Are Sexual Minorities More at Risk? Bullying Victimization Among Lesbian,Gay,Bisexual,and Questioning Youth

Abstract

Bullying has garnered the attention of researchers and policy makers alike, because of various negative physical, mental, and educational outcomes that stem from these experiences. Certain youth are more at risk for bullying victimization (ASPA, 2012). Thus, research highlighting and addressing these experiences is crucial to provide safer environments for youth. This study utilizes the 2013 Youth Risk Behavior Surveillance System (YRBSS) data to investigate whether or not experiences of victimization differ for lesbian, gay, bisexual, and questioning (LGBQ) youth. Drawing from a sample of 12,642 9th through 12th grade youth, this study investigates two primary areas: (a) the prevalence of traditional bullying, electronic bullying, and homophobic bullying victimizations among LGBQ youth, and (b) the interaction of sexual orientation and gender with traditional bullying, electronic bullying, and homophobic bullying victimizations. Results suggest that LGBQ youth experience all types of bullying victimization at higher rates than heterosexual youth. Results also highlight the importance of the interaction of sexual orientation and gender in bullying victimization. Findings reveal that LGBQ females, LGBQ males, and heterosexual females experience each type of victimization at higher rates than heterosexual males. Findings confirm that disparities exist in bullying victimization among LGBQ youth, and thus cannot be ignored in schools. School policies must explicitly acknowledge and address how sexual orientation and gender matter within the constructs of youth violence if they wish to create safer learning environments for youth.

Keywords

bullying youth violence GLBT

Introduction

Bullying is a form of youth violence that comprises a multifaceted set of behaviors, and the reasons why children and adolescents bully one another are complex (Espelage & Swearer, 2008). The Centers for Disease Control and Prevention (CDC) defines bullying as “any unwanted aggressive behavior(s) by another youth or group of youths who are not siblings or current dating partners that involves an observed or perceived power imbalance and is repeated multiple times or is highly likely to be repeated” (Gladden, Vivolo-Kantor, Hamburger, & Lumpkin, 2014). Bullying occurs directly (communicated to the target) and indirectly (not directly communicated to the target) through a variety of physical, verbal, and relational means. Overall, about 30% of adolescents report being bullied annually, and as many as 23% report being bullied on a weekly or daily basis (Craig et al., 2009; Lumeng et al., 2010). The CDC identifies bullying as a significant public health concern worldwide, because of its negative effects on physical, mental, and emotional health (David-Ferdon & Simon, 2014). It has been linked to behavioral disorders, poor educational outcomes, as well as increased involvement in crime and substance use, and thus has become a primary concern for researchers and policy makers alike.

What makes bullying behavior uniquely detrimental is that it encompasses a very clear asymmetric power imbalance favoring the perpetrator (Olweus, 1993). Thus, understanding why and among whom bullying is occurring is crucial. Sexual minority youth¹—those who identify as gay, lesbian, or bisexual or who have sexual contact with persons of the same or both sexes (CDC, 2016)—are among those most at risk for bullying victimization. The term sexual minority is employed as an umbrella term, and for the purposes of this study is used as the broadest form of such. In contrast, there are many times throughout the study where the acronym for the specific identities of interest is used. According to the 2013 National School Climate Survey, 50% of lesbian, gay, bisexual, and transgender (LGBT) youth, in comparison with only 9% of heterosexual youth, experienced some form of violence while at school, and nearly twice as many LGBT youth experienced bullying in particular (Kosciw, Greytak, Palmer, & Boesen, 2014). Overall, LGBT youth are at increased risk of all types of bullying, including physical, relational, electronic, and homophobic bullying (McGuire, Dixon, & Russell, 2009, as cited in Cianciotto & Cahill, 2012).

Studies find that victimization carries with it significant health consequences, and sexual minority youth are at increased risk (Russell, Everett, Rosario, & Birkett, 2014). This research utilizes data from the 2013 National Youth Risk Behavior Survey (YRBS) to investigate three different types of bullying victimization and whether sexual orientation and gender influence the risk for such types of victimization. Findings indicate that lesbian, gay, bisexual, and questioning (LGBQ) youth are at significantly higher risk for each type of bullying victimization, and the interaction of sexual orientation and gender also matters. Finally, this study discusses the implications for these findings within school policy that appropriately addresses protections against bullying of sexual minority youth.

