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. 2025 Mar 31;86(2):261–270. doi: 10.15288/jsad.24-00005

Risk Factors for Consensual and Coercive Sexual Hookup Behaviors Among College Men: A Daily Diary Study

Alisa R Garner a,,*, Ryan C Shorey b, L Christian Elledge c, Melissa A Lewis d, Gregory L Stuart c
PMCID: PMC11980413  PMID: 39665612

Abstract

Objective:

Hookup behaviors (HUBs; i.e., sexual activity outside an exclusive relationship with no mutual expectation of romantic commitment) are prevalent on college campuses and are linked with alcohol use and sexual assault. There is limited understanding of risk factors for consensual and coercive HUBs. We examined the proximal associations between alcohol use and consensual and coercive HUBs and the moderating influence of positive urgency and alcohol-related sexual affect and drive expectancies among college men.

Method:

Ninety-nine college men completed a baseline assessment and 60 consecutive daily surveys assessing their alcohol use and HUBs.

Results:

An alcohol use day increased the odds of a consensual and coercive HUB, compared with no HUB. An alcohol use day decreased the odds of a consensual HUB versus a coercive HUB in the models that included alcohol-related sexual affect and drive expectancies. Only alcohol-related sexual affect expectancies were a significant moderator. An alcohol use day was significantly associated with a consensual HUB, compared with no HUB, among college men at low, B = 0.93, p = .009, OR = 2.53 (95% CI [1.27, 5.06]), and high, B = 1.93, p < .001, OR = 6.87 (95% CI [4.32, 10.92]), levels of alcohol-related sexual affect expectancies.

Conclusions:

Results suggest that greater alcohol-related sexual affect expectancies may increase the odds of an alcohol-facilitated consensual HUB among college men. An alcohol use day increases the odds of engaging in a HUB and increases the odds of a coercive HUB, compared with a consensual HUB. Additional research is needed to identify risk factors for coercive HUBs.

Eighty percent (80%) of college men report alcohol use, with 35% consuming five or more drinks in one sitting in the past 2 weeks (Schulenberg et al., 2017). Associated with college men's alcohol use is hookup behaviors (HUBs; i.e., sexual activity outside an exclusive relationship with no mutual expectation of romantic commitment; Fielder & Carey, 2010b; Lewis et al., 2012). HUBs tend to be impulsive sexual encounters associated with negative consequences including sexually transmitted infections (Fielder & Carey, 2010a, 2010b; Napper et al., 2016). Sixty percent to 80% of college students engage in HUBs, with most HUBs occurring following alcohol use (Fielder & Carey, 2010a; Garcia & Reiber, 2008; Garcia et al., 2012; LaBrie et al., 2014; Paul & Hayes, 2002). Sexual aggression perpetration is associated with male college students' alcohol use and risk-taking behaviors (Abbey, 2002; Garner et al., 2020). Among college men, HUBs and sexual aggression frequently co-occur. Approximately 80% of female sexual assault victims reported that their victimization occurred during a HUB (Flack et al., 2016). In addition, frequency of HUBs was a significant predictor of college men's sexual assault perpetration (Testa & Cleveland, 2017). A theory-informed examination of risk factors for college men's consensual and coercive HUBs is needed to inform intervention and prevention efforts. The focus on college men is particularly needed given that college men, compared to women, engage in more frequent and riskier HUBs, have greater expectations of engaging in HUB during college, and perpetrate sexual violence at greater rates (Flack et al., 2008; Krebs et al., 2007; Napper et al., 2016; Olmstead et al., 2018).

Alcohol myopia theory (AMT; Steele & Josephs, 1990) suggests that the pharmacological effects of alcohol use directly influence sexual risk-taking by focusing cognitive resources on the most emotionally salient contextual cues that instigate behaviors. If sexual arousal is the most salient stimulus, cognitive resources are directed toward the seeking of sexual experiences, leaving minimal attention for risk-inhibiting stimuli (Brown & Vanable, 2007; Davis et al., 2007; MacDonald et al., 2000; Scott-Sheldon et al., 2016). AMT received substantial empirical support for the relationship between alcohol use and risky sexual behaviors. Alcohol administration studies showed that intoxicated college men high in sexual arousal were more likely to report favorable attitudes/intentions toward unprotected sex compared with sober men (MacDonald et al., 2000). Intoxicated participants, compared with sober ones, reported greater attention to impelling sexual cues and greater intention to engage in risky sexual behaviors (Davis et al., 2007). AMT is also supported in the relation between alcohol use and sexual aggression perpetration. Alcohol use increased the odds of sexual aggression perpetration in intimate dating relationships among college men (Shorey et al., 2014) and college men's sexual aggression toward a new sexual partner (Testa et al., 2015).

Although it is a robust risk factor for HUBs, alcohol use is neither necessary nor sufficient for risky sexual behaviors to occur, and researchers have called for the examination of individual difference factors as moderators of alcohol-facilitated risky sexual behaviors (Cooper, 2010; Moss & Albery, 2009). The dual systems model (Steinberg, 2008), a theory of risk-taking behaviors among emerging adults, may help explain the relationship between alcohol and HUBs by providing a framework for individual difference factors that moderate this relationship. The dual systems model is based on the socio-emotional and cognitive control systems (Steinberg, 2008, 2010). The socio-emotional system is responsible for reward seeking, is fast acting, and relies on heuristics created through learned associations (e.g., alcohol-related sexual expectancies) and emotional reactions (e.g., positive affect; Ellingson et al., 2013; Lieberman, 2007). The cognitive control system is responsible for self-regulation and impulse control. Around puberty, increased dopaminergic activity within the socio-emotional system results in increased reward-seeking behavior (Lambert et al., 2014). The cognitive control system matures much slower and does not reach full maturation until the mid-20s. The maturation gap among young adults increases the likelihood of risky behavior.

The dual systems model received support to explain emerging adults' engagement in risky sexual behaviors and sexual aggression perpetration. Impulsivity has consistently been linked to sexual risk-taking (Dir et al., 2014) among emerging adults, particularly in response to high affective states (Deckman & DeWall, 2011; Zapolski et al., 2009). Difficulty regulating positive emotions, such as positive urgency or the tendency to give in to impulses while experiencing high positive affect, increases risky sexual behaviors (Curry et al., 2018; Cyders et al., 2007; Deckman & DeWall, 2011; Zapolski et al., 2009). Furthermore, college men with a history of sexual aggression perpetration, compared with men without a history of perpetration, reported higher positive urgency (Mouilso et al., 2013).

