance abuse, as well as education regarding community resources and early intervention strategies. Offenses such as stealing and running away were more prominent around early adolescence, about the same time girls come to the attention of the justice system. This may be indicative of a tendency to utilize justice responses to address these problems. Because prostitution tended to occur later in adolescence, after most girls had already entered the justice system, juvenile justice programmers may wish to develop more focused awareness and risk reduction around sexual exploitation.

Our findings regarding associations between victimization and girls’ offending provide valuable information regarding content for gender-responsive programming to reduce crime and delinquency. One prominent theme in girls’ accounts involved substance abuse as a form of self-medication used to cope with past caregiver violence and witnessed violence. This illuminates the need for education and services addressing alcohol and drug use among traumatized girls, as well as need for skill-building to develop alternative coping mechanisms to address violence and other stressors in girls’ lives. Our findings indicated that girls’ use of violence and aggression frequently occurred in retaliation to witnessed violence in the girls’ homes or communities. Thus, enhancing the safety of girls’ ecological contexts may be a necessary step in reducing this type of reactive aggression. Again, alternative coping skills may be needed, including non-violent conflict resolution and use of appropriate systemic resources (e.g., law enforcement, social services). Both substance abuse and involvement in prostitution bore associations to these young girls’ relationships with criminally involved adults. These findings highlight the importance of examining corruption of girls through social networks, including mis-socialization by caregivers and sexual exploitation by older men. This also holds important policy implications for addressing child corruption. For instance, advocates for girls might wish to address guidelines and penalties surrounding issues such as provision of alcohol and drugs to minors, statutory rape, and enticement of youth into criminal activities such as drug dealing and prostitution. Girls’ accounts also illustrated how involvement in high-risk activities such as drug use and commercial sex work heightened risk for revictimization, including exposure to drug and gang violence, physical abuse from “johns” and pimps, and sexual assaults by acquaintances and predators. These risks indicate that there may be a need for greater presence of confidential community-based services to address victimization that may occur in a criminal context, in that these victims may be unlikely to utilize systemic resources for fear of implicating themselves in criminal conduct.

Collectively, project findings have theoretical implications regarding the range and consequences of violence exposure for at-risk girls, as well as applied utility for service interventions, justice interventions to promote rehabilitation and accountability, and efforts to increase safety for delinquent girls through work with families and communities. This might include applications for educators, faith-based groups and non-governmental organizations that provide services in community settings, program developers and social service staff working in juvenile justice settings, and policy makers concerned about the well-being of youth and families. Furthermore, our findings provide information for researchers regarding the importance of focusing inquiry on issues such as victimization by caregivers and sexual predators and the role of social networks in girls’ pathways to delinquency. Understanding prevalence and dynamics of these risks is essential for developing effective prevention, risk reduction, and intervention.

Regarding the timing of various types of victimization and delinquency relative to one another, our survival analyses and median ages of onset show some interesting patterns that merit discussion. Analyses indicate that victimization experiences began earlier than delinquent behavior, particularly for the three types of victimization that were most closely associated with offending: caregiver violence, sexual violence, and witnessing violence. The earliest victimization experiences included witnessing violence, with a median age of onset of 8 years old, and caregiver violence, with a median onset of 12 years. The earliest self-reports of offending tended to be for fighting, with a median onset of 12 years of age. Substance abuse and sexual violence appeared to follow with medians at age 13. Around 14, the girls began running away, stealing, and becoming involved for the first time in the justice system. Dating violence, gang violence, and prostitution were typically manifest later in the girls’ teens. These findings should be viewed cautiously, as these patterns of occurrence are derived from group hazard rates and median scores rather than individual girls’ pathways of risk. Nevertheless, the progression is a familiar one: victimization to status offenses such as substance use and running away, then to “street” crimes such as stealing and prostitution, which place girls at further risk of community violence and intimate partner violence. This sequence closely approximates early theories of pathways to offending put forth by researchers (Chesney-Lind & Rodriguez, 1983; Daly, 1992; Gilfus, 1992).

