College Students’ Perceptions of Rape: An Exploratory Study Through the Use of Visual Vignettes

Abstract

While research has examined the level of blame placed on victims and perpetrators for rape and sexual assault in simulations, there is very little research examining whether college students can accurately identify rape. In addition, the simulations presented to students in this area of research have overwhelmingly focused on female victims and male perpetrators and tend to use audio or read vignettes. This exploratory study examines if college students can accurately identify rape, using four visual vignettes demonstrating four simulations: (1) a clear violation of law, (2) an ambiguous violation of law, (3) a clear non-violation of law, and (4) an ambiguous non-violation of law, with a male victim and two female perpetrators. Findings from this study suggest that gender may significantly influence an individual’s likelihood of accurately identifying rape. Additionally, students overall are able to accurately identify rape, except for the ambiguous non-violation of law simulation, which is critically examined.

Keywords

visual vignettes rape identification college students

Introduction

According the to the National Center for Education Statistics (2023), in 2020, 9,400 forcible sex offenses, including 5,200 rapes were reported on college campuses, making up “44[%] of reported on-campus crimes” (p. 1). The U.S. Department of Justice found that rape is the most common form of violent crime to occur on college campuses, and that “college women ‘have a higher risk of being raped or experiencing] other forms of sexual assault than women the same age but not in college’” (Sampson, 2003, p. 2). One out of every 5 college women and 1 out of every 16 college men are sexually assaulted in the United States at some point during their college experience (Cantor et al., 2015; Krebs et al., 2016), demonstrating that both men and women who attend college are at a high risk of becoming victims of sexual assault, with women having a significantly higher risk. However, these estimated rates are probably much lower than actual rates as college campus sexual assaults generally suffer from a lack of reporting (Langton & Sinozich, 2014). Although college women are 1.2 times less likely to be sexually victimized than nonstudents, they are less likely to report such victimizations with 80% and 67% going unreported, respectively (Sinozich & Langton, 2014). Estimates suggest roughly 2/3 of total rapes go unreported (Morgan & Truman, 2020) making sexual victimizations, especially of college students, one of the top “underreported crime[s] in the U.S.” (Murphy-Oikonen et al., 2022; Passmore, 2023, para. 9). Specifically, over 40% of college rape¹ victims do not report their victimization (Sampson, 2003) and over 90% of sexual assaults² on college campuses go unreported (National Sexual Violence Resource Center [NSVRC], 2016), with reporting rates of roughly 15.8% having “not significantly increased since the 1990s” (Wolitzky-Taylor et al., 2011, p. 808). According to Dardis et al. (2021) roughly “60% of legally defined rape victims do not label their experiences as ‘rape’” (p. 33). A lack of identification of what rape is, could also account for not only a lack of reporting, but rape perpetration as well. Based on these findings it can be suggested that high rates of rape and sexual assault, in addition to a lack of reporting among college students, is the result of a lack of understanding of the legal definition of rape combined with societal perceptions of victim and perpetrator blame and responsibility.

Current research on college student sexual assault victimizations is limited in that it tends to focus on female victimization more than male victimization (Sampson, 2003). The current study seeks to help address this limitation by examining college students’ ability to accurately identify rape and non-rape scenarios in cases involving a male victim and female perpetrators. Previous studies examining rape identification, perceptions of victim and offender blameworthiness, and how blameworthiness influences students’ ability to correctly identify rape and non-rape scenarios, is examined. Additionally, how gender influences blameworthiness perceptions is examined as prior research has demonstrated males are less likely to believe an action as being that of a sexual assault compared to females (Davies et al., 2001).

Literature Review

Although this study examines college students’ ability to accurately identify rape, such research is extremely limited with majority of research focusing on identifying one’s own experience as rape, or identifying rape through read or audio simulations. An examination of this research is provided, including a discussion of victim and perpetrator blameworthiness. It can be assumed the more the victim is blamed, the less likely an individual will perceive the incident as rape, and the more the perpetrator is blamed, the more likely an individual will perceive the incident as rape. Other variables that could potentially influence perceptions of rape are provided.

Communication of Legal Acts

According to Friedman (1977), “a legal act. . .is a message [that] must be transmitted to an audience or it can have no effect on behavior” (p 111). In order to most effectively transmit the message, the transmission needs to be direct (face to face) and personal (relating to each individual). Without appropriately relating the message to the audience, the audience is unable to obtain a full and comprehensive understanding (Friedman, 1977). In order to effectively communicate what a law entails, specifically in terms of what actions constitute a violation of such law, the law needs to be delivered to those who are to adhere to the law in a specific and clear manner. Otherwise, the law can be misunderstood or not taken seriously (Friedman, 1977).

In relation to this research, for example, if society is told that rape is illegal but is not provided with a clear understandable definition or the specific actions that constitute a rape, misunderstanding and violation of the law becomes likely. This potentially results in individuals adhering to what they believe rape is, instead of the legal definition. A consequence could be rape perpetration and a lack of reporting of rape victimizations. In fact, Siegel et al. (2021) via a qualitative study of male college students, found that males with a history of sexual violence perpetration were less likely to correctly define rape than males who had no such perpetration history. This suggests an increase in perpetration resulting from a lack of legal knowledge of law. Furthermore, with individuals generating their own guidelines, which tend to be created based off of influences around them, the influence of the legal system on law definitions becomes excluded. With the influence media has on how we think and act (Arias, 2019) and college programs working to address and decrease rape myth beliefs (Gidycz et al., 2001; Wilson et al., 2021), it can be suggested that college students are likely to base their guidelines pertaining to rape off of how rape is portrayed in the media or the programs offered to them while attending college due to the exposure of such influences. Media tends to portray rape myth acceptance (Kosloski et al., 2018; Musso, 2022) by glamorizing (Southern Connecticut State University, 2022) and encouraging (Kaya, 2019; Ryalls, 2021) the sexual violence of women. As a result, individuals are likely to view non-violent actions as non-rape (Bondurant, 2001; Littleton et al., 2009) and more normalized (Weiss, 2013). This calls for an examination of how each element of rape is depicted by college students to see if the elements of rape constitute rape per their perceptions, and an examination of the influence participation in college programs has on rape perceptions.

Rape Perceptions Versus Legal Definitions

Research suggests there is disconnect between the legal definition of rape and individuals’ perceptions of what constitutes a rape. Marsil and McNamara (2016) examined college students’ ability to self-identify their own sexual victimizations. Based on data from the Sexual Experiences Survey-Short Form Victimization (SES-SFV) survey completed by roughly 1,650 college students, a clear disconnect between the legal definition of rape and students’ definition of rape was prominent. According to the legal definition of rape, 11.1% of female and 5.2% of male students (9.4% total in their study) experienced rape since enrolling in college, “but only 2.9% of [the] students self-identified” as rape victims (Marsil & McNamara, 2016, p. 416). This research suggests there is a clear differential between college students’ perceptions of rape and the legal definitions of rape. Similarly, in a meta-analysis of 28 studies, consisting of 5,917 female rape survivors, Wilson and Miller (2016) found that of the women whose experiences met the legal definition of rape 60.4% did not identify their experience as rape, with a higher prevalence among college students than non-college students. Hills et al. (2021) research using visual vignettes of consensual and non-consensual encounters also supported this finding, empirically showering there may be a lack of understanding of what rape is among college students.

Similarly, Ballman et al. (2016) examined how college students labeled rape scenarios differing by gender and how this identification was influenced by perpetrator and victim blame attribution as well as the likelihood of recidivism and revictimization. After the random assignment of scenarios, the study found college students were more likely to identify the same-gender scenario as a non-rape and the mixed-gender scenario as a rape. Additionally, 42.2% of participants identified nonconsensual oral sex as a non-rape, demonstrating disconnect between student perceptions of rape and the legal definition of rape. Blame attribution was found to be insignificant (Ballman et al., 2016) suggesting more research is needed on the impact it plays on rape perceptions.

Victim and Offender Blameworthiness

The level of blame placed on the victim or perpetrator for the sexual victimization influences how individuals perceive what occurred. Dardis et al. (2021) found that female participants who labeled their experience as rape were more likely to blame the perpetrator and less likely to blame themselves, while female participants who labeled their experiences as a non-rape or a miscommunication were more likely to blame themselves and less likely to blame the perpetrator. This suggests the more victims blame themselves for their victimization the less likely they are to categorize it as rape.