Alcohol-related sexual expectancies are the anticipation of a positive sexual outcome, such as increased sexual intimacy (i.e., sexual affect) and sexual arousal (i.e., sexual drive), following alcohol use (Abbey et al., 1999; Dir et al., 2013). Also consistent with the dual systems model, heuristics such as alcohol-related expectancies were associated with sexual risk-taking (Patrick & Maggs, 2009; Patrick et al., 2015) and sexual aggression perpetration (Palmer et al., 2010; Wilson et al., 2002). An integrated AMT and dual systems model would suggest that the risk of alcohol-facilitated HUBs may depend on the presence of distal socio-emotional system factors such as positive urgency and alcohol-related sexual expectancies.

Aims and hypotheses

The present study examined the proximal association between an alcohol use day and HUBs (consensual and coercive) among college men and the moderating effect of positive urgency and alcohol-related sexual expectancies on this proximal association using a daily diary design. We hypothesized that an alcohol use day would increase the odds of college men engaging in a consensual and coercive HUB. We also hypothesized that on an alcohol use day, (a) the odds of consensual and coercive HUBs would be greater among college men high, relative to low, in positive urgency and (b) the odds of engagement in consensual and coercive HUBs would be greater for college men high, relative to low, in alcohol-related sexual expectancies.

Method

Participants

The study methods were approved by the local institutional review board. Men attending a large southeastern university (n = 99) were recruited for the present study. To be eligible, individuals had to (a) be a man attending college, (b) be 18–25 years of age, (c) have engaged in at least one HUB in the past month, and (d) have consumed alcohol in the past month. Individuals were excluded from the study if they were in an exclusive dating relationship (i.e., both partners agreed to only engage in an intimate relationship with one another). Students interested in participating in the study first completed an eligibility survey (N = 529), and 283 (53.50%) students were screened as eligible. Eligible participants were then directed to the consent form and baseline survey. Five eligible participants did not proceed to the baseline survey. Of the participants who moved on to the baseline survey, nine were removed because of responses in the demographics questionnaire that determined they were not eligible for the study (e.g., women; men who never engaged in a HUB), and two only completed the demographics questionnaire. This resulted in 267 (50.47%) participants completing the baseline survey.

Participants were then given the option to continue to the daily diary portion of the study, and 106 (39.70%) continued as daily participants. Participants were excluded from study analyses if they completed less than three daily surveys (n = 5) or did not complete the baseline assessments needed for data analysis (n = 2). Baseline self-report assessments of past-year alcohol use and sexual aggression perpetration, as well as the average number of HUBs in the past month, were not significantly different between participants who did and did not participate in the daily surveys.

Participants included cisgender (99%) and transgender (1%) men with a mean age of 19.93 years (SD = 1.84). Participants' academic level included freshmen (33.3%), sophomores (24.2%), juniors (17.2%), seniors (19.2%), and postbaccalaureate or graduate students (6.1%). The ethnic/racial identities of participants were 75% White, 8.3% Hispanic or Latino, 7.4% Asian, 5.6% Black or African American, 1.9% other, 0.9% Native American, and 0.9% Indian or Middle Eastern, with 8.1% of participants reporting multiple racial/ethnic identities. Participants identified as straight or heterosexual (84%), gay (12%), bisexual (3%), and queer (1%), with 1% of participants reporting multiple sexual identities. Most participants reported being single (99%), whereas one reported being in a non-exclusive dating relationship (1%).

Procedure

Study recruitment materials included flyers around campus, advertisements on university-affiliated media, and the psychology department's research participation website. Recruitment materials advertised a research study on college men's hookup experiences and included eligibility criteria and study description (i.e., completion of brief surveys for 60 days). Interested individuals were directed to a brief eligibility screening survey. Eligible participants were then directed to an online baseline assessment. Participants who completed the baseline assessment were given the option to receive two psychology course credits for research participation or $20, later raised to $40 to increase participant recruitment. Following the baseline survey, participants were offered the opportunity to participate in the daily diary portion of the study. Participants received $1.00—later increased to $2.00 to increase participant recruitment—for each daily survey they completed and a $5 bonus for every week of completed surveys. Participants could earn up to $100, later increased to $160, for participating in the daily diary portion of the study.

A Qualtrics.com survey link was sent to participants starting the day after baseline assessment and every day for 60 consecutive days via email or text at 6:00 a.m. Participants were asked to report on their alcohol use and HUB the day prior, defined as the time they woke up to the time they went to sleep, consistent with prior daily diary research (Brem et al., 2022; Shorey et al., 2014). Participants who did not complete their daily survey were sent up to two reminder messages each day (i.e., one at 12:00 noon and one at 5:00 p.m.). Participants who failed to complete two consecutive days of surveys were called or texted to ensure they were not encountering problems.

Measures

Baseline measures. The Alcohol Expectancies Regarding Sex, Aggression, and Sexual Vulnerability Questionnaire (Abbey et al., 1999) is a 25-item self-report measure comprising four alcohol-related sexual expectancies: (a) aggression, (b) sexual affect, (c) sexual drive, and (d) vulnerability to sexual coercion. The sexual affect and sexual drive domains were used in the present study. Participants rated items on a 5-point Likert-type scale ranging from 1 (not at all) to 5 (very much). Items within each domain were summed and averaged. This measure demonstrated validity among college students (Abbey et al., 1999). The sexual affect (α = .92) and sexual drive (α = .95) domains demonstrated excellent internal reliability in the present study.

The Short Form UPPS-P Impulsive Behavior Scale (Cyders et al., 2014) is a 20-item self-report measure of five impulsivity factors: positive urgency, negative urgency, lack of perseverance, lack of premeditation, and sensation seeking. The positive urgency subscale was used in the present study. Items were rated on a 1 (strongly disagree) to 4 (strongly agree) scale and averaged. This measure showed validity and reliability in a college sample (Cyders et al., 2014). The positive urgency (α = .71) facet showed good internal reliability in the current study.

