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. Author manuscript; available in PMC: 2024 Jun 21.
Published in final edited form as: Partner Abuse. 2015 Jan;6(1):8–28. doi: 10.1891/1946-6560.6.1.8

An Exploratory Study of Teen Dating Violence in Sexual Minority Youth

Tyson R Reuter 1, Carla Sharp 2, Jeff R Temple 3
PMCID: PMC11192464  NIHMSID: NIHMS1952674  PMID: 38911329

Abstract

Objective:

Teen dating violence (TDV) represents a serious social problem in adolescence and is associated with a host of physical and emotional consequences. Despite advances in identification of risk factors, prevention efforts, and treatment, the TDV literature has overwhelmingly used samples that do not assess sexual orientation or assume heterosexuality. Although a few studies have explicitly examined dating violence among sexual minorities in adolescents, methodological issues limit the generalizability of these findings, and no study to date has examined patterns of dating violence over time in sexual minority youth.

Method:

An ethnically diverse sample of 782 adolescents completed self-report measures of dating violence, hostility, alcohol use, exposure to interparental violence, and sexual orientation.

Results:

Sexual minority adolescents reported higher rates of both TDV perpetration and victimization, and this finding persisted across 2 years for perpetration but not victimization. Findings also revealed that traditional risk factors of TDV (i.e., alcohol use, exposure to interparental violence) were not associated with TDV for sexual minority youth, although sexual orientation itself emerged as a risk factor over and above covariates when considering severe (i.e., physical and sexual) dating violence perpetration.

Conclusions:

Sexual minorities may be at a greater risk for TDV than their heterosexual peers. Findings are discussed within the context of a minority stress model. Future research is needed to parse out factors specifically related to sexual orientation from a stressful or invalidating environment.

Keywords: adolescence, bisexual, gay, lesbian, sexual minorities, teen dating violence

Teen dating violence (TDV) represents a serious public health problem (Center for Disease Control and Prevention, 2012). Both cross-sectional and a growing, albeit limited, number of longitudinal studies have clearly demonstrated that TDV is associated with a host of physical and emotional consequences (Exner-Cortens, Eckenrode, & Rothman, 2013). Depending on the population and how narrow the construct is defined, prevalence rates vary considerably. When constrained to physical and sexual violence, intimidation, and coercion, an estimated 10%–20% of adolescents report having experienced TDV (Eaton, Davis, Barrios, Brener, & Noonan, 2007; Foshee et al., 2009; Shorey, Cornelius, & Bell, 2008). Rates can escalate to 50% when examining at-risk populations or when less physically injurious forms of abuse are considered, such as insults, ridicule, and verbal threats (Orpinas, Nahapetyan, Song, McNicholas, & Reeves, 2012; Wolfe, Scott, Wekerle, & Pittman, 2001). With respect to gender, although females are as or more likely to perpetrate physical acts of violence (Hickman, Jaycox, & Aronoff, 2004; Malik, Sorenson, & Aneshensel, 1997), they are more likely to report negative consequences (Foshee, 1996; Tjaden & Thoennes, 2000).

In addition to physical injury, TDV is associated with several serious short- and long-term emotional outcomes, including a heightened risk of internalizing and externalizing problems such as depression, anxiety, suicidal ideation, substance use, and risky sexual behavior (Rothman, Reyes, Johnson, & LaValley, 2012; Silverman, Raj, Mucci, & Hathaway, 2001; Temple & Freeman, 2011; Temple, Shorey, Fite, Stuart, & Le, 2013; Wolitzky-Taylor et al., 2008). For example, using data from the Massachusetts Youth Risk Behavior Survey, Silverman et al. (2001) assessed physical and sexual dating violence victimization and associated risk factors in 1,977 9th- through 12th-grade females. Findings revealed that approximately one in five adolescents reported physical and/or sexual abuse by a dating partner and that these girls were at increased risk for substance use (e.g., episodic heavy drinking, cocaine use), early sexual intercourse, pregnancy, and suicidality. Similar findings were found by Temple and Freeman (2011), who assessed TDV and substance use and found that victims of TDV were up to 4 times more likely to smoke cigarettes, use marijuana, or drink alcohol. In a study of 397 emergency department adolescent patients, Rothman and colleagues (2012) found a strong association between substance use and TDV perpetration. Beyond these more immediate consequences, TDV may be a “developmental stepping stone” on the trajectory toward adult partner violence (Dank, Lachman, Zweig, & Yahner, 2014, p. 846), as suggested by accumulating evidence showing that perpetrators and victims of TDV are more likely to continue this maladaptive pattern of relating in future intimate relationships (Gidycz, Warkentin, & Orchowski, 2007; Gómez, 2011; White & Smith, 2009).

To understand the development of TDV, it is helpful to refer to theories of adult partner violence. Social learning theory (Bandura, 1973), for example, posits that individuals learn to behave aggressively through observational learning and modeling of others’ violent behavior. Feminist theory (Dobash & Dobash, 1977), on the other hand, argues that partner violence can be explained primarily through female inequality, rigid gender roles, and patriarchal beliefs. Although these traditional theories have received some empirical support (Leonard & Senchak, 1996; Mihalic & Elliott, 1997; Shook, Gerrity, Jurich, & Segrist, 2000; Sims, Dodd, & Tejeda, 2008), more recent etiological models have become increasingly comprehensive in scope, appreciating the heterogeneity of variables that may explain violence in the context of romantic relationships (Bell & Naugle, 2008; Bogat, Levendosky, & von Eye, 2005). This integrative framework has confirmed a broad array of risk factors, cutting across personality traits (e.g., hostility), distal antecedents (e.g., exposure to parental violence), and motivating factors (e.g., substance use). This model is perhaps advantageous over previous approaches given that there are many pathways leading to and from partner abuse.

Despite advances in identification of risk factors, prevention efforts, and treatment, the TDV literature has very consistently used samples that assume heterosexuality among participants or fail to assess sexual orientation altogether. Although numerous studies have investigated the relations between intimate partner violence and sexual orientation among adult and young adult populations (Edwards & Sylaska, 2013; Finneran & Stephenson, 2013; Krahé & Berger, 2013; Porter & Williams, 2011; Waldner-Haugrud, Gratch, & Magruder, 1997), the majority of research—and media attention—on violence in sexual minority youth tends to focus on sexual harassment, bullying, and hate crimes (e.g., D’Augelli, Pilkington, & Hershberger, 2002; King, 2013; Kosciw et al., 2011; Williams, Connolly, Pepler, Craig, 2005). Relatively little is known about the relation between sexual orientation and dating violence in adolescence.

In one study, Freedner, Freed, Yang, and Austin (2002) administered self-report surveys to 521 adolescents attending a gay, lesbian, bisexual, and transgender (GLBT) rally assessing sexual orientation and five types of dating violence (control, emotional, scared for safety, physical, sexual). Results showed that the overall prevalence of dating violence was similar for GLB and heterosexual adolescents. Interestingly, bisexual adolescents were significantly more likely than gay/lesbian adolescents to be threatened with “outing” (i.e., exposing one’s sexual orientation to others without the individual’s consent). In another study examining sexual risk-taking behaviors among urban adolescents, Hipwell et al. (2013) administered measures of sexual orientation and minor physical dating violence to an ethnically diverse sample of 1,647 females. Sexual minority girls (i.e., lesbian or bisexual) reported a significantly higher rate of dating violence victimization than heterosexual girls (31% vs. 18%), although no differences in perpetration were found.

