Characteristics of Victims of Sexual Abuse by Gender and Race in a Community Corrections Population

Abstract

The purpose of this study was to examine how victims of sexual abuse in a community corrections population differ as a result of their sex and race. Of the 19,422 participants, a total of 1,298 (6.7%) reported a history of sexual abuse and were compared with nonabused participants. The sample was analyzed by race–gender groups (White men, White women, African American men, and African American women) using univariate and logistic regression analyses, which were conducted separately for each group. White women were the most likely to report a history of sexual abuse (26.5%), followed by African American women (16.0%), White men (4.0%), and African American men (1.1%). For all groups, histories of suicidal ideation and suicide attempts were associated with a history of sexual abuse. Sexual abuse was associated with substance abuse problems for women but not the men. Cannabis dependence was associated with sexual abuse for the White women while cocaine dependence was associated with sexual abuse for the African American women. Several other variables were associated with sexual abuse for women but not men, including lower education (White women only), a history of violent offenses (White women only), and living in a shelter (African American women only). African American men tended to have higher levels of education; this was the only variable uniquely associated with either male group. Receiving psychiatric medications was associated with sexual abuse for all groups except African American men and a history of sex for drugs was associated with sexual abuse for all groups except White men. Consistent with national sample, women, particularly White women, were more likely to be victims of sexual abuse. The gender–race differences for the sociodemographic factors associated with sexual abuse, particularly the risk of substance abuse for women, suggest the need for tailored interventions for sexual abuse prevention and treatment.

Keywords

sexual abuse abuse drug dependence alcohol dependence community corrections race gender HIV

Introduction

Sexual abuse is a well-documented problem, with prevalence estimates ranging from 17% to 30% for women (Briere & Elliott, 2003; Kendler et al., 2000; Nelson et al., 2002; Pereda, Guilera, Forns, & Gómez-Benito, 2009). Estimates for men are slightly lower, ranging from 5% to 14% (Briere & Elliott, 2003; Nelson et al., 2002). The exact prevalence of sexual abuse is difficult to estimate as most victims do not disclose incidents of abuse for years and some never disclose the traumatic event (Hébert, Tourigny, Cyr, McDuff, & Joly, 2009). The physical and psychological harm to victims has been documented to include higher rates of suicide attempts (Briere, & Runtz, 1986; Hakansson, Bradvik, Schlyter, & Berglund, 2010), severe physical health problems (Sachs-Ericsson, Blazer, Plant, & Arnow, 2005), relationship difficulties (Feiring, Simon, & Cleland, 2009), infidelity (Whisman & Snyder, 2007), high-risk sexual behaviors (Senn, Carey, Vanable, Coury-Doniger, & Urban, 2006), borderline personality disorder (Westen, Ludolph, Misle, Ruffins, & Block, 1990), and substance abuse problems (Kilpatrick et al., 2000). The consequences have been shown to persist and in many cases cause further distress to victims. For example, female victims of sexual abuse have been shown to be more likely to abuse substances which may lead to repetitive revictimization (Kilpatrick, Acierno, Resnick, Saunders, & Best, 1997; Testa, Hoffman, & Livingston, 2010). Although many victims show remarkable resiliency (Breno & Galupo, 2007; McClure, Chavez, Agars, Peacock, & Matosian, 2007), in other cases, sexual abuse has detrimental effects on victims and continues to cause distress and impairment years after the transgression occurred.

The prevalence of victims of sexual abuse has been well documented in the criminal justice population (Wolff, Blitz, & Shi, 2007; Worling, 1995; also see Brewer-Smyth, 2004 for a review). Studies have found that both male (Johnson et al., 2006) and female (Blackburn, Mullings, & Marquart, 2008) offenders tend to report being sexually abused at higher rates than the general population. However, less attention has been directed toward the prevention and treatment of sexual abuse in this population than has been directed toward the investigation of the link between being sexually abused and becoming a sexual offender (i.e., Connolly & Woollons, 2008; Felson & Lane, 2009; Wijkman, Bijleveld, & Hendriks, 2010). Similar to the general population, sexual abuse in the criminal justice population has been linked to suicide attempts (Hakansson et al., 2010), antisocial behavior (Verona, Hicks, & Patrick, 2005), and self-mutilation (Roe-Sepowitz, 2007).

