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Journal of Child Sexual Abuse Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/wcsa20
Differentiating Single and Multiple Victim Child Sexual Abuse Cases: A Research Note Considering Social Disorganization Theory a
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Elizabeth Ehrhardt Mustaine , Richard Tewksbury , Jay Corzine & Lin Huff-Corzine a
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University of Central Florida , Orlando , Florida , USA
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University of Louisville , Louisville , Kentucky , USA Published online: 06 Jan 2014.
To cite this article: Elizabeth Ehrhardt Mustaine , Richard Tewksbury , Jay Corzine & Lin HuffCorzine (2014) Differentiating Single and Multiple Victim Child Sexual Abuse Cases: A Research Note Considering Social Disorganization Theory, Journal of Child Sexual Abuse, 23:1, 38-54, DOI: 10.1080/10538712.2014.863260 To link to this article: http://dx.doi.org/10.1080/10538712.2014.863260
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Journal of Child Sexual Abuse, 23:38–54, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 1053-8712 print/1547-0679 online DOI: 10.1080/10538712.2014.863260
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RESEARCH ON CHILD SEXUAL ABUSE AND ADULT SURVIVORS
Differentiating Single and Multiple Victim Child Sexual Abuse Cases: A Research Note Considering Social Disorganization Theory ELIZABETH EHRHARDT MUSTAINE University of Central Florida, Orlando, Florida, USA
RICHARD TEWKSBURY University of Louisville, Louisville, Kentucky, USA
JAY CORZINE and LIN HUFF-CORZINE University of Central Florida, Orlando, Florida, USA
This study examined the utility of social disorganization theory as an explanation for child sexual abuse with a focus on differentiating single and multiple victim cases. Drawing on 1,172 child sexual abuse cases (including 159 cases with multiple victims) in Orange County, Florida, from 2004 to 2006, the present study considered case characteristics and elements of social disorganization as potential predictors of child sexual abuse cases involving single and multiple victims. We found that social disorganization theory does not successfully predict the locations of multiple victim child sexual abuse incidents and is not useful for distinguishing between child sexual abuse incidents with single or multiple victims. KEYWORDS child disorganization
sexual
abuse,
community,
social
Received 30 May 2012; revised 12 June 2012; accepted 27 August 2012. Address correspondence to Richard Tewksbury, Department of Justice Administration, University of Louisville, Brigman Hall, Louisville, KY 40292. E-mail: [email protected] 38
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Sexual offenses, especially those perpetrated against children, are among the most serious and most despised crimes in American society. Criminal justice policy and practice has focused a bright light on sexual offenses, especially those against children, in recent decades. Recent years have witnessed both substantial public attention to the issue (media coverage of sexual abuse in the Catholic Church and the Penn State football cases) as well as a continuation of ambivalence and reluctance to directly confront the issue in many arenas. In part due to the divergent and sometimes seemingly contradictory ways that contemporary society has responded to the sexual abuse of children, research addressing the issue has been plagued by methodological difficulties, widely divergent estimates of prevalence and incidence, and challenges to the identification of “true” statistics (Douglas & Finkelhor, 2005). Significant advances have been in made in recent decades in our understanding of the dynamics of child sexual abuse through examinations of the correlates of victimization, perpetration, and service/treatment needs for victims and offenders. However, two issues have remained largely absent in the scholarly literature concerning child sexual abuse: (a) the influence of community characteristics on incidents and rates of child sexual abuse and (b) the explication of characteristics of child sexual abuse cases involving multiple victims (including if and how such cases may differ from cases involving only one victim). The goal of the present study was to begin addressing these two gaps in the literature. A concern with whether community-level issues are related to the incidence of child sexual abuse is important because if neighborhood structural issues are found to correlate with varying rates of such offenses then both criminal justice and child welfare officials may be able to more effectively and efficiently target scarce resources to prevention, intervention, and responses to victims. Understanding and addressing macrolevel issues requires information about both community characteristics and individual cases of child sexual abuse.
CHILD SEXUAL ABUSE AND SOCIAL DISORGANIZATION Rates of Child Sexual Abuse Researchers have estimated that children make up 66% of all known victims of sexual assault (Snyder, 2000), and sexual abuse has accounted for approximately 7% to 10% of all reports of child maltreatment in the United States (U.S. Department of Health and Human Services, 2009). Estimates of the prevalence of child sexual abuse range from 9% to 32% for adult women (Douglas & Finkelhor, 2005). A meta-analysis of 22 American studies suggests that 30% to 40% of girls and 13% of boys experienced sexual abuse during childhood (Bolen & Scannapieco, 1999).
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An often overlooked aspect of child sexual abuse (outside of occasional high profile media attention) concerns cases that involve multiple victims. According to data from the National Incident Based Reporting System (NIBRS), for 1991 to 1996, 19% of victims of child sexual abuse were assaulted along with another child (Snyder, 2000). One in 8 instances (13%) of child sexual abuse involved at least 2 victims, and 6% included 3 or more victims (Snyder, 2000). Unfortunately, relatively little is known about multiple victim cases. However, when multiple victims are present, younger children are more likely to be involved than older juveniles (Snyder, 2000). For young children who were sexually abused, 1 in 4 victims under the age of 12 was victimized by a perpetrator with more than 1 victim (Snyder, 2000). However, only 13% of sexual abuse victims over the age of 12 were sexually abused with another victim. Multiple victim child sexual abuse cases were also more likely to involve girls than boys (Snyder, 2000). However, beyond initial estimates of number and age and the sex distributions of victims, little is known about children who are sexually victimized with others, and essentially no research has examined the characteristics of communities in which multiple victim child sexual abuse is more likely to occur.
Characteristics of Sexually Abused Children and Perpetrators Sexually abused children come from all socioeconomic, cultural, and demographic categories. Even so, there are important patterns and trends that can be seen in the population of sexually abused children. First, girls are more likely than boys to be victimized (Snyder, 2000). Furthermore, although children of all ages can be, and are, sexually abused, girls are more likely to be sexually abused in early adolescence (ages 11 to 14) while boys are most often victimized during their preschool or early elementary school years (ages 4 to 6; Berliner & Elliott, 2002). Gender also appears to interact with socioeconomic status, as sexually abused boys are more likely to come from lower socioeconomic households, while sexually abused girls come from all socioeconomic backgrounds (Berliner & Elliott, 2002). Research about sexual abuse perpetrators has suggested that they are almost always men (Bolen, 2001; Preble & Groth, 2002; Snyder, 2000). Women who sexually abuse children do so less frequently and most often offend against very young (age 6 and under) victims (Snyder, 2000). Somewhat contradictory to popular belief, the majority of reported child sexual abuse cases do not involve immediate family members (Douglas & Finkelhor, 2005; Finkelhor & Ormrod, 2001, Snyder, 2000). While there is a preexisting relationship between most child sexual abuse victims and perpetrators, it is often one of acquaintanceship, family friend, or extended family. Only relatively rarely are child sexual abuse victims and offenders strangers (Finkelhor & Ormrod, 2001). When familial sexual abuse of children does occur, it is most likely to be perpetrated against girls (Berliner & Elliott,
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2002; Finkelhor, 1984). In addition, familial sexual abuse may be most likely to occur in low-income households (Berliner & Elliott, 2002; Gartner, 2005; Preble & Groth, 2002).
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COMMUNITY CHARACTERISTICS AND SOCIAL DISORGANIZATION THEORY In addition to examining the characteristics of individual victims and perpetrators of child sexual abuse, it is important to assess characteristics of communities in which child sexual abuse is more or less prevalent. This has not been a focus of significant research, however, leading Payne and Gainey (2009) to conclude that “few studies have addressed how community level factors contribute to child abuse” (p. 123). The study of community characteristics and their possible relationships with locations and rates of crime and violence typically draws on social disorganization theory. Social disorganization theory focuses on issues of economic and social disadvantage, community cohesion, and population (in)stability as factors that correlate with crime, disorder, and the lack of effective informal social control mechanisms. At its core, social disorganization theory includes aspects of not only whether residents lack social and economic capital but also the presence and strength of inhabitants’ relationships with other residents. The theory assumes that when economic and social capital is low and interactions and bonds between residents (e.g., collective efficacy and community cohesion) are weak or lacking, numerous forms of disorder, including criminal victimization, will increase (Bursik & Grasmick, 1993; Shaw & McKay, 1942). Since its initial appearance in the early 20th century, scholars have repeatedly demonstrated the value of social disorganization concepts for explaining numerous forms of crime, especially violent crime (Hannon & Defina, 2005; Morenoff, Sampson, & Raudenbush, 2001; Pratt & Cullen, 2005; Pridemore, 2002; Sampson, Raudenbush, & Earls, 1997). Research on social disorganization theory has also identified critical concepts and variables that are necessary for accurately and adequately assessing the role of social disorganization and its relationship to criminal activity. Central to any social disorganization analysis are concepts (and accompanying measures) of economic disadvantage, community cohesion, stability of the community’s residential population, and the presence of individuals prone to both criminal behavior and victimization.