The current findings are limited in deriving from a modest sample of girls committed to juvenile facilities. Our participants may have been more criminally involved or experienced higher levels of victimization than delinquent girls who had not penetrated the juvenile justice system. Similarly, these findings may not generalize to girls who were referred to adult youthful offender programs. For particular delinquent activity within our sample (e.g., stealing, running away), it is possible that ceiling effects of frequent offending or other sample biases may have attenuated associations with victimization. Additional research might examine associations between victimization and delinquency among probationers or less systemically involved girls. Researchers could also investigate ways in which patterns identified here continue into adulthood. Finally, research is needed to explore how potential intervening variables including resiliency, substance use, and mental health outcomes may mediate or moderate associations between girls’ victimization and delinquency.

Footnotes

Appendix

Sample Life History Calendar (Actual Sample With Some Details Changed to Protect Confidentiality)

Grade	Preschool	1	2	3	4	5	6	7	8	9	10	11
School	As & Bs							Fs; fights in school
School				Suspended & write-ups for disrespecting teachers, disturbing school, cigarettes, tardiness
Home	live w/Mom, Dad, Sis			Mom & Sis	Dad, Stepmom, Grandmom				Mom	Dad	Grandmom	Mom
				Di-vorce
								D drank more
												Mom crack
Alcohol & drugs	drinking some							drinking regularly & using cocaine
					smoking pot & huffing chemicals
											meth
Crime & delinquency						Trespass
						Dmg prop
								Disturbing school
								Drv w/o lic			Drv w/o lic
										Incite riot
										Dirty urine
											Grand larc
											Selling crack
											Poss gun
												Endngr child
											Shoplifting, stealing
											Prostitution
Victimization					Dad beat		Dad beat					Mom beat
								Dad & stepmom call whore
		Witness Dad/Mom DV
	Sexual Assault – cousin
	SA–peer		SA–peer					SA drug’d
	SA–gang
								Sex with older men
											Dating violence
											Witness drug violence

Acknowledgements

We thank Seokwon Yoon for providing research assistance for the project. We also appreciate contributions of our project advisory board, consultants, and the many girls who shared their stories.

Authors’ Note

Points of view in this document are those of the authors and do not necessarily represent the official position or policies of the U.S. Department of Justice or the South Carolina Department of Juvenile Justice.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was supported by Grant 2006-WG-BX-0011 awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice, and in cooperation of the South Carolina Department of Juvenile Justice.

Notes

Author Biographies

Dana D. DeHart is assistant Dean for Research at the University of South Carolina’s College of Social Work. Her specialty area is violence and victimization, particularly as these relate to women’s and girls’ offending and victim service responses. She has expertise in needs assessment, program evaluation, scale design, and ethical research design. She is interested in exploring a range of qualitative and quantitative methods, and she has extensive experience with state and federally funded projects.

Robert Moran is a clinical assistant professor and director of Data Support Services at the University of South Carolina’s Department of Epidemiology and Biostatistics. He teaches courses on data management, epidemiologic methods, and biostatistics. His research interests include nutritional measurement, diabetes, disabilities, and mental health.

References

Acoca

(1998). Outside/inside: The violation of American girls at home, on the streets, and in the juvenile justice system. Crime & Delinquency, 44, 561-589.

Acoca

Dedel

(1998). No place to hide: Understanding and meeting the needs of girls in the California juvenile justice system. San Francisco, CA: National Council on Crime and Delinquency.

American Bar Association & National Bar Association. (2001). Justice by gender: The lack of appropriate prevention, diversion, and treatment services for girls in the juvenile justice system. Chicago, IL: Author.

American Professional Society on the Abuse of Children. (1995). Psychosocial evaluation of suspected psychological maltreatment in children and adolescents. Cultic Studies Journal, 13, 153-170.

Artz

(1998). Sex, power, and the violent school girl. Toronto, Ontario, Canada: Trifolium.

Axinn

Pearce

Ghimire

(1999). Innovations in Life History Calendar applications. Social Science Research, 28, 243-264.

Belknap

Holsinger

(2006). The gendered nature of risk factors for delinquency. Feminist Criminology, 1, 48-71.