Preliminary research suggests that racial and gender differences for sexual abuse likely exist within the criminal justice population (Amodeo, Griffin, Fassler, Clay, & Ellis, 2006; Boykins et al., 2010; Brewer-Smyth, 2004). For example, existing literature indicates sexual abuse is a more significant precursor to criminal activity for women than it is for men (Brewer-Smyth, 2004). Indeed, one study found that 60% of female juvenile offenders reported being raped or being threatened with rape, and posttraumatic stress disorder was significantly higher in women compared with men (Cauffman, Feldman, Waterman, & Steiner, 1998). Furthermore, childhood sexual abuse has been documented to occur at a higher rate for African American children than for White children (Amodeo et al., 2006; Kenny & McEachern, 2000) and may represent different patterns of abuse. Compared with White children, African American children may receive more support from their mother after the assault, report higher rates of penetration as opposed to molestation, and are less likely to be abused by their biological father but more likely to be abused by an uncle (Kenny & McEachern, 2000). Following the abuse, it has been suggested that African American male victims may feel compelled to assert their masculinity to a greater extent than White male victims (McGuffey, 2008). White women are more likely to report consuming alcohol prior to assaults, whereas African American women are more likely to report using illicit drugs prior to assaults. African American women who are sexually abused are also more likely to be assaulted with a weapon (Boykins et al., 2010). In a study of general mental health in juvenile offenders, White women reported the highest prevalence of traumatic experiences and the most mental health problems, whereas African American men reported the fewest (Cauffman, 2004).

Examining the unique associations of psychosocial variables and history of sexual abuse among racial and gender groups within the criminal justice population can help to identify important risk factors that may shape future intervention strategies. Previous studies that have looked to explore differences in abuse by racial and gender groups have been limited by small sample sizes (e.g., Cauffman et al., 1998; Kataoka et al., 2001) which have made such analyses not feasible. The current study assessed history of sexual abuse, sociodemographic variables, and clinical traits (e.g., psychopathology, drug and alcohol use, and physical health) while subdivided into four racial and gender categories (White men, White women, African American men, and African American women) in a large group of community corrections participants. This sample was under community corrections supervision and enrolled in a Treatment Alternatives for Safer Communities (TASC) program that worked with individuals in the criminal justice system to coordinate and supervise substance abuse treatment as an alternative to jail or prison sentencing.

Method

Sample Characteristics

The study examined agency data collected from 2002 to 2007. All data elements were provided to the investigators without identifiers. The sample consisted of individuals from a community corrections population in the southeastern United States. All participants in this program had been charged with a felony. Of the 19,422 participants in the data set, 1,298 (6.7%) reported a history of sexual abuse. The remaining 18,124 (93.3%) were used as a comparison group. The prevalence of sexual abuse varied by gender and racial group with the highest percentage of victims being White women (26.5%) followed by African American women (16.0%), White men (4.0%), and African American men (1.1%). Participants were asked in the interview to identify their race and ethnicity via free response. Those who did not identify themselves as either being exclusively racially African American or White were excluded from analyses. Specifically, individuals identifying their ethnicity as Latino, or racial background as Native American, or Asian were excluded from analyses. Choosing how to divide people into groups and how to compare groups is always a sensitive and difficult task. Although the current study divided participants by their race and gender, we acknowledge that there exists considerable variance within both our sample and the general population. Within this set of data, participants’ self-report of race and gender was related to differences in patterns for the predictor variables; however, much of these results may be specific to the criminal justice population tested and must be viewed within the cultural framework in which they were recorded.

Data-Collection Procedures

The data were initially obtained for programmatic purposes through semistructured interviews which were administered by case managers during offenders’ enrollment into community corrections supervision. The interviews included both open-ended and close-ended questions and took approximately 1 hr to administer, and the results were then put into a summary report which was used clinically. The interviews included questions probing a range of social, psychological, and medical conditions. Data were entered directly into a database and were later extracted and provided to the investigators for this study. The variable sexual abuse was derived from the single question, “Have you ever been sexually abused?” If the interviewee endorsed that they had been sexually abused, several follow-up questions ascertaining the nature, time, and extent of abuse were asked and included in the summary report. However, the researchers did not have access to this information. The items selected as independent variables fell into two categories: sociodemographic and clinical history variables. The sociodemographic variables include age, education (<HS = less than high school, HS = high school or equivalent, >HS = greater than high school), health insurance (government, private, none), employment (unemployed, disabled, employed), and living situation (shelter, alone, relatives/friends, spouse/children). The clinical history items include suicide status (no attempts or ideation, ideation only, or attempts), prescribed medication for a mental problem, history of sex for drugs, history of a violent offense, alcohol dependence, cannabis dependence, cocaine dependence, and opiate dependence. A diagnosis of substance dependence was based on criteria established by the American Psychiatric Association (2000). The participants were asked specific questions that corresponded to diagnostic criteria. For example, the criteria of tolerance was met by a participant answering yes to either the question: “Do you have the need for markedly increased amounts of the substance to achieve intoxication or desired effect?” or “Have you experienced markedly diminished effect with continued use of the same amount of the substance?” All seven criteria were assessed and a diagnosis was based on a participant’s endorsement of three criteria in the past 12-month period.