Community Characteristics and Child Abuse Interestingly, while research has identified aspects of social disorganization as important for explaining the occurrence and distribution of child
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maltreatment (defined as physical, sexual, and emotional child abuse and neglect; Coulton, Korbin, & Su, 1999; Drake & Padney, 1996; Garbarino & Sherman, 1980; Paulsen, 2003; Zuravin, 1989), few scholars have assessed whether social disorganization may be related to child sexual abuse specifically. Given that child sexual abuse is only one component of child maltreatment and that the perpetrators of child sexual abuse are less likely to be family members than perpetrators of other forms of maltreatment, it may be that locations and correlates of child sexual abuse differ from the correlates of child maltreatment in general. The limited available research suggests that children who are left alone, who are unsupervised, or who do not have the physical presence of numerous friends and neighbors are more likely to be sexually abused (Berliner & Elliott, 2002; Bolen, 2001). Regarding residential stability, Lauritsen (2003) showed that youth who have lived at their current address for shorter periods of time are more likely to suffer a variety of violent victimizations. However, others (Paulsen, 2003; Spearly & Lauderdale, 1982) have found that residential stability is not related to child abuse or neglect. With the limited evidence being mixed, it is important to continue to investigate if and how measures of community cohesion, stability, and interactions may be related to rates of child sexual abuse. To date, only three studies have specifically addressed the potential role of community characteristics and social disorganization as contributing factors to child abuse in general or to child sexual abuse specifically. Paulsen’s (2003) spatial analysis of 156 cases of child abuse and 134 cases of child neglect shows that child abuse is more geographically dispersed than child neglect and that spatial areas with high rates of child abuse are the most dispersed. Regarding community characteristics, Paulsen reports that census tracts with higher rates of poverty and those with larger total and Black populations are more likely to have a higher number of reported cases of child abuse. Furthermore, 25% of the variation in child abuse rates is explained by measures of neighborhood disadvantage and the percent of the population that is Black. One important conclusion offered by Paulsen (2003) is that residential stability is not a significant predictor of child abuse or neglect; rather, issues of economic disadvantage are clearly more important for explaining where child abuse occurs. Two additional studies (Mustaine, Tewksbury, Huff-Corzine, & Corzine, 2011; Tewksbury, Mustaine, & Covington, 2010) have also examined the role of social disorganization in explaining rates of child abuse. Tewksbury and colleagues (2010) argued that social disorganization offers a moderate level of explanation (27%) for understanding sexual offenses against children. They did so by focusing on distinguishing census tracts as being more or less socially disorganized than the county average and concluded that a high level of social disorganization in a census tract is significantly related to increased child sexual abuse rates. They also found that the census tract’s
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percentage of the population that was women age 16 to 64 years with a disability was significant in predicting child sexual abuse. However, they were not able to consider measures of collective efficacy and social cohesion, and they did not distinguish between measures of economic disadvantage and other types of social disorganization. Mustaine and colleagues (2011) examined all cases of documented sexual assault in Orange County, Florida, over a three-year period and found that, for the 1,172 cases of child sexual abuse, social disorganization theory provided a strong explanation for varying rates of offenses across census tracts. Specifically, they concluded that social disorganization theory provides a strong explanation for varying rates of child sexual abuse, with economic disadvantage, residential instability, greater population density, more violent crime, more registered sex offenders in residence, lower levels of female economic status relative to men, and a greater concentration of never married men in the census tract as significant predictors of increased rates of child sexual abuse. Somewhat contrary to social disorganization theory, however, they also found that as the concentration of immigrants in the population increases, the rate of reported child sexual abuse actually decreases.
Other Potential Relationships with Child Sexual Abuse Based on other research findings, two additional community characteristics may also be important in explaining rates of child sexual abuse, including rates of incidents with multiple victims. First, the presence of known sexual offenders in a community may be related to increased rates of child sexual abuse (as the belief behind many recent legal developments, including sex offender registries and community notification, is that the presence of known sex offenders is a risk factor for victimization). In addition, when considering social disorganization theory approaches for explaining sex offense rates of any type, it is important to recognize that registered sex offenders are known to be severely limited in their housing options (Barnes, Dukes, Tewksbury, & DeTroye, 2009; Levenson, Zgoba, & Tewksbury, 2007; Tewksbury & Levenson, 2007) and to more frequently reside in socially disorganized areas (Mustaine, Tewksbury, & Stengel, 2006a, 2006b; Tewksbury & Mustaine, 2006). Second, as both Tewksbury and colleagues (2010) and Mustaine and colleagues (2011) show, female status indicators (concentration of women with disabilities and the economic status of women relative to men, respectively) are important for predicting child sexual abuse rates. As such, some measure of gendered circumstances is important to consider. Considering these issues and the weaknesses of the current literature, the present study seeks to explain whether social disorganization theory is a useful perspective for understanding and differentiating locations of incidents of child sexual abuse with single and multiple victims. Overall, our goal is
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to examine whether community-level and case-level variables are useful in understanding the distribution of child sexual abuse cases with single versus multiple victims across metropolitan areas.
METHODS
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Data We obtained data sets for incidents, victims, and offenders for four offense types of violent crime (homicide, aggravated assault, robbery, and sexual assault) for the 2004–2006 calendar years from the Orlando Police Department (OPD) and Orange County Sheriff’s Office (OCSO). For the three-year period, there were a total of 2,467 sexual assault incidents with 2,850 total suspects and 2,759 total victims. As with all crime statistics, there were several potential sources of incomplete data. These data were likely incomplete because not all occurrences of crime are reported to law enforcement. This was particularly relevant for the present study as the general consensus among researchers is that sexual assault is likely to be the least reported violent crime (O’Brien, 1985). Since the crimes being analyzed were most likely committed by adults against children, it was even less likely they would be reported. In addition, this might have been exacerbated with children who are sexually victimized multiple times, as it was unlikely that all victims or victimizations were reported to law enforcement officers. Furthermore, if the police were unable to identify a prospective offender for a reported crime, there would be no demographic information for the suspect. A final problem limiting the completeness of the crime data was that the responding officer did not always obtain all information that was routinely included in the agency’s data system, or the information was recorded incorrectly. Some data fields were optional, and obtaining the information may not be a high priority for some officers, particularly when time was of the essence (e.g., a victim needs emergency medical treatment). In other cases, the lack of data completeness occurred through human oversight or error. In most cases, missing data in police records were random, and their omission was unlikely to have biased the results from statistical analyses. After combining all data available on sexual assault, we linked the identified sexual assault location address with its census tract. Under Florida statute, the residential addresses of sexual assault victims are legally protected. By placing each incident location into a census tract, we were able to examine the relationships between child sexual abuse incidents and community characteristics at the aggregate level by collecting neighborhood information from the census. Urban census tracts are approximately the size of neighborhoods, and research has consistently found that neighborhood characteristics influence crime levels within cities (Bursik & Grasmick, 1993;
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Liberman, 2007). There were 194 census tracts in Orlando/Orange County Florida in 2006. For the purposes of the present study, we used the information associated with the first suspect and first victim listed when there were multiple suspects or victims. This was done to ensure that multiple suspects or victims did not bias the results, given that those census tracts’ information would be included in the analysis multiple times for the same case.
