Analyzing Predictors of Bullying Victimization With Routine Activity and Social Bond Perspectives

Abstract

Bullying victimization in school settings is a serious problem in many countries including the United States. It has been associated with serious incidents of school violence as well as detrimental physical, psychological, emotional, and social consequences for its victims. Given its consequences, it is crucial to understand who is more likely to be targeted for bullying victimization. This study examines whether a number of important factors such as gender, physical and interactionist school security measures, and involvement in extracurricular activities influence an individual’s risk of bullying victimization from social bond and routine activity perspectives. The study employs the 2011 School Crime Supplement of the National Crime Victimization Survey to investigate the causes of bullying victimization. The results show that gender, interactionist school security measures, and extracurricular activities affect an individual’s likelihood of bullying victimization.

Keywords

bullying victimization routine activity theory social bond theory

Introduction

Recently, researchers have become interested in explaining the causes and consequences of bullying (Felix, Furlong, & Austin, 2009). Olweus (2003) defines bullying as a specific form of aggression, which occurs intentionally and repeatedly, and involves an imbalance of power between a perpetrator and a victim. Bullying can be direct, which encompasses a relatively open attack at a person such as hitting, kicking, spitting, and taking someone’s belongings, or can be indirect, including behaviors such as making fun of, spreading rumors about someone, and social exclusion (Carbone-Lopez, Esbensen, & Brick, 2010).

A number of negative emotional, psychological, and behavioral consequences result from bullying victimization. Those consequences can be immediate for victims such as experiencing higher levels of anxiety (Olweus, 1997; Richard, Schneider, & Mallet, 2012), lower self-esteem, poorer emotional and social adjustment (Olweus, 1997; Vanderbilt & Augustyn, 2010), and higher risks of depression and suicide ideation (Turner, Exum, Brame, & Holt, 2013; Vanderbilt & Augustyn, 2010). The consequences for victims compared with non-victims may also be long-lasting such as greater health problems, being in abusive relationships during adulthood, and poorer self-esteem later in life (Rigby, 2004).

The consequences of bullying may be especially important given that approximately one out of three youth is involved in bullying as either a victim, perpetrator, or both (Nansel et al., 2001; U.S. Department of Education, 2011). According to the School Crime Supplement (SCS) data, approximately 28% of students were bullied in 2009 and in 2011 (U.S. Department of Education, 2011, 2013).

Given the prevalence and detrimental consequences of bullying, it is important to understand the theoretical causes of who is more likely to be targeted for bullying victimization. In this study, routine activity and social bond theory are used to understand the causes of bullying victimization in school settings by focusing on a number of important factors such as gender, physical security, interactionist school security measures (closeness of relationships between students and adults in the school), and involvement in extracurricular activities. Although these are different theories with unique perspectives, each of them provides a significant lens to understand how these factors affect a student’s likelihood of bullying victimization. For instance, according to routine activity theory, crime is more likely to occur when suitable targets come into contact with motivated offenders in the absence of capable guardians (Cohen & Felson, 1979). Suitable targets refer to someone or something that draws motivated offenders who intend to commit crime, while a capable guardian is someone or some object who prevents offenders from committing crime. Routine activity theory is well suited to explain the causes of victimization in the school environment given that schools vary in the presence of suitable targets, motivated offenders, and capable guardians (Popp, 2012; Popp & Peguero, 2011). Based on the routine activity perspective, increasing the supply of guardians such as security guards and other forms of adult supervision should discourage bullies and reduce the risk of bullying victimization. For example, extracurricular activities with adult supervision should discourage bullies preventing bullying victimization at school. Given the plausibility of these arguments, it is surprising that very few studies have utilized this framework to explicitly examine bullying victimization (Popp, 2012). Thus, this study contributes to the literature through explaining bullying victimization through these mechanisms.

In addition, social bond theory emphasizes how strong bonds with conventional society prevent individuals from committing crime (Hirschi, 1969). Although this theory is usually used to understand what causes crime, a large overlap exists in offenders and victims of crime, which indicates that the causes of offending and victimization may be similar (Higgins, Khey, Dawson-Edwards, & Marcum, 2012). This is a beneficial framework for understanding bullying victimization because stronger bonds with conventional others have been found to reduce criminal involvement and victimization (Catalano, Oesterle, Fleming, & Hawkins, 2004; Payne, Gottfredson, & Gottfredson, 2003) and being bullied has been found to reduce bonds (Popp & Peguero, 2012). Therefore, by extension, bonds with others should also reduce the likelihood of bullying victimization. Based on social bond theory, close and positive relationships between students and adults should strengthen students’ attachments with school and reduce their involvement in bullying and victimization. Attending extracurricular activities in school should also protect students from being a victim of bullying because these activities occupy their time, and are important in building and providing social support and strengthening attachments with others in school. While the effect of bonds on bullying victimization have been examined among a Chinese sample (Chan & Chui, 2013), this study contributes to the literature through assessing how bonds affect youth based on a nationally representative sample in the United States.

Applying these frameworks, we utilize the 2011 SCS of the National Crime Victimization Survey (NCVS) to assess theoretical differences in gender, physical security and interactionist security measures, and involvement in extracurricular activities on the likelihood of bullying victimization. This research is important because while studies have identified factors related to bullying victimization (Carbone-Lopez et al., 2010; Nansel, Overpeck, Haynie, Ruan, & Scheidt, 2003; Sawyer, Bradshaw, & O’Brennan, 2008; Turner et al., 2013; Wang, Iannotti, & Nansel, 2009), very few have applied theoretical frameworks to understand how these factors affect bullying (Chan & Chui, 2013; Cunningham, 2007; Higgins et al., 2012; Popp, 2012; Popp & Peguero, 2011). Through understanding why certain groups are more vulnerable to being a victim of bullying, effective policies can be created to prevent bullying in schools.

Below, we review the theoretical frameworks followed by a discussion of the factors related to bullying victimization, and then we apply these frameworks to explain the findings in the literature. Next, we describe our methods followed by a presentation of our results. We conclude with a discussion of our findings and implications for future research and policy aimed at preventing bullying victimization.

Theoretical Background

Routine Activity Theory

Cohen and Felson (1979) developed a routine activity approach to explain how increasing crime rates in the United States from 1947 to 1974 may be affected by changing social trends and people’s routine activity patterns, such as increasing proportions of female college attendance, working women, single households, and traveling. Routine activities are defined as “any recurrent and prevalent activities, which provide for basic population and individual needs” (p. 593). Those activities that individuals involve in their daily routines may occur at home or away from home such as attending school, engaging in leisure activities, or working.