Data Analysis

A chi-square analysis was used to examine the relationship between victims of sexual abuse and a comparison group by race and gender. A chi-square was also used to determine the association between all categorical sociodemographic and clinical history variables. “Age” was analyzed with one-way analysis of variance (ANOVA). Four separate binary logistic regression analyses were used to determine sets of risk factors associated with a history of sexual abuse among the different race–gender groups. The groups were divided by race and gender for the analyses so that a separate analysis was conducted for the African American men, the White men, the African American women, and the White women. For each analysis, the criterion variable was the participants’ answers to the question: “Have you ever been sexually abused?” Predictor variables, all of which were significant in the unvariate analyses, were then force entered into the logistic regressions. A “yes” answer to the question “Have you ever been sexually abused?” was coded as 1. As a result positive correlations with the criterion indicate a positive relationship between that specific predictor and the criterion. This study was approved by the Institutional Review Board of the University of Alabama at Birmingham.

Results

Table 1 compares the sociodemographic and clinical differences between victims of sexual abuse and the comparison group, partitioned by race–gender groupings. A similar pattern was found among all four race–gender groups; victims of sexual abuse exhibited less adaptive behavior in all areas. Regardless of the group, victims of sexual abuse were more likely to have histories of suicide attempts or ideations, be unemployed or on disability, have lived in a shelter, received medication for a mental problem, traded sex for drugs, and met criteria for alcohol and cocaine dependence. African American men and women with a history of sexual abuse were older at the time of entry into community corrections than their nonabused counterparts. Both White and African American female victims of sexual abuse reported less education than the comparison group: on the contrary, African American male victims were better educated than the comparison group. All of the victims of sexual abuse except for African American men were more likely to report being uninsured or being on government health insurance, having a history of a violent offense, and being diagnosed with cannabis dependence. In addition, White men who were sexually abused were more likely to endorse criteria for opiate dependence. When estimates of effect size were calculated between the groups, small effect sizes (i.e., a Cohen’s d of approximately .2 or Cramer’s V of approximately .1) were found for all significant relationships with few exceptions. The variable of suicide status demonstrated a medium effect size for both groups of women. Moreover, the effect sizes for trading sex for drugs for White women, suicide status for White men, and age for African American men were all between the small and medium range. Overall, results suggest that victims of sexual abuse are more dysfunctional than the comparison group, although some variations were noted between the four groups.

Table 1.

Sociodemographic Characteristics by Sexual Abuse Status (N = 19,422)

		White women			White men			African American women			African American men
Sociodemographic and clinical characteristics		No sexual abuse (N = 1,793)	Sexual abuse (N = 645)	V or d	No sexual abuse (N = 5,149)	Sexual abuse (N = 213)	V or d	No sexual abuse (N = 1,766)	Sexual abuse (N = 337)	V or d	No sexual abuse (N = 9,409)	Sexual abuse (N = 103)	V or d
Age (M, SD)		32.37; 9.89	32.71; 8.87	−0.036	32.08; 10.71	32.90; 8.86	−0.044	31.20; 10.17^a	32.72; 9.00^a	−0.158^a	30.19; 10.47^a	33.56; 10.92^a	−0.315^a
Suicide status	No attempts or ideation	81.0^a	48.9^a	0.330^a	87.2^a	42.7^a	0.256^a	88.8^a	50.1^a	0.379^a	94.4^a	56.3^a	0.175^a
	Ideation	5.4^a	8.1^a		5.5^a	16.9^a		3.9^a	12.2^a		3.0^a	16.5^a
	Attempt	13.6^a	43.0^a		7.3^a	40.4^a		7.3^a	37.7^a		2.6^a	27.2^a
Education	<HS	29.5^a	40.2^a	0.109^a	38.2^a	46.2^a	0.032^a	38.5^a	47.3^a	0.073^a	46.1^a	40.8^a	0.036^a
	HS	30.8^a	28.5^a		33.4^a	28.4^a		31.2^a	23.5^a		35.4^a	27.2^a
	>HS	40.2^a	31.3^a		28.4^a	25.5^a		30.3^a	29.2^a		18.6^a	32.0^a
Health insurance	Government	10.5^a	15.8^a	0.117^a	7.4^a	13.2^a	0.065^a	23.3^a	29.6^a	0.081^a	12.5	19.8	0.023
	Private	25.8^a	15.8^a		25.9^a	13.7^a		18.9^a	11.4^a		19.1	15.8
	None	63.7^a	68.3^a		66.7^a	73.1^a		57.9^a	59.0^a		68.4	64.4
Employment	Unemployed	48.5^a	51.7^a	0.115^a	29.4^a	38.8^a	0.065^a	44.8^a	51.3^a	0.117^a	38.6^a	45.6^a	0.034^a
	Disabled	7.9^a	14.4^a		7.2^a	12.9^a		9.7^a	16.9^a		8.6^a	15.5^a
	Employed	43.5^a	33.9^a		63.4^a	48.3^a		45.5^a	31.8^a		52.8^a	38.8^a
Living situation	Shelter	4.7^a	8.1^a	0.071^a	3.4^a	6.2^a	0.039^a	3.0^a	11.6^a	0.156^a	2.5	5.8	0.027
	Alone	9.0^a	10.1^a		14.5^a	13.8^a		12.0^a	13.1^a		8.5	10.7
	Relatives/friends	49.7^a	49.2^a		57.9^a	51.0^a		47.7^a	41.7^a		67.7	58.3
	Spouse/children	36.5^a	32.6^a		24.2^a	29.0^a		37.2^a	33.6^a		21.3	25.2
Medicated for a mental problem		26.9^a	38.1^a	0.109^a	14.6^a	32.9^a	0.099^a	9.1^a	26.4^a	0.196^a	4.3^a	21.4^a	0.086^a
Hx of trading sex for drugs		6.1^a	20.2^a	0.209^a	1.9^a	6.1^a	0.059^a	5.9^a	19.3^a	0.180^a	2.8^a	16.5^a	0.084^a
Violent offense		11.3^a	17.9^a	0.086^a	21.7^a	29.1^a	0.035^a	24.0^a	31.5^a	0.063^a	29.6	32.0	0.006
Alcohol dependence		14.3^a	24.8^a	0.123^a	26.8^a	36.6^a	0.043^a	8.9^a	18.7^a	0.117^a	16.9^a	31.1^a	0.039^a
Cannabis dependence		18.7^a	29.0^a	0.111^a	32.9^a	40.8^a	0.033^a	30.7^a	37.1^a	0.050^a	47.9	41.7	−0.013
Cocaine dependence		29.6^a	48.1^a	0.172^a	28.6^a	42.7^a	0.061^a	24.9^a	48.1^a	0.188^a	27.3^a	47.6^a	0.047^a
Opiate dependence		36.5	39.8	0.030	25.8^a	34.3^a	0.038^a	4.2	5.6	0.025	5.1	6.8	0.008