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DEPENDENT
VARIABLE
The primary variable of interest—whether a child sexual abuse incident had multiple victims or a single victim—was constructed using OPD and OCSO data. To compute whether an incident of sexual abuse had a child victim, we used the data on age of victim provided by OPD and OCSO. We recoded this variable into a dichotomous one indicating whether the victim of the sexual assault was a child (defined as 17 years old and younger) or an adult (persons aged 18 years and older). Next, using the number-of-victims variable and the dichotomous-age-of-victims variable, we delineated the child sexual abuse cases with single victims and those with multiple victims. Here we assign cases with single victims a “0” and cases with multiple victims a “1.” In Orange County and Orlando for the years 2004 through 2006, there were 159 (13.6% of the total) incidents of child sexual abuse with multiple victims and 1,013 (86.4% of the total) child sexual abuse incidents with single victims. This distribution between child sexual abuse with single victims and those with multiple victims was consistent with previous literature (Snyder, 2000). INDEPENDENT
VARIABLES
Independent variables assessed five case characteristics of child sexual abuse incidents and four social disorganization concepts that had been important in understanding rates and distributions of violent crime (including child sexual abuse) in communities. The case characteristics were victim’s age, race, and sex as well as offender’s race and sex. Offenders’ ages were not included in the analysis because of the extensive missing data on this measure. Therefore, the relationship between the victim and offender was not available in this data set. The social disorganization concepts were Violent Crime in the Community, Collective Efficacy and Social Cohesion (including Economic Disadvantage and Immigrant Concentration), and the Rate of Registered Sexual Offenders (RSOs). Other variables included in the model are Male versus Female Status, two measures of Population Density, and the Percentage of Males Never Married. Recall that the social disorganization variables were attached to the incident locations for each child sexual abuse incident via
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the census tract. Each variable and its operationalization is discussed in the following sections. Case characteristics. Five individual variables were used to assess the impact of victim and offender characteristics on whether an incident of sexual assault had single or multiple victims. Specifically, we used the victim’s age, sex, and race as well as the suspect’s sex and race. Both victim and offender ages were recorded as number of years old. Victim and offender sex was a dichotomous variable, with females coded as “0” and males coded as “1.” Regarding race, victims were coded as either non-White = “0” or White = “1.” For purposes of description, 91% of child sexual abuse victims were female (N = 1,942), and only 9% were male. The race of the victim was more likely to be White as slightly over two-thirds of the victims of child sexual abuse were such (67.8%). Finally, the average age of child victims was 12.5 years, indicating that slightly older children were more likely to be victims of reported child sexual abuse than younger children. It was disturbing to note, however, that 10% of the child victims were very young—6 years old or younger. Regarding offenders, 97% were male (N = 2,266). The average age of offenders was 30 years old. Violent crime in the community. Here we used the homicide, robbery, and aggravated assault counts provided by OPD and OCSO. To standardize these measures, we geocoded all incidents of violence with their census tract, divided by the total population of that census tract, and multiplied by 1,000. This gave us a rate of per 1,000 residents for each of the offenses. As expected, these variables were all highly correlated. As such, we summed the three rates and used a total rate of violent crime (excluding sexual assault) in the regression analysis. Rates of violence varied across communities, with a low of .41 and a high of 305.14. This measure of violence in the community had a mean rate of 31.99 per 1,000 residents. RSOs in the community. Based on Tewksbury and colleagues (2010), who found that a community’s concentration of RSOs in residence was related to the overall rate of sexual assaults, we included this variable. To do so, we obtained a 2006 listing of all RSOs in Orange County (including the city of Orlando) from the Florida Department of Corrections Sex Offender Registry, and, for each sex offender with a valid address, we identified his or her census tract of residence. We divided the number of RSOs by the total population of the census tract and multiplied by 1,000 to calculate a standardized rate. This rate had a range of 0 to 26.54 and a mean of 1.83 registered sexual offenders in residence per census tract. Collective efficacy and social cohesion. We also included measures of collective efficacy and social cohesion. These theoretical concepts are aspects of social disorganization theory that may work to temper the negative effects of economic and social disadvantage. We utilized the same factor constructs that Sampson and colleagues (1997) and Morenoff and colleagues (2001) employed. These measures represented the similarity of community
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residents and the level of resources in the community. The theoretical relevance of these factors was that neighborhoods where residents were more similar to one another and those with a greater level of resources would be more encouraging of interactions among neighbors, thereby facilitating greater cohesion, unity, and willingness to work together to minimize local social problems. Three factors composed the measures of collective efficacy and social cohesion: concentrated disadvantage, immigrant concentration, and residential stability. All of these factors served as proxies, assuming that communities with more resources, greater homogeneity, and greater stability were better able to form a cooperative neighborhood environment, which in turn heightened residents’ potential efficacy. We replicated these three factors using a modified form of variables and computations of Sampson and colleagues (1997) and Morenoff and colleagues (2001). Due to multicollinearity, the concept of residential stability could not be included. We did, however, use the individual measures of residential stability in the bivariate analysis. All variables used to calculate these factors were taken from the five-year estimates (2005 to 2009) of the American Community Surveys. Concentrated disadvantage index. Similar to Morenoff and colleagues (2001), we created a factor (using principal components factor analysis) that includes the percentage of families below poverty, percentage of families receiving public assistance, percentage of civilian labor force that was unemployed, and percentage of female-headed households with children. Here, as with Morenoff and his colleagues, our measures all loaded on one factor with values of .86 or higher. Immigrant concentration. As used by Sampson, Morenoff, and GannonRowley (2002), we created a factor with two measures of immigrant concentration: the percentage of Latinos in the population and the percentage of persons who are native citizens. Again, as with Sampson and colleagues (1997) and Morenoff and colleagues (2001), our measures loaded on one factor with values of .83 or higher. This measure reflected several theoretical relationships. First, higher rates of immigrant populations might have been a sign of economic disadvantage. However, a greater concentration of immigrants might also have indicated social homogeneity. It is also possible that higher rates of immigrant concentration pointed toward less residential stability; as immigrants became more settled with jobs, they moved to more economically advantaged areas. Overall, recent studies of the impact of the “new” immigration on criminal offending patterns found immigrant concentration to be unrelated or negatively related to crime levels. In a prior investigation of immigrant concentration at the census tract level in Orange County, Polczynski Olson, Laurikkala, Huff-Corzine, and Corzine (2009) found no relationship to violent crime rates. Male versus female status. The variables encompassing this measure reflected those used by Hunnicutt (2007) whose study of child homicide
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showed that, in urban areas, women’s absolute economic status was positively related to child homicide. Here, given the relationship between female economic status and violence against children in the form of homicide as well as the findings of Tewksbury and colleagues (2010), it was appropriate to include gender status as a potential predictor of child sexual abuse. This measure included the percentage of females (and a separate measure also for males) with a college degree, the percentage of females (and males) who were divorced, the percentage of females (and males) in the labor force, the percentage of employed females (and males) who were in professional and managerial positions, and the median income for females (and males). All measures for females and for males were summed together to create two variables: female economic status and male economic status. For this measure we created a ratio of male versus female economic status by dividing male status by female status. Ratio values less than 1 indicate that females had a higher status than males. Ratio values greater than 1 indicate that males’ status was higher. Ratio values ranged from 0.1 to 76.5, with a mean of 1.6. It should be noted that 99.5% of the sexual abuse incidents occurred in census tracts with values of 5.0 or lower. As an interesting aside, however, females had a higher economic status in nearly one-third of the census tracts. Population density. We used two variables as measures of population density. One variable was the number of residents per square mile for each census tract. We computed this by dividing the total population by the total square miles of each census tract. The second variable was also collected from the census and was a measure of the number of occupants per residential unit. Single men in residence. We utilized the proportion of men in the population who never married as a measure of men who were possibly more crime prone than men who were married. As per Finkelhor and Ormrod (2001) and Snyder (2000), most offenders in child sexual abuse incidents were men.
Data Analysis Strategies To examine the case and community characteristics that may differentially predict whether an incident of child sexual abuse has a single or multiple victim(s), we utilized logistic regression techniques. This was the appropriate statistical technique for this analysis because the dependent variable was dichotomous.
FINDINGS Table 1 highlights the results of the logistic regression analysis. Only two of the measures included in the model were significant indicators of multiple
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TABLE 1 Logistic Regression of Community and Resident Characteristics on Child Sexual Assault with Single or Multiple Victims
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Independent Variables Victim Age Victim Race Victim Sex (Male) Offender Race Offender Sex (Male) Rate of RSOs in Residence Concentrated Economic Disadvantage Immigrant Concentration Violent Crime Rate Persons per Occupied Unit Population Density Male Status versus Female Status % Males Never Married Constant
B −0.07 −0.04 −0.11 −0.35 −0.68 −0.01 −0.22 −0.01 0.01∗∗ 0.36 0.01 −0.01 0.01 −1.59 ∗
SE
Exp(B)
0.02 0.29 0.28 0.29 0.62 0.04 0.17 0.11 0.01 0.34 0.01 0.09 0.01 1.46
0.94 0.96 0.90 0.71 0.51 0.99 0.80 0.99 1.01 1.44 1.00 0.99 1.00
Note. RSOs = registered sexual offenders; χ 2 = 20.63 (p = .081); df = 13; –2 log likelihood = 764.99. ∗ α < .01. ∗∗ α < .05.
victims versus single victim child abuse cases. To elaborate, victim age and the violent crime rate were significant predictors of whether a child sexual abuse incident would have a single victim or multiple victims. Each relationship reflected the expected pattern. Specifically, as the age of the victim decreased by each year, the odds that the sexual abuse incident would have multiple victims increased by 4%. This was similar to the results of Snyder (2000) who found younger child victims of sexual abuse were more likely to be victimized with other children than older children (who were more likely to be victimized alone). In addition, as the overall rate of violent crime increased in a community, the likelihood that any sexual abuse against a child would have multiple victims increased by 1%. This also corresponded with previous research (Coulton, Korbin, & Su, 1999; Drake & Padney, 1996; Garbarino & Sherman, 1980; Paulsen, 2003; Zuravin, 1989) that found a relationship between crime rates (typically used as measures of social disorganization) and rates of child sexual assault. Nonetheless, these findings were somewhat disappointing as they illustrated that social disorganization was not a good explanation for any differences in the sources and patterns of multiple child sexual assault versus single child sexual assault. Even so, these findings provided a great example of how research in support of the null hypothesis is still relevant.