In relation to victim and perpetrator blameworthiness for the rape victimizations several characteristics have been identified, including: victim’s dress (Vandiver & Dupalo, 2013; Whatley, 2005), victim and perpetrator’s gender (Vandiver & Dupalo, 2013; B. H. White & Kurpius, 2002), victim-perpetrator relationship (Ben-David & Schneider, 2005; Gölge et al., 2013; Grubb & Harrower, 2009; Rebeiz & Harb, 2010), alcohol usage (Dardis et al., 2021; Grubb & Turner, 2012; Orchowski et al., 2020), and respondent’s gender (Sleath & Bull, 2010; S. White & Yamawaki, 2009). Research pertaining to victim dress has generally found that college students tend to place more blame on victims who are provocatively dressed and less blame on victims who are conservatively dressed (Whatley, 2005). For instance, Vandiver and Dupalo (2013) found that over 20% of college students surveyed agreed “a women who dressed in skimpy clothes should not be surprised if a man tries to force her to have sex” (p. 600). Similarly, Whatley (2005) in surveying college students after they read a rape scenario that depicted a husband raping his wife found more blame was placed on the wife when they thought she dressed provocatively.

Although majority of research on victim and perpetrator gender examines female victims and male perpetrators, there is some research that examines of the impact male victims have on individuals’ perceptions of rape. Research has generally found that college students tend to perceive scenarios as rape more often when the victim is female than when the victim is male (Vandiver & Dupalo, 2013; B. H. White & Kurpius, 2002) as college students have difficulty believing males can be victims of rape (Groth & Burgess, 1980; Vandiver & Dupalo, 2013), especially if the perpetrator is female (PeConga et al., 2022). As with people viewing stranger rapes as “real rape,”³ research tends to demonstrate that the more the victim knows their offender the more the victim is blamed for their victimization (Ben-David & Schneider, 2005; Rebeiz & Harb, 2010). Overall, college students tend to view stranger rapes as more severe than acquaintance rape, date rape, and marital rape (Gölge et al., 2013; Grubb & Harrower, 2009), no matter the gender of the victim (Sleath & Bull, 2010; S. White & Yamawaki, 2009).

Due to the influence of alcohol/drugs being an element of rape, it is important to examine how it plays a role in perceptions and blameworthiness. Grubb and Turner (2012) found that perpetrator alcohol usage decreased perpetrator blame and responsibility while victim alcohol usage increased victim blame and responsibility. Similarly, when victims used alcohol it was found that the incident was less likely to be labeled a rape by student participants (Orchowski et al., 2020) and by women victims, themselves (Dardis et al., 2021). This suggests that when alcohol plays a factor students are less likely to perceive the incident as a rape.

Gender

Although the impact a respondent’s gender has on their perceptions of rape is the most heavily examined relationship pertaining to college students’ perceptions of rape available in the scholarly literature, research findings have been mixed. Some research has found that males blame victims more than females (Davies et al., 2001; Grubb & Harrower, 2009; Schneider et al., 2009), while other research has found no differences in college students’ perceptions of rape based on their gender (Abrams et al., 2003; Frese et al., 2004; Newcombe et al., 2008; Viki et al., 2004) or the level of blame placed on the perpetrator (Newcombe et al., 2008). While research has demonstrated mixed results, research tends to lead toward males blaming rape victims for their victimization more than females. Overall, research on perceptions via vignettes has found that male college students tended to place more blame on rape victims for their victimization than they placed on perpetrators (Davies et al., 2001; Grubb & Harrower, 2009). Generally, compared to female college students, male college students tend to hold victims more responsible for their victimization than perpetrators (Schneider et al., 2009), blame the victim more than the perpetrator and male victims more than female victims (Davies et al., 2001), are significantly more likely to minimize the seriousness of a rape (Newcombe et al., 2008), and recommend shorter prison sentences for rapists (Kanekar & Nazareth, 1988).

Additional Influential Variables

Additional variables that influence victim and offender blameworthiness include race, major, athletic status, Greek life membership, attending a sexual assault awareness event, and being aware of University policy. As a result, these variables are controlled for in this study.

Although limited, research has demonstrated individuals of different races/ethnicities have differing views of sexual assault. Japanese college students are more likely than American college students to minimize the seriousness of the rape, blame the victim, and excuse the perpetrator (Lee et al., 2005; Yamawaki & Tschanz, 2005), Spanish college students blame the victim more when they are intoxicated and less when the perpetrator used force (Romero-Sanchez et al., 2012), and White students were more likely to blame a male perpetrator while Black students were more likely to blame the victim (Varelas & Foley, 1998). In relation to major, due to criminology/criminal justice (CCJ) majors receiving information pertaining to issues within the criminal justice system, such students appear to have a slightly more realistic and accurate perception of criminal justice issues (Lambert & Clarke, 2004; Tsoudis, 2000) and the lowest rape myth acceptance scores of all majors (Hancock et al., 2021). College athletics have been found to host a culture that degrades women and femininity (McCray, 2015). Athletes tend to be more sexually aggressive (Carter et al., 2018; Koss & Gaines, 1993), have more rape-supportive attitudes (Navarro & Tewksbury, 2019; Young et al., 2016), and a higher tendency to perpetrate rape than non-athletes (Boeringer, 1996; Young et al., 2016), with female college sexual assault victims reporting higher rates of athlete perpetration (Frinter & Rubinson, 1993). Fraternities, specifically, have been found to support a culture which is prone to rape and provides venues through fraternity parties that increase the risk of sexual assault (Decker & Baroni, 2011; Harkins & Dixon, 2010), partially due to male fraternity members having more rape-supportive attitudes than non-Greek males (Canan et al., 2018; Seabrook et al., 2018). Even female sorority members, who are more rejecting of rape myths than fraternity men (Bannet et al., 2013), are more likely to blame the victim and accept rape myths and interpersonal violence (Kalof, 1993).

With college programs focused on addressing the goal of decreasing rape myth beliefs (Gidycz et al., 2001; Wilson et al., 2021) it can be suggested, as per the communication of legal acts theory, that students who participate in sexual assault awareness events, and are thus exposed to legal definitions of rape, are more likely to accurately identify rape and non-rape scenarios than students who did not attend such events. Similarly, students with knowledge of the University sexual assault policy have an increased exposure to legal definitions and should therefore be more apt to accurately identify rape.

Simulation Research

There has been minimal research pertaining to the use of simulations in assessing individual perceptions of crime broadly and even less that has focused on rape specifically. That said, within this scant body of literature there are three forms of simulation research: (1) participatory simulations, (2) analog simulations, and (3) visual simulations. Participatory simulations are the most used type of simulation method due to their effectiveness of being used for educational and training purposes (Gates et al., 2001). Analog simulations have participants listen to the audio version of a simulation (Bernat et al., 1999). While effective at determining individual perceptions (Atzmüller & Steiner, 2010) such simulations can be limited by the realness within them (Aguinis & Bradley, 2014; Hughes & Huby, 2002). What we see is processed better than what we hear (Bigelow & Poremba, 2014) resulting in visual simulations, especially videos (Goldman et al., 2006), being preferable due to the increased participant immersion (Aguinis & Bradley, 2014) and potential realness (Sauer, 2011) of the simulations (Hughes & Huby, 2002; Taylor, 2006). Visual simulations are when participants watch various visual materials (Annear et al., 2014). Being an external observer allows participants to watch sensitive material in a safe and controlled environment (Liyanapathirana et al., 2016). Research has found the more realistic the simulation the greater the external validity (Chen et al., 2022; Taylor, 2006). For these reasons, a visual simulation was the preferred simulation for this study.

Current Study

One key limitation of the prior literature in this area is a lack of research on the use of visual simulations to examine college students’ perceptions of victim and offender blameworthiness and their ability to accurately identify rape. There is sparse research in this area, and that which does exist is difficult to compare based on methodological differences. The foundation for many of the simulation studies cited above were written scenarios that were read by the respondents, permitting each respondent to envision their perception of the event and add their own details where the scenarios lacked specific information. Also, much of the research combines rape and sexual assault as one construct.

Another key limitation of the literature is gender-bias. Previous research in this area has incorporated scenarios depicting female and male victims and male perpetrators only, ignoring female perpetrators. These limitations are addressed in the current study.

With these limitations in mind, the current exploratory study had two overarching objectives:

(1) To determine college students’ ability to accurately identify rape and non-rape simulations.