The three important elements which affect the opportunities for crime are motivated offenders, suitable targets, and the absence of capable guardians (Cohen & Felson, 1979; Felson, 2002). A motivated offender is someone who is intent to commit crime and is able to act on that intention (Cohen & Felson, 1979). A suitable target is anything or anyone that draws motivated offenders to commit crime, and a capable guardian is anyone or anything that prevents motivated offenders from committing crime (Cohen & Felson, 1979; Felson, 2002). Importantly, Felson (2002) argued that guardians include not only police officers or security guards but the most important guardians are ordinary citizens as well. Therefore, crime is more likely to occur when motivated offenders and suitable targets meet in the absence of capable guardians, but any of these three elements might be sufficient to affect criminal acts. Through the course of routine activities, people become available targets for motivated offenders (Cohen & Felson, 1979).

Routine activity theory provides an important framework for examining bullying victimization within a school setting because attending school is an important routine activity of juveniles where the presence of capable guardians and motivated offenders fluctuates throughout the day (Popp, 2012). A motivated offender is a bully who takes advantage of power differentials to harm others intentionally and repeatedly. Target suitability could depend on whether victims are viewed as weak in some way. For example, targets of bullies are commonly emotionally and physiologically weaker than other students (Olweus, 1997), are less likely to stand up for themselves, and have fewer friends (Jeralds, 2011). Therefore, the perception that some students are weaker and have fewer friends to provide guardianship may make them suitable targets for motivated offenders. Furthermore, schools vary in the level of guardianship, and can include anyone or anything that prevents students from becoming victims of bullies such as the use of security cameras, security personnel, and others in the hallways (Burrow & Apel, 2008). In sum, routine activity theory is well suited to explain bullying victimization in schools.

Social Bond Theory

Hirschi (1969) emphasized the importance of bonds individuals have to conventional society, and argues that when bonds to society are broken or weakened, deviant acts occur because the motivation to engage in deviance is constant. Specifically, the attachment, commitment, involvement, and belief bonds inhibit individuals from committing crime (Hirschi, 1969). Attachment, according to Hirschi, refers to individuals’ sensitivity to the opinions of other people and institutions. He argues that parents’ interactions with youth have a significant role in the formation of the attachment bond. Youth are less likely to engage in delinquent activities when they spend time with their parents because their parents directly supervise them (Hirschi, 1969). In addition, youth with greater attachment to parents refrain from crime because they care what they think and do not wish to disappoint them.

Similarly, a stronger attachment bond within schools may lower the risk of deviant acts because youth are concerned about the opinion of others such as teachers (Hirschi, 1969). For instance, Hirschi (1969) reported that youth who do care about what teachers think about them were less likely to engage in delinquent acts. In sum, the greater attachment level results in increased social control on individuals, which prevents them from engaging in delinquent acts.

Second, the commitment bond emphasizes the importance of investments in conventional society, such as getting an education, working, and saving money for the future (Hirschi, 1969). Hirschi (1969) argued that individuals think about how much they have to lose when they break the law because they may endanger those investments that they have made for their future. Therefore, individuals with higher educational and career aspirations are more likely to obey the rules of society to protect these investments (Hirschi, 1969).

Third, Hirschi (1969) argued that a strong involvement bond reduces the time youth have available to engage in deviant acts. In addition, Hirschi emphasized the importance of the quality of activities and reported that youth who are involved in “working-class-adult” activities such as riding around, smoking, drinking, and dating are more likely to commit delinquent acts than youth who are involved in conventional activities such as homework (p. 196).

Finally, the belief bond refers to the existence of a shared common value system within society, although people vary in how much they feel they should abide by these rules (Hirschi 1969). Therefore, deviant behavior depends on how important such values are to individuals. For instance, Hirschi (1969) reported that youth who have a lack of respect for the police and the law were more likely to engage in deviant acts.

Strong support has been found for the importance of school bonds in reducing the likelihood of delinquency (Catalano et al., 2004; Payne et al., 2003; Welsh, 2001). Although Hirschi’s theory was created to explain delinquent acts and not bullying victimization, a strong overlap exists between bullying others and bullying victimization (Anderson et al., 2001; Higgins et al., 2012; Nansel et al., 2003), which indicates that the causes of bullying and victimization may be similar. In support of the importance of social bonds, Popp and Peguero (2012) found that being bullied at school reduces students’ attachment to school and belief in a school environment as not tolerating misbehavior. Chan and Chui (2013) found that social bonds influence bullying perpetration among a sample of Chinese youth. Furthermore, Higgins et al. (2012) argued that those with weaker bonds will differ in their lifestyle, which puts them at a greater risk of not only delinquency but being victims of bullying as well. In sum, social bonds may play an important role in explaining the causes of bullying victimization.

Factors Related to Bullying Victimization

Gender

Most studies have found that male students are more likely to become victims of direct bullying whereas female students are more likely to be victims of indirect bullying (Bradshaw, Sawyer, & O’Brennan, 2009; Richard et al., 2012; Wang et al., 2009) with limited exceptions (Peskin, Tortolero, & Markham, 2006). Despite the importance of gender as an explanatory variable, few studies have incorporated specific theoretical mechanisms to explain these gendered processes. The routine activities of males and females may explain differences in bullying victimization due to unique “gendered” experiences in socialization. Specifically, males are expected to be masculine which includes traits such as being strong, aggressive, dominant, and competitive (Padavic & Reskin, 2002). Therefore, for male students, bullying other male students might be a way to assert their masculinity and dominance (Ringrose & Renold, 2010). However, females are expected to act feminine, which includes traits such as passivity, frailty, and being virtuous (Padavic & Reskin, 2002). Because females are expected to be nice, supportive, and non-competitive, they are more likely to show their aggressiveness indirectly rather than physically (Ringrose & Renold, 2010). In addition, these gender norms imply that males should not bully females given stereotypes of their weaker nature (Ringrose & Renold, 2010). Therefore, males may not view females as suitable targets for direct bullying. Also, females may be less likely to see males or females as suitable targets for direct bullying because this behavior would be inconsistent with femininity and they are socialized to believe that males are dominant, powerful, and physically stronger than females (Ringrose & Renold, 2010).

In support of the influence of gender stereotypes on target suitability, Popp and Peguero (2011) found that females who violate stereotypes through participating in intramural sports were more likely to be targeted for school victimization than male students, and male students who violated stereotypical expectations through participating in school clubs were more likely to be viewed as vulnerable targets than female club participants. Furthermore, Lehman (2014) found that male students with high academic achievement were more likely to be bullied presumably because academic achievement is associated with femininity rather than masculinity. Academic achievement was not related to bullying victimization for female students (Lehman, 2014).

