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. Author manuscript; available in PMC: 2025 Oct 14.
Published in final edited form as: Violence Vict. 2024 Oct 14;39(5):571–587. doi: 10.1891/VV-2022-0131

The Confluence Model of Sexual Aggression in the Context of Acute Intoxication and State Emotion Regulation

Lauren Smith 1, William H George 1, Elizabeth C Neilson 2
PMCID: PMC11803821  NIHMSID: NIHMS2033027  PMID: 39245470

Abstract

Understanding the mechanisms underlying sexual aggression perpetration is critical for the development of targeted, evidence-based prevention. The current study evaluates the effects of state emotion regulation (ER), acute alcohol intoxication, and Confluence Model constructs on sexual aggression perpetration intentions. Single, male social drinkers, aged 21–30 years, with a history of sexual risk-taking (N = 90) were randomly assigned to an alcohol (BrAC = 0.1%) or sober control condition and completed measures of hypothetical sexual aggression intentions, state ER, and Confluence Model constructs. Logistic regression demonstrated men high in hostile masculinity expressed significantly greater sexual aggression intentions. In addition, men with poor state ER endorsed significantly greater sexual aggression intentions, although this relationship only held for the men in the sober condition. Results suggest that interventions targeting state ER may be beneficial to sexual aggression perpetration prevention programming.

Sexual aggression is a pervasive problem, with almost half of cisgender women reporting an experience of sexual victimization (Kilpatrick et al., 2007). Sexual aggression refers to a continuum of sexual acts attempted or committed against a nonconsenting individual; it includes non-penetrative and penetrative sexual contact obtained through coercive tactics such as verbal coercion, substance facilitated coercion, or physical coercion (Basile et al., 2014; Koss, Gidycz, et al., 1987). Survivors of sexual aggression are at increased risk for myriad negative outcomes relative to non-survivors, including increased risk for posttraumatic stress disorder or major depressive disorder, substance misuse, and problems in academic, social, and occupational functioning (Kilpatrick, 2000; Nickerson et al., 2013; Testa et al., 2011). The adverse impact of sexual aggression victimization and the disproportionate amount of sexual aggression acts perpetrated by men against women indicate a scientific imperative to better understand the mechanisms underlying male sexual aggression perpetration (Black et al., 2014).

Prior work has identified several robust risk factors for sexual aggression. These include beliefs about women, sex, and sexual assault, which comprise a theory of perpetration referred to as the confluence model (Davis et al., 2018; Malamuth, 1986; Malamuth et al., 1996; Thompson et al., 2013), and acute alcohol intoxication (Abbey & Helmers, 2020; Abbey et al., 2014; Testa, 2002). Emerging evidence suggests that affective processes, such as emotion regulation, also contribute to perpetration risk (Craig et al., 2020; Kirwan et al., 2019; Stappenbeck et al., 2016), but little is known about their predictive utility within pre-existing frameworks of sexual aggression perpetration. The current study examines an integrated model of sexual aggression perpetration by evaluating the effects of confluence model predictors, acute alcohol intoxication, and emotion regulation on sexual aggression perpetration intentions.

Confluence Model for Sexual Aggression

The confluence model proposes that sexual aggression perpetration is primarily driven by the confluence, or convergence, of two core risk factors: hostile masculinity and impersonal sex (Malamuth, 1986; Malamuth et al., 1996; Malamuth et al., 2021). Hostile Masculinity (HM) reflects adversarial beliefs about sex, negative attitudes towards women and victims of sexual assault, and a desire for dominance over women; impersonal sex (IS) reflects preference for frequent, casual sexual relationships and a view of sex as a conquest (Malamuth, 1986; Malamuth et al., 1996). According to this model, HM and IS exert both independent and additive effects on risk for sexual aggression perpetration. Although the synergistic effects of HM and IS have mixed empirical support (Davis & Logan-Greene, 2012; Kohut et al., 2021; Parkhill & Abbey, 2008), the evidence for HM and IS as independent predictors of sexual aggression perpetration is robust (Davis et al., 2018; Thompson et al., 2013; Wheeler et al., 2002). HM and IS are associated with sexual aggression perpetration in cross-sectional, longitudinal, and prospective studies (Abbey et al., 2011; Abbey & McAuslan, 2004; Davis et al., 2015; Kohut et al., 2021).

To-date, the predictive validity of HM and IS has primarily been assessed through survey methods. Few published studies have examined main effects of HM and IS on sexual aggression perpetration intentions in experimental contexts, and most have focused exclusively on constructs related to HM (Norris et al., 1999; Norris and Kerr, 1993; Noel et al., 2009). This is a significant gap, as experimental paradigms provide a controlled opportunity to evaluate proximal pathways from HM and IS to sexual aggression perpetration. Thus far, the limited experimental literature has largely failed to replicate the direct effects of HM and IS on sexual aggression found in cross-sectional and longitudinal survey data, generally finding moderating effects of confluence model constructs (Noel et al., 2009; Woerner et al., 2018, for an exception see Franz et al., 2018). More experimental work is warranted to evaluate the causal pathways from HM and IS to sexual aggression perpetration, especially in the context of other established predictors like acute intoxication.

Alcohol Intoxication & Sexual Aggression

Acute alcohol intoxication has emerged as a strong proximal predictor of sexual aggression perpetration, with roughly half of sexual aggression incidents committed by men who had consumed alcohol (Abbey, 2002). Cross-sectional and experimental studies have consistently demonstrated associations between acute alcohol intoxication and increased sexual aggression perpetration (Abbey & Helmers, 2020; Abbey et al., 2014; Testa, 2002). Findings from prospective studies also suggest a link between increasing alcohol consumption and the initiation of sexual aggression perpetration (Abbey et al., 2012).

Several competing explanations are typically raised to account for alcohol’s association with sexual aggression, and transgressive behavior more broadly including disinhibition and alcohol myopia. According to a disinhibition model, acute intoxication impairs men’s ability to inhibit (antisocial) behavior, including sexual aggression (Giancola et al., 2010; Noel et al., 2009). Alternatively, an alcohol myopia model attributes the effects of acute intoxication on (sexually aggressive) behavior to its indirect effects on information processing (Steele & Josephs, 1990). Alcohol myopia theory posits that alcohol intoxication can cause attentional “nearsightedness,” restricting one’s attention to the most salient cues in the environment (Steele & Josephs, 1990). This results in disproportionate attention to the more salient impelling (“go”) cues at the expense of peripheral inhibiting (“stop”) cues, allowing the impelling cues to exert an undue influence over behavior (Steele & Josephs, 1990). Alcohol myopia has been shown to account for alcohol’s effects on a broad range of behaviors including risky sexual behavior, driving when intoxicated, and physical aggression (Giancola et al., 2010). In the context of sexual aggression, alcohol myopia theory suggests that acute intoxication increases a man’s attention to the most salient aspects of the situation, the impelling cues (e.g., his own sexual arousal, the sexual attractiveness of a partner, the partner’s consent to non-intercourse sexual behaviors) and limits his ability to attend to inhibitory cues (e.g. partner’s non-consent cues, potential social or legal consequences of engaging in nonconsensual sexual activity). In line with an alcohol myopia model, a study of bar patrons found that acute intoxication was associated with increased sexual aggression perpetration intentions when the target was wearing provocative clothing, suggesting the clothing served as a salient impelling cue (Flowe et al., 2011).

