Rape Myth Acceptance Among Lesbian,Gay,Bisexual,and Mostly Heterosexual College Students

Abstract

Although there is a wealth of existing research on various correlates and patterns of rape myth acceptance (RMA), including how RMA relates to homophobia (i.e., antigay and antilesbian perspectives) and negativity toward lesbian, gay, and bisexual (LGB) men and women rape victims, no research to date has specifically focused on RMA among LGB and “mostly heterosexual” men and women. The current study examines how gender, sexual identity, personal experiences with rape (i.e., knowing/being a survivor), feminist identity, patriarchal gender norms, attitudes toward lesbian, gay, bisexual, and transgender (LGBT) people, and the interactions among these relate to LGB college students’ (n = 389; 24% gay/lesbian, 19% bisexual, 57% mostly heterosexual) RMA using the Illinois Rape Myth Acceptance Scale–Short Form. Findings show that being a woman, being LGB, identifying as a feminist, and knowing/being a survivor are all negatively related to RMA, whereas patriarchal gender norms are positively related to RMA. Attitudes toward LGBT people had differing effects whereby attitudes toward gay men were unassociated with RMA, attitudes toward lesbian women and trans men were negatively associated with RMA, and attitudes toward bisexual men and women and trans women differed depending on the comparison reference group (exclusive heterosexuals, n = 1,551, mostly heterosexuals, n = 222). Furthermore, the interacting effects of these identities, experiences, and perspectives also revealed significant findings that add complexity to these relationships. Overall, this research seeks to fill the gaps in the literature, expand our knowledge about rape myths, and contribute to new lines of inquiry that focus on LGB people’s perspectives to work toward a deeper understanding of rape myths, so that ultimately, these damaging perspectives can be dispelled.

Keywords

rape myth acceptance gay lesbian bisexual gender sexual identity

There is a wealth of existing research on various correlates and patterns of rape myth acceptance (RMA; for example, Burt, 1980; Payne, Lonsway, & Fitzgerald, 1999; Suarez & Gadalla, 2010), including how RMA relates to homophobia (i.e., antigay and antilesbian perspectives, Aosved & Long, 2006; Davies, Gilston, & Rodgers, 2012; Suarez & Gadalla, 2010) and negativity toward lesbian, gay, and bisexual (LGB) men and women rape victims (e.g., Davies et al., 2012; White & Kurpius, 2002). However, no studies to date have specifically focused on RMA among LGB and “mostly heterosexual” men and women. In the handful of RMA studies that do include lesbian, gay, or bisexual respondents, there are too few LGB respondents to draw any meaningful conclusions. Indeed, multiple studies have included five or fewer gay and/or bisexual respondents in their research on RMA (e.g., Bohner, Siebler, & Schmelcher, 2006, had four bisexual men and 154 heterosexual men respondents; Locke & Mahalik, 2005, had 249 heterosexual men, two gay men, and three bisexual men respondents; Peterson & Muehlenhard, 2004, had three bisexual women and 83 heterosexual women respondents), only one study could be located that included lesbian women (Aosved & Long, 2006, had two lesbian women, four gay men, six bisexual people with unspecified genders, and 977 heterosexual respondents), and no RMA studies included those identifying as “mostly heterosexual.” Davies and McCartney (2003) did include gay men’s perspectives (n = 50) about a depicted male rape and their findings showed that gay men were significantly less likely to support rape myths than heterosexual women and men (n = 100) and that gay men viewed male rape to be more severe and were less likely to blame the male rape victim when compared with heterosexual men. Such results suggest that gay men may differ from heterosexuals in their perspectives about rape but certainly much more research is needed to understand these findings. Furthermore, researchers have yet to carefully explore lesbian, bisexual, or mostly heterosexual individuals’ attitudes toward rape.

It is important to examine LGB people’s RMA for several reasons. First, LGB people are significantly more likely to be sexual assault victims when compared with heterosexual men and women (Balsam, Rothblum, & Beauchaine, 2005). Second, LGB people have been found to be less homophobic, less sexist, less supportive of patriarchal gender norms, and more likely to support feminism than heterosexual men (Worthen, under review). Third, no existing research has carefully examined rape myth attitudes among lesbian, gay, bisexual, and mostly heterosexual men and women. Together, this suggests that LGB people may be more likely to have personal experiences with rape and less likely to adhere to many of the established perspectives that have been found to be associated with RMA among heterosexuals. Yet it is unclear how these experiences and perspectives relate to RMA among LGB people.

Furthermore, the roles of gender and sexual identity as they relate to RMA among LGB people have yet to be explored. This is particularly important to examine because we know, for example, that heterosexual men are overwhelmingly more likely to support rape myths when compared with heterosexual women (e.g., Burt, 1980; Suarez & Gadalla, 2010) but we do not know if these same gendered patterns in rape myth support uphold when examining LGB people’s perspectives. In addition, there are multiple negative events that have been found to be associated with RMA among heterosexuals including rape proclivity among heterosexual men and rape denial among heterosexual women (e.g., Bohner et al., 2006; Peterson & Muehlenhard, 2004). However, without examining LGB people’s perspectives about rape myths, we are unable to fully understand how RMA may be associated with such problematic events for LGB people and we are less able to work toward dispelling these myths among LGB people. In addition, bisexual college women’s increased likelihood of experiencing sexual assault (Cantor et al., 2015) may relate to their significantly lower RMA when compared with gay and bisexual men and lesbian women, but without specifically investigating the intersections between gender and sexual identity among LGB people’s RMA, these relationships are speculative. As a result, it is essential to examine LGB people’s RMA.

In the current study, I explore RMA using a sample of LGB college students enrolled at university in the southern United States (n = 389; 24% gay/lesbian, 19% bisexual, 57% mostly heterosexual). Specifically, I examine how personal experiences with rape (i.e., knowing/being a survivor), established perspectives found to be associated with RMA in research among heterosexuals (i.e., feminist identity, patriarchal gender norms, attitudes toward gay men and lesbian women), and attitudes toward bisexual and trans men and women relate to LGB college students’ RMA using the Illinois Rape Myth Acceptance Scale–Short Form (IRMA-SF; Payne et al., 1999). In addition, I explore the interactions among gender, sexual identity, knowing/being a survivor, feminist identity, patriarchal gender norms, and lesbian, gay, bisexual, and transgender (LGBT) attitudes to better understand RMA among LGB men and women. Overall, this research seeks to fill the gaps in the literature, expand our knowledge about rape myths, and contribute to new lines of inquiry that focus on LGB people’s perspectives. In doing so, the current study works toward a deeper understanding of rape myths so that ultimately, these damaging perspectives can be dispelled.

RMA and LGB Identities

Rape myths have been identified as “prejudicial, stereotyped, or false beliefs about rape, rape victims, and rapists” (Burt, 1980, p. 217). Using heterosexual samples, ample research finds that RMA perpetuates problematic falsities surrounding rape. In particular, those who support and accept rape myths are likely to deny or minimize injuries associated with rape, blame victims for their own victimization, absolve the perpetrator from responsibility, perpetrate sexual aggression, and protect nonvictims from feeling vulnerable (Burt, 1980; Payne et al., 1999). Thus, rape myths distort the realities of rape and have many problematic consequences; so it is essential to explore the correlates of these damaging beliefs among lesbian, gay, bisexual, and mostly heterosexual men and women and expand the scope of the existing literature beyond its current focus on heterosexuals’ perspectives. Below, I review research regarding RMA and LGB people as related to (a) personal experiences with rape and sexual assault, (b) gender, and (c) perspectives and attitudes.