While gender is typically included as a control variable in tests of social bond theory, this theory is well suited to explain gender differences in bullying victimization. In support of the idea that bonds differ by gender, Jenkins (1997) found that female students were more committed and attached to school and have a greater belief in school rules than male students, and these bonds were related to less misbehavior at school. In addition, evidence suggests that strong attachment to parents and commitment to school protect females from delinquency compared with male students (Laundra, Kiger, & Bahr, 2002), and attachment to parents is positively and significantly related to academic achievement and inversely related to delinquency for females compared with males (Huebner & Betts, 2002). These stronger bonds with parents and school may protect females from delinquency as well as bullying victimization (Higgins et al., 2012). This is because stronger bonds likely increase girls’ involvement in activities such as doing homework and participation in organized conventional activities, thus reducing opportunities to engage in delinquency or be victimized.

While social bonds may protect female students from direct bullying, especially given that they are supervised more closely than males (Huebner & Betts, 2002), they are unlikely to protect females from indirect bullying. Indirect bullying can occur when the victim is not present, for example, when others gossip or exclude victims from social activities. It is also considered “natural” (Ringrose & Renold, 2010) or acceptable for girls to gossip, tease, and exclude others from social events (Bjorkqvist, Lagerspetz, & Kaukiainen, 1992).

In sum, compared with other demographic variables, gender is specifically important to explain theoretically because regardless of students’ age and race/ethnicity, gender differences in bullying victimization especially by victimization type are pervasive. For instance, for females one of the most common victimization types is relational aggression, whereas for males, it is physical victimization (Felix et al., 2009).

Therefore based on the routine activity and social bond frameworks, we hypothesize the following:

Hypothesis 1: Males will be more likely to be a victim of direct bullying than females.

Hypothesis 2: Females will be more likely to be a victim of indirect bullying than males.

School Security Measures

Based on routine activity theory, school security measures may serve to increase the supply of guardians while reducing the attractiveness of targets (Cohen & Felson, 1979). Strategies to reduce bullying can be classified into two main categories of security measures: physical and interactionist (Gregory et al., 2010; Richard et al., 2012; Time & Payne, 2008). Physical security measures focus on structural changes and include measures such as security cameras, security guards, and locker checks (Time & Payne, 2008). Some evidence supports the effectiveness of reducing bullying when adults, staff, or security guards supervise the hallways (Blosnich & Bossarte, 2011; Jeong, Kwak, Moon, & San Miguel, 2013). In contrast, some studies find that measures such as cameras, metal detectors, and security personnel were ineffective in reducing victimization risks at school (Burrow & Apel, 2008; Popp, 2012; Schreck, Miller, & Gibson, 2003).

Based on routine activity theory, physical security measures such as capable guardians may play an important role in terms of preventing direct bullying victimization because students are aware that they are being watched. However, physical security measures might not be related to indirect bullying because security cameras, guards, or teachers are unlikely to see or be able to prevent a rumor from starting, for example. Therefore, we hypothesize the following:

Hypothesis 3: Physical security measures will be inversely related to direct bullying victimization.

Hypothesis 4: Physical security measures will be unrelated to indirect bullying victimization.

In contrast, interactionist security measures focus on increasing positive and open communication between students and school staff (Time & Payne, 2008). Olweus (2003) argued that teachers, school officials, and administrators must be involved with students to prevent bullying incidences. This involvement should lead to improvements in the emotional connection between teachers and students, the guardianship which they provide, and also encourage students to talk to them when they have a problem (Olweus, 1997).

In support of these ideas, research shows that bullying victimization is reduced when students have good communication with teachers (Cunningham, 2007; Richard et al., 2012; Popp, 2012). While usually framed in terms of increasing guardianship at school, the effectiveness of interactionist measures can also be attributed to social bond theory. For example, close relationships with teachers and social support are directly related to the attachment bond. Students with close relationships to teachers likely feel that they can report their bullying victimization compared with those who do not have these social supports. They will also likely avoid situations and places that increase their likelihood of being victimized because of these strong bonds (Higgins et al., 2012).

Interactionist security measures also foster an environment where students feel comfortable reporting rule violations (Time & Payne, 2008). When rules are perceived as fair, as being enforced, and understood, victimization at school is less likely (Catalano et al., 2004; Cunningham, 2007; Gregory et al., 2010). In addition, when students perceive that school rules are fair, the belief bond should increase. Also, when students do not believe that bullying is acceptable behavior, they may seek out measures to protect themselves from being bullied. According to Catalano et al. (2004), strong school bonds inhibit behavior that is inconsistent with the values and rules of the school. They add that if school rules are negative, problem behaviors likely result, but if the rules are positive, positive behaviors likely result. Therefore, it is likely that students who are victims have more negative perceptions of school rules and are less strongly bonded to the school than non-bullied students.

In sum, while close supportive relationships with teachers and fair and enforced rules may increase guardianship, these factors should also strengthen the attachment and belief bond. Therefore, we hypothesize the following:

Hypothesis 5: Interactionist security measures will be inversely related to direct bullying victimization.

Hypothesis 6: Interactionist security measures will be inversely related to indirect bullying victimization.

Extracurricular Activity Involvement

From a routine activity perspective, involvement in activities may provide students with capable guardians when adults supervise these activities, which thus reduces bullying victimization (Peguero, 2009; Popp & Peguero, 2011). However, involvement in activities may increase interactions with motivated offenders, and depending on the activity, provide very little guardianship (Popp, 2012). Also, the type of activity students are involved in and/or the gender of the participants may affect who is perceived as a more suitable target (Popp, 2012; Popp & Peguero, 2011). In support of these arguments, Popp (2012) found that involvement in classroom-related activities increased the likelihood that students were physically and socially bullied, while those who participated in sports or school clubs did not have an increased risk of victimization. Similarly, Peguero (2009) found that students involved in classroom-related activities and school clubs were more likely to be victims of crime at school which includes being bullied. In contrast, those involved in interscholastic sports were less likely to be targeted for violent crimes presumably because their perceived strength and higher status made them a less suitable target (Peguero, 2009). In sum, the effect of participation in extracurricular activities on bullying victimization should depend on the type of activity given variations in guardianship and target suitability.

Extracurricular activity involvement regardless of the type of activity should also affect bullying victimization from a social bond perspective. Involvement in activities may foster supportive relationships, increasing the strength of the attachment bond. For instance, Clark (2011) found that extracurricular activity involvement provides students with the opportunity to develop social skills and establish supportive and positive relationships, which protect them from becoming a victim of violence at school. These findings are applicable to this study given that social support from others decreases the likelihood that students are bullied (Popp, 2012).

Not only does participation in extracurricular activities increase the attachment bond but when students are occupied in conventional activities, they do not have time to engage in bullying behaviors. For example, involvement in extracurricular activities provides protective factors from risky behavior and provides better academic achievement during high school (Eccles & Barber, 1999). Youth who are involved in school activities have higher grades, higher academic aspirations, and more positive attitudes toward school than other students who did not participate in those activities (Darling, Caldwell, & Smith, 2005). This should further occupy their time and reduce the opportunity they will be victimized. In sum, bullying victimization is likely reduced for students who are involved in extracurricular activities because they refrain from risky behaviors, have higher educational achievement, social support from others, and more social networks.