Literature Review

Just over 25 years ago, the Gay, Lesbian and Straight Education Network (GLSEN) began research that focused on the ways in which anti-LGBT bias and violence was affecting the lives of sexual minority youth. Research highlights that the prevalence of bullying victimizations are higher among sexual minority youth. For example, the 2007 National School Climate Survey, as well as the Massachusetts Youth Risk Behavior Survey found that about 40% to 42% of sexual minority youth in comparison with about 21% of heterosexual youth experienced bullying at school (Kosciw, Diaz, & Greytak, 2007; Massachusetts Department of Education, 2004). Another study found that lesbian, gay, and bisexual (LGB) students were significantly more likely to experience physical bullying (39% vs. 25%) and relational bullying (54% vs. 33%) than their heterosexual peers (McGuire et al., 2009). In addition, some studies have specifically measured whether sexual minority youth are being targeted as a direct result of their sexual orientation or gender identity, and find that unfortunately high numbers of youth report witnessing or experiencing forms of homophobic bullying. Homophobic bullying is, “behavior or language which makes a young person feel unwelcomed or marginalized because of their actual or perceived sexual orientation” (The Rainbow Project: Homophobic Bullying, 2012). A study by D’Augelli, Grossman, and Starks (2006) found that 78% of LGB and gender atypical youth reported experiencing verbal victimization, while 11% reported physical victimization, and as high as 9% reported sexual victimization. For the sample, the average age of victimization was 13 years old, with some types of victimization happening as young as 6. Furthermore, the 2013 National School Climate Survey found that, among LGBT students, 74.1% reported being verbally harassed, 36.2% reported being physically harassed, and 49.9% reported being electronically harassed, because of their perceived sexual orientation.

While differences exist in bullying victimization rates in LGBT students, research also finds important gender differences as well. First, several studies find that boys are more likely than girls to be involved in bullying, both as bullies and bully-victims (Nansel et al., 2001; Scheithauer, Hayer, Petermann, & Jugert, 2006; Viljoen, O’Neill, & Sidhu, 2005). Furthermore, other studies found that boys were more likely to be involved in physical and verbal direct forms of bullying, while girls were more likely to be involved in indirect (or relational) forms of bullying (Carbone-Lopez, Esbensen, & Brick, 2010; Scheithauer et al., 2006). For example, one nationally representative study found that boys experienced more physical bullying than girls, and girls experienced more bullying via rumors and sexual comments than boys (Nansel et al., 2001).

In recent years, bullying has taken on an additional means of perpetration through technological devices and forums. Cyberbullying is defined as, “willful and repeated harm inflicted through the use of computers, cell phones, and other electronic devices” (Hinduja & Patchin, 2008, p. 5). Cyberbullying differs from traditional bullying in that it can occur anywhere and at all times, often rendering the victims increasingly vulnerable (Hinduja & Patchin, 2008). As outlined above, sexual minorities are more vulnerable to cyberbullying; evidence for gender differences in cyberbullying, however, is mixed. For example, some research finds that girls may actually be more involved in cyberbullying than traditional forms of bullying, because of their propensity for relational forms of violence (Hinduja & Patchin, 2008; Kowalski & Limber, 2007). In contrast, other studies find mirroring trends between traditional and cyberbullying, where boys committed and experienced more cyberbullying than girls (Erdur-Baker, 2010; Sincek, 2014).

Obtaining state and national secondary data that adequately measure sexual orientation items has proven difficult and even invisible until recent years, especially for youth. According to the report formulated by the Institute of Medicine (2011), one of the greatest challenges in describing the health-related needs of LGBTQ people is the overall lack of population-based data, where only a limited number of publicly funded probability sample studies actually include such measures. For example, it wasn’t until 2013 that the Department of Education finally announced its initiatives to prioritize data collection specifically focusing on LGBT students in schools (Slater, 2013). Stemming from this initiative, The Civil Rights Data Collection (CRDC), The High School Longitudinal Study, and The Bureau of Justice Statistics (BJS), as well as versions of the YRBS questionnaires aim to aid in understanding the experiences of LGBT youth in America’s schools.