RMA, Personal Experiences With Rape, and LGB People

LGB people are significantly more likely than heterosexual people to experience rape and sexual assault (Balsam et al., 2005). In addition, compared with heterosexual women, mostly heterosexual women are at a higher risk for sexual victimization (Austin, Roberts, Corliss, & Molnar, 2008). Furthermore, compared with lesbian women and gay men, bisexual men and women are more likely to report lifetime sexual violence (Balsam et al., 2005). Among college students, bisexual women indicate significantly more nonconsensual sexual contact while enrolled in college as compared with bisexual men, heterosexual, gay, and lesbian women and men (Cantor et al., 2015). Such findings suggest that LGB people, including those identifying as “mostly heterosexual,” have more personal experiences with rape than heterosexual people and that bisexual men and women may endure the most frequent experiences with sexual victimization among these groups. In addition, because those who are more likely to be victimized themselves (e.g., women, sorority women, Black women) have been found to be more likely to know a sexual assault victim (as compared with men, fraternity men, and Asian men, respectively; Anderson, Cooper, & Okamura, 1997; Sorenson, Joshi, & Sivitz, 2014), we may also expect that LGB people, and perhaps bisexuals in particular, might be especially likely to know sexual assault victims. Furthermore, being and/or knowing a sexual assault victim is associated with lower RMA among heterosexual respondents (Anderson et al., 1997; Anderson et al., 1998; Navarro & Tewksbury, 2017); however, no research to date has explored these associations among LGB respondents.

There may also be important distinctions between knowing a man sexual assault survivor and knowing a woman sexual assault survivor. In the only study to date that could be located that specifically examined the effects of knowing a man sexual assault survivor, Worthen and Wallace (under review) found that knowing a man survivor is significantly less common than knowing a woman sexual assault survivor among college students. Furthermore, among those who knew man survivors, 37% were LGB. Additional research shows that men sexual assault victims are treated very differently than women sexual assault victims and endure unique stigmatizing experiences that can relate to perceived or actual gay identities associated with men victims (Davies et al., 2012; Struckman-Johnson & Struckman-Johnson, 1992). Moreover, compared with knowing a woman sexual assault survivor, knowing a man sexual assault survivor has been found to have different effects on perspectives about rape and sexual assault (Worthen & Wallace, under review). Thus, knowing a man survivor may be an indicator of more heightened awareness about the complexities of rape and sexual assault. Together, these findings suggest that it is important to explore both knowing a man sexual assault survivor and/or knowing a woman sexual assault survivor as they may relate to RMA among LGB respondents.

RMA, Gender, and LGB People

One of the most consistent findings across multiple studies is that men are overwhelmingly more likely to support rape myths when compared with women (e.g., Aosved & Long, 2006; Burt, 1980; Hayes-Smith & Levett, 2010; Navarro & Tewksbury, 2017; Payne et al., 1999). Indeed, in their meta-analysis of 37 studies, Suarez and Gadalla (2010) found that men had significantly higher RMA when compared with women; thus, this “gender gap” in RMA is notable and robust. Furthermore, RMA has different gendered effects and relates to many problematic events. For example, researchers have documented how the endorsement of RMA relates to increased rape proclivity among men and rape denial among women rape victims (e.g., Bohner et al., 2006; Peterson & Muehlenhard, 2004).

However, studies that explore RMA and the intersections between gender and sexual identity are extremely limited. As previously noted, nearly all past studies that have included lesbian, gay, or bisexual respondents have included fewer than five LGB respondents (e.g., Bohner et al., 2006; Locke & Mahalik, 2005; Peterson & Muehlenhard, 2004) and no studies to date have carefully examined rape myth attitudes among lesbian, bisexual, or mostly heterosexual men and women. At least one study (Davies & McCartney, 2003) provides evidence of meaningful differences in RMA by gender and sexual identity, with gay men (n = 50) less likely to support rape-of-men-by-men myths compared with heterosexual men and women (n = 100). But overall, it is unknown if there is a “gender gap” in RMA endorsement among LGB people and thus, it is unclear how such perspectives may relate to problematic events in LGB people’s lives. As a result, rape myth attitudes among lesbian, gay, bisexual, and mostly heterosexual men and women deserve further exploration.

RMA, Perspectives and Attitudes, and LGB People

Numerous perspectives and attitudes have been found to be associated with RMA including negativity toward certain groups (i.e., heterosexism, classism, ageism, racism, hostility toward women, sexism—including traditional “sex role” stereotypes that support patriarchy and homophobia) as well as religious intolerance and the endorsement of violence, sexual aggression, and adversarial heterosexual sexual arrangements (Aosved & Long, 2006; Burt, 1980; Payne et al., 1999; Suarez & Gadalla, 2010). Furthermore, research with college women finds that RMA is associated with negative attitudes toward feminism (Senn & Radtke, 1990). Additional work focusing on college men finds that adherence to specific hetero-masculine norms (i.e., having power over women, believing that emotional involvement in sexual relationships is not a good idea, disdaining gay men, being dominant, being violent, and taking risks) relates to both higher RMA and participation in sexually aggressive behavior (Locke & Mahalik, 2005).

Many of these perspectives and attitudes associated with RMA have been found to be more common among heterosexual men compared with heterosexual women. For example, heterosexual men report more patriarchal, homophobic, antigay, antilesbian, and antifeminist perspectives than heterosexual women report (e.g., Eliason, 1997; Herek, 1988; Hinrichs & Rosenberg, 2002; Negy & Eisenman, 2005; Worthen, 2012, 2016); There are also similar gender differences in these perspectives among gay, bisexual, and mostly heterosexual men as compared with lesbian, bisexual, and mostly heterosexual women (though not as robust; see Worthen, under review) and this may contribute to similar gendered patterns in RMA among LGB men and women.

Although not explored in any previous work to date, attitudes toward bisexual men and women may also be related to RMA. Similar to homophobic, antigay, and antilesbian perspectives that have been found to be related to RMA in past studies (e.g., Aosved & Long, 2006; Locke & Mahalik, 2005; Suarez & Gadalla, 2010), antibisexual perspectives demonstrate less support of sexual diversity and more restrictive understandings of sexuality, both of which have also been found to be associated with RMA (e.g., Suarez & Gadalla, 2010). Bisexuality among women in particular is sexualized in American culture, especially among heterosexual men (Rupp & Taylor, 2010; Worthen, 2013). The sexualization of bisexual women may relate to RMA because women participating in public displays of bisexuality are sometimes thought to be seeking the attention of heterosexual men because they know bisexuality is a sexual turn-on to them (Rupp & Taylor, 2010). Thus, bisexual women may be perceived as in part “asking for it” due to their sexualized cultural presence and as a result, there may be a significant relationship between attitudes toward bisexual women and RMA.