In a nationally representative sample, Halpern, Young, Waller, Martin, and Kupper (2004) analyzed data on a subset of 117 adolescents who reported exclusively same-sex intimate relationships within the past 18 months. Using the Conflict Tactics Scale (Straus, 1979), these authors found that one-fourth of adolescents had experienced any violence victimization (i.e., psychological or physical), and one-tenth had experienced physical victimization. Furthermore, males reporting exclusively same-sex intimate relationships were less likely than females to report experiencing any violence victimization. Questions regarding perpetration of violence were not included in the study. In a regionally representative sample, Martin-Storey (2014) examined data on a subset of youth ages 14–18 years old using the Massachusetts Youth Risk Behavior Survey, with 540 girls and 323 boys reporting a nonheterosexual identity. Dating violence was assessed using the following question: “Have you ever been hurt physically or sexually by a date or someone you were going out with? This might include being hurt by being shoved, slapped, hit, or forced into any sexual activity.” Responses were then collapsed into “hurt by a date” or “not hurt.” Results showed a higher prevalence of dating violence among those with a nonheterosexual identity compared to heterosexual peers, and these findings remained largely significant after controlling for risk factors (e.g., peer victimization, binge drinking, number of sexual partners).

Finally, using a regionally representative sample of 3,754 12–19-year-old students (74% White, 6% LGBT), Dank et al. (2014) compared sexual minority youth to heterosexual youth on the prevalence of TDV perpetration and victimization, and risk of physical TDV victimization. Results showed that sexual minority youth, in particular transgender youth and females, were at higher risk for all forms of TDV victimization (e.g., physical, psychological, cyber, sexual coercion) and almost all forms of TDV perpetration. Regarding risk factors, sexual minority youth who were victims of physical dating violence were more likely to be female, transgender, have higher depression scores, lower grades, and previous sexual activity. Although the Dank et al. (2014) study addressed many of the methodological limitations of previous research in this area, it was limited in several important ways. First, the sample was predominantly White. Second, risk factors of other forms of dating violence (e.g., psychological, relational) were not explored. Third, the study was cross-sectional in nature. Finally, and most concerning, of the 229 students who identified as sexual minorities, only 15 (6.6%) identified as “lesbian” and 4 (1.7%) as “gay,” whereas 136 (59.4%) identified as “bisexual,” 27 (11.8%) as “questioning,” 10 (4.4%) as “queer,” and 37 (16.2%) as “other,” thus restricting the generalizability of these findings, particularly to lesbian and gay adolescents.

Despite the important contributions made from these studies on a historically understudied area, research on dating violence in sexual minority populations, especially in youth, is limited because of a host of methodological concerns. Very often, these studies lack a comparison group of heterosexual adolescents, are qualitative or quasi-empirical in nature, do not assess perpetration of violence, are cross-sectional, measure dating violence through a single item, use a behavioral criterion to define sexual orientation (e.g., has the participant dated a same-sex partner), lack ethnic diversity, study one gender exclusively, and/or recruit subjects through samples of convenience (e.g., gay and lesbian organizations, bars, rallies). For example, exclusively dating individuals of the same gender may not necessarily entail having a gay or lesbian sexual orientation, and such a method excludes individuals who date both genders. Furthermore, data collected through GLBT organizations or rallies may not generalize to sexual minority youth as a whole. Finally, assessing dating violence via a single item likely does not capture and differentiate multiple forms of violence (e.g., psychological, physical, sexual, relational). Taken together, perhaps the most challenging methodological barrier to overcome is obtaining a representative sample that allows for meaningful comparisons between sexual minority youth and heterosexual adolescents (Halpern et al., 2004).

As a result, our understanding of the causes and consequences of TDV in sexual minority youth is at best limited and at worst misinformed, and it remains unclear whether prevalence and risk factors derived from heterosexual samples are similar for sexual minority youth. As previous authors have noted (Burke & Follingstad, 1999; Dank et al., 2014), there is a desperate need for well-controlled, longitudinal research with strong methodology capturing the experiences of dating violence among sexual minorities. Against this background, the first aim of this study is to identify the prevalence of TDV perpetration and victimization in sexual minority youth using a large, geographically and ethnically diverse community sample of adolescents. The second aim is to compare rates of TDV perpetration and victimization among sexual minority youth to heterosexual adolescents. The third aim is to explore rates of TDV perpetration and victimization within specific subgroups of sexual minorities (i.e., lesbian, bisexual, gay). The fourth aim is to explore whether similar risk factors (i.e., hostility, exposure to parental violence, alcohol use) of TDV perpetration and victimization derived from heterosexual samples are relevant to sexual minorities and whether sexual orientation will emerge as a predictor of TDV over and above these risk factors. Finally, because no previous study has investigated dating violence in sexual minority youth over time, the fifth aim is to examine whether sexual orientation explains the persistence of TDV perpetration and victimization across baseline and 2-year follow-up.

As etiological models of TDV become increasingly comprehensive in scope, recognizing the breadth of risk factors, which may explain aggressive and abusive behaviors between partners (Bell & Naugle, 2008), research has confirmed key variables to have significant associations with TDV, including hostility (Wolfe et al., 2003), exposure to interparental violence (Roberts, McLaughlin, Conron, & Koenen, 2011; Temple, Shorey, Tortolero, Wolfe, & Stuart, 2013), and alcohol use (Stuart et al., 2008; Temple, Shorey, Fite, et al., 2013). These variables will therefore be controlled for in regression analyses. Given that few studies include violence perpetration in addition to victimization, and given the evidence suggesting these two forms of violence occur together (Malik et al., 1997), both TDV perpetration and victimization will be investigated.

Guided by findings from the adult literature examining intimate partner violence in LGBT populations and limited evidence from the TDV literature involving sexual minority youth, we hypothesize that (a) TDV perpetration and victimization will be higher in sexual minority adolescents compared to heterosexual adolescents; (b) TDV perpetration and victimization will be higher in bisexual adolescents compared to lesbian and gay adolescents; (c) hostility, exposure to parental violence, and alcohol use will remain important correlates of TDV regardless of sexual orientation; (d) sexual orientation will make unique contributions to TDV perpetration and victimization while controlling for covariates; and (e) TDV perpetration and victimization among sexual minority youth will be more persistent across 2 years of follow-up compared to their heterosexual counterparts.

METHODS

Participants

Data for this study is part of an ongoing school-based longitudinal study investigating the risk and protective factors of TDV (Temple, Shorey, Fite, et al., 2013). Participants were recruited from seven schools in five Houston-area school districts (62% response rate, which is higher than the 60% suggested by the Centers for Disease Control and Prevention). Only students reporting a history of dating at 2-year follow-up (i.e., endorsed the item “I have begun dating, going out with someone, or had a boyfriend/girlfriend”) were included in current analyses (n = 782; 56.8% male). Average age at 2-year follow-up was 17.06 years (SD = 0.77). The sample was ethnically diverse, with 32.5% identifying as Hispanic, 31.2% as White, 26.0% as Black, 2.3% as Asian, and 8.1% as mixed or other.