A variety of studies have used the YRBS data to focus on the experiences of youth in terms of victimization, fighting and weapon carrying, dating violence, truancy, substance use, mental health and suicidality, as well as sexual risk behaviors (DuRant, Krowchuck, & Sinai, 1998; Faulkner & Cranston, 1998; Garofalo, Wolf, Kessel, Palfrey, & DuRant, 1998; Howard, Wang, & Yan, 2007; Russell et al., 2014). Few studies, however, have used the data to examine the interaction of sexual orientation and gender. The current study is the most recent to combine multistate level data from the 2013 YRBS, to examine bullying victimizations, specifically, in LGBQ youth.

Current Study

The CDC identifies bullying as a significant public health concern worldwide (David-Ferdon & Simon, 2014). Bullying victimizations and their detriments have become a major topic of concern to researchers and policy makers alike. Stemming from the need for more LGBT inclusive studies, the CRDC, the High School Longitudinal Study, and the BJS, as well as the 2015 version of the YRBS questionnaires are to aid in understanding, specifically, the experiences of LGBTQ youth in America’s schools. To investigate this issue more in depth, three primary research questions emerge. First, what are the distinctions between LGBQ and heterosexual youth, in terms of the prevalence of bullying victimization? Second, does identifying as LGBQ influence the likelihood of bullying victimization? Third, does the interaction of gender and sexual orientation influence the likelihood of bullying victimization?

Method

Sample

This project utilized data from the 2013 Youth Risk Behavior Surveillance System (YRBSS) which, to date, has the most state, district, and territorial participation in asking at least one of two questions pertaining to sexual orientation. Developed in 1990 by the CDC, the YRBSS is used to monitor health risk behaviors that contribute to causes of death, disability, and social problems among youth in the United States. The sampling frame for the 2013 national YRBS included all 50 states and the District of Columbia. Data were collected through self-report questionnaires distributed within classrooms, systematically chosen through equal probability sampling within the 193 schools in the sample. For the purposes of this study, all states that did not include the sexual orientation question were eliminated. Four states were selected that adequately included all variables of interest: Connecticut, Florida, Illinois, and North Carolina. The total sample for the analysis included 12,642 (1,428 LGBQ and 11,214 heterosexual) public school students.

Sexual Orientation

According to the Sexual Minority Assessment Research Team (2009), sexual orientation encompasses three different conceptual dimensions: (a) self-identification—how one identifies their own sexual orientation, (b) sexual behavior—the sex of the sex partners, and (c) sexual attraction—the sex or gender of individuals that someone feels attracted to. In this study, sexual orientation was used as a measure of self-identification, in which respondents were asked, “Which of the following best describes you?” Response items ranged from (1) heterosexual (straight), (2) gay or lesbian, (3) bisexual, and (4) not sure.

Bullying Victimization

In most youth violence research, the predominant method for assessing involvement in bullying is self-report (Vivolo-Kantor, Martell, Holland, & Westby, 2014). The 2013 YRBS defined bullying as,

. . . when 1 or more students tease, threaten, spread rumors about, hit, shove, or hurt another student over and over again. It is not bullying when 2 students of about the same strength or power argue or fight or tease each other in a friendly way. (Kann et al., 2014, p. 7)

Thus, Traditional Bullying was operationalized from the question, “During the past 12 months, have you ever been bullied on school property?” Response items were dichotomized as (0) no and (1) yes. Electronic Bullying was operationalized from the question, “During the past 12 months, have you ever been electronically bullied?” Response items were dichotomized as (0) no and (1) yes. Sexual Orientation Bullying was operationalized from the question, “During the past 12 months, have you ever been the victim of teasing or name calling because someone thought you were gay, lesbian, or bisexual?” Response items were dichotomized as (0) no and (1) yes.