Daily measures. Participants were asked how many standard drinks of alcohol they consumed, with a definition of standard drink provided (National Institute on Alcohol Abuse and Alcoholism, 2010). A dichotomous alcohol use variable was created from the number of standard drinks reported on a 0 (no alcohol consumed) to 1 (yes alcohol consumed) scale. Participants who endorsed a HUB the day prior were also asked how many standard drinks of alcohol they consumed before their HUB. The dichotomous alcohol use variable was then re-coded for participants who engaged in a HUB to reflect the alcohol use that only occurred before the HUB. This allowed for the temporal examination of alcohol use resulting in HUB and prevented confounding alcohol consumed after a HUB with consumption that occurred before a HUB. This coding approach for alcohol use was used in previous alcohol-related daily diary studies (Brem et al., 2022; Shorey et al., 2014).

Participants were asked if they consumed any nonprescription drugs (e.g., marijuana, stimulants, opiates) and, if so, what type of drug(s) they consumed. Drug use was then coded on a 0 (no drug[s] used) to 1 (yes drug[s] used) scale. Participants who endorsed a HUB the day prior were also asked about any nonprescription drug use before their HUB. The dichotomous drug use variable was then re-coded to reflect the drug use that only occurred before the HUB.

Participants were asked if they engaged in any type of sexual behavior with someone 18 years or older and if their sexual behavior was a HUB (i.e., sexual activity with some-one they were not in a dating/romantic relationship with and there was no mutual expectation of a romantic commitment; Bogle, 2007; Lewis et al., 2012). Participants were asked to select all of the sexual activity that occurred during the hookup (e.g., kissing, manual stimulation, oral sex, vaginal sex), whether their hookup partner was a new sexual partner, and the use of any forms of protection against sexually transmitted infections (e.g., condoms).

Participants who engaged in a HUB were asked the extent to which they used (a) verbal pressure, (b) physical pressure or force, and (c) encouragement of the hookup partner's alcohol or drug use as a means of obtaining sexual activity from the partner, consistent with prior daily diary research on sexual coercion (Testa et al., 2015). Responses were rated on a 1 (not at all) to 7 (a great deal) scale. Scoring of HUBs was dichotomized such that those who endorsed a 1 on all three coercive tactics were categorized as a consensual HUB, whereas those who endorsed 2–7 on one or more of the coercive tactics (i.e., verbal, physical, or use of alcohol or drugs) were categorized as a coercive HUB (Testa et al., 2015).

Data analytic strategy

Descriptive statistics were analyzed using IBM SPSS Statistics for Windows, Version 27.0 (IBM Corp, Armonk, NY). Multilevel modeling using fixed slopes (due to the sample size of less than 100) and full maximum likelihood estimation in HLM7 were used to test the study's hypotheses. All participants' daily data were used in the analyses despite some missing data since multilevel modeling procedures use Bayesian rules to estimate missing data. Multinomial sampling distribution was used for the analyses, which allowed for an examination of the odds of a particular type of HUB compared with a reference group. We examined two sets of multinomial models. In one model, no HUB was the reference group to examine the odds of a consensual HUB compared with no HUB and the odds of a coercive HUB compared with no HUB. In the second model, coercive HUB was the reference group used to compare the odds of a coercive HUB to a consensual HUB. Results from the model where coercive HUBs are the reference group compared with no HUBs are not included because they are the same as those from the model where no HUBs are the reference group but in the opposite direction (i.e., positive coefficients are negative).

First, we examined an alcohol use day as it related to HUBs using the two multinomial models (no HUB reference group, coercive HUB reference group). We then examined positive urgency, alcohol-related sexual affect expectancies, and alcohol-related sexual drive expectancies as moderators of the association between an alcohol use day and HUBs. Separate analyses were conducted for the three moderating variables using the two multinomial models (no HUB reference group, coercive HUB reference group).

Two-level models were used in the present study. Level 1 variables were time-variant (i.e., daily reports of alcohol use). Daily drug use was included in Level 1 to control for the effect of drug use on HUBs. Level 2 variables were not time-variant (i.e., positive urgency and alcohol-related sexual affect and drive expectancies). To examine the between-person effects of alcohol use on HUBs, we calculated the participant's daily average alcoholic drinks consumed and then centered it on the grand mean as a Level 2 variable. Significant interactions were decomposed using simple effects tests (Aiken & West, 1991).

Results

Descriptive statistics

See Table 1 for means, standard deviations, and correlations among Level 2 study variables. Sexual affect and sexual drive alcohol-related sexual expectancies, as well as participant's mean alcohol drinks consumed and alcohol-related sexual drive expectancies, were significantly and positively correlated. The 99 participants completed 4,689 of the 5,940 surveys (78.93%), with an average of 47.36 (SD = 20.03) completed daily surveys. There were 343 (7.31%) instances of HUBs. Sixty-nine (69.70%) participants engaged in at least one HUB with an average of 4.97 (SD = 4.11) HUBs, ranging from 1 to 17. The sexual acts during HUBs included kissing (93.88%), fondling/petting over clothing (85.13%), manual stimulation (74.93%), digital penetration (53.94%), vaginal sex (53.35%), oral sex (51.02%), anal sex (7.87%), and “other” (0.87%). The average number of sexual acts during a HUB was 4.23 (SD = 1.74), ranging from 1 to 7. Of the 245 (71.43%) hookups that included at least one of the following—vaginal sex, oral sex, or anal sex—84 (34.29%) included condom use, 5 (2.04%) included the use of pre-exposure prophylaxis (PrEP), 3 (1.22%) included the use of some other type of protection, and 149 (60.82%) included no use of protection. Most HUBs (66.76%) involved a partner with whom the individual had previously engaged in sexual activity.

Table 1.

Summary of bivariate correlations, means, and standard deviations of Level 2 variables

graphic file with name jsad.24-00005tbl1.jpg

Measure 1. 2. 3. 4. 5.
1. Sexual affect –
2. Sexual drive .55† –
3. Positive urgency -.17 -.11 –
4. Mean HUBs .12 .11 -.12 –
5. Mean alcoholic drinks .09 .27** -.12 .20 –
M 3.72 3.40 2.05 0.07 1.32
SD 0.93 1.10 0.68 0.09 1.68
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Notes: Mean HUBs = the average number of hookup behaviors an individual engaged in per day; mean alcoholic drinks = the average number of alcoholic drinks consumed per day.

**

p < .01;

†

p < .001.