Note: For the effect size calculations Cohen’s d was used for the ANOVA run on the variable age while Cramer’s V was used for the chi-squares which were run on all other variables.

Significant results.

Results from the logistic regression (see Table 2) were similar to those found with the chi-square and ANOVA analyses; however, some variables are no longer significant as the analyses accounted for overlapping variance among the variables when grouped together. Logistic regression revealed greater differences between the four groups when investigating sexual abuse. Suicidal ideation and suicide attempts were associated with a history of sexual abuse for all of the race–gender groups. Lower education was associated with a history of sexual abuse only among White women; inversely, sexual abuse among African American men corresponded to higher education. A history of sexual abuse was associated with a lack of health insurance among White participants, although there were no significant differences regarding insurance for African American participants. Sexual abuse was associated with living in a shelter for African American women and living with relatives among White men. There was an association between sexual abuse and being medicated for a mental problem for all groups except African American men, and there was an association between sexual abuse and a history of trading sex for drugs among all of groups except White men. For White women, there were associations between sexual abuse and a history of violent offenses as well as cannabis dependence, and for African American women there was an association between sexual abuse and cocaine dependence.

Table 2.

Characteristics of Victims of Sexual Abuse in Community Corrections Population

History of sexual abuse
		White women		White men		African American women		African American men
Sociodemographic and clinical characteristics		OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Age		1.00	0.98-1.01	1.00	0.98-1.01	0.98	0.97-1.00	1.00	0.98-1.02
Suicide status	Ideation	2.24***	1.53-3.26	4.72***	3.07-7.27	4.57***	2.94-7.12	6.12***	3.35-11.17
	Attempts	3.82***	3.02-4.83	8.13***	5.75-11.49	5.99***	4.28-8.40	11.42***	6.58-19.81
	No attempts or ideation (ref)	—	—	—	—	—	—	—	—
Education	<HS	1.39**	1.08-1.78	1.03	0.70-1.50	0.99	0.72-1.37	0.62	0.37-1.03
	HS	1.14	0.88-1.47	0.85	0.56-1.27	0.73	0.51-1.03	0.52*	0.31-0.89
	>HS (ref)	—	—	—	—	—	—	—	—
Employment	Unemployed	0.97	0.77-1.21	1.24	0.89-1.73	1.07	0.80-1.45	1.34	0.84-2.13
	Disabled	1.37	0.88-2.13	1.07	0.57-2.03	1.04	0.62-1.73	0.85	0.37-1.96
	Employed (ref)	—	—	—	—	—	—	—	—
Health insurance	None	1.43*	1.08-1.89	1.77*	1.13-2.76	1.38	0.91-2.09	0.91	0.50-1.64
	Government	1.31	0.86-2.00	1.87	0.95-3.70	1.40	0.87-2.24	0.84	0.37-1.91
	Private (ref)	—	—	—	—	—	—	—	—
Living situation	Shelter	1.12	0.71-1.75	0.73	0.37-1.45	2.30**	1.33-3.99	1.05	0.40-2.75
	Alone	1.13	0.78-1.64	0.89	0.55-1.44	1.15	0.75-1.77	1.01	0.48-2.13
	Relatives	0.91	0.72-1.14	0.66*	0.46-0.94	0.83	0.61-1.12	0.83	0.50-1.37
	Spouse/children (ref)	—	—	—	—	—	—	—	—
Medicated for a mental problem		1.46**	1.16-1.84	1.60*	1.12-2.29	1.74**	1.18-2.56	1.85	0.97-3.53
Hx of trading sex for drugs		2.37***	1.71-3.30	1.78	0.90-3.54	1.74*	1.12-2.71	3.17***	1.74-5.80
Violent offense		1.38*	1.04-1.83	1.22	0.88-1.70	1.20	0.90-1.61	0.99	0.64-1.54
Alcohol dependence		1.28	0.98-1.65	1.12	0.82-1.54	1.14	0.77-1.70	1.18	0.72-1.93
Cannabis dependence		1.38**	1.08-1.76	1.23	0.89-1.71	0.99	0.74-1.33	0.70	0.45-1.09
Cocaine dependence		1.23	0.98-1.55	1.18	0.85-1.63	1.62**	1.14-2.29	1.45	0.89-2.37
Opiate dependence		0.92	0.75-1.14	1.18	0.86-1.62	1.14	0.64-2.03	1.06	0.47-2.40

