Building a Model to Predict Sexual Assault Victimization Frequency Among Undergraduate Women

Abstract

Previous research has identified several factors, including sexual risk behaviors, alcohol consumption, sexual refusal assertiveness, impulse control difficulties, drinking to cope, and sex to cope, as being associated with sexual assault victimization. Data were collected from 465 adult, undergraduate women, and analyzed using structural equation modeling to determine how these variables related to one another. Results showed that together, these factors predicted 17.1% of the variance in victimization frequency. These findings may help future researchers better understand the etiology of sexual assault victimization on college campuses and prove crucial to the development of future intervention programs which reduce victimization.

Keywords

sexual assault victimization alcohol consumption sexual refusal assertiveness impulse control difficulties sexual risk behaviors

Introduction

Sexual assault victimization is a major problem facing women on college campuses. In the first major, nationwide study of its kind, 53.7% of college women self-reported that they had been victims of sexual assault, including 15.4% who indicated that they had experienced a completed rape (Koss et al., 1987). Unfortunately, although these rates have declined somewhat in the decades since the publication of this landmark study, rates of sexual assault victimization are still alarmingly high. Specifically, a review of 34 studies assessing victimization among undergraduates found that up to 44.2% of college women reported victimization, including as many as 8.4% who reported they had been forcibly raped and 14.2% who reported that they had been raped while incapacitated due to alcohol or other drugs (Fedina et al., 2018). Unfortunately, attempts to reduce or stop sexual assault perpetration have largely been unsuccessful, likely due to the variety and complexity of factors which contribute to sexual assault, and the absence of a “one-size-fits-all” approach to prevention that is effective for each of these factors and situations (Newlands & O’Donohue, 2016). Furthermore, sexual assault perpetrators are known to target women whom they perceive to be vulnerable due to environmental or personality factors (Clark & Quadara, 2010; Stevens, 1994). Thus, this article aims to provide a brief review of some of these factors which may be used by perpetrators when selecting women to target, to develop a single model predicting victimization frequency, and to better inform future prevention efforts.

Previous research has identified several risk factors which may be targeted by perpetrators and are associated with sexual assault victimization (e.g., Franklin, 2016). For instance, prominent proximal risk factors associated with victimization in many studies include sexual risk behaviors (Ray et al., 2021) and alcohol consumption during dating and sexual situations (Parkhill et al., 2016; Testa & Livingston, 2018). In contrast, other factors, most notably sexual refusal assertiveness, have emerged as proximal protective factors against sexual assault victimization (Davis et al., 2018; Ullman & Vasquez, 2015). Finally, still other factors, such as impulse control difficulties (Messman-Moore et al., 2013; Pratt et al., 2014; Ullman & Vasquez, 2015), drinking to cope (Fossos et al., 2011; Neilson et al., 2018), and sex to cope (Orcutt et al., 2005) have been more distally associated with sexual assault victimization. However, in spite of these standalone associations, no study has successfully examined these disparate predictors of sexual assault victimization simultaneously within a single model to examine the ways in which they may interact with one another. However, some research has attempted to model how risk factors may be related to each other and increase vulnerability to sexual assault victimization. For example, Franklin (2016) explored how several risk factors (e.g., substance use, self-control, number of sexual partners, and contact with fraternity men) may be related to one another and to victimization among women in sororities. However, the conclusions drawn from this study are limited by the characteristics inherent to the sample that may increase vulnerability to victimization, namely, that sorority members tend to hold more traditional beliefs regarding gender roles and consume alcohol at a higher rate than individuals who are not in a sorority (Kalof, 1993; Scott-Sheldon et al., 2008). Therefore, the development of a comprehensive victimization model for college women is needed to examine how risk factors may directly or indirectly influence sexual assault victimization.

Risk Factors for Sexual Assault Victimization

Impulse Control Difficulties

Impulse control difficulties, or difficulties controlling one’s impulses, especially when experiencing negative emotions (Gratz & Roemer, 2004) have been implicated as a risk factor for sexual assault victimization (Franklin, 2011; Messman-Moore et al., 2013; Pratt et al., 2014). For example, one study demonstrated that difficulty with controlling one’s behavior was positively associated with alcohol-related sexual assault victimization (Franklin, 2011). However, most research examining the relationship between impulse control difficulties and more general sexual assault victimization has looked at how impulse control difficulties relate to other distal predictors of victimization, such as avoidant coping behaviors, which include drinking or having sex to cope with negative emotions. These results suggest that those who have more difficulty with controlling their impulses are also more likely to drink or have sex to cope (Bird et al., 2019; Messman-Moore & Ward, 2014). Such results are strengthened by a longitudinal study which demonstrated that difficulties with impulse control preceded coping behaviors, in that women’s impulse control difficulties prospectively predicted their subsequent likelihood of drinking to cope (Watkins et al., 2015). Thus, individuals who report difficulties with impulse control appear to be more likely to drink or have sex to cope with unwanted, negative emotions, leading to an increased risk of being victimized.