Of the 343 HUBs, 212 were consensual (61.81%) and 129 were coercive (37.61%), with missing information from 2 HUBs. Fifty-two (52.53%) participants engaged in at least one coercive HUB. Of the 69 participants who engaged in at least one HUB, 33 (47.83%) engaged in both consensual and coercive HUBs, 17 (24.64%) engaged in only consensual HUBs, and 19 (27.54%) engaged in only coercive HUBs. The average number of consensual HUBs was 3.07 (SD = 3.47), and the average number of coercive HUBs was 1.87 (SD = 2.32). There were 113 (87.60%) instances of the use of verbal coercion, 34 (26.36%) instances of physical force/threats, and 24 (18.60%) instances of alcohol or drug use during coercive HUBs. Ninety-one (70.54%) coercive HUBs included the use of one coercive tactic, 34 (26.36%) included the use of two coercive tactics, and 4 (3.10%) included the use of all three coercive tactics.

There were 816 (17.40%) drinking days, with 162 (19.85%) drinking days in which alcohol consumption occurred before the HUB. An average of 7.11 (SD = 4.55) alcoholic drinks were consumed before a consensual HUB and 8.11 (SD = 6.21) before a coercive HUB. Regarding drug use, there were 513 (10.94%) instances of drug use, primarily marijuana use (93.96%), followed by other (2.53%), stimulants (1.36%), cocaine (1.17%), poppers (1.17%), hallucinogens (0.39%), and anxiolytics (0.19%). Most days included using only one drug (99.03%). On 130 (15.93%) of the 816 drinking days, drug use also occurred.

Primary analyses

Alcohol use day. See Table 2 for parameter estimates of the alcohol use day models. Results from the no HUB reference group model showed that there was a significant main effect of an alcohol use day. An alcohol use day increased the odds of engaging in a consensual HUB, compared with no HUB, by 4.36. An alcohol use day also increased the odds of engaging in a coercive HUB, compared with no HUB, by 8.40. Results from the coercive HUB reference group model showed that an alcohol use day decreased the odds of engaging in a consensual HUB, relative to a coercive HUB, by 0.66.

Table 2.

Parameters of the alcohol use day models

graphic file with name jsad.24-00005tbl2.jpg

Variable No-hookup reference group Coercive hookup reference group
Consensual hookup Coercive hookup Consensual hookup
B SE OR [95% CI] B SE OR [95% CI] B SE OR [95% CI]
Level 1 (within-person effects and cross-level interactions)
 Alcohol use day 1.47† 0.21 4.36 [2.88, 6.59] 2.13† 0.28 8.40 [4.81, 14.68] -0.66* 0.32 0.52 [0.28, 0.96]
 Drug use day 0.39 0.36 1.48 [0.74, 2.98] -0.42 0.37 0.66 [0.32, 1.36] 0.81 0.44 2.25 [0.96, 5.29]
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Notes: Separate models were analyzed for the two reference groups. OR = odds ratio; CI = confidence interval.

*

p < .05;

†

p < .001.

Positive urgency. See Table 3 for parameters of the no HUB reference group, positive urgency model. Results from the no HUB reference group model showed that the interaction between alcohol use and positive urgency was not significant. There was a significant main effect of an alcohol use day. An alcohol use day increased the odds of engaging in a consensual HUB compared with not engaging in a HUB by 4.54. An alcohol use day also increased the odds of engaging in a coercive HUB compared with not engaging in a HUB by 8.17. No other main effects were significant. See Table 4 for the parameters of the coercive HUB reference group models. Results from the coercive HUB reference group model revealed that on a drug use day, the odds of engaging in a consensual HUB versus a coercive HUB increased by 2.33. The main effect of an alcohol use day on a consensual HUB, compared with a coercive HUB, approached significance (B = -0.59, p = .056).

Table 3.

Parameters of the no-hookup reference group, positive urgency models

graphic file with name jsad.24-00005tbl3.jpg

Variable Consensual hookup Coercive hookup
B SE OR [95% CI] B SE OR [95% CI]
Level 2 (between-person effects)
 M alcohol use -0.02 0.09 0.98 [0.81, 1.18] 0.04 0.06 1.05 [0.93, 1.18]
 Positive urgency -0.46 0.31 0.63 [0.34, 1.16] -0.06 0.27 0.94 [0.55, 1.61]
Level 1 (within-person effects and cross-level interactions)
 Alcohol use day 1.51† 0.22 4.54 [2.96, 6.92] 2.10† 0.28 8.17 [4.68, 14.28]
 Alcohol × Positive Urgency 0.28 0.31 1.33 [0.72, 2.46] 0.51 0.33 1.67 [0.87, 3.21]
 Drug use day 0.41 0.35 1.51 [0.76, 3.02] -0.43 0.37 0.65 [0.31, 1.34]
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Notes: OR = odds ratio; CI = confidence interval.

†

p < .001.

Table 4.

Parameters of the coercive hookup reference group models

graphic file with name jsad.24-00005tbl4.jpg

Variable Consensual hookup
Positive urgency model Sexual drive model Sexual affect model
B SE OR [95% CI] B SE OR [95% CI] B SE OR [95% CI]
Level 2 (between-person effects)
 M alcohol use -0.07 0.11 0.93 [0.75, 1.17] -0.02 0.12 0.98 [0.77, 1.25] -0.04 0.12 0.96 [0.76, 1.21]
 Trait -0.40 0.31 0.67 [0.36, 1.24] -0.17 0.30 0.84 [0.47, 1.52] -0.04 0.37 0.96 [0.46, 2.00]
Level 1 (within-person effects and cross-level interactions)
 Alcohol use day -0.59 0.31 0.56 [0.30, 1.02] -0.65* 0.32 0.52 [0.28, 0.98] -0.66* 0.31 0.51 [0.28, 0.96]
 Alcohol × Trait -0.23 0.39 0.80 [0.37, 1.71] 0.16 0.32 1.18 [0.62, 2.22] 0.28 0.40 1.32 [0.60, 2.89]
 Drug use day 0.85* 0.43 2.33 [1.01, 5.40] 0.82 0.43 2.28 [0.97, 5.32] 0.79 0.43 2.20 [0.94, 5.15]
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Notes: Separate models were analyzed for the three traits: positive urgency, sexual drive, and sexual affect alcohol-related sexual expectancies. OR = odds ratio; CI = confidence interval.

*

p < .05.