While predictions from social bond theory do not specify which types of conventional activities are important, based on routine activity theory, vulnerability to bullying victimization will depend on the type of activity. As mentioned above, those who are involved in sports are likely perceived as stronger and as having more status, while those involved in other activities may be perceived as more suitable, weaker targets. Therefore, we hypothesize the following:

Hypothesis 7: Involvement in sports-related extracurricular activities will decrease the likelihood of direct and indirect bullying victimization.

Hypothesis 8: Involvement in non-sports-related extracurricular activities will increase the likelihood of direct and indirect bullying victimization.

Method

The NCVS is the main source of nationally representative victimization data in the United States and provides information not captured through arrest data (U.S. Department of Justice, Office of Justice Programs, Bureau of Justice, 2011). Individuals 12 years of age and older residing within households are interviewed every 6 months over a 3-year period based on a multi-stage cluster sample. Approximately every 2 years, the SCS is completed by youth in the household who are aged 12 to 18, fall between sixth and 12th grade, and attended school sometime during the previous 6 months.

The 2011 SCS of the NCVS data is used in this study. The primary purpose of the SCS is to obtain information on school-related victimization on a national level. The SCS includes questions related to security measures employed in school, participation in after-school activities, perceptions of school rules and enforcement of these rules, the presence of drugs, alcohol, weapons, and gangs in school, hate-related incidents, bullying victimization, and attitudinal questions relating to fear of victimization at school (U.S. Department of Justice, Office of Justice Programs, Bureau of Justice, 2011).

The 2011 SCS was administered to 10,341 eligible NCVS respondents aged 12 through 18 within households between January through June of the year of data collection. Of those eligible, 63.3% or 6,547 completed the survey. Youth who were homeschooled (n = 237) during any part of the year were excluded from analyses because it was unclear how many months they were at risk of being bullied at school.

Dependent Variables

This study relies on a commonly used measure of bullying from the SCS in which students are directly asked if they have been bullied during the school year (Hutzell & Payne, 2012; Popp, 2012). The likelihood of a student’s bullying victimization was measured by whether the student experienced any form of direct or indirect bullying victimization. For direct bullying, respondents indicated whether they have been threatened, have been pushed, shoved, tripped, or spit on, had their personal property destroyed, and were made to do things that they did not want to do. The indirect bullying variable includes responses to whether students had been made fun of, had rumors spread about them, or been excluded from activities by their peers. Because the prevalence of bullying was low, both direct and indirect bullying victimization were coded yes if the student experienced at least one of these bullying behaviors and were coded no if the student did not experience any of these bullying behaviors during the school year.

Independent Variables

Gender is captured by the sex of the respondent, which was coded 0 for females and 1 for males.

The physical security measures indicate whether a student reported the school had security guards or assigned police officers, other school staff or other adults supervising the hallways, metal detectors, including wands, locked entrance, or exit doors during the day, a requirement that visitors sign in, locker checks, a requirement that students wear badges or picture identification, and one or more security cameras to monitor the school. These items capture the guardianship element of routine activity theory and closely match other scales using the SCS (see Popp, 2012). Response options include yes (coded 1), no (coded 0), and don’t know (coded 0). Don’t know was coded 0 for two reasons: First, if the student was unaware of a security measure, then the effect would likely be similar to the security measure not being present. In addition, a large percentage of the sample due to listwise deletion would be lost if unknown was coded as missing (approximately 1,500 cases). Physical security measures range from 0 (none of these security measures are present) to 8 (all of these measures are present).

Interactionist security measures were captured through five items, including whether students reported they had an adult or friend who care about them, a friend they can talk to, and how much respondents believe school rules are known, fair, or strictly enforced. Each response category ranged from 1 (strongly agree) to 4 (strongly disagree). These items were reverse coded and summed, so that a higher number represents a student’s greater attachment to school (α = .68). While an alpha reliability score of .68 is somewhat below the ideal level, principal components factor analysis verified the construction of this measure.

Involvement in activities was separated into two types, athletic teams and spirit groups in one group with performing arts, academic clubs, student government, performing arts, volunteer clubs, and other clubs included in the second group. Each of these variables was coded yes (1) if a student reported involvement in at least one of these activities and no (0) if they were not involved in any of these activities.

Control Variables

Given that many studies have found significant correlations between race and/or ethnicity and bullying victimization, race was included as a control variable (Carbone-Lopez et al., 2010; Popp, 2012; Wang et al., 2009). Four dummy variables for race were created, including White, Black, Asian, and Other. Other included American Indian, Asian, Hawaiian, and anyone who reported being more than one race. Black was used as the reference category. In addition, Hispanic origin was coded 1, and non-Hispanic origin was coded 0.

Type of school was included as a control variable given that those attending public versus private schools tend to be affected more by bullying victimization (Nolin, Davies, & Chandler, 1996). The school variable was coded 1 for public and 0 for private. Household income was included as a control and ranged from 1 indicating income less than US$5,000 to 11 indicating income more than US$75,000. Age has been found to predict bullying victimization and is thus included as a control variable (Schumann, Craig, & Rosu, 2014; Solberg, Olweus, & Endresen, 2007). Age ranges from 12 to 18 years. Finally, students indicated which month the current school year began. Students varied in how long they attended school before being interviewed, ranging anywhere from 4 months to 10 months before being interviewed. Therefore, a time at risk of being bullied variable was created which indicated the number of months the student attended school before being interviewed.

Analytic Strategy

First, descriptive statistics are provided, including the key dependent and independent variables as well as the control variables. Next, logistic regression is used to analyze the effects of gender, security measures, extracurricular activity involvement, and the controls on bullying victimization. Logistic regression is chosen for analyses because most students reported that they had not experienced any form of bullying. Therefore, the bullying variables are dichotomized to indicate whether any of the types of bullying occur. Odds ratios are used for the interpretations of logistic regression analyses of direct and indirect bullying victimization. Odds ratios were interpreted in the following way: For each unit change in the independent variable, the odds are expected to change by a factor of exp(B), when all other variables are held constant (Long & Freese, 2003).

For each type of bullying victimization (direct and indirect), two models are presented. The first model includes only the key independent variables whereas the second model includes the independent variables as well as the controls. The data were weighted for regression analyses, so that they are representative of the school-aged population of the United States. Adjustments were also taken into account for the stratified cluster design. To compare model fit, the adjusted Wald test is used instead of the likelihood-ratio test because observations are non-independent and not selected at random (Lee & Forthofer, 2006).