p < .05. **p < .01. ***p < .001.

Discussion

The results of the study extended four well-established findings from the general population to a criminal justice population. First, women are more likely to be sexually abused than men (Bailey et al., 2003). Second, sexual abuse is associated with an increased risk of attempting suicide (Briere & Runtz, 1986; Hakansson et al., 2010). Third, sexual abuse is associated with substance use disorders (Kilpatrick et al., 2000). Fourth, victims of sexual abuse tend to have more mental health problems and tend to be more involved in the mental health care system (Chen et al., 2010). In the current sample, victims of sexual abuse reported higher levels of being medicated for a mental problem, higher levels of suicidal ideation and attempts, and higher levels of substance dependence. Overall, the results indicate that victims of sexual abuse were less financially stable; for example, they were more likely to live in a shelter, be uninsured, and be unemployed or disabled than the comparison group. Thus, the general pattern of results in the current study was in congruence with previous research.

The data show some support for the hypothesis that sexual abuse is associated with a propensity to commit crimes of a sexual nature within a criminal justice population (Felson & Lane, 2009). The literature has shown that victims of sexual abuse are more likely to commit crimes of a sexual nature, such as child molestation (Connolly & Woollons, 2008) and sex in exchange for drugs (El-Bassel et al., 2001). Our sample is not ideal for testing the hypothesized link between sexual abuse and sexual perpetration. However, it does indicate an association between sexual abuse and exchanging sex for drugs in every group except White men.

The link between sexual abuse and trading sex for money or drugs is well documented among women (Farley, Baral, Kiremire, & Sezgin, 1998; Kramer & Berg, 2003). Men who exchange sex for drugs or money have received less attention and no investigations into racial differences between sexually abused African American and White men who exchange sex for drugs or money could be found. Research by the authors Widom and Kuhns (1996) demonstrated that sexual abuse leads to prostitution in women but not in men. These authors did not look at differences between racial groups. McKirnan, Strokes, Doll, and Burzette’s (1995) examination of bisexual men indicated that African American men were more likely to engage in exchanging sex for money compared with White men. In our sample, White men were more financially equipped (i.e., higher education and employment) and may not have resorted to exchanging sex to obtain drugs; alternatively, they may have underreported this behavior due to social stigma.

Overall, White female participants were the most educated among all the groups; however, women with lower education were more likely to have a history of sexual abuse. Interestingly, the opposite pattern was observed for the African American men. Among this group, there was a positive relationship between education and sexual abuse—that is, African American male victims of sexual abuse were better educated than the comparison group. These associations bear further investigation.

Finally, we noted significant differences in health insurance status between races. White participants with a history of sexual abuse were associated with a lack of health insurance, but this was not a significant association for African American participants. Regardless of race, the victims of sexual abuse appeared to have less private insurance (14.4% compared with 21.6%) and more government insurance (19.2% compared with 11.8%), perhaps reflecting more disability insurance for mental illness.

There were several limitations to the current study. Most notably the study relied on retrospective self-report data which were collected by the participants’ case managers which may have led participants to over- or underreport psychosocial problems or events. Thus, this method of data collection did not include any formal or verified documentation of sexual abuse and also did not measure the type, duration, extent of abuse, or the relationship of the victim to the perpetrator. These factors are important and would have been useful to include as they have been shown to impact the long-term recovery of the victim. Also the participants were compared by their self-reported race and gender. Although race is a common means of self-identification, the authors acknowledge that an understanding of culture is paramount to any discussion of race. In some circumstances, the term race can be interpreted to threaten to undermine the importance of culture as well as variations in culture by asserting the importance of biology (Fontes, 1998; Fontes, Cruz, & Tabachnick, 2001). This was not the intention of using race as a criterion for distinguishing groups. Considerable differences may exist between cultures regarding both views of sexual abuse and of reporting sexual abuse. The purpose of this article was to identify at risk individuals within a criminal justice sample, no definitive conclusions about race should be generalized from these results. In addition, assessment of the participants’ clinical history also relied on retrospective self-reports and did not include any structured assessment of psychiatric diagnoses other than substance abuse or dependence. Administration of a clinical instrument to assess major psychiatric diagnostic criteria would have provided a much better understanding of the psychiatric impact that may have been associated with sexual abuse. Finally, given the uncertain timeline of events (e.g., did substance use begin before or after sexual abuse), causal inferences cannot be determined.

