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. Author manuscript; available in PMC: 2026 Jun 1.
Published in final edited form as: J Interpers Violence. 2024 Sep 27;40(11-12):2556–2581. doi: 10.1177/08862605241275994

Preliminary Efficacy of Positive Change (+Change): A Pilot Randomized Controlled Trial of an Integrated Alcohol and Sexual Assault Prevention Program Tailored by Gender and Sexual Orientation

Amanda K Gilmore 1, Karen E Nielsen 1, Nashalys K Salamanca 1, Daniel W Oesterle 2, Anushka Parekh 1, Ruschelle M Leone 1, Lindsay M Orchowski 3,4, Viswanathan Ramakrishnan 5, Debra Kaysen 6, Kelly Cue Davis 7
PMCID: PMC12440384  NIHMSID: NIHMS2087939  PMID: 39329408

Abstract

Background:

The current study presents preliminary efficacy findings of a pilot randomized controlled trial of Positive Change (+Change). +Change utilizes personalized normative feedback to target alcohol use, sexual assault (SA) victimization, SA perpetration, and bystander intervention tailored for heterosexual cisgender men, heterosexual cisgender women, and sexual and gender minoritized groups [SGM].

Methods:

Participants included 165 undergraduate students aged 18–25 years old from a large public university in the Southwestern US who engaged in past month heavy episodic drinking. Participants (57 cisgender heterosexual men; 54 cisgender heterosexual women; and 54 SGM) were randomized to +Change (n = 83) or an assessment-only control (n = 82) and completed surveys online at baseline and 3-month follow-up in a parallel design with a 1:1 ratio (NCT04089137). The principal investigator was blinded to participant condition. The current study presents the secondary outcomes of the pilot randomized controlled trial which include alcohol use, sexual assault victimization, sexual assault perpetration, and bystander intervention behavior.

Results:

+Change was associated with significantly less severe sexual assault victimization and more bystander intervention behavior at 3-month follow-up relative to the control. There were not significant differences between conditions in alcohol use at 3-month follow-up, however, the magnitude of decreases in drinking in the +Change condition in this pilot study were consistent with other personalized normative feedback interventions. The present study was unable to assess differences in sexual assault perpetration due to low base rates. No adverse effects among those receiving the intervention were observed.

Conclusions:

Findings suggested that +Change may be a feasible strategy to prevent sexual assault, by reducing student sexual assault victimization and increasing bystander intervention. A fully powered randomized clinical trial is needed to examine effects of +Change.

Keywords: sexual assault, alcohol, college students, sexual minorities, gender, +Change

Introduction

Rates of alcohol consumption are high on college campuses, with approximately 40% of college students engaging in heavy episodic drinking (HED), defined as 4 or more drinks for women and 5 or more drinks for men in less than two hours (NIAAA, 2023; Hingson & White, 2013). Sexual assault (SA) victimization rates are also high on college campuses, with 22% of college students experiencing SA victimization since entering college (Mellins et al., 2017). Depending on the scope of the definition and population, SA rates range from 1.8% to 34% for college women and 4.8% to 31% for college men, with most studies reporting rates for women at 20% or higher and rates for men at 6% or lower (Fedina, Holmes, & Backes, 2018). Notably, women and sexual and gender minoritized (SGM) students report the highest rates of SA victimization (Mellins et al., 2017). In a study national study, 7–8% of gender diverse students compared to 1.5–4.5% of cisgender college students experienced sexual assault in the first three months of college (Fedina et al., 2024). Similarly, 4–9% of gay, lesbian, bisexual, and queer college students compared to 2.8% of heterosexual college students experienced sexual assault in the first three months of college (Fedina et al., 2024). In terms of gender differences in SA perpetration during college, cisgender men are the most common perpetrators against cisgender women and gender minoritized groups, whereas cisgender women are the most common perpetrators against cisgender men (Martin et al., 2022).

While numerous risk factors for SA have been identified, alcohol use represents one of the most prominent risk factors for both SA victimization (Basile et al., 2021) and perpetration (Abbey et al., 2022). In fact, approximately half of all college sexual assaults involve alcohol use by either the victim or the perpetrator (Abbey et al., 2004); although, the frequency of alcohol-involved sexual assault may be even higher among individuals holding marginalized identities (Hequembourg et al., 2015). While the association between alcohol use and SA is exceedingly complex, acute alcohol intoxication is a unique situational risk factor that has been linked to both SA victimization and perpetration (Parrott & Eckhardt, 2018). Although numerous pathways have been proposed to explain the link between acute alcohol intoxication and SA more broadly (Abbey et al., 2001; Davis et al., 2006), proximal effects models—which emphasize the psychopharmacological impacts of acute alcohol intoxication on behavioral disinhibition, disruptions to social information processing, and impaired decision making—are supported by the empirical literature and consistent with recent models of SA victimization and perpetration. Since alcohol use represents a shared risk factor for both perpetrating and experiencing SA, alcohol use may be a promising modifiable intervention target for prevention programs seeking to reduce rates of SA victimization and perpetration (Abbey, 2011; Crane et al., 2016; Eckhardt et al., 2021).

