Abstract
This chapter includes the first systematic attempt to examine the association between bullying perpetration and sexual violence perpetration among a middle school sample and the most comprehensive longitudinal study to examine whether risk (e.g., anger, family violence exposure) and protective factors (e.g., caring, school support) predict these two behaviors among female middle school students (N = 576). Using longitudinal data, two separate regression analyses were performed to predict future bullying and sexual violence perpetration by middle school girls. The strongest predictors of bullying perpetration over a 2-year period were sibling aggression, depression, and delinquency, after controlling for baseline levels of bully perpetration. Additionally, greater perceived family social support was associated with less bullying perpetration over time. For sexual harassment perpetration, significant predictors included attitudes that were dismissive of sexual harassment and earlier sexual harassment perpetration. The lack of overlap between predictors for these two behaviors suggests that sexual harassment perpetration among girls in middle school could not be explained by predictors that are well documented in the bullying literature. Much more scholarship needs to focus on identifying what predicts sexual harassment perpetration among girls. Finally, the assumption that addressing risk and protective factors associated with bullying perpetration might reduce sexual violence perpetration over time was not supported. Additional results and implications are presented.
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Introduction
Rape prevention educators from sexual assault coalitions often gain entry to schools by implementing bullying prevention programs because bully prevention is more palatable to administrators than rape prevention. However, these bully prevention programs rarely involve discussions of sexual violence because there is an inherent assumption that addressing risk and protective factors associated with bullying perpetration might reduce sexual violence perpetration over time (Basile, Espelage, Rivers, McMahon, & Simon, 2009; Espelage, Basile, & Hamburger, 2012). This assumption is further predicated on a theoretical argument that bullying perpetration and sexual violence perpetration can be explained by similar risk and protective factors. This practice ignores the possibility that unique predictors of sexual violence might be related to gender. For example, young girls who dismiss sexual harassment as normative might also be more likely to perpetrate sexual harassment. This study represents the first systematic investigation to examine the association between bullying perpetration and sexual violence perpetration among a middle school sample of females to explore whether these two phenomena originate from the same precursors. More specifically, multiple risk (e.g., anger, family violence exposure) and protective factors (e.g., caring, school support) are examined as predictors of bullying and sexual violence perpetration using longitudinal data in order to isolate the most pertinent unique predictors.
Prevalence of Bullying and Sexual Violence Among Females
Involvement in bullying among youth is a concern in the USA and across the globe and has been the focus of scholarship for many years (Espelage, Bosworth, & Simon, 2000). A cross-national survey from representative samples of 11- to 15-year-old school children across 27 countries from 1994 to 2006 indicated that 1/3 of children reported occasional bullying or victimization and 1 in 10 children reported chronic involvement in bullying (Molcho et al., 2009). Bullying is recognizably a major problem for American schools today, and estimates suggest that nearly 30% of American students are involved in bullying in some capacity (Nansel et al., 2001). Findings from this nationally representative sample of sixth to tenth graders indicate that 13% had bullied others, 11% had been bullied, and 6% had both bullied and been bullied. “A student is being bullied or victimized when he or she is exposed, repeatedly and over time, to negative actions on the part of one or more students” (Olweus, 2001, pp. 9–11). The preceding definition highlights the aggressive component of bullying and the associated inherent power imbalance and potentially repetitive nature.
Sexual harassment is a form of sex discrimination under federal law Title IX (1972), and is defined as unwelcome sexual advances, requests for sexual favors, and other verbal or physical contact of a sexual nature when the conduct is sufficiently severe, persistent, or pervasive to limit a student’s ability to participate in or benefit from the education program, or to create a hostile or abusive educational environment. Further, the Centers for Disease Control and Prevention (Basile & Saltzman, 2002) recently defined sexual harassment as a component of sexual violence. Sexual harassment during early adolescence tends to involve sexual commentary, spreading of sexual rumors, and inappropriate touching (Espelage et al., 2012). Both sexual harassment and sexual violence terms will be used throughout this chapter. Studies consistently find that sexual harassment is pervasive in secondary schools (e.g., AAUW, 1993; Stein, 2003). Most of the research in the area of sexual violence among young adolescents has focused on victimization so the data are somewhat limited. However, these data suggest that sexual harassment perpetration is common among school-aged adolescents, with one national study reporting peer harassment rates of 66% and 52%, for boys and girls, respectively, and 76% of the boys and 86% of the girls reported at least some harassment victimization (AAUW, 1993). In addition, a more recent study of 1,300 middle school students found that 32% of boys and 22% of girls reported often making unwanted sexual comments to other students (Espelage et al., 2012), suggesting that girls do perpetrate sexual violence during early adolescence, although forced sexual contact perpetration was low for females in that study.