Drinking to Cope

Individuals who use alcohol to cope, meaning that they drink alcohol to help cope with negative emotions (Cooper et al., 1998), may also be at an increased risk for other maladaptive behaviors as well. Specifically, individuals who drink to cope with negative emotions consume more alcohol, are more likely to engage in binge drinking (Ehlke & Kelley, 2019), and are more likely to drink prior to or during sexual situations (M. L. Kelley et al., 2018; Messman-Moore et al., 2015). Likewise, drinking to cope is associated with increased sexual risk behaviors, such as having sex with a larger number of partners; having more frequent, short-term, casual sexual encounters; or having unprotected sex (Turchik & Garske, 2009). In addition, those who drink to cope are also more likely to engage in sexual risk behaviors than those who drink for other reasons (Dvorak et al., 2016).

Sex to Cope

Similarly, some individuals may engage in sex to cope, meaning that they have sex to decrease negative affect and increase positive affect (Cooper et al., 1998), and women who use sex to cope are also at risk of engaging in similar maladaptive behaviors as those who drink to cope. Specifically, individuals who use sex to cope are also more likely to drink alcohol before or during sex (Grossbard et al., 2007). Sex to cope is also associated with an increase in sexual risk behaviors, such as having a higher number of sexual partners (Gardner, 2017; Grossbard et al., 2007). Thus, drinking and having sex to cope are similarly associated with sexual risk behaviors and alcohol consumption before and during sex, which are two proximal risk factors for sexual assault victimization due to perpetrators perceiving women who are drinking or engaging in casual sex as being more vulnerable to perpetration (Parkhill et al., 2016; Ray et al., 2021; Ullman & Vasquez, 2015).

Sexual Risk Behaviors

Perpetrators of sexual assault are more likely to target individuals who take part in certain “sexual risk behaviors” for perpetration because they perceive such individuals as being more vulnerable to coercion (Franklin, 2010; Wegner et al., 2017); sexual risk behaviors may include having more sexual partners, having sex at a younger age, and not using condoms (Ray et al., 2021). This perception may arise because women who engage in more sexual risk behaviors are less likely to assertively refuse sex. Studies examining women’s intentions to engage in safe sex have found that women who do not regularly use condoms are less sexually assertive than women who consistently use condoms, perhaps because women who are less assertive were uncomfortable requesting that their partner use a condom or did not perceive risky sex to be as risky as more assertive women (Morokoff et al., 2009; Parks et al., 2009; Stoner et al., 2007). Similarly, women with more total sexual partners and who prefer short-term, casual sexual partners also refuse sex less assertively than women with fewer partners or who prefer long-term, committed partners (Ullman & Vasquez, 2015; Walker, 2011).

Alcohol Consumption During Dating and Sexual Situations

The role of alcohol use in sexual assault is well established (see Lorenz & Ullman, 2016 for a review), but acute alcohol intoxication may decrease a woman’s sexual refusal assertiveness when she is experiencing pressure to have unwanted sex. Notably, several experimental studies show that women under the influence of alcohol are more likely to respond passively and less likely to respond assertively during a vignette in which she is being pressured into unwanted sex (Abbey et al., 2002; Davis et al., 2004; Testa et al., 2006). Furthermore, intoxicated women are more likely to respond to the situation with uncertainty, which makes them less likely to refuse assertively (Stoner et al., 2007). As such, sexual assault perpetrators often seek out intoxicated women as targets of their assaults (Clark & Quadara, 2010; Stevens, 1994).

Sexual Refusal Assertiveness

Unlike the other factors discussed in this article, previous research shows that women’s sexual refusal assertiveness, or how assertively an individual behaves when in a sexual situation where they do not want to have sex (Morokoff et al., 1997), serves as a potent protective factor against sexual assault victimization (E. L. Kelley et al., 2016; Relyea & Ullman, 2017; Ullman & Vasquez, 2015). Notably, longitudinal research shows that sexual refusal assertiveness prospectively predicts sexual assault victimization (E. L. Kelley et al., 2016). These results are also supported by research conducted on male perpetrators, which shows that men behave less aggressively during a hypothetical scenario in which a woman is assertive compared to when she is passive (Wegner et al., 2017), likely because they view women who behave in a more passive manner as being more vulnerable (Stevens, 1994).