Preventing alcohol use and SA in an integrated manner is a viable strategy to reducing alcohol use and risk of victimization among college women (Gilmore et al., 2015). Similarly, this approach is a viable strategy to preventing alcohol use and increasing bystander intervention among college men, although these interventions have primarily been facilitated in-person (Orchowski et al., 2018; 2023). This approach is especially promising given the co-occurring nature of alcohol use and SA (Abbey et al., 2004; Koss et al., 2022). In fact, integrated SA prevention programs that target alcohol use may be particularly effective when targeting theoretically-based factors linking alcohol and SA, including difficulties in resisting unwanted sexual advances (Norris, Masters, & Zawacki, 2004; Norris, Nurius, & Dimeff, 1996), impairments in engaging in effective bystander intervention behavior (Leone, Haikalis, Parrott, & DiLillo, 2018), and cognitive impairments associated with sexual perpetration including difficulty accurately assessing consent (Abbey et al., 2004; Crane et al., 2016). Although commercially-available online prevention programs (e.g., Alcohol.Edu) targeting combined alcohol use and related consequences (e.g., SA victimization) do exist, the scope of content specific to SA is limited. Furthermore, positive post-intervention outcomes pertaining to reduced alcohol consumption and lower rates of SA victimization are time-limited, wherein significant effects do not persist across academic semesters (Paschall et al., 2011).

Although integrated prevention programs to date have demonstrated preliminary efficacy (Gilmore et al., 2015; Orchowski et al., 2018), there are several limitations. Numerous prevention programs have been developed to separately target SA victimization, bystander intervention, or SA perpetration prevention. However, in light of best-practice recommendations put forth by prevention scholars (Banyard, 2014; Heise, 2011), while also acknowledging the existence of multiple shared risk factors contributing to these varying SA-related outcomes (Bendixen et al., 2024; Tomaszewska & Krahé, 2018), a multi-pronged approach targeting alcohol use, SA victimization, SA perpetration, and bystander intervention is needed to comprehensively reduce SA occurring on college campuses. This is imperative given that targeting alcohol use and SA is not as effective as integrated prevention programs (Gilmore et al., 2015) and there are overlapping risks for victimization, perpetration, and bystander intervention that may be better addressed within one program. Despite this, few integrated programs have been evaluated. There are some integrated programs which have shown progress including a program targeting alcohol and SA concurrently focused on either women’s victimization risk (Gilmore et al., 2015) or men’s alcohol use and bystander intervention (Orchowski et al., 2018), demonstrating that these programs are feasible. Additional interventions have focused on women’s victimization risk and bystander intervention integrated with alcohol use (Salazar et al., 2023) or men’s perpetration risk and bystander intervention (Salazar et al., et al., 2014). Collectively, these interventions provide separate programs for men and women and do not address the unique needs of sexual- or gender-minoritized groups.

Integrated alcohol and SA prevention programs have often excluded sexual and gender minority students, while those that have included SGM students do not include culturally tailored content for the students who identify as SGM (Blackburn et al., 2024). This is problematic because students who identify as SGM engage in alcohol use at higher rates and are targeted for SA victimization at higher rates than their cisgender, heterosexual peers (Marshal et al., 2008; Marshal et al., 2009; Johnson et al., 2016). They also may use alcohol in somewhat different contexts than their cisgender or heterosexual peers (Dyar & Kaysen, 2022; Griffin et al., 2022). Providing lesbian, gay, bisexual, trans, and queer (LGBTQ) students with programs that are not tailored to their needs could be invalidating or discriminatory towards students who identify as LGBTQ.

Personalized Normative Feedback Interventions

Personalized normative feedback to reduce alcohol use is an evidence-based strategy recommended by the National Institute on Alcohol Abuse and Alcoholism (NIAAA; 2015). Personalized normative feedback uses a social norms approach to correct misperceptions about peer alcohol use. Descriptive drinking norms, or perceptions of peer alcohol use, is the strongest predictor of alcohol use among college students (Neighbors et al., 2007; Perkins, 2002). In a systematic review of alcohol interventions among college students, the majority of trials found support for descriptive drinking norms as the mechanism of change for alcohol use (Reid & Carey, 2015). A meta-analysis of brief, personalized normative feedback interventions found a reduction of 1.5 drinks from baseline to 3-month follow-up (Foxcroft et al., 2015). Therefore, personalized normative feedback interventions for alcohol use are an evidence-based and mechanistic-based strategy to reduce alcohol use. A limited number of sexual assault prevention programs for women (Gilmore et al., 2015) and men (Orchowski et al., 2018) also incorporate personalized normative feedback to address alcohol, integrated with evidence-based prevention programming for sexual assault, in order to address the intersection of alcohol use and sexual assault.