Measures

Teen Dating Violence.

The Conflict in Adolescent Dating and Relationship Inventory (CADRI; Wolfe, Scott, Reitzel-Jaffe, et al., 2001) is a 50-item measure that assesses TDV perpetration and victimization (e.g., physical, psychological, sexual, and relational). Each question is divided into two parts, with one indicating perpetration (e.g., “I threw something at him/her”) and the other indicating victimization (“He/she threw something at me”). Using binary responses (i.e., 1 = yes, 0 = no), participants chose whether or not they perpetrated and/or were victimized by an act during a conflict or argument with their boyfriend/girlfriend (ex-boyfriend/ex-girlfriend) in the past year. Summary scores for the perpetration and victimization scales were calculated dimensionally (i.e., adding total number of “yes” responses for each scale). Internal consistency for the CADRI ranges from acceptable to strong, with Wolfe, Scott, Reitzel-Jaffe, et al. (2001) reporting a Cronbach’s alpha of .76 for the physical abuse subscales, .81 for the verbal and emotional abuse subscale, and .83 for the total abuse scale. Alphas for this study were .88, .90, and .92, respectively.

Sexual Orientation.

Adolescents were asked how they identify their sexual orientation by choosing one of the following: “completely heterosexual,” “mostly heterosexual,” “bisexual,” “mostly homosexual,” “completely homosexual,” and “not sure.” Those who identified as “completely heterosexual” were grouped as heterosexual, and those who identified as “mostly heterosexual,” “bisexual,” “mostly homosexual,” “completely homosexual,” and “not sure” were grouped as sexual minorities. In addition to distinguishing two groups (i.e., heterosexual youth and sexual minority youth), sexual orientation was used categorically as an independent variable in regression analyses.

Hostility.

Hostility was assessed through the use of the hostility subscale from the Symptom Checklist (SCL-90; Derogatis, Lipman, & Covi, 1973). The SCL-90 is a 90-item self-report measure that identifies 10 clinical subscales, including somatization, obsessive–compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, psychoticism, and sleep difficulty (Lipman, Covi, & Shapiro, 1979). Because of time constraints, only the hostility subscale was included in this study. This subscale identifies feelings and behaviors that are characteristic of anger, including aggression, irritability, rage, and resentment (Derogatis, Rickels, & Rock, 1976). A summary score was used dimensionally as an independent variable in regression analyses. Internal consistency for the subscale has been demonstrated to be adequate, with Derogatis et al. (1976) reporting a Cronbach’s alpha of .84. Alpha for this study was .84.

Alcohol Use.

Using items adapted from the Monitoring the Future Surveys (Johnston, O’Malley, Bachman, & Schulenberg, 2010), alcohol use was operationalized as total number of days out of the past 30 days that the participant engaged in episodic heavy drinking, which was used dimensionally as an independent variable in regression analyses.

Exposure to Interparental Violence.

Father-to-mother and mother-to-father parental violence was assessed by asking the following: “In the past year, how many times did your father (or male caregiver) do any of the above behaviors to your mother (or female caregiver)?” The same question was then asked for mother-to-father violence. Participants were provided with examples of moderate to severe violent acts (e.g., pushed, grabbed, or shoved; slammed against wall; choked) and then asked to report the number of times they have witnessed violence using one of the following options: 0 (never), 1 = (once or twice), 2 = (3–20 times), and 3 = (more than 20 times). This variable was used dimensionally as an independent variable in regression analyses, and previous research has demonstrated single-item measures to be reliable and valid when the construct is clearly defined and homogenous (Loo & Kelts, 1998; Postmes, Haslam, & Jans, 2013).

Procedures

This study was approved by the appropriate institutional review board. Recruitment at baseline and 2-year follow-up occurred during school hours in classes with required attendance. Research staff attended each class twice prior to assessment to explain the study and answer questions. Information about the study as well as parental permission slips were sent home with the students for their parents to read, sign, and return. Assent was then obtained from students who returned the forms, and those who assented were pulled from class to complete the survey. Identical measures of TDV were given at both baseline and 2-year follow-up. Assessments at each time point occurred during school hours, and students received a $10 gift card for participating. To increase reliability of adolescent self-report, teachers and other school administrators were not allowed to be present during questionnaire administration, and privacy was emphasized, including instructing participants not to write their names on surveys (participants were assigned unique subject numbers to link follow-up surveys), and informing them that a federal certificate of confidentiality protected their responses. The high retention rate at 2-year follow-up (85%) was accomplished through the collection of detailed locator information and from working with school personnel in scheduling follow-up assessments.

Data Analytic Strategy

For the first and second aims of exploring and comparing prevalence rates of TDV perpetration and victimization, frequencies were run on the CADRI perpetration and victimization scales for sexual minority adolescents and heterosexual adolescents. Two separate independent-samples t tests were conducted for dimensional scores of overall TDV perpetration and TDV victimization, and chi-square analyses were then conducted on categorical variables of experiencing any specific forms of violence (i.e., physical, psychological, sexual, and relational). For the third aim of exploring rates of TDV perpetration and victimization within sexual minorities, two separate independent-samples t tests were conducted to compare rates of TDV between bisexual versus homosexual (i.e., gay or lesbian) adolescents and between male versus female adolescents. For the fourth aim of exploring correlates of TDV perpetration and victimization for sexual minorities, correlational analyses were conducted to explore bivariate relations between TDV perpetration and victimization, hostility, alcohol use, and exposure to interparental violence for sexual minorities in isolation. To examine whether sexual orientation makes unique contributions to TDV perpetration and victimization over covariates, two separate linear regressions were conducted, with all main study variables (hostility, alcohol use, father-to-mother violence, mother-to-father violence, and sexual orientation) entered as independent variables and TDV perpetration and victimization, respectively, as dependent variables. Methods were also repeated using a more conservative definition of TDV. Analyses for the first four aims used data from 2-year follow-up. Finally, for the fifth aim of investigating whether sexual orientation explains the persistence of TDV perpetration and victimization across time (i.e., baseline and 2-year follow-up), two repeated measures analysis of variance (ANOVA) were conducted with baseline and 2-year follow-up TDV as the within subjects variable and sexual minority status as the between-subjects variable.

RESULTS

Descriptive Statistics and Missing Data

To examine whether data was missing at random, differences between participants with complete data and incomplete data were examined. Chi-square analyses and independent-samples t tests showed that participants with incomplete data were not significantly different from those with complete data on gender x2= 2.435, p = .130), sexual orientation (x2= 1.351, p = .332), alcohol use (t = 1.479, p = .142), father-to-mother violence (t = 1.095, p = .276), or mother-to-father violence (t = 1.970, p = .052), thus confirming that data was missing at random for these main study variables. However, data was found to be missing at nonrandom for hostility (t = 2.057, p = .042).