Controls

Research demonstrates that certain student characteristics are associated with bullying victimization. Student characteristics, such as gender (Espelage, Bosworth, & Simon, 2000; Seals & Young, 2003), age (Espelage & Horne, 2008), race and ethnicity (Hong & Espelage, 2012), weight (Farhart, Iannotti, & Simons-Morton, 2010; Wang, Iannotti, & Luk, 2010), misbehavior (Peguero, 2008), and geographic location (Guerra & Williams, 2010), are associated with differences in victimization, and therefore, included as control variables in the study. Grade was operationalized from the following question: “In what grade are you?” Responses ranged from (9) ninth, (10) 10th, (11) 11th, (12) 12th. White was dichotomized from the following question: “What is your race?” Responses ranged from (0) not White and (1) White. Black was dichotomized from the following question: “What is your race?” Responses ranged from (0) not Black and (1) Black. Latino was dichotomized from the following question: “What is your race?” Responses ranged from (0) not Latino and (1) Latino. Asian or Pacific Islander was dichotomized from the following question: “What is your race?” Responses ranged from (0) not Asian or Pacific Islander (1) Asian or Pacific Islander. Other race/ethnicity was dichotomized from the following question: “What is your race?” Responses ranged from (0) not Other and (1) Other. Florida was measured using the state identifier. Responses were dichotomized as (0) not Florida and (1) Florida. Illinois was measured using the state identifier. Responses were dichotomized as (0) not Illinois and (1) Illinois. North Carolina was measured using the state identifier. Responses were dichotomized as (0) not North Carolina and (1) North Carolina. Weight was comprised from the following question: “How do you describe your weight?” Responses ranged from (1) underweight, (2) average weight, and (3) overweight. Misbehavior was operationalized from the following questions: “During the past 30 days, on how many days did you carry a weapon such as a gun, knife, or club on school property?” and “During the past 12 months, how many times were you in a physical fight?” Responses ranged from (0) no/no; (1) either/or; (2) yes/yes.

Analytic Strategy

Research suggests that bullying occurs more often to those who identify as a sexual minority. This project explores different types of bullying victimization in the lives of LGBQ youth, as well as the interactions between an individual’s gender and sexual orientation. Binary logistic regression predicts categorical outcomes based on predictor variables (Field, 2009), and thus is utilized to estimate the probability of bullying victimization based on an individual’s gender and sexual orientation.

The analyses proceed in several steps. Table 1 presents a split sample comparison of descriptive statistics among LGBQ and heterosexual youth. Table 2 presents logistic regression results of sexual orientation, sex, and traditional bullying victimization. In Model 1 of Table 2, traditional bullying is regressed on LGBQ youth, gender, grade, race and ethnicity, weight, misbehavior, and geographic location. To understand the role of both gender and sexual orientation on traditional bullying victimization, interactions by gender and sexual orientation are presented in Model 2 of Table 2. Similar analyses are presented for electronic bullying in Models 3 and 4 of Table 3, and sexual orientation bullying in Models 5 and 6 of Table 4.

Table 1.

Descriptive Statistics for Sexual Minority and Heterosexual Youth.

	Sexual Minority			Heterosexual
	n	M	SD	n	M	SD
Victimization
Traditional bullying	1,428	0.32	0.466	11,214	0.16	0.369*
Electronic bullying	1,428	0.26	0.421	11,214	0.12	0.327*
Sexual orientation bullying	1,428	0.33	0.470	11,214	0.06	0.232*
Controls
Female	951	0.67	0.472	5,543	0.49	0.5*
Grade	1,428	10.36	1.09	11,214	10.4	1.09
Black	279	0.20	0.397	2,018	0.18	0.384
Latino	402	0.28	0.450	2,953	0.26	0.440
Asian or Pacific Islander	63	0.04	0.205	435	0.04	0.193
Other	173	0.12	0.326	811	0.07	0.259*
Weight	1,428	2.18	0.740	11,214	2.14	0.644*
Misbehavior	1,428	0.49	0.606	11,214	0.30	0.519*
Florida	612	0.43	0.495	5,131	0.46	0.498*
Illinois	416	0.29	0.297	2,747	0.12	0.326*
North Carolina	140	0.10	0.297	1,354	0.12	0.326*

Note. Levene’s Test for equality of variances indicates differences between the variances in sexual minority and heterosexual populations.

p ≤ .001.

Table 2.

Logistic Regressions of Traditional Bullying Victimization of Sexual Minority Youth.

	Model 1			Model 2
	β	Exp(B)	SE	β	Exp(B)	SE
Sexual minorities	0.701	2.017***	0.067	—	—	—
Sexual minority females	—	—	—	1.168	3.217***	0.084
Heterosexual females	—	—	—	0.578	1.782***	0.056
Sexual minority males	—	—	—	0.927	2.526***	0.113
Controls
Female	0.529	1.698***	0.052	—	—	—
Grade	−0.203	0.816***	0.022	−0.204	0.815***	0.022
Black	−0.659	0.447***	0.106	−0.654	0.449***	0.106
Latino	−0.269	0.661*	0.096	−0.268	0.661***	0.096
Asian or Pacific Islander	−0.103	0.78	0.149	−0.115	0.770*	0.149
Other	−0.146	0.864	0.088	−0.147	0.863	0.089
Weight	0.106	1.112*	0.037	0.108	1.114*	0.037
Misbehavior	0.653	1.921***	0.043	0.655	1.925***	0.043
Florida	−0.325	0.723***	0.067	−0.324	0.723***	0.067
Illinois	−0.063	0.939	0.073	−0.063	0.939	0.073
North Carolina	−0.016	0.984	0.086	−0.016	0.984	0.087
Constant	0.122	1.13	0.252	0.101	1.107	0.252
Nagelkerke R		.092			.093
Log likelihood		11,048.708			11,042.893
χ²		722.265			728.079