(2) To analyze how gender, and victim and perpetrator blameworthiness influences an individual’s ability to correctly identify such simulations.

Methodology

Sample

Cross-sectional data for this project were obtained from a random sample of 2,000 college students attending a Western Pennsylvania University⁴ during the fall 2018 semester. An invitation email containing a Qualtrics link to a self-report survey with four simulations of a student-involved rape scenario was sent to the random sample of students. In total, 158 students agreed to participate in the study and 81 completed the survey in its entirety. After providing consent participants were shown the first simulation followed by a series of survey questions. This process was repeated for all four simulations presented to students.

Dependent Variable

The dependent variable measured college students’ ability to accurately identify rape and non-rape simulations. The following definition of rape as per the Commonwealth of Pennsylvania was used. An individual commits rape when:

The person engages in sexual intercourse with a complainant: 1) By forcible compulsion.

2) By threat of forcible compulsion that would prevent resistance by a person of reasonable resolution. 3) Who is unconscious or where the person knows that the complainant is unaware that the sexual intercourse is occurring. 4) Where the person has substantially impaired the complainant’s power to appraise or control his or her conduct by administering or employing, without the knowledge of the complainant, drugs, intoxicants or other means for the purpose of preventing resistance. 5) Who suffers from a mental disability which renders the complainant incapable of consent. (18 Pa. Cons. Stat. § 3121(a)(1-5) (2016))

For each simulation survey respondents were asked, Do you consider this incident to be a rape? with dichotomous response categories of “yes” (1) or “no” (0).

Independent Variables

To determine whether college students perceive the provided rape-based simulations as that of a crime or not, each of the simulations serves as an independent variable. The two simulations implying a rape occurred were based off of the Commonwealth of Pennsylvania’s legal definition of rape. Although there are five subsections within the definition of rape, for this research, only the first four subsections (by forcible compulsion, by threat of force, unconscious victim, and influence of drugs) were used. In total, four simulations were used depicting two females engaging a male in sexual activity, whereby two simulations demonstrate rape and two demonstrate consenting non-rape situations.⁵ According to Chen et al. (2022) effective visual simulations are developed when a four step process is followed: (1) scenario development, (2) scrip creation, medication, and validation, (3) video production and editing, and (4) video validation and application. Although the four simulations for the current study were created before Chen et al. (2022) was published, upon analyzing the simulation methodology it was determined this effective process was followed.

Video #1: Clear Violation of Law

The victim and the perpetrators are talking at a party. The perpetrators forcefully pull the victim (who is clearly exceedingly intoxicated) to a bedroom. The perpetrators push the victim onto the bed and start to undress the victim. The victim tells the perpetrators to stop.

Video #2: Ambiguous Violation of Law

The victim and the perpetrators are talking at a party. During their conversation, the victim agreed (gave consent) to have sex with the perpetrators. The perpetrators and the victim walk to the bedroom together. While undressing, the victim passes out. The perpetrators continue to engage in sexual relations with the victim.

Video #3: Clear Non-Violation of Law

The “victim” and the “perpetrators” are talking at a party. The “perpetrators” and the “victim” walk to the bedroom together. They start kissing, falling onto the bed, where they begin to undress each other.

Video #4: Ambiguous Non-Violation of Law

The “victim” and the “perpetrators” are talking at a party. During their conversation the “victim” agreed (gave consent) to have sex with the “perpetrators.” The “victim” and the “perpetrators” walk to the bedroom together, where they begin undressing one another. In a playful manner, the “victim” pulls away from the “perpetrators.” The “perpetrators” push the victim against the wall. The “perpetrators,” in an aggressive manner, continue undressing the “victim,” pushing the “victim” to the bed. The “victim” does not take back consent, thereby consent is still present.

Covariates

In following past research about college students’ perceptions of rape, the level of control and responsibility placed on the victim and the offender were measured as the covariates of “victim blameworthiness” and “offender blameworthiness” due to their ability to influence respondents’ perceptions of each simulation (Sentürk & Müller, 2005). For each simulation, questions adapted from the Rape Minimization Scale⁶ and the Victim Blame Attribution Scale⁷ were incorporated, with 11-point Likert scales ranging from 0 to 10 for response categories, as demonstrated below.

The following questions were asked for each simulation to measure “victim blameworthiness” and “offender blameworthiness” via substituting John for the victim and Rebecca and Emily for the offenders, thus five questions measured “victim blameworthiness” and four measured “offender blameworthiness.”⁸

(1) How much control did [victim/offenders] have of this situation?—“No control” (0) to “complete control” (10)

(2) How much desire did [victim/offenders] have for intercourse?—“No desire” (0) to “complete desire” (10)

(3) How much did [victim/offenders] provoke this situation?—“Not at all” (0) to “a great extent” (10)

(4) John was dressed in a provocative manner.—“Strongly disagree” (0) to “strongly agree” (10)

(5) [Victim/Offenders] knew [Offenders/Victim]—“strongly disagree” (0) to “strongly agree” (10)

Conditional Results Variables

As per the Commonwealth of Pennsylvania’s definition of rape, there are five possible aspects of rape, four of which were used for this study. The conditional results variables are “force identification,” “threat identification,” “victim conscious identification,” and “drug/alcohol incapacitation.” For each simulation survey respondents were asked four questions, each pertaining to one conditional results variable as follows:

(1) “Force Identification”—Did Rebecca and Emily use force to engage in sexual activity with John?

(2) “Threat Identification”—Did Rebecca and Emily threaten to harm John?

(3) “Victim Conscious Identification”—Was John conscious during the incident?

(4) “Drug/Alcohol Identification”—Was John’s actions influenced by the use of drugs or alcohol?

Dichotomous response categories of “yes” (1) and “no” (0) were provided for each of the four questions. These questions, which constitute the various aspects of the legal definition of rape, allowed for a lead-up to the overall question of whether respondents believed a rape occurred. If respondents reported they perceived force used, threat of force, an unconscious victim, or a victim impaired by drugs or alcohol, then respondents should also report that a rape occurred. If there is a discrepancy in these responses with the dependent variable, it can be the result of a lack of understanding of the legal definition of rape.

Control Variables

Seven variables were controlled for: (1) gender, (2) race, (3) major, (4) athlete, (5) Greek life member, (6) ever attended an event promoting sexual assault awareness (Six O’clock Series, Haven Project, Take Back the Night, Green Light Campaign, Rainn Day, Turn the Red Zone Green, Bystander Step Up Training, and Sexual Assault Awareness Month), and (7) awareness of university policy. Athlete and Greek Life Member were dichotomous with responses of “yes” (1) and “no” (0), while the other variables were categorical. Based on the sample demographics Gender⁹ was measured as “male” (0) and “female” (1), Race as “White” (0) and “non-White” (1), Major as “criminology/criminal justice” (0) and “other” (1), and Awareness of University Policy as “no” (0), “yes” (1), and “unknown” (2). For attending an event promoting sexual assault awareness the events conducted at the University were provided with respondents instructed to check all events they had previously attended.

Analytic Strategy

Five statistical analyses were conducted. Descriptive statistics, bivariate statistics, a factor analysis of the covariate variables,¹⁰ and logistic regression were conducted. Only the logistic regression of the fourth video (ambiguous non-violation of law) is discussed as while the regression models for the other three videos were significant, none of the variables within the models were significant due to the low power of the sample as a result of the limited effect size between respondents who classified the three simulations as rape and those who classified them as non-rape.

Results

Descriptive Statistics

A majority of participants identified as White (83.9%) and female¹¹ (70.4%) as demonstrated in Table 1. Roughly 15% of the sample were criminology/criminal justice majors (14.8%), 92.6% were not athletes, and 92.6% were not a member of Greek life. Of the 81 participants, 79.0% reported having read or had the University’s sexual assault policy explained to them, and 8.6% and 4.9% attended Bystander Step Up Training¹² and Green Light Campaign,^13,14 respectively.

Table 1.

Descriptive Statistics (N = 81).