However, despite these limitations, this study is one of the largest to examine important psychosocial variables associated with sexual abuse and is one of the first to examine this issue among individuals under criminal justice supervision in the community. This is an important population as they comprise the bulk of individuals in the criminal justice system (about 70%) but are maintained in the community and generally unable to access mental or medical services due to a lack of insurance and poverty issues. Our findings suggest that victims of sexual abuse suffer from generally poor psychosocial functioning, including higher rates of substance abuse. More research is needed to determine ways to engage these individuals in treatment to improve psychosocial functioning and reduce criminal behavior and recidivism.

Footnotes

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

The authors received no financial support for the research, authorship, and/or publication of this article.

Bios

C. Brendan Clark, PhD, is a clinical psychologist completing his postdoctoral fellowship at the University of Alabama at Birmingham.

Adam Perkins, MA, is a clinical psychology graduate student with research interests in the treatment of substance abuse.

Cheryl B. McCullumsmith, MD, PhD, is a liaison psychiatrist with research interests in assessing and treating suicide.

M. Aminul Islam, MD, MSc, DrPH, is an assistant professor at the University of Alabama at Birmingham with research interests in mental illness, substance abuse, and criminal justice.

Erin E. Hanover, MD, is a 4th-year psychiatry resident working at the University of Alabama at Birmingham.

Karen L. Cropsey, PsyD, is an associate professor at the University of Alabama at Birmingham with research interests in addiction in criminal justice populations.

References

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text revision). Washington, DC: Author. doi:10.1176/appi.books.978089042334910.1176/appi.books.9780890423349

Amodeo

Griffin

M. L.

Fassler

I. R.

Clay

C. M.

Ellis

M. A.

(2006). Childhood sexual abuse among Black women and White women from two-parent families. Child Maltreatment, 11, 237-246. doi:10.1177/107755950628918610.1177/1077559506289186

Bailey

B. E.

Freedenfeld

R. N.

Kiser

R. S.

Gatchel

R. J.

(2003). Lifetime physical and sexual abuse in chronic pain patients: psychosocial correlates and treatment outcomes. Disability and Rehabilitation, 25, 331-342. doi:10.1080/096382802100005686610.1080/0963828021000056866

Blackburn

A. G.

Mullings

J. L.

Marquart

J. W.

(2008). Sexual assault in prison and beyond toward an understanding of lifetime sexual assault among incarcerated women. The Prison Journal, 88, 351-377. doi:10.1177/003288550832244310.1177/0032885508322443

Boykins

A. D.

Alvanzo

A. A. H.

Carson

Forte

Leisey

Plichta

S. B.

(2010). Minority women victims of recent sexual violence: Disparities in incident history. Journal of Women’s Health, 19, 453-461. doi:10.1089/jwh.2009.148410.1089/jwh.2009.1484

Breno

A. L.

Galupo

M. P.

(2007). Sexual abuse histories of young women in the U.S. child welfare system: A focus on trauma-related beliefs and resilience. Journal of Child Sexual Abuse, 16, 97-113. doi:10.1300/J070v16n02_0610.1300/J070v16n02_06

Brewer-Smyth

(2004). Women behind bars: Could neurobiological correlates of past physical and sexual abuse contribute to criminal behavior? Health Care for Women International, 25, 835-852. doi:10.1080/0739933049051711810.1080/07399330490517118

Brewer-Smyth

Burgess

A. W.

Shults

(2004). Physical and sexual abuse, salivary cortisol, and neurologic correlates of violent criminal behavior in female prison inmates. Biological Psychiatry, 55, 21-31. doi:10.1016/S0006-3223(03)00705-410.1016/S0006-3223(03)00705-4

Briere

Elliott

D. M.

(2003). Prevalence and psychological sequelae of self-reported childhood physical and sexual abuse in a general population sample of men and women. Child Abuse & Neglect, 27, 1205-1222. doi:10.1016/j.chiabu.2003.09.00810.1016/j.chiabu.2003.09.008

10.

Briere

Runtz

(1986). Suicidal thoughts and behaviours in former sexual abuse victims. Canadian Journal of Behavioural Science 18, 413-423. doi:10.1037/h007996210.1037/h0079962

11.