Building on this demonstrated efficacy, Positive Change (+Change) is a web-based, multi-pronged prevention program targeting alcohol use, SA victimization risk, SA perpetration, and bystander intervention that uses personalized normative feedback. The program provides personalized normative feedback intervention on one’s own attitudes and behavior compared to peer attitudes and behavior related to alcohol use and sexual assault. For example, for alcohol use, participants were shown the number of alcoholic drinks consumed per week based on their own behavior, their perception of their peer’s behavior (descriptive drinking norms), and their actual peer’s behavior. Peer groups were tailored based on gender identity and sexual orientation, so participants could have received personalized normative feedback for cisgender heterosexual women, cisgender heterosexual men, or LGBTQ college students (see Gilmore et al., 2022 for a full program description with example content and theoretical targets). This program has demonstrated acceptable usability with college students aged 18–25 who engage in HED (Gilmore et al., 2022). In an open pilot study, +Change resulted in reductions in descriptive drinking norms as well as increases in awareness of SA victimization risk, readiness to change SA on their college campus, deciding to not have sex with someone who is drunk while they are drinking, and likelihood to intervene when witnessing a potential SA situation (Gilmore et al., 2022). Notably, this is the only intervention that targets these four interrelated behaviors (alcohol, SA victimization, SA bystander intervention, and SA perpetration) in a single intervention, with one exception of a program for college athletes (Thompson et al., 2021). This program is also the only intervention that provides tailored-content for LGBTQ students. However, +Change has not yet been evaluated in a pilot randomized controlled trial to determine if there are any initial effects on behavioral outcomes.

Current Study

The current study assessed the preliminary outcomes of a pilot randomized controlled trial of +Change among HED students aged 18–25. +Change included personalized normative feedback on alcohol use, SA victimization, SA perpetration, and bystander intervention among cisgender heterosexual men, cisgender heterosexual women and LGBTQ college students. It was hypothesized that +Change (vs. assessment only control) would be associated with less drinks per week, less severe SA victimization, less SA perpetration, and more SA-related bystander intervention at the 3-month follow-up. It’s important to note that alcohol use patterns changed during the COVID-19 pandemic (White et al., 2020) and given that the current study took place prior to and during the pandemic, timing of the study was controlled for in the analyses.

Methods

Participants

Participants in this randomized controlled trial included 165 students, ages 18–25, who engaged in HED at least once in the past month and were enrolled full-time students at a large public university in the southwestern region of the United States (see Figure 1 for CONSORT diagram). Participants identified as heterosexual cisgender women (n = 54, 32.73%), heterosexual cisgender men (n = 57, 34.55%), SGM (n = 52, 31.52%), or preferred not to answer questions related to gender identity and sexual orientation (n = 2, 1.21%). On average, participants were 20.35 years old (SD = 1.62). SGM participants identified as trans (n=2), gender queer/non-conforming/non-binary (n=7), questioning gender identity (n=1), lesbian (n=7), gay (n=8), bisexual (n=24), queer (n=5), two-spirit (n=1), questioning sexual orientation (n=4), asexual (n=2), pansexual (n=1), sexual orientation not listed (n=1). Additional sample characteristics are presented in Table 1.

Figure 1.

Figure 1.

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CONSORT Diagram

Table 1.

Descriptive Statistics of Key Variables

Variable Control (n=82) +Change (n=83) χ 2 t p
% (n) M (SD) % (n) M (SD)
Demographics
Cisgender heterosexual woman 32.9% (27) - 42.55 (20) - .088 - .957
Cisgender heterosexual man 35.4% (29) - 31.91 (15) - - - -
Sexual or gender minority 30.5% (25) - 25.53 (12) - - - -
Age - 20.5 (1.59) 20.2 (1.66) - .929 .763
Racial minority 22.0% (18) - 25.3% (21) - .21 - .647
Latine 29.3% (24) - 25.3% (21) - .091 - .763
COVID-19-Related Variables
Enrolled in the study before the COVID-19 pandemic 46.3% (38) - 59.0% (49) - 2.182 - .14
Alcohol Use
Average drinks (baseline) - 7.71 (8.08) - 8.21 (7.67) - −.4 .69
Average drinks (follow-up) - 6.41 (6.76) - 4.82 (4.83) - 1.55 .124
Descriptive drinking norms (baseline) - 19.7 (11.3) - 17.6 (15.2) - .962 .338
Descriptive drinking norms (follow-up) - 18.5 (10.8) - 14.5 (12.0) - 1.9646 .054
Sexual Assault Victimization
Any sexual assault victimization since age 14 (baseline) 53.7 (44) - 61.4 (51) - 1.093 - .296
Sexual assault victimization severity since age 14 (baseline) - 12.3 (17.4) - 12.5 (17.3) - −.096 .923
Any sexual assault victimization past 3 months (follow-up) 7.3 (6) - 15.7 (13) - 2.772 - .096
Sexual assault victimization severity past 3 months (follow-up) - .913 (3.89) - 3.34 (10.5) - −1.748 .084
Bystander Intervention
Bystander intervention behavior (baseline) - 3.34 (3.83) - 2.99 (3.65) - .607 .545
Bystander intervention behavior (follow-up) - .853 (2.83) - .788 (1.73) - .161 .872
Sexual Assault Perpetration
Any sexual assault perpetration since age 14 (baseline) 9.8 (8) - 4.8 (4) - 0.849 - .357
Sexual assault perpetration severity since age 14 (baseline) - .171 (.625) - .108 (.541) - .684 .495
Any sexual assault perpetration since past 3 months (follow-up) 8.5 (7) - 4.8 (4) - .334 - .563
Sexual assault perpetration severity past 3 months (follow-up) - .132 (.420) - .121 (.512) - .138 .891
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*