	Percentage (%)
Demographics
Female	70.4
White	83.9
CJ/criminology major	14.8
Non-athlete	92.6
Non-Greek life member	92.6
Knowledge of IUP policy	79.0
Attended green light campaign	4.9
Bystander step up training	8.6

Table 2 demonstrates the frequency of “rape identification” for each of the four simulations. Roughly 95% of the respondents correctly identified the clear violation simulation as rape, and 90.1% correctly identified the ambiguous violation simulation as rape. For the clear non-violation simulation, 79.0% correctly identified the simulation as non-rape, and roughly one-third (34.6%) accurately identified the ambiguous non-violation simulation as non-rape. In total, 25.9% of the sample accurately identified all four simulations, 48.1% accurately identified three simulations, and 21.0% and 2.5% accurately identified two and one simulations, respectively. It is not surprising almost half accurately identified three simulations, as majority of the sample failed to accurately identify the ambiguous non-violation of law simulation.

Table 2.

Dependent Variable Frequencies.

IV	Respondent responses	N	Percentage (%)
Video #1: clear violation	Not rape	4	4.9
Video #1: clear violation	Rape	77	95.1
Video #2: ambiguous violation	Not rape	8	9.9
Video #2: ambiguous violation	Rape	73	90.1
Video #3: clear non-violation	Not rape	64	79.0
Video #3: clear non-violation	Rape	16	19.8
Video #4: ambiguous non-violation	Not rape	28	34.6
Video #4: ambiguous non-violation	Rape	52	64.2

As demonstrated in Table 3, respondents who identified the ambiguous non-violation simulation as a non-rape had higher average scores on questions pertaining to “victim blameworthiness” and blamed the victim more overall than respondents who inaccurately identified the incident as a rape. Respondents who identified the incident as a non-rape had a victim blameworthiness average score of 17.18 (SD = 8.060), almost twice the average score (9.15, SD = 7.863) for respondents who identified the incident as a rape. In terms of the overall average scores of “perpetrator blameworthiness,” respondents who identified the incident as a non-rape had a slightly lower average score, 27.98 (SD = 2.299) than respondents who identified the incident as a rape, 27.92 (SD = 4.247).

Table 3.

Ambiguous Non-Violation of Law (Video #4) with Victim and Perpetrator Blameworthiness Means Comparison.

“Victim blameworthiness”			“Perpetrator blameworthiness”
	Do you consider this incident to be rape?			Do you consider this incident to be rape?
	No	Yes		No	Yes
Desire for intercourse			Desire for intercourse
$\bar{X}$	6.43	3.19	$\bar{X}$	9.68	9.19
SD	0.723	2.000	SD	2.631	2.458
Knew perpetrators			Knew victim
$\bar{X}$	2.11	1.98	$\bar{X}$	2.39	2.31
SD	2.362	2.762	SD	2.347	2.684
Control of situation			Control of situation
$\bar{X}$	4.64	1.92	$\bar{X}$	9.29	9.38
SD	1.013	1.223	SD	2.765	2.239
Provocation of situation			Provocation of situation
$\bar{X}$	3.46	1.67	$\bar{X}$	8.93	9.35
SD	2.822	2.167	SD	1.654	1.327
Provocatively dressed			Provocatively dressed
$\bar{X}$	—	—		0.54	0.42
SD	1.290	1.036	SD	—	—
Victim blameworthiness			Perpetrator blameworthiness
$\bar{X}$	27.89	27.92	$\bar{X}$	17.18	9.15
SD	2.299	4.247	SD	8.060	7.863

Bivariate Statistics

As demonstrated in Table 4, “victim blameworthiness” was found to be statistically different for “rape identification” t₍₇₈₎ = 4.316 (p = .000), while “perpetrator blameworthiness” was not statistically significant between the groups t₍₇₈₎ = -0.035 (p = .972). All of the conditional results variables and one of the control variables have a statistically significant relationship with the dependent variable “rape identification.” The chi-squared values are 6.648 (p = .010) for “force identification,” 3.239 (p = .072) for “threat identification,” 15.793 (p = .000) for “victim conscious identification,” 4.475 (p = .034) for “drug/alcohol impairment,” and 11.397 (p = .001) for “gender.” This means there is a statistically significant difference between respondents who identified this incident as a rape and respondents who identified this incident as a non-rape based on the level of blame placed on the victim, whether the perpetrators used force on or threatened the victim, whether the victim was identified as conscious or unconscious or was under the influence of drugs or alcohol, and the gender of the respondent.

Table 4.

Ambiguous Non-Violation of Law (Video #4) Bivariate Statistics.

Item	t-test	χ²	p-value
Conditional results variables
Force identification		6.648	.010***
Threat identification		3.239	.072*
Victim conscious identification		15.793	.000***
Drug/alcohol impairment		4.475	.034**
Covariates
Victim blameworthiness	4.316		.000***
Perpetrator blameworthiness	−0.035		.972
Control variables
Gender		11.397	.001***
Race		0.017	.896
Major		0.632	.462
Athlete		0.477	.490
Greek life member		0.624	.423
Knowledge university policy		0.377	.828
Six O’clock series		0.122	.727
Have project		1.248	.264
Take back the night		0.517	.472
Green light campaign		0.416	.519
Rainn day		1.586	.208
Turn the red zone green		1.105	.293
Bystander step up training		0.139	.709
Sexual assault awareness month		1.130	.288

p ≤ .1. **p ≤ .05. ***p ≤ .01.

Binary Logistic Regression

While the regression models for “clear violation of law,” “ambiguous violation of law,” and “clear non-violation of law” were significant, none of the variables within the models were significant, likely due to the power of the sample. Therefore, only the regression model for “ambiguous non-violation of law,” as demonstrated in Table 5, is discussed. The model has a chi-squared value of 35.359 (p = .000) and was statistically significant with a Wald statistic of 6.499 (p = .011). Overall, the model had a good fit and explained roughly 50% of the variance in rape identification. “Victim Conscious Identification” (b = -2.354, p = .007), “Victim Blameworthiness” (b = -0.082, p = .040), and “Gender” (b = 1.548, p = .021), were all found to be statistically significant predictors in this model. Results suggest respondents who perceived the victim as conscious were less likely to perceive the incident as rape than respondents who perceived the victim as unconscious, and the more a respondent blamed the victim in the simulation, the less likely they were to view the incident as rape. Additionally, females were more likely to perceive the incident as being a rape than males.

Table 5.

Ambiguous Non-Violation of Law (Video #4) Logistic Regression Model.

Variables	b	SE	Wald	Exp(B)	Sig.
Constant	3.824	2.940	1.691	45.809	.193
Force identification	0.328	0.780	0.177	1.388	.674
Threat identification	0.575	1.213	0.224	1.776	.636
Victim conscious identification	−2.354	0.874	7.265	0.095	.007***
Drug/alcohol impairment	0.869	1.322	0.432	2.385	.511
Victim blameworthiness	−0.082	0.040	4.231	0.921	.040**
Perpetrator blameworthiness	−0.090	0.078	1.331	0.914	.249
Gender	1.548	0.673	5.292	4.703	.021**

Note. Cox and Snell R² = .361, Nagelkerke R² = .496.

p ≤ .1. **p ≤ .05. ***p ≤ .01.

Discussion

Can College Students Accurately Identify Rape?

Overall, most college students in the sample were able to accurately identify instances of rape, whether clear or ambiguous, and accurately identify clear non-rape. However, upon examination of the ambiguous non-violation simulation, students, especially females, had a harder time accurately identifying the incident as a non-rape, with only 23.2% of females and 62.5% of males accurately identifying the incident. This supports research conducted by Siegel et al. (2021) that males, especially males who have never perpetrated sexual violence, tend to have relatively accurate definitions of rape. This could be due to the simulation being too ambiguous, especially as a result of the forcefulness used. This simulation specifically demonstrates the use of force in a playful manner with the victim playfully pulling away from the perpetrators resulting in the perpetrators playfully pushing the victim against the wall as they continued kissing and undressing. Some participants could have perceived this playful use of force as non-playful, calling into question the differing definitions of true versus playful force among study participants. Instead of disconnect between perceptions and legal definitions of rape, differences in acceptable uses of force in the bedroom could account for the limited ability to accurately identify the ambiguous non-violation simulation as a non-rape.

