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. Author manuscript; available in PMC: 2025 Apr 1.
Published in final edited form as: Prev Sci. 2024 Jan 12;25(4):590–602. doi: 10.1007/s11121-023-01640-z

Gender and Sexual Orientation Differences in Sexual Violence Knowledge, Prevention Behaviors, and Care-Seeking Behaviors

Robert W S Coulter 1,2, Nicholas Szoko 1, Jessica Frankeberger 2, Brian Adams 3, Kelley A Jones 1, Carla D Chugani 1, Jocelyn Anderson 1,4, Janine Talis 1, Heather L McCauley 5, Elizabeth Miller 1,2
PMCID: PMC11111351  NIHMSID: NIHMS1967176  PMID: 38214789

Abstract

Purpose:

Sexual violence (SV) on college campuses disproportionately affects cisgender (non-transgender) women, sexual minorities (e.g., gays/lesbians, bisexuals), and gender minority (e.g., transgender/nonbinary) people. This study investigates gender and sexual behavior differences in common SV intervention targets—SV-related knowledge, prevention behaviors, and care-seeking.

Methods:

We analyzed cross-sectional survey data, collected in 9/2015–3/2017, from 2,202 students aged 18–24 years attending college health and counseling centers at 28 Pennsylvania and West Virginia campuses. Multivariable multilevel models tested gender and sexual behavior differences in: SV history; recognition of SV; prevention behaviors (self-efficacy to obtain sexual consent, intentions to intervene, positive bystander behaviors); and care-seeking behaviors (knowledge of, self-efficacy to use, and actual use of SV services).

Results:

Adjusting for lifetime exposure to SV, compared with cisgender men, cisgender women had higher recognition of SV and reproductive coercion, prevention behaviors, and care-seeking self-efficacy (betas range: 0.19–1.36) and gender minority people had higher recognition of SV and intentions to intervene (betas range: 0.33–0.61). Cisgender men with any same-gender sexual partners had higher SV knowledge (beta=0.23) and self-efficacy to use SV services (beta=0.52) than cisgender men with only opposite-gender partners. SV history did not explain these differences.

Conclusions:

Populations most vulnerable to SV generally have higher SV knowledge, prevention behaviors, and care-seeking behaviors than cisgender men with only opposite-gender sexual partners. Innovative SV intervention approaches are necessary to increase SV-related knowledge among heterosexual cisgender men and may need to target alternative mechanisms to effectively reduce inequities for sexual and gender minority people.

Keywords: sexual violence prevention, sexual minority, gender minority, college students

Sexual violence (SV) represents a major public health concern on U.S. college campuses (American College Health Association, 2016; Krebs et al., 2016; Krebs et al., 2007), with the prevalence estimates varying across studies (Fedina et al., 2018). Yet studies consistently show that SV disproportionately affects certain populations. For example, cisgender women and gender minorities (i.e., transgender and nonbinary people) experience higher rates of sexual assault than cisgender men (American College Health Association, 2016; Cantor et al., 2015; Coulter RWS et al., 2017; Krebs et al., 2016; Krebs et al., 2007; Sinozich & Langton, 2014). In a survey of students at 120 colleges, 3.6% of cisgender men reported past-year SV compared with 8.6% of cisgender women and 20.9% of transgender people (Coulter RWS et al., 2017). Additionally, sexual minorities (e.g., gay/lesbian and bisexual people) disproportionately experience SV during college (Cantor et al., 2015; Coulter RWS et al., 2017; Martin et al., 2011; Mellins et al., 2017): for example, 6.4% of heterosexuals reported past-year SV compared with 9.8% of gays/lesbians and 15.7% of bisexuals (Coulter RWS et al., 2017).

Given the alarming prevalence of SV, many national and local efforts have aimed to improve SV prevention and care (The White House, 2017; White House Task Force to Protect Students From Sexual Assault, 2014). Interventions intended to reduce SV experiences and SV-related sequelae often target common risk and protective factors; such factors include college students’ SV-related knowledge, intentions to intervene in situations potentially leading to SV, as well as their knowledge, self-efficacy, and use of SV treatment services (DeGue et al., 2014). Research about whether these common intervention targets differ by gender or sexual orientation can be used to inform future intervention programs and studies that aim to reduce gender and sexual orientation inequities in SV and SV-related care-seeking.

Several studies have examined differences in SV knowledge, prevention behaviors, and care-seeking behaviors by gender—as well as other demographics such as race, ethnicity, and socioeconomic status. For example, compared with cisgender men, cisgender women report less acceptance of rape myths, greater intentions to intervene against SV, and more positive bystander behaviors (Amar et al., 2014; Banyard et al., 2007; Hoxmeier et al., 2017; McMahon, 2010). However, gender differences in care-seeking behaviors are more variable: some studies show cisgender women have greater knowledge about and self-efficacy to use SV-related treatment services, while other studies found no gender differences (Hayes-Smith & Levett, 2010; Sabina & Ho, 2014). Unfortunately, research elucidating differences in these outcomes by gender identity inclusive of transgender and nonbinary people is completely absent. Also understudied is whether SV-related knowledge, attitudes, and behaviors differ by sexual orientation. Understanding differences by gender and sexual minority status is critical because these groups experience elevated rates of SV (Cantor et al., 2015; Coulter RWS et al., 2017; Martin et al., 2011; Mellins et al., 2017) and are at risk for multiple SV-associated health sequelae (Miller & McCaw, 2019). Furthermore, examining differences by gender and sexual orientation can help tailor interventions aimed at reducing disparities for sexual and gender minorities (SGMs), a priority area for the National Academy of Medicine (Institute of Medicine, 2011).