p ≤ .05, ***p ≤ .001.

Table 3.

Logistic Regressions of Electronic Bullying Victimization of Sexual Minority Youth.

	Model 3			Model 4
	β	Exp(B)	SE	β	Exp(B)	SE
Sexual minorities	0.687	1.988***	0.072	—	—	—
Sexual minority females	—	—	—	1.645	5.183***	0.093
Heterosexual females	—	—	—	1.180	3.254***	0.067
Sexual minority males	—	—	—	1.224	3.401***	0.125
Controls
Female	1.055	2.873***	0.062	—	—	—
Grade	−0.065	0.938*	0.025	−0.067	0.935*	0.025
Black	−0.711	0.416***	0.119	−0.699	0.419***	0.119
Latino	−0.373	0.583***	0.107	−0.37	0.582***	0.107
Asian or Pacific Islander	−0.288	0.635*	0.175	−0.315	0.615*	0.175
Other	−0.167	0.847	0.098	−0.17	0.843	0.098
Weight	−0.004	0.996	0.041	0.001	1.001	0.041
Misbehavior	0.807	2.241***	0.048	0.813	2.254***	0.048
Florida	−0.367	0.693***	0.074	−0.364	0.695***	0.074
Illinois	−0.071	0.931	0.08	−0.071	0.931	0.08
North Carolina	−0.311	0.733*	0.101	−0.309	0.734***	0.101
Constant	−1.689	0.185***	0.283	−1.756	0.173***	0.284
Nagelkerke R		.116			.119
Log likelihood		9,157.308			9,132.96
χ²		823.721			848.069

p ≤ .05, ***p ≤ .001.

Table 4.

Logistic Regressions of Sexual Orientation Bullying Victimization of Sexual Minority Youth.

	Model 3			Model 4
	β	Exp(B)	SE	β	Exp(B)	SE
Sexual minorities	2.153	8.615***	0.076	—	—	—
Sexual minority females	—	—	—	2.045	7.727***	0.093
Heterosexual females	—	—	—	−0.205	0.814*	0.087
Sexual minority males	—	—	—	2.015	7.504***	0.117
Controls
Female	−0.132	0.876	0.073	—	—	—
Grade	−0.179	0.836***	0.032	−0.177	0.838***	0.032
Black	−0.556	0.489***	0.144	−0.561	0.487***	0.144
Latino	−0.22	0.684***	0.13	−0.221	0.684***	0.13
Asian or Pacific Islander	−0.407	0.568*	0.219	−0.39	0.578*	0.219
Other	−0.159	0.853	0.119	−0.158	0.853	0.119
Weight	0.058	1.06	0.051	0.056	1.057	0.051
Misbehavior	0.568	1.765***	0.055	0.565	1.759***	0.055
Florida	−0.066	0.936	0.091	−0.068	0.934	0.091
Illinois	−0.631	0.532***	0.113	−0.631	0.532***	0.112
North Carolina	0.216	1.242	0.117	0.216	1.241	0.117
Constant	−0.902	0.406*	0.355	−0.88	0.415*	0.355
Nagelkerke R		.187			.187
Log likelihood		6,322.324			6,319.92
χ²		1,089.359			1,091.763

p ≤ .05, ***p ≤ .001.