Emotion Regulation & Sexual Aggression

Emotion regulation (ER) is the process by which individuals influence their experience and expression of emotions and is conceptualized at both the trait- and state-level (Gratz & Roemer, 2004; Gross, 1998; Lavender et al., 2017). Trait ER refers to one’s general tendency to use certain strategies to regulate emotions, and state ER refers to the specific strategies one uses in-the-moment to modulate emotional arousal (Gratz & Roemer, 2004; Lavender et al., 2017). ER deficits have been linked with aggressive behaviors broadly (Pond et al., 2012; Stappenbeck et al., 2016) and with sexually aggressive behaviors specifically (Craig et al., 2020; Davis et al., 2020; Shorey et al., 2011). Several models of sexual aggression perpetration have included ER as an explanatory mechanism, theorizing that men who experience difficulties managing negative emotions may engage in sex and/or aggression as a means of modulating (negative) affect, particularly in response to provocation (Hall & Hirschman, 1991; Ward & Beech, 2006). Consistent with this hypothesis, sexually aggressive men with poor ER abilities were more likely to respond aggressively to negative feedback (Pickett et al., 2016) and condom use requests from a hypothetical woman (Davis et al., 2021).

Given that ER requires higher order cognitive processes likely impaired by acute alcohol intoxication, ER deficits may play a critical role in alcohol-involved sexual aggression. Specifically, acute intoxication may exacerbate difficulties modulating emotion and inhibiting behavioral responses, resulting in greater sexual aggression perpetration. In line with this hypothesis, alcohol’s association with increased dating violence and sexual aggression perpetration is stronger for men with poor trait ER (Kirwan et al., 2019; Stappenbeck et al., 2016). Because trait ER is unable to capture situational variability (Brans et al., 2013; Lavender et al., 2017; Tomko et al., 2014), it is not clear whether 1) acute intoxication impairs ER ability in some men and 2) this alcohol x state ER interaction is temporally linked to subsequent sexual aggression perpetration. Thus, understanding the role of ER on an event-level (state ER) on its own and in conjunction with alcohol intoxication is essential to determining ER’s relevance to an etiological model.

Present Study

While research has evaluated the links between both alcohol and the confluence model and alcohol and ER in sexual aggression perpetration, no work to-date has examined a comprehensive model of sexual aggression perpetration that accounts for hostile masculinity, impersonal sex, and emotion regulation in the context of acute intoxication1. This is a significant gap, as there is evidence to suggest that acute intoxication may influence the effects of confluence model constructs and state ER on sexual aggression perpetration (Benbouriche et al., 2019; Kirwan et al., 2019; Stappenbeck et al., 2016). The current study has two primary goals: 1) to advance the experimental literature on the role of the confluence model in sexual aggression perpetration; 2) to evaluate the unique contribution of state ER on sexual aggression perpetration in the context of established predictors; and 3) to examine the interaction between state ER and alcohol on sexual aggression perpetration intentions using data from an alcohol administration experiment. We hypothesized that: higher scores on HM and/or IS would be associated with increased sexual aggression intentions (H1); alcohol intoxication would be associated with increased sexual aggression intentions (H2); poorer state ER, or greater emotion dysregulation, would be associated with increased sexual aggression intentions (H3); state ER will moderate the association between alcohol intoxication and sexual aggression perpetration intentions, such that the association between alcohol intoxication and sexual aggression perpetration strengthens as emotion dysregulation increases (H4).

Method

All recruitment and study procedures for the primary study were approved by the Institution’s Human Subjects Division of the Institutional Review Board. For detailed description of study recruitment and procedure, see (Neilson et al., 2021; Neilson et al., 2018).

Participants

One hundred and one men were recruited from a metropolitan community in the Pacific Northwest. Inclusion criteria included: a) single men age 21–30; b) at least one instance of condomless penetrative sex with a woman in the past six months; c) at least two female sexual partners in the past six months; d) average weekly alcohol consumption of at least five drinks; e) at least one instance of heavy episodic drinking (HED, five drinks over a two hour period) in the past 6 months; f) no history of alcohol use problems (assessed through Brief Michigan Alcohol Screening Test (Connor et al., 2007)). The inclusion criteria related to risky sexual behavior (e.g. condomless sex, number of partners) and HED were used to obtain a sample at an elevated risk of perpetration, as both have been linked to increased likelihood of perpetration (Davis et al., 2018; Tharp et al., 2013). Exclusion criteria included any current medication or medical condition that would be contraindicated with alcohol consumption.

Of the 101 men included in the study, 90 were retained for analyses. Six were excluded for missing all measures of a variable of interest, two were excluded for nonsensical responses for number of lifetime opposite sex partners, and one was excluded for no longer meeting eligibility criteria (no condomless penetrative sex with a woman in past six months). The sample was approximately 56% White, 18% Multiracial (or other), 12% Asian or Asian-American, 9% Black or African American, and 1% Hawaiian or Pacific Islander. The remaining 4% of the sample did not provide information on their racial identity. The mean age for the sample was 24.59 (SD = 2.85) and slightly less than half the sample were current full- or part-time students (43%). About 42% of the sample reported completing some college, 38% reported completing college or a graduate degree, 18% reported completing high school, vocational school, or a GED, and 2% reported completing some high school. See Appendix A for descriptive statistics related to inclusion criteria and sample characteristics.

Procedure

Participants arrived at the laboratory where a male experimenter verified their identity and age, compliance with pre-session procedures and confirmed they had a breath alcohol content (BrAC) = 0.00 through a breathalyzer (Alco-Sensor IV; Intoximeters, Inc). Participants then provided informed consent and were weighed to calculate their correct beverage dose. After completing background measures, participants were block randomized to an alcohol condition (target peak BrAC = .10 % gm) or sober control by past sexual aggression perpetration history. For more detailed information on procedure, see (Neilson et al., 2021; Neilson, 2018).

Beverage Administration.

Participants in the alcohol condition were administered 1.25 ml ethanol per pound of body weight to reach the target peak BrAC of .10% gm. Those in the control condition were given 1.25 ml water per pound of body weight. Upon completion of rinsing procedures, participants in the alcohol condition were Breathalyzed every four minutes until BrAC = .07% gm. Each control participant received the same number of Breathalyzer checks as a yoked participant in the alcohol condition to account for possible time and idiographic absorption effects.

Sexual Aggression Analogue.