Predictors of Bully and Sexual Violence Perpetration
Both bullying and sexual violence can be thought as emerging from the complex interactions among individual psychological attributes as well as girls’ experiences at home, school, and in their community. In order to understand the potential overlap between bullying and sexual violence perpetration, it is helpful to draw upon a social–ecological theoretical framework to examine the multitude of potential risk and protective factors (Basile et al., 2009; Bronfenbrenner, 1977; Espelage & Holt, 2012; Hong & Espelage, 2012). The ecological perspective provides a conceptual framework for investigating the independent and combined impact of these social contexts and dynamic, transactional influences on behavioral development. This ecological framework has been applied to the conceptualization of bullying perpetration and victimization and highlights reciprocal influences on bullying behaviors between individual, family, school, peer, and community (Espelage et al., 2000; Espelage, Bosworth, & Simon, 2001; Hong & Espelage, 2012).
Bully Perpetration
Individual Risk Factors
Certain individual characteristics heighten one’s risk for being victimized. In demographic terms, boys are victimized and also perpetrate bullying more than girls (Bosworth, Espelage, & Simon, 1999; Espelage & De La Rue, 2011), although this depends somewhat on the form of victimization/perpetration. Whereas boys are more likely to experience physical bullying victimization (e.g., being hit), girls are more likely to be targets of indirect victimization (e.g., social exclusion) (Jeffrey, Miller, & Linn, 2001). In one of the few studies addressing the influence of race on bullying, Black students reported less victimization than White or Hispanic youth (Nansel et al., 2001). Juvonen and colleagues (2003) found that Black middle school youth were more likely to be categorized as bullies and bully-victims than White students. Another study found that Hispanic students reported somewhat more bullying than Black and White youth (Nansel et al., 2001).
Cook, Williams, Guerra, Kim, and Sadek (2010) conducted a meta-analysis on the cross-sectional outcomes for bullies, victims, and bully-victims across 153 studies. The strongest individual predictors of being a perpetrator of bullying included having high levels of externalizing behavior (and internalizing behavior to a lesser extent) and being a male student. Among the constellation of emotions associated with bully perpetration, empathy and caring behaviors have consistently been found to be negatively associated with aggression, including bullying perpetration (Espelage, Mebane, & Adams, 2004), and positively associated with and prosocial skills (Endresen & Olweus, 2001; Feshbach & Feshbach, 1982). In several cross-sectional and longitudinal studies of bullying behavior (e.g., name calling, teasing, threatening), anger was the strongest predictor of bullying (Bosworth et al., 1999; Espelage et al., 2001).
Great debate ensues around the potential longitudinal associations between bullying perpetration and later delinquency. Indeed, extant research suggests that bullies are more likely than their peers to engage in externalizing behaviors, to experience conduct problems, and to be delinquent into young adulthood (Farrington & Ttofi, 2011). However, many of these longitudinal studies have included only male samples; thus, it is unclear whether bully perpetration during early adolescence among females would be associated with delinquency.
Contextual Influences
Family, peer, and school contexts can exert positive or negative influences on bullying involvement and are critical to measure when trying to understand bullying dynamics. Parent-level factors, such as negative adult influences and lack of parental support, have been found to be associated with bullying perpetration (Espelage et al., 2000). A few scholars have shown witnessing parental violence at home was a risk factor for peer conflicts (see Corvo & deLara, 2010 for a review; McCloskey & Stuewig, 2001), such as aggression and bullying among youth (Baldry, 2003; Bauer et al., 2006; Espelage et al., 2000; McCloskey & Lichter, 2003). These studies found that youth who are exposed to inter-parental violence at home are likely to engage in bullying in school, as well as become victims of bullying. Baldry’s (2003) study, which investigates the association between inter-parental violence and bullying in a sample of Italian youth, found that both boys and girls who witnessed violence between their parents were significantly more likely to bully their peers compared to those who were not exposed to inter-parental violence.