Hostility directed toward bisexual men and women among gay men and lesbian women may also relate to RMA. For example, Weiss (2004) suggested that there is a wedge through the GLBT acronym that creates a “GL vs BT” scenario that separates gay/lesbian issues from bisexual/transgender issues (p. 25; see also Welzer-Lang, 2008). Indeed, studies show that both gay men and lesbian women have negative and dismissive attitudes about bisexuality among men and women (Brewster & Moradi, 2010; Weiss, 2004; Welzer-Lang, 2008) and that lesbian women in particular indicate resentment toward bisexual women who can benefit from appearing to be in “heterosexual” relationships with men (Rust, 1995). Due to antagonism toward bisexuality and a belief that “bisexuals just want to have their cake and eat it too” (Weiss, 2004, p. 45), gay men and lesbian women may perhaps attribute some blameworthiness to women—including and perhaps especially bisexual women—who are raped by men.

Also unexplored in previous work, attitudes toward trans men and women may relate to RMA. Hostility and negativity toward trans men and women is indicative of cisnormative biases that preference cisgender people (those whose personal gender identity is the same as the sex they were assigned at birth) over noncisgender (i.e., trans) people. Such cisnormative, antitrans perspectives have been found to be related to antifeminist, antigay, and antibisexual perspectives among heterosexual and LGB college students (Worthen, 2016), all of which are also related to RMA (Aosved & Long, 2006; Burt, 1980; Payne et al., 1999; Suarez & Gadalla, 2010). Thus, it stands to reason that antitrans attitudes may also be related to RMA.

Furthermore, gender may further complicate these relationships. For example, compared with women, men have been found to be more antagonistic toward trans people and especially trans women among both heterosexual and LGB samples (Serano, 2007; Worthen, 2016). Indeed, trans women are especially vulnerable to extreme violence from heterosexual men due to their culturally sexualized status as women and their denigrated status as trans (Schilt & Westbrook, 2009). This may also effect RMA because trans women can be conceived of as “tricksters” who mislead others in sexualized situations (Schilt & Westbrook, 2009) and thus may also be perceived of as somehow “deserving” of sexual violence.

Current Study

Using a sample of LGB college students enrolled at a university in the southern United States (n = 389), I examine how personal experiences with rape (i.e., knowing/being a survivor), patriarchal gender norms, feminist identity, and LGBT attitudes relate to RMA using the IRMA-SF (Payne et al., 1999). I also explore the interactions among gender, sexual identity, knowing/being a survivor, feminist identity, patriarchal gender norms, and LGBT attitudes to better understand RMA among lesbian, gay, bisexual, and mostly heterosexual men and women. Overall, this research fills the gaps in the literature by expanding our knowledge about LGB college students’ RMA and works toward a deeper understanding of rape myths so that, ultimately, these damaging perspectives can be dispelled.

Method

Data and Sample Characteristics

The data set was derived from student responses to an online survey written by the author and distributed by mass email to all students enrolled in a large southern university (~24,000). Students were offered a recruitment incentive (the chance to win an iPad). The survey included the IRMA-SF (Payne et al., 1999) as well as items about gender norms, feminism, LGBT attitudes, and other demographics. The LGB sample (n = 389) comprised 20% of the total study sample (N = 1,940) and was 67% women, 76% Caucasian/White, 5% African American/Black, 7% Asian/Pacific Islander, 5% Native American/Alaskan Native, 7% Other race, and 7% Hispanic (of any race). The average age was 23.72 and 11% were freshmen.

Measures

Dependent variable

RMA

Scores derived from the 20-item IRMA-SF (Payne et al., 1999) formed the dependent variable. It includes statements such as “A woman who ‘teases’ men deserves anything that might happen” and “A lot of women lead a man on and then they cry rape” and asks students to indicate their level of agreement with these statements on a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5). Higher scores indicate more RMA.

Independent variables

Gender and sexual identity

Students were asked to provide their gender (man or woman) and their sexual identity (exclusively heterosexual, mostly heterosexual, bisexual, mostly homosexual, and exclusively homosexual). All those identifying as something other than “exclusively heterosexual” were included in the LGB sample (n = 389). Those identifying as “mostly homosexual” (n = 31) and “exclusively homosexual” (n = 64) were collapsed into the two categories of “gay” or “lesbian” in accordance with gender identities of “man” and “woman,” respectively. “Mostly heterosexual” was kept as a distinct category for four reasons. First, college is a place of new personal discovery as well as freedom and many college students are exploring their sexual identities and having diverse sexual feelings and experiences. Thus, especially for college students, “mostly heterosexual” may reflect a new set of sexual interests that have not been solidified into a sexual identity such as “bisexual.” Second, and related, there is likely a qualitative difference between those that identify as “bisexual” and those that identify as “mostly heterosexual.” Indeed, “bisexual” is an identity label that can carry palpable stigma (Worthen, 2013); however, indicating that you are “mostly heterosexual” may not be associated with as much stigma. Third, a large number of students in the current study identified as “mostly heterosexual” (n = 222) but this group is often neglected in previous literature. Some past work with “mostly straight/heterosexual” college women (e.g., Thompson & Morgan, 2008) finds that this group differs from “exclusively straight/heterosexual,” “bisexual,” and “lesbian” women in their same-sex sexual attraction levels and fantasies, which “suggest[s] that mostly straight women inhabit a behaviorally unique space, one that falls between exclusively straight and bisexual women” (p. 19). Finally, “mostly heterosexual” women are at higher risk for sexual victimization when compared with “heterosexual” women (Austin et al., 2008). Together, this demonstrates that examining “mostly heterosexual” as a distinct category is an interesting and potentially fruitful line of inquiry (Savin-Williams & Vrangalova, 2013).

Know a man/woman/any survivor

Students were also asked to respond to two statements on a 5-point Likert-type scale¹ ranging from 1 (strongly disagree) to 5 (strongly agree). Those responding to the statement “In my opinion, I know a woman who has been a victim of sexual assault” with (4) agree or (5) strongly agree were coded as 1 for know a woman sexual assault survivor, all others (those responding with 1 = strongly disagree, 2 = disagree, or 3 = neither agree nor disagree) were coded as 0. Similarly, those responding to the statement “In my opinion, I know a man who has been a victim of sexual assault” with (4) agree or (5) strongly agree were coded as 1 for know a man sexual assault survivor, all others were coded as 0. Another dummy variable was created for those who reported knowing any sexual assault survivor such that those who indicated knowing a woman survivor, a man survivor, or both were coded as 1, all others were coded as 0. It is important to note that the way these survey items were phrased allowed students to include themselves and/or others they know as survivors when responding affirmatively. Thus, these variables include both survivors and those who know survivors.

Feminist Identity, Patriarchal Gender Norms, and Attitudes Toward LGBT People Scales

For feminist identity, students were asked, “Do you think of yourself as a feminist?” with four response options: (a) No, I do not consider myself to be a feminist and I disagree with feminism. (b) No, I do not consider myself to be a feminist. (c) Yes, I consider myself to be a feminist. (d) Yes, I consider myself to be a strong feminist. The Patriarchal Gender Norms scale included questions about attitudes toward women in the workplace, in the home, and in politics. Higher scores indicate more adherence to patriarchal gender norms. Attitudes toward gay men, lesbian women, bisexual men and women, and trans men and women were measured with the Attitudes toward LGBT People Scales developed by Worthen (2012, 2016); higher scores indicate more positive/supportive attitudes. The appendix lists the individual scale items.