Discussion and Conclusion This study found that social disorganization was not a useful perspective for explaining the differences in the locations of single victim and multiple victim child sexual abuse incidents in Orange County, Florida. Even though
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previous research (Mustaine et al., 2011) found that social disorganization may be valuable in understanding varying community rates of child sexual abuse in general, as we can see here it was not helpful when considering the differences between single and multiple victim sexual abuse incidents at the community level. It is possible that community cohesion might have a different relationship with the reporting of types of child sexual abuse cases than with the reporting of most other violent crimes. As one of the only studies specifically examining community characteristics of locations as well as case characteristics regarding multiple victim child sexual abuse incidents, the present findings offer important theoretical and practical implications for future researchers. Understanding and identifying case, location, and community characteristics of multiple victim child sexual abuse incidents might allow for child advocates, law enforcement, social services, and others to more effectively and efficiently target scarce resources in attempts to prevent such offenses. Unfortunately, the findings of the present study did not facilitate such efforts. It did not appear that the important differences between child sexual abuse incidents with single or multiple victims were at the community level, nor were they necessarily dependent on basic case characteristics. To elaborate, in the current study, only two variables provided significant differentiation between multiple victim cases and single victim cases. Moreover, only one of these variables (violent crime rate) was a social disorganization measure. Coupled with recent research (Mustaine et al., 2011), the current findings suggest that while social disorganization was highly valuable for understanding where child sexual abuse is more prominent, it did not identify factors that differentiate cases that had multiple victims from cases with only one victim. It is quite possible that familial level indicators might provide the more useful explanations for understanding the different contexts of multiple and single victim child sexual abuse. The particular locations and correlates of child sexual abuse may differ for instances of single and multiple victim cases. This may be related to issues of whether perpetrators are family members and other unexamined issues. For example, suppose that child neglect in communities was related to varying amounts of child sexual abuse with multiple victims in communities. It may happen that the measurement of child neglect, at the macrolevel, is a more encompassing and accurately termed measure of lower social class combined with greater ethnic immigration than the latter terms were by themselves. Finally, these findings might plausibly be explained with more simple thinking. It may be possible that multiple child sexual abuse did not actually exacerbate any aspect of the conditions surrounding child sexual abuse, nor was it aggravated by these community conditions. It may not be all that different from the prevalence of single victim child sexual abuse.
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There were several limitations in the current study. First, we relied on sexual assault data collected by law enforcement agencies. Such data suffers from biases because of unreported crime. This is likely compounded in the current study, because research has consistently suggested that this problem is probably the greatest with sexual offense data (Casey & Nurius, 2006; Wolitzky-Taylor et al., 2011). Furthermore, we studied only one community. It is possible that Orange County is a unique community in which the forces producing violent crimes were, to some degree, idiosyncratic. Finally, some of the measures we used to gauge social disorganization are proxies, albeit commonly employed ones in the extant research literature. In the end, this study provided an important advance in our understanding of the roles of community-level variables in identifying where child sexual abuse is most common. Perhaps, unfortunately, this advance was the knowledge that community-level variables may not be significant predictors of multiple victim child sexual abuse incidents. Rather, if multiple versus single victim cases can be distinguished, it may be with variables that have not yet been identified or with more familial-level characteristics rather than broader community features. Future research should continue to explore this issue in order to hopefully identify factors that can distinguish such cases so that the issue of multiple victim child sexual abuse can receive more effective prevention, intervention, and response efforts.
REFERENCES Barnes, J. C., Dukes, T., Tewksbury, R., & De Troye, T. (2009). Predicting the impact of a statewide residence restriction law on South Carolina sex offenders. Criminal Justice Policy Review, 20, 21–43. Berliner, L., & Elliott, D. M. (2002). Sexual abuse of children. In J. E. B. Myers, L. Berliner, J. Briere, C. T. Hendrix, C. Jenny, & T. A. Reid (Eds.), The APSAC handbook on child maltreatment (pp. 55–78). Thousand Oaks, CA: Sage. Bolen, R. (2001). Child sexual abuse: Its scope and our failure. New York: Plenum. Bolen, R. M., & Scannapieco, M. (1999). Prevalence of child sexual abuse: A corrective metanalysis. Social Service Review, 73(3), 281–313. Bursik, R. J., Jr., & Grasmick, H. G. (1993). Neighborhoods and crime: The dimensions of effective community control. New York: Lexington Books. Casey, E. A., & Nurius, P. S. (2006). Trends in the prevalence and characteristics of sexual violence: A cohort analysis. Violence and Victims, 21, 629–644. Coulton, C., Korbin, J., & Su, M. (1999). Community level factors and child maltreatment rates. Child Development, 66, 1262–1276. Douglas, E. M., & Finkelhor, D. (2005). Childhood Sexual Abuse Factsheet. Durham, NH: Crimes Against Children Research Center, University of New Hampshire. Drake, B., & Padney, S. (1996). Understanding the relationship between neighborhood poverty and specific types of child maltreatment. Child Abuse & Neglect, 20, 1003–1018.
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Finkelhor, D. (1984). How widespread is child sexual abuse? In National Center on Child Abuse and Neglect, Perspectives on Child Maltreatment in the Mid-80s (pp. 3–9). Washington, DC: National Center on Child Abuse and Neglect. Finkelhor, D., & Ormrod, R. (2001). Child abuse reported to the police. Washington, DC: Office of Juvenile Justice and Delinquency Prevention. Garbarino, J., & Sherman, D. (1980). Child maltreatment as a community problem. Child Abuse & Neglect, 16, 455–464. Gartner, R. B. (2005). Beyond betrayal. New York: Wiley & Sons. Hannon, L., & Defina, R. (2005). Violent crime in African American and White neighborhoods: Is poverty’s detrimental effect race specific? Journal of Poverty, 9, 49–67. Hunnicutt, G. (2007). Female status and infant and child homicide victimization in rural and urban counties in the US. Gender Issues, 24, 35–50. Lauritsen, J. L. (2003). How families and communities influence youth victimization. Washington, DC: Office of Juvenile Justice and Delinquency. Levenson, J., Zgoba, K., & Tewksbury, R. (2007). Sex offender residence restrictions: Sensible crime policy or flawed logic? Federal Probation, 71, 2–9. Liberman, A. (2007). Adolescents, neighborhoods and violence: Recent Findings from the Project on Human Development in Chicago Neighborhoods. Washington, DC: National Institute of Justice. Morenoff, J. D., Sampson, R. J., & Raudenbush, S. W. (2001). Neighborhood inequality, collective efficacy and the spatial dynamics of urban violence. Criminology, 39, 517–559. Mustaine, E. E., Tewksbury, R., Huff-Corzine, L., & Corzine, J. (2011). Community characteristics and child sexual abuse: A social disorganization analysis. Unpublished manuscript. Mustaine, E. E., Tewksbury, R., & Stengel, K. M. (2006a). Residential location and mobility of registered sex offenders. American Journal of Criminal Justice, 30, 177–192. Mustaine, E. E., Tewksbury, R., & Stengel, K. M. (2006b). Social disorganization and residential locations of registered sex offenders: Is this a collateral consequence? Deviant Behavior, 27, 329–350. O’Brien, P. H. (1985). Stopping rape: Successful survival strategies. New York: Pergamon Press. Paulsen, D. (2003). No safe place: Assessing spatial patterns of child maltreatment victimization. Journal of Aggression, Maltreatment and Trauma, 8, 63–85. Payne, B. K., & Gainey, R. R. (2009). Family violence & criminal justice (3rd ed.). New Providence, NJ: Matthew Bender & Company. Polczynski Olson, C., Laurikkala, M. K., Huff-Corzine, L., & Corzine, J. (2009). Immigration and violent crime: Citizenship status and social disorganization. Homicide Studies, 13, 227–241. Pratt, T., & Cullen, F. (2005). Assessing macro level theories and predictors of crime: A meta-analysis. In M. Tonry (Ed.), Crime and justice: A review of research (pp. 373–450). Chicago: University of Chicago Press. Preble, J. M., & Groth, A. N. (2002). Male victims of same sex abuse. Baltimore: Sidran Press.