Empirically supported theories explaining gender and sexual orientation differences in SV-related knowledge, prevention behaviors, and care-seeking are nascent. The extant differences in these outcomes between cisgender men and cisgender women may exist for several reasons. First, at the individual level, cisgender women are more likely than cisgender men to experience SV, and such experiences may make cisgender women more knowledgeable about SV as well as more knowledgeable and willing to use SV-related care. Second, at the community level, it is well-understood that heterosexual cisgender men often perpetrate SV against cisgender women; as such, the cultural milieu, including the #MeToo movement, has raised community-level awareness about SV definitions, sexual consent, and SV-related services (PettyJohn et al., 2019). Furthermore, cisgender women may know they are at greater risk and be taught by caregivers, role models, and peers about how to protect themselves—but cisgender men may not receive the same type of education. Thus, cisgender women are often provided as examples in SV risk reduction and resistance programming on college campuses (Orchowski et al., 2020). Taken together, these socio-ecological factors may make cisgender women have higher knowledge, prevention behaviors, and care-seeking related to SV.

The same socio-ecological factors that make cisgender women more likely to engage in prosocial, prevention, and care-seeking behaviors may not necessarily function in the same way for SGMs. SGMs experience stigma and discrimination, which fundamentally negatively influences health and can create barriers for SGMs to obtain SV-related knowledge and resources (Calton et al., 2016). For example, many SGMs experience discrimination in healthcare and campus settings, which can reduce their likelihood of seeking care when they need it, including after experiencing SV. Additionally, SV interventions often target cisgender heterosexual people and may exclude representations of SGMs (Davison et al., 2021). If interventions aimed at increasing knowledge of SV and reproductive coercion are not SGM-inclusive, then SGM people may gain less knowledge on these topics. On the other hand, since SGMs are at increased risk of SV, perhaps there is greater community-level awareness about SV which may result in the transmission of knowledge and skills that make SGM more knowledgeable and more likely to engage in prevention behaviors and care-seeking. To date, research has yet to examine whether there are SGM differences in SV knowledge, prevention behaviors, and care-seeking in college populations. Such findings can inform the development of new or adapted SV interventions inclusive of or tailored for SGM populations.

Therefore, the purpose of our study was to examine gender (including transgender and nonbinary status) and sexual orientation differences in SV knowledge, prevention behaviors, and care-seeking behaviors with data collected from 28 college campuses. Based on the aforementioned research, we hypothesized cisgender women would have greater SV knowledge, prevention behaviors, and care-seeking behaviors than cisgender men. However, we had no a priori hypotheses about differences by transgender/nonbinary status or by sexual behavior given the paucity of existing theory and research. Among the cisgender sample, we also explored the interactions between sexual orientation and gender on these outcomes to understand whether the sexual-orientation differences exist among both cisgender men and women, or whether the intersections of gender and sexuality produce markedly different experiences in SV prevention knowledge, behaviors, and care-seeking. Importantly, our analyses adjusted for many potential confounders, including demographic correlates and exposure to SV victimization.

Methods

Study Design and Population

We analyzed baseline data from a cluster-randomized controlled trial aimed at testing the effects of a brief intervention to reduce alcohol-related SV (Abebe et al., 2018). Between September 2015 and March 2017, we recruited students aged 18–24 years from college health and counseling centers at 28 higher education institutions in Pennsylvania and West Virginia. Registration and clinical staff referred age-eligible clients to study staff, who provided information about the study and a link to the online survey. Overall, 2,291 participants consented, enrolled, and completed online surveys at baseline (prior to their clinical appointment and intervention/control delivery). We offered participants a $15 gift card for completing the baseline survey. Additional study details are reported elsewhere (Abebe et al., 2018). The University of Pittsburgh Human Research Protection Office approved our procedures.

Measures

Exposure Variables

We assessed gender using a two-step approach (The GenIUSS Group, 2014). First, participants were asked: “How do you identify yourself? Male; Female; Transgender Female; Transgender Male; I’m not on the binary; or None of the above.” Second, participants were asked “What is your biological sex (assignment at birth)? Assigned female; or Assigned male.” We categorized gender into three groups: cisgender women (participants who identified as and were assigned female); cisgender men (participants who identified as and were assigned male); and transgender or nonbinary (participants who identified as transgender, non-binary, or whose assigned sex did not match their current gender). We combined transgender and nonbinary participants into a single group because of the small sample size. We removed the 3 participants who selected “none of the above” from our current analyses, because we could not be certain whether they were transgender or nonbinary or simply did not understand the question; however, when we coded these participants as transgender in our analyses, results (available upon request) remained similar in direction and magnitude.

We measured sexual orientation with lifetime sexual behavior. Those who responded affirmatively to ever having vaginal or anal sex were asked: “Since you started having sex, have you had sex with: Women only; Mostly women; Equally men and women; Mostly men; Men only.” Based on their gender and response to these items, we categorized participants into three groups: never had anal or vaginal sex; opposite-gender-only sexual behavior; and any same-gender sexual behavior. We combined participants who had sex with the same gender only with people who had sex with both men and women due to the small sample size. Because sexual behavior was assessed using binary gender (men versus women), we could not adequately categorize nonbinary people’s sexual behavior, therefore we conducted all sexual behavior analyses among cisgender people only.