Familial social support also is influential. Lack of parental social support is a risk factor for bullying perpetration (Espelage et al., 2000). Middle school students classified as bullies indicate receiving substantially less social support from parents than those who are not involved in bullying (Demaray & Malecki, 2003). The school and community contexts are salient contributors to bullying perpetration. Youth with lower levels of school connectedness were significantly more likely to be involved in bullying and peer victimization (Espelage et al., 2000; Glew, Fan, Katon, Rivara, & Kernic, 2005; Skues, Cunningham, & Pokharel, 2005). Because schools are embedded in neighborhoods, an unsafe neighborhood environment can influence bullying behavior due to inadequate adult supervision or negative peer influences. There are relatively few studies (Bacchini, Esposity, & Affuso, 2009; Espelage et al., 2000) that have investigated how bullying behavior is influenced by experiences in environments outside of school, such as neighborhoods. Nevertheless, researchers consistently found an association between neighborhood violence and bullying behavior.
Sexual Violence Perpetration
Individual Risk Factors
Although sexual harassment/violence is a pervasive problem for middle and high school students, the individual characteristics of some students may put them at increased risk for perpetration. In terms of gender differences, it appears that more boys than girls harass their peers (AAUW, 1993, 2001). Among girls, more African-American students (63%) report harassing peers than did Hispanic or White females (50% each). Many studies have documented a relation between hostile attitudes toward women and perpetration of sexual violence (see review by Basile et al., 2009), but no studies have examined anger as a predictor of sexual violence perpetration by middle school females.
Contextual Influences
Virtually nothing is known about contextual influences on sexual harassment/violence in middle school settings. Studies are needed to explore family, school, and community influences on sexual violence perpetration. Drawing from what is known about sexual harassment generally, there is reason to believe that these contexts operate in a similar fashion as with bullying; that is, they serve to either promote or reduce sexual harassment. In terms of family context, following from the literature on bullying, it is probable that children from families which condone any type of aggressive behaviors (and more specifically those of a sexual nature) will be more apt to sexually harass their peers (Baldry, 2003). It also might be that, as is the case with bullying, youth with secure attachments and adequate parental support are less likely to be involved in sexual harassment, potentially protected by personality features derived from positive parental relationships. With respect to peer context, the AAUW studies (2001) revealed that perpetrators of sexual harassment felt their behaviors were justified because “all kids do it” and because of pressure from peers to engage in such behaviors. Social network analyses and hierarchical linear modeling were applied to a large sample of middle school students, and found that if students had friends that were dismissive of sexual harassment (condoning), their individual levels of sexual harassment increased over the middle school years (Birkett & Espelage, in press). Finally, in regard to school context, existing studies have found that sexual harassment often occurs in public arenas, and that treatment of these incidents witnessed by school staff have a critical impact on how students view the school climate. Finally, there appears to be a general acceptance of sexual harassment in schools that likely influences perpetration rates; as noted by students and teachers who argued that many females in their middle schools “were asking to get sexually harassed” because of the way they dressed or the way they interacted with boys (Charmaraman, Jones, Stein, & Espelage, in press).