Results

Descriptive Statistics

Descriptive statistics for the dependent, independent, and control variables are presented for the unweighted sample in Table 1. The most frequently reported types of direct bullying victimization were being pushed, shoved, or tripped (8.0%) and being threatened with harm (5.1%), while the least frequently reported direct bullying victimizations were being coerced (3.3%) and having property destroyed by another (2.8%). Overall, 12.7% of students experienced at least one type of direct bullying.

Table 1.

Descriptive Statistics.

Variables	n	%/M	SD	Minimum	Maximum
Dependent variables
Direct bullying	5,685	12.68%		0	1
Threatened	5,695	5.11%		0	1
Pushed	5,693	7.97%		0	1
Coerced	5,691	3.29%		0	1
Destroyed property	5,688	2.76%		0	1
Indirect bullying	5,680	25.76%		0	1
Rumors	5,687	18.60%		0	1
Excluded	5,689	5.52%		0	1
Called names	5,696	17.85%		0	1
Independent variables
Male	6,016	50.43%		0	1
Physical security	5,327	4.83	1.46	0	8
Interactionist security	5,641	16.30	2.00	9	20
Sports activities	5,722	43.31%		0	1
Non-sports activities	5,717	49.48%		0	1
Control variables
White	6,016	79.44%		0	1
Black	6,016	12.42%		0	1
Asian	6,016	3.84%		0	1
Other	6,016	4.31%		0	1
Hispanic	6,013	22.43%		0	1
Public school	5,749	92.12%		0	1
Household income	4,770	8.49	2.93	1	11
Age	6,016	14.84	1.93	12	18
Time at risk	5,754	7.20	1.80	4	10

The most frequently reported types of indirect bullying victimization include the spread of rumors (18.6%) and being made fun of or called names (17.9%) while the least frequently reported were being excluded from activities (5.5%). Overall, 25.8% of students experienced at least one type of indirect bullying. In addition, 10.3% experienced at least one type of both direct and indirect bullying while 71.8% did not report either form of bullying.

Second, with regard to the distribution of the independent variables, gender was evenly distributed within the sample. In addition, schools implemented an average of 4.83 security measures. Regarding the interactionist security measures, participants responded affirmatively to the presence of caring adults and friends, knowledge of school rules, fairness of school rules, and enforcement of school rules. For extracurricular activities, 43.3% of students participated either in athletic teams or in spirit groups. In addition, 49.5% of students participated in at least one non-sports-related activity.

Finally, reporting the frequency of the control variables, regarding the racial categories, the majority of students were White (79.4%), and students of Hispanic origin comprised of 22.4% of the sample. Most participants reported attending public schools (92.1%). The average household income fell between US$35,000 and US$49,999. Respondents were 14.8 years of age on average. Finally, participants had attended school an average of 7.2 months before being surveyed.

Multivariate Analyses

As shown in Table 2, Models 1 and 2, interactionist security measures served to decrease the likelihood of direct bullying victimization. In particular, for each unit increase in interactionist security measures, the odds of students experiencing direct bullying victimization decreases by 0.81 times. In addition, as expected, those who participated in non-sports-related activities were more likely to be victims of direct bullying victimization. In particular, the odds of students who are involved in non-sports-related activities being a victim of direct bullying is 1.33 times greater than that for students who are not involved in these activities. Contrary to expectations, gender, physical security measures, and sports-related activities were unrelated to direct bullying victimization.

Table 2.

Logistic Regression of Direct Bullying Victimization on Selected Predictors (N = 4,415).

	Model 1			Model 2
	b	SE	OR	b	SE	OR
Male	0.08	0.09	1.08	0.07	0.10	1.08
Physical security	0.01	0.03	1.01	0.05	0.03	1.05
Interactionist security	−0.21	0.03***	0.81	−0.21	0.03***	0.81
Sports activities	−0.08	0.10	0.92	−0.03	0.10	0.97
Non-sports activities	0.28	0.09**	1.32	0.29	0.10**	1.33
White				0.08	0.16	1.09
Asian				−0.87	0.35*	0.42
Other				0.03	0.27	1.03
Hispanic				−0.37	0.13**	0.69
Public school				0.22	0.20	1.24
Household income				−0.03	0.02	0.97
Age				−0.19	0.03***	0.83
Time at risk				0.01	0.03	1.01
Constant	1.23	0.45	3.41	3.82	0.65***	45.58

Note. Black is the reference category.

p ≤ .05. **p ≤ .01. ***p ≤ .001.

The addition of the control variables significantly improves the fit of the model, F(8, 150) = 6.92, p < .001. Specifically, student characteristics of race, ethnicity, and age show a statistically significant relationship with direct bullying victimization. The analysis indicates that Asian students were 0.42 times less likely to experience direct bullying victimization than African American students. In addition, results indicate that Hispanic students are 0.69 times less likely to experience direct bullying victimization than non-Hispanics. Finally, the results show that age was negatively related to direct bullying victimization. In particular, for every unit increase in age, a student’s risk of direct bullying victimization decreases by a factor of .83.

Logistic regression was also used to predict the likelihood of a student’s indirect bullying victimization. Two models were presented for indirect bullying: The first model shows the main effects of the independent variables, and the second model includes both independent and control variables. Table 3, Models 1 and 2, indicates that as expected, male students were less likely to be indirectly bullied. Specifically, males are 0.63 times less likely to be indirectly bullied than females. As hypothesized, there was not a significant relationship between physical security measures and indirect bullying victimization. Similar to direct bullying, participation in non-sports-related activities increased a student’s likelihood of being indirectly bullied, and interactionist security measures decreased the likelihood of a student’s indirect bullying victimization. In particular, for each unit increase in interactionist security measures, the odds of the students experiencing indirect bullying victimization decreases by 0.87 times. Finally, the odds are 1.6 times higher for being an indirect bully victim for those involved in non-sports compared with those not involved in these activities.

Table 3.

Logistic Regression of Indirect Bullying Victimization on Selected Predictors (n = 4,412).

	Model 1			Model 2
	b	SE	OR	b	SE	OR
Male	−0.45	0.07***	0.64	−0.46	0.07***	0.63
Physical security	−0.02	0.03	0.98	0.00	0.03	1.00
Interactionist security	−0.14	0.02***	0.87	−0.14	0.02***	0.87
Sports activities	−0.02	0.08	0.98	0.00	0.08	1.00
Non-sports activities	0.46	0.07***	1.59	0.47	0.07***	1.60
White				0.25	0.14	1.28
Asian				−0.49	0.28	0.61
Other				0.04	0.21	1.04
Hispanic				−0.55	0.10***	0.58
Public school				0.25	0.14	1.29
Household income				−0.03	0.02	0.97
Age				−0.09	0.02***	0.91
Time at risk				0.05	0.02*	1.05
Constant	1.36	0.35***	3.91	2.22	0.54***	9.16

Note. Black is the reference category.

p ≤ .05. **p ≤ .01. ***p ≤ .001.