What is even more concerning is the number of students who identified at least one of the conditional results variables in the simulation but did not classify the incident as rape. With the conditional results variables representing the four elements of the legal definition of rape (e.g., force, threat of force, victim unconscious, and victim impaired by drugs/alcohol), if one element is legitimately present, a rape has occurred. Of the participants who stated an element was present but then identified the simulation was not a rape, it suggests a disconnect between participants’ knowledge and the legal elements of rape. While there were few respondents demonstrating such disconnect with the clear and ambiguous violations of law simulations, for the clear non-violation simulation the number of respondents increased, with the ambiguous non-violation of law simulation having the highest amount of disconnect.¹⁵

In addition to disconnect between the elements of rape and identification of rape, remains the fact that majority of the sample still inaccurately identified the simulations, with only 25.9% correctly identifying all four of the simulations. While identifying non-rape simulations as that of rape does have concern for cause, what is more detrimental is students lacking the ability to identify rape when it is present, especially in the clear violation simulation. Roughly 5% of the sample (4.9%) identified the clear violation simulation and 9.9% identified the ambiguous violation simulation as not being a rape. Based on the disconnect between the elements and rape identification, along with students not being able to accurately identify instances of rape, it can be suggested there is a discord in student knowledge of the definition of rape with the legal definition.

The Influence of Gender

Females were more likely to perceive incidents as rape than males, for all incidents, with a statistically significant difference for the ambiguous non-violation of law simulation. For the clear violation of law simulation, 96.5% of females and 91.7% of males identified the incident as rape, while 92.9% of females and 83.3% of males identified the ambiguous violation of law simulation as rape. Although high percentages of males and females identified these incidents as rape, women, overall, were more likely to identify the incidents as such. Even though the clear non-violation and ambiguous non-violation simulations did not depict rape, females were still more likely than males to identify such incidents as that of a rape. For the clear non-violation simulation, 63.6% of females and 9.1% of males identified the incident as a rape, and 76.8% of females and 37.5% of males identified the ambiguous non-violation simulation as that of a rape. Such numbers, in combination with females being statistically significantly more likely to identify the ambiguous non-violation of law simulation as rape, suggests females are more likely to view actions as that of a rape, even when the actions are legal. A potential explanation for this is that females are at an increased risk of becoming rape victims (RAINN, 2024; Rennison, 2002) while males are at an increased risk of perpetration (Rennison, 2002).

Impact on College Campuses

With college students incorrectly identifying the ambiguous non-violation of law simulation as rape and incorrectly identifying, or not identifying, the four key elements that constitute a rape, further exploration of the impact colleges have on explaining the elements of rape to students, is needed. While the sexual assault policies provided to students define what rape is, colleges should also provide clear and ambiguous examples and clearly explain the elements of rape so students are fully aware of what actions constitute rape. One way to do this could be through the use of sexual assault awareness events, such as the Green Light Campaign and the Bystander Step Up Training. Although these programs were not found to significantly influence accurate rape identification, potentially due to the low participant numbers, the programs still showed some promise. Such programs could provide students with a clearer definition of what constitutes rape and address ambiguous “gray” situations, as the study participants struggled to accurately identify the ambiguous non-violation of law simulation. These steps could assist in clearing up confusion of what constitutes rape and potentially increase students’ ability to accurately know and identify what situations constitute rape.

Policy Implications

Due to the small sample size definitive conclusions and generalizations cannot be made from the data. That said, there are several findings from modeling, as previously discussed, that warrant further discussion and future consideration. The research suggests: (1) more research within this area overall is needed, (2) a need to accurately depict the legal elements of rape so students are not reporting incidents that do not constitute a crime, (3) the ambiguous incidents should be discussed in sexual assault trainings more so than the clear-cut incidents, and (4) the effectiveness of the Green Light Campaign and the Bystander Step Up Training should too be examined.

It appears students are erring on the side of caution when identifying rape simulations by identifying non-rape simulations as that of rape. Siegel et al. (2021) supports this having found male college students tend to provide definitions of rape that are broader than the legal definition. This in part, could be due to the current societal climate surrounding sexual assault. Students may believe it is better to identify an incident as a rape than to ignore the potential sex crime that occurs. While this is a safe way to go about it, it brings about the issues of potentially reporting acts that were not in fact sex crimes; the consequences of which fall on the suspected perpetrator due to the automatic label of rapist individuals place on the accused. While the rate of false rape accusations is low (NSVRC, 2012) ranging from 2-8% (Leithead, 2022), it still occurs, with a societal climate that tends to view potential sexual predators as guilty by accusation instead of “innocent until proven guilty” (Wells, 2015). This results in potentially irreparable damage (i.e., several social adjustment problems; Grounds, 2004; Ministry of Justice, 2010), psychological trauma (Brooks & Greenberg, 2021; Ministry of Justice, 2010), and suicide (Brooks & Greenberg, 2021)) to the falsely accused’s reputation as a result of negative publicity. If anything, policy should address this issue by educating students on the legal elements of rape and other sexual assaults. Similarly, females are more likely to identify both the violation and non-violation simulations as that of rape than males. It could be suggested that women are more likely to identify incidents as being rape due to the fact that they are more likely to be victims of such actions, putting them at a greater victimization risk, and thus more likely to be more cautious (McDonald et al., 2019) of sexual actions, compared to males. In fact, with males being less likely to identify simulations depicting rape as that of a rape, it calls into question if this relates to males perpetrating rape at higher rates than females. Such educational programs could bridge the gap between one’s knowledge of rape and the legal definition of rape. This in turn could increase victim reporting and decrease the likelihood of college students perpetrating rape overall due to students having a better understanding of what constitutes rape.

Respondents who participated in the Green Light Campaign or the Bystander Step Up Training, were more likely to correctly identify the simulations than respondents who participated in none or other sexual assault awareness events. The Green Light Campaign and Bystander Step Up Training both consist of a training portion for those participating, whereas the other events are simply open to the public for participation without any training necessary. Although it is unknown if the respondents participated in these trainings specifically, the potential impact these programs have should be examined. Orchowski et al. (2020) and Siegel et al. (2021) recommend college sexual education programs include information pertaining to the legal consequences of perpetrating sexual violence. These programs should be honest about the rates of victimization and perpetration while also highlighting that all genders can be victims of rape (Siegel et al., 2021), which could influence student perceptions on male victims. Additionally, such programs should be based on research (Jouriles et al., 2018; Santelli et al., 2018; Siegel et al, 2021), allowing for the inclusion of important and helpful information.

Limitations

There are five main limitations of this study, four of which involve the sample. Limitations include a low response rate and small sample size, which is comprised of mainly white (83.9%) females (70.4%). This leads to an inability to generalize the results and is the potential cause of the lack of variation in the dependent variable for three of the independent variables. A final, potential limitation, is historical events including the “me too.” movement, Justice Kavanaugh’s Supreme Court nomination, and the Pittsburgh, Pennsylvania Catholic Diocese sexual assault allegations.

Due to a sample size of 81, one must be cautious in running regression analyses due to the small sample size increasing the likelihood of Type II error. Even with a power of 80.3%, the question of just how representative the same is comes into question, especially with an undiversified sample that is not representative of the college student population. As a result, generalizability of the data is not possible. Additionally, a limited sample size could have caused the lack of variance of the dependent variable, which prevented certain statistical analyses from being conducted on three of the four independent variables. There are three potential reasons a small sample size was obtained. First, only 2,000 students were randomly selected for the sample. It is possible if more students had been randomly selected a higher response rate and thus a larger more diversified sample could have been obtained. Second, the number of email reminders sent might not have been enough, adding to the limited response rate. Lastly, study participation was approximately 20 minutes which could have resulted in individuals choosing not to participate or to drop out of the study. To mitigate this, incentives could be used.

A potential limitation were the historical events that took place directly before and during the data collection process, which could have influenced respondents’ perceptions and responses. The spread of the “me too (2014).” movement allowed for the awareness of how widespread sexual assault is, shifting public attitude in a manner that demands action be taken for any potential sexual allegations. In July 2018 Brett Kavanaugh was nominated for U.S. Supreme Court Justice and by September 2018, three women had accused him of sexual assault (Hauser, 2018), which received heavy news media coverage. Lastly, in August 2018, a grand jury examining 301 Pennsylvania priests accused of child sexual abuse within the Catholic Church (Sheehan, 2018), released the names, 99 of which were within the Diocese of Pittsburgh (Pittsburgh Post-Gazette, 2018). Within a week of the list release, the Pittsburgh Diocese had received roughly 50 additional new abuse claims (Flores et al., 2018). These events were heavily publicized throughout Western Pennsylvania, where the study took place. Throughout this study, three high-profile events pertaining to sexual assault occurred, all of which had the potential to influence student perceptions of what constitutes rape, causing them to potentially err on the side of caution when identifying the incidents.