Breakdown by sexual orientation was as follows: 592 adolescents identified as “completely heterosexual,” 50 as “mostly heterosexual,” 39 as “bisexual,” 12 as “mostly homosexual,” 21 as “completely homosexual,” and 13 “not sure.” Demographic information and percentage of adolescents reporting TDV is presented in Table 1. No significant differences were found between heterosexual and sexual minority adolescents on age (t = −.025; p = .980) or race (x2 = 2.43; p = .127), although more females identified as sexual minorities than males (x2 = 16.23, p < .001). Table 2 summarizes means and standard deviations for main study variables as well as the results of correlational analyses examining the bivariate relations between continuous variables separately for heterosexual and sexual minority adolescents.

TABLE 1.

Demographics and Percentage of Adolescents Experiencing Various Types of Dating Violence

Heterosexual Sexual Minority
Variable n % n % x 2 P
Gender Male 317 53.5 33 27.4 16.230*** <.001
Female 275 46.5 98 72.6
Race White 199 33.6 36 26.7 2.430 .127
Non-White 393 66.4 99 73.3
Physical violence Victimization 108 18.4 37 27.6 5.720* .023
Perpetration 93 15.7 33 24.6 6.100* .016
Psychological violence Victimization 73 12.5 29 21.8 7.590** .009
Perpetration 63 10.8 25 18.8 6.530* .018
Sexual violence Victimization 76 12.9 27 20.3 5.210* .032
Perpetration 49 8.4 20 14.9 4.610* .042
Relational violence Victimization 69 11.8 23 17.2 2.630 .125
Perpetration 28 4.8 7 5.2 0.026 .837
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*

p < .05.

**

p < .01.

***

p < .001.

TABLE 2.

Results of Correlational Analyses Examining Bivariate Relations Between Continuous Variables for Heterosexual and Sexual Minority Adolescents

Sexual Minority Adolescents
TDV Perpetration TDV Victimization Severe TDV Perpetration Severe TDV Victimization Hostility Alcohol Use Exposure to Mother-to-Father Violence Exposure to Father-to-Mother Violence M (SD)
Heterosexual adolescents
 TDV perpetration — .806*** .827*** .645*** .321*** .040 .030 .118 4.87 (4.83)
 TDV victimization .772*** — .627*** .791*** .279** .019 .070 .082 5.12 (4.88)
 Severe TDV perpetration .726*** .524*** — .710*** .199* .058 .129 .142 0.82 (1.50)
 Severe TDV victimization .561*** 709*** .659*** — .220* .006 .107 .090 0.77 (1.32)
 Hostility .318*** .263*** .248*** .199*** — .212*** −.002 −.024 11.76 (3.90)
 Alcohol use .089* .125** .077 .059 .105* — −.053 .060 1.22 (3.14)
 Exposure to mother-to-father violence .054 .075 −.022 .064 .062 .120** — .530*** 0.19 (0.51)
 Exposure to father-to-mother violence .066 .112** .021 .045 .013 .184*** .524*** — 0.15 (0.40)
 M (SD) 3.92 (3.79) 4.19 (4.06) 0.44 (1.05) 0.52 (1.10) 10.94 (3.63) 0.97 (2.30) 0.08 (0.32) 0.09 (0.33) —
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Note. TDV = teen dating violence.

*

p < .05.

**

p < .01.

***

p < .001.

Bivariate Relations Between Main Study Variables

As hypothesized, sexual minority adolescents reported more overall TDV perpetration (t = −2.110; p = .036) and victimization (t = −2.04; p = .043) compared to heterosexual adolescents. Specifically, sexual minority adolescents were more likely to experience TDV, both perpetration and victimization, across all forms of violence (i.e., physical, sexual, and psychological) except relational abuse (see Table 1).

When examining sexual minority adolescents in isolation, bisexual adolescents reported more TDV perpetration (t = 2.93, p = .005) but not TDV victimization (t = 1.94, p = .056) compared to homosexual (i.e., gay or lesbian) adolescents. With respect to gender, sexual minority males and sexual minority females did not differ on reports of TDV perpetration (t = 1.69, p = .095) or victimization (t = 1.04, p = .302).

Regarding risk factors of TDV, all main study variables were associated with TDV perpetration and victimization for heterosexual adolescents, including hostility, alcohol use, and exposure to interparental violence (father-to-mother only). However, for sexual minority adolescents, only hostility was associated with TDV perpetration and victimization (see Table 2).

The Relation Between Sexual Orientation and Teen Dating Violence Controlling for Confounds

Teen Dating Violence Victimization.

As shown in Table 3, after entry of all main study variables (hostility, alcohol use, father-to-mother violence, mother-to-father violence, and sexual orientation), the total variance explained by the model was 9.3%, F(5, 706) = 14.431, p , .001. Only hostility (β = .265, p < .001) was statistically significant. To determine whether similar findings were demonstrated when using a more conservative definition of TDV, additional analyses were conducted with severe victimization (i.e., combination of physical and sexual abuse subscales) as the dependent variable. The total variance explained by this model was 5.4%, F(5, 708) = 7.162, p < .001, with only hostility (β = .200 p < .001) retaining significance.

Table 3.

Results of Linear Regressions

Variable N B SE β t P df 1 df 2 R 2
TDV victimization Hostility 706 .306 .042 .265 7 271*** .000 5 706 .093
Alcohol use .084 .063 .049 1.330 .184
Exposure to father-to-mother violence .968 .536 .077 1.805 .071
Exposure to mother-to-father violence .286 .507 .024 0.563 .574
Sexual orientation .574 .394 .053 1.455 .146
TDV perpetration Hostility 708 .352 .039 .323 9.013*** .000 5 708 .120
Alcohol use .037 .059 .023 0.631 .529
Exposure to father-to-mother violence .822 .497 .070 1.656 .098
Exposure to mother-to-father violence .043 .470 .004 0.091 .928
Sexual orientation .590 .366 .058 1.613 .107
Severe TDV victimization Hostility 708 .063 .012 .200 5.380*** .000 5 708 .054
Alcohol use .004 .018 .008 0.211 .833
Exposure to father-to-mother violence .148 .150 .043 0.990 .322
Exposure to mother-to-father violence .138 .142 .042 0.972 .332
Sexual orientation .171 .110 .057 1.547 .122
Severe TDV perpetration Hostility 708 .073 .011 .232 6.333*** .000 5 708 .078
Alcohol use .016 .017 .034 0.916 .360
Exposure to father-to-mother violence −.046 .146 −.014 −0.317 .751
Exposure to mother-to-father violence .213 .139 .066 1.540 .124
Sexual orientation .296 .108 .100 2.745** .006
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Note. TDV = teen dating violence. Hostility, alcohol use, exposure to interparental violence, and sexual orientation as independent variables and TDV victimization, TDV perpetration, Severe TDV victimization, and Severe TDV perpetration as dependent variables.

**

p < .01.

***

p < .001.

Teen Dating Violence Perpetration.