Participants were asked to read and project themselves into a detailed, sexually explicit sexual aggression scenario. The vignette, written in the second person at a fifth grade reading level, was based on vignettes used in prior research (Davis, 2010) and updated through interviews with men recruited using the study’s inclusion and exclusion criteria. Briefly, the scenario depicts a sexual encounter between the participant and a hypothetical woman (“Michelle”) with whom the protagonist previously had consensual sexual intercourse. The vignette begins at a party, where the protagonist briefly converses with Michelle and is provided with cues that she is experiencing impairment from intoxication (e.g. number of drinks she consumed, unsteady gait). The two go to Michelle’s apartment and engage in consensual non-penetrative sexual activity (e.g. kissing, fondling, nudity) which is described in detailed, highly eroticized language. The protagonist attempts to initiate penetrative sex multiple times. Michelle responds to the initial attempts with nonverbal non-consent cues (e.g. moving protagonist’s hand away from genitals) and subsequent attempts with verbal non-consent cues (e.g. “I don’t want to have sex tonight”). The scenario concludes with no depiction of completed rape. Participants then rated their state ER when reading the vignette and their intentions to engage in sexual aggression in the hypothetical scenario. Upon completion of the vignette and associated measures, participants in the control condition were debriefed and provided compensation and a bus voucher. Participants in the alcohol condition remained at the site until BrAC fell below .03% and were then debriefed and provided compensation and a bus voucher.

Measures

Past Adult Sexual Aggression Perpetration.

Sexual aggression perpetration since age 14 was assessed with the revised Sexual Experiences Survey Long-Form Perpetration (SES; Koss et al., 2007) and the Sexual Strategies Survey (SSS; Strang et al., 2013; Struckman-Johnson et al., 2003). The SES assesses the frequency (0–3+ times) participants performed a range of nonconsensual sexual acts (unwanted sexual contact, attempted or completed oral sex, attempted or completed penetrative sex) and tactics (verbal coercion, intoxication, and force) since the age of 14. The SSS asks participants to report (Y/N) their use of a range of tactics (sexual enticement, verbal coercion, intoxication, and force) to engage in unwanted sexual activity with a woman. A combined past sexual aggression perpetration score was computed for the SES and SSS. Any tactic endorsed on the SSS but not SES was counted as one incidence (up to three) of the relevant SES tactic. Then, a weighted score was calculated with severity of tactic multiplied by frequency of use (see Davis et al., 2014). Given the low base rate of sexual aggression perpetration, total score was collapsed into an ordinal variable with three levels: no past sexual aggression perpetration, low past sexual aggression perpetration (≤ sample mean), and high past sexual aggression perpetration (> sample mean). The mean was chosen as the cut-off point to maximize group sizes and evaluate differences among individuals with “normative” perpetration histories and those with more significant perpetration histories.

Hostile Masculinity.

Hostile Masculinity was measured with the Updated Illinois Rape Myth Acceptance Scale (IRMA; McMahon & Farmer, 2011), Adversarial Heterosexual Beliefs Scale (Lonsway & Fitzgerald, 1995), and the Sex Roles and Beliefs Scale (Burt, 1980). The IRMA is a 22-item measure where participants rate their agreement (1 = strongly disagree, 7 = strongly agree) with statements pertaining to four subscales of rape myth acceptance: She Asked for It, It Wasn’t Really Rape, He Didn’t Mean To, and She Lied. The IRMA has demonstrated reliability (α = .87) and validity (McMahon & Farmer, 2011). The Adversarial Heterosexual Beliefs Scale asks participants to rate their agreement (1 = strongly disagree, 7 = strongly agree) with statements like “men and women cannot really be friends” and has demonstrated reliability (α = .79) and validity (Lonsway & Fitzgerald, 1995). Three subscales were used from Burt’s (1980) Sex Roles and Beliefs Scale, which has participants rate their agreement with various statements on a seven-point Likert scale: Sex Role Stereotyping (α = .80), Sex Role Conservatism (α = .81), and Acceptance of Interpersonal Violence (α = .59).

Impersonal Sex.

Impersonal sex was operationalized as number of opposite sex partners with whom the participant reported having vaginal intercourse (Abbey et al., 2001).

State Emotion (Dys)regulation.

State ER was measured with the State-Difficulties in Emotion Regulation Scale (SDERS; Lavender et al., 2017) which asked participants to rate (1 = not at all, 5 = completely) the extent to which various statements applied to them when they read the vignette. The S-DERS assesses acceptance of current emotions (seven items; “I felt like a weak person for feeling this way”), ability to modulate emotional and behavioral response (seven items; “My emotions felt overwhelming”), awareness of current emotions (five items, “I took the time to figure out what I was feeling”), and emotional clarity (two items, “I was confused about how I feel”). The S-DERS has demonstrated good reliability (α = .86) and validity (Lavender et al., 2017). A total mean score was calculated, with higher scores indicating greater emotion dysregulation. For clarity, this score will be referred to as emotion dysregulation.

Sexual Aggression Intentions.

Participants were asked to rate their likelihood on a scale from one (not at all likely) to seven (extremely likely) of engaging in unwanted sex with Michelle. The tactics were derived from the SES and SSS and included seduction, verbal coercion, intoxication, threats, and force. Given the low base rate of endorsed sexual aggression intentions, a total mean score was calculated and then collapsed into an ordinal variable with three levels: no sexual aggression intentions, low sexual aggression intentions (≤ sample mean), and high sexual aggression intentions (> sample mean). The mean was chosen as the cut-off point to maximize group sizes and evaluate differences among individuals with “normative” perpetration intentions and those with more significant perpetration intentions.

Data Analyses

Statistical analyses were performed in R version 1.2.5001. Ordinal logistic regressions were run regressing hostile masculinity, impersonal sex, alcohol condition, state emotion dysregulation, and alcohol condition x state emotion regulation on sexual aggression intentions, with past sexual aggression perpetration included as a covariate. All continuous variables (HM, IS, and state emotion dysregulation) were mean-centered. Average marginal effects (AME) for the alcohol condition x state emotion dysregulation interaction were calculated using the margins package in R (Leeper, 2021).

Results

Of the 91 men included in the study, 33 (36%) reported no past sexual aggression perpetration, 37 (41%) reported low past sexual aggression perpetration, and 21 (23%) reported high past sexual aggression perpetration. In response to the hypothetical sexual aggression scenario, 35 (38%) endorsed no sexual aggression perpetration intentions, 27 (30%) endorsed low sexual aggression perpetration intentions, and 29 (32%) endorsed high sexual aggression perpetration intentions. See Table 1 for descriptive statistics for past perpetration, HM, IS, emotion dysregulation, and sexual aggression intentions.

Results from the ordinal logistic regression can be found in Table 2. Past perpetration had a statistically significant linear association with sexual aggression intentions and was retained as a covariate in the model. Hypothesis 1 was partially supported; higher HM scores were associated with increased likelihood of endorsing sexual aggression perpetration intentions (β = .05, SE = .02, p = .002). Contrary to Hypothesis 2, there was no statistically significant effect of alcohol condition on sexual aggression perpetration intentions. Consistent with Hypothesis 3, greater state emotion dysregulation was associated with increased likelihood of endorsing sexual aggression perpetration intentions (β = 1.36, SE = .65, p = .036). Contrary to Hypothesis 4, there was a statistically significant interaction between alcohol condition and state emotion dysregulation (β = −1.98, SE = .90, p = .029), such that there was a relationship between emotion dysregulation and sexual aggression intentions for participants in the control condition but not the alcohol condition. As depicted in Figure 1, greater state emotion dysregulation predicted greater likelihood of endorsing sexual aggression perpetration intentions in the control group (AME = −.26, SE = .11, p = .019) but not the alcohol group.