Alcohol-related sexual drive expectancies. See Table 5 for parameters of the no HUB reference group, sexual drive expectancies model. Results from the no HUB reference group model revealed that the interaction between alcohol use and alcohol-related sexual drive expectancies was not significant. There was a significant main effect of an alcohol use day. An alcohol use day increased the odds of engaging in a consensual HUB by 4.26 compared with not engaging in a HUB. An alcohol use day also increased the odds of engaging in a coercive HUB compared with not engaging in a HUB by 8.17. No other main effects were significant. See Table 4 for parameter estimates of the coercive HUB reference group models. Results from the sexual drive expectancies and coercive HUB reference group model showed only one significant main effect. An alcohol use day decreased the odds of engaging in a consensual HUB relative to a coercive HUB by 0.52.

Table 5.

Parameters of the no-hookup reference group, sexual drive models

graphic file with name jsad.24-00005tbl5.jpg

Variable Consensual hookup Coercive hookup
B SE OR [95% CI] B SE OR [95% CI]
Level 2 (between-person effects)
 M alcohol use -0.02 0.10 0.98 [0.80, 1.20] -0.002 0.06 1.00 [0.88, 1.13]
 Sexual drive -0.02 0.17 0.98 [0.70, 1.39] 0.15 0.27 1.17 [0.68, 1.99]
Level 1 (within-person effects and cross-level interactions)
 Alcohol use day 1.45† 0.21 4.26 [2.81, 6.46] 2.10† 0.30 8.17 [4.58, 14.58]
 Alcohol × Sexual Drive 0.23 0.21 1.26 [0.83, 1.91] 0.07 0.33 1.07 [0.57, 2.04]
 Drug use day 0.38 0.36 1.47 [0.73, 2.95] -0.44 0.37 0.64 [0.31, 1.33]
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Notes: OR = odds ratio; CI = confidence interval.

†

p < .001.

Alcohol-related sexual affect expectancies. See Table 6 for parameters of the no HUB reference group, sexual affect expectancies model. Examination of the alcohol-related sexual affect expectancies and no HUB as the reference group model revealed that the interaction between alcohol use and sexual affect expectancies was significantly related to the odds of a consensual HUB but not a coercive HUB. Explication of the interaction at high (+1 SD) and low (-1 SD) levels of sexual affect expectancies revealed that an alcohol use day was significantly associated with a consensual HUB, compared with no HUB, at both low, B = 0.93, p = .009, OR = 2.53, 95% CI [1.27, 5.06], and high, B = 1.93, p < .001, OR = 6.87, 95% CI [4.32, 10.92], levels of sexual affect expectancies. Examination of the main effects showed that an alcohol use day was significantly associated with engagement in a coercive HUB. An alcohol use day increased the odds of engaging in a coercive HUB compared with not engaging in a HUB by 5.00. See Table 4 for parameter estimates of the coercive HUB reference group models. Results from the sexual affect and coercive HUB reference group model showed only one significant main effect. An alcohol use day decreased the odds of engaging in a consensual HUB relative to a coercive HUB by 0.51.

Table 6.

Parameters of the no-hookup reference group, sexual affect models

graphic file with name jsad.24-00005tbl6.jpg

Variable Consensual hookup Coercive hookup
B SE OR [95% CI] B SE OR [95% CI]
Level 2 (between-person effects)
 M alcohol use -0.02 0.10 0.98 [0.81, 1.19] 0.03 0.06 1.03 [0.91, 1.16]
 Sexual affect -0.002 0.21 1.00 [0.66, 1.51] 0.04 0.34 1.04 [0.53, 2.05]
Level 1 (within-person effects and cross-level interactions)
 Alcohol use day 1.43† 0.22 4.17 [2.71, 6.41] 2.09† 0.29 8.10 [4.63, 14.16]
 Alcohol × Sexual Affect 0.54* 0.22 1.71 [1.11, 2.64] 0.26 0.41 1.30 [0.58, 2.89]
 Drug use day 0.37 0.36 1.45 [0.72, 2.92] -0.42 0.37 0.66 [0.32, 1.36]
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Notes: OR = odds ratio; CI = confidence interval.

*

p < .05;

†

p < .001.

Discussion

The current study's findings support an alcohol use day as a proximal correlate of HUBs, both consensual and coercive, among college men. The findings also suggest that among college men, an alcohol use day increases the likelihood of a HUB becoming a coercive HUB. The significant main effect of an alcohol use day on HUBs remained the same throughout all moderation models, except for the positive urgency, coercive hookup reference group. When accounting for positive urgency, an alcohol use day was no longer a significant predictor of a consensual HUB compared with a coercive HUB. Instead, this model was the only instance of a significant main effect of a drug use day, in that a drug use day increased the likelihood of a consensual HUB versus a coercive HUB. Engagement in some types of HUBs might not be an impulsive decision. One study found that intent to engage in a non-intercourse HUB, but not intent to engage in an intercourse HUB, was significantly associated with increased alcohol use among college students (Beckmeyer, 2017). It is possible, then, that accounting for positive urgency resulted in an alcohol use day no longer being a significant predictor in that college men's alcohol use as it relates to HUBs is an intentional action. In this instance, drug use may be a more relevant correlate of HUBs, given that prior research showed that marijuana use increases sexual activity and risky sexual behaviors (Anderson & Stein, 2011; Metrik et al., 2016).

In the present study, although the vast majority of drug days were marijuana use days, there were drug use days that included the use of other nonprescription drugs. It is also possible that an alcohol use day was not significant in this model because of the sample size, given that the main effect approached significance. Additional research is needed to understand the role of impulsivity, particularly positive urgency, and drug use as they relate to consensual HUBs versus coercive HUBs.

Regarding the moderation hypotheses, only alcohol-related sexual affect expectancies were found to be a significant moderator of the alcohol and HUBs relation. An alcohol use day was significantly associated with a consensual HUB versus no HUB among those with low and high levels of sexual affect expectancies, with the odds increasing as levels of sexual affect expectancies increased. These results suggest that higher expectations that alcohol use will result in heightened sexual intimacy may increase the odds of a college man engaging in a consensual HUB on a day that alcohol is consumed.

Alcohol-related sexual drive expectancies did not moderate the association between alcohol use and consensual HUB. Prior work suggested that sexual drive expectancies may be an important moderator of the alcohol/sexual behavior relation (Patrick & Maggs, 2009; Patrick et al., 2015); however, these prior studies were not limited to college men. Alcohol-related sexual drive expectancies may be a more salient risk factor for women compared with men (Lefkowitz et al., 2016). Neither of the alcohol-related sexual expectancies moderated the association between alcohol use and coercive HUBs. Prior research found that alcohol-related sexual expectancies regarding women's sexuality, but not men's sexuality, were significantly associated with men's perpetration of sexual coercion (Bonneville & Trottier, 2022). It may be that alcohol-related sexual expectancies regarding oneself may be less influential than the expectancies regarding alcohol's effects on potential victims as it relates to engagement in coercive HUBs.