As shown in Table 3, after entry of all main study variables (hostility, alcohol use, father-to-mother violence, mother-to-father violence, and sexual orientation), the total variance explained by the model was 12.0%, F(5, 708) = 19.259, p < .001. Only hostility (β = .323, p < .001) was statistically significant. To determine whether similar findings were demonstrated when using a more conservative definition of TDV, additional analyses were conducted with severe perpetration (i.e., combination of physical and sexual abuse subscales) as the dependent variable. The total variance explained by this model was 7.8%, F(5, 708) = 11.934, p < .001, with both hostility (β = .232, p , .001) and sexual orientation (β = .100, p = .006) retaining significance.

The Relation Between Sexual Orientation and the Persistence of Teen Dating Violence

Teen Dating Violence Victimization.

Sexual orientation was entered as the between-subjects factor in the repeated measures ANOVA, with TDV victimization at baseline and 2-year follow-up as the within-subjects variable. As shown in Table 4, results showed no interaction effect for group (heterosexual vs. sexual minority) and time, Wilks’s lambda = 1.000, F(1, 640) = .044, p = .835, and no effect was found for time, Wilks’s lambda = .999, F(1, 640) = .397, p = .529. No main effect emerged in TDV victimization for heterosexual versus sexual minority groups across both time points, although results approached significance, F(1, 640) = 3.203, p = .074.

TABLE 4.

Results of Repeated Measures ANOVA, With Sexual Orientation as the Between-Subjects Factor and TDV Victimization and TDV Perpetration at Baseline and 2-Year Follow-Up as the Within-Subjects Factor

Effect MS df F P
Tests of Within-Subjects Effects
TDV victimization Time 4.409 1 0.397 .529
Time × Sexual orientation 0.484 1 0.044 .835
Error 11.110 640
TDV perpetration Time 0.391 1 0.051 .821
Time × Sexual orientation 11.685 1 1.536 .216
Error 7.609 655
Tests of Between-Subjects Effects
Effect MS df F P
TDV victimization Sexual orientation 79.574 1 3.203 .074
Error 24.874 640
TDV perpetration Sexual orientation 118.685 1 5.189* .023
Error 22.874 655
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Note. ANOVA = analysis of variance; TDV = teen dating violence.

*

p < .05.

Teen Dating Violence Perpetration.

Sexual orientation was entered as the between-subjects factor in the repeated measures ANOVA, with TDV perpetration at baseline and 2-year follow-up as the within-subjects variable. As shown in Table 4, results showed no interaction effect for group (heterosexual vs. sexual minority) and time, Wilks’s lambda = .998, F(1, 655) = 1.536, p = .216, and no effect was found for time, Wilks’s lambda = 1.000, F(1, 655) = .051, p = .821. However, tests of between-subjects effects showed a main effect in TDV perpetration for heterosexual versus sexual minority groups across both time points, F(1, 655) = 5.189, p = .023, demonstrating sexual minority adolescents sustained more stability in dating violence across two years.

DISCUSSION

Given the serious physical and emotional consequences associated with TDV, and given the dearth of empirical literature investigating TDV in sexual minority youth, this study sought to explore prevalence, risk factors, and patterns of TDV over time in a community sample of adolescents. Several findings merit discussion. First, as expected, sexual minorities experienced more dating violence than their heterosexual peers, including more serious forms of abuse such as physical and sexual violence. Bisexual adolescents appear particularly at risk. Second, traditional risk factors of TDV (alcohol use, exposure to interparental violence) were not relevant for sexual minority youth. Third, sexual orientation emerged as a significant predictor of severe dating violence perpetration controlling for covariates. Finally, sexual minority adolescents reported more stability in TDV perpetration over time.

The finding that sexual minority adolescents reported more dating violence can perhaps be explained, at least in part, through a minority stress model (Meyer, 2003). Stated briefly, the interplay between minority status and majority, dominant values results in conflict with the greater social environment, typically characterized for sexual minorities as homophobia, self-stigmatization, hostility, expectations of rejection, and/or invalidation. Ultimately, this leads to increased stress and poor mental and physical outcomes (Dohrenwend et al., 1992; Meyer, 2003). Indeed, individuals with a nonheterosexual orientation, including youth, often experience various distal and proximal interpersonal, institutional/structural, and health stressors including rejection from friends and family, violence and victimization, lower earning wages, and increased risk of sexually transmitted disease and HIV infection (Badgett, Lau, Sears, & Ho, 2007; D’Augelli, Hershberger, & Pilkington, 1998; Halkitis, Green, & Carragher, 2006; Herek, Gillis, Cogan, & Glunt, 1997; Meyer, 2003). Further support for this model comes from evidence demonstrating that the link between sexual orientation and deleterious health outcomes is strongly attenuated when controlling for experiences of discrimination (Mays & Cochran, 2001).

Other researchers have argued that, in addition to these stigma-related stressors unique to sexual minorities, there are also general psychological processes, shared by both heterosexuals and sexual minorities, which influence adverse behavioral outcomes. This integrative framework posits that specific social, cognitive, and emotional processes (e.g., emotion dysregulation, social isolation) are relatively robust predictors of psychopathology and that these processes are elevated in sexual minorities because of stigma-related stressors (Hatzenbuehler, 2009). Indeed, one study demonstrated that sexual minority adolescents, compared to their heterosexual peers, had higher levels of emotion dysregulation, which in turn accounted for higher levels of depression and anxiety (Hatzenbuehler, McLaughlin, & Nolen-Hoeksema, 2008). Given the strong association between poor affect/emotion regulation and partner violence across adolescent and adult populations (Dutton, Saunders, Starzomski, & Bartholomew, 1994; Kinsfogel & Grych, 2004), perhaps greater emotion dysregulation, coupled with limited coping resources because of social isolation, hopelessness, and experiences of discrimination (Plöderl & Fartacek, 2005), can explain elevated levels of TDV in sexual minorities.

The finding that bisexual adolescents experienced even greater dating violence than homosexual adolescents fits with literature demonstrating those with a double minority status often show poorer mental and physical health outcomes (Balsam, Beauchaine, Mickey, Rothblum, 2005; Diaz, Ayala, Bein, Jenne, & Marin, 2001). Some authors have suggested that bisexuals experience dual marginalization (Ochs, 1996), or simultaneous discrimination from both the minority (i.e., homosexual) and dominant, majority (i.e., heterosexual) cultures (Burrill, 2009; Eliason, 1997). Indeed, bisexuals often face unique challenges not shared by homosexuals, such as more pronounced invalidation of their identity as legitimate or “bi-invisibility” (Bronn, 2001) and pressure to dichotomize their sexuality into either heterosexual or homosexual (Oswalt, 2009). Research has demonstrated that heterosexuals’ attitudes toward bisexuals are largely unfavorable, even more so than various racial and religious groups (Herek, 2002). Within the LGB community, gays and lesbians may stereotype bisexuals as simply confused or unsure of their sexual identity, uncommitted or un-trustworthy in romantic relationships, or remain closeted to maintain heterosexual privilege (Israel & Mohr, 2004). Perhaps the dual marginalization from both the heterosexual and homosexual communities leads to increased minority stress, which may in part explain higher rates of TDV.