The adjusted Wald test indicates that the addition of the control variables significantly improves the fit of the model, F(8, 150) = 6.96, p < .001. The results indicate that Hispanic students were 0.58 times less likely to experience indirect bullying victimization than non-Hispanic students. For age, the results show that for every unit increase in age, a student’s risk of indirect bullying victimization decreases by a factor of .91. Finally, students who attended more months in school were significantly more likely to be victims of indirect bullying. Specifically, for every month increase in school attendance, the student’s risk of indirect bullying victimization increases by 1.05 times.

In sum, the results show that there was not a significant relationship between gender and direct bullying while there was a significant relationship between gender and indirect bullying as expected. Unexpectedly, physical security measures were not significantly related to direct bullying victimization. As expected, physical security measures were not related to indirect bullying victimization. In addition, interactionist security measures significantly decrease the likelihood of both direct and indirect bullying victimization as expected. Results also show that sports-related activities were not significantly related to direct and indirect bullying victimization contrary to expectations, while non-sports-related activities significantly increase the risk of direct and indirect bullying victimization as expected.

Discussion and Conclusion

The purpose of this study was to explore whether a number of important factors such as gender, security measures, and extracurricular activities affect a student’s likelihood of direct or indirect bullying victimization with routine activity and social bond perspectives. Very few studies rely on theoretical frameworks to explain predictors of bullying, and none to our knowledge have explained bullying victimization as a consequence of weak bonds among a U.S. sample. Social bond theory especially provides insight into how interactionist security measures reduce a student’s risk of victimization at school. In addition, routine activity theory provides an explanation as to why the effects of sports and non-sports-related activities on victimization differ. Future research should examine the relationship between bonds and victimization longitudinally given that those who experience bullying have weaker bonds (Popp & Peguero, 2012). In addition, longitudinal research is needed to assess the time order and overlap between bullying perpetration and victimization. It is likely that weakened social bonds increase bullying perpetration and victimization, which in turn further weakens social bonds.

It was hypothesized that females would be more likely to be a victim of indirect bullying whereas males would be more likely to be a victim of direct bullying. Similar to previous research (Bradshaw et al., 2009; Carbone-Lopez et al., 2010; Felix et al., 2009; Richard et al., 2012; Wang et al., 2009), this study shows that females were significantly more likely to be a victim of indirect bullying than males. However, contrary to expectations, there were no significant gender differences in direct bullying, which replicates previous findings (Peskin et al., 2006). This finding may have occurred because males underreport their direct bullying victimization. Specifically, males may not want to be seen as weak due to gendered expectations of what it means to be a “man” such as powerful and strong (Padavic & Reskin, 2002).

Contrary to expectations, physical security measures did not affect direct bullying victimization. But as expected, these measures were unrelated to indirect bullying victimization. These findings are similar to previous research that has found that physical security measures were ineffective in reducing victimization at school (Burrow & Apel, 2008; Schreck et al., 2003). While these findings seem to contradict the importance of capable guardians, the amount and implementation of physical security measures require more attention. For instance, the number of security cameras and security guards or adults supervising hallways might be important in terms of reducing victimization based on the school size. One security camera or security guard cannot reduce bullying victimization in highly populated schools. In this study, it is not possible to know the school size as well as how many security measures exist in those schools. In addition, many students did not know whether measures were in place. It may be when students did not know if a measure was in place, they assumed that it was not in place and therefore, potential motivated bullies felt that they were free to victimize other students given the assumed lack of capable guardianship. Given these limitations, future research should examine more closely the size of the school, how many security measures are in place, and how the knowledge of these measures affects bullying behavior.

However, it was hypothesized that interactionist security measures would reduce the likelihood of both direct and indirect bullying victimization. The results point out that interactionist security measures significantly reduce the risk of both direct and indirect bullying. These findings replicate previous research, which linked the effect of interactionist security measures in reducing the risk of victimization at school (Time & Payne, 2008). They also support social bond theory, which proposes the importance of individual bonds in preventing criminal involvement and victimization (Cunningham, 2007). These findings are encouraging from a policy standpoint, in that school administrators can reduce bullying victimization by focusing on building relationships between teachers and students, and encouraging fair and consistent rules in the school rather than spending money on hiring security guards and purchasing equipment such as metal detectors.

In addition, it was hypothesized that sports-related extracurricular activities would decrease the likelihood of both direct and indirect bullying victimization. Contrary to expectations and previous findings that sports-related activities reduce victimization risk (Peguero, 2009, 2013), the results here indicate that sports-related activities were unrelated to the likelihood of direct or indirect bullying victimization. It is important to note that involvement in sports did not increase the likelihood of being a victim. However, we found as expected that those who participated in non-sports-related extracurricular activities were more likely to be a victim of direct and indirect bullying. These findings are consistent with others who find that classroom-related activities put students at an increased risk of victimization (Peguero, 2009; Popp, 2012). These findings may be explained through two possible mechanisms. First, those who attend non-sports-related activities may be perceived as a weaker target for motivated offenders (Peguero, 2008), which increases their risk of bullying victimization. Second, some classroom-related activities occur without the supervision of adults whereas sports may include coaches as capable guardians, which will reduce the opportunity for bullying in these contexts (Popp, 2012).

Future studies should also examine the role of race and ethnicity in bullying victimization. In this study, Asians were less likely to be directly bullied than African American students, and Hispanic students were less likely to be directly and indirectly bullied than non-Hispanic students. Previous findings on the role of race and ethnicity have varied as to which groups are more vulnerable to bullying victimization (Carbone-Lopez et al., 2010; Felix et al., 2009; Popp, 2012). On one hand, Asian and Hispanic students may be targeted for bullying based on their race or ethnicity. On the other hand, being part of a distinct cultural group may serve as a protective factor against bullying victimization. The results from this study support this possibility. Future studies should examine under what conditions being part of a racial/ethnic group serves as a protective factor to bullying victimization.

While this study has made numerous contributions to the literature, it is important to note a few limitations. One of the important limitations of the SCS data is the measurement of bullying victimization. Specifically, the measure may not capture all of the elements of the definition of bullying, which includes an imbalance of power, a repeated occurrence, and an intentional act. While it is likely that the acts captured in this survey are intentional, it is impossible to know whether the bullying involved an imbalance of power given that students only reported whether they were bullied by another student. In addition, it is not possible to look at the frequency of bullying by type of bullying because students were only asked how prevalent the bullying was overall. Supplemental analyses (results available upon request) demonstrate that the substantive patterns remain the same with frequency of being bullied as the dependent variable. Future studies should incorporate a more comprehensive measure of bullying victimization. While outside the scope of this study, future research should further explore the causes and consequences of cyberbullying compared with traditional forms of bullying (Payne & Hutzell, 2017).