Results

Descriptive Statistics

As presented in Table 1, the distinctions between LGBQ and heterosexual student’s experiences with bullying victimization are significant. On average, LGBQ students experience higher rates than heterosexual students of traditional bullying (LGBQ: µ = .32, SD = .466; H: µ = .16, SD = .369), electronic bullying (LGBQ: µ = .26, SD = .421; H: µ = .12, SD = .327), and sexual orientation bullying (LGBQ: µ = .33, SD = .470; H: µ = .06, SD = .232). In terms of controls, there are significant differences in the distribution of sexual orientation as well. LGBQ students are more likely to be female (µ = .67, SD = .472), while heterosexual students have a relatively even distribution of females (µ = .49, SD = .5) to males. There are also significant differences in sexual orientation among students who identify as “other” racial or ethnic identities (LGBQ: µ = .12, SD = .326; H: µ = .07, SD = .259). Only slight differences exist in the perceptions of weight among sexual orientation (LGBQ: µ = 2.18, SD = .740; H: µ = 2.14, SD = .644), but significant differences exist among school misbehavior, where LGBQ students (µ = .49, SD = .606) are significantly more involved than heterosexual students (H: µ = .30, SD = .519). Finally, while Florida and North Carolina have fairly even distributions of LGBQ and heterosexual students, Illinois has significantly more LGBQ students (LGBQ: µ = .29, SD = .297; H: µ = .12, SD = .326).

Traditional Bullying

Table 2 represents logistic regression models for traditional bullying victimization of LGBQ youth. The baseline model of Table 2 represents the role of sexual orientation in traditional bullying victimization. LGBQ students are significantly more likely to experience traditional bullying than heterosexual students, Exp(B) = 2.017, p ≤ .001. In terms of controls, gender, grade, race and ethnicity, weight, misbehavior, and state are related to traditional school bullying. Female students, Exp(B) = 1.698, p ≤ .001, are more likely to experience traditional bullying than male students. As student perceptions of weight increase, so does the likelihood of traditional bullying, Exp(B) = 1.112, p ≤ .05, and as involvement in misbehavior increases, so does the likelihood of traditional bullying, Exp(B) = 1.921, p ≤ .001. In turn, as student’s grade level increases, the likelihood of traditional bullying decreases, Exp(B) = 0.816, p ≤ .001. In addition, Black students, Exp(B) = 0.447, p ≤ .001, and Latino students, Exp(B) = 0.661, p ≤ .05, are less likely than White students to experience traditional bullying, and students in the state of Florida are less likely to experience traditional bullying, Exp(B) = 0.723, p ≤ .001, than students from Connecticut.

Model 2 of Table 2 represents the interaction of gender and sexual orientation in traditional bullying victimization. The interaction of gender and sexual orientation matters, where LGBQ females, Exp(B) = 3.217, p ≤ .001; heterosexual females, Exp(B) = 1.782, p ≤ .001; and LGBQ males, Exp(B) = 2.526, p ≤ .05, are significantly more likely to experience traditional bullying victimization than heterosexual males. In terms of controls, similar directions and strength of relationships remain in Model 2, with the exception of gender, and race and ethnicity. The interaction of gender and sexual orientation was tested as an independent covariate; thus gender is eliminated from the controls. In addition, Asian or Pacific Islander students, Exp(B) = 0.770, p ≤ .05, are now less likely than White students to experience traditional bullying.

Electronic Bullying

Table 3 represents logistic regression models for Electronic bullying victimization of LGBQ youth. Model 3 of Table 3 represents the role of sexual orientation in electronic bullying victimization. Sexual minority students, Exp(B) = 1.988, p ≤ .001, are significantly more likely to experience electronic bullying than heterosexual students. In terms of controls, gender, grade, race and ethnicity, misbehavior, and state are related to electronic school bullying. Female students, Exp(B) = 2.873, p ≤ .001, are more likely to experience electronic bullying than male students, and as involvement in misbehavior increases, so does the likelihood of electronic bullying, Exp(B) = 2.241, p ≤ .001. In turn, as student’s grade level increases, the likelihood of electronic bullying decreases, Exp(B) = 0.938, p ≤ .05. In addition, Black students, Exp(B) = 0.416, p ≤ .001; Latino students, Exp(B) = 0.538, p ≤ .05; and Asian or Pacific Islander students, Exp(B) = 0.635, p ≤ .05, are less likely than White students to experience electronic bullying. Finally, students from the state of Florida, Exp(B) = 0.693, p ≤ .001, and North Carolina, Exp(B) = 0.733, p ≤ .05, are less likely to experience electronic bullying than students from the state of Connecticut.