Why traditional risk factors of TDV (alcohol use, exposure to interparental violence) were not relevant for sexual minorities remains puzzling. One possibility is insufficient power because of the significantly smaller sample of sexual minorities. Another possibility that may explain the lack of association between alcohol use and TDV is difference in drinking patterns among sexual minorities and heterosexuals. Supporting evidence for the “bar culture” comes from research demonstrating sexual minorities have generally more permissive social norms and positive expectancies for alcohol use (Hatzenbuehler, Corbin, & Fromme, 2008; Heffernan, 1998). Perhaps higher baseline levels and less variability of alcohol use across this population contributes to this null finding. Finally, it is important to consider the possibility that the current explanatory model for TDV may not easily translate to sexual minorities. Perhaps there is something unique about the dating experiences of sexual minorities that limits the applicability of the dominant heteronormative model to this population.

LIMITATIONS

As with all research, our findings should be interpreted in light of several limitations. For example, questions concerning dating violence tap into the frequency and not the severity or context of TDV. In addition, because of study design, sexual orientation was only assessed at 2-year follow-up, therefore assuming a similar sexual orientation at baseline, which may be problematic given previous research showing relative instability of same-sex romantic attraction and sexual orientation in adolescence and young adulthood (Savin-Williams & Ream, 2007). Finally, although sexual minorities reported more TDV at the bivariate level, sexual orientation was significant in only one of the models when considering other variables known to relate to TDV, with aggressive personality traits (i.e., hostility) remaining most predictive.

STRENGTHS AND IMPLICATIONS

Despite these limitations, the results of this study are strengthened in several important ways. First, the study had a large, ethnically and geographically diverse non-convenience sample. Second, rather than inferring sexual orientation through a behavioral criterion (e.g., dating a same-sex partner), this study explicitly assessed sexual orientation. Third, in addition to investigating victimization, this study also included perpetration as well as differentiated between less physically injurious (i.e., psychological) and more severe (i.e., physical and sexual) types of violence. Fourth, given that the majority of studies on GLB populations collapse gay, lesbian, and bisexual orientations across one category, this study contributes to the literature by examining variations not only between but also within a specific minority group. Fifth, variables known to relate to TDV were controlled for, which highlight the importance of the unique impact of sexual orientation on the perpetration of severe TDV. Finally, this study is the first to examine and compare TDV in sexual minorities over time.

From both a research and clinical standpoint, assuming heterosexuality or neglecting to assess sexual orientation altogether may result in failure to identify those at a particularly high risk of TDV. Indeed, traditional risk factors derived predominantly from studies using heterosexual samples were largely not associated with dating violence for sexual minorities in this study. Although in need of future replication, this finding calls into question the applicability of decades of research on TDV to a particular subgroup of individuals—namely, those who identify as nonheterosexual. Taken together, given the high prevalence rates coupled with negative physical and mental health outcomes, findings from this study suggest sexual orientation should not be overlooked when considering TDV, and continued investigation and inclusion of this understudied, yet important variable is warranted.

Contributor Information

Tyson R. Reuter, University of Houston.

Carla Sharp, University of Houston.

Jeff R. Temple, University of Texas Medical Branch.