Future Research

There is an abundance of future research that should be conducted pertaining to this topic. First, this study should be replicated at colleges in other states. In doing so, more students should be randomly selected for the sample, as a way to increase response rates and diversity within the sample. Obtaining a larger and more diverse sample can allow for the generalizability of data. Second, an examination of the effectiveness of sexual assault awareness programs, such as the Green Light Campaign or the Bystander Step Up Training, and their potential impact on assisting students to accurately identify incidents of rape and non-rape, should occur. Third, this research provided simulations that portrayed one male victim and two female offenders. Future research should incorporate other victim-offender combinations (i.e., female victim-male offender, female victim-female offender, and male victim-male offender), and alter the number of offenders as well. Lastly, research should be conducted via different simulations—visual and analog—to examine the impact that each type of simulation has on an individual’s perceptions of the event.

Conclusion

College students’ perceptions of rape and how such perceptions influence their ability to accurately identify rape and non-rape simulations is complex. Females are more likely to perceive incidents, even non-rape incidents as being that of rape than males, with college students overall appearing to err on the side of caution and report an incident as being that of a rape even when it is not. It is clear there is a disconnect between perceptions of the legal definition of rape as college students identified elements of rape in the simulations but then reported the simulation as being a non-rape. High instances of rape and sexual assault on college campuses combined with a lack of reporting, calls for further exploratory research into this topic and incorporating additional visual simulations, to really understand how college students perceive what they see.

Footnotes

Declaration of Conflicting Interests

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

Funding

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

ORCID iD

Samantha M. Gavin

Notes

Author Biography

Samantha M. Gavin is Assistant Professor of Criminology at St. Bonaventure University. She earned her PhD in Criminology from Indiana University of Pennsylvania.

References

Abrams

Viki

G. T.

Masser

Bohner

(2003). Perceptions of stranger and acquaintance rape: The role of benevolent and hostile sexism in victim blame and rape proclivity. Journal of Personality and Social Psychology, 84(1), 111–125. https://doi.org/10.1037/0022-3514.84.1.111

Aguinis

Bradley

K. J.

(2014). Brest practice recommendations for designing and implementing experimental vignette methodology studies. Organizational Research Methods, 17(4), 351–371. https://doi.org/10.1177/1094428114547952

Annear

M. J.

Cushman

Gidlow

Keeling

Wilkinson

Hopkins

(2014). A place for visual research methods in the field of leisure studies? Evidence from two studies of older adults’ active leisure. Leisure Studies, 33(6), 618–643. https://doi.org/10.1080/02614367.2013.841743

Arias

(2019). How does media influence social norms? Experimental evidence on the role of common knowledge. Political Science Research and Methods, 7(3), 561–578. https://doi.org/10.1017/psrm.2018.1

Atzmüller

Steiner

P. M.

(2010). Experimental vignette studies in survey research. Methodology: European Journal of Research Methods for the Behavioral Sciences, 6(3), 128–138. https://doi.org/10.1027/1614-2241/a000014

Ballman

A. D.

Leheny

E. K.

Miller

K. E.

Simmons

B. L.

Wilson

L. C.

(2016). Bystander perceptions of same-gender versus mixed-gender rape: A pilot study. Journal of Aggression, Maltreatment & Trauma, 25(10), 1079–1096. https://doi/org/10.1080/1096771.2016.1228019

Bannet

R. S.

Brosi

M. W.

Foubert

J. D.

(2013). Sorority women’s and fraternity men’s rape myth acceptance and bystander intervention attitudes. Journal of Student Affairs Research & Practice, 50(1), 72–87. https://doi.org/10.1515/jsarp-2013-0005

Ben-David

Schneider

(2005). Rape perceptions, gender role attitudes, and victim perpetrator acquaintance. Sex Roles, 53(5/6), 385–399. https://doi.org/10.1007/s11199-005-6761-4

Bergen

R. K.

Barnhill

(2006). Marital rape: New research and directions. https://vawnet.org/material/marital-rape-new-research-and-directions

10.

Bernat

J. A.

Wilson

A. E.

Calhoun

K. S.

(1999). Sexual coercion history, calloused sexual beliefs and judgments of sexual coercion in a date rape analogue. Violence and Victims, 4(2), 147–160.

11.

Bigelow

Poremba

(2014). Achille’s ear? Inferior human short-term and recognition memory in the auditory modality. PLOS One, 9(2), e89914. https://doi.org/10.1371/journal.pone.0089914

12.

Boeringer

S. B.

(1996). Influences of fraternity membership, athletics, and male living arrangements on sexual aggression. Violence Against Women, 2(2), 134–147. doi: 1177/1077801296002002002

13.

Bondurant

(2001). University women’s acknowledgment of rape: Individual, situational, and social factors. Violence Against Women, 7(3), 294–314. https://doi.org/10.1177/1077801201007003004

14.

Brooks

S. K.

Greenberg

(2021). Psychological impact of being wrongfully accused of criminal offenses: A systematic literature review. Medicine, Science, and the Law, 61(1), 44–54. https://doi.org/10.1177/0025802420949069

15.

Canan

S. N.

Jozkowski

K. N.

Crawford

B. L.

(2018). Sexual assault supportive attitudes: Rape myth acceptance and token resistance in Greek and non-Greek college students from two university samples in the United States. Journal of Interpersonal Violence, 33(22), 3502–3530. https://doi.org/10.1177/0886260516636064

16.

Cantor

Fisher

Chibnall

Townsend

Lee

Bruce

Thomas

(2015). Report on the AAU campus climate survey on sexual assault and sexual misconduct. Association of American Universities.

17.

Carter

D. M.

Khan

Brewer

(2018). Sexual aggression in sport. Journal of Forensic Practice, 20(3), 211–214. https://doi.org/10.1108/JFP-10-2017-0042

18.

Chen

Hsu

C. H. C.

Pearce

P. L.

(2022). Developing video vignettes for tourism research: Protocol and quality indicators. Journal of Travel Research, 61(8), 1828–1847. https://doi.org/10.1177/00472875211051413

19.

Dardis

C. M.

Kraft

K. M.

Gidycz

C. A.

(2021). “Miscommunication” and undergraduate women’s conceptualizations of sexual assault: A qualitative analysis. Journal of Interpersonal Violence, 36(1–2), 33–61. https://doi.org/10.1177/0886260517726412

20.

Davies

Pollard

Archer

(2001). The influence of victim gender and sexual orientation on judgments of the victim in a depicted stranger rape. Violence and Victims, 16(6), 607–619.

21.

Decker

J. F.

Baronia

P. G.

(2011). “No” still means “yes”: The failure of the “non-consent” reform movement in American rape and sexual assault law. Journal of Criminal Law & Criminology, 101(4), 1081–1169.

22.

Findlater

J. E.

(1988). Reexamining the law of rape. Michigan Law Review, 86(6), 1356–1364.

23.

Flores

Conlin

Willingham

(2018, August 22). The Pittsburgh Diocese has received about 50 new abuse claims since the grand jury report came out. CNN. https://www.cnn.com/2018/08/22/us/pittsburgh-diocese-abuse-claims/index.html.

24.

Frese

Moya

Megías

J. L.

(2004). Social perception of rape: How rape myth acceptance modulates the influence of situational factors. Journal of Interpersonal Violence, 19(2), 143–161.

25.

Friedman

L. M.

(1977). Law and society: An introduction. Prentice-Hall.

26.

Frinter

M. P.

Rubinson

(1993). Acquaintance rape: The influence of alcohol, fraternity membership, and sports team membership. Journal of Sex Education & Therapy, 19(4), 272–284. https://doi.org/10.1080/01614576.1993.11074089

27.

Gates

D. M.

Fitzwater

Telintelo

(2001). Using simulations and standardized patients in intervention research. Clinical Nursing Research, 10(4), 387–400.

28.

Gidycz

C. A.

Layman

M. J.

Rich

C. L.

Crothers

Gylys

Matorin

Jacos

C. D.

(2001). An evaluation of an acquaintance rape prevention program: Impact on attitudes, sexual aggression, and sexual victimization. Journal of Interpersonal Violence, 16(11), 1120–1138. https://doi.org/10.1177/088626001016011002

29.