Positive urgency was not a significant moderator of the relation between alcohol use and HUBs, either consensual or coercive. It may be that positive urgency increases the likelihood of HUBs only when state positive affect is high. An alcohol administration study of a laboratory intimate partner aggression paradigm found that negative urgency (i.e., the tendency to act impulsively when negative affect is high; Cyders et al., 2007) was positively associated with intimate partner aggression only when state negative affect was high, but not low (Bresin et al., 2022). This study highlights the need to assess state affect to more accurately assess the potential role of positive urgency on HUBs.

The present study examined risk factors for college men's HUBs from an integrated AMT (Steele & Josephs, 1990) and dual systems model (Steinberg, 2008) perspective. The findings from the current study support the application of AMT to college men's HUBs. An alcohol use day increased the likelihood of both consensual and coercive HUBs, as well as decreased the likelihood of a consensual HUB compared with a coercive HUB. This suggests that alcohol's pharmacological effects result in cognitive resources directed toward cues that facilitate hookup experiences and away from inhibiting cues such as the risk of sexually transmitted infections and consequences of sexually coercive acts. Results from the cross-level interactions showed that only alcohol-related sexual affect expectancies moderated the association between an alcohol use day and consensual versus no HUBs. This finding provides preliminary support for an integrated AMT and dual systems model as it relates to consensual HUBs, but not coercive HUBs, in that reward-seeking heuristics increased the risk of alcohol-facilitated consensual HUBs. Additional research is needed to replicate these findings and provide additional support for an integrated AMT/dual systems model.

Limitations and future directions

The study findings should be considered with the following limitations. Participants were sent a link each day asking them to report their behaviors the previous day. Although recalling events from the day before is likely to result in fewer recall errors than retrospective methods that span a greater distance in time, participants' recall may still have inaccuracies. As alcohol use increases, participants may be less likely to recall the exact number of standard drinks consumed. Participants may also minimize engagement in potentially problematic behaviors such as underage alcohol use and sexual coercion. Sexual coercion tactics that were attempted but did not result in sexual contact with a potential hookup partner were not assessed, which may result in a limited understanding of the risk factors of college men's use of sexual coercion tactics. A portion of alcohol use days also included the use of drugs; however, it is unclear if co-occurring alcohol and drug use occurred or if both substances were used on the same day but at different times, which prevented examination of the effects of co-use on HUBs. Contextual factors specific to college students' drinking, such as the day of the week, were not assessed.

Given that college student drinking is more likely to occur on Thursdays, Fridays, and Saturdays, such information could further clarify alcohol's proximal effect on HUBs among the college population. The sample largely comprised White, straight/heterosexual, cisgender college men, and results may not generalize to other populations such as marginalized populations and adolescents. In addition, only 40% of participants who completed baseline assessments went on to participate in the daily diary portion of the study.

Despite these limitations, the present study can inform future research into college men's engagement in consensual and coercive HUBs. The use of transdermal alcohol sensors or breath alcohol analyzers could provide a more accurate assessment of a participant's alcohol use. Alcohol-related sexual expectancies regarding a potential partner were not examined in the present study and should be included in future research. Measurement of state affect during drinking episodes and HUBs may be needed to examine the effect of positive urgency on the alcohol/HUBs link. Use of ecological momentary assessment methods that assess participants several times a day would be beneficial to examine the temporal associations of alcohol use, drug use, affect, and consensual and coercive HUBs.

The present study's findings highlight the need to address alcohol use and alcohol-related sexual affect expectancies when attempting to prevent and intervene in college men's alcohol-related consensual and coercive HUBs. Given the prevalence of “hookup culture” on college campuses (Garcia et al., 2012), it may be beneficial to increase awareness of risk factors for risky and sexually coercive HUBs, including alcohol use and alcohol-related sexual expectancies, among the college population in general to assist in shifting cultural beliefs surrounding HUBs. Such educational opportunities could be incorporated into existing student health center programs and/or first-year programs that address common transitional issues among incoming college students, including risky alcohol use and sexual violence. In sum, these findings provide insight into risk factors to be addressed in intervention and prevention efforts for alcohol-facilitated sexual behaviors on college campuses and inform future sexual risk-taking and coercion research.

Footnotes

This work was supported by National Institute on Alcohol Abuse and Alcoholism (NIAAA) Grant F31AA028150 (awarded to the first author). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIAAA or the National Institutes of Health.