Bystander intervention behaviors were only available for those who witnessed a potential sexual assault situation.

Measures

Demographics.

Demographics including gender, sexual orientation, race, ethnicity, and time of enrollment in the study (before or after COVID-19 pandemic) were assessed at baseline.

Alcohol use.

The Daily Drinking Questionnaire (DDQ; Collins et al., 1985) assessed the average standard drinks consumed each day of the week. Average drinks per day were summed to calculate average drinks per week. The Drinking Norms Rating Form (DNRF; Baer, Stacy, & Larimer, 1991) was utilized to assess normative perceptions of alcohol use among peers (cisgender heterosexual men, cisgender heterosexual women, or LGBTQ). Of note, it was possible to answer 0 to this survey despite the requirement to engage in HED to enroll because drinking, including HED, may occur infrequently for the individual. Both the DDQ (Cronbach’s α=.868) and the DRNF (Cronbach’s α=.864) demonstrated good reliability in the present study.

SA victimization severity.

SA victimization was assessed using the Revised Sexual Experiences Survey (SES-SFV; Koss et al., 2007) where participants are asked to indicate whether they have previously experienced seven distinct sexual behaviors (e.g., someone had oral sex with me or I was forced to have oral sex with someone else without my consent) through the use of five sexually-coercive tactics (e.g., taking advantage of me when I was too drunk or out of it to stop what was happening). Participants responded to each item series indicating whether a specific behavior had occurred since the age of 14 via each tactic domain (e.g., verbal criticism, verbal pressure, alcohol intoxication, physical force, and threats of physical force). Participants were asked to indicate the number of times (0, 1, 2, or 3+) they experienced each item. SA victimization was scored using a severity scale which allows for frequency and severity of SA to be accounted for with a 0 to 63-point scale range (Davis et al., 2014). Prior studies document the reliability and validity of the Revised SES (Johnson et al., 2017). Baseline timeframe was since age 14 and follow-up assessed experiences in the past 3 months. The SES-SFV showed excellent reliability within the current study (Cronbach’s α = .954).

Bystander intervention behavior.

Bystander intervention behavior was assessed using the Bystander Behavior Scale (BBS; Banyard et al., 2014), a 44-item survey assessing engagement in bystander behavior with both friends and strangers in the past 3 months at both baseline and follow-up. An example item included “If I saw a friend/stranger grabbing or pushing their partner, I said something to them.” Opportunities to intervene were also assessed for each item on the Bystander Behavior Scale as recommended by recent studies (Hoxmeier, 2019; Hoxmeier et al., 2021), and participants who had no opportunities to intervene were not included in the bystander intervention behavior analyses. Items were modified to be gender neutral. The BBS showed acceptable reliability within the current study (Cronbach’s α = .789).

SA perpetration.

SA perpetration was assessed using the Revised Sexual Experiences Survey (SES-SFP; Koss et al., 2007) where participants are asked to indicate whether they have previously engaged in seven distinct sexual behaviors (e.g., I had oral sex with someone or I made someone have oral sex with me without their consent) through the use of five sexually-coercive tactics (e.g., taking advantage of them when they were too drunk or out of it to stop what was happening). Participants responded to each item series indicating whether a specific behavior had occurred since the age of 14 via each tactic domain (e.g., verbal criticism, verbal pressure, alcohol intoxication, physical force, and threats of physical force). Participants were asked to indicate the number of times (0, 1, 2, or 3+) they engaged in each behavior. SA perpetration was scored using a dichotomous method of 0 (no perpetration) and 1 (perpetration). Studies support the reliability and validity of the Revised SES to assess perpetration of violence (Anderson et al., 2017). Baseline timeframe was since age 14 and follow-up assessed experiences in the past 3 months. The SES-SFP showed excellent reliability within the current study (Cronbach’s α = .993).