REFERENCES

  1. Badgett MV, Lau H, Sears B, & Ho D (2007). Bias in the workplace: Consistent evidence of sexual orientation and gender identity discrimination. Los Angeles, CA: The Williams Institute. [Google Scholar]
  2. Balsam KF, Beauchaine TP, Mickey RM, & Rothblum ED (2005). Mental health of lesbian, gay, bisexual, and heterosexual siblings: Effects of gender, sexual orientation, and family. Journal of Abnormal Psychology, 114(3), 471–476. [DOI] [PubMed] [Google Scholar]
  3. Bandura A (1973). Aggression: A social learning analysis. Englewood Cliffs, NJ: Prentice-Hall. [Google Scholar]
  4. Bell KM, & Naugle AE (2008). Intimate partner violence theoretical considerations: Moving towards a contextual framework. Clinical Psychology Review, 28(7), 1096–1107. [DOI] [PubMed] [Google Scholar]
  5. Bogat GA, Levendosky AA, & von Eye A (2005). The future of research on intimate partner violence: Person-oriented and variable-oriented perspectives. American Journal of Community Psychology, 36(1–2), 49–70. [DOI] [PubMed] [Google Scholar]
  6. Bronn CD (2001). Attitudes and self-images of male and female bisexuals. Journal of Bisexuality, 1(4), 5–29. [Google Scholar]
  7. Burke LK, & Follingstad DR (1999). Violence in lesbian and gay relationships: Theory, prevalence, and correlational factors. Clinical Psychology Review, 19(5), 487–512. [DOI] [PubMed] [Google Scholar]
  8. Burrill KG (2009). Queering bisexuality. Journal of Bisexuality, 9(3–4), 491–499. [Google Scholar]
  9. Center for Disease Control and Prevention. (2012). Teen dating violence. Retrieved from http://www.cdc.gov/violenceprevention/intimatepartnerviolence/teen_dating_violence.html
  10. Dank M, Lachman P, Zweig JM, & Yahner J (2014). Dating violence experiences of lesbian, gay, bisexual, and transgender youth. Journal of Youth and Adolescence, 43(5), 846–857. [DOI] [PubMed] [Google Scholar]
  11. D’Augelli AR, Hershberger SL, & Pilkington NW (1998). Lesbian, gay, and bisexual youth and their families: Disclosure of sexual orientation and its consequences. American Journal of Orthopsychiatry, 68(3), 361–371. [DOI] [PubMed] [Google Scholar]
  12. D’Augelli AR, Pilkington NW, & Hershberger SL (2002). Incidence and mental health impact of sexual orientation victimization of lesbian, gay, and bisexual youths in high school. School Psychology Quarterly, 17(2), 148–167. [Google Scholar]
  13. Derogatis LR, Lipman RS, & Covi L (1973). SCL-90: An outpatient psychiatric rating scale-preliminary report. Psychopharmacology Bulletin, 9, 13–17. [PubMed] [Google Scholar]
  14. Derogatis LR, Rickels K, & Rock AF (1976). The SCL-90 and the MMPI: A step in the validation of a new self-report scale. British Journal of Psychiatry, 128(3), 280–289. [DOI] [PubMed] [Google Scholar]
  15. Diaz RM, Ayala G, Bein E, Jenne J, & Marin BV (2001). The impact of homophobia, poverty, and racism on the mental health of Latino gay men: Findings from 3 US cities. American Journal of Public Health, 91, 927–932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Dobash RE, & Dobash RP (1977). Wives: The “appropriate” victims of marital violence. Victimology, 2(3–4), pp. 426–442. [Google Scholar]
  17. Dohrenwend BP, Levav I, Shrout P, Schwartz S, Nahev G, Link BG, … Stueve A (1992). Socioeconomic status and psychiatric disorders: The causation-selection issue. Science, 255, 946–952. [DOI] [PubMed] [Google Scholar]
  18. Dutton DG, Saunders K, Starzomski A, & Bartholomew K (1994). Intimacy-anger and insecure attachment as precursors of abuse in intimate relationships. Journal of Applied Social Psychology, 24(15), 1367–1386. [Google Scholar]
  19. Eaton DK, Davis KS, Barrios L, Brener ND, & Noonan RK (2007). Associations of dating violence victimization with lifetime participation, co-occurrence, and early initiation of risk behaviors among U.S. high school students. Journal of Interpersonal Violence, 22(5), 585–602. [DOI] [PubMed] [Google Scholar]
  20. Edwards KM, & Sylaska KM (2013). The perpetration of intimate partner violence among LGBTQ college youth: The role of minority stress. Journal of Youth and Adolescence, 42(11), 1721–1731. [DOI] [PubMed] [Google Scholar]
  21. Eliason MJ (1997). The prevalence and nature of biphobia in heterosexual undergraduate students. Archives of Sexual Behavior, 26(3), 317–326. [DOI] [PubMed] [Google Scholar]
  22. Exner-Cortens D, Eckenrode J, & Rothman E (2013). Longitudinal associations between teen dating violence victimization and adverse health outcomes. Pediatrics, 131(1), 71–78. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Finneran C, & Stephenson R (2013). Intimate partner violence among men who have sex with men: a systematic review. Trauma, Violence, & Abuse, 14(2), 168–185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Foshee VA (1996). Gender differences in adolescent dating abuse prevalence, types and injuries. Health Education Research, 11(3), 275–286. [Google Scholar]
  25. Foshee VA, Benefield T, Suchindran C, Ennett ST, Bauman KE, Karriker-Jaffe KJ, … Mathias J (2009). The development of four types of adolescent dating abuse and selected demographic correlates. Journal of Research on Adolescence, 19(3), 380–400. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Freedner N, Freed LH, Yang YW, & Austin SB (2002). Dating violence among gay, lesbian, and bisexual adolescents: Results from a community survey. Journal of Adolescent Health, 31(6), 469–474. [DOI] [PubMed] [Google Scholar]
  27. Gidycz CA, Warkentin JB, & Orchowski LM (2007). Predictors of perpetration of verbal, physical, and sexual violence: A prospective analysis of college men. Psychology of Men & Masculinity, 8(2), 79–94. [Google Scholar]
  28. Gómez AM (2011). Testing the cycle of violence hypothesis: Child abuse and adolescent dating violence as predictors of intimate partner violence in young adulthood. Youth & Society, 43(1), 171–192. [Google Scholar]
  29. Halkitis PN, Green KA, & Carragher DJ (2006). Methamphetamine use, sexual behavior and HIV seroconversion. Journal of Gay and Lesbian Psychotherapy, 10(3/4), 95–109. [Google Scholar]
  30. Halpern CT, Young ML, Waller MV, Martin SL, & Kupper LL (2004). Prevalence of partner violence in same-sex romantic and sexual relationships in a nationally sample of adolescents. Journal of Adolescent Health, 35(2), 124–131. [DOI] [PubMed] [Google Scholar]
  31. Hatzenbuehler ML (2009). How does sexual minority stigma “get under the skin”? A psychological mediation framework. Psychological Bulletin, 135(5), 707–730. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Hatzenbuehler ML, Corbin WR, & Fromme K (2008). Trajectories and determinants of alcohol use among LGB young adults and their heterosexual peers: Results from a prospective study. Developmental Psychology, 44(1), 81–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Hatzenbuehler ML, McLaughlin KA, & Nolen-Hoeksema S (2008). Emotion regulation and internalizing symptoms in a longitudinal study of sexual minority and heterosexual adolescents. Journal of Child Psychology and Psychiatry, 49(12), 1270–1278. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Heffernan K (1998). The nature and predictors of substance use among lesbians. Addictive Behaviors, 23(4), 517–528. [DOI] [PubMed] [Google Scholar]
  35. Herek GM (2002). Heterosexuals’ attitudes toward bisexual men and women in the United States. Journal of Sex Research, 39(4), 264–274. [DOI] [PubMed] [Google Scholar]
  36. Herek GM, Gillis JR, Cogan JC, & Glunt EK (1997). Hate crime victimization among lesbian, gay, and bisexual adults: Prevalence, psychological correlates, and methodological issues. Journal of Interpersonal Violence, 12(2), 195–215. [Google Scholar]
  37. Hickman LJ, Jaycox LH, & Aronoff J (2004). Dating violence among adolescents: Prevalence, gender distribution, and prevention program effectiveness. Trauma, Violence, & Abuse, 5(2), 123–142. [DOI] [PubMed] [Google Scholar]
  38. Hipwell AE, Stepp SD, Keenan K, Allen A, Hoffmann A, Rottingen L, & McAloon R (2013). Examining links between sexual risks behaviors and dating violence involvement as a function of sexual orientation. Journal of Pediatric and Adolescent Gynecology, 26(4), 212–218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Israel T, & Mohr JJ (2004). Attitudes toward bisexual women and men: Current research, future directions. Journal of Bisexuality, 4(1–2), 117–134. [Google Scholar]
  40. Johnston LD, O’Malley PM, Bachman JG, & Schulenberg JE (2010). Monitoring the future: National survey results on drug use, 1975–2009: Vol. I. Secondary school students (NIH Publication No. 10–7584). Bethesda, MD: National Institute on Drug Abuse. [Google Scholar]