Control variables

Race, age, and freshman

Because race and ethnicity have been found to be related to RMA (Kennedy & Gorzalka, 2002; Lee, Pomeroy, Yoo, & Rheinboldt, 2005; Suarez & Gadalla, 2010), race (Caucasian/White, Black/African American, Asian/Pacific Islander, Native American/Alaskan Native, or “Other”) and Hispanic/Latino ethnicity (regardless of race) are included as controls with Caucasian/White as the reference category. Previous research also indicates that younger people and those early in their student career think about sexual assault differently than older people and those later in their tenure at a university (Suarez & Gadalla, 2010). Thus, age and student classification (collapsed to “freshman” as compared with all others) are also included as controls.

Method of Analysis

In the first set of analyses, the mean values of the independent variables and RMA were compared by gender and sexual identity using ANOVAs and post hoc Tukey–Kramer tests in Table 1. In the second set of analyses, ordinary least squares (OLS) regressions were used to explore the effects of gender and sexual identity, knowing/being a survivor, feminist identity, patriarchal gender norms, and attitudes toward LGBT individuals on RMA. OLS regression was chosen because the dependent variable (RMA) is ordinal and estimates for skewness (.98 entire sample, 1.62 LGB sample) and kurtosis (4.23 entire sample, 6.86 LGB sample) were within the acceptable range of no greater than 3 for skewness and no greater than 10 for kurtosis suggesting that the data did not violate the normality assumption (Kline, 2005).

Table 1.

Mean Values of Independent Variables by Gender and Sexual Identity with ANOVA Results (n = 389).

			Group 1		Group 2		Group 3		Group 4		Group 5		Group 6
			Mostly Heterosexual Men (n = 60)		Mostly Heterosexual Women (n = 162)		Bisexual Men (n = 11)		Bisexual Women (n = 61)		Gay Men(n = 59)		Lesbian Women (n = 36)
	Range	α	M	SD	M	SD	M	SD	M	SD	M	SD	M	SD
Know Any Survivor^a	0-1	—	0.53	0.53	0.75	0.44	0.55	0.52	0.82	0.39	0.66	0.48	0.64	0.49
Know Woman Survivor^b	0-1	—	0.53	0.50	0.73	0.45	0.55	0.52	0.80	0.40	0.53	0.50	0.61	0.49
Know Man Survivor^c	0-1	—	0.37	0.49	0.36	0.48	0.27	0.47	0.31	0.47	0.47	0.50	0.22	0.42
Feminist Identity^d	1-4	—	2.43	0.74	2.91	0.71	2.55	0.69	3.08	0.74	2.73	0.83	2.81	0.52
Patriarchal Gender Norms^e	7-35	.85	11.67	3.79	9.52	3.17	11.64	4.01	8.84	2.78	9.85	4.48	9.41	3.09
Attitudes Toward Gay Men^f	14-70	.93	61.93	8.18	65.49	6.69	64.09	6.82	68.67	2.73	67.53	8.04	63.83	8.76
Attitudes Toward Lesbian Women^g	14-70	.94	62.73	8.35	65.43	6.88	64.73	6.39	68.80	2.60	66.53	8.94	63.97	10.58
Attitudes Toward Bisexual Men^h	5-25	.84	19.58	3.61	20.80	3.57	21.27	3.29	22.79	2.42	20.25	3.46	19.53	4.80
Attitudes Toward Bisexual Womenⁱ	5-25	.85	19.72	3.49	20.89	3.47	21.36	3.32	23.20	2.29	20.15	3.98	19.75	4.77
Attitudes Toward Trans Men^j	3-15	.92	12.23	2.90	13.72	1.98	11.09	2.95	14.56	1.18	13.97	2.00	12.75	3.34
Attitudes Toward Trans Women^k	3-15	.84	11.8	2.92	13.32	2.21	10.91	3.05	14.25	1.46	13.66	2.00	12.92	2.68

Note. The alpha (α) scores for the scales reported here were calculated using the entire LGB sample (n = 389). LGB = lesbian, gay, and bisexual.

F = 3.28, df(5, 383), p < .01; post hoc Tukey–Kramer test: Group 1 ≠ Group 2; Group 1 ≠ Group 4.

F = 3.96, df(5, 383), p < .01; post hoc Tukey–Kramer test: Group 1 ≠ Group 4.

F = 1.47, df(5, 383), ns.

F = 5.99, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 2; Group 1 ≠ Group 4.

F = 5.33, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 2; Group 1 ≠ Group 4; Group 1 ≠ Group 6.

F = 7.20, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 2; Group 1 ≠ Group 4; Group 1 ≠ Group 5; Group 2 ≠ Group 4; Group 4 ≠ Group 6.

F = 4.63, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 4; Group 2 ≠ Group 4; Group 4 ≠ Group 6.

F = 6.51, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 4; Group 2 ≠ Group 4; Group 4 ≠ Group 5; Group 4 ≠ Group 6.

F = 7.80, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 4; Group 2 ≠ Group 4; Group 4 ≠ Group 5; Group 4 ≠ Group 6.

F = 10.72, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 2; Group 1 ≠ Group 4; Group 1 ≠ Group 5; Group 2 ≠ Group 3; Group 3 ≠ Group 4; Group 3 ≠ Group 5.

F = 9.99, df(5, 383), p < .001; post hoc Tukey–Kramer test: Group 1 ≠ Group 2; Group 1 ≠ Group 4; Group 1 ≠ Group 5; Group 2 ≠ Group 3; Group 3 ≠ Group 4; Group 3 ≠ Group 5.

The same set of models was estimated with “exclusive heterosexuals” (n = 1,551) as the reference category in Table 2 and with “mostly heterosexuals” (n = 222) as the reference category in Table 3. Because LGB people are the focus of the current study, the first two models focus on LGB identities. Specifically, in Model 1, the baseline effects of gender and sexual identity were estimated along with controls and Model 2 added the interaction effects of gender and sexual identity. Next, the other independent variables were added and include knowing any survivor (only Model 3), knowing a woman survivor and knowing a man survivor (only Model 4), feminist identity, patriarchal gender norms, and attitudes toward LGBT individuals (Models 3 and 4). Finally, interaction effects created by multiplying the gender and sexual identities by the other independent variables (knowing any survivor [only Model 5], knowing a woman survivor and knowing a man survivor [only Model 6], feminist identity, patriarchal gender norms, and attitudes toward LGBT individuals [Models 5 and 6]) were included. A series of power analyses determined that the sample sizes were large enough to yield significant results using Stata command powerreg with power equal to .8 (Cohen, 1988).

Table 2.

OLS Regression Results Predicting the Effects of Gender, Sexual Identity, Experiences, and Attitudes on Rape Myth Acceptance with Interaction Effects (N = 1,940).