Cauffman

(2004). A statewide screening of mental health symptoms among juvenile offenders in detention. Journal of the American Academy of Child and Adolescent Psychiatry, 43, 430-439. doi:10.1097/01.chi.0000112481.08386.0c10.1097/01.chi.0000112481.08386.0c

12.

Cauffman

Feldman

Waterman

Steiner

(1998). Posttraumatic stress disorder among female juvenile offenders. Journal of the American Academy of Child and Adolescent Psychiatry, 37, 1209-1216. doi:10.1097/00004583-199811000-0002110.1097/00004583-199811000-00021

13.

Chen

L. P.

Murad

M. H.

Paras

M. L.

Colbenson

K. M.

Sattlar

A. L.

Goranson

E. N.

Zirakzadeh

(2010). Sexual abuse and lifetime diagnosis of psychiatric disorders: Systematic review and meta-analysis. Mayo Clinic Proceedings, 85, 618-629. doi:10.4065/mcp.2009.058310.4065/mcp.2009.0583

14.

Connolly

Woollons

(2008). Childhood sexual experience and adult offending: An exploratory comparison of three criminal groups. Child Abuse Review, 17, 119-132. doi:10.1002/car.101910.1002/car.1019

15.

El-Bassel

Simoni

J. M.

Cooper

D. K.

Gilbert

Schilling

R. F.

(2001). Sex trading and psychological distress among women on methadone. Psychology of Addictive Behaviors, 15, 177-184. doi: 10.1037//0893-164X.15.3.17710.1037//0893-164X.15.3.177

16.

Feiring

Simon

V. A.

Cleland

C. M.

(2009). Childhood sexual abuse, stigmatization, internalizing symptoms, and the development of sexual difficulties and dating aggression. Journal of Consulting and Clinical Psychology, 77, 127-137. doi:10.1037/a001347510.1037/a0013475

17.

Felson

R. B.

Lane

K. J.

(2009). Social learning, sexual and physical abuse, and adult crime. Aggressive Behavior, 35, 489-501. doi:10.1002/ab.2032210.1002/ab.20322

18.

Fontes

L. A.

(1998). Ethics in family violence research: Cultural issues. Family Relations, 47, 53-61.

19.

Fontes

L. A.

Cruz

Tabachnick

(2001). Views of child sexual abuse in two cultural communities: An exploratory study with African Americans and Latinos. Child Maltreatment, 6, 103-117. doi:10.1177/107755950100600200310.1177/1077559501006002003

20.

Hakansson

Bradvik

Schlyter

Berglund

(2010). Factors associated with the history of attempted suicide. Crisis, 31, 12-21. doi:10.1027/0227-5910/a00000810.1027/0227-5910/a000008

21.

Hébert

Tourigny

Cyr

McDuff

Joly

(2009). Prevalence of childhood sexual abuse and timing of disclosure in a representative sample of adults from Quebec. The Canadian Journal of Psychiatry, 54, 631-636.

22.

Johnson

R. J.

Ross

M. W.

Taylor

W. C.

Williams

M. L.

Carvajal

R. I.

Peters

R. J.

(2006). Prevalence of childhood sexual abuse among incarcerated males in county jail. Child Abuse & Neglect, 30, 75-86. doi:10.1016/j.chiabu.2005.08.01310.1016/j.chiabu.2005.08.013

23.

Kataoka

S. H.

Zima

B. T.

Dupre

D. A.

Moreno

K. A.

Yang

McCracken

J. T.

(2001). Mental health problems and service use among female juvenile offenders: Their relationship to criminal history. Journal of the American Academy of Child and Adolescent Psychiatry, 40, 549-555. doi:10.1097/00004583-200105000-0001410.1097/00004583-200105000-00014

24.

Kendler

K. S.

Bulik

C. M.

Silberg

Hettema

J. M.

Myers

Prescott

C. A.

(2000). Childhood sexual abuse and adult psychiatric and substance use disorders in women: An epidemiological and cotwin control analysis. Archives of General Psychiatry, 57, 953-959.

25.

Kenny

M. C.

McEachern

A. G.

(2000). Racial, ethnic and cultural factors of childhood sexual abuse: A selected review of the literature. Clinical Psychology Review, 20, 905-922. doi:10.1016/S0272-7358(99)00022-710.1016/S0272-7358(99)00022-7

26.

Kilpatrick

D. G.

Acierno

Resnick

H. S.

Saunders

B. E.

Best

C. L.

(1997). A 2-year longitudinal analysis of the relationships between violent assault and substance use in women. Journal of Consulting and Clinical Psychology, 65, 834-847. doi:10.1037//0022-006X.65.5.83410.1037//0022-006X.65.5.834

27.

Kilpatrick

D. G.

Acierno

Saunders

B. E.

Resnick

H. S.

Best

C. L.

Schnurr

P. P.

(2000). Risk factors for adolescent substance abuse and dependence: Data from a national sample. Journal of Consulting and Clinical Psychology, 68, 19-30. doi:10.1037//0022-006X.68.1.1910.1037//0022-006X.68.1.19

28.