  41. King J (2013, June). Hate violence against LGBT community is on a dangerous rise. Colorlines: News for action. Retrieved from http://colorlines.com/archives/2013/06/hate_violence_against_lgbt_is_one_a_dangerous_rise.html [Google Scholar]
  42. Kinsfogel KM, & Grych JH (2004). Interparental conflict and adolescent dating relationships: Integrating cognitive, emotional, and peer influences. Journal of Family Psychology, 18(3), 505–515. [DOI] [PubMed] [Google Scholar]
  43. Kosciw JG, Palmer NA, Kull RM, & Greytak EA (2013). The effect of negative school climate on academic outcomes for LGBT youth and the role of in-school supports. Journal of School Violence, 12(1), 45–63. [Google Scholar]
  44. Krahé B, & Berger A (2013). Men and women as perpetrators and victims of sexual aggression in heterosexual and same-sex encounters: A study of first-year college students in Germany. Aggressive Behavior, 39(5), 391–404. [DOI] [PubMed] [Google Scholar]
  45. Leonard KE, & Senchak M (1996). Prospective prediction of husband marital aggression within newlywed couples. Journal of Abnormal Psychology, 105(3), 369–380. [DOI] [PubMed] [Google Scholar]
  46. Lipman RS, Covi L, & Shapiro AK (1979). The Hopkins Symptom Checklist (HSCL)—Factors derived from the HSCL-90. Journal of Affective Disorders, 1(1), 9–24. [DOI] [PubMed] [Google Scholar]
  47. Loo R, & Kelts P (1998). A caveat on using single-item measures. Employee Assistance Quarterly, 14(2), 75–80. [Google Scholar]
  48. Malik S, Sorenson SB, & Aneshensel CS (1997). Community and dating violence among adolescents: Perpetration and victimization. Journal of Adolescent Health, 21(5), 291–302. [DOI] [PubMed] [Google Scholar]
  49. Martin-Storey A (2014). Prevalence of dating violence among sexual minority youth: Variation across gender, sexual minority identity and gender of sexual partners. Journal of Youth and Adolescence, 1–14. [DOI] [PubMed] [Google Scholar]
  50. Mays VM, & Cochran SD (2001). Mental health correlates of perceived discrimination among lesbian, gay, and bisexual adults in the United States. American Journal of Public Health, 91(11), 1869–1876. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Meyer IH (2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129(5), 674–697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Mihalic SW, & Elliott D (1997). A social learning theory model of marital violence. Journal of Family Violence, 12(1), 21–47. [Google Scholar]
  53. Ochs R (1996). Biphobia: It goes more than two ways. In Firestein BA (Ed.), Bisexuality: The psychology and politics of an invisible minority (pp. 217–239). Thousand Oaks, CA: Sage. [Google Scholar]
  54. Orpinas P, Nahapetyan L, Song X, McNicholas C, & Reeves PM (2012). Psychological dating violence perpetration and victimization: Trajectories from middle to high school. Aggressive Behavior, 38(6), 510–520. [DOI] [PubMed] [Google Scholar]
  55. Oswalt SB (2009). Don’t forget the “B”: Considering bisexual students and their specific health needs. Journal of American College Health, 57(5), 557–560. [DOI] [PubMed] [Google Scholar]
  56. Plöderl M, & Fartacek R (2005). Suicidality and associated risk factors among lesbian, gay, and bisexual compared to heterosexual Austrian adults. Suicide and Life-Threatening Behavior, 35(6), 661–670. [DOI] [PubMed] [Google Scholar]
  57. Porter J, & Williams LM (2011). Intimate violence among underrepresented groups on a college campus. Journal of Interpersonal Violence, 26(16), 3210–3224. [DOI] [PubMed] [Google Scholar]
  58. Postmes T, Haslam SA, & Jans L (2013). A single-item measure of social identification: Reliability, validity, and utility. British Journal of Social Psychology, 52(4), 597–617. [DOI] [PubMed] [Google Scholar]
  59. Roberts AL, McLaughlin KA, Conron KJ, & Koenen KC (2011). Adulthood stressors, history of childhood adversity, and risk of perpetration of intimate partner violence. American Journal of Preventive Medicine, 40(2), 128–138. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Rothman EF, Reyes LM, Johnson RM, & LaValley M (2012). Does the alcohol make them do it? Dating violence perpetration and drinking among youth. Epidemiologic Reviews, 34(1), 103–119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Savin-Williams RC, & Ream GL (2007). Prevalence and stability of sexual orientation components during adolescence and young adulthood. Archives of Sexual Behavior, 36(3), 385–394. [DOI] [PubMed] [Google Scholar]
  62. Shook NJ, Gerrity DA, Jurich J, & Segrist AE (2000). Courtship violence among college students: A comparison of verbally and physically abusive couples. Journal of Family Violence, 15(1), 1–22. [Google Scholar]
  63. Shorey RC, Cornelius TL, & Bell KM (2008). A critical review of theoretical frameworks for dating violence: Comparing the dating and marital fields. Aggression and Violent Behavior, 13(3), 185–194. [Google Scholar]
  64. Silverman JG, Raj A, Mucci LA, & Hathaway JE (2001). Dating violence against adolescent girls and associated substance use, unhealthy weight control, sexual risk behavior, pregnancy, and suicidality. JAMA, 286(5), 572–579. [DOI] [PubMed] [Google Scholar]
  65. Sims EN, Dodd VJN, & Tejeda MJ (2008). The relationship between severity of violence in the home and dating violence. Journal of Forensic Nursing, 4(4), 166–173. [DOI] [PubMed] [Google Scholar]
  66. Straus MA (1979). Measuring intrafamily conflict and violence: The Conflict Tactics (CT) scales. Journal of Marriage and the Family, 41, 75–88. [Google Scholar]
  67. Stuart GL, Temple JR, Follansbee KW, Bucossi MM, Hellmuth JC, & Moore TM (2008). The role of drug use in a conceptual model of intimate partner violence in men and women arrested for domestic violence. Psychology of Addictive Behaviors, 22(1), 12–24. [DOI] [PubMed] [Google Scholar]
  68. Temple JR, & Freeman DH (2011). Dating violence and substance use among ethnically diverse adolescents. Journal of Interpersonal Violence, 26(4), 701–718. [DOI] [PubMed] [Google Scholar]
  69. Temple JR, Shorey RC, Fite P, Stuart GL, & Le VD (2013). Substance use as a longitudinal predictor of the perpetration of teen dating violence. Journal of Youth and Adolescence, 42(4), 596–606. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Temple JR, Shorey RC, Tortolero SR, Wolfe DA, & Stuart GL (2013). Importance of gender and attitudes about violence in the relationship between exposure to interparental violence and the perpetration of teen dating violence. Child Abuse & Neglect, 37(5), 343–352. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Tjaden P, & Thoennes N (2000). Prevalence and consequences of male-to-female and female-to-male intimate partner violence as measured by the National Violence Against Women Survey. Violence Against Women, 6(2), 142–161. [Google Scholar]
  72. Waldner-Haugrud LK, Gratch LV, & Magruder B (1997). Victimization and perpetration rates of violence in gay and lesbian relationships: Gender issues explored. Violence and Victims, 12(2), 173–184. [PubMed] [Google Scholar]
  73. White JW, & Smith PH (2009). Covariation in the use of physical and sexual intimate partner aggression among adolescent and college-age men A longitudinal analysis. Violence Against Women, 15(1), 24–43. [DOI] [PubMed] [Google Scholar]
  74. Williams T, Connolly J, Pepler D, & Craig W (2005). Peer victimization, social support, and psychosocial adjustment of sexual minority adolescents. Journal of Youth and Adolescence, 34(5), 471–482. [Google Scholar]
  75. Wolfe DA, Scott K, Reitzel-Jaffe D, Wekerle C, Grasley C, & Straatman AL (2001). Development and validation of the conflict in adolescent dating relationships inventory. Psychological Assessment, 13(2), 277–293. [PubMed] [Google Scholar]
  76. Wolfe DA, Scott K, Wekerle C, & Pittman AL (2001). Child maltreatment: Risk of adjustment problems and dating violence in adolescence. Journal of the American Academy of Child & Adolescent Psychiatry, 40(3), 282–289. [DOI] [PubMed] [Google Scholar]
  77. Wolfe DA, Wekerle C, Scott K, Straatman AL, Grasley C, & Reitzel-Jaffe D (2003). Dating violence prevention with at-risk youth: A controlled outcome evaluation. Journal of Consulting and Clinical Psychology, 71(2), 279–291. [DOI] [PubMed] [Google Scholar]
  78. Wolitzky-Taylor KB, Ruggiero KJ, Danielson C, Resnick HS, Hanson RF, Smith DW, … Kilpatrick DG (2008). Prevalence and correlates of dating violence in a national sample of adolescents. Journal of the American Academy of Child & Adolescent Psychiatry, 47(7), 755–762. [DOI] [PMC free article] [PubMed] [Google Scholar]

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