Overlap of Bully and SV Perpetration
While there are few studies that have examined associations between bullying and sexual harassment, such studies have found that these behaviors are associated. Pepler and colleagues (2002) found that sexual harassment perpetration in fifth to eighth grade students was associated with increased bullying rates. DeSouza and Ribeiro (2005) examined a sample of Brazilian high school students and found that for both males and females, peers who self-reported bullying perpetration were more likely to sexually harass peers. Pepler and colleagues (2006) also found a positive association between sexual harassment perpetration and bullying perpetration among students. In this cross-sectional study of nearly 2,000 adolescents, sexual harassment perpetration was more prevalent among students who bullied others than those who did not report bullying others. Finally, in a recent study of over 1,000 middle school students bullying perpetration was predictive of sexual violence perpetration over a 1-year period for both males and females (Espelage et al., 2012). To add to this limited literature, the purpose of this chapter is to provide prevalence estimates of bullying experiences and sexual harassment/sexual violence (SH/SV) perpetration for female middle school students in a midwest school district. Further, another purpose is to identify risk and protective factors identified in the literature as associated with these two outcomes. To this end, this study included analyses to examine how risk and protective factors predict future bullying perpetration and sexual harassing behaviors in an effort to better understand shared risk and protective factors for these behaviors.
Methods
Participants
Participants for this study consisted of 576 female students in fifth to seventh grades from four public middle schools located in a Midwestern state. Ages ranged from 11 to 15 years with a mean of 12.6 years in the first wave of data collection. Students included 56.5% African American, 26.1% White, 11% other or biracial, 3.8% Hispanic/Latino, 1.5% Asian, and 1.1% American Indian/Alaskan Native. Data were collected over five waves, which included Spring 2008 (Wave 1), Fall–Spring 2008–2009 (Waves 2 and 3), and Fall 2009 (Wave 4).
Procedure
Data were collected in collaboration with school administrators, teachers, and community representatives. Upon receiving assent from the university Institutional Review Board (IRB) and the school districts, consent forms were mailed to parents and guardians of all registered students by the school districts. Parents and guardians were provided with phone numbers, addresses, and fax numbers to return the form if they did not wish their son/daughter to participate. All schools returned surveys for 90–95% of their student population. At the beginning of each data collection period, students were informed that the researchers were interested in knowing how they think and feel about some things in their lives (e.g., school, friends, family, community). They were asked to provide a written assent by signing their name on the survey coversheet. Students were informed that their name would be converted to a number and were assured of anonymity and confidentiality. Students who elected not to participate or who had parental consent forms sent back were asked to go to another supervised classroom. The remaining students were informed that their participation was strictly voluntary and that they had the option of withdrawing from the study at any time. The survey administration lasted approximately 45 minutes.
Measures
Bullying and sexual violence perpetration scales at Wave 4 were the outcome variables.
Predictor variables included Wave 1 bully and sexual violence perpetration scales and a wide range of individual, family, community, and school Wave 1 predictors.
Bullying and Sexual Violence Perpetration Waves 1 and 4
Bully Perpetration
The 9-item Illinois Bully Scale (Espelage & Holt, 2001) was used to assess the frequency of teasing, name-calling, social exclusion, and rumor spreading. Students are asked how often in the past 30 days they teased other students, upset other students for the fun of it, excluded others from their group of friends, and helped harass other students, etc. Response options include “Never,” “1 or 2 times,” “3 or 4 times,” “5 or 6 times,” and “7 or more times.” The construct validity of this scale has been supported via exploratory and confirmatory factor analysis (Espelage & Holt, 2001). Factor loadings in the development sample for these items ranged from 0.52 to 0.75, and this factor accounted for 31% of the variance in the factor analysis (Espelage & Holt, 2001). A Cronbach’s alpha coefficient of 0.87 was found for the development sample and the Bullying Scale correlated 0.65 with the Youth Self-Report Aggression Scale (Achenbach, 1991) and was not significantly correlated with the Victimization Scale (r = 0.12). The scale consistently emerges as distinct from physical aggression scales and correlated with peer nominations of bullying (Espelage & Holt, 2001; Espelage, Holt, & Henkel, 2003). Alpha coefficients of 0.86 and 0.85 were found for Waves 1 and 4 in the current study.