As covariates, we included age, race/ethnicity (White, Black, Asian, Latinx, and other), and lifetime history of SV victimization. We included lifetime history of SV victimization as a covariate because it is known to be associated with our key exposure variables and outcome variables (Anderson et al., 2020), and therefore may serve as a confounder. Lifetime history of SV was assessed using 6 items modified from the Sexual Experiences Survey (Carey et al., 2015). We asked participants about specific unwanted sexual experiences (e.g., sexual touching, vaginal, anal, and oral sex). Participants indicated the number of times each type of SV occurred. (These questions asked about any unwanted sexual experiences, unconnected to any specific tactic used by the perpetrator; example item: “how many times has anyone made you do oral sex or have it done to you when you indicated that you didn’t want to?”). We dichotomized participants’ responses as any SV versus none.

Outcome Variables

We measured eight SV knowledge, prevention behaviors, and care-seeking behaviors, drawn from prior studies, reported in detail elsewhere (Abebe et al., 2018). Higher scores indicate more positive outcomes.

Recognition of alcohol-related SV and sexual risk

Recognition of alcohol-related SV and sexual risk was assessed using 12 items (e.g., “Please indicate how much you agree or disagree with the following statements: Alcohol is the most common date rape drug”) (Ward et al., 2012). Response options included a 5-point Likert scale ranging from “strongly disagree” to “strongly agree.” We calculated an average score across items (Cronbach’s α=0.73).

Recognition of sexual and reproductive coercion

Recognition of sexual and reproductive coercion was assessed using 9 items (e.g., “How abusive do you think this is: threatening to leave someone if they don’t have sex.”) (Tancredi et al., 2015). Response options included a 5-point Likert scale from “not abusive” to “extremely abusive.” We calculated an average score (α=0.85).

Self-efficacy to obtain sexual consent

Self-efficacy to obtain sexual consent was assessed using 10 items (e.g., “I feel confident that I could ask for sexual consent from a new partner.”) (Humphreys & Brousseau, 2010). Response options included a 5-point Likert scale from “strongly agree” to “strongly disagree.” We calculated an average score (α=0.91).

Intentions to intervene

Intentions to intervene were assessed using 10 items (e.g., “If you see a friend or peer doing any of the following things, how likely are you to try to stop it? Saying that it is OK to have sex with someone who is passed out or very drunk.”) (Miller et al., 2015; Miller et al., 2012; Tancredi et al., 2015). Response options included a 5-point Likert scale from “very unlikely” to “very likely.” We calculated an average score (α=0.92).

Positive bystander behaviors

Positive bystander behaviors (Abebe et al., 2018; Miller et al., 2012) were assessed, first, by asking participants if they witnessed 10 different scenarios (e.g., “In the past 4 months, have you: heard a friend or peer saying that it is OK to have sex with someone who is passed out or very intoxicated?”). From these scenario-based questions, each participant received an exposure to SV score (observed range: 0–9). Second, participants were asked how they responded to each scenario they witnessed. Participants received a score of 1 for each scenario they responded with at least one positive bystander behavior (e.g., “I told the person that acting like that was not okay”; 3 out of 7 options were positive bystander behaviors); otherwise, they received a score of 0. We calculated the total number of positive bystander behaviors using a summary score across the witnessed scenarios (observed range: 0–8). For analyses involving this outcome, we restricted the sample to only participants who reported witnessing at least one SV scenario (n=1,861; 84.4%).

Knowledge of SV services

Knowledge of SV services was assessed with 5 items (e.g., “Did you know that there are on-campus sexual assault experts that you can talk to?”) (Miller et al., 2015; Tancredi et al., 2015). Response options included “yes” or “no.” We calculated a summary score for the “yes” responses.

Self-efficacy to use SV services

Self-efficacy to use SV services was assessed with 6 items (e.g., “How likely would you be to talk to the doctors, nurses, counselors, and staff at your college health clinic if you needed information or help related to sexual assault?”) (Abebe et al., 2018). Response options included a 5-point Likert scale from “very unlikely” to “very likely.” We calculated an average score (α=0.89).

Use of SV services

Use of SV services was assessed with 6 items (e.g., “In the past 4 months, have you: called the National Sexual Assault Hotline or visited their website?”) (Miller et al., 2015; Tancredi et al., 2015). Response options included “yes” or “no.” Due to the low prevalence of service use, if a participant responded “yes” to any item, we coded them as 1, creating a binary variable. For analyses involving this outcome, we restricted the sample analyzed to participants who reported experiencing lifetime SV.

Analyses

We conducted analyses in StataSE v.15 (College Station, Texas). We used descriptive statistics to describe the demographics and outcome variables by gender and sexual behavior. We utilized the total sample to examine gender differences in the outcomes, and we utilized only cisgender participants to examine sexual behavior differences in the outcomes; the latter decision was made because, as previously mentioned, sexual behavior was assessed in a binary fashion (inclusive of only men and women) and gender was assessed more expansively (inclusive of nonbinary people).