The Present Study

The purpose of this study was to develop and evaluate a model of sexual assault victimization frequency which includes a variety of factors perpetrators perceive as making women more vulnerable to being victimized, including impulse control difficulties, maladaptive coping, alcohol consumption, and sexual risk behaviors, among others (Clark & Quadara, 2010; Stevens, 1994). Although many studies have examined the relations between each of these individual factors and sexual assault victimization (see Decker & Littleton, 2018 for a review), no study has examined all of them within a single model. Such a model is important to determine how these variables may influence and affect each other to predict victimization frequency, and to better understand its etiology. Thus, this study will examine these variables as proximal and distal factors within a model of sexual assault victimization, to identify women at risk for victimization, and to develop and deploy intervention programs combating this issue.

Hypotheses

The hypothesized model which this study is testing is available in Figure 1. The development of this model was based on the previously cited research, which provided the rationale for the hypothesized relations for each of these individual factors, as well as their placement in the model. In addition, the literature demonstrates that childhood sexual abuse (CSA) and posttraumatic stress disorder (PTSD) increase one’s likelihood of both sexual assault victimization and many of the risk factors for victimization present in this model (see Decker & Littleton, 2018 for a review), mainly through emotion regulation-motivated drinking behavior (Hannan et al., 2017) and avoidance or hyperarousal (Batchelder et al., 2018; Risser et al., 2006). Therefore, participants’ PTSD symptoms and exposure to CSA were entered into this model as covariates to test the effects of these other factors independently of CSA and other forms of trauma (Hypothesis 1).

In addition to these covariates, the proposed model also specified several other relations between variables seen in previous research; notably, women who reported more impulse control difficulties were expected to be more likely to use sex or alcohol to cope with negative emotions (Hypothesis 2). Subsequently, increases in drinking or having sex to cope with negative emotions were expected to lead to increases in sexual risk behaviors and an increased likelihood of consuming alcohol when in dating or sexual situations (Hypothesis 3). As a result, these increases in sexual risk behaviors and alcohol consumption during dating or sexual situations were expected to lead to reduced assertiveness when in unwanted sexual situations, either because of the effects of alcohol intoxication, or because of the increased risk associated with these encounters (Hypothesis 4). Also, reduced assertiveness when refusing unwanted sex following risky sexual behaviors or alcohol consumption was expected to be associated with an increase in the frequency of sexual victimization (Hypothesis 5). Finally, drinking to cope with negative emotions and having sex to cope with negative emotions were expected to be positively correlated with one another, as were sexual risk behaviors and alcohol consumption during dating or sexual situations (Hypothesis 6).

Method

Participants

A total of 585 undergraduate women who were 18 or older were recruited to participate via the psychology department subject pool of a large, Midwestern, suburban university. Of the 585 women who signed up for this online study, 20 were excluded because they did not complete the survey before the allotted deadline. In addition, several “attention check” questions were nested within this survey (e.g., “please answer ‘very often true’ to this question”), to ensure that the women were providing accurate responses to the questions they were asked, and an additional 100 participants were excluded for providing an inaccurate response on at least one of these questions. Finally, as this study recruited college students, and surveyed participants regarding attitudes and behaviors typical of college-aged women, 11 participants of nontraditional age (i.e., over 30) were also excluded, leaving a sample with a mean age of 19.59 (SD = 1.996). Following these omissions, the final sample consisted of data from 454 women; demographic information about the final sample is available in Table 1.

Table 1.

Demographic Information About the Final Sample.

Variable	n	%
Age
18–19	295	65.0
20–22	121	26.7
23–25	28	6.2
26–30	10	2.2
Race
White	349	76.9
African American	41	9.0
Asian American	20	4.4
Arabic	16	3.5
Native American	1	0.2
Pacific Islander	1	0.2
Multiracial	10	2.2
Other	14	3.1
Did not respond	2	0.4
Ethnicity
Hispanic/Latino	19	4.2
Not Hispanic/Latino	428	94.2
Did not respond	7	1.5
Sexual orientation
Exclusively heterosexual	381	83.9
Mostly heterosexual	37	8.1
Bisexual	8	1.8
Mostly gay	5	1.1
Exclusively gay	5	1.1
Did not respond	18	4.0
Relationship status
Single, not dating exclusively	178	39.2
Single, dating exclusively	237	52.2
Living with partner	24	5.3
Engaged	7	1.5
Married	5	1.1
Did not respond	3	0.7

Procedure

Participants viewed the advertisement for this study online, via the psychology department subject pool, where it was presented as a study examining the relations between participants’ childhood experiences, personality characteristics, and social and interpersonal behaviors. After they enrolled in the survey, participants were given a link to complete the survey, hosted on Qualtrics.com, and they consented to the study electronically on the survey’s first page. These participants had roughly 1 week to complete the study after enrollment. Participants were also informed that their responses would remain confidential and they were free to refuse to answer any question on the survey for any reason by selecting a “prefer not to answer” option. All participants answered the questions in the same order, which took approximately 30 minutes to complete, and after they completed the survey, participants were automatically compensated with partial course credit for their participation. All procedures were approved by the Human Subjects Institutional Review Board prior to any data collection.