Model 4 of Table 3 represents the interaction of gender and sexual orientation in electronic bullying victimization. The interaction of gender and sexual orientation matters, where LGBQ females, Exp(B) = 5.183, p ≤ .001; heterosexual females, Exp(B) = 3.254, p ≤ .001; and LGBQ males, Exp(B) = 3.401, p ≤ .05, are significantly more likely to experience electronic bullying victimization than heterosexual males. With the exception of gender, which was dropped from the analysis, similar directions and strength of relationships remain in the controls in Model 4.

Bullying Based on Sexual Orientation

Table 4 represents logistic regression models for sexual orientation bullying victimization of LGBQ youth. Model 5 of Table 4 represents the role of sexual orientation in sexual orientation bullying victimization. LGBQ students, Exp(B) = 8.615, p ≤ .001, are significantly more likely to experience sexual orientation bullying than heterosexual students. In terms of controls, grade, race and ethnicity, misbehavior, and state are related to sexual orientation bullying. As involvement in misbehavior increases, so does the likelihood of sexual orientation bullying, Exp(B) = 1.765, p ≤ .001. In turn, as student’s grade level increases, the likelihood of sexual orientation bullying decreases, Exp(B) = 0.836, p ≤ .001. In addition, Black students, Exp(B) = 0.489, p ≤ .001; Latino students, Exp(B) = 0.684, p ≤ .001; and Asian or Pacific Islander students, Exp(B) = 0.568, p ≤ .05, are less likely than White students to experience sexual orientation bullying. Finally, students from the state of Illinois are less likely to experience sexual orientation bullying, Exp(B) = 0.532, p ≤ .001, than students from Connecticut.

Model 6 of Table 4 represents the interaction of gender and sexual orientation in sexual orientation bullying victimization. The interaction of gender and sexual orientation matters. While LGBQ females, Exp(B) = 7.727, p ≤ .001, and LGBQ males, Exp(B) = 7.504, p ≤ .05, are significantly more likely to experience sexual orientation bullying victimization, heterosexual females are significantly less likely, Exp(B) = 0.814, p ≤ .05, to experience sexual orientation bullying victimization than heterosexual males. With the exception of gender, which was dropped from the analysis, similar directions and strength of relationships remain in the controls in Model 6.

Discussion and Conclusion

Children who are perceived to be “different” have experienced and continue to experience harassment at school (Rivers, 2011). Oftentimes, bullying targeting sexual minority youth may be because of perceived nonconformity to gender and sexualized norms (Stopbullying.gov, 2016). This study confirms that certain characteristics are associated with increased bullying victimization, specifically, sexual orientation. LGBQ youth are at increased risk for all three types of bullying victimization: traditional, electronic, and homophobic. The following section discusses this in three primary ways: (a) the prevalence rates and likelihood of LGBQ bullying victimization, (b) the interactions of sexual orientation and gender on the likelihood of bullying victimizations, and (c) other characteristics associated with bullying victimizations in LGBQ youth.

As prior research denotes, LGBT youth experience higher rates of bullying victimization than heterosexual youth (Kosciw et al., 2007; Kosciw et al., 2014; Massachusetts Department of Education, 2004; McGuire et al., 2009). This study supports these findings by showing that LGBQ youth in this study were more likely to experience traditional bullying (32% vs. 16%), electronic bullying (26% vs. 12%), and homophobic bullying (33% vs. 6%) than heterosexual youth. In an effort to capture a more detailed picture, this study also measured the odds of experiencing traditional, electronic, and homophobic bullying if students identified as a LGBQ. Findings reveal that LGBQ youth are about twice as likely to experience traditional and electronic bullying as heterosexual youth, and over 8 times as likely to experience homophobic bullying as heterosexual youth. These findings confirm that LGBQ youth are clear targets for bullying victimizations, even if the possible homophobic intent of the perpetrator is not delineated.

Significant gender differences exist in the prevalence rates and types of bullying victimizations that occur. First, while research suggests that males are more likely to be involved in bullying both, as victims and perpetrators (Nansel et al., 2001; Scheithauer et al., 2006; Viljoen et al., 2005), this study finds that females are actually more likely than males to be involved in all types of bullying victimization. For example, with the exception of homophobic bullying, both LGBQ and heterosexual females are almost 2 to 3 times more likely to experience traditional bullying, and between 3 and 5 times more likely to experience electronic bullying than heterosexual males. More specifically, LGBQ females have the highest odds of experiencing all types of bullying victimization. They are 3.2 times more likely to experience traditional bullying, 5.2 times more likely to experience electronic bullying, and 7.7 times more likely to experience sexual orientation bullying than heterosexual males. Such results are unique given that some studies find that girls are more likely to be involved in only indirect or relational forms of bullying (Carbone-Lopez et al., 2010; Nansel et al., 2001; Scheithauer et al., 2006). Finally, these findings also lend additional support to the literature that suggests that females may be more involved in cyberbullying, because of their propensity for relational forms of violence (Hinduja & Patchin, 2008; Kowalski & Limber, 2007). Overall, gender, in addition to sexual orientation matters in terms of the prevalence of bullying victimization.