Figure 1. Alcohol x State Emotion Regulation (ER) Centered Effect Plot.

Figure 1

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NI = No Intentions, LI = low intentions, HI = high intentions.

Dotted lines indicate cut-off between levels of Sexual Aggression Intentions.

X-axis is mean-centered state ER. Y-axis is predicted probabilities in logit scale.

Despite the range of tactics encompassed by the sexual aggression perpetration intentions variable, excluding the most severe tactics (physical force and threat of physical force) from analysis had no effect on the results (see Appendix B).

Discussion

The present study examined the effects of confluence model constructs (HM and IS), alcohol intoxication, and state emotion dysregulation on sexual aggression intentions. Results partially supported Hypothesis 1; HM but not IS was associated with significantly greater sexual aggression intentions. Alcohol condition was also not associated with increased sexual aggression intentions (contrary to Hypothesis 2). Greater state emotion dysregulation was associated with significantly increased sexual aggression intentions (Hypothesis 3), although this association only held for sober individuals (contrary to Hypothesis 4).

These findings provide experimental support for the proximal role of HM in sexual aggression perpetration. Despite consistent empirical support for the confluence model constructs at the aggregate level (Abbey et al., 2011; Davis et al., 2018; Thompson et al., 2013), few studies have found evidence for proximal direct effects of HM on sexual aggression perpetration (Abbey et al., 2009; Noel et al., 2009; Woerner et al., 2018; for exceptions see Franz et al., 2018; Testa et al., 2019). Although further replication is needed, the main effect of HM on sexual aggression intentions in this sample suggests that previous failures to replicate confluence model effects in experimental literature (Abbey et al., 2009; Noel et al., 2009; Woerner et al., 2018) may not reflect an inherent incompatibility of confluence model constructs with proximal models.

That IS had no effect on sexual aggression intentions is surprising, although survey-based studies have found evidence to suggest it may offer more limited predictive ability than HM (Kohut et al., 2021; Logan-Greene et al., 2011). This finding may also be accounted for by the narrow operationalization of IS and the high-risk nature of the study sample. Impersonal sex is conceptualized as both an attitudinal and behavioral preference for casual sexual partners (Malamuth et al., 2021), and the measure of IS employed in this study (number of sexual partners) provides only an indirect behavioral preference and is unable to capture the attitudinal component of the construct. Given that inclusion criteria selected for a sample at elevated risk of sexual aggression perpetration, study participants are likely to be relatively high in IS compared to the general population (Davis et al., 2018; Malamuth et al., 2021). Further studies are needed to determine whether the constellation of IS attitudes and behaviors predicts event-level sexual aggression risk in a more representative population, particularly given that few studies have directly examined IS as a proximal predictor (Woerner et al., 2018; Testa et al., 2019; Franz et al., 2018) of sexually aggressive behavior and only one has directly examined both attitudinal and behavioral components of IS (Testa et al., 2019).

The absence of any main effect of alcohol on sexual aggression intentions was also unexpected but may be explained by the selection of a sample with recent history of condomless sex and multiple partners, factors associated with an elevated risk for sexual aggression (Davis et al., 2018; Tharp et al., 2013). However, the absence of a direct effect of acute intoxication on sexual aggression intentions is consistent with studies employing vignettes as sexual aggression analogues which tend to find indirect rather than direct effects (for a review, see Abbey et al., 2014).

Study results provide support for Hypothesis 3 but not Hypothesis 4; state emotion dysregulation was associated with greater sexual aggression perpetration intentions, but only for sober men. Results from men in the no-alcohol condition are consistent with prior work on global associations between trait ER and aggression (Pond et al., 2012), trait ER and interpersonal violence (Tager et al., 2010), and trait ER and sexual aggression (Craig et al., 2020; Davis et al., 2020; Gratz et al., 2009; Kirwan et al., 2019). The absence of an association between state emotion dysregulation and sexual aggression intentions in intoxicated men was surprising, given that high trait emotion dysregulation has been shown to strengthen the relationship between alcohol and dating violence (Stappenbeck et al., 2016) and sexual aggression perpetration (Kirwan et al., 2019). It is unclear why state emotion dysregulation was unrelated to sexual aggression intentions in intoxicated men. One possibility is that some element(s) of the procedure directed participants’ attention away from potentially impelling cues in the sexual aggression analogue, which has been found to reduce the effects of acute intoxication on aggression (Gallagher & Parrot, 2011). As part of a larger study (see Neilson et al., 2018), psychophysiological measures (respiratory sinus arrhythmia, galvanic skin response, penile plethysmography) were administered with the sexual aggression analogue, and it is conceivable that these provided sufficient distraction to elicit this effect.

How alcohol impacts the deployment and execution of ER strategies in-the-moment (i.e. at the state level) is currently unknown, and further research is needed to delineate alcohol’s effects on state ER broadly as well as in the context of sexual aggression perpetration.

Novel to the current study is the evaluation of HM and IS within an experimental paradigm and the integration of these constructs with alcohol and state emotion dysregulation to predict sexual aggression intentions. Unlike prior experimental studies, which relied on single measures of HM, the present study employed multiple measures to capture the various facets of the latent construct of HM. Although replication is needed, the alcohol administration procedure and highly descriptive eroticized vignette lend significant internal validity to these findings. This study extends prior work with this sample that found a moderating effect of state emotion dysregulation on the association between anger and sexual aggression perpetration intentions (Neilson et al., 2021) but did not evaluate the interaction between alcohol condition and state ER. The impact of state ER on sexual aggression intentions in the previous study was significant for men high but not low in state anger, suggesting that state anger may account for some of the variance in state ER (Neilson et al., 2021). One can infer from both studies that although ER can mitigate sexual aggression intentions, its actual implementation and efficacy is likely context dependent. Further studies are required to identify sexual aggression congruent emotions amenable to ER strategies and to ascertain how acute intoxication influences these emotions and their response to ER strategies.

Unlike the prior study, the present study evaluates the impact of state emotion dysregulation on sexual aggression intentions while accounting for the contribution of HM and IS. In addition, this study included a broad array of sexual aggression tactics, specifically those related to sexual enticement strategies which may also contribute to the differential effect of state emotion regulation. Sexual enticement tactics, also referred to as coaxing, involve efforts to obtain sex from a nonconsenting partner through seduction (French et al., 2017; Struckman-Johnson et al., 2003). Although enticement strategies deviate less significantly from traditional sexual scripts than other tactics, they are sexual acts attempted or committed against a nonconsenting individual, consistent with the consensus definition of sexual aggression (Basile et al., 2014; Koss et al., 1987). Furthermore, a measure including enticement items demonstrates appropriate Rasch properties (Testa et al., 2015), suggesting enticement, verbal coercion, intoxication, threats, and force represent an underlying unidimensional continuum (Testa et al., 2015).