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Pridemore, W. A. (2002). What we know about social structure and homicide: A review of the theoretical and empirical literature. Violence and Victims, 17, 127–156. Sampson, R. J., Morenoff, J., & Gannon-Rowley, T. (2002). Assessing “neighborhood” effects: Social processes and new directions in research. Annual Review of Sociology, 28, 443–478. Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 227, 918–924. Shaw, C. R., & McKay, H. D. (1942). Juvenile delinquency and urban areas: A study of rates of delinquents in relation to different characteristics of local communities in American cities. Chicago: University of Chicago Press. Snyder, H. N. (2000). Sexual assault of young children as reported to law enforcement: Victim, incident, and offender characteristics. Washington, DC: U.S. Department of Justice. Spearly, J., & Lauderdale, M. (1982). Community characteristics and ethnicity in the prediction of child maltreatment rates. Child Abuse and Neglect, 7, 91–105. Tewksbury, R., & Levenson, J. (2007). When evidence is ignored: Residential restrictions for sex offenders. Corrections Today, 69, 54–57. Tewksbury, R., & Mustaine, E. E. (2006). Where to find sex offenders: An examination of residential locations and neighborhood conditions. Criminal Justice Studies, 19, 61–75. Tewksbury, R., Mustaine, E. E., & Covington, M. (2010). Offender presence, available victims, social disorganization and sex offense rates. American Journal of Criminal Justice, 35, 1–14. U.S. Department of Health and Human Services. (2009). Child maltreatment, 2007. Washington, DC: U.S. Government Printing Office. Wolitzky-Taylor, K. B., Resnick, H. S., McCauley, J. L., Amstadter, A. B., Kilpatrick, D. G., & Ruggiero, K. J. (2011). Is reporting of rape on the rise? A comparison of women with reported versus unreported rape experiences in the National Women’s Study–Replication. Journal of Interpersonal Violence, 26, 807–832. Zuravin, S. J. (1989). The ecology of child abuse and neglect: Review of the literature and presentation of data. Violence and Victims, 4, 101–120.
AUTHOR NOTES Elizabeth Ehrhardt Mustaine, PhD, is a professor in the Department of Sociology at the University of Central Florida in Orlando, Florida. Her current research interests include sexual offenses and offenders and pedagogical issues in sociology and criminal justice. Richard Tewksbury, PhD, is a professor in the Department of Justice Administration at the University of Louisville in Louisville, Ky. His research centers on issues of sex offender registration and experiences and institutional corrections.
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Jay Corzine, PhD, is a professor in the Department of Sociology at the University of Central Florida in Orlando, Florida. His research interests include homicide and correlates of violence.
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Lin Huff-Corzine, PhD, is a professor in the Department of Sociology at the University of Central Florida in Orlando, Florida. Her research focuses on issues of violence and social influences on crime and deviance.
Journal of Child Sexual Abuse Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/wcsa20
Differentiating Single and Multiple Victim Child Sexual Abuse Cases: A Research Note Considering Social Disorganization Theory a
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Elizabeth Ehrhardt Mustaine , Richard Tewksbury , Jay Corzine & Lin Huff-Corzine a
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University of Central Florida , Orlando , Florida , USA
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University of Louisville , Louisville , Kentucky , USA Published online: 06 Jan 2014.
To cite this article: Elizabeth Ehrhardt Mustaine , Richard Tewksbury , Jay Corzine & Lin HuffCorzine (2014) Differentiating Single and Multiple Victim Child Sexual Abuse Cases: A Research Note Considering Social Disorganization Theory, Journal of Child Sexual Abuse, 23:1, 38-54, DOI: 10.1080/10538712.2014.863260 To link to this article: http://dx.doi.org/10.1080/10538712.2014.863260
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Journal of Child Sexual Abuse, 23:38–54, 2014 Copyright © Taylor & Francis Group, LLC ISSN: 1053-8712 print/1547-0679 online DOI: 10.1080/10538712.2014.863260
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RESEARCH ON CHILD SEXUAL ABUSE AND ADULT SURVIVORS
Differentiating Single and Multiple Victim Child Sexual Abuse Cases: A Research Note Considering Social Disorganization Theory ELIZABETH EHRHARDT MUSTAINE University of Central Florida, Orlando, Florida, USA
RICHARD TEWKSBURY University of Louisville, Louisville, Kentucky, USA
JAY CORZINE and LIN HUFF-CORZINE University of Central Florida, Orlando, Florida, USA
This study examined the utility of social disorganization theory as an explanation for child sexual abuse with a focus on differentiating single and multiple victim cases. Drawing on 1,172 child sexual abuse cases (including 159 cases with multiple victims) in Orange County, Florida, from 2004 to 2006, the present study considered case characteristics and elements of social disorganization as potential predictors of child sexual abuse cases involving single and multiple victims. We found that social disorganization theory does not successfully predict the locations of multiple victim child sexual abuse incidents and is not useful for distinguishing between child sexual abuse incidents with single or multiple victims. KEYWORDS child disorganization
sexual
abuse,
community,
social
Received 30 May 2012; revised 12 June 2012; accepted 27 August 2012. Address correspondence to Richard Tewksbury, Department of Justice Administration, University of Louisville, Brigman Hall, Louisville, KY 40292. E-mail: [email protected] 38
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Sexual offenses, especially those perpetrated against children, are among the most serious and most despised crimes in American society. Criminal justice policy and practice has focused a bright light on sexual offenses, especially those against children, in recent decades. Recent years have witnessed both substantial public attention to the issue (media coverage of sexual abuse in the Catholic Church and the Penn State football cases) as well as a continuation of ambivalence and reluctance to directly confront the issue in many arenas. In part due to the divergent and sometimes seemingly contradictory ways that contemporary society has responded to the sexual abuse of children, research addressing the issue has been plagued by methodological difficulties, widely divergent estimates of prevalence and incidence, and challenges to the identification of “true” statistics (Douglas & Finkelhor, 2005). Significant advances have been in made in recent decades in our understanding of the dynamics of child sexual abuse through examinations of the correlates of victimization, perpetration, and service/treatment needs for victims and offenders. However, two issues have remained largely absent in the scholarly literature concerning child sexual abuse: (a) the influence of community characteristics on incidents and rates of child sexual abuse and (b) the explication of characteristics of child sexual abuse cases involving multiple victims (including if and how such cases may differ from cases involving only one victim). The goal of the present study was to begin addressing these two gaps in the literature. A concern with whether community-level issues are related to the incidence of child sexual abuse is important because if neighborhood structural issues are found to correlate with varying rates of such offenses then both criminal justice and child welfare officials may be able to more effectively and efficiently target scarce resources to prevention, intervention, and responses to victims. Understanding and addressing macrolevel issues requires information about both community characteristics and individual cases of child sexual abuse.
CHILD SEXUAL ABUSE AND SOCIAL DISORGANIZATION Rates of Child Sexual Abuse Researchers have estimated that children make up 66% of all known victims of sexual assault (Snyder, 2000), and sexual abuse has accounted for approximately 7% to 10% of all reports of child maltreatment in the United States (U.S. Department of Health and Human Services, 2009). Estimates of the prevalence of child sexual abuse range from 9% to 32% for adult women (Douglas & Finkelhor, 2005). A meta-analysis of 22 American studies suggests that 30% to 40% of girls and 13% of boys experienced sexual abuse during childhood (Bolen & Scannapieco, 1999).
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An often overlooked aspect of child sexual abuse (outside of occasional high profile media attention) concerns cases that involve multiple victims. According to data from the National Incident Based Reporting System (NIBRS), for 1991 to 1996, 19% of victims of child sexual abuse were assaulted along with another child (Snyder, 2000). One in 8 instances (13%) of child sexual abuse involved at least 2 victims, and 6% included 3 or more victims (Snyder, 2000). Unfortunately, relatively little is known about multiple victim cases. However, when multiple victims are present, younger children are more likely to be involved than older juveniles (Snyder, 2000). For young children who were sexually abused, 1 in 4 victims under the age of 12 was victimized by a perpetrator with more than 1 victim (Snyder, 2000). However, only 13% of sexual abuse victims over the age of 12 were sexually abused with another victim. Multiple victim child sexual abuse cases were also more likely to involve girls than boys (Snyder, 2000). However, beyond initial estimates of number and age and the sex distributions of victims, little is known about children who are sexually victimized with others, and essentially no research has examined the characteristics of communities in which multiple victim child sexual abuse is more likely to occur.