+Change Intervention Condition

+Change was delivered via a web-based platform to provide personalized normative feedback on alcohol use, SA victimization, bystander intervention, and perpetration tailored for cisgender heterosexual men, cisgender heterosexual women, and LGBTQ students, which takes participants between 15–20 minutes on average to complete. The +Change program included adapted content from web-based BASICS for the personalized normative feedback and psychoeducation for alcohol (Labrie et al., 2013), an integrated alcohol and sexual assault risk reduction program for women (Gilmore et al., 2015; 2018), an adaptation of content from an in-person brief motivational interviewing personalized feedback protocol integrated with the men’s workshop for sexual assault perpetration and bystander intervention for men (Orchowski et al., 2018; 2023), and perpetration prevention content based on psychoeducation regarding consent and the effect of alcohol on the ability to give and receive consent [for a detailed description of +Change, the development of the program, the theoretical basis for content, and example content, see Gilmore, 2022].

Briefly, +Change includes personalized normative feedback based on answers to a baseline survey using a motivational interviewing approach. Misperceptions of alcohol use and peer acceptance of SA was corrected by providing actual normative data from college students on their campus. Normative feedback was tailored by gender identity and sexual orientation such that participants received normative feedback in one of three groups: cisgender heterosexual men, cisgender heterosexual women, and LGBTQ individuals. While separate theoretically-based content was provided to target alcohol use, SA risk reduction, bystander intervention, and SA perpetration, the influence of alcohol on each SA construct (victimization, perpetration, and bystander intervention) was integrated throughout.

Procedure

The primary aim of the pilot trial was to assess feasibility. Therefore, it was not powered to detect differences in behavioral outcomes assessed in the present analyses. Sample size (n=162) was calculated a priori using a power analysis in PASS© to estimate rates of alcohol use, SA victimization, bystander intervention, and SA perpetration, accounting for the anticipated low base rates of SA victimization and perpetration as well as 20% attrition.

All study procedures were completed online and approved by the university’s human subjects board of the corresponding author (H20066). Prior to conducting the current study, a norms documentation was conducted to assess norms at the university for the personalized normative feedback (procedures and results presented in Gilmore, 2022). Participants in the RCT were recruited from a list of students between the ages of 18–25 provided by the university registrar. To oversample LGBTQ students, we engaged in targeted recruitment for LGBTQ students through student organizations, ads on college online platforms, and social media. Interested participants were first verified to be currently enrolled college students through a list of students from the registrar. Participants were prevented from participating more than once. A total of 3,075 participants began the screening procedures to assess for eligibility, 625 completed the screening questions and 319 were eligible to participate in the study and were provided informed consent. Of the 319 eligible, 257 agreed and indicated they had time to participate, and 156 participants completed the baseline procedures and were randomized to the assessment only control (n = 82) or +Change (n = 83) condition using a parallel design with a 1:1 ratio. To equally distribute participants’ gender and sexual orientation across conditions, sequentially numbered containers were created to randomize participants upon completing their baseline assessment using block randomization. The allocation sequence was generated by the software engineer, who was not involved in analyses, and participants were automatically assigned to a condition by the web-based program. The Principal Investigator was blinded to participant assignments across conditions. Participants in the +Change condition completed the baseline assessment, received the single session +Change intervention, completed a post-intervention survey to assess usability, and a 3-month follow-up survey. Participants in the assessment only control group completed the baseline and 3-month follow-up assessments. See Figure 1 for participant retention. Participants were paid $25 and $35, respectively, for completing their baseline and follow-up assessments. The protocol can be accessed on clinicaltrials.gov (NCT04089137).

Analysis Plan

Descriptive statistics were produced prior to conducting analyses. Demographic and baseline responses for participants in the +Change intervention and control groups were compared using t-tests for continuous and count variables with a range of at least 20, and chi-square tests for categorical variables. Models were estimated for weekly drinking, SA victimization severity, and bystander intervention reported at the 3-month follow-up. For each outcome, the distribution of the outcome, contextual interpretation, and model fit were all considered to determine an appropriate statistical model. All models are variations on an analysis of covariance, or ANCOVA, a model that includes baseline values as predictors along with time-invariant covariates. Because all outcomes are counts, model selection began with fitting a Poisson model using the baseline value, treatment group, time of enrollment (before or during the COVID-19 pandemic), gender and sexual identity, age, race, and ethnicity as predictors, followed by assessment for overdispersion and zero-inflation. All models exhibited overdispersion and were refit as negative binomial models. All predictors were considered for predicting excess zeros in zero-inflated models and removed from that portion of the model if they did not improve model fit. Given that the pilot randomized controlled trial was not powered to detect differences in secondary outcomes examined in this study, effect sizes were produced for comparison to publish expected differences along with results of statistical tests. Specifically, incidence rate ratios (IRRs) were estimated as effect sizes to reflect relative rates across values of the predictors for the count outcomes (Higgins, Li, & Deeks, 2022). Comparison of non-significant intervention findings to existing literature is detailed in the discussion.