Several study limitations warrant caution in interpreting and extending findings. The number of indicators was chosen through theoretical rationale, and the sample size was smaller than what is typically recommended for ordinal logistic regression. Although the representation of past perpetration and sexual aggression intentions as ordinal variables allowed the analysis of these low base rate variables across conceptually meaningful groups (above and below sample averages), the use of ordinal variables may have also reduced statistical power. The use of a single behavioral indicator of IS also limits the inferences that can be drawn about proximal effects of IS on sexual aggression perpetration. In addition, the use of sample with elevated perpetration risk, as well as a relatively high target BAC, limit the generalizability of the findings. While the racial/ethnic distribution of the sample is largely reflective of the metropolitan area from which participants were recruited, the sample is not representative, limiting generalizability (U.S. Census Bureau, 2021). Further studies on the roles of state ER and alcohol intoxication in sexual aggression perpetration are needed in larger, representative samples. The current study did not examine the effects of trait ER, and research is needed to elucidate how trait ER impacts the availability of state ER in both sober and intoxicated men. Future research should also consider whether state ER, acute intoxication, and/or confluence model constructs are specific to the heteronormative context of male-on-female sexual aggression or function similarly to increase risk in non-heterosexual contexts.

This study found that HM predicted event-specific sexual aggression intentions and that state emotion dysregulation contributes to sexual aggression intentions above and beyond the effects of past perpetration and HM in sober men. Further research is needed to understand how alcohol intoxication impacts ER implementation and efficacy broadly as well as in relation to sexual aggression perpetration. The results of this study can be taken as preliminary support for ER as a promising intervention target for non-alcohol-involved sexual aggression, an approach that has already demonstrated positive effects (Davis et al., 2020). Consistent with our findings, a recent study also found an ER intervention to be effective in reducing sexual aggression intentions in sober but not intoxicated men, and future studies are needed to ascertain whether ER-based interventions are applicable to alcohol-involved sexual aggression (Davis et al., 2021).

Acknowledgments:

The current study was supported by funding provided by the National Institute on Alcohol Abuse and Alcoholism (F31AA024352, PI: E.C. Neilson) and the Association for Treatment of Sexual Abusers.

Footnotes

1

Although this study was not conceptualized within the framework of the I-cubed theory (Finkel, 2014), the I-cubed theory would provide a comprehensive model in which to examine the effects of acute intoxication, state emotion dysregulation, and Confluence Model constructs on sexual aggression perpetration. Briefly, the I-cubed theory delineates three processes that produce aggressive behavior: instigation, impellance, and inhibition (Finkel & Hall, 2018). Instigating factors are situational stimuli (e.g. verbal provocation) that would be expected to elicit (an urge for) aggressive responding. Impelling factors are dispositional or situational characteristics that increase the likelihood an individual will experience a strong urge to aggress in response to a given instigator. Inhibitory factors are situational or dispositional factors that influence the likelihood an individual will suppress an urge to aggress. Within this framework, a sexual aggression paradigm would be the instigating factor, Confluence Model constructs and state emotion dysregulation would be impelling factors, and acute intoxication would be a (dis)inhibitory factor.

Conflict of Interest:

We have no conflicts of interest to disclose.

Appendix A

Sample Characteristics

Table 1.

Sample Characteristics: Recent Drinking and Sexual Behavior

Mean SD Median Min Max
Past 3-month number vaginal sex partnersa 1.73 1.44 1 0 7
Past 3-month condom use during vaginal sex (percent of times)b 43.88% 39.60% 30% 0 100
Past month typical weekly number of drinksc 14.64 9.32 14 1 48
Past month number of times with binge drinkingd 4.23 4.75 2 1 25
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Screening responses were not retained with participant responses. Sample characteristics were calculated with related measures at time of data collection.

a

Participants were asked to report the number of vaginal sex partners from the past three months.

b

Participants were asked to estimate the percentage of times they used a condom during vaginal sex over the past three months.

c

Participants were asked to estimate the typical number of standard drinks consumed on a typical weekday over the past month; estimated number of drinks was summed across days to calculate typical weekly number of drinks.

d

Participants were asked to report the number of times they consumed five or more drinks containing alcohol over a two-hour period during the past month.

Appendix A

Table 2.

Sample Characteristics: Sexual Interest

N %
Exclusively heterosexual desire 70 78
Largely heterosexual desire 18 20
Equal levels of heterosexual and homosexual desire 1 1
Some heterosexual desire 1 1
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Participant responses to Kinsey Scale. (Kinsey et al., 1948).

Appendix B

Sexual Aggression Tactic Correlation Table (Table 1) and Key (Table 2)

Table 1.

Correlations among Sexual Aggression Tactics (Outcome Measure)

Variable Tactic 1 Tactic 2 Tactic 3 Tactic 4 Tactic 5 Tactic 6 Tactic 7 Tactic 8 Tactic 9 Tactic 10 Tactic 11 Tactic 12 Tactic 13 Tactic 14 Tactic 15 Tactic 16 Tactic 17
Tactic 1 0.773 0.695 0.713 0.714 0.575 0.751 0.735 0.588 0.447 0.586 0.705 0.788 0.541 0.371 0.443 0.592
Tactic 2 0.796 0.811 0.793 0.607 0.661 0.726 0.48 0.425 0.548 0.753 0.692 0.588 0.42 0.354 0.613
Tactic 3 0.891 0.947 0.548 0.546 0.667 0.373 0.32 0.474 0.629 0.577 0.441 0.273 0.258 0.461
Tactic 4 0.909 0.597 0.632 0.693 0.384 0.338 0.48 0.67 0.6 0.472 0.286 0.255 0.489
Tactic 5 0.543 0.583 0.679 0.397 0.338 0.471 0.671 0.607 0.445 0.277 0.27 0.468
Tactic 6 0.79 0.497 0.534 0.444 0.477 0.513 0.483 0.363 0.42 0.337 0.438
Tactic 7 0.68 0.629 0.536 0.651 0.649 0.69 0.592 0.479 0.396 0.66
Tactic 8 0.719 0.655 0.723 0.758 0.774 0.721 0.601 0.509 0.799
Tactic 9 0.883 0.838 0.691 0.745 0.705 0.85 0.736 0.818
Tactic 10 0.88 0.655 0.643 0.782 0.935 0.729 0.808
Tactic 11 0.825 0.812 0.821 0.829 0.743 0.87
Tactic 12 0.946 0.8 0.623 0.582 0.799
Tactic 13 0.793 0.612 0.572 0.792
Tactic 14 0.796 0.564 0.857
Tactic 15 0.721 0.795
Tactic 16 0.682
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Table 2.