	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Gender and sexual identity
Woman	−5.16*	−5.50*	−2.49*	−2.39*	−2.56*	−2.44*
Mostly heterosexual	−1.93*	−2.63*	1.14	1.13	1.00	0.95
Bisexual	−4.32*	−1.76	1.83	1.87	1.59	1.63
Gay/lesbian	−3.28*	−5.63*	0.83	0.54	0.68	0.31
Gender × Sexual Identity interaction effects
Woman × Mostly Heterosexual		1.04	1.00	0.93	26.73*	26.71*
Woman × Bisexual		−2.90	−1.18	−1.26	4.72	8.91
Woman × Lesbian		6.02*	1.81	2.04	−18.49	−17.86
Experiences and attitudes
Know any survivor			−1.56*		−1.55*
Know woman survivor				−1.89*		−1.91*
Know man survivor				0.59		0.85
Feminist identity			−0.25	−0.21	0.01	0.05
Patriarchal gender norms			0.68*	0.68*	0.69*	0.69*
Attitudes toward gay men			−0.04	−0.04	−0.05	−0.04
Attitudes toward lesbian women			−0.11*	−0.11*	−0.12*	−0.12*
Attitudes toward bisexual men			−0.24	−0.26	−0.28	−0.29*
Attitudes toward bisexual women			0.05	0.06	0.13	0.14
Attitudes toward trans men			−1.16*	−1.17*	−1.19*	−1.20*
Attitudes toward trans women			0.87*	0.90*	0.90*	0.89*
Controls
African American/Black	0.23	0.36	−1.15	−1.17	−1.17	−1.18
Asian/Pacific Islander	5.39*	5.37*	3.78*	3.79*	3.74*	3.77*
Native American/Alaskan	1.02	1.08	1.28	1.30	1.16	1.20
Other race	1.32	1.26	0.98	.93	0.96	0.91
Hispanic/Latino	−0.85	−0.74	−0.87	−.85	−0.84	−0.80
Age	−0.13*	−0.13*	−0.08*	−.08*	−0.08*	−0.08*
Freshman	2.92*	2.97*	1.15*	1.19*	1.12*	1.17*
Adjusted R²	.13	.13	.44	.44	.44	.44

Note. Reference category is “exclusive” heterosexuals (n = 1,551). OLS = ordinary least squares. Models 5 and 6 also included 33 interaction effects created by multiplying gender (woman) by sexual identity (mostly heterosexual, bisexual, lesbian) by experiences and attitudes (know any survivor, know woman survivor, know man survivor, feminist identity, patriarchal gender norms, as well as attitudes toward gay men, lesbian women, bisexual men, bisexual women, trans men and trans women). Because none of these interaction effects were significant, they are not presented here.

p < .05.

Table 3.

OLS Regression Results Predicting the Effects of Gender, Sexual Identity, Experiences, and Attitudes on Rape Myth Acceptance with Interaction Effects Among LGB College Students (n = 389).

	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
Gender and sexual identity
Woman	−3.49*	−4.69*	−0.33	−0.42	−0.09	−0.12
Bisexual	−2.79*	0.36	0.35	0.33	0.14	0.19
Gay/lesbian	−1.22	−3.79*	−0.04	−0.28	0.19	−0.10
Gender × Sexual Identity interaction effects
Woman × Bisexual		−3.55	−0.87	−0.88	−3.15	−1.49
Woman × Lesbian		5.57*	0.59	0.78	−34.34*	−33.90*
Experiences and attitudes
Know any survivor			−1.96*		−2.25*
Know woman survivor				−1.81*		−2.23*
Know man survivor				−0.35		0.06
Feminist identity			−1.51*	−1.49*	−1.51*	−1.53*
Patriarchal gender norms			0.85*	0.85*	0.78*	0.78*
Attitudes toward gay men			0.11	0.11	−0.10	−0.10
Attitudes toward lesbian women			−0.26*	−0.27*	−0.27*	−0.28*
Attitudes toward bisexual men			0.68*	0.68*	0.78*	0.76*
Attitudes toward bisexual women			−0.92*	−0.91*	−1.01*	−1.00*
Attitudes toward trans men			−0.77*	−0.79*	−0.83*	−0.88*
Attitudes toward trans women			0.27	0.30	0.16	0.23
Gender × Sexual Identity × Attitudes interaction effects
Woman × Lesbian × Patriarchal Gender Norms					0.82*	0.77
Controls
African American/Black	2.89	3.32	−1.45	−1.45	−0.81	−0.81
Asian/Pacific Islander	6.60*	6.67*	2.57*	2.62*	2.49*	2.57*
Native American/Alaskan	−0.73	−0.57	−0.40	−0.49	−0.04	−0.06
Other race	0.81	0.51	−1.18	−1.18	−0.50	−0.44
Hispanic/Latino	1.48	1.86	0.91	1.00	0.86	0.93
Age	0.01	−0.01	−0.02	−0.02	−0.01	−0.01
Freshman	1.87	2.07	0.96	0.99	0.92	0.96
Adjusted R²	.08	.10	.57	.57	.58	.57

Note. Reference category is “mostly” heterosexuals (n = 222). OLS = ordinary least squares; LGB = lesbian, gay, and bisexual. Models 5 and 6 also included 22 interaction effects created by multiplying gender (woman) by sexual identity (bisexual, lesbian) by experiences and attitudes (know any survivor, know woman survivor, know man survivor, feminist identity, patriarchal gender norms, as well as attitudes toward gay men, lesbian women, bisexual men, bisexual women, trans men and trans women). The single significant interaction effect is presented here.

p < .05.

Results

Mean Comparisons

In Table 1, ANOVA and post hoc Tukey–Kramer test results reveal significant gender and sexual identity differences in means whereby mostly heterosexual men are less likely to indicate knowing any survivors as compared with mostly heterosexual and bisexual women with percentages ranging from 53% (mostly heterosexual men) to 82% (bisexual women). Mostly heterosexual men are also significantly less likely to indicate knowing a woman survivor as compared with bisexual women with percentages ranging from 53% (mostly heterosexual men) to 80% (bisexual women). There are no significant differences in knowing a man survivor although percentages range from 22% (lesbian women) to 47% (gay men). Mostly heterosexual men are significantly lower on feminist identity and higher on patriarchal gender norms than mostly heterosexual and bisexual women as well as lesbian women (for patriarchal gender norms only).

Mostly heterosexual men are significantly more anti-LGBT on all six scales of attitudes toward LGBT individuals as compared with most other groups. Specifically, mostly heterosexual men are significantly less supportive of gay men than mostly heterosexual women, bisexual women, and gay men are. In contrast, bisexual women are significantly more supportive of gay men than mostly heterosexual women and lesbian women are. Mostly heterosexual men are significantly less supportive of lesbian women than bisexual women are. Interestingly, bisexual women are significantly more supportive of lesbian women than mostly heterosexual women and lesbian women are. Bisexual women also indicate significantly more support of bisexual men and women as compared with all other groups except bisexual men who do not differ from bisexual women in their attitudes. Both mostly heterosexual men and bisexual men are significantly less supportive of trans men and trans women than mostly heterosexual women, bisexual women, and gay men are.

In Figure 1, box and whisker plots reveal visual differences with bisexual women indicating the lowest RMA as demonstrated by the lowest outlier value (49), median (33), and interquartile range (5). Not surprisingly, heterosexual men have the highest RMA as demonstrated by the highest outlier value (100), median (43), and interquartile range (16). Interestingly, mostly heterosexual men, bisexual men, and lesbian women appear to be somewhat similar in RMA according to medians (mostly heterosexual men, 39.5; bisexual men, 38; lesbian women, 36) and interquartile ranges (mostly heterosexual men, 14.5; bisexual men, 14; lesbian women, 13.5). In addition, gay men and mostly heterosexual women appear to be somewhat similar in RMA according to medians (gay men, 35; mostly heterosexual women, 34) and interquartile ranges (gay men, 9; mostly heterosexual women, 10), although the highest outlier value is much higher for gay men (84) than it is for mostly heterosexual women (63). Overall, ANOVA and post hoc Tukey–Kramer test results reveal significant gender and sexual identity differences in means with mostly heterosexual men having significantly higher RMA than mostly heterosexual and bisexual women. In addition, heterosexual men have significantly higher RMA as compared with all groups except mostly heterosexual and bisexual men.