Sexual Violence Perpetration
A modified version of the American Association of University Women Sexual Harassment Survey (AAUW, 1993) was used to measure the frequency with which students perpetrated sexually harassing behaviors within the last year. The original AAUW 15-item scale was subjected to an exploratory factor analysis using principal axis factoring and a two-factor solution (groping/sexual harassment; forced sexual contact) was indicated when evaluated with the screen test and the Kaiser criterion (Espelage et al., 2012). Given the low incidence of forced sexual contact among middle school students, we used only the first factor in the analyses reported here. The first factor, Groping/Sexual Harassment, contained nine items (e.g., making sexual comments, spreading rumors, and pulling at clothing of another student), had exemplary internal consistency (α = 0.81), and accounted for 23.62% of the variance in the factor score (factor loadings ranging from 0.46 through 0.62). Response options included “Not sure,” “Never,” “Rarely,” “Sometimes,” and “Often.” Higher scores indicated greater sexual violence perpetration. Alpha coefficients of 0.72 and 0.81 were found for Waves 1 and 4 in the current study, respectively.
Individual Characteristics at Wave 1
Anger
Self-reported anger was assessed using the University of Illinois Anger Scale (Espelage & Stein, 2006). Students were asked how often the following things happened to them in the past 30 days: “I got in a physical fight because I was angry”; “I lost my temper for no reason”; “I was mean to someone when I was angry”; and “I was angry all day.” Response options included “Never,” “1 or 2 times,” “3 or 4 times,” “5 or 6 times,” and “7 or more times.” Higher scores indicated more self-reported anger. A Cronbach’s alpha coefficient of 0.81 was found for Wave 1 of the current study.
Depression
The Orpinas Modified Depression Scale (Orpinas, 1993) includes six items that asks adolescents how often they felt or acted in certain ways (e.g., “Did you feel happy,” “Did you feel hopeless about your future”) in the previous 30 days. A 5-point Likert-type scale ranging from 1 (Never) through 5 (Almost Always) is used to measure responses. All responses were summed with a range of 6–30; higher scores indicate more depressive symptoms. The Modified Depression scale has demonstrated strong construct validity through factor analyses and good internal consistency (0.74) when administered to adolescents 10–18 years of age (Orpinas, 1993). In the current study, good internal consistency reliability was found as the Cronbach’s alpha was 0.82 for Wave 1.
Delinquency
This 8-item scale is based on Jessor and Jessor’s (1977) General Deviant Behavior Scale and asks students to report how many behaviors listed on the measure they took part in during the last year. The scale consists of items such as “Skipped school” and “Damaged school or other property that did not belong to you.” Responses are recorded on a 5-point Likert-type scale with options ranging from 1 (Never) through 5 (10 or more times). The original study by Jessor and Jessor utilized this scale in a longitudinal study of 432 largely white middle class students in grades 7–10. A mean Cronbach’s alpha coefficient of 0.76 was reported across the 3-year study (1977). Since its development, this scale has been used numerous times resulting in Cronbach’s alpha coefficients ranging from 0.76 to 0.83 (Farrell, Danish, & Howard, 1992; Farrell, Kung, White, & Valois, 2000). In the current study, we found the scale to have a Cronbach’s alpha of 0.74 for Wave 1.
Caring Behaviors
The 4-item caring acts scale (Crick, 1996) measures exclusion, rumor spreading, and other activities meant to damage another child’s reputation or social relationships. Students are asked how often in the past 30 days they let others know that they cared about them; helped out other kids when they needed it, said or did nice things for other kids; and tried to cheer up other kids who felt upset or sad. Response options include “Never,” “1 or 2 times,” “3 or 4 times,” “5 or 6 times,” and “7 or more times.” A confirmatory factor analysis supported the scales’ construct validity (Crick, 1996), and the scale’s Cronbach’s alpha was 0.89 in a middle school sample (Espelage et al., 2004).
Family Abuse and Violence at Wave 1
Domestic Violence and Child Maltreatment
Three items from the Student Health and Safety Survey (CDC, 2004) were used to measure past abuse in the family. Students were presented with the following stem “Before you were 9 years old, did you ever…” followed by three items to assess domestic violence exposure and history of childhood maltreatment: (1) see or hear one of your parents or guardians being hit, slapped, punched, shoved, kicked, or otherwise physically hurt by their spouse or partner? (2) have injuries, such as bruises, cuts, or broken bones, as a result of being spanked, struck, or shoved by your parents or guardians or their partners? and (3) did someone ever force you to have sex or to do something sexual that you did not want to? Response options are “yes” or “no.” Each item was entered as separate predictors in the regression.