Key for Table1 – Tactics and Associated Text Provided to Participants

Tactic 1 Try to persuade Michelle to have sex with you
Tactic 2 Continue kissing and touching Michelle until she agrees to have sex with you
Tactic 3 Get Michelle so sexually excited that she agrees to have sex
Tactic 4 Get Michelle really aroused and then start having sex
Tactic 5 Seduce Michelle until she is willing to have sex
Tactic 6 Offer to get Michelle another drink
Tactic 7 Encourage Michelle to have another drink
Tactic 8 Tell Michelle how happy you would be if you had sex
Tactic 9 Tell Michelle how upset you would be if you did not have sex
Tactic 10 Tell Michelle how angry you would be if she insists on not having sex
Tactic 11 Promise to have a relationship with Michelle so she will have sex with you
Tactic 12 Tell Michelle she is special so that she will have sex with you
Tactic 13 Tell Michelle you trust each other so she will have sex with you
Tactic 14 Tell Michelle you love her so that she will have sex with you
Tactic 15 Threaten to hurt Michelle if she will not have sex with you
Tactic 16 Use physical force to get Michelle to have sex with you
Tactic 17 Make sure you have sex with Michelle no matter what
Open in a new tab

References

  1. Abbey A, McAuslan P, Zawacki T, Clinton AM, & Buck PO (2001). Attitudinal, experiential, and situational predictors of sexual assault perpetration. J Interpers Violence, 16(8), 784–807. doi: 10.1177/088626001016008004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Abbey A. (2002). Alcohol-related sexual assault: a common problem among college students. J Stud Alcohol Suppl(14), 118–128. doi: 10.15288/jsas.2002.s14.118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Abbey A, & McAuslan P. (2004). A longitudinal examination of male college students’ perpetration of sexual assault. J Consult Clin Psychol, 72(5), 747–756. doi: 10.1037/0022-006X.72.5.747 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Abbey A, Parkhill MR, Jacques-Tiura AJ, & Saenz C. (2009). Alcohol’s role in men’s use of coercion to obtain unprotected sex. Subst Use Misuse, 44(9–10), 1329–1348. doi: 10.1080/10826080902961419 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Abbey A, Jacques-Tiura AJ, & LeBreton JM (2011). Risk factors for sexual aggression in young men: an expansion of the confluence model. Aggress Behav, 37(5), 450–464. doi: 10.1002/ab.20399 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Abbey A, Wegner R, Pierce J, & Jacques-Tiura AJ (2012). Patterns of sexual aggression in a community sample of young men: Risk factors associated with persistence, desistance, and initiation over a one year interval. Psychol Violence, 2(1), 1–15. doi: 10.1037/a0026346 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Abbey A, Wegner R, Woerner J, Pegram SE, & Pierce J. (2014). Review of survey and experimental research that examines the relationship between alcohol consumption and men’s sexual aggression perpetration. Trauma Violence Abuse, 15(4), 265–282. doi: 10.1177/1524838014521031 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Abbey A, & Helmers BR (2020). Sexual aggression analogues used in alcohol administration research: Critical review of their correspondence to alcohol-involved sexual assaults. Alcoholism Clinical and Experimental Research, 44(8), 1514–1528. [DOI] [PubMed] [Google Scholar]
  9. Basile K, Smith S, Breiding M, Black M, & Mahendra R. (2014). Sexual violence surveillance: Uniform definitions and recommended data elements, Version 2.0. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention. Retrieved from https://www.cdc.gov/violenceprevention/pdf/sv_surveillance_definitionsl-2009-a.pdf [Google Scholar]
  10. Benbouriche M, Testé B, Guay JP, & Lavoie ME (2019). The role of rape-supportive attitudes, alcohol, and sexual arousal in sexual (mis)perception: An experimental study. J Sex Res, 56(6), 766–777. doi: 10.1080/00224499.2018.1496221 [DOI] [PubMed] [Google Scholar]
  11. Black MC, Basile KC, Breiding MJ, & Ryan GW (2014). Prevalence of sexual violence against women in 23 States and two U.S. territories, BRFSS 2005. Violence Against Women, 20(5), 485–499. doi: 10.1177/1077801214528856 [DOI] [PubMed] [Google Scholar]
  12. Brans K, Koval P, Verduyn P, Lim YL, & Kuppens P. (2013). The regulation of negative and positive affect in daily life. Emotion, 13(5), 926–939. doi: 10.1037/a0032400 [DOI] [PubMed] [Google Scholar]
  13. Burt MR (1980). Cultural myths and supports for rape. Journal of Personality and Social Psychology, 38(2), 217–230. doi: 10.1037/0022-3514.38.2.217 [DOI] [PubMed] [Google Scholar]
  14. Connor JP, Grier M, Feeney GF, & Young RM (2007). The validity of the Brief Michigan Alcohol Screening Test (bMAST) as a problem drinking severity measure. J Stud Alcohol Drugs, 68(5), 771–779. doi: 10.15288/jsad.2007.68.771 [DOI] [PubMed] [Google Scholar]
  15. Craig AN, Peterson ZD, Janssen E, Goodrich Mba D, & Heiman JR (2020). The impact of sexual arousal and emotion regulation on men’s sexual aggression Proclivity. J Interpers Violence, 886260520915544. doi: 10.1177/0886260520915544 [DOI] [PubMed] [Google Scholar]
  16. Davis KC (2010). The influence of alcohol expectancies and intoxication on men’s aggressive unprotected sexual intentions. Exp Clin Psychopharmacol, 18(5), 418–428. doi: 10.1037/a0020510 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Davis KC, & Logan-Greene P. (2012). Young men’s use of aggressive tactics to avoid condom use: A test of a theoretical model. Soc Work Res, 36(3), 223–231. doi: 10.1093/swr/svs027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Davis KC, Gilmore AK, Stappenbeck CA, Balsan MJ, George WH, & Norris J. (2014). How to score the Sexual Experiences Survey? A comparison of nine methods. Psychol Violence, 4(4), 445–461. doi: 10.1037/a0037494 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Davis KC, Danube CL, Stappenbeck CA, Norris J, & George WH (2015). Background predictors and event-specific characteristics of sexual aggression incidents: The roles of alcohol and other factors. Violence Against Women, 21(8), 997–1017. doi: 10.1177/1077801215589379 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Davis KC, Neilson EC, Wegner R, & Danube CL (2018). The intersection of men’s sexual violence perpetration and sexual risk behavior: A literature review. Aggress Violent Behav, 40, 83–90. doi: 10.1016/j.avb.2018.04.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Davis KC, Neilson EC, Kirwan M, Eldridge N, George WH, & Stappenbeck CA (2020). Alcohol-involved sexual aggression: Emotion regulation as a mechanism of behavior change. Health Psychology, 40(12), 940–950. doi: 10.1037/hea0001048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Davis KC, Neilson EC, Kirwan M, Bird ER, Eldridge N, George WH, & Stappenbeck CA (2021). The interplay of sexual arousal and power-related emotions in men’s alcohol-involved sexual aggression intentions. J Sex Res, 1–15. doi: 10.1080/00224499.2021.1972923 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Finkel EJ (2014). The I3 model. Metatheory, theory, and evidence. In Advances in Experimental Social Psychology, vol. 49, Academic Press Inc, pp. 1–104. 10.1016/B978-0-12-800052-6.00001-9 [DOI] [Google Scholar]