References

  1. Abbey A., McAuslan P., Ross L. T., Zawacki T. Alcohol expectancies regarding sex, aggression, and sexual vulnerability: Reliability and validity assessment. Psychology of Addictive Behaviors. 1999;13(3):174–182. doi: 10.1037/0893-164x.13.3.174. [DOI] [Google Scholar]
  2. Abbey A. Alcohol-related sexual assault: A common problem among college students. Journal of Studies on Alcohol, Supplement 14. 2002:118–128. doi: 10.15288/jsas.2002.s14.118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Aiken L. S., West S. G. Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage; 1991. [Google Scholar]
  4. Anderson B. J., Stein M. D. A behavioral decision model testing the association of marijuana use and sexual risk in young adult women. AIDS and Behavior. 2011;15(4):875–884. doi: 10.1007/s10461-010-9694-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Beckmeyer J. J. Non-intercourse and intercourse hookup intentions, drinking expectancies, and college students' heavy drinking. Substance Abuse. 2017;38(3):245–248. doi: 10.1080/08897077.2016.1214212. [DOI] [PubMed] [Google Scholar]
  6. Bogle K. A. The shift from dating to hooking up in college: What scholars have missed. Sociology Compass. 2007;1(2):775–788. doi: 10.1111/j.1751-9020.2007.00031.x. [DOI] [Google Scholar]
  7. Bonneville V., Trottier D. Gender differences in sexual coercion perpetration: Investigating the role of alcohol-use and cognitive risk factors. Journal of Interpersonal Violence. 2022;37(15–16):NP13791–NP13812. doi: 10.1177/08862605211006360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Brem M. J., Shorey R. C., McNulty J., Elledge L. C., Temple J. R., Stuart G. L. Proximal associations among college students' alcohol use and cyber partner abuse perpetration. Psychology of Addictive Behaviors. 2022;36(7):815–823. doi: 10.1037/adb0000818. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bresin K., Parrott D. J., Maner C., Eckhardt C. I. Impulsivity and perpetration of intimate partner aggression: The moderating effects of negative affective state and alcohol. Substance Use & Misuse. 2022;57(10):1618–1625. doi: 10.1080/10826084.2022.2102191. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Brown J. L., Vanable P. A. Alcohol use, partner type, and risky sexual behavior among college students: Findings from an event-level study. Addictive Behaviors. 2007;32(12):2940–2952. doi: 10.1016/j.addbeh.2007.06.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Cooper M. L. Toward a person × situation model of sexual risk-taking behaviors: Illuminating the conditional effects of traits across sexual situations and relationship contexts. Journal of Personality and Social Psychology. 2010;98(2):319–341. doi: 10.1037/a0017785. [DOI] [PubMed] [Google Scholar]
  12. Curry I., Luk J. W., Trim R. S., Hopfer C. J., Hewitt J. K., Stallings M. C., Brown S. A., Wall T. L. Impulsivity dimensions and risky sex behaviors in an at-risk young adult sample. Archives of Sexual Behavior. 2018;47(2):529–536. doi: 10.1007/s10508-017-1054-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Cyders M. A., Littlefield A. K., Coffey S., Karyadi K. A. Examination of a short English version of the UPPS-P Impulsive Behavior Scale. Addictive Behaviors. 2014;39(9):1372–1376. doi: 10.1016/j.addbeh.2014.02.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Cyders M. A., Smith G. T., Spillane N. S., Fischer S., Annus A. M., Peterson C. Integration of impulsivity and positive mood to predict risky behavior: development and validation of a measure of positive urgency. Psychological Assessment. 2007;19(1):107–118. doi: 10.1037/1040-3590.19.1.107. [DOI] [PubMed] [Google Scholar]
  15. Davis K. C., Hendershot C. S., George W. H., Norris J., Heiman J. R. Alcohol's effects on sexual decision making: An integration of alcohol myopia and individual differences. Journal of Studies on Alcohol and Drugs. 2007;68(6):843–851. doi: 10.15288/jsad.2007.68.843. [DOI] [PubMed] [Google Scholar]
  16. Deckman T., DeWall C. N. Negative urgency and risky sexual behaviors: A clarification of the relationship between impulsivity and risky sexual behavior. Personality and Individual Differences. 2011;51(5):674–678. doi: 10.1016/j.paid.2011.06.004. [DOI] [Google Scholar]
  17. Dir A. L., Coskunpinar A., Cyders M. A. A meta-analytic review of the relationship between adolescent risky sexual behavior and impulsivity across gender, age, and race. Clinical Psychology Review. 2014;34(7):551–562. doi: 10.1016/j.cpr.2014.08.004. [DOI] [PubMed] [Google Scholar]
  18. Dir A. L., Cyders M. A., Coskunpinar A. From the bar to the bed via mobile phone: A first test of the role of problematic alcohol use, sexting, and impulsivity-related traits in sexual hookups. Computers in Human Behavior. 2013;29(4):1664–1670. doi: 10.1016/j.chb.2013.01.039. [DOI] [Google Scholar]
  19. Ellingson J. M., Verges A., Littlefield A. K., Martin N. G., Slutske W. S. Are bottom-up and top-down traits in dual-systems models of risky behavior genetically distinct? Behavior Genetics. 2013;43(6):480–490. doi: 10.1007/s10519-013-9615-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Fielder R. L., Carey M. P. Prevalence and characteristics of sexual hookups among first-semester female college students. Journal of Sex & Marital Therapy. 2010a;36(4):346–359. doi: 10.1080/0092623x.2010.488118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fielder R. L., Carey M. P. Predictors and consequences of sexual “hookups” among college students: A short-term prospective study. Archives of Sexual Behavior. 2010b;39(5):1105–1119. doi: 10.1007/s10508-008-9448-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Flack W. F., Jr., Caron M. L., Leinen S. J., Breitenbach K. G., Barber A. M., Brown E. N., Gilbert C. T., Harchak T. F., Hendricks M. M., Rector C. E., Schatten H. T., Stein H. C. “The red zone”: Temporal risk for unwanted sex among college students. Journal of Interpersonal Violence. 2008;23(9):1177–1196. doi: 10.1177/0886260508314308. [DOI] [PubMed] [Google Scholar]
  23. Flack W. F., Hansen B. E., Hopper A. B., Bryant L. A., Lang K. W., Massa A. A., Whalen J. E. Some types of hookups may be riskier than others for campus sexual assault. Psychological Trauma: Theory, Research, Practice, and Policy. 2016;8(4):413–420. doi: 10.1037/tra0000090. [DOI] [PubMed] [Google Scholar]
  24. Garcia J. R., Reiber C. Hook-up behavior: A biopsychosocial perspective. Journal of Social, Evolutionary, and Cultural Psychology. 2008;2(4):192–208. doi: 10.1037/h0099345. [DOI] [Google Scholar]
  25. Garcia J. R., Reiber C., Massey S. G., Merriwether A. M. Sexual hookup culture: A review. Review of General Psychology. 2012;16(2):161–176. doi: 10.1037/a0027911. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Garner A. R., Spiller L. C., Williams P. Sexual coercion in the college population: A form of risk-taking behavior. Journal of Interpersonal Violence. 2020;35(23–24):5276–5291. doi: 10.1177/0886260517720736. [DOI] [PubMed] [Google Scholar]