Sibling Aggression Perpetration
A sibling aggression perpetration scale was created for this study and included five items that assessed aggression between siblings (Espelage & Stein, 2006). Items were selected from the University of Illinois Bullying Scale in order to parallel that scale. Five items emerged as a scale in factor analysis, which includes the following: I upset my brother or sister for the fun of it; I got into a physical fight with my brother or sister; I started arguments with my brother or sister; I hit back when a sibling hit me first; and I teased my siblings for the fun of it. Students were asked to indicate how often they did these things to a sibling or other children in their family during that last 30 days. Response options include “Never,” “1 or 2 times,” “3 or 4 times,” “5 or 6 times,” and “7 or more times.” A Cronbach’s alpha coefficient of 0.82 was found for Wave 1.
Parental Monitoring and Family Social Support at Wave 1
Parental Monitoring
The Parental Supervision subscale from the Seattle Social Development Project (Arthur, Hawkins, Pollard, Catalano, & Baglioni, 2002) was used to measure respondents’ perceptions of established familial rules and perceived parental awareness regarding school work and attendance, peer relationships, alcohol or drug use, and weapon possession. The subscale includes eight items measured on a 4-point Likert scale ranging from 1 (Never) through 4 (Always). Example items include, “My family has clear rules about alcohol and drug use” and “My parents ask if I’ve gotten my homework done.” A Cronbach’s alpha of 0.86 was calculated for Wave 1.
Family Social Support
Family social support was measured using the family subscale from the Vaux Social Support Record. The VSSR is a 9-item questionnaire that is an adaptation of Vaux et al’s. (1986) Social Support Appraisals (SSA) 23-item scale that was designed to assess the degree to which a person feels cared for, respected, and involved (Vaux et al., 1986). The family subscale is three items that measure the support available from the family. Scores range from 0 to 6, with higher scores indicating greater perceived support. A sample item is “There are people in my family I can talk to, who care about my feelings and what happens to me.” The family subscale showed good internal consistency across samples. Mean Cronbach’s alpha coefficients were 0.80 for the five student samples, and 0.81, and for the five community samples. Internal consistency reliability for the family social support scale was 0.78–0.82. Alpha coefficient of 0.82 was found for Wave 1 in the current study.
School Social Support at Wave 1
School social support was measured using the school subscale from the Vaux Social Support Record (Vaux et al., 1986). The school subscale is three items that measure the support available from the school. Scores range from 0 to 6, with higher scores indicating greater perceived support. A sample item is “There are people in my school I can talk to, who care about my feelings and what happens to me.” The school subscale showed good internal consistency across samples. Mean Cronbach’s alpha coefficients were 0.80 for the five student samples, and 0.81, and for the five community samples. Internal consistency reliability for the school social support scale was 0.78–0.82. Alpha coefficient of 0.80 was found for Wave 1 in the current study.
Community Violence at Wave 1
Exposure to community violence was measured with five items from the 12-item Children’s Exposure to Community Violence scale (Richters & Martinez, 1990). Students are asked “How often do you hear or see the following in your neighborhood, school, or at your home?”: (1) I have heard guns being shot; (2) I have seen somebody arrested; (3) I have seen drug deals; (4) I have seen somebody being beaten up; and (5) I have seen gangs. Response options range from 1 (Never) through 4 (Often). Alpha coefficient of 0.91 was found for Wave 1 in the current study.
Dismissive of Sexual Harassment at Wave 1
An adapted version of the National Institute of Justice Survey of Attitudes and Behaviors Related to Sexual Harassment (Taylor & Stein, 2007) was used to measure dismissive attitudes toward sexual harassment. Students were asked how much they agreed or disagreed with ten items including “sexual harassment is just having fun,” “When boys make comments about girls’ bodies, girls should take it as a compliment” and “If I have flirted with a person in the past, then I am encouraging them to sexually harass me.” Response options ranged from 1 (Strongly Disagree) through 4 (Strongly Agree).