Another possible limitation is that students may misinterpret or underreport answers to survey questions. For instance, students who participate in athletic teams may not consider shoving or pushing or teasing as a bullying behavior because these behaviors might be part of the sports culture itself. For example, Endresen and Olweus (2005) showed that involvement in sports increases levels of violence. Therefore, those who are involved in sports may not perceive some of these behaviors as bullying compared with those who are not involved in sports or are involved in other classroom-related activities or school clubs. In addition, as shown in this study, a substantial number of students did not know which security measures were in place. While a response of don’t know was treated as the same as no, the measure was not in place, future studies should examine how students who are unsure of the presence of physical security measures experience bullying victimization.

In addition, because the data focus only on victims’ experiences, it is not possible to know who is a victim of bullying and also who is a bully. Research on school shooting incidents show that most of the shooters were bullies and victims (Anderson et al., 2001), and studies show that bullying involvement causes several detrimental problems such as lower self-esteem, loneliness, poorer psychological and social adjustment, higher risk of depression, and suicide ideation (Olweus, 1997; Turner et al., 2013; Vanderbilt & Augustyn, 2010). Therefore, it is important to know which students also bully to create effective strategies for reducing bullying behavior.

This study has significant implications for bullying prevention programs. First of all, to reduce bullying, schools should provide educational training for teachers as well as students to increase awareness of bullying. Students should be able to understand bullying behaviors and how to respond to them. These training programs should also help students improve social-emotional skills to support them in building healthy peer relationships. In addition, teachers should be able to identify bullying and intervene to prevent further victimization. As interactionist security measures were found to be significant in reducing bullying victimization, increasing adult awareness and supervision and enhancing the quality of interpersonal relations between juveniles and adults should help reducing bullying victimization. Interventions can be strengthened if teachers and administrators pay special attention to finding different ways of improving students’ bonds with school. By improving relationships among students, teachers, and school administrators, and creating consistent and clear norms, which everyone agrees on (Payne et al., 2003), schools can reduce direct and indirect bullying victimization. Teachers and administrators should especially focus on students involved in non-sports-related activities given their greater risk of victimization. In conclusion, our results confirmed the important roles of social bonds and routine activities in reducing bullying victimization, which is important to consider when examining or planning interventions on school bullying.

Footnotes

Acknowledgements

The authors offer thanks to the Republic of Turkey Ministry of National Education for the scholarship which supported Hatice Cecen-Celik during her graduate studies. The authors offer appreciation to the Bureau of Justice Statistics and Dr. Lynn Addington for the opportunity for Shelley Keith to learn about the SCS data in the Quantitative Analysis of Crime and Criminal Justice Workshop.

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Hatice Cecen-Celik completed her master’s degree in sociology at Mississippi State University in 2014. She is currently pursuing a PhD in sociology at the University of Leicester. Her research interests are in the areas of bullying, victimization, culture and victimization, and qualitative methodology.

Shelley Keith is an associate professor of sociology at Mississippi State University. Her research interests are in the areas of criminological theory, juvenile delinquency, juvenile justice, gender, race, social class, and crime, restorative justice, and the social psychological causes of crime.

References

Anderson

Kaufman

Simon

T. R.

Barrios

Paulozzi

Ryan

, . . . School-Associated Violent Deaths Study Group. (2001). School-associated violent deaths in the United States, 1994-1999. The Journal of the American Medical Association, 286, 2695-2702.

Bjorkqvist

Lagerspetz

K. M. J.

Kaukiainen

(1992). Do girls manipulate and boys fight? Developmental trends in regard to direct and indirect aggression. Aggressive Behavior, 18, 117-127.

Blosnich

Bossarte

(2011). Low-Level violence in schools: Is there an association between school safety measures and peer victimization? Journal of School Health, 81, 107-113.

Bradshaw

C. P.

Sawyer

A. L.

O’Brennan

L. M.

(2009). A social disorganization perspective on bullying-related attitudes and behaviors: The influence of school context. American Journal of Community Psychology, 43, 204-220.

Burrow

J. D.

Apel

(2008). Youth behavior, school structure, and student risk of victimization. Justice Quarterly, 25, 349-380.

Carbone-Lopez

Esbensen

F. A.

Brick

B. T.

(2010). Correlates and consequences of peer victimization: Gender differences in direct and indirect forms of bullying. Youth Violence and Juvenile Justice, 8, 332-350.

Catalano

R. F.

Oesterle

Fleming

C. B.

Hawkins

J. D.

(2004). The importance of bonding to school for healthy development: Findings from the Social Development Research Group. Journal of School Health, 74, 252-261.

Chan

H. C. O.

Chui

W. H.

(2013). Social bonds and school bullying: A study of Macanese male adolescents on bullying perpetration and peer victimization. Child Youth Care Forum, 42, 599-616.

Clark

S. L.

(2011). Factors related to school violence victimization: The role of extracurricular activities (Doctoral dissertation). Available from University of Iowa Theses and Dissertation database. Retrieved from http://ir.uiowa.edu/etd/2687/

10.

Cohen

L. E.

Felson

(1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44, 588-608.

11.

Cunningham

N. J.

(2007). Level of bonding to school and perception of the school environment by bullies, victims, and bully victims. The Journal of Early Adolescence, 27, 457-478.

12.

Darling

Caldwell

L. L.

Smith

(2005). Participation in school-based extracurricular activities and adolescent adjustment. Journal of Leisure Research, 37, 51-76.

13.

Eccles

J. S.

Barber

B. L.

(1999). Student council, volunteering, basketball, or marching band what kind of extracurricular involvement matters? Journal of Adolescent Research, 14, 10-43.

14.

Endresen

I. M.

Olweus

(2005). Participation in power sports and antisocial involvement in preadolescent and adolescent boys. Journal of Child Psychology and Psychiatry, 46, 468-478.

15.

Felix

E. D.

Furlong

M. J.

Austin

(2009). A cluster analytic investigation of school violence victimization among diverse students. Journal of Interpersonal Violence, 24, 1673-1695.

16.

Felson

(2002). Crime and everyday life. Thousand Oaks, CA: Sage.

17.

Gregory

Cornell

Fan

Sheras

Shih

T. H.

Huang

(2010). Authoritative school discipline: High school practices associated with lower bullying and victimization. Journal of Educational Psychology, 102, 483-496.

18.

Higgins

G. E.

Khey

D. N.

Dawson-Edwards

B. C.

Marcum

C. D.

(2012). Examining the link between being a victim of bullying and delinquency trajectories among an African American sample. International Criminal Justice Review, 22, 110-122.

19.

Hirschi

(1969). Causes of delinquency. Berkeley: University of California Press.

20.

Huebner

A. J.

Betts

S. C.

(2002). Exploring the utility of social control theory for youth development issues of attachment, involvement, and gender. Youth and Society, 34, 123-145.