Measures

CSA

CSA was assessed with the 5-item sexual abuse subscale of the Childhood Trauma Questionnaire (CTQ; Bernstein et al.,1994, 2003). These items assessed how often the participants were sexually abused by another individual before they were 14 years old, and were assessed on a 5-point scale, from 1 = never true to 5 = very often true. A sample item from this subscale is “When I was growing up, someone threatened to hurt me or tell lies about me unless I did something sexual with them.” The mean of these five items was calculated and used as a covariate in this model, and this assessment showed excellent reliability, with Cronbach’s α = .958.

PTSD symptoms

Symptoms of PTSD were assessed using the 20-item PTSD Checklist for the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-V; PCL-5; Weathers et al., 2013). Items from this scale asked participants about PTSD symptoms they may have experienced within the past month as a result of previous threatened or actual sexual violence, serious injury, or death to the participant, a close family member, or a close friend. These items were assessed on a 5-point scale from 0 = not at all to 4 = extremely, and a sample item from this questionnaire asked participants how much they had been bothered by “repeated, disturbing dreams of the stressful experience?” Participants’ responses were summed to obtain an overall scale of their past month PTSD symptoms for use as a covariate within the present model, and this scale showed excellent reliability overall, with Cronbach’s α = .947.

Impulse control difficulties

Participants’ impulse control difficulties were assessed using the 6-item impulse control difficulties subscale of the Difficulties in Emotion Regulation Scale (DERS; Gratz & Roemer, 2004). These questions assessed the extent to which participants were able to remain in control of their behaviors, particularly when they were upset, and were assessed on a 5-point scale, from 1 = almost never (0%–10%) to 5 = almost always (91%–100%). A sample item from this subscale is “When I’m upset, I feel out of control.” The mean of participants’ responses to these six items was calculated, and used as an assessment of their impulse control difficulties. This assessment showed good reliability, with Cronbach’s α = .860.

Drinking to cope

Participants’ drinking to cope was measured using the 5-item coping subscale from Cooper’s (1994) Drinking Motives scale. These items assessed how often participants consumed alcohol to cope with upset feelings, and a sample item included “How often do you drink to forget about your problems?” Participants’ responses to questions on this subscale were assessed on a five-point scale, from 1 = never/almost never to 5 = almost always/always, and the average of participants’ responses on these five items was calculated as an assessment of their use of drinking to cope. Overall, this subscale showed good overall reliability, with Cronbach’s α = .884.

Sex to cope

Likewise, participants’ use of sex to cope with negative emotions was assessed with the 5-item coping subscale from the Motivations for Sex scale (Cooper et al., 1998). This scale included items asking participants how often they had sexual intercourse to reduce negative feelings, and a sample item was “How often do you have sex to cope with upset feelings?” Participants’ responses to this questionnaire were assessed on a 5-point scale, from 1 = almost never (0%–10%) to 5 = almost always (91%–100%). The mean of each participant’s responses to these five items was calculated and entered into the model as an assessment of their use of sex to cope, and these items showed good reliability, with Cronbach’s α = .863.

Sexual risk behaviors

Participants’ sexual risk behaviors within the past 6 months were measured using the 23-item sexual risk survey (Turchik & Garske, 2009). This survey assessed various vaginal, oral, and anal sexual acts in addition to other sexual risk behaviors, which included kissing, fondling, petting, and digital stimulation of the genitals or anus. The sexual risk behaviors were assessed across five dimensions: sexual risk taking with uncommitted partners, risky sex acts, impulsive sexual behaviors, intent to engage in sexual risk behaviors, and risky anal sex acts; responses were assessed numerically, ranging from 0 = times to 51+ = times. A sample item from this questionnaire was “In the past six months, how many times have you had an unexpected and unanticipated sexual experience?.” As recommended by Marcus et al., (2011), the SRS was scored continuously, with the mean of participants’ responses to all of these items used as an assessment of their sexual risk behaviors. These items showed acceptable reliability, with Cronbach’s α = .763.