Results
Prevalence of Bully Perpetration and Sexual Violence Perpetration Wave 1
Prevalence of bullying perpetration was calculated as the number of students whose bully perpetration scale scores were one standard deviation above the mean. Using this as a cutoff, 12% of females could be considered bully perpetrators. Given the dearth of literature on SV perpetration among middle school female students, prevalence data are presented for selected items to inform future conceptualizations of SV. In relation to the AAUW-revised sexual harassment/violence perpetration scale, 28% of girls reported making sexual comments to other students in the last year, 7% of girls spread a sexual rumor, and 2% of girls pulled at someone’s clothing.
Correlational Analysis
An initial correlational analysis was conducted to examine the relations among all of the study variables (Table 3.1). A review of the correlational analysis reveals that many of the Wave 1 predictors share an association with bullying perpetration and sexual harassment perpetration at Wave 4. Specifically, dismissive attitudes towards sexual harassment, anger, depression, delinquency, and community violence were all significantly positively related to later levels of bullying and sexual harassment. In addition, a history of child abuse and sibling aggression was significantly and positively related to each outcome. Parental monitoring and family support both showed significant negative correlations with bullying and sexual harassment at Wave 4. However, what is important to notice is that the magnitude of the associations between the predictor variables and the two outcomes were strongest for bullying perpetration. These findings suggest that when these predictors are considered comprehensively and baseline levels of bullying and sexual harassment perpetration are accounted for, it is likely that these variables will explain more variance in bullying than sexual harassment perpetration.
Longitudinal Predictors of Bullying Perpetration
The first regression model included independent variables from Wave 1 predicting bullying perpetration at Wave 4, controlling for Wave 1 bullying perpetration. The overall model was significant (F(15,487) = 14.91, p < 0.001; adjusted R 2 = 0.29; Table 3.2). Six of the independent variables contributed significantly to the prediction of later bullying perpetration and explained 29% of the variance of the outcome of bullying perpetration. The strongest predictor was sibling aggression (β = 0.24), followed by depression (β = 0.15), delinquency (β = 0.11), and previous bullying perpetration (β = 0.18). These findings indicate that higher rates of bullying perpetration at Wave 4 (after controlling for bullying at Wave 1) is predicted by greater sibling aggression, greater depression and delinquency at Wave 1. From a protective standpoint, less involvement in bully perpetration at Wave 4 (after controlling for bullying at Wave 1) was associated with greater caring behaviors directed toward other students. Finally, greater perceived family social support was associated with less bullying at Wave 4. Interestingly, exposure to domestic violence and experiencing childhood sexual abuse and neglect were not significant predictors of bullying perpetration over time (Table 3.2).
In an effort to get a more nuanced understanding of the bullying behaviors, Table 3.3 displays frequency information for specific bullying behaviors targeted towards male or female peers. The girls in this study tended to engage in similar amounts of bullying behaviors across genders and did not show substantial deviations in who they targeted. The girls in this study did tend to threaten male peers more and engaged in more rumor spreading directed towards girls.
Longitudinal Predictors of Mild Sexual Violence Perpetration
The second regression also used Wave 1 independent variables to predict later levels of mild sexual violence/harassment perpetration. The overall model was significant (F(17,485) = 3.81, p < 0.001; adjusted R 2 = 0.09; Table 3.4). Two of the independent variables were significant predictors. Attitudes that were dismissive of sexual harassment (β = 0.18) and earlier sexual harassment perpetration (β = 0.18) were predictive of later sexual harassment behaviors. Table 3.5 displays frequency information for sexual harassment behaviors. Most behaviors occurred rarely or never, and the most frequent behavior was girls’ calling both girls and boys “gay.”
Discussion
In this study of early adolescent females, bullying perpetration was associated with later sexual violence perpetration when cross-sectional data were considered, but this association was nonsignificant in the longitudinal analyses. These findings could be due to the high stability of bully perpetration during the middle school years. Further, the individual and family predictors are better predictors of bully perpetration than sexual harassment perpetration. Interestingly, when we predict sexual violence perpetration overtime, bully perpetration was not a significant predictor either. The only significant predictor of sexual violence included dismissiveness of sexual harassment.