To examine our primary research questions, we conducted multilevel regression models with random intercepts (accounting for the nesting of students within schools) and controlled for covariates. For continuous outcomes, we used multilevel linear regression models. For positive bystander behaviors, we used multilevel Poisson regression models among those who reported witnessing at least one SV scenario; these models also accounted for the total number of witnessed scenarios as the exposure variable. For use of SV services, we conducted multivariable logistic regression models among participants who reported lifetime history of SV (multilevel models were not necessary; intraclass correlation<0.001).

We used a 4-step model building process. First, for the total sample, we added the main effects of gender, controlling for covariates. Second, for the cisgender sample, we added the main effect of sexual behavior, controlling for gender and covariates. Third, we added the interaction term between gender and sexual behavior. Fourth, we replaced the gender and sexual behavior variables with a six-category variable representing all the unique combinations of gender by sexual behavior, but only when the interaction term was significant.

Missingness on exposure variables and covariates was low, ranging from 0.1% for gender to 1.7% for sexual behavior. After removing these participants and the single participant missing data on all outcomes, our final analytic sample size included 2,202 total participants (96.2% of the original sample) and 2,176 participants in the cisgender sample. We allowed sample sizes to vary across models.

Results

Overall, 72.7% of participants were cisgender women, 26.2% were cisgender men, and 1.1% were transgender/nonbinary people (Table 1). Among the 25 transgender/nonbinary participants, 12 were transgender men, 2 were transgender women, and 11 were not on the binary (data not shown). Regarding sexual behavior, 22.4% of participants reported not having sex in their lifetimes; 69.9% of participants reported having opposite-gender-only sexual partners; and 7.7% reported having same-gender sexual partners. In the sample, 56.1% indicated experiencing sexual violence in their lifetimes. This included 64.6% of cisgender women, 60% of transgender/nonbinary participants, and 77.1% of participants with any same-gender sexual partners.

Table 1.

Demographic Description of the Total Sample, by Gender, and by Sexual Behavior

Gender in Total Sample Sexual Behavior in Cisgender Sample
Total Cisgender men Cisgender women Transgender or nonbinary Opposite-gender-only partners Any same-gender partners Never had anal or vaginal sex
Characteristic n (%) n (%) n (%) n (%) n (%) n (%) n (%)
Total Observations, Row Percentage 2,202 (100.0) 577 (26.2) 1,600 (72.7) 25 (1.1) 1,539 (69.9) 170 (7.7) 493 (22.4)
Gender
 Cisgender men 577 (26.2) 577 (100.0) 0 (0.0) 0 (0.0) 1,143 (74.3) 111 (70.7) 346 (71.9)
 Cisgender women 1,600 (72.7) 0 (0.0) 1,600 (100.0) 0 (0.0) 396 (25.7) 46 (29.3) 135 (28.1)
 Transgender/nonbinary 25 (1.1) 0 (0.0) 0 (0.0) 25 (100.0) n/a n/a n/a n/a n/a n/a
Age (years), mean (standard deviation) 20.1 (1.5) 20.1 (1.6) 20.0 (1.5) 20.2 (1.6) 20.1 (1.6) 20.0 (1.5) 20.2 (1.6)
Race/Ethnicity
 White 1,506 (68.4) 355 (61.5) 1,132 (70.8) 19 (76.0) 355 (61.5) 1,132 (70.8) 19 (76.0)
 Black 206 (9.4) 72 (12.5) 134 (8.4) 0 (0.0) 72 (12.5) 134 (8.4) 0 (0.0)
 Asian 117 (5.3) 35 (6.1) 82 (5.1) 0 (0.0) 35 (6.1) 82 (5.1) 0 (0.0)
 Latinx 294 (13.4) 95 (16.5) 195 (12.2) 4 (16.0) 95 (16.5) 195 (12.2) 4 (16.0)
 Other 79 (3.6) 20 (3.5) 57 (3.6) 2 (8.0) 20 (3.5) 57 (3.6) 2 (8.0)
Lifetime History of Sexual Violence Victimization
 No 967 (43.9) 391 (67.8) 566 (35.4) 10 (40.0) 635 (41.3) 36 (22.9) 286 (59.5)
 Yes 1,235 (56.1) 186 (32.2) 1,034 (64.6) 15 (60.0) 904 (58.7) 121 (77.1) 195 (40.5)
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Note. n/a = not applicable because transgender and nonbinary people were excluded from analyses by sexual behavior, as a result of sexual behavior being assessed in a binary manner while gender was assessed more expansively.

Table 2 provides raw scores and percentages for recognition of SV, SV prevention behaviors, and care-seeking behaviors in the sample. Table 3 shows results from the multivariable models examining differences in the outcomes by gender and sexual behavior after adjustment for demographics and history of SV exposure. Model 1 found that, compared with cisgender men, cisgender women had significantly higher levels of all SV knowledge, prevention behaviors, and care-seeking behavior outcomes, with the exception of use of SV services among people who experienced SV. Transgender/nonbinary people, compared with cisgender men, had significantly higher recognition of SV and sexual risk (b = 0.33; 95% CI: 0.13, 0.52) and intentions to intervene (b = 0.61; 95% CI: 0.26, 0.95).

Table 2.