  24. Finkel EJ, & Hall AN (2018). The I3 Model: A metatheoretical framework for understanding aggression. Current Opinion in Psychology, 19, 125–130 [DOI] [PubMed] [Google Scholar]
  25. Flowe HD, Stewart J, Sleath ER, & Palmer FT (2011). Public house patrons’ engagement in hypothetical sexual assault: a test of Alcohol Myopia Theory in a field setting. Aggress Behav, 37(6), 547–558. doi: 10.1002/ab.20410 [DOI] [PubMed] [Google Scholar]
  26. Franz MR, Haikalis M, Riemer AR, Parrott DJ, Gervais SJ, DiLillo D. (2018). Further validation of a laboratory analog sexual aggression task: Associations with novel risk factors for sexual violence. Violence and Victims, 33, 486–503. [DOI] [PubMed] [Google Scholar]
  27. French BH, Suh HN, & Arterberry B. (2017). Exploratory factor analysis and psychometric properties of the Sexual Coercion Inventory. J Sex Res, 54(8), 962–970. doi: 10.1080/00224499.2016.1235129 [DOI] [PubMed] [Google Scholar]
  28. Gallagher KE, & Parrott DJ (2011). Does distraction reduce the alcohol–aggression relation? A cognitive and behavioral test of the attention-allocation model. Journal of Consulting and Clinical Psychology, 79(3), 319–329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Giancola PR, Josephs RA, Parrott DJ, & Duke AA (2010). Alcohol myopia revisited: Clarifying aggression and other acts of disinhibition through a distorted lens. Perspect Psychol Sci, 5(3), 265–278. doi: 10.1177/1745691610369467 [DOI] [PubMed] [Google Scholar]
  30. Gratz KL, & Roemer L. (2004). Multidimensional assessment of emotion regulation and dysregulation: Development, factor structure, and initial validation of the difficulties in emotion regulation scale. Journal of Psychopathology and Behavioral Assessment, 26(1), 41–54. doi: 10.1023/B:JOBA.0000007455.08539.94 [DOI] [Google Scholar]
  31. Gratz KL, Paulson A, Jakupcak M, & Tull MT (2009). Exploring the relationship between childhood maltreatment and intimate partner abuse: gender differences in the mediating role of emotion dysregulation. Violence Vict, 24(1), 68–82. doi: 10.1891/0886-6708.24.1.68 [DOI] [PubMed] [Google Scholar]
  32. Gross JJ (1998). Antecedent- and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology, 74(1), 224–237. doi: 10.1037/0022-3514.74.1.224 [DOI] [PubMed] [Google Scholar]
  33. Gross AM, Bennett T, Sloan L, Marx BP, & Juergens J. (2001). The impact of alcohol and alcohol expectancies on male perception of female sexual arousal in a date rape analog. Exp Clin Psychopharmacol, 9(4), 380–388. doi: 10.1037//1064-1297.9.4.380 [DOI] [PubMed] [Google Scholar]
  34. Hall GCN, & Hirschman R. (1991). Toward a theory of sexual aggression: A quadripartite model. Journal of Consulting and Clinical Psychology, 59(5), 662–669. doi: 10.1037/0022-006X.59.5.662 [DOI] [PubMed] [Google Scholar]
  35. Kilpatrick D. (2000). The mental health impact of rape. National Violence Against Women Prevention Research Center. Retrieved from https://mainweb-v.musc.edu/vawprevention/research/mentalimpact.shtml [Google Scholar]
  36. Kilpatrick D, Resnick H, Ruggiero K, Conoscenti L, & McCauley J. (2007). Drug-facilitated, incapacitated, and forcible rape: A national study. National Crime Reference Services. Retrieved from https://www.ojp.gov/pdffiles1/nij/grants/219181.pdf [Google Scholar]
  37. Kinsey AC, Pomery WB, & Martin CE (1948). Kinsey Scale [Database record]. In: APA PsycTests. [Google Scholar]
  38. Kirwan M, Lanni DJ, Warnke A, Pickett SM, & Parkhill MR (2019). Emotion regulation moderates the relationship between alcohol consumption and the perpetration of sexual aggression. Violence Against Women, 25(9), 1053–1073. doi: 10.1177/1077801218808396 [DOI] [PubMed] [Google Scholar]
  39. Kohut T, Landripet I, & Štulhofer A. (2021). Testing the confluence model of the association between pornography use and male sexual aggression: A longitudinal assessment in two independent adolescent samples from Croatia. Arch Sex Behav, 50(2), 647–665. doi: 10.1007/s10508-020-01824-6 [DOI] [PubMed] [Google Scholar]
  40. Koss M, Abbey A, Campbell R, Cook S, Norris J, Testa M, Ullman S, West C, White J. (2007). Revising the SES: A collaborative process to improve assessment of sexual aggression and victimization. Psychology of Women Quarterly, 31(4), 357–370. [Google Scholar]
  41. Koss MP, Gidycz CA, & Wisniewski N. (1987). The scope of rape: Incidence and prevalence of sexual aggression and victimization in a national sample of higher education students. Journal of Consulting and Clinical Psychology, 55(2), 162–170. doi: 10.1037/0022-006X.55.2.162 [DOI] [PubMed] [Google Scholar]
  42. Lavender JM, Tull MT, DiLillo D, Messman-Moore T, & Gratz KL (2017). Development and validation of a state-based measure of emotion dysregulation. Assessment, 24(2), 197–209. doi: 10.1177/1073191115601218 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Leeper T. (2021). margins: Marginal Effects for Model Objects. R package version 0.3.26. In. [Google Scholar]
  44. Logan-Greene P, Logan Greene P, & Cue Davis K. (2011). Latent profiles of risk among a community sample of men: implications for sexual aggression. J Interpers Violence, 26(7), 1463–1477. doi: 10.1177/0886260510369138 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Lonsway KA, & Fitzgerald LF (1995). Attitudinal antecedents of rape myth acceptance: A theoretical and empirical reexamination. Journal of Personality and Social Psychology, 68(4), 704–711. doi: 10.1037/0022-3514.68.4.704 [DOI] [Google Scholar]
  46. Malamuth NM (1986). Predictors of naturalistic sexual aggression. Journal of Personality and Social Psychology, 50(5), 953–962. doi: 10.1037/0022-3514.50.5.953 [DOI] [PubMed] [Google Scholar]
  47. Malamuth NM, Heavey CL, & Linz D. (1996). The confluence model of sexual aggression: combining hostile masculinity and impersonal sex. Journal of Offender Rehabilitation, 23(3–4). [Google Scholar]
  48. Malamuth NM, Lamade RV, Koss MP, Lopez E, Seaman C, Prentky R. (2021). Testing the four pillars of the Confluence Model in a large diverse sample of college men. Aggressive Behavior, 47(4), 405–420. [DOI] [PubMed] [Google Scholar]
  49. McMahon S, & Farmer G. (2011). An updated measure for assessing subtle rape myths. Social Work Research, 35(2), 71–81. [Google Scholar]