Figure 1.

Box and whisker plot of rape myth acceptance by gender and sexual identity with ANOVA results.

OLS Regression Results

In Table 2, Model 1 estimates the baseline effects of gender and sexual identity as they relate to RMA with “exclusively heterosexual” as the reference category. Although the focus of the current study is on LGB college students’ perspectives, the inclusion of exclusive heterosexuals as the reference category allows us to draw comparisons between these groups. Being a woman is a robust and significant negative predictor of RMA across all six models. In addition, in Model 1, being mostly heterosexual, bisexual, and gay/lesbian (as compared with being exclusively heterosexual) are significantly negatively related to RMA. Model 2 includes gender and sexual identity interaction effects. Being bisexual is no longer significant and the interaction effect between lesbian and woman is positive and significantly related to RMA. In Model 3, only being a woman remains significantly negatively related to RMA among the gender and sexual identity measures. Furthermore, knowing any survivor, attitudes toward lesbian women, and attitudes toward trans men are negatively related to RMA, whereas patriarchal gender norms and attitudes toward trans women are positively related to RMA. In Model 4, there is a similar pattern of results; however, knowing a woman survivor and knowing a man survivor were included instead of knowing any survivor but only knowing a woman survivor is significantly negatively related to RMA.

Additional interaction effects among experiences and attitudes are included in Model 5 and being a mostly heterosexual woman is now positively and significantly related to RMA. Similar to Model 3, being a woman, knowing any survivor, attitudes toward lesbian women, and attitudes toward trans men are negatively related to RMA, whereas patriarchal gender norms and attitudes toward trans women are positively related to RMA in Model 5. While none of the interaction effects among experiences and attitudes are significant at the p < .05 level, one approached significance: The interaction effect between woman, mostly heterosexual, and feminist identity approached a significant negative relationship to RMA (p = .06). In Model 6, being a woman is negatively related to RMA, whereas being a mostly heterosexual woman is positively related to RMA. Also, knowing a woman survivor is significantly negatively related to RMA, whereas knowing a man survivor approaches a significant positive relationship to RMA (p = .10). In addition, attitudes toward lesbian women, bisexual men, and trans men are negatively related to RMA, whereas patriarchal gender norms and attitudes toward trans women are positively related to RMA. As in Model 5, the same interaction effect approached significance: the interaction effect between woman, mostly heterosexual, and feminist identity approached a significant negative relationship to RMA (p = .06). Across all models, being Asian/Pacific Islander and being a freshman are positively related to RMA, whereas age is negatively related to RMA. The inclusion of experiences and attitudes in Models 3 to 6 significantly increased the adjusted R² values from .13 to .44.

In Table 3, Model 1 estimated the baseline effects of gender and sexual identity as they related to RMA with “mostly heterosexual” as the reference category and thus focuses exclusively on LGB college students’ perspectives and differences among them. Both being a woman and being bisexual were significantly negatively associated with RMA; however, being gay/lesbian was not significantly related to RMA. In Model 2, the interaction effects of gender and sexual identity were added. Both being a woman and being gay/lesbian remained significantly negatively associated with RMA; however, being a lesbian woman was positively associated with RMA in Model 2. In Model 3, there were no significant effects for gender or sexual identity but knowing any survivor, feminist identity, and attitudes toward lesbian women, bisexual women, and trans men were all negatively and significantly related to RMA. In contrast, patriarchal gender norms and attitudes toward bisexual men were positively related to RMA. In Model 4, there were no significant effects for gender or sexual identity. Knowing a woman survivor and knowing a man survivor were included instead of knowing any survivor but only knowing a woman survivor was significantly related to RMA. In addition, feminist identity and attitudes toward lesbian women, bisexual women, and trans men were all negatively and significantly related to RMA, whereas patriarchal gender norms and attitudes toward bisexual men were positively related to RMA in Model 4.

In Model 5, being a lesbian woman was negatively associated with RMA, as were knowing any survivor, feminist identity, and attitudes toward lesbian women, bisexual women, and trans men, whereas patriarchal gender norms and attitudes toward bisexual men were positively related to RMA in Model 5. There was one significant interaction effect among the attitudes and experiences in Model 5: the interaction effect between woman, lesbian, and patriarchal gender norms was positively related to RMA. In Model 6, being a lesbian woman, knowing a woman survivor, feminist identity, and attitudes toward lesbian women, bisexual women, and trans men were negatively related to RMA, whereas patriarchal gender norms and attitudes toward bisexual men were positively related to RMA. The interaction effect between woman, lesbian, and patriarchal gender norms as positively related to RMA approached significance (p = .06) in Model 6. Across all models, being Asian/Pacific Islander was the only significant control variable and was positively related to RMA. The inclusion of experiences and attitudes in Models 3 to 6 significantly increased the adjusted R² values from .08 to .10, to .57 to .58.

Discussion

The current study examined LGB college student’s RMA with a focus on gender, sexual identity, knowing/being a survivor, feminist identity, patriarchal gender norms, LGBT attitudes and the intersections between these identities, experiences, and attitudes. Consistent with previous work focusing on heterosexuals (e.g., Aosved & Long, 2006; Burt, 1980; Hayes-Smith & Levett, 2010; Navarro & Tewksbury, 2017; Payne et al., 1999; Suarez & Gadalla, 2010), there was a “gender gap” in RMA found in the current study. Although the negative effect of being a woman on RMA was robust and significant across all models using exclusive heterosexuals as a reference group (see Table 2), the main effect of being a woman on RMA in models that exclusively included LGB students (see Table 3), was only significant in models with basic sociodemographic variables (i.e., Models 1 and 2); subsequent models that included experiences and attitudes did not reveal a significant relationship between being a woman and RMA. Furthermore, the adjusted R² values for these models were lower in the LGB-only models (.08 and .10) as compared with the adjusted R² values for the same models that used exclusive heterosexuals as the reference category (.13). This suggests that being a woman is not a very robust predictor of RMA among LGB college students. This contrasts with previous studies with heterosexual-only samples that find that gender has among the strongest relationships with RMA (e.g., Suarez & Gadalla, 2010).