Belli

(1998). The structure of autobiographical memory and the event history calendar: Potential improvements in the quality of retrospective reports in surveys. Memory, 6, 383-406.

Cauffman

Feldman

Watherman

Steiner

(1998). Posttraumatic stress disorder among female juvenile offenders. Journal of the American Academy of Child & Adolescent Psychiatry, 37, 1209-1216.

10.

Chesney-Lind

Rodriguez

(1983). Women under lock and key: A view from the inside. Prison Journal, 63, 47-65.

11.

Chesney-Lind

Shelden

(1992). Girls, delinquency, and juvenile justice. Pacific Grove, CA: Brooks/Cole.

12.

Daly

(1992). Women’s pathway to felony court: Feminist theories of lawbreaking and problems of representation. Southern California Review of Law and Women’s Studies, 2, 11-52.

13.

DeHart

D. D.

(2008). Pathways to prison: Impact of victimization in the lives of incarcerated women. Violence Against Women, 14, 1362-1381.

14.

Edmund

Bland

(2011). Real tools: Responding to multi-abuse trauma. Juneau: Alaska Network on Domestic Violence & Sexual Assault.

15.

Fantuzzo

Lindquist

(1989). The effects of observing conjugal violence on children: A review and analysis of research methodology. Journal of Family Violence, 4, 77-94.

16.

Fantuzzo

Mohr

(1999). Prevalence and effects of child exposure to domestic violence. Future of Children, 9(2), 21-32.

17.

Finkelhor

Ormrod

Turner

Hamby

(2005). Measuring poly-victimization using the Juvenile Victimization Questionnaire. Child Abuse & Neglect, 29, 1297-1312.

18.

Freedman

Thornton

Camburn

Alwin

Young-DeMarco

(1988). The life history calendar: A technique for collecting retrospective data. Sociological Methodology, 18, 37-68.

19.

Gilfus

(1992). From victims to survivors to offenders: Women’s routes of entry and immersion into street crime. Women & Criminal Justice, 4, 63-89.

20.

Hamby

Finkelhor

(2004). The comprehensive Juvenile Victimization Questionnaire. Durham, NH: Crimes against Children Research Center.

21.

Hamby

Finkelhor

Ormrod

Turner

(2004). The Juvenile Victimization Questionnaire (JVQ): Administration and scoring manual. Durham, NH: Crimes Against Children Research Center.

22.

Hart

S. M.

Germain

Brassard

M. R.

(1987). The challenge: To better understand and combat the psychological maltreatment of children and youth. In Brassard

M. R.

Germain

Hart

S. N.

(Eds.), Psychological maltreatment of children and youth (pp. 3-24). New York: Pergamon.

23.

Iwaniec

(1997). An overview of emotional maltreatment and failure-to-thrive. Child Abuse Review, 6, 370-388.

24.

Jennings

(2011). Models for developing trauma-informed behavioral health systems and trauma-specific services: An update of the 2004 report. Washington, DC: U.S. Department of Health and Human Services.

25.

Kolbo

Blakely

Engleman

(1996). Children who witness domestic violence: A review of empirical literature. Journal of Interpersonal Violence, 11, 281-293.

26.

Levin

(2001). EasyScript express. Newton, MA: Legend.

27.

Margolin

(1998). Effects of domestic violence on children. In Trickett

P. K.

Shellenbach

C. J.

(Eds.), Violence against children in the family and the community (pp. 57-101). Washington, DC: American Psychological Association.

28.

Margolin

Gordis

(2000). The effects of family and community violence on children. Annual Review of Psychology, 51, 445-479.

29.

McGee

(2000). Childhood experiences of domestic violence. London, England: Kingsley.

30.

Mullender

Hague

Imam

Kelly

Malos

Regan

(2002). Children’s perspectives on domestic violence. Thousand Oaks, CA: Sage.

31.

Norman-Eady

Reinhart

Martino

(2003). Office of Legislative Research Report: Statutory rape laws by state. Hartford, CT: Office of Legislative Research, General Assembly.

32.