For girls who engage in bullying behaviors there appear to be a set of contextual factors and individual predictors that remain stable as risk and protective factors. Specifically, the family environment poses a concern when there are low levels of family support and high levels of sibling aggression. At the individual level depression and delinquency remained as significant predictors for bullying perpetration, which is consistent with recent research with male samples (Farrington & Tfoti, 2011). When considering sexual violence perpetration by females it appears that a significant risk is the attitudes and behaviors that young women have regarding sexual violence and harassing behaviors. When girls engaged in sexually harassing behaviors and were also more dismissive of sexual harassment, this created a significant risk for later being a perpetrator of sexual violence. In combination, these results suggest that those variables that predict bully perpetration among girls are not good predictors of sexual violence perpetration.
Predictors of bully perpetration included sibling aggression and lower levels of family social support. These factors predicted later levels of bullying, consistent with research that shows children in families that encourage “fighting back” and display indifference to their youth have children who display high levels of bully perpetration (Baldry & Farrington, 2000; Loeber & Dishion, 1984; Olweus, 1995b). These young girls may be coming from family environments that are more likely to condone aggression, and therefore they may be quicker to use bullying behaviors as a way to interact with their peers.
An additional contextual factor that predicted bullying was engagement in delinquency and prior bullying behaviors. It is likely that these associations could be linked to the girls’ friends and their behaviors. Indeed, peer group membership is an important influence on adolescent girls’ behaviors. Girls who hang out with friends who engage in bullying often take on these same behaviors (Espelage et al., 2003). The same has been noted for delinquency, where females who engage with delinquent peers are at an increased risk of continued delinquency in the future (Jennings, Maldonado-Molina, & Komro, 2010). This suggests that the peer group is influential in maintaining aggressive or adverse behaviors, especially when these behaviors are present early on. Therefore, there is a strong need to engage in efforts to target the peer group, as prevention efforts aimed solely at the individual level are likely not to be as effective.
This is not to say that individual level predictors are not also important to consider. In this study, depression was a significant predictor of bullying perpetration. Researchers have shown that depression may influence a girl’s propensity to engage in aggressive behavior and have hypothesized this may be due to girls feeling a greater indifference to engagement in prosocial behaviors and a greater attachment to deviant peers (Ehrensaft, 2005). This is also consistent with lower levels of caring behaviors being predictive of later bullying behaviors. When girls are experiencing greater levels of depression they may have less motivation to develop and maintain prosocial relationships. This is consistent with what was noted above, where girls who are engaged with peer groups who engage in less prosocial behavior are at greater risk of future bullying perpetration.
In this study there was no overlap between predictors of bullying perpetration and that of sexual harassment. Girl’s dismissive attitudes toward sexual harassment and previous engagement of harassing behaviors predicted later sexual harassment. Girls in this study tended to maintain their level of sexually harassing behaviors, suggesting that early experiences may play a significant role in establishing a pattern of behavior. Indeed, findings from the AAUW (1993) revealed that 38% of girls reported having first been sexually harassed in sixth grade. Further, the few empirical studies of sexual harassment among middle school students have supported that sexual harassment is pervasive even among young adolescents, and that rates of sexual harassment increase throughout middle school, indicating a need for early intervention (for review see Espelage & Holt, 2012). However, it should be noted that the low base rate of sexual harassment among the girls in this sample may have made it difficult to detect predictors of this behavior. That said, the findings here suggest that more research needs to be conducted with middle school girls to determine what risk and protective factors are associated with the onset and continuation of sexual harassment perpetration. But even more pressing is that bully prevention programs that target individual and family variables will have limited efficacy in reducing sexual harassment perpetration unless the conversations focus on gender and attitudes that are dismissive of unwanted sexual commentary and behaviors.
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Espelage, D.L., De La Rue, L. (2013). Examining Predictors of Bullying and Sexual Violence Perpetration Among Middle School Female Students. In: Russell, B. (eds) Perceptions of Female Offenders. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5871-5_3
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