Overall, the current study’s focus on LGB college students revealed a pattern in RMA whereby being a woman was not as consistently or as robustly related to RMA as found in previous work with heterosexuals. There are two likely reasons for this. First, the robust RMA gender gap among heterosexuals can be attributed to a variety of perspectives that are significantly more common among heterosexual men than heterosexual women (e.g., patriarchal, homophobic, antigay, antilesbian, and antifeminist perspectives; Eliason, 1997; Herek, 1988; Hinrichs & Rosenberg, 2002; Negy & Eisenman, 2005; Worthen, 2012, 2016). However, among LGB men and women, gender differences in these perspectives are not as extreme (Worthen, under review). Thus, the RMA gender gap may be more pronounced among heterosexuals because heterosexual men and women differ more than LGB men and women do in their perspectives about issues associated with RMA. Second, compared with heterosexual men, heterosexual women indicate more accurate knowledge about sexual assault prevalence and they are more likely to be and/or know sexual assault victims (all of which relate to lower RMA; Anderson et al., 1997; Cantor et al., 2015; Sorenson et al., 2014; Worthen & Wallace, 2017). Among LGB men and women, gender differences in sexual assault knowledge and victimization are not as extreme (Balsam et al., 2005; Cantor et al., 2015; Worthen & Wallace, 2017). Thus, the gender gaps in the relationships between being informed about sexual assault and having personal experiences with sexual assault are more pronounced among heterosexuals than among LGB people. Whereas heterosexual men and women differ quite significantly in RMA and its associated underpinnings, LGB men and women are much more similar to one another. As a result, gender plays a stronger role in understanding heterosexuals’ RMA than it does in explaining LGB peoples’ RMA.

Looking at sexual identity, the main effects of being mostly heterosexual, bisexual, and gay/lesbian were all negative and significantly related to RMA but the inclusion of experiences and attitudes washed out these significant effects for both sets of models (see Tables 2 and 3). This suggests that there is a relationship between sexual identity and RMA, but it may not be as robust when compared with other measures. Even so, such findings expand upon Davies and McCartney’s (2003) study that found that gay men were significantly less likely to support rape myths than heterosexual women and men and show that being mostly heterosexual, bisexual, and gay/lesbian are negatively related to RMA. Overall, the current study’s results demonstrate that sexual identity is important to examine in RMA research.

Among the gender and sexual identity interaction effects, being a lesbian woman was positively and significantly related to RMA in Model 2 in both tables. This finding may be related to lesbian women’s biases about women who have relationships with men (i.e., heterosexual, mostly heterosexual, and bisexual women). Indeed, multiple studies have uncovered animosity among lesbian women directed toward bisexual women and other women who have relationships with men (Brewster & Moradi, 2010; Rust, 1995; Weiss, 2004; Welzer-Lang, 2008; Worthen, 2013). These biases may lead to victim blaming and other types of RMA among lesbian women. Furthermore, lesbian women may be generally underinformed about rape. Indeed, most sexual assault education efforts are focused either exclusively or predominantly around heterosexual sexual assault and neglect lesbian women’s experiences (Rothman & Silverman, 2007; Worthen & Baker, 2014; Worthen & Wallace, 2017). The significant relationship between being a lesbian woman and rape myth support found here demonstrates the importance of sexual assault education that includes lesbian women’s experiences and addresses potential biases among lesbian women.

Although the significant effects of being a lesbian woman on RMA were washed out in subsequent models when experiences and attitudes were included, there were two additional significant gender and sexual identity interaction effects that appeared and remained robust. Using heterosexuals as the reference category in Table 2, being a mostly heterosexual woman was strongly positively related to RMA in Models 5 and 6. This finding is likely driven by the inclusion of additional interaction effects. In particular, the interaction effect between woman, mostly heterosexual, and feminist identity approached a significant negative association with RMA (p = .06) demonstrating that among mostly heterosexual women, having a feminist identity is negatively related to RMA. Using mostly heterosexuals as the reference category in Table 3, being a lesbian woman was strongly negatively related to RMA, whereas the interaction effect between woman, lesbian, and patriarchal gender norms was positively related to RMA in Model 5 and approached significance in Model 6 (p = .06). Such findings are in line with previous work that finds similar relationships between feminism, sexism, patriarchy, and RMA among heterosexuals (e.g., Burt, 1980; Payne et al., 1999; Senn & Radtke, 1990; Suarez & Gadalla, 2010) and expand our understandings by including nonheterosexuals’ perspectives.

Even though mostly heterosexual and bisexual women were significantly more likely to know a survivor (75% and 85% respectively), as compared with mostly heterosexual men (53%), knowing any survivor was consistently negatively associated with RMA among both sets of models in Tables 2 and 3, consistent with past research with heterosexuals (Anderson et al., 1997; Anderson et al., 1998; Navarro & Tewksbury, 2017). However, when separated into knowing a woman survivor and knowing a man survivor, only knowing a woman survivor was significantly negatively related to RMA in the models using mostly heterosexuals as the reference category. In contrast, in the models using exclusive heterosexuals as the reference category, knowing a man survivor approached a significant positive relationship to RMA in Model 6 (p = .10). Previous studies demonstrate differences in perspectives toward men victims and women victims (Davies et al., 2012; Struckman-Johnson & Struckman-Johnson, 1992) and in the effects of knowing a woman and man survivor (Worthen & Wallace, under review). The findings here demonstrate that knowing a man survivor is related to the support of rape-of-women-by-men myths and demonstrate the need for further research to investigate these relationships in order to develop sexual assault education efforts that work toward dispelling this complicated constellation of perspectives about rape, gender, and sexual identities.

Feminist identity was consistently negatively related to RMA across all models among LGB college students; however, surprisingly, feminist identity was not significantly related to RMA in the models using exclusive heterosexuals as the reference category, which is contrary to past work (e.g., Senn & Radtke, 1990; Suarez & Gadalla, 2010). Feminist identity, however, was significant in models (not shown) that did not include patriarchal gender norms suggesting that patriarchal norms washed out the significant negative effects of feminist identity on RMA for models that included exclusive heterosexuals as the reference category. Such findings demonstrate that feminist identity is an important negative predictor of RMA among LGB college students and complement existing literature focusing on heterosexuals (e.g., Senn & Radtke, 1990; Suarez & Gadalla, 2010).

Even though mostly heterosexual, bisexual, and lesbian women indicated significantly lower adherence to patriarchal gender norms as compared with mostly heterosexual men, patriarchal gender norms were consistently positively related to RMA across all models as found in previous studies with heterosexuals (e.g., Suarez & Gadalla, 2010). In addition, the only significant (p < .05) interaction effect found in the current study included patriarchal gender norms, demonstrating the robust effect that adherence to restrictive and sexist perspectives about women has on RMA among both heterosexual and LGB college students.

Among the measures of attitudes toward LGBT individuals, attitudes toward gay men were not significantly related to RMA in any model. In contrast, all of the other LBT attitudinal measures were significant but some varied between Tables 2 and 3. When the reference category was exclusive heterosexuals in Table 2, attitudes toward lesbian women, bisexual men, and trans men were negatively related to RMA, whereas attitudes toward bisexual women were not significant and attitudes toward trans women were positively related to RMA. Perhaps those that support lesbian women, bisexual men, and trans men are generally more accepting of and open to gender and sexual diversity and these qualities negatively relate to RMA. Indeed, being sexually conservative and less open to sexual diversity has been found to be positively related to RMA (Suarez & Gadalla, 2010). In addition, support of LBT people may also be indicative of more awareness of the difficulties LGBT people face, including their increased likelihood of experiencing sexual violence (Austin et al., 2008). Indeed, being an LGBT ally has been found to be associated with increased awareness about campus sexual assault (Worthen & Wallace, 2017). Furthermore, the lack of significant findings related to attitudes toward bisexual women and the positive relationship between support of trans women and RMA may relate to the sexualization of these women (Rupp & Taylor, 2010; Schilt & Westbrook, 2009; Worthen, 2013). Indeed, viewing heterosexual women as sexual objects has been found to be related to increased rape myth support (Suarez & Gadalla, 2010) and this type of sexual objectification may also explain the relationships between attitudes toward bisexual and trans women and RMA. Overall, the findings here suggest that being supportive of lesbian women, bisexual men, and trans men likely taps into a set of understandings and perspectives about sexuality and gender that negatively relates to RMA while the sexualization of bisexual and trans women may drive the relationship between attitudes toward bisexual and trans women and RMA.