Alcohol consumption during dating and sexual situations

Participants’ alcohol consumption during dating and sexual situations was assessed using the 4-item Alcohol Consumption in Dating and Sexual Situations scale (Abbey et al., 1998; Abbey & McAuslan, 2004). Two of these items asked participants how often they drank alcohol when they were on a date and when they had consensual sex. These two items were assessed on a 7-point scale, from 1 = never to 7 = every time. The other two items asked participants how many alcoholic drinks they typically consumed when they were on a date or having consensual sex, which were assessed using open-ended, numerical responses. Consistent with previous research, participants’ responses to the two dating items were multiplied together to form a quantity by frequency measure of alcohol consumption while dating. Likewise, participants’ responses regarding the quantity and frequency with which they consumed alcohol while having sexual intercourse were also multiplied together to form a quantity by frequency measure of alcohol consumption during sex (Abbey et al., 1998; Abbey & McAuslan, 2004). These assessments of quantity and frequency were then z-scored and averaged together to form a single assessment of participants’ alcohol consumption during dating and sexual situations.

Sexual refusal assertiveness

Participants’ sexual refusal assertiveness was assessed using the 6-item refusal subscale of the Sexual Assertiveness Scale (Morokoff et al., 1997). Responses were obtained on a 5-point scale, from 1 = never, 0% of the time to 5 = always, 100% of the time. A sample item was “I refuse to let my partner touch my breasts if I don’t want that, even if my partner insists.” The average of these six items was calculated and used as a measure of participants’ sexual refusal assertiveness during data analysis. These items showed an acceptable level of reliability, with Cronbach’s α = .740.

Sexual assault victimization frequency

Finally, the frequency with which participants had previously been victimized by sexual assault since they were 14 years old was measured using the Revised Sexual Experiences Survey (SES; Koss et al., 1987; Parkhill & Abbey, 2008). This survey contained 16 questions which asked participants about various tactics that may have been used to perpetrate various types of forced sexual acts against them, including overwhelming them with arguments and pressure, showing displeasure, threatening or using physical force, giving them alcohol or drugs, or taking advantage of them when they were too intoxicated to consent. In addition, the questions about these tactics were examined in regards to four different types of forced sex which the women may have been victimized by: forced sexual touching, oral/anal sex or penetration by an object, attempted intercourse, and completed intercourse. Responses to the questions on this survey were collected as open-ended, numerical responses, and were summed to form a count variable of the frequency with which each woman had been victimized by an act of sexual aggression. A sample item from this questionnaire was “How many times has a man made you have sexual intercourse with him when you didn’t want to by giving you alcohol or drugs?” The items on this survey showed good reliability, with Cronbach’s α = .857.

Data Analysis

Preliminary Analyses

Prior to conducting the main analysis, the bivariate correlations, means, and standard deviations of this study’s variables were examined, and these results are available in Table 2. In addition, participants’ responses to the SES were also examined, and results showed that 42.6% (N = 198) of participants reported some form of victimization, while the remaining 57.4% (N = 267) reported that they had not been victimized. More specifically, when categorized into mutually exclusive categories, 8.0% (N = 37) of the overall sample reported their most severe victimization experience was forced sexual contact, 15.3% (N = 71) reported it was verbal coercion, 3.7% (N = 17) reported it was attempted rape, and 15.7% (N = 73) reported at least one competed rape. The hypothesized model outlined below was conceptualized based on the results of previous research, and the final model was conceptualized using both previous research as well as the aforementioned bivariate correlations and Mplus’s model modification indices. In addition, participants produced a small amount of missing data (1.8%), which was handled using maximum likelihood estimation.

Table 2.

Bivariate Correlations, Means, and Standard Deviations for Study Variables.

	1	2	3	4	5	6	7	8	9
1. CSA
2. PTSD symptoms	.356^‡
3. Drinking to cope	.141**	.220^‡
4. Sex to cope	.155**	.203^‡	.284^‡
5. Impulse control difficulties	.095*	.275^‡	.337^‡	.263^‡
6. Sexual risk behaviors	.122**	.136**	.174^‡	.246^‡	.096*
7. Alcohol use during dating and sexual situations	.093*	.158^‡	.416^‡	.277^‡	.172^‡	.435^‡
8. Sexual refusal assertiveness	−.063	−.146**	−.139**	−.239^‡	−.131**	−.070	−.172^‡
9. Sexual assault victimization frequency	.316^‡	.159^‡	.003	.109*	.001	.225^‡	.188^‡	−.184^‡
M	1.245	14.040	1.626	1.392	2.008	2.012	1.776	4.119	7.709
SD	0.775	18.405	0.872	0.612	0.824	2.697	1.137	0.854	31.370

Note. CSA = childhood sexual abuse; PTSD = posttraumatic stress disorder.

p ≤ .05. **p < .01. ^‡p < .001.