Research demonstrates that characteristics such as, gender, age, race and ethnicity, weight, misbehavior, and geographic location (Guerra & Williams, 2010) are associated with differences in bullying victimization. While we know that gender is associated with bullying victimization, this study confirms that increasing age, racial and ethnic identities other than White, and living in Florida, Illinois, and North Carolina are associated with decreased likelihood of bullying victimization in LGBQ youth. While they support current claims that an individual’s age and geographic location can serve as protective factors against bullying victimization (Espelage & Horne, 2008; Guerra & Williams, 2010), they actually contradict findings that racial and ethnic minorities experience more bullying victimization (Hong & Espelage, 2012). More research is needed that investigates this phenomenon. In contrast, these findings support studies that show that those who have poor perceptions of weight (Farhart et al., 2010; Wang et al., 2010) and involvement of misbehavior (Peguero, 2008) are significantly more likely to experience all three types bullying victimizations.

Limitations and Future Research

Although this study contributes to the body of literature regarding bullying victimizations in sexual minority youth, it does not exist without certain limitations. First, the 2013 YRBS does not include transgender youth, thus significantly limiting the scope of the study in terms of inclusivity and investigation of true intersections of sexual orientation and gender. Future research must look to include populations of gender nonconforming students. Second, the cross-sectional analysis limited the ability to establish a causal relationship between sexual orientation, gender, and youth violence at school. Ideally, future research would utilize longitudinal data to develop a causal model that links sexual orientation and gender to school bullying victimization and perpetration. Third, qualitative research could better illuminate researchers’ understanding of the factors that influence school bullying victimization from the perspective of both the victim and perpetrator. To tap the sexualized and gendered elements of why this violence may be occurring, supplementing quantitative data with in-depth interviews may be extremely valuable. Despite the limitations associated with this analysis, this study’s findings provide additional evidence for the need of school policies that protect sexual minority youth and contributes to bettering their well-being.

Bullying victimization encompasses a very clear asymmetric power imbalance, and investigating the role that sexual orientation and gender play in the abuse of young people cannot be ignored. This study confirms that egregious disparities exist in bullying victimization of sexual minority youth. Therefore, these elements should not and cannot be ignored in school policy development. There is a significant lack of school policies that address the existence of violence against sexual minority youth. For example, the 2013 National School Climate Survey reported that only half of students had a Gay Straight Alliance (GSA) or similar club at their school, while just over half (55.5%) of LGBT youth in reported personally experiencing anti-LGBT related discriminatory policies or practices (Kosciw et al., 2014). Finally, only 18 states across the United States have officially passed enumerated antibullying laws that, specifically, protect students based on sexual orientation and/or gender identity. Thus, ameliorating bullying victimization among sexual minority youth requires a combination of elements that directly address these problems. For example, state and federal policies, school programming, and support systems that acknowledge and address sexual orientation and gender identity must exist. Support networks for sexual minority youth—those bullied and not bullied—should be a required element within the school environment, as well as antibullying laws that specifically address facets of identity that are clearly a basis for bullying behavior to account for the justice that all youth deserve.

Footnotes

Author’s Note

This article is a piece from the author’s dissertation that investigates traditional bullying, electronic bullying, and homophobic bullying in sexual minority youth.

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.

Notes

Author Biography

Lindsay Kahle earned her PhD from the Department of Sociology at Virginia Tech. She also holds a master’s degree in sociology and a bachelor’s degree in psychology from Indiana University of Pennsylvania. Her primary areas of research and teaching include youth violence, criminology, and women, gender, and sexuality studies. She has coauthored publications appearing in Sociological Spectrum, Victims & Offenders, Violence and Victims, The Journal of Criminology, and a book chapter featured in From Bullies to Terrorists: The Causes and Consequences of Youth Violence. More broadly, her research focuses on inequalities associated with youth violence.

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