Goldman

B. M.

Gutek

B. A.

Stein

J. H.

Lewis

(2006). Employment discrimination in organizations: Antecedents and consequences. Journal of Management, 32(6), 786–830. https://doi.org/10.1177/0149206306293544

30.

Gölge

Z. B.

Yavuz

M. F.

Müderrisoglu

Yavuz

M. S.

(2013). Turkish university students’ attitudes towards rape. Sex Roles, 49, 653–661.

31.

Groth

A. N.

Burgess

A. W.

(1980). Male rape: Offenders and victims. American Journal of Psychiatry, 137(7), 806–810.

32.

Grounds

(2004). Psychological consequences of wrongful conviction and imprisonment. Canadian Journal of Criminology and Criminal Justice, 46(20, 165–182.

33.

Grubb

A. R.

Harrower

(2009). Understanding attribution of blame in cases of rape: An analysis of participant gender, type of rape and perceived similarity to the victim. Journal of Sexual Aggression, 15(1), 63–81. https://doi.org/10.1080/13552600802641649

34.

Grubb

Turner

(2012). Attribution of blame in rape cases: A review of the impact of rape myth acceptance, gender role conformity and substance use on victim blaming. Aggression and Violent Behavior, 17(5), 443–452. https://doi.org/10.1016/j.avb.2012.06.002

35.

Hancock

K. P.

Policastro

Crittenden

C. A.

Garland

T. S.

(2021). Major blame: Examining male rape myth acceptance across college majors. Journal of Criminal Justice Education, 32(2), 1–17. doi: 10.1080/10511253.2021.1882518

36.

Harkins

Dixon

(2010). Sexual offending in groups: An evaluation. Aggression and Violent Behavior, 15(2), 87–99.

37.

Hauser

(2018, September 26). The women who have accused Brett Kavanaugh. The New York Times. https://www.nytimes.com/2018/09/26/us/politics/brett-kavanaugh-accusers-women.html

38.

Hills

P. J.

Pleva

Seib

Cole

(2021). Understanding how university students use perceptions of consent, wantedness, and pleasure in labeling rape. Archives of Sexual Behavior, 50(1), 247–262. https://doi.org/10.1007/s10508-020-01772-1

39.

Hughes

Huby

(2002). The application of vignettes in social and nursing research. Journal of Advanced Nursing, 37(4), 382–386. https://doi.org/10.1046/j.1365-2648.2002.02100.x

40.

IUP Center for Health and Well-Being. (2023). Green dot. https://www.iup.edu/chwb/services/green-dot/index.html

41.

Jouriles

E. N.

Krauss

N. L.

Vanyard

V. L.

McDonald

(2018). Bystander programs addressing sexual violence on college campuses: A systematic review and meta-analysis of program outcomes and delivery methods. Journal of American College Health, 66(6), 457–466. https://doi.org/10.1080/00224490701263660

42.

Kalof

(1993). Rape-supportive attitudes and sexual victimization experiences of sorority and nonsorority women. Sex Roles, 29, 767–780.

43.

Kanekar

Nazareth

A. M.

(1988). Attributed rape victim’s fault as a function of her attractiveness, physical hurt, and emotional disturbance. Social Behaviour, 3(1), 37–40.

44.

Kaya

(2019). Gender and violence: Rape as a spectacle on prime-time television. Social Science Information, 58(4), 681–700. https://doi.org/10.1177/0539018419883831

45.

Kosloski

A. E.

Diamond-Welch

B. K.

Mann

(2018). The presence of rape myths in the virtual world: A qualitative textual analysis of the Steubenville sexual assault cause. Violence & Gender, 5(3), 166–173. https://doi.org/10.1089/vio.2017.0067

46.

Koss

M. P.

Gaines

(1993). The prediction of sexual aggression by alcohol use, athletic participation, and fraternity affiliation. Journal of Interpersonal Violence, 8(1), 94–107. https://doi.org/10.1177/088626093008001007

47.

Krebs

C. P.

Lindquist

Berzofsky

Shooks-Sa.

Peterson

(2016). Campus climate survey validation study: Final technical report. U.S. Department of Justice, office of Justice Programs, Bureau of Justice Statistics.

48.

Lambert

Clarke

(2004). Crime, capital punishment, and knowledge: Are criminal justice majors better informed than other majors about crime and capital punishment? The Social Science Journal, 41(1), 53–66. doi: 10.1016/j.soscij.2003.10.005

49.

Langhinrichsen-Rohling

Monson

C. M.

(1998). Marital rape: Is the crime taken seriously without co-occurring physical abuse? Journal of Family Violence, 13, 433–443.

50.

Langton

Sinozich

(2014). Rape and sexual assault among college-aged females, 1995- 2013. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

51.

Lee

Pomeroy

Yoo

Rheinboldt

K. T.

(2005). Attitudes toward rape: A comparison between Asian and Caucasian college students. Violence Against Women, 11(2), 177–196. https://doi.org/10.1177/1077801204271663

52.

Leithead

(2022). False reports – percentage. https://evawintl.org/best_practice_faqs/falsereports-percentage/

53.

Littleton

Axsom

Grills-Taquechel

(2009). Sexual assault victim’s acknowledgment status and revictimization risk. Psychology of Women Quarterly, 33, 34–42. https://doi.org/10.1111/j.1471-6402.2008.01472.x

54.

Liyanapathirana

N. S.

Samkin

Low

Davey

(2016). Developing written and video vignettes for ethical decision-making research. New Zealand Journal of Applied Business Research, 14(2), 29–41.

55.

Marsil

D. F.

McNamara

(2016). An examination of the disparity between self-identified versus legally identified rape victimization: A pilot study. Journal of American College Health, 64(5), 416–420. doi: 10.1080/07448481.2015.1107838

56.

McCray

K. L.

(2015). Intercollegiate athletes and sexual violence: A review of literature and recommendation for further study. Trauma, Violence, and Abuse, 16(4), 438–443. https://doi.org/10.1177/1524838014537907

57.

McDonald

M. M.

Coleman

Brindley

(2019). Calibrating fear of rape: Threat likelihood and victimization costs. Personality and Individual Differences, 139, 326–330. https://doi.org/10.1037/t01616-000

58.

me too. (2014). me too. https://metoomvmt.org/

59.

Ministry of Justice. (2010). Providing anonymity to those accused of rape: An assessment of evidence. Crown Copyright.

60.

Morgan

R. E.

Truman

J. L.

(2020). Criminal victimization, 2019. Bureau of Justice Statistics.

61.

Murphy-Oikonen

McQueen

Miller

Chambers

Hiebert

(2022). Unfounded sexual assault: Women’s experiences of not being believed by the police. Journal of Interpersonal Violence, 37(11–12), 8916–8940. https://doi.org/10.1177/0886260520978190

62.

Musso

M. G.

(2022). Social change and media representations of rape: How TV series reshape the global imaginary on violence against women (any why). H-ermes: Journal of Communication, 20, 219–246. https://doi.org/10.1285/i22840753n209219

63.

National Center for Education Statistics. (2023). Criminal incidents at postsecondary institutions. U.S. Department of Education, Institute of Education Sciences.

64.

National Crime Victimization Survey. (2023). Terms & definitions. https://ncvs.bjs.ojp.gov/terms

65.

National Sexual Violence Resource Center. (2016). NSRVP tip sheet: Going to college: What families need to know about sexual assault and safety on campus. https://www.nsvrc.org/sites/default/files/2016-06/publications_nsvrc_tip-sheet_going-to-college-what-families-need-know-sexual-assault-safety-campus.pdf

66.

Navarro

J. C.

Tewksbury

(2019). National comparisons of rape myth acceptance predictors between nonathletes and athletes from multi-institutional settings. Sexual Abuse, 31(5), 543–559. https://doi.org/10.1177/1079063217732790

67.

Newcombe

P. A.

van den Eynde

Hafner

Jolly

(2008). Attributions of responsibility for rape: Differences across familiarity of situation, gender, and acceptance of rape myths. Journal of Applied Social Psychology, 38(7), 1736–1754. https://doi.org/10.1111/j.1559-1816.2008.00367.x

68.

NSVRC. (2012). False reporting. Department of Justice, Office on Violence Against Women.

69.

Orchowski

L. M.

Edwards

K. M.

Hollander

J. A.

Banyard

V. L.

Sean

C. Y.

Gidycz

C. A.

(2020). Integrating sexual assault resistance, bystander, and men’s social norms strategies to prevent sexual violence on college campuses: A call to action. Trauma, Violence & Abuse, 21(4), 811–827. https://doi.org/10.1177/1524838018789153

70.