Results

Drinks per Week

A zero-inflated negative binomial regression did not uncover significant intervention effects on drinking behavior as measured with drinks per week (see Table 2). Significant predictors of excess zero drinks per week at the 3-month follow-up included: enrolling pre-COVID (IRR:8.77, 95%CI:1.62–47.45), identifying as a cisgender heterosexual man (compared to identifying as a cisgender heterosexual woman; IRR:6.53, 95%CI:1.27–33.68), being younger (age IRR:0.64, 95%CI:0.42–0.96), and reporting no drinks (i.e., a value of 0 on DDQ) at baseline (IRR:16.59, 95%CI:3.71–74.20). After accounting for excess zeros, those enrolling pre-COVID (IRR:1.35, 95%CI:1.04–1.76) and those with higher counts of baseline drinks (IRR:1.04, 95%CI:1.02–1.06) had significantly higher predicted drinks per week at the 3-month follow-up regardless of intervention condition. Although not significant in the model, estimated drinks per week at the 3-month follow-up were lower in the +Change condition than the control condition when controlling for baseline drinks and zero-inflation (IRR=0.85). When comparing means without adjusting for covariates or zero-inflation, there was a larger decrease in drinks per week in the +Change condition (Mpaired_difference=−2.41) than in the control condition (Mpaired_difference=−1.47).

Table 2.

Average Drinks Per Week Analyses

Predictors Incidence Rate Ratios CI p
Count Model
 Baseline average drinks per week 1.04 1.02 – 1.06 <0.001
 No average drinks per week at baseline 0.85 0.47 – 1.56 0.605
 +Change condition (vs. control condition) 0.85 0.66 – 1.11 0.244
 Racial minority 1.00 0.72 – 1.39 0.994
 Hispanic/Latine 1.22 0.88 – 1.70 0.225
 Age 0.93 0.85 – 1.01 0.074
 Cisgender heterosexual woman (vs. cisgender heterosexual man) 0.98 0.69 – 1.38 0.889
 Sexual or gender minority (vs. cisgender heterosexual man) 0.87 0.61 – 1.25 0.463
 Enrolled in study before the COVID-19 pandemic 1.35 1.04 – 1.76 0.026
Zero-Inflated Model
 No drinks per week at baseline 16.59 3.71 – 74.20 <0.001
 +Change condition (vs. control condition) 1.70 0.50 – 5.81 0.398
 Racial minority 2.45 0.58 – 10.27 0.221
 Hispanic/Latine 1.79 0.44 – 7.27 0.416
 Age 0.64 0.42 – 0.96 0.030
 Cisgender heterosexual woman (vs. cisgender heterosexual man) 6.53 1.27 – 33.68 0.025
 Sexual or gender minority (vs. cisgender heterosexual man) 2.74 0.54 – 13.89 0.223
 Enrolled in study before the COVID-19 pandemic 8.77 1.62 – 47.45 0.012
 Observations 122
 R2 / R2 adjusted 0.888 / 0.878
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SA Victimization Severity

A zero-inflated negative binomial model revealed an intervention effect of +Change: those in the +Change condition had lower severity of SA victimization at the 3-month follow-up compared to those in the control condition (IRR:0.38, 95%CI:0.16–0.89; see Table 3). Baseline SA victimization was also significantly associated with victim severity at the 3-month follow-up (IRR:1.03, 95%CI:1.01–1.05) and excess zeros in the severity scores at the 3-month follow-up (IRR:0.96, 95%CI:0.93–1.00).

Table 3.

Sexual Assault Victimization Analyses

Predictors Incidence Rate Ratios CI p
Count Model
 +Change condition (vs. control condition) 0.38 0.16 – 0.89 0.027
 Sexual assault victimization severity at baseline 1.03 1.01 – 1.05 0.002
 Racial minority 0.35 0.12 – 1.00 0.050
 Hispanic/Latine 1.02 0.39 – 2.67 0.974
 Age 1.11 0.84 – 1.46 0.478
 Cisgender heterosexual woman (vs. cisgender heterosexual man) 1.45 0.37 – 5.65 0.595
 Sexual or gender minority (vs. cisgender heterosexual man) 2.45 0.49 – 12.35 0.278
 Enrolled in study before the COVID-19 pandemic 0.67 0.30 – 1.51 0.336
Zero-Inflated Model
 +Change condition (vs. control condition) 0.37 0.11 – 1.23 0.104
 Sexual assault victimization severity at baseline 0.96 0.93 – 1.00 0.032
 Racial minority 1.42 0.30 – 6.71 0.658
 Hispanic/Latine 1.11 0.25 – 4.98 0.887
 Age 1.25 0.83 – 1.90 0.287
 Cisgender heterosexual woman (vs. cisgender heterosexual man) 0.24 0.04 – 1.56 0.135
 Sexual or gender minority (vs. cisgender heterosexual man) 0.61 0.09 – 4.15 0.612
 Enrolled in study before the COVID-19 pandemic 1.96 0.57 – 6.80 0.288
 Observations 126
 R2 / R2 adjusted 0.941 / 0.937
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SA Perpetration