Raw Scores and Percentages of Sexual Violence Knowledge, Prevention Behaviors, and Care-Seeking Behaviors by Gender and Sexual Behavior

Recognition of Sexual Violence and Sexual Risk Recognition of Sexual and Reproductive Coercion Self-efficacy to Obtain Sexual Consent Intentions to Intervene Positive Bystander Behaviors Among Witnesses Knowledge of Sexual Violence Services Self-efficacy to Use Sexual Violence Services Use of Sexual Violence Services Among Survivors
Characteristic mean (sd) mean (sd) mean (sd) mean (sd) mean (sd) mean (sd) mean (sd) n (%)
AMONG THE TOTAL SAMPLE
Number of observations, n 2,201 2,191 2,198 2,192 1,858 2,178 2,176 1,218
Gender
 Cisgender men 3.78 (0.53) 3.14 (0.65) 3.90 (0.81) 3.80 (0.90) 1.24 (1.21) 3.50 (1.62) 3.06 (1.07) 21 (11.70)
 Cisgender women 4.06 (0.48) 3.41 (0.56) 4.19 (0.76) 4.17 (0.85) 1.77 (1.32) 3.69 (1.41) 3.51 (0.99) 134 (13.10)
 Transgender/nonbinary 4.14 (0.52) 3.40 (0.79) 4.02 (0.85) 4.44 (0.57) 1.71 (1.76) 4.00 (1.67) 3.13 (1.01) 1 (7.14)
AMONG THE CISGENDER SAMPLE
Number of observations, n 2,176 2,166 2,173 2,167 1,837 2,154 2,152 1,204
Sexual Behavior
 Opposite-gender-only partners 3.95 (0.51) 3.35 (0.60) 4.14 (0.78) 4.06 (0.89) 1.65 (1.33) 3.65 (1.48) 3.37 (1.04) 120 (13.44)
 Any same-gender partners 4.02 (0.49) 3.38 (0.67) 4.09 (0.89) 4.12 (0.89) 1.89 (1.30) 3.73 (1.40) 3.56 (1.00) 22 (18.64)
 Never had anal or vaginal sex 4.09 (0.49) 3.31 (0.58) 4.05 (0.75) 4.09 (0.85) 1.51 (1.24) 3.56 (1.48) 3.39 (1.02) 13 (6.74)
Gender and Sexual Behavior Subgroups
 Cisgender Men
  Opposite-gender-only partners 3.72 (0.52) 3.11 (0.66) 3.91 (0.80) 3.78 (0.88) 1.19 (1.20) 3.51 (1.65) 2.99 (1.05) 11 (9.09)
  Any same-gender partners 4.01 (0.54) 3.32 (0.77) 3.93 (1.07) 3.93 (0.97) 1.76 (1.25) 3.47 (1.49) 3.55 (1.06) 7 (24.14)
  Never had anal or vaginal sex 3.88 (0.52) 3.19 (0.57) 3.83 (0.73) 3.83 (0.92) 1.17 (1.19) 3.48 (1.61) 3.12 (1.11) 3 (10.34)
 Cisgender women
  Opposite-gender-only partners 4.03 (0.48) 3.43 (0.55) 4.21 (0.75) 4.15 (0.87) 1.79 (1.33) 3.71 (1.41) 3.51 (1.00) 109 (14.12)
  Any same-gender partners 4.03 (0.46) 3.40 (0.62) 4.15 (0.80) 4.19 (0.84) 1.94 (1.33) 3.84 (1.36) 3.56 (0.98) 15 (16.85)
  Never had anal or vaginal sex 4.17 (0.46) 3.36 (0.58) 4.14 (0.74) 4.20 (0.80) 1.63 (1.24) 3.59 (1.43) 3.50 (0.96) 10 (6.10)
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Table 3.

Multivariable Models of Sexual Violence Knowledge, Prevention Behaviors, and Care-Seeking Behaviors