21.

Hutzell

K. L.

Payne

A. A.

(2012). The impact of bullying victimization on school avoidance. Youth Violence and Juvenile Justice, 10, 370-385.

22.

Jenkins

P. H.

(1997). School delinquency and the school social bond. Journal of Research in Crime & Delinquency, 34, 337-367.

23.

Jeong

Kwak

D. H.

Moon

San Miguel

(2013). Predicting school bullying victimization: Focusing on individual and school environmental/security factors. Journal of Criminology, 2013. Article ID 401301. doi:10.1155/2013/401301.

24.

Jeralds

L. M.

(2011). Bullying victimization, target suitability, and guardianship: A routine activities approach (Doctoral dissertation). Department of Sociology and Criminology, University of North Carolina, Wilmington.

25.

Laundra

K. H.

Kiger

Bahr

S. J.

(2002). A social development model of serious delinquency: Examining gender differences. Journal of Primary Prevention, 22, 389-407.

26.

Lee

E. S.

Forthofer

R. N.

(2006). Analyzing complex survey data. Thousand Oaks, CA: Sage.

27.

Lehman

(2014). Gender differences in bullying victimization: The role of academics and school context. Sociological Spectrum, 34, 549-570.

28.

Long

J. S.

Freese

(2003). Regression models for categorical dependent variables using Stata. College Station, TX: Stata Press.

29.

Nansel

T. R.

Overpeck

M. D.

Haynie

D. L.

Ruan

W. J.

Scheidt

P. C.

(2003). Relationships between bullying and violence among US youth. Archives of Pediatrics and Adolescent Medicine, 157, 348-353.

30.

Nansel

T. R.

Overpeck

M. D.

Pilla

R. S.

Ruan

W. J.

Simons-Morton

Scheidt

(2001). Bullying behaviors among US youth: Prevalence and association with psychosocial adjustment. The Journal of the American Medical Association, 285, 2094-2100.

31.

Nolin

M. J.

Davies

Chandler

(1996). Student victimization at school. Journal of School Health, 66, 216-222.

32.

Olweus

(1997). Bully/victim problems in school: Facts and intervention. European Journal of Psychology of Education, 12, 495-510.

33.

Olweus

(2003). A profile of bullying at school. Educational Leadership, 60, 12-17.

34.

Padavic

Reskin

(2002). Women and men at work. Thousand Oaks, CA: Sage.

35.

Payne

A. A.

Gottfredson

D. C.

Gottfredson

G. D.

(2003). Schools as communities: The relationships among communal school organization, student bonding, and school disorder. Criminology, 41, 749-778.

36.

Payne

A. A.

Hutzell

K. L.

(2017). Old wine, new bottle? Comparing interpersonal bullying and cyberbullying victimization. Youth & Society, 49, 1149-1178. doi:10.1177/0044118X15617401

37.

Peguero

A. A.

(2008). Bullying victimization and extracurricular activity. Journal of School Violence, 7, 71-85.

38.

Peguero

A. A.

(2009). Opportunity, involvement, and student exposure to school violence. Youth Violence and Juvenile Justice, 7, 299-312.

39.

Peguero

A. A.

(2013). An adolescent victimization immigrant paradox? School-based routines, lifestyles, and victimization across immigration generations. Journal of Youth and Adolescence, 42, 1759-1773.

40.

Peskin

M. F.

Tortolero

S. R.

Markham

C. M.

(2006). Bullying and victimization among Black and Hispanic adolescents. Adolescence, 41, 467-484.

41.

Popp

A. M.

(2012). The effects of exposure, proximity, and capable guardians on the risk of bullying victimization. Youth Violence and Juvenile Justice, 10, 315-332.

42.

Popp

A. M.

Peguero

A. A.

(2011). Routine activities and victimization at school: The significance of gender. Journal of Interpersonal Violence, 26, 2413-2436.

43.

Popp

A. M.

Peguero

A. A.

(2012). Social bonds and the role of school-based victimization. Journal of Interpersonal Violence, 27, 3366-3388.

44.

Richard

J. F.

Schneider

B. H.

Mallet

(2012). Revisiting the whole-school approach to bullying: Really looking at the whole school. School Psychology International, 33, 263-284.

45.

Rigby

(2004). Addressing bullying in schools theoretical perspectives and their implications. School Psychology International, 25, 287-300.

46.

Ringrose

Renold

(2010). Normative cruelties and gender deviants: The performative effects of bully discourses for girls and boys in school. British Educational Research Journal, 36, 573-596.

47.

Sawyer

A. L.

Bradshaw

C. P.

O’Brennan

L. M.

(2008). Examining ethnic, gender, and developmental differences in the way children report being a victim of “bullying” on self-report measures. Journal of Adolescent Health, 43, 106-114.

48.

Schreck

C. J.

Miller

J. M.

Gibson

C. L.

(2003). Trouble in the school yard: A study of the risk factors of victimization at school. Crime & Delinquency, 49, 460-484.

49.

Schumann

Craig

Rosu

(2014). Power differentials in bullying: Individuals in a community context. Journal of Interpersonal Violence, 29, 846-865.

50.

Solberg

M. E.

Olweus

Endresen

I. M.

(2007). Bullies and victims at school: Are they the same pupils? British Journal of Educational Psychology, 77, 441-464.

51.

Time

Payne

B. K.

(2008). School violence prevention measures: School officials’ attitudes about various strategies. Journal of Criminal Justice, 36, 301-306.

52.

Turner

M. G.

Exum

M. L.

Brame

Holt

T. J.

(2013). Bullying victimization and adolescent mental health: General and typological effects across sex. Journal of Criminal Justice, 41, 53-59.

53.

U.S. Department of Education. (2011). Student reports of bullying and cyber-bullying: Results From the 2009 School Crime Supplement to National Crime Victimization Survey. Retrieved from http://nces.ed.gov/pubs2011/2011336.pdf

54.

U.S. Department of Education. (2013). Student reports of bullying and cyber-bullying: Results from the 2011 School Crime Supplement to National Crime Victimization Survey. Retrieved from http://nces.ed.gov/pubs2013/2013329.pdf

55.

U.S. Department of Justice, Office of Justice Programs, Bureau of Justice. (2011). National Crime Victimization Survey: School Crime Supplement, 2011. doi:10.3886/ICPSR33081.v1

56.

Vanderbilt

Augustyn

(2010). The effects of bullying. Pediatrics and Child Health, 20, 315-320.

57.

Wang

Iannotti

R. J.

Nansel

T. R.

(2009). School bullying among adolescents in the United States: Physical, verbal, relational, and cyber. Journal of Adolescent Health, 45, 368-375.

58.

Welsh

W. N.

(2001). Effects of student and school factors on five measures of school disorder. Justice Quarterly, 18, 911-994.