Passmore

(2023). The underreporting and dismissal of sexual assault cases against women in the United States. https://ballardbrief.byu.edu/issue-briefs/the-underreporting-and-dismissal-of-sexual-assault-cases-against-women-in-the-united-states

71.

PeConga

E. K.

Spector

J. E.

Smith

R. E.

(2022). Judgments about male victims or sexual assault by women: A 35-year replication study. Journal of Interpersonal Violence, 37, 23–24. https://doi.org/10.1177/08862605211062990

72.

Pittsburgh Post-Gazette. (2018, August 16). Abuse allegations against Pittsburgh priests named in grand jury report released. Pittsburgh Post-Gazette. http://www.post-gazette.com/news/faith-religion/2018/08/16/grand-jury-report-pa-Diocese-of-Pittsburgh-priests-accused-sexual-misconduct-sortable-list-names/stories/201808160149

73.

RAINN. (2024). Victims of sexual violence: Statistics. https://www.rainn.org/statistics/victims-sexual-violence

74.

Rebeiz

M. J.

Harb

(2010). Perceptions of rape and attitudes toward women in a sample of Lebanese students. Journal of Interpersonal Violence, 25(4), 735–752. https://doi.org/10.1177/0886260509334410

75.

Rennison

C. M.

(2002). Rape and sexual assault: Reporting to police and medical attention, 1992-2000. U.S. Department of Justice, Office of Justice Programs.

76.

Romero-Sanchez

Megias

J. L.

Krahe

(2012). The role of alcohol and victim sexual interest in Spanish students’ perceptions of sexual assault. Journal of Interpersonal Violence, 27(11), 2230–2258.

77.

Ryalls

E. D.

(2021). Representing rape culture on teen television. Popular Communication, 419(1), 1–13. https://doi.org/10.1080/15405702.2020.1868044

78.

Sampson

(2003). Acquaintance rape of college students. U.S. Department of Justice, Office of Community Oriented Policing Services. http://www.cops.usdoj.gov/html/cd_rom/inaction1/pubs/AcquaintanceRapeCollegeStudents.pdf

79.

Santelli

J. S.

Grilo

S. A.

Choo

T.-H.

Diaz

Walsh

Wall

Hirsch

J. S.

Wilson

P. A.

Gilbert

Kahn

Mellins

C. A.

(2018). Does sex education before college protect students from assault in college? PLoS One, 13(11), e0205951. https://doi.org/10.137/journal.pone.0205951

80.

Sauer

S. J.

(2011). Taking the reins: The effects of new leader status and leadership style on team performance. Journal of Applied Psychology, 96(3), 574–587. https://doi.org/10.1037/a0022741

81.

Schneider

L. J.

Mori

L. T.

Lambert

P. L.

Wong

A. O.

(2009). The role of gender and ethnicity in perceptions of rape and its aftereffects. Sex Roles 60, 410–421. https://doi.org/10.1007/s11199-008-9545-9

82.

Seabrook

R. C.

Ward

L. M.

Giaccardi

(2018). Why is fraternity membership associated with sexual assault? Exploring the roles of conformity to masculine norms, pressure to uphold masculinity, and objectification of women. Psychology of Men & Masculinity, 19(1), 3–13. http://dx.doi.org/10.1037/men0000076

83.

Sentürk

Müller

H. G.

(2005). Covariate-adjusted regression. Biometrika, 92(1), 75–89.

84.

Sheehan

(2018, August 14). 301 ‘predator priests’ named in Pa. grand jury sex abuse report: ‘They were raping little boys & girls.’ KDKA2 CBS Pittsburgh. https://pittsburgh.cbslocal.com/2018/08/14/pennsylvania-diocese-sex-abuse-grand-jury-report-released/

85.

Siegel

J. A.

Anderson

R. A.

Silver

K. E.

Mitchell

T. L.

(2021). Yes, (most) men now what rape is: A mixed-methods investigation into college men’s definitions of rape. Psychology of Men & Masculinity, 22(2), 401–411. https://doi.org/10.1037/men0000337

86.

Sinozich

Langton

(2014). Rape and sexual assault victimization among college-age females, 1995-2013. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

87.

Sleath

Bull

(2010). Male rape victim and perpetrator blaming. Journal of Interpersonal Violence, 25(6), 969–988. https://doi.org/10.1177/0886260509340534

88.

Southern Connecticut State University. (2022). Rape culture, victim blaming, and the facts. https://inside.southernct.edu/sexual-misconduct/facts

89.

Step Up! Program. (n.d.). About. https://stepupprogram.org/about/

90.

Taylor

B. J.

(2006). Factorial surveys: Using vignettes to study professional judgement. The British Journal of Social Work, 36(7), 1187–1207. https://doi.org/10.1093/bjsw/bch345

91.

Tsoudis

(2000). Does majoring in criminal justice affect perceptions of criminal justice? Journal of Criminal Justice Education, 11(2), 225–236.

92.

Vandiver

D. M.

Dupalo

J. R.

(2013). Factors that affect college students’ perceptions of rape: What is the role of gender and other situational factors? International Journal of Offender Therapy & Comparative Criminology, 57(2), 592–612.

93.

Varelas

Foley

L. A.

(1998). Blacks’ and Whites’ perceptions of interracial and intraracial date rape. The Journal of Social Psychology, 138(3), 382–400.

94.

Viki

G. T.

Abrams

Masser

(2004). Evaluating stranger and acquaintance rape: The role of benevolent sexism in perpetrator blame and recommended sentence length. Law and Human Behavior, 28(3), 295–303. https://doi.org/10.1023/B:LAHU.0000029140.72880.69

95.

Weiss

K. G.

(2013). “You just don’t report that kind of stuff”: Investigating teens’ ambivalence toward peer-perpetrated, unwanted sexual incidents. Violence and Victims, 28(2), 288–302. https://doi.org/10.1891/0886-6708.11-061

96.

Wells

(2015, October 28). ‘Guilty until proven innocent’: Life after a false rape accusation. The Telegraph. https://www.telegraph.co.uk/men/thinking-man/11912748/Guilty-until-proven-innocent-life-after-a-false-rape-accusation.html

97.

Whatley

M. A.

(2005). The effect of participant sex, victim dress, and traditional attitudes on causal judgments for marital rape victims. Journal of Family Violence, 20(3), 191–200. https://doi.org/10.1007/s10896-005-3655-8

98.

White

B. H.

Kurpius

S. E. R.

(2002). Effects of victim sex and sexual orientation of perceptions of rape. Sex Roles, 46(5/6), 191–200.

99.

White

Yamawaki

(2009). The moderating influence of homophobia and gender-role traditionality on perceptions of male rape victims. Journal of Applied Social Psychology, 39(5), 1116–1136.

100.

Wilson

L. C.

Miller

K. E.

(2016). Meta-analysis of the prevalence of unacknowledged rape. Trauma, Violence, & Abuse, 17(2), 149–159. https://doi.org/10.1177/1524838015576391

101.

Wilson

L. C.

Truex

H. R.

Murphy-Neilson

M. C.

Kunaniec

K. P.

Pamlanye

J. T.

Reed

R. A.

(2021). How female disclosure recipients react to women survivors: The impact of rape acknowledgment and rejection of rape myths. Sex Roles, 84, 337–346. https://doi.org/10.1007/s11199-020-01169-3

102.

Wolitzky-Taylor

K. B.

Resnick

H. D.

McCauley

J. L.

Amstadter

A. B.

Kilpatrick (2011). Is reporting of rape on the rise? A comparison of women with reported versus unreported rape experiences in the National Women’s Study - Replication. Journal of Interpersonal Violence, 26(4), 807–832. doi: 10.1177/0886260510365869

103.

Yamawaki

Tschanz

B. T.

(2005). Rape perception differences between Japanese and American college students: On the mediating influence of gender role traditionally. Sex Roles: A Journal of Research, 52(5/6), 379–392. http://doi.org/10.1007/s11199-005-2680-7

104.

Young

Desmarais

S. L.

Baldwin

J. A.

Chandler

(2016). Sexual coercion practices among undergraduate male recreational athletes, intercollegiate athletes, and non-athletes. Violence Against Women, 23(7), 795–812. https://doi.org/10.1177/1077801216651339