Recognition of Sexual Violence and Sexual Risk Recognition of Sexual and Reproductive Coercion Self-efficacy to Obtain Sexual Consent Intentions to Intervene Postive Bystander Behaviors Among Witnesses Knowledge of Sexual Violence Services Self-efficacy to Use Sexual Violence Services Use of Sexual Violence Services Among Survivors
Characteristic b [95% CI] b [95% CI] b [95% CI] b [95% CI] IRR [95% CI] b [95% CI] b [95% CI] OR [95% CI]
MODEL 1: Main Effects of Gender in Total Sample
Number of observations, n 2,201 2,191 2,198 2,192 1,858 2,178 2,176 1,218
Gender
 Cisgender men referent referent referent referent referent referent referent referent
 Cisgender women 0.25 *** [0.21,0.30] 0.24 *** [0.19,0.30] 0.31 *** [0.23,0.38] 0.35 *** [0.26,0.44] 1.36 *** [1.23,1.49] 0.19 * [0.04,0.33] 0.40 *** [0.30,0.51] 1.19 [0.72,1.94]
 Transgender/nonbinary 0.33 ** [0.13,0.52] 0.23 [−0.01,0.46] 0.11 [−0.20,0.42] 0.61 *** [0.26,0.95] 1.29 [0.92,1.81] 0.49 [−0.11,1.09] 0.06 [−0.35,0.48] 0.59 [0.07,4.78]
MODEL 2: Main Effects of Gender and Sexual Behavior in Cisgender Sample
Number of observations, n 2,176 2,166 2,173 2,167 1,837 2,154 2,152 1,204
Gender
 Cisgender men referent referent referent referent referent referent referent referent
 Cisgender women 0.26 *** [0.21,0.30] 0.25 *** [0.19,0.31] 0.31 *** [0.23,0.38] 0.35 *** [0.27,0.44] 1.36 *** [1.24,1.50] 0.18 * [0.04,0.33] 0.41 *** [0.31,0.51] 1.22 [0.74,2.00]
Sexual Behavior
 Opposite-gender-only partners referent referent referent referent referent referent referent referent
 Any same-gender partners 0.06 [−0.02,0.14] 0.03 [−0.07,0.13] −0.03 [−0.16,0.10] 0.07 [−0.07,0.21] 1.13 [1.00,1.29] 0.10 [−0.14,0.35] 0.17 * [0.01,0.34] 1.47 [0.88,2.44]
 Never had anal or vaginal sex 0.14 *** [0.08,0.19] −0.03 [−0.09,0.03] −0.07 [−0.15,0.01] 0.05 [−0.04,0.14] 1.04 [0.95,1.15] −0.07 [−0.22,0.09] 0.05 [−0.06,0.15] 0.47 * [0.26,0.86]
MODEL 3: Interaction Effects of Gender by Sexual Behavior in Cisgender Sample
Number of observations, n 2,176 2,166 2,173 2,167 1,837 2,154 2,152 1,204
Gender
 Cisgender men referent referent referent referent referent referent referent referent
 Cisgender women 0.27 *** [0.21,0.33] 0.29 *** [0.22,0.36] 0.32 *** [0.22,0.41] 0.36 *** [0.26,0.46] 1.40 *** [1.25,1.57] 0.19 * [0.02,0.37] 0.48 *** [0.36,0.60] 1.73 [0.90,3.34]
Sexual Behavior
 Opposite-gender-only partners referent referent referent referent referent referent referent referent
 Any same-gender partners 0.23 ** [0.08,0.38] 0.17 [−0.01,0.35] 0.03 [−0.20,0.27] 0.14 [−0.13,0.40] 1.35 * [1.05,1.74] −0.02 [−0.47,0.44] 0.52 ** [0.20,0.83] 3.29 * [1.14,9.48]
 Never had anal or vaginal sex 0.12 ** [0.03,0.22] 0.06 [−0.05,0.18] −0.06 [−0.21,0.09] 0.05 [−0.12,0.22] 1.04 [0.85,1.28] 0.01 [−0.29,0.30] 0.14 [−0.06,0.34] 1.17 [0.30,4.53]
Interactions of Gender x Sexual Behavior
 Cisgender women x Any same-gender partners −0.24** [−0.41,−0.06] −0.20 [−0.41,0.01] −0.09 [−0.37,0.19] −0.09 [−0.41,0.22] 0.79 [0.59,1.06] 0.17 [−0.36,0.71] −0.48* [−0.85,−0.11] 0.36 [0.11,1.22]
 Cisgender women x Never had anal or vaginal sex 0.02 [−0.09,0.13] −0.12 [−0.26,0.01] 0.00 [−0.18,0.17] 0.00 [−0.20,0.20] 1.01 [0.80,1.27] −0.10 [−0.44,0.23] −0.13 [−0.36,0.11] 0.34 [0.08,1.55]
MODEL 4: Main Effects of Gender-Sexual Behavior Subgroups in Cisgender Sample
Number of observations, n 2,176 2,166 2,173 2,167 1,837 2,154 2,152 1,204
Gender and Sexual Behavior Subgroups
 Cisgender Men
  Opposite-gender-only partners referent referent referent referent referent referent referent referent
  Any same-gender partners 0.23 ** [0.08,0.38] 0.17 [−0.01,0.35] 0.03 [−0.20,0.27] 0.14 [−0.13,0.40] 1.35 * [1.05,1.74] −0.02 [−0.47,0.44] 0.52 ** [0.20,0.83] 3.29 * [1.14,9.48]
  Never had anal or vaginal sex 0.12 ** [0.03,0.22] 0.06 [−0.05,0.18] −0.06 [−0.21,0.09] 0.05 [−0.12,0.22] 1.04 [0.85,1.28] 0.01 [−0.29,0.30] 0.14 [−0.06,0.34] 1.17 [0.30,4.53]
 Cisgender women
  Opposite-gender-only partners 0.27 *** [0.21,0.33] 0.29 *** [0.22,0.36] 0.32 *** [0.22,0.41] 0.36 *** [0.26,0.46] 1.40 *** [1.25,1.57] 0.19 * [0.02,0.37] 0.48 *** [0.36,0.60] 1.73 [0.90,3.34]
  Any same-gender partners 0.26 *** [0.16,0.37] 0.27 *** [0.14,0.39] 0.26 ** [0.09,0.43] 0.41 *** [0.22,0.59] 1.50 *** [1.25,1.79] 0.35 * [0.03,0.67] 0.51 *** [0.29,0.73] 2.05 [0.89,4.74]
  Never had anal or vaginal sex 0.41 *** [0.34,0.48] 0.23 *** [0.14,0.32] 0.25 *** [0.14,0.36] 0.41 *** [0.28,0.54] 1.46 *** [1.27,1.68] 0.10 [−0.12,0.31] 0.49 *** [0.34,0.64] 0.69 [0.28,1.70]
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Note. OR = odds ratio; IRR = incidence rate ratio; CI = confidence interval. Multivariable models are adjusted for race/ethnicity, age, lifetime history of sexual violence victimization. Boldface indicates p<0.05.