As with Table 2, in Table 3 when the comparison group was mostly heterosexuals, attitudes toward lesbian women and trans men were negatively related to RMA. However, three findings differed from those in Table 2: attitudes toward bisexual women were negatively related to RMA, attitudes toward bisexual men were positively related to RMA, and attitudes toward trans women were not significantly related to RMA. When focusing on LGB people’s perspectives, support of bisexual women may not be associated with the generally heterosexual male-driven sexual objectification of women’s bisexuality (Rupp & Taylor, 2010; Worthen, 2013) and may instead tap into awareness and support of sexual diversity, which is negatively related to RMA (Worthen & Wallace, 2017). In contrast, LGB people’s support of bisexual men may be associated with the acceptance of male hyper-sexuality and the willingness to engage in sexual activity with a variety of partners outside of romantic relationships, both of which have been found to be positively associated with RMA among heterosexuals (Suarez & Gadalla, 2010; Yost & Zurbriggen, 2006) and are stereotypes commonly associated with bisexual men (Eliason, 1997) that LGB people are likely keenly aware of and may also agree with.

Overall, focusing on LGB people’s perspectives helps us to better understand RMA and demonstrates the significance of incorporating the intersections between gender and sexual identity into future RMA research. Furthermore, expanding the scope of the existing literature beyond its current focus on heterosexuals’ perspectives and examining RMA among lesbian, gay, bisexual, and mostly heterosexual men and women can have far-reaching impacts. In particular, given that we know that RMA perpetuates victim blaming, rape denial, and sexual aggression among heterosexuals (Burt, 1980; Payne et al., 1999), learning how LGB people’s RMA might relate to such problematic beliefs and behaviors is essential because it can arm us with the knowledge to work toward dispelling rape myths among LGB people and contribute to changes to rape culture.

Limitations and Future Research

The current study is limited by the use of one relatively small predominantly White sample at one university located in a southern U.S. state. Even so, one consistent finding across all models was the positive relationship between being Asian/Pacific Islander and RMA as also seen in previous research (Kennedy & Gorzalka, 2002; Lee et al., 2005). However, future studies would benefit from more diverse cross-national investigations of both college and noncollege populations. In addition, this study utilized the IRMA-SF to explore RMA and therefore only focused on rape myths associated with men perpetrators and women victims. Additional work examining rape myths with variations in the gender and sexual identities of perpetrators and victims (e.g., White & Kurpius, 2002) as they relate to LGB people’s RMA would certainly expand this line of inquiry. Furthermore, the measurements of gender and sexual identity were limited and there were no measures of socioeconomic status available. Thus, future work might incorporate more response options to better capture these identities. Finally, it would be especially valuable to examine how additional perspectives known to be associated with RMA among heterosexuals (e.g., classism, ageism, racism, religious intolerance, hostility toward women, endorsement of violence, victim blaming, and sexual aggression; Aosved & Long, 2006; Burt, 1980; Payne et al., 1999; Suarez & Gadalla, 2010) relate to RMA among LGB people. Such prospective work can not only allow us to better understand LGB people’s RMA, but also, can contribute to programming efforts that work toward dispelling RMA among LGB people. Thus, future research should continue to incorporate diverse sociocultural constructs and multiple measures of rape supportive attitudes to best explore how gender and sexual identities relate to RMA.

Footnotes

Appendix

Individual Scale Items.

Attitudes Toward Gay Men and Attitudes Toward Lesbian Women

I wouldn’t mind going to a party that included ____.

I would not mind working with ___.

I welcome new friends who are ___.

I don’t think it would negatively affect our relationship if I learned that one of my close relatives was ___.

I am comfortable with the thought of two ___ being romantically involved.

I would remove my child from class if I found out the teacher was ___.^R

It’s alright with me if I see two ___ holding hands.

I would not vote for a political candidate who was openly ___.^R

_____ shouldn’t be allowed to join the military.^R

Marriages between two ____ should be legal.

_____ are incapable of being good parents.^R

_____ is a psychological disease.^R

Physicians and psychologists should strive to find a cure for ____.^R

______ should undergo therapy to change their sexual orientation.^R

Attitudes Toward Bisexual Men and Attitudes Toward Bisexual Women

Most ____ who call themselves bisexual are temporarily experimenting with their sexuality.^R

Gay men [Lesbians] are less confused about their identity than bisexual ______.^R

Just like homosexuality and heterosexuality, bisexuality is a stable sexual orientation for ____.

As far as I’m concerned, ____ bisexuality is wrong.^R

____ bisexuality is harmful to society because it breaks down natural divisions between the sexes.^R

Attitudes Toward Trans Men and Attitudes Toward Trans Women

If a friend wanted to have his penis removed in order to become a woman, I would openly support him. (Trans Women Scale only)

I would avoid talking to a woman if I knew she had surgically created penis and testicles.^R (Trans Men Scale only)

Men[women] who see themselves as women[men] are disgusting.^R

It is morally wrong for a man[woman] to present himself[herself] as a woman[man] in public.^R

Patriarchal Gender Norms

Women should take care of running their homes and should leave running the country up to men.

If my political party nominated a woman for President, I would vote for her if she was qualified for the job.^R

Women’s sexual needs are just as important as men’s.^R

It is more important for a wife to help her husband’s career than to have one herself.

The household tasks should be evenly divided between both partners in committed relationships.^R

It’s much better for everyone involved if the man is the earner outside the home and the woman takes care of the home and family.

All in all, family life suffers when the woman has a full-time job in heterosexual partnerships.

Note. Response options = strongly disagree to strongly agree. All statements for attitudes toward gay men and lesbian women are from Raja and Stokes’s (1998) Modern Homophobia Scale (MHS-G and MHS-L). All statements for attitudes toward bisexual men and women are from Mohr and Rochlen’s (1999) Attitudes Regarding Bisexual Scale. All statements for attitudes toward trans men and women are from Hill and Willoughby’s (2005) 32-item Genderism and Transphobia Scale. Principal component factor (PCF) analyses were conducted to create all scales. Although an exact number of factors was not requested, each factor analysis revealed only one factor with an eigenvalue greater than 1. Following the initial PCF analysis, the factor solution was optimized using orthogonal varimax rotation. PCF analyses results for the LGBT attitudes scales can be found in Worthen (2012, 2016).

This item was reverse coded to indicate higher numbers are more supportive attitudes.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author would like to thank the University of Oklahoma, Department of Sociology, for funding for this project.

Notes

Author Biography

Meredith G. F. Worthen is an associate professor of sociology and elected faculty member of the women’s and gender studies program at the University of Oklahoma. She is interested in the sociological constructions of deviance and stigma, adolescent sexuality, lesbian, gay, bisexual, transgender, and queer (LGBTQ) identities, feminist criminology, and gender differences in adolescent delinquency.

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