Path Analysis

All of the models assessed in this study were analyzed using Mplus version 7.11 (Muthén & Muthén, 2013), using maximum likelihood estimation, due to its robustness to violations of normality (Chou & Bentler, 1995). As previous work recommends using multiple indices of fit to evaluate a model during path analysis (Bollen, 1989), the models assessed in this study were evaluated using both the root mean square error of approximation (RMSEA; MacCallum & Austin, 2000; Steiger & Lind, 1980) the Comparative Fit Index (CFI; Bentler & Bonett, 1980; Browne & Cudeck, 1992), the Tucker–Lewis Index (TLI; Tucker & Lewis, 1973), and the root mean squared residual (SRMR; Bentler, 1995) in addition to the traditional chi-square test. Based on previous research, CFI and TLI values of greater than .95, an RMSEA value of less than .06, and an SRMR value of less than .08 denoted acceptable fit (West et al., 2012).

Results

Hypothesized Model

This study’s hypothesized model did not fit the data well, χ² (10, N = 454) = 38.908, p < .001; RMSEA = .080; CFI = .931; TLI = .772; SRMR = .043. When examining the results of this model, the model showed support for hypotheses 1, 2, 3, 5, and 6, and partial support for Hypothesis 4. Specifically, all of the hypothesized pathways were supported in the expected direction, with the exception of the effect of sexual risk behaviors on sexual refusal assertiveness, which was not significant. As a result, modifications were made to this model based on existing theory and the model modification indices provided by Mplus, which led to the generation of the final model.

Final Model

The final model fit the data very well, χ² (8, N = 454) = 10.352, p = .241; RMSEA = .026; CFI = .994; TLI = .977; SRMR = .017. The final model contained two additional pathways relative to the hypothesized model. The first was a significant, negative pathway directly from sex to cope to sexual refusal assertiveness, and the second was a significant, positive pathway directly from sexual risk behaviors to victimization frequency. Full results of this final model are available in Figure 2. The final model predicted a total of 17.1% of the variance in victimization frequency.

Indirect Effects

The indirect effects of the variables in the final model were also estimated during data analysis, using 10,000 bootstrapped resamples. Notable indirect effects included that impulse control difficulties had a significant indirect effect on victimization frequency through sex to cope and sexual refusal assertiveness (β = .236, p = .03, 95% CI [.075, .640]), through drinking to cope motives and sexual risk behaviors (β = .210, p = .05, 95% CI [.045, .690]), and through sex to cope and sexual risk behaviors (β = .287, p = .02, 95% CI [.077, .864]). Likewise, sex to cope also had a significant indirect effect on victimization frequency through sexual refusal assertiveness (β = 1.530, p = .01, 95% CI [.571, 3.385]) and through sexual risk behaviors (β = 1.856, p = .004, 95% CI [.503, 4.672]). The full list of all of the results of the indirect effects in the final model are available in Table 3.

Table 3.

Significant Indirect Effects Predicting Victimization Frequency in the Final Model.

	Estimate	SE	95% CI
ICD→SC→SRA→VF	0.236*	0.106	[.075, .640]
ICD→DC→SRB→VF	0.210*	0.109	[.045, .690]
ICD→SC→SRB→VF	0.287*	0.118	[.077, .864]
DC→SRB→VF	0.714*	0.352	[.138, 2.226]
SC→SRA→VF	1.530*	0.598	[.571, 3.385]
SC→SRB→VF	1.856**	0.643	[.503, 4.672]

Note. ICD = impulse control difficulties; DC = drinking to cope; SC = sex to cope; SRB = sexual risk behaviors; SRA = sexual refusal assertiveness; and VF = victimization frequency.

p ≤ .05. **p < .01.

Discussion

The purpose of this study was to develop and test a model of various factors predicting sexual assault victimization frequency, based on existing theory and previous research. As such, several variables were tested within a hypothesized model. This model was modified based on the results, in conjunction with supplemental theories in a manner consistent with the relations between its variables according to the bivariate correlations between variables and the model modification indices supplied by Mplus. The resulting final model was successful in accomplishing the goals of this study in that it was supported by the study’s data in predicting victimization frequency.