Reported SA perpetration was relatively rare within the sample. Eight individuals reported perpetration at both baseline and the 3-month follow-up (5 in the control condition and 3 in +Change), while 3 (2 control and 1 +Change) individuals reported at baseline but not at the 3-month follow-up (1 additional individual in the control condition reported perpetration at baseline and did not respond at the 3-month follow-up) and 3 individuals (2 control and 1 +Change) newly reported perpetration at the 3-month follow-up after reporting no perpetration at baseline. Because of the low SA perpetration rates, inferential analyses were not conducted.

Bystander Intervention Behavior

Analysis of the bystander behavior scale was limited to only those who had the opportunity to intervene in risky situations, which included 34 (42.5%) participants in the control condition and 30 (36.6%) participants in the +Change intervention condition (see Table 4); therefore, a total of 101 (38.8%) participants across both conditions were excluded from analyses examining bystander intervention. After accounting for excess zeros in a zero-inflated negative binomial model, participants who received +Change and had the opportunity to intervene in risky situations reported higher bystander intervention behavior (IRR:4.34, 95%CI:1.63–11.60) compared to participants in the control condition who had the opportunity to intervene, as did Latine (compared to not Latine; IRR:7.01, 95%CI:2.37–20.73) respondents. Additionally, cisgender heterosexual women had higher bystander intervention behavior than SGM (IRR:4.03, 95%CI:1.35–12.05) and cisgender heterosexual men (IRR:4.01, 95%CI:1.55–10.37).

Table 4.

Bystander Intervention Behavior Analyses

Predictors Incidence Rate Ratios CI p
 +Change condition (vs. control condition) 4.34 1.63 – 11.60 0.003
 Bystander intervention behavior at baseline 1.07 0.96 – 1.18 0.209
 Age 1.17 0.90 – 1.52 0.229
 Racial minority 0.54 0.23 – 1.27 0.158
 Hispanic/Latine 7.01 2.37 – 20.73 <0.001
 Enrolled in study before the COVID-19 pandemic 0.50 0.22 – 1.14 0.098
 Cisgender heterosexual woman (vs. cisgender heterosexual man) 4.01 1.55–10.37 0.004
 Sexual or gender minority (vs. cisgender heterosexual man) 1.00 0.32 – 3.09 0.994
Zero-Inflated Model
 Intercept 0.00 0.00 – inf 0.980
 Observations 60
 R2 / R2 adjusted 0.837 / 0.807
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Discussion

The current study includes findings from a pilot randomized controlled trial of +Change, a personalized normative feedback on alcohol use, SA victimization, SA perpetration, and bystander intervention among cisgender heterosexual men, cisgender heterosexual women and LGBTQ college students. Because this is a pilot study, it was powered to detect preliminary differences rather than statistically significant findings. Nonetheless, current results extend previous research which found promising pre-post attitudinal changes (Gilmore et al., 2022) to find behavioral changes at 3-month follow-up. These promising findings suggest that this integrated alcohol and SA intervention has promise and merits further investigation. Moreover, it demonstrates that prevention programs addressing sexual assault and alcohol use can be successfully tailored and inclusive across gender identity and sexual orientation. This is novel as alcohol use and sexual assault prevention programs separately do not currently provide tailored content for LGBTQ college students, so the findings from this study suggest that future research tailoring both separate and integrated programs for LGBTQ college students may be warranted.

Findings from this pilot randomized controlled trial revealed that +Change was associated with less severe SA victimization and more bystander intervention behavior than the control condition at 3-month follow-up. This extends previous open pilot findings indicating +Change had acceptable usability and initial efficacy on reducing SA-related attitudinal constructs (Gilmore et al., 2022), by revealing significant changes in SA victimization and bystander intervention behavior. While there are other programs that reduce SA victimization or increase bystander behavior (Salazar et al., 2014; Salazar et al., 2023; Senn et al., 2015), +Change is the briefest existing intervention to target multiple sexual assault risk factors within a single intervention (less than 20 minutes compared to all other programs which last several hours or even several days). This extends findings that integrated alcohol and SA victimization risk reduction for women (Gilmore et al., 2015) and integrated alcohol and SA bystander intervention programming for men (Orchowski et al., 2018) can be 1) delivered via a brief web-based program; 2) personalized for cisgender heterosexual men, cisgender heterosexual women, and LGBTQ+ students; and 3) be effective at changing SA victimization and bystander behavior for all targeted demographics.