*

p<0.05;

**

p<0.01;

***

p<0.001

Among the cisgender sample, there were fewer differences by sexual behavior (Table 3, Model 2). Compared with people who had opposite-gender-only sexual partners, people with any same-gender sexual partners had higher self-efficacy to use SV services (b = 0.41; 95% CI: 0.01, 0.34), but did not significantly differ on any other outcome. In addition, people without sexual contact had higher recognition of SV and sexual risk (b = 0.14; 95% CI: 0.08, 0.19) but lower odds of SV service use (OR = 0.47; 95% CI: 0.26, 0.86) compared with people who had opposite-gender-only sexual partners.

In models testing the interactions between gender and sexual behavior, only two significant interactions existed across all outcomes (Table 3, Model 3). For recognition of SV and sexual risk as well as self-efficacy to use SV services, the differences between people with any same-gender sexual partners and those who had opposite-gender-only sexual partners were larger for cisgender men than cisgender women. To illustrate these two interactions, Model 4 (Table 3) shows the differences among the six gender and sexual behavior groups. Compared with cisgender men who had opposite-gender-only sexual partners, cisgender men who had any same-gender sexual partners had significantly higher recognition of SV and sexual risk (b = 0.23; 95% CI: 0.08, 0.38) and self-efficacy to use services (b = 0.52; 95% CI: 0.20, 0.83). Compared with cisgender men who had opposite-gender-only partners, all subgroups of cisgender women had significantly higher scores with similar magnitude for these outcomes. Additionally, compared to cisgender men who had opposite-gender-only partners, both cisgender men and women who reported having never had anal or vaginal sex had higher recognition of SV and sexual risk, and women who never had anal or vaginal sex also had higher self-efficacy to use SV services.

Discussion

Our study addresses novel questions related to an understudied disparity: SV-related intervention targets among SGMs. We found the populations who are most vulnerable to SV—cisgender men with any same-gender partners (sexual minority men), cisgender women, and transgender/nonbinary people—generally, had greater SV knowledge, prevention behaviors, and care-seeking behaviors than cisgender heterosexual men. Importantly, these results are independent of exposure to sexual violence. These findings reaffirm previous work showing greater SV-related knowledge and bystander behaviors among cisgender women and builds upon this literature by considering the unique experiences of SGMs. Our results inform future programmatic work for reducing SV and improving treatment for these vulnerable populations.

Current SV programming commonly targets SV knowledge, prevention behaviors, and care-seeking behaviors (DeGue et al., 2014), and our study found most of these outcomes are higher among SGMs—yet SGM disparities in SV persist. Therefore, targeting these mechanisms among SGMs may likely not reduce inequities for these vulnerable populations. Instead, SV prevention and treatment programs likely need to identify alternative mechanisms and approaches to reduce these disparities.

The Future of Reducing SV Inequities for SGMs

Our primary study findings—that compared with cisgender heterosexual men, SGMs and cisgender women have higher recognition of SV, higher prevention behaviors, and higher care-seeking—point to the need for alternative, more comprehensive SV prevention strategies to address SV in these populations (McCauley et al., 2019). The first implication is the need to focus SV prevention efforts by targeting perpetrators’ SV-related knowledge, attitudes, and behaviors to reduce SV exposure among the most vulnerable. Thus, it may be beneficial for SV programming to target perpetrators to reduce SV disparities more efficiently.

Second, the field has shown SGM populations face risk factors at multiple levels of the social ecological model that increase their risk of SV (Coulter & Rankin, 2020; McCauley et al., 2018). For example, based on minority stress theory (Meyer, 2003), SGMs face chronic individual, interpersonal, and structural stigma and discrimination. These factors can make SGMs targets for victimization (Coulter & Rankin, 2020; McCauley et al., 2018; Meyer, 2003). For example, at a structural level, addressing policies and practices on campuses to increase inclusion, visibility, and safety for SGMs may improve SV-related outcomes. One potential avenue for doing so is to address larger cultural and social norms concerning SGM equality. Having a sense of community is associated with one’s prosocial behaviors (Banyard, 2008) and greater perceived inclusion of SGMs is associated with lower odds of experiencing SV (Coulter & Rankin, 2020). Therefore, promoting greater inclusivity of SGM students (e.g., policies and programming reducing SGM discrimination) across campuses may enhance existing SV prevention and treatment efforts (Moylan et al., 2021). Another method is to ensure SV educational interventions use SGM-inclusive language and examples. A major critique of early SV interventions concerned the focus on cisgender men as perpetrators and cisgender women as victims, to the exclusion of SGMs (Berkowitz, 2002; Foubert, 2000; Foubert et al., 2007; Langhinrichsen-Rohling et al., 2011). This emphasis can perpetuate inaccurate and harmful heteronormative stereotypes likely limiting these interventions’ receptivity. By infusing evidence-based SV interventions (Banyard et al., 2004; Koss & Harvey, 1991) with SGM cultural relevance and inclusivity, we may be able to reduce SV disparities for SGMs.

Furthermore, in our care-seeking sample, we also found that SGMs are disproportionally more likely to have a history of SV. This aligns with prior research showing SGM disparities among the general population of college students (Cantor et al., 2015; Coulter RWS et al., 2017; Martin et al., 2011; Mellins et al., 2017). Because SGM disparities in SV are present in health and counseling centers, college health clinicians should be trained in providing trauma-sensitive care that is inclusive of SGM students and reflective of competence in gender affirming care. Such strategies include asking affirmed names and pronouns, having intake forms that invite students to identify their gender, posters and materials that reflect diverse individuals in same-gender relationships, and sexual assault evidence collection that recognizes same-gender sexual relationships as well as the unique medical and social needs of gender minority people. To integrate such strategies, providers should receive education on SGM competency, since many are not provided with this specialized training during their formal education (Obedin-Maliver et al., 2011). Qualitative research with SGM students can further elucidate ways in which to make campus-based health and SV services more culturally relevant and inclusive.