Significant Effects on Sexual Assault Victimization Frequency

This study helps to shed light on the complex relationships between many of the variables predicting sexual assault victimization frequency. Notably, although previous research suggests that impulse control difficulties predict sexual assault victimization (Messman-Moore et al., 2015; Ullman & Vasquez, 2015), this study’s model provides specific indirect pathways through which impulse control difficulties may facilitate increases in victimization frequency. Specifically, impulse control difficulties are associated with increases in sex to cope, which is associated with an increase in sexual risk behaviors and a decrease in sexual refusal assertiveness. Increased sexual risk behaviors and decreased sexual refusal assertiveness are each associated with an increased sexual assault victimization frequency. Likewise, greater impulse control difficulties are also associated with greater drinking to cope, which is associated with higher sexual risk behaviors which, once again, are associated with more sexual assault victimization frequency.

Such results corroborate previous research indicating that individuals who have difficulty controlling their emotions when experiencing negative emotions are more likely to engage in maladaptive strategies to reduce their negative emotional experience, such as drinking or having sex (Bird et al., 2019; Messman-Moore & Ward, 2014; Watkins et al., 2015). Unsurprisingly, individuals who use sex to cope with negative emotions are also more likely to engage in sexual risk behaviors, such as having more sexual partners, than individuals who do not use sex to cope with negative emotions (Gardner, 2017; Grossbard et al., 2007). Likewise, individuals who drink to cope are also more likely to engage in sexual risk behaviors (Turchik & Garske, 2009). Especially among undergraduates, this may occur because of the drinking culture which exists at many colleges and universities. Individuals in college who drink to reduce negative affect are likely to obtain their alcohol from a bar or at a house party, which are also strongly associated with casual sexual encounters among college students (Pham, 2019). Regardless of whether the sexual risk behavior is the result of drinking to cope, sex to cope, or some alternative factor, women who engage in sexual risk behaviors are more likely to be viewed as targets by sexual assault perpetrators (Clark & Quadara, 2010) and are more likely to be victimized by them as a result (George et al., 2014; Ullman & Vasquez, 2015). In this manner, impulse control difficulties is distally associated with sexual assault victimization through factors such as maladaptive coping and sexual risk behaviors.

In addition to the relationship with sexual risk behaviors, sex to cope was also associated with a decrease in sexual refusal assertiveness in this study’s model. Although there is little research directly examining the relation between these two variables, previous research does note that avoidant or maladaptive coping strategies, like using sex to cope with negative emotions, are associated with reduced sexual refusal assertiveness (Kennedy & Prock, 2018), perhaps due to a lack of an internal, positive motivation for sex (Kaplinska, 2016) under such circumstances. As a result of reduced assertiveness, perpetrators of sexual assault are more likely to view these women as being vulnerable to sexual assault (Stevens, 1994) and perpetrate sexual assault against them (E. L. Kelley et al., 2016; Wegner et al., 2017).

Implications

The results of the final model in this study help to establish the etiology of sexual assault victimization on college campuses, and as such, the results of this model could be used to reduce the prevalence of sexual assault victimization by identifying women most at risk for victimization, and deploying interventions targeting impulse control difficulties, maladaptive coping strategies, sexual risk behaviors, or sexual refusal assertiveness to reduce their risk. For instance, interventions targeting maladaptive coping behaviors have been shown to be effective (Seiffge-Krenke, 2004), and mindfulness-based interventions are known to reduce impulse control difficulties (Russell et al., 2019). Based on the results of this model, such interventions may be able to reduce the risk of sexual assault victimization based on the downstream effects of these factors. Likewise, these results offer further support for alcohol use interventions already used to combat victimization risk among women who are considered to be at extremely high risk of future victimization (Gilmore et al., 2015). Alternatively, that sexual refusal assertiveness emerged as a protective factor suggests that interventions could seek to bolster environments in which women’s sexual decision-making is empowered, such as interventions encouraging affirmative consent, meaning consent that is ongoing, continuous, and clearly communicated. Implementing such interventions among both men and women would change the culture surrounding consent, and afford women more opportunities to safely refuse unwanted sex (Shumlich & Fisher, 2020). Thus, the results of this study provide multiple pathways through which researchers may identify women who are at risk for frequent sexual assault victimization, as well as specific behaviors or cultural attitudes which should be targeted to reduce the frequency with which women are victimized.