Characteristics of Sexually Abused Children and Perpetrators Sexually abused children come from all socioeconomic, cultural, and demographic categories. Even so, there are important patterns and trends that can be seen in the population of sexually abused children. First, girls are more likely than boys to be victimized (Snyder, 2000). Furthermore, although children of all ages can be, and are, sexually abused, girls are more likely to be sexually abused in early adolescence (ages 11 to 14) while boys are most often victimized during their preschool or early elementary school years (ages 4 to 6; Berliner & Elliott, 2002). Gender also appears to interact with socioeconomic status, as sexually abused boys are more likely to come from lower socioeconomic households, while sexually abused girls come from all socioeconomic backgrounds (Berliner & Elliott, 2002). Research about sexual abuse perpetrators has suggested that they are almost always men (Bolen, 2001; Preble & Groth, 2002; Snyder, 2000). Women who sexually abuse children do so less frequently and most often offend against very young (age 6 and under) victims (Snyder, 2000). Somewhat contradictory to popular belief, the majority of reported child sexual abuse cases do not involve immediate family members (Douglas & Finkelhor, 2005; Finkelhor & Ormrod, 2001, Snyder, 2000). While there is a preexisting relationship between most child sexual abuse victims and perpetrators, it is often one of acquaintanceship, family friend, or extended family. Only relatively rarely are child sexual abuse victims and offenders strangers (Finkelhor & Ormrod, 2001). When familial sexual abuse of children does occur, it is most likely to be perpetrated against girls (Berliner & Elliott,
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2002; Finkelhor, 1984). In addition, familial sexual abuse may be most likely to occur in low-income households (Berliner & Elliott, 2002; Gartner, 2005; Preble & Groth, 2002).
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COMMUNITY CHARACTERISTICS AND SOCIAL DISORGANIZATION THEORY In addition to examining the characteristics of individual victims and perpetrators of child sexual abuse, it is important to assess characteristics of communities in which child sexual abuse is more or less prevalent. This has not been a focus of significant research, however, leading Payne and Gainey (2009) to conclude that “few studies have addressed how community level factors contribute to child abuse” (p. 123). The study of community characteristics and their possible relationships with locations and rates of crime and violence typically draws on social disorganization theory. Social disorganization theory focuses on issues of economic and social disadvantage, community cohesion, and population (in)stability as factors that correlate with crime, disorder, and the lack of effective informal social control mechanisms. At its core, social disorganization theory includes aspects of not only whether residents lack social and economic capital but also the presence and strength of inhabitants’ relationships with other residents. The theory assumes that when economic and social capital is low and interactions and bonds between residents (e.g., collective efficacy and community cohesion) are weak or lacking, numerous forms of disorder, including criminal victimization, will increase (Bursik & Grasmick, 1993; Shaw & McKay, 1942). Since its initial appearance in the early 20th century, scholars have repeatedly demonstrated the value of social disorganization concepts for explaining numerous forms of crime, especially violent crime (Hannon & Defina, 2005; Morenoff, Sampson, & Raudenbush, 2001; Pratt & Cullen, 2005; Pridemore, 2002; Sampson, Raudenbush, & Earls, 1997). Research on social disorganization theory has also identified critical concepts and variables that are necessary for accurately and adequately assessing the role of social disorganization and its relationship to criminal activity. Central to any social disorganization analysis are concepts (and accompanying measures) of economic disadvantage, community cohesion, stability of the community’s residential population, and the presence of individuals prone to both criminal behavior and victimization.
Community Characteristics and Child Abuse Interestingly, while research has identified aspects of social disorganization as important for explaining the occurrence and distribution of child
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maltreatment (defined as physical, sexual, and emotional child abuse and neglect; Coulton, Korbin, & Su, 1999; Drake & Padney, 1996; Garbarino & Sherman, 1980; Paulsen, 2003; Zuravin, 1989), few scholars have assessed whether social disorganization may be related to child sexual abuse specifically. Given that child sexual abuse is only one component of child maltreatment and that the perpetrators of child sexual abuse are less likely to be family members than perpetrators of other forms of maltreatment, it may be that locations and correlates of child sexual abuse differ from the correlates of child maltreatment in general. The limited available research suggests that children who are left alone, who are unsupervised, or who do not have the physical presence of numerous friends and neighbors are more likely to be sexually abused (Berliner & Elliott, 2002; Bolen, 2001). Regarding residential stability, Lauritsen (2003) showed that youth who have lived at their current address for shorter periods of time are more likely to suffer a variety of violent victimizations. However, others (Paulsen, 2003; Spearly & Lauderdale, 1982) have found that residential stability is not related to child abuse or neglect. With the limited evidence being mixed, it is important to continue to investigate if and how measures of community cohesion, stability, and interactions may be related to rates of child sexual abuse. To date, only three studies have specifically addressed the potential role of community characteristics and social disorganization as contributing factors to child abuse in general or to child sexual abuse specifically. Paulsen’s (2003) spatial analysis of 156 cases of child abuse and 134 cases of child neglect shows that child abuse is more geographically dispersed than child neglect and that spatial areas with high rates of child abuse are the most dispersed. Regarding community characteristics, Paulsen reports that census tracts with higher rates of poverty and those with larger total and Black populations are more likely to have a higher number of reported cases of child abuse. Furthermore, 25% of the variation in child abuse rates is explained by measures of neighborhood disadvantage and the percent of the population that is Black. One important conclusion offered by Paulsen (2003) is that residential stability is not a significant predictor of child abuse or neglect; rather, issues of economic disadvantage are clearly more important for explaining where child abuse occurs. Two additional studies (Mustaine, Tewksbury, Huff-Corzine, & Corzine, 2011; Tewksbury, Mustaine, & Covington, 2010) have also examined the role of social disorganization in explaining rates of child abuse. Tewksbury and colleagues (2010) argued that social disorganization offers a moderate level of explanation (27%) for understanding sexual offenses against children. They did so by focusing on distinguishing census tracts as being more or less socially disorganized than the county average and concluded that a high level of social disorganization in a census tract is significantly related to increased child sexual abuse rates. They also found that the census tract’s
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percentage of the population that was women age 16 to 64 years with a disability was significant in predicting child sexual abuse. However, they were not able to consider measures of collective efficacy and social cohesion, and they did not distinguish between measures of economic disadvantage and other types of social disorganization. Mustaine and colleagues (2011) examined all cases of documented sexual assault in Orange County, Florida, over a three-year period and found that, for the 1,172 cases of child sexual abuse, social disorganization theory provided a strong explanation for varying rates of offenses across census tracts. Specifically, they concluded that social disorganization theory provides a strong explanation for varying rates of child sexual abuse, with economic disadvantage, residential instability, greater population density, more violent crime, more registered sex offenders in residence, lower levels of female economic status relative to men, and a greater concentration of never married men in the census tract as significant predictors of increased rates of child sexual abuse. Somewhat contrary to social disorganization theory, however, they also found that as the concentration of immigrants in the population increases, the rate of reported child sexual abuse actually decreases.
Other Potential Relationships with Child Sexual Abuse Based on other research findings, two additional community characteristics may also be important in explaining rates of child sexual abuse, including rates of incidents with multiple victims. First, the presence of known sexual offenders in a community may be related to increased rates of child sexual abuse (as the belief behind many recent legal developments, including sex offender registries and community notification, is that the presence of known sex offenders is a risk factor for victimization). In addition, when considering social disorganization theory approaches for explaining sex offense rates of any type, it is important to recognize that registered sex offenders are known to be severely limited in their housing options (Barnes, Dukes, Tewksbury, & DeTroye, 2009; Levenson, Zgoba, & Tewksbury, 2007; Tewksbury & Levenson, 2007) and to more frequently reside in socially disorganized areas (Mustaine, Tewksbury, & Stengel, 2006a, 2006b; Tewksbury & Mustaine, 2006). Second, as both Tewksbury and colleagues (2010) and Mustaine and colleagues (2011) show, female status indicators (concentration of women with disabilities and the economic status of women relative to men, respectively) are important for predicting child sexual abuse rates. As such, some measure of gendered circumstances is important to consider. Considering these issues and the weaknesses of the current literature, the present study seeks to explain whether social disorganization theory is a useful perspective for understanding and differentiating locations of incidents of child sexual abuse with single and multiple victims. Overall, our goal is
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to examine whether community-level and case-level variables are useful in understanding the distribution of child sexual abuse cases with single versus multiple victims across metropolitan areas.