In our study, cisgender women and SGMs had higher SV knowledge, prevention behaviors, and care-seeking behaviors, even when controlling for SV history. Thus, experiencing SV victimization is likely not the primary driver of our findings. Instead, there are likely alternative explanations for why vulnerable populations had higher scores. Existing literature suggests having a relationship with a perpetrator or victim increases intentions to intervene (Burn, 2009), and having a friend or colleague who has experienced SV predicts fewer pro-rape attitudes and greater willingness to intervene (Banyard, 2008; Talbot et al., 2010). Thus, regardless of personal SV history, these populations possibly have a greater likelihood of knowing a victim of SV, and therefore have greater SV knowledge and prevention behaviors. Future qualitative research ought to explore mechanistic drivers of the gender and sexual orientation differences in SV knowledge, prevention behaviors, and care-seeking behaviors found in our study.

Our paper adds to the nascent knowledge about sexual violence among college students who have never had sex. We found that people who reported never having had vaginal or anal sex had higher recognition of SV and sexual risk and lower odds of SV service use compared with people who had opposite gender-only sexual partners. Notably, 40.5% of people who never had vaginal or anal sex reported experiencing sexual violence victimization in their lifetime. Given the dearth of knowledge about this subgroup, further research is warranted to ensure that sexual health programming, SV prevention, and SV services can be tailored to meet their needs. This includes revising and refining messages that make assumptions about sexual activity and exposure to sexual violence.

Limitations

Our findings must be considered within our study’s limitations. Our study was conducted with a sample seeking care in a medical setting that agreed to participate in a cluster-randomized controlled trial located in Pennsylvania and West Virginia, and the sample is comprised largely of cisgender women; therefore, our results may not generalize. We analyzed cross-sectional baseline data, limiting our ability to infer causality. Though our analyses included over 2,000 participants, there were only 25 transgender/nonbinary people; though this number is small, we were able to detect significant differences across many of our examined outcomes, suggesting that statistical power was not limited. Nevertheless, we were unable to parse out effects for different subgroups of gender minority people (e.g., transgender men versus transgender women versus non-binary people), which is worthy of future examination. We used sexual behavior as a measure of sexual orientation—and this item did not focus on consensual or non-consensual sexual behaviors; it is unclear how our results may have changed if we utilized sexual identity or sexual attractions. Despite using validated scales that are widely used in studies on SV, there are no known “clinically meaningful” levels for each of these constructs. We do not know what levels of knowledge and self-efficacy effectively translate into behavior or action, and items were self-reported making them vulnerable to social desirability bias.

Conclusions

Our study addresses a public health problem plaguing college campuses: sexual violence. Populations most vulnerable to SV victimization, such as SGMs and cisgender women, generally have greater SV knowledge, prevention behaviors, and care-seeking behaviors than cisgender heterosexual men. In addition to increasing SV-related knowledge and prevention behaviors among cisgender heterosexual men, our study suggests the need for new theories and research examining the mechanistic drivers of gender and sexual orientation inequities in SV on college campuses if we want to design and implement interventions that effectively reduce SV perpetration against the most vulnerable populations.

Implications and Contribution.

College students most vulnerable to sexual violence (SV)—cisgender women, sexual minority individuals, and gender minority people—generally have higher SV knowledge, prevention behaviors, and care-seeking behaviors than heterosexual cisgender men. To reduce SV inequities, the field will likely need to identify new intervention targets and design tailored intervention programs.

Sources of Funding

The National Institute on Alcohol Abuse and Alcoholism (R01AA023260, K01AA027564, and K23AA027288), the National Center for Advancing Translational Sciences (TL1TR001858), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (T32HD087162) of the National Institutes of Health supported this research article. This work was presented at 2019 Prevention Conference, the Annual Meeting of the American College of Preventive Medicine. The opinions expressed in this work are those of the authors and do not necessarily represent those of the funders. Funders had no role in the study design, data collection, analysis, interpretation, manuscript preparation, or the decision to submit for publication.

Abbreviations

CI

confidence interval

OR

odds ratio

SGM

sexual and gender minority

SV

sexual violence

Footnotes

Disclosure of Potential Conflicts of Interest

Dr. Miller receives royalties for writing content for UpToDate, Wolters Kluwer. The other authors had no conflicts.

Research involving Human Participants

The Human Research Protections Office at the University of Pittsburgh approved all study procedures. Most of the 28 schools chose to use the University of Pittsburgh’s IRB approval; additional IRB approval was received from three schools that required their own IRB committees to review the study protocol.

Informed Consent

All participants provided informed consent.

Clinical Trials Registry Site and Number

Data from this study were collected as part of the Clinical Trials #NCT02355470 (University of Pittsburgh).

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The Human Research Protections Office at the University of Pittsburgh approved all study procedures (IRB approval number: PRO14050158). Most of the 28 schools chose to use the University of Pittsburgh’s IRB approval; additional IRB approval was received from three schools that required their own IRB committees to review the study protocol.

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