Richie

(2000). Exploring the link between violence against women and women’s involvement in illegal activity. In Samuels

(Ed.), Research on women and girls in the justice system: Plenary papers of the 1999 Conference on Criminal Justice Research and Evaluation (Vol. 3, pp. 1-13). Washington, DC: U.S. Department of Justice.

33.

Salcido

Welthorn

Behrman

(1999). Domestic violence and children: Analysis and recommendations. Future of Children, 9(3), 4-20.

34.

Salisbury

Van Voorhis

(2009). Gendered pathways: A quantitative investigation of women probationers’ paths to incarceration. Criminal Justice and Behavior, 36, 541-566.

35.

Singer

Willett

(1991). Modeling the days of our lives: Using survival analysis when designing and analyzing longitudinal studies of duration and the time of events. Psychological Bulletin, 110, 268-290.

36.

Snyder

Sickmund

(1999). Juvenile offenders and victims: 1999 national report. Washington, DC: Office of Juvenile Justice and Delinquency Prevention.

37.

Steiner

Garcia

I. G.

Matthews

(1997). Posttraumatic stress disorder in incarcerated juvenile delinquents. Journal of American Academy of Child & Adolescent Psychiatry, 36, 357-365.

38.

Sutton

J. E.

(2010). A review of the life-events calendar method for criminological research. Journal of Criminal Justice, 38, 1038-1044.

39.

Sutton

J. E.

Bellair

P. E.

Kowalski

B. R.

Light

Hutcherson

(2011). Reliability and validity of prisoner self-reports gathered using the life event calendar method. Journal of Quantitative Criminology, 27, 151-171.

40.

Thornberry

Huizinga

Loeber

(2004). The causes and correlates studies: Findings and policy implications. Juvenile Justice, 9. Retrieved from https://www.ncjrs.gov/html/ojjdp/203555/jj2.html

41.

Topitzes

Mersky

Reynolds

(2011). Child maltreatment and offending behavior: Gender-specific effects and pathways. Criminal Justice and Behavior, 38, 492-510.

42.

Trickett

Negriff

Peckins

(2011). Child maltreatment and adolescent development. Journal of Research on Adolescence, 21, 3-20.

43.

Turner

Finkelhor

Ormrod

(2006). The effect of lifetime victimization on the mental health of children and adolescents. Social Science & Medicine, 62, 13-27.

44.

Widom

(1995a). Cycle of violence revisited 6 years later. Washington, DC: U.S. Department of Justice.

45.

Widom

(1995b). Victims of childhood sexual abuse: Later criminal consequences. Washington, DC: U.S. Department of Justice.

46.

Widom

(2000). Childhood victimization and the derailment of girls and women to the criminal justice system. In Samuels

(Ed.), Research on women and girls in the justice system: Plenary papers of the 1999 Conference on Criminal Justice Research and Evaluation (Vol. 3, pp. 27-36). Washington, DC: U.S. Department of Justice.

47.

Wood

Foy

Goguen

Pynoos

James

(2002). Violence exposure and PTSD among delinquent girls. Journal of Aggression, Maltreatment & Trauma, 6, 109-126.

48.

Wood

Foy

Layne

Pynoos

Boyd

(2002). An examination of the relationships between violence exposure, posttraumatic stress symptomatology, and delinquent activity: An “ecopathological” model of delinquent behavior among incarcerated adolescents. Journal of Aggression, Maltreatment & Trauma, 6, 127-147.

49.

Wright

Salisbury

Van Voorhis

(2007). Predicting prison misconducts of women offenders: The importance of gender-responsive needs. Journal of Contemporary Criminal Justice, 23, 310-340.

50.

Wright

Van Voorhis

Salisbury

Bauman

(2012). Gender responsive lessons learned and policy implications for women in prison: A review. Criminal Justice & Behavior, 39, 1612-1632.

51.

Yoshihama

Gillespie

(2002). Age adjustment and recall bias in the analysis of domestic violence data: Methodological improvements through the application of survival analysis methods. Journal of Family Violence, 17, 199-221.

52.

Zahn

Agnew

Fishbein

Miller

Winn

Dakoff

. (2010). Girls study group: Understanding and responding to girls’ delinquency. Washington, DC: U.S. Department of Justice.