  27. Krebs C. P., Lindquist C. H., Warner T. D., Fisher B. S., Martin S. L. The campus sexual assault (CSA) study: Final report. Washington, DC: National Institute of Justice, U.S. Department of Justice; 2007. [Google Scholar]
  28. LaBrie J. W., Hummer J. F., Ghaidarov T. M., Lac A., Kenney S. R. Hooking up in the college context: The event-level effects of alcohol use and partner familiarity on hookup behaviors and contentment. The Journal of Sex Research. 2014;51(1):62–73. doi: 10.1080/00224499.2012.714010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Lambert A. E., Simons-Morton B. G., Cain S. A., Weisz S., Cox D. J. Considerations of a dual systems model of cognitive development and risky driving. Journal of Research on Adolescence. 2014;24(3):541–550. doi: 10.1111/jora.12126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Lefkowitz E. S., Waterman E. A., Morgan N. R., Maggs J. L. College students' perceptions of the links between alcohol use and sexual experiences. Emerging Adulthood. 2016;4(4):272–283. doi: 10.1177/2167696815610694. [DOI] [Google Scholar]
  31. Lewis M. A., Granato H., Blayney J. A., Lostutter T. W., Kilmer J. R. Predictors of hooking up sexual behaviors and emotional reactions among U.S. college students. Archives of Sexual Behavior. 2012;41(5):1219–1229. doi: 10.1007/s10508-011-9817-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Lieberman M. D. Social cognitive neuroscience: A review of core processes. Annual Review of Psychology. 2007;58(1):259–289. doi: 10.1146/annurev.psych.58.110405.085654. [DOI] [PubMed] [Google Scholar]
  33. MacDonald T. K., MacDonald G., Zanna M. P., Fong G. Alcohol, sexual arousal, and intentions to use condoms in young men: Applying alcohol myopia theory to risky sexual behavior. Health Psychology. 2000;19(3):290–298. doi: 10.1037/0278-6133.19.3.290. [DOI] [PubMed] [Google Scholar]
  34. Metrik J., Caswell A. J., Magill M., Monti P. M., Kahler C. W. Sexual risk behavior and heavy drinking among weekly marijuana users. Journal of Studies on Alcohol and Drugs. 2016;77(1):104–112. doi: 10.15288/jsad.2016.77.104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Moss A. C., Albery I. P. A dual-process model of the alcohol-behavior link for social drinking. Psychological Bulletin. 2009;135(4):516–530. doi: 10.1037/a0015991. [DOI] [PubMed] [Google Scholar]
  36. Mouilso E. R., Calhoun K. S., Rosenbloom T. G. Impulsivity and sexual assault in college men. Violence and Victims. 2013;28(3):429–442. doi: 10.1891/0886-6708.vv-d-12-00025. [DOI] [PubMed] [Google Scholar]
  37. Napper L. E., Montes K. S., Kenney S. R., LaBrie J. W. Assessing the personal negative impacts of hooking up experienced by college students: Gender differences and mental health. The Journal of Sex Research. 2016;53(7):766–775. doi: 10.1080/00224499.2015.1065951. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. National Institute on Alcohol Abuse and Alcoholism. Rethinking drinking: Alcohol and your health. National Institutes of Health; 2010. https://www.niaaa.nih.gov/sites/default/files/publications/NIAAA_RethinkingDrinking.pdf [Google Scholar]
  39. Olmstead S. B., Conrad K. A., Anders K. M. First semester college students' definitions of and expectations for engaging in hookups. Journal of Adolescent Research. 2018;33(3):275–305. doi: 10.1177/0743558417698571. [DOI] [Google Scholar]
  40. Palmer R. S., McMahon T. J., Rounsaville B. J., Ball S. A. Coercive sexual experiences, protective behavioral strategies, alcohol expectancies and consumption among male and female college students. Journal of Interpersonal Violence. 2010;25(9):1563–1578. doi: 10.1177/0886260509354581. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Patrick M. E., Maggs J. L. Does drinking lead to sex? Daily alcohol–sex behaviors and expectancies among college students. Psychology of Addictive Behaviors. 2009;23(3):472–481. doi: 10.1037/a0016097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Patrick M. E., Maggs J. L., Lefkowitz E. S. Daily associations between drinking and sex among college students: A longitudinal measurement burst design. Journal of Research on Adolescence. 2015;25(2):377–386. doi: 10.1111/jora.12135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Paul E. L., Hayes K. A. The casualties of ‘casual sex’: A qualitative exploration of the phenomenology of college students' hookups. Journal of Social and Personal Relationships. 2002;19(5):639–661. doi: 10.1177/0265407502195006. [DOI] [Google Scholar]
  44. Schulenberg J. E., Johnston L. D., O'Malley P. M., Bachman J. G., Miech R. A., Patrick M. E. Monitoring the Future National Survey Results on Drug Use, 1975–2016: Volume II, College Students and Adults Ages 19–55. Ann Arbor, MI: Institute for Social Research, University of Michigan; 2017. [Google Scholar]
  45. Scott-Sheldon L. A., Carey K. B., Cunningham K., Johnson B. T., Carey M. P., the MASH Research Team Alcohol use predicts sexual decision-making: a systematic review and meta-analysis of the experimental literature. AIDS and Behavior. 2016;20(S1):19–39. doi: 10.1007/s10461-015-1108-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Shorey R. C., Stuart G. L., McNulty J. K., Moore T. M. Acute alcohol use temporally increases the odds of male perpetrated dating violence: A 90-day diary analysis. Addictive Behaviors. 2014;39(1):365–368. doi: 10.1016/j.addbeh.2013.10.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Steele C. M., Josephs R. A. Alcohol myopia: Its prized and dangerous effects. The American Psychologist. 1990;45(8):921–933. doi: 10.1037/0003-066x.45.8.921. [DOI] [PubMed] [Google Scholar]
  48. Steinberg L. A social neuroscience perspective on adolescent risk-taking. Developmental Review. 2008;28(1):78–106. doi: 10.1016/j.dr.2007.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Steinberg L. A dual systems model of adolescent risk-taking. Developmental Psychobiology. 2010;52(3):216–224. doi: 10.1002/dev.20445. [DOI] [PubMed] [Google Scholar]
  50. Testa M., Cleveland M. J. Does alcohol contribute to college men's sexual assault perpetration? Between-and within-person effects over five semesters. Journal of Studies on Alcohol and Drugs. 2017;78(1):5–13. doi: 10.15288/jsad.2017.78.5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Testa M., Parks K. A., Hoffman J. H., Crane C. A., Leonard K. E., Shyhalla K. Do drinking episodes contribute to sexual aggression perpetration in college men? Journal of Studies on Alcohol and Drugs. 2015;76(4):507–515. doi: 10.15288/jsad.2015.76.507. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Wilson A. E., Calhoun K. S., McNair L. D. Alcohol consumption and expectancies among sexually coercive college men. Journal of Interpersonal Violence. 2002;17(11):1145–1159. doi: 10.1177/088626002237399. [DOI] [Google Scholar]
  53. Zapolski T. C. B., Cyders M. A., Smith G. T. Positive urgency predicts illegal drug use and risky sexual behavior. Psychology of Addictive Behaviors. 2009;23(2):348–354. doi: 10.1037/a0014684. [DOI] [PMC free article] [PubMed] [Google Scholar]

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