METHODS
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Data We obtained data sets for incidents, victims, and offenders for four offense types of violent crime (homicide, aggravated assault, robbery, and sexual assault) for the 2004–2006 calendar years from the Orlando Police Department (OPD) and Orange County Sheriff’s Office (OCSO). For the three-year period, there were a total of 2,467 sexual assault incidents with 2,850 total suspects and 2,759 total victims. As with all crime statistics, there were several potential sources of incomplete data. These data were likely incomplete because not all occurrences of crime are reported to law enforcement. This was particularly relevant for the present study as the general consensus among researchers is that sexual assault is likely to be the least reported violent crime (O’Brien, 1985). Since the crimes being analyzed were most likely committed by adults against children, it was even less likely they would be reported. In addition, this might have been exacerbated with children who are sexually victimized multiple times, as it was unlikely that all victims or victimizations were reported to law enforcement officers. Furthermore, if the police were unable to identify a prospective offender for a reported crime, there would be no demographic information for the suspect. A final problem limiting the completeness of the crime data was that the responding officer did not always obtain all information that was routinely included in the agency’s data system, or the information was recorded incorrectly. Some data fields were optional, and obtaining the information may not be a high priority for some officers, particularly when time was of the essence (e.g., a victim needs emergency medical treatment). In other cases, the lack of data completeness occurred through human oversight or error. In most cases, missing data in police records were random, and their omission was unlikely to have biased the results from statistical analyses. After combining all data available on sexual assault, we linked the identified sexual assault location address with its census tract. Under Florida statute, the residential addresses of sexual assault victims are legally protected. By placing each incident location into a census tract, we were able to examine the relationships between child sexual abuse incidents and community characteristics at the aggregate level by collecting neighborhood information from the census. Urban census tracts are approximately the size of neighborhoods, and research has consistently found that neighborhood characteristics influence crime levels within cities (Bursik & Grasmick, 1993;
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Liberman, 2007). There were 194 census tracts in Orlando/Orange County Florida in 2006. For the purposes of the present study, we used the information associated with the first suspect and first victim listed when there were multiple suspects or victims. This was done to ensure that multiple suspects or victims did not bias the results, given that those census tracts’ information would be included in the analysis multiple times for the same case.
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DEPENDENT
VARIABLE
The primary variable of interest—whether a child sexual abuse incident had multiple victims or a single victim—was constructed using OPD and OCSO data. To compute whether an incident of sexual abuse had a child victim, we used the data on age of victim provided by OPD and OCSO. We recoded this variable into a dichotomous one indicating whether the victim of the sexual assault was a child (defined as 17 years old and younger) or an adult (persons aged 18 years and older). Next, using the number-of-victims variable and the dichotomous-age-of-victims variable, we delineated the child sexual abuse cases with single victims and those with multiple victims. Here we assign cases with single victims a “0” and cases with multiple victims a “1.” In Orange County and Orlando for the years 2004 through 2006, there were 159 (13.6% of the total) incidents of child sexual abuse with multiple victims and 1,013 (86.4% of the total) child sexual abuse incidents with single victims. This distribution between child sexual abuse with single victims and those with multiple victims was consistent with previous literature (Snyder, 2000). INDEPENDENT
VARIABLES
Independent variables assessed five case characteristics of child sexual abuse incidents and four social disorganization concepts that had been important in understanding rates and distributions of violent crime (including child sexual abuse) in communities. The case characteristics were victim’s age, race, and sex as well as offender’s race and sex. Offenders’ ages were not included in the analysis because of the extensive missing data on this measure. Therefore, the relationship between the victim and offender was not available in this data set. The social disorganization concepts were Violent Crime in the Community, Collective Efficacy and Social Cohesion (including Economic Disadvantage and Immigrant Concentration), and the Rate of Registered Sexual Offenders (RSOs). Other variables included in the model are Male versus Female Status, two measures of Population Density, and the Percentage of Males Never Married. Recall that the social disorganization variables were attached to the incident locations for each child sexual abuse incident via
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the census tract. Each variable and its operationalization is discussed in the following sections. Case characteristics. Five individual variables were used to assess the impact of victim and offender characteristics on whether an incident of sexual assault had single or multiple victims. Specifically, we used the victim’s age, sex, and race as well as the suspect’s sex and race. Both victim and offender ages were recorded as number of years old. Victim and offender sex was a dichotomous variable, with females coded as “0” and males coded as “1.” Regarding race, victims were coded as either non-White = “0” or White = “1.” For purposes of description, 91% of child sexual abuse victims were female (N = 1,942), and only 9% were male. The race of the victim was more likely to be White as slightly over two-thirds of the victims of child sexual abuse were such (67.8%). Finally, the average age of child victims was 12.5 years, indicating that slightly older children were more likely to be victims of reported child sexual abuse than younger children. It was disturbing to note, however, that 10% of the child victims were very young—6 years old or younger. Regarding offenders, 97% were male (N = 2,266). The average age of offenders was 30 years old. Violent crime in the community. Here we used the homicide, robbery, and aggravated assault counts provided by OPD and OCSO. To standardize these measures, we geocoded all incidents of violence with their census tract, divided by the total population of that census tract, and multiplied by 1,000. This gave us a rate of per 1,000 residents for each of the offenses. As expected, these variables were all highly correlated. As such, we summed the three rates and used a total rate of violent crime (excluding sexual assault) in the regression analysis. Rates of violence varied across communities, with a low of .41 and a high of 305.14. This measure of violence in the community had a mean rate of 31.99 per 1,000 residents. RSOs in the community. Based on Tewksbury and colleagues (2010), who found that a community’s concentration of RSOs in residence was related to the overall rate of sexual assaults, we included this variable. To do so, we obtained a 2006 listing of all RSOs in Orange County (including the city of Orlando) from the Florida Department of Corrections Sex Offender Registry, and, for each sex offender with a valid address, we identified his or her census tract of residence. We divided the number of RSOs by the total population of the census tract and multiplied by 1,000 to calculate a standardized rate. This rate had a range of 0 to 26.54 and a mean of 1.83 registered sexual offenders in residence per census tract. Collective efficacy and social cohesion. We also included measures of collective efficacy and social cohesion. These theoretical concepts are aspects of social disorganization theory that may work to temper the negative effects of economic and social disadvantage. We utilized the same factor constructs that Sampson and colleagues (1997) and Morenoff and colleagues (2001) employed. These measures represented the similarity of community
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residents and the level of resources in the community. The theoretical relevance of these factors was that neighborhoods where residents were more similar to one another and those with a greater level of resources would be more encouraging of interactions among neighbors, thereby facilitating greater cohesion, unity, and willingness to work together to minimize local social problems. Three factors composed the measures of collective efficacy and social cohesion: concentrated disadvantage, immigrant concentration, and residential stability. All of these factors served as proxies, assuming that communities with more resources, greater homogeneity, and greater stability were better able to form a cooperative neighborhood environment, which in turn heightened residents’ potential efficacy. We replicated these three factors using a modified form of variables and computations of Sampson and colleagues (1997) and Morenoff and colleagues (2001). Due to multicollinearity, the concept of residential stability could not be included. We did, however, use the individual measures of residential stability in the bivariate analysis. All variables used to calculate these factors were taken from the five-year estimates (2005 to 2009) of the American Community Surveys. Concentrated disadvantage index. Similar to Morenoff and colleagues (2001), we created a factor (using principal components factor analysis) that includes the percentage of families below poverty, percentage of families receiving public assistance, percentage of civilian labor force that was unemployed, and percentage of female-headed households with children. Here, as with Morenoff and his colleagues, our measures all loaded on one factor with values of .86 or higher. Immigrant concentration. As used by Sampson, Morenoff, and GannonRowley (2002), we created a factor with two measures of immigrant concentration: the percentage of Latinos in the population and the percentage of persons who are native citizens. Again, as with Sampson and colleagues (1997) and Morenoff and colleagues (2001), our measures loaded on one factor with values of .83 or higher. This measure reflected several theoretical relationships. First, higher rates of immigrant populations might have been a sign of economic disadvantage. However, a greater concentration of immigrants might also have indicated social homogeneity. It is also possible that higher rates of immigrant concentration pointed toward less residential stability; as immigrants became more settled with jobs, they moved to more economically advantaged areas. Overall, recent studies of the impact of the “new” immigration on criminal offending patterns found immigrant concentration to be unrelated or negatively related to crime levels. In a prior investigation of immigrant concentration at the census tract level in Orange County, Polczynski Olson, Laurikkala, Huff-Corzine, and Corzine (2009) found no relationship to violent crime rates. Male versus female status. The variables encompassing this measure reflected those used by Hunnicutt (2007) whose study of child homicide
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showed that, in urban areas, women’s absolute economic status was positively related to child homicide. Here, given the relationship between female economic status and violence against children in the form of homicide as well as the findings of Tewksbury and colleagues (2010), it was appropriate to include gender status as a potential predictor of child sexual abuse. This measure included the percentage of females (and a separate measure also for males) with a college degree, the percentage of females (and males) who were divorced, the percentage of females (and males) in the labor force, the percentage of employed females (and males) who were in professional and managerial positions, and the median income for females (and males). All measures for females and for males were summed together to create two variables: female economic status and male economic status. For this measure we created a ratio of male versus female economic status by dividing male status by female status. Ratio values less than 1 indicate that females had a higher status than males. Ratio values greater than 1 indicate that males’ status was higher. Ratio values ranged from 0.1 to 76.5, with a mean of 1.6. It should be noted that 99.5% of the sexual abuse incidents occurred in census tracts with values of 5.0 or lower. As an interesting aside, however, females had a higher economic status in nearly one-third of the census tracts. Population density. We used two variables as measures of population density. One variable was the number of residents per square mile for each census tract. We computed this by dividing the total population by the total square miles of each census tract. The second variable was also collected from the census and was a measure of the number of occupants per residential unit. Single men in residence. We utilized the proportion of men in the population who never married as a measure of men who were possibly more crime prone than men who were married. As per Finkelhor and Ormrod (2001) and Snyder (2000), most offenders in child sexual abuse incidents were men.