  50. Neilson EC, Davis KC, Norris J, & George WH (2018, June 17). The roles of acute alcohol intoxication, emotional arousal, and emotion regulation on men’s self-reported sexual aggression intentions. In Jaffe A. & Hahn C. (Chairs), Alcohol-involved sexual assault: Novel perspectives from laboratory studies [Symposium]. Research Society on Alcoholism, San Diego, CA, United States. [Google Scholar]
  51. Neilson EC, Smith L, Davis KC, & George WH (2021). Acute alcohol intoxication, state anger, and sexual assault perpetration: The role of state emotion regulation. Psychology of Violence, 12(1), 42–51 doi: 10.1037/vio0000381 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Nickerson A, Steenkamp M, Aerka IM, Salters-Pedneault K, Carper TL, Barnes JB, & Litz BT (2013). Prospective investigation of mental health following sexual assault. Depress Anxiety, 30(5), 444–450. doi: 10.1002/da.22023 [DOI] [PubMed] [Google Scholar]
  53. Noel NE, Maisto SA, Johnson JD, & Jackson LA (2009). The effects of alcohol and cue salience on young men’s acceptance of sexual aggression. Addict Behav, 34(4), 386–394. doi: 10.1016/j.addbeh.2008.11.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Norris J, & Kerr KL (1993). Alcohol and violent pornography: responses to permissive and nonpermissive cues. Journal of Studies on Alcohol And Drugs, Supplement, 11, 118–127. [DOI] [PubMed] [Google Scholar]
  55. Norris J, George WH, Davis KC, Martell J, & Leonesio RJ (1999). Alcohol and Hypermasculinity as Determinants of Men’s Empathic Responses to Violent Pornography. Journal of Interpersonal Violence, 14(7), 683–700. [Google Scholar]
  56. Parkhill MR, & Abbey A. (2008). Does alcohol contribute to the confluence model of sexual assault perpetration? J Soc Clin Psychol, 27(6), 529–554. doi: 10.1521/jscp.2008.27.6.529 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Parkhill MR, & Pickett SM (2016). Difficulties in emotion regulation as a mediator of the relationship between child sexual abuse victimization and sexual aggression perpetration in male college students. J Child Sex Abus, 25(6), 674–685. doi: 10.1080/10538712.2016.1205161 [DOI] [PubMed] [Google Scholar]
  58. Pickett SM, Parkhill MR, & Kirwan M. (2016). The influence of sexual aggression perpetration history and emotion regulation on men’s aggressive responding following social stress. Psychology of Men & Masculinity, 17(4), 363–372. 10.1037/men0000032 [DOI] [Google Scholar]
  59. Pond RS, Kashdan TB, DeWall CN, Savostyanova A, Lambert NM, & Fincham FD (2012). Emotion differentiation moderates aggressive tendencies in angry people: A daily diary analysis. Emotion, 12(2), 326–337. doi: 10.1037/a0025762 [DOI] [PubMed] [Google Scholar]
  60. Shorey RC, Brasfield H, Febres J, & Stuart GL (2011). An examination of the association between difficulties with emotion regulation and dating violence perpetration. J Aggress Maltreat Trauma, 20(8), 870–885. doi: 10.1080/10926771.2011.629342 [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Stappenbeck CA, Davis KC, Cherf N, Gulati NK, & Kajumulo KF (2016). Emotion regulation difficulties moderate the association between heavy episodic drinking and dating violence perpetration among college men. J Aggress Maltreat Trauma, 25(9), 921–935. doi: 10.1080/10926771.2016.1232328 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Steele CM, & Josephs RA (1990). Alcohol myopia. Its prized and dangerous effects. Am Psychol, 45(8), 921–933. doi: 10.1037//0003-066x.45.8.921 [DOI] [PubMed] [Google Scholar]
  63. Strang E, Peterson ZD, Hill YN, & Heiman JR (2013). Discrepant responding across self-report measures of men’s coercive and aggressive sexual strategies. J Sex Res, 50(5), 458–469. doi: 10.1080/00224499.2011.646393 [DOI] [PubMed] [Google Scholar]
  64. Struckman-Johnson C, Struckman-Johnson D, & Anderson PB (2003). Tactics of sexual coercion: When men and women won’t take no for an answer. Journal of Sex Research, 40(1), 76–86. doi: 10.1080/00224490309552168 [DOI] [PubMed] [Google Scholar]
  65. Tager D, Good GE, & Brammer S. (2010). “Walking over ‘em”: An exploration of relations between emotion dysregulation, masculine norms, and intimate partner abuse in a clinical sample of men. Psychology of Men & Masculinity, 11(3), 233–239. doi: 10.1037/a0017636 [DOI] [Google Scholar]
  66. Testa M. (2002). The impact of men’s alcohol consumption on perpetration of sexual aggression. Clin Psychol Rev, 22(8), 1239–1263. doi: 10.1016/s0272-7358(02)00204-0 [DOI] [PubMed] [Google Scholar]
  67. Testa M, Hoffman JH, & Livingston JA (2011). Intergenerational transmission of sexual victimization vulnerability as mediated via parenting. Child Abuse Negl, 35(5), 363–371. doi: 10.1016/j.chiabu.2011.01.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Testa M, Hoffman JH, Lucke JF, & Pagnan CE (2015). Measuring sexual aggression perpetration in college men: A comparison of two measures. Psychol Violence, 5(3), 285–293. doi: 10.1037/a0037584 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Testa M, Brown WC, & Wang W. (2019). Do Men Use More Sexually Aggressive Tactics When Intoxicated? A Within-Person Examination of Naturally Occurring Episodes of Sex. Psychology of Violence, 9(5), 546–554. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Tharp AT, DeGue S, Valle LA, Brookmeyer KA, Massetti GM, & Matjasko JL (2013). A systematic qualitative review of risk and protective factors for sexual violence perpetration. Trauma Violence Abuse, 14(2), 133–167. doi: 10.1177/1524838012470031 [DOI] [PubMed] [Google Scholar]
  71. Thompson MP, Swartout KM, & Koss MP (2013). Trajectories and predictors of sexually aggressive behaviors during emerging adulthood. Psychol Violence, 3(3), 247–259. doi: 10.1037/a0030624 [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Tomko RL, Solhan MB, Carpenter RW, Brown WC, Jahng S, Wood PK, & Trull TJ (2014). Measuring impulsivity in daily life: the momentary impulsivity scale. Psychol Assess, 26(2), 339–349. doi: 10.1037/a0035083 [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. United States Census Bureau. (2021). QuickFacts: Seattle city, Washington. Retrieved from https://www.census.gov/quickfacts/seattlecitywashington May, 2022. [Google Scholar]
  74. Ward T, & Beech A. (2006). An integrated theory of sexual offending. Aggression and Violent Behavior, 11(1), 44–63. doi: 10.1016/j.avb.2005.05.002 [DOI] [Google Scholar]
  75. Wheeler JG, George WH, & Dahl BJ (2002). Sexually aggressive college males: Empathy as a moderator in the “Confluence Model” of sexual aggression. Personality and Individual Differences, 33(5), 759–776. doi: 10.1016/S0191-8869(01)00190-8 [DOI] [Google Scholar]
  76. Woerner J, Abbey A, Pegram SE, & Helmers BR (2018). The effects of alcohol intoxication and sexual interest on men’s sexual persistence and hostility in a dating simulation. Aggress Behav. doi: 10.1002/ab.21773 [DOI] [PMC free article] [PubMed] [Google Scholar]

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