Limitations

The limitations of this study should also be considered. For example, this study employed a correlational, cross-sectional design which limits the conclusions which may be drawn, especially with regard to causation and the temporal order of the factors in the final model. However, many of the pathways included in this study are supported by previous research which includes prospective, longitudinal, or experimental designs (e.g., Kelley et al., 2016; Watkins et al., 2015; Wegner et al., 2017). Still, future research should confirm the results of this study’s final model using experimental and longitudinal designs. In addition, many of the measures included in this study’s model are likely to be considered sensitive by many participants, making them reluctant to disclose such information, and may have led to them being underreported. Appropriate safeguards were put in place to maximize participants’ confidence in disclosing these experiences or behaviors; however, even with these protections, it is extremely likely that some participants still did not feel comfortable disclosing some or all of this information during the survey. Furthermore, although the final model of this study highlights several contributors to sexual assault victimization, it also accounts for only 17.1% of the variance in such frequencies. Other variables, including risk perception, self-efficacy to engage in protective strategies, typical alcohol consumption, and psychiatric conditions may also play a role in predicting victimization. Likewise, much of the remaining variance would also be accounted for by examining the attitudes and behaviors of sexual assault perpetrators, which was beyond the scope of this study. Future research should examine these additional factors, especially how these factors relate to attitudes and behaviors displayed by sexual assault perpetrators. Also, participants in this study self-selected whether or not they wished to participate from the psychology department subject pool, and provided online, self-reported data throughout the study’s procedures. As such, the data reported here are affected by self-selection bias, and are subject to the inaccuracies inherent to online, self-report data. Future research should recruit a more random sample of participants, and should collect data in person, using more objective measurements, to reduce sampling error. Finally, one last limitation of this study was that it only surveyed women about male-perpetrated sexual aggression. This study recruited an exclusively female sample because previous work shows that the vast majority (up to 90%) of victims of sexual assault are female (Breiding et al., 2014; Catalano, 2004). However, in doing so, it overlooks the smaller, but no less serious, instances of sexual assault with nonfemale victims or, even more rarely, nonmale perpetrators. Future research should test this study’s model in a sample without restrictions on gender to determine the etiology of sexual assault victimization among nonfemale genders and using gender-neutral language to describe their assailants.

Conclusion

Sexual assault victimization is among the most serious and widespread issues facing women on college campuses. This study sought to combat this issue by developing a model predicting the frequency of sexual assault victimization from various predictors of sexual assault implicated in past research, including impulse control difficulties, drinking to cope motives, sex to cope, sexual risk behaviors, alcohol consumption during dating and sexual situations, and sexual refusal assertiveness, while controlling for the effects of CSA and PTSD. The results of this study demonstrate a model which successfully predicts victimization frequency based on these individual factors, which may provide insight into the etiology of sexual assault victimization. In addition, it may also provide further insight into the best and most efficient ways to identify women who are at risk of being victimized by a sexual assault while in college, and to develop intervention programs to reduce their future risk.

Footnotes

Declaration of Conflicting Interests

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

Funding

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

ORCID iD

Mitchell Kirwan

Author Biographies

Mitchell Kirwan is a postdoctoral scholar at the Edson College of Nursing and Health Innovation at Arizona State University, under the mentorship of Dr. Kelly Davis. He earned his PhD at Oakland University, in Rochester, Michigan, under the mentorship of Dr. Scott Pickett. His primary research interests include the effects of emotion regulation and alcohol use on sexual assault perpetration and victimization. Through his research on the relationships between these variables, he hopes to inform intervention and prevention efforts to reduce the prevalence of sexual assault.

Daniel J. Lanni is currently completing his doctoral degree in clinical-community psychology at Georgia State University and is affiliated with the Center for Research of Interpersonal Violence. He received his bachelor’s and master’s degrees in psychology from Oakland University in Rochester, Michigan. His primary research interests examine the interactive and longitudinal effects of emotion regulation, substance use, and masculinity on sexual assault perpetration.

Samantha Nagy is currently a first-year clinical psychology graduate student at the University of Arizona under the mentorship of Dr. Daniel Taylor. She earned a bachelor’s degree in Psychology and a master’s degree in Psychology with a focus in Behavioral Health from Oakland University in Rochester, MI under the mentorship of Dr. Scott Pickett. Her broad research interests include insomnia, PTSD, emotion regulation, mindfulness, and intervention outcomes. Her recent work has focused on trauma exposure, sleep disturbance, and shift work disorder in medical workers and first responders, as well as comprehensive modeling of PTSD symptoms and maintenance factors.

Scott M. Pickett is an associate professor at the Center for Translational Behavioral Science at Florida State University, College of Medicine. He earned his PhD from Northern Illinois University where he completed predoctoral training at the Center for the Study of Family Violence and Sexual Assault. He completed a postdoctoral fellowship at the University of Michigan, Department of Psychiatry. His research examines the risk and recovery factors associated with psychological trauma. By understanding the mechanisms involved in risk and recovery, he hopes his research will inform prevention and intervention efforts.

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