Data Analysis Strategies To examine the case and community characteristics that may differentially predict whether an incident of child sexual abuse has a single or multiple victim(s), we utilized logistic regression techniques. This was the appropriate statistical technique for this analysis because the dependent variable was dichotomous.
FINDINGS Table 1 highlights the results of the logistic regression analysis. Only two of the measures included in the model were significant indicators of multiple
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TABLE 1 Logistic Regression of Community and Resident Characteristics on Child Sexual Assault with Single or Multiple Victims
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Independent Variables Victim Age Victim Race Victim Sex (Male) Offender Race Offender Sex (Male) Rate of RSOs in Residence Concentrated Economic Disadvantage Immigrant Concentration Violent Crime Rate Persons per Occupied Unit Population Density Male Status versus Female Status % Males Never Married Constant
B −0.07 −0.04 −0.11 −0.35 −0.68 −0.01 −0.22 −0.01 0.01∗∗ 0.36 0.01 −0.01 0.01 −1.59 ∗
SE
Exp(B)
0.02 0.29 0.28 0.29 0.62 0.04 0.17 0.11 0.01 0.34 0.01 0.09 0.01 1.46
0.94 0.96 0.90 0.71 0.51 0.99 0.80 0.99 1.01 1.44 1.00 0.99 1.00
Note. RSOs = registered sexual offenders; χ 2 = 20.63 (p = .081); df = 13; –2 log likelihood = 764.99. ∗ α < .01. ∗∗ α < .05.
victims versus single victim child abuse cases. To elaborate, victim age and the violent crime rate were significant predictors of whether a child sexual abuse incident would have a single victim or multiple victims. Each relationship reflected the expected pattern. Specifically, as the age of the victim decreased by each year, the odds that the sexual abuse incident would have multiple victims increased by 4%. This was similar to the results of Snyder (2000) who found younger child victims of sexual abuse were more likely to be victimized with other children than older children (who were more likely to be victimized alone). In addition, as the overall rate of violent crime increased in a community, the likelihood that any sexual abuse against a child would have multiple victims increased by 1%. This also corresponded with previous research (Coulton, Korbin, & Su, 1999; Drake & Padney, 1996; Garbarino & Sherman, 1980; Paulsen, 2003; Zuravin, 1989) that found a relationship between crime rates (typically used as measures of social disorganization) and rates of child sexual assault. Nonetheless, these findings were somewhat disappointing as they illustrated that social disorganization was not a good explanation for any differences in the sources and patterns of multiple child sexual assault versus single child sexual assault. Even so, these findings provided a great example of how research in support of the null hypothesis is still relevant.
Discussion and Conclusion This study found that social disorganization was not a useful perspective for explaining the differences in the locations of single victim and multiple victim child sexual abuse incidents in Orange County, Florida. Even though
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previous research (Mustaine et al., 2011) found that social disorganization may be valuable in understanding varying community rates of child sexual abuse in general, as we can see here it was not helpful when considering the differences between single and multiple victim sexual abuse incidents at the community level. It is possible that community cohesion might have a different relationship with the reporting of types of child sexual abuse cases than with the reporting of most other violent crimes. As one of the only studies specifically examining community characteristics of locations as well as case characteristics regarding multiple victim child sexual abuse incidents, the present findings offer important theoretical and practical implications for future researchers. Understanding and identifying case, location, and community characteristics of multiple victim child sexual abuse incidents might allow for child advocates, law enforcement, social services, and others to more effectively and efficiently target scarce resources in attempts to prevent such offenses. Unfortunately, the findings of the present study did not facilitate such efforts. It did not appear that the important differences between child sexual abuse incidents with single or multiple victims were at the community level, nor were they necessarily dependent on basic case characteristics. To elaborate, in the current study, only two variables provided significant differentiation between multiple victim cases and single victim cases. Moreover, only one of these variables (violent crime rate) was a social disorganization measure. Coupled with recent research (Mustaine et al., 2011), the current findings suggest that while social disorganization was highly valuable for understanding where child sexual abuse is more prominent, it did not identify factors that differentiate cases that had multiple victims from cases with only one victim. It is quite possible that familial level indicators might provide the more useful explanations for understanding the different contexts of multiple and single victim child sexual abuse. The particular locations and correlates of child sexual abuse may differ for instances of single and multiple victim cases. This may be related to issues of whether perpetrators are family members and other unexamined issues. For example, suppose that child neglect in communities was related to varying amounts of child sexual abuse with multiple victims in communities. It may happen that the measurement of child neglect, at the macrolevel, is a more encompassing and accurately termed measure of lower social class combined with greater ethnic immigration than the latter terms were by themselves. Finally, these findings might plausibly be explained with more simple thinking. It may be possible that multiple child sexual abuse did not actually exacerbate any aspect of the conditions surrounding child sexual abuse, nor was it aggravated by these community conditions. It may not be all that different from the prevalence of single victim child sexual abuse.
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There were several limitations in the current study. First, we relied on sexual assault data collected by law enforcement agencies. Such data suffers from biases because of unreported crime. This is likely compounded in the current study, because research has consistently suggested that this problem is probably the greatest with sexual offense data (Casey & Nurius, 2006; Wolitzky-Taylor et al., 2011). Furthermore, we studied only one community. It is possible that Orange County is a unique community in which the forces producing violent crimes were, to some degree, idiosyncratic. Finally, some of the measures we used to gauge social disorganization are proxies, albeit commonly employed ones in the extant research literature. In the end, this study provided an important advance in our understanding of the roles of community-level variables in identifying where child sexual abuse is most common. Perhaps, unfortunately, this advance was the knowledge that community-level variables may not be significant predictors of multiple victim child sexual abuse incidents. Rather, if multiple versus single victim cases can be distinguished, it may be with variables that have not yet been identified or with more familial-level characteristics rather than broader community features. Future research should continue to explore this issue in order to hopefully identify factors that can distinguish such cases so that the issue of multiple victim child sexual abuse can receive more effective prevention, intervention, and response efforts.
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AUTHOR NOTES Elizabeth Ehrhardt Mustaine, PhD, is a professor in the Department of Sociology at the University of Central Florida in Orlando, Florida. Her current research interests include sexual offenses and offenders and pedagogical issues in sociology and criminal justice. Richard Tewksbury, PhD, is a professor in the Department of Justice Administration at the University of Louisville in Louisville, Ky. His research centers on issues of sex offender registration and experiences and institutional corrections.
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Jay Corzine, PhD, is a professor in the Department of Sociology at the University of Central Florida in Orlando, Florida. His research interests include homicide and correlates of violence.
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Lin Huff-Corzine, PhD, is a professor in the Department of Sociology at the University of Central Florida in Orlando, Florida. Her research focuses on issues of violence and social influences on crime and deviance.