Kramer

L. A.

Berg

E. C.

(2003). A survival analysis of timing of entry into prostitution: The differential impact of race, education level, and childhood/adolescent risk factors. Sociological Inquiry, 73, 511-528. doi: 10.1111/1475-682X.0006910.1111/1475-682X.00069

29.

McClure

F. H.

Chavez

D. V.

Agars

M. D.

Peacock

M. J.

Matosian

(2007). Resilience in sexually abused women: Risk and protective factors. Journal of Family Violence, 23, 81-88. doi:10.1007/s10896-007-9129-410.1007/s10896-007-9129-4

30.

McGuffey

(2008). “Saving masculinity”: Gender reaffirmation, sexuality, race, and parental responses to male child sexual abuse. Social Problems, 55, 216-237. doi:10.1525/sp.2008.55.2.21610.1525/sp.2008.55.2.216

31.

McKirnan

D. J.

Strokes

J. P.

Doll

Burzette

R. G.

(1995). Bisexually active men: Social characteristics and sexual behavior. The Journal of Sex Research, 32, 65-76

32.

Nelson

E. C.

Heath

A. C.

Madden

P. A. F.

Cooper

M. L.

Dinwiddie

S. H.

Bucholz

K. K.

. . . Martin

N. G.

(2002). Association between self-reported childhood sexual abuse and adverse psychosocial outcomes: Results from a twin study. Archives of General Psychiatry, 59, 139-145.

33.

Pereda

GuPereda

Guilera

Forns

Gómez-Benito

(2009). The prevalence of child sexual abuse in community and student samples: A meta-analysis. Clinical Psychology Review, 29, 328-338. doi:10.1016/j.cpr.2009.02.00710.1016/j.cpr.2009.02.007

34.

Roe-Sepowitz

(2007). Characteristics and predictors of self-mutilation: A study of incarcerated women. Criminal Behavior and Mental Health, 17, 312-321. doi:10.1002/cbm.66510.1002/cbm.665

35.

Sachs-Ericsson

Blazer

Plant

E. A.

Arnow

(2005). Childhood sexual and physical abuse and the 1-year prevalence of medical problems in the National Comorbidity Survey. Health Psychology, 24, 32-40. doi:10.1037/0278-6133.24.1.3210.1037/0278-6133.24.1.32

36.

Senn

T. E.

Carey

M. P.

Vanable

P. A.

Coury-Doniger

Urban

M. A.

(2006). Childhood sexual abuse and sexual risk behavior among men and women attending a sexually transmitted disease clinic. Journal of Consulting and Clinical Psychology, 74, 720-731. doi:10.1037/0022-006X.74.4.72010.1037/0022-006X.74.4.720

37.

Testa

Hoffman

J. H.

Livingston

J. A.

(2010). Alcohol and sexual risk behaviors as mediators of the sexual victimization-revictimization relationship. Journal of Consulting and Clinical Psychology, 78, 249-259. doi:10.1037/a001891410.1037/a0018914

38.

Verona

Hicks

B. M.

Patrick

C. J.

(2005). Psychopathy and suicidality in female offenders: Mediating influences of personality and abuse. Journal of Consulting and Clinical Psychology, 73, 1065-1073. doi:10.1037/0022-006X.73.6.106510.1037/0022-006X.73.6.1065

39.

Westen

Ludolph

Misle

Ruffins

Block

(1990). Physical and sexual abuse in adolescent girls with borderline personality disorder. American Journal of Orthopsychiatry, 60, 55-66.

40.

Whisman

M. A.

Snyder

D. K.

(2007). Sexual infidelity in a national survey of American women: Differences in prevalence and correlates as a function of method of assessment. Journal of Family Psychology, 21, 147-154. doi:10.1037/0893-3200.21.2.14710.1037/0893-3200.21.2.147

41.

Widom

C. S.

Kuhns

J. B.

(1996). Childhood victimization and subsequent risk for promiscuity, prostitution, and teenage pregnancy: A prospective study. American Journal of Public Health, 86, 1607-1612.

42.

Wijkman

Bijleveld

Hendriks

(2010). Women don’t do such things! Characteristics of female sex offenders and offender types. Sexual Abuse: A Journal of Research and Treatment, 22, 135-156. doi:10.1177/107906321036382610.1177/1079063210363826

43.

Wolff

Blitz

C. L.

Shi

(2007). Rates of sexual victimization in prison for inmates with and without mental disorders. Psychiatric Services, 58, 1087-1094. doi:10.1176/appi.ps.58.8.108710.1176/appi.ps.58.8.1087

44.

Worling

J. R.

(1995). Sexual abuse histories of adolescent male sex offenders: Differences on the basis of the age and gender of their victims. Journal of Abnormal Psychology, 104, 610-613.