The current study did not detect significant differences in typical drinking at the 3-month follow-up based on condition. However, changes in drinking for personalized normative feedback programs tend to result in small effect sizes, and the current study was not powered to detect such small effects. A meta-analysis of 45 studies with a 3-month follow-up period found evidence of a small effect size (SMD = 0.14) equivalent to a difference of 1.5 drinks at follow-up between alcohol intervention and control conditions (Foxcroft et al., 2015). A comparable calculation on our data results in a larger effect size (SMD=−.27) reflecting fewer drinks per week at follow-up in the +Change condition than in the control condition. Our results also revealed a mean decrease of 2.41 drinks per week for participants assigned to the +Change condition compared to a mean decrease of 1.47 drinks per week in the control condition. This suggests that our findings were consistent with changes found in a meta-analysis of similar interventions. However, our modeling approach accounts for baseline behavior, covariates, and zero-inflation. With a larger sample size, it is likely that significant differences may be detectable. Results may have also been impacted by differences in drinking based on participants’ enrollment period in relation to the COVID-19 pandemic. In fact, alcohol use patterns did change for many during the pandemic (e.g., Dumas et al., 2020) and this was corroborated in our study. We found the enrollment prior to the pandemic was significantly associated with excess zeros in the model and positively related to number of drinks beyond the excess zeros, suggesting more extreme behavior in our sample prior to COVID-19. A higher proportion of participants in the +Change condition were enrolled prior to the start of the pandemic. Thus, changes in drinking due to historical factors may have obscured the effects of the intervention.

Unfortunately, this study was not able to evaluate intervention effects on perpetration as the base rates of sexual assault perpetration in the 3-month follow-up period were too low to allow for any meaningful statistical comparisons. This is not surprising, as this was a pilot study and sexual assault perpetration is a low base-rate behavior. Future research should include a large randomized controlled trial to assess differences in sexual assault perpetration.

Study Limitations

The current study was a pilot randomized control trial of a random sample of college students at a large university. Although the randomization and sampling procedures were a strength of the study design, there are several limitations that are worth noting. First, study recruitment occurred in the context of the COVID-19 pandemic. All participants completed the follow-up surveys during the pandemic, and some enrolled in the study before the pandemic. Additionally, it was not possible to look at differences within the SGM identities due to the small sample size, but future research should examine differences among gay, lesbian, bisexual, and trans populations as there may be differences in +Change efficacy based on identity. Further, future research should examine if +Change is differentially effective across gender identity and sexual orientation separately. It was also a limitation that the alcohol use measure did not have a specific timeframe for alcohol use, but instead assessed the average standard drinks consumed each day of the week, consistent with the validated measure (Collins et al., 1985). Due to the low endorsement of perpetration, it was not possible to conduct analyses on the effect of +Change on perpetration rates. Finally, there were only two time points separated by 3 months in the current study, therefore, future work is needed to assess the long-term impacts of +Change.

Conclusions

This was the first study to tailor alcohol and/or SA programming for SGM students. The current study suggests that tailoring prevention programming based on gender and sexual orientation may be a useful strategy to reducing alcohol use and SA among college students and suggest the need for a larger randomized controlled trial to test the efficacy of +Change. Further, results of this study suggest that integrated programs for alcohol use, SA victimization, perpetration prevention, and bystander intervention may be a viable method to reduce SA on college campuses.

Biographies

Amanda K. Gilmore, PhD, is an associate professor in the Department of Health Policy & Behavioral Sciences in the School of Public Health at Georgia State University as well as the director of the National Center for Sexual Violence Prevention in the Mark Chaffin Center for Healthy Development. Her research focuses on the prevention of alcohol use, sexual assault, and suicide, as well as secondary prevention of substance use and mental health symptoms after sexual assault.

Karen E. Nielsen, PhD, is an assistant professor in the Department of Population Health Sciences in the School of Public Health at Georgia State University. She is a biostatistician and has expertise in multilevel modeling and techniques for modeling time-intensive longitudinal data.

Nashalys K. Salamanca, MA, is a doctoral student clinical-community psychology at Georgia State University. Her research interests are to apply an intersectional and ecological framework to the treatment and prevention of interpersonal violence.

Daniel W. Oesterle, MS, is a clinical psychology doctoral student and a Frederick N. Andrews Fellow within the Department of Psychological Sciences at Purdue University. Daniel’s work is focused on examining risk factors for sexual assault, intimate partner violence, and aggression.

Anushka Parekh, BS, received her BS in neuroscience at Georgia State University and is now a medical student at VCOM Carolinas.

Ruschelle M. Leone, PhD, is an assistant professor in the Department of Health Policy and Behavioral Sciences and the Mark Chaffin Center for Healthy Development within the School of Public Health at Georgia State University. Her research focuses on informing and developing intervention programming to reduce alcohol misuse and interpersonal violence.

Lindsay M. Orchowski, PhD, is a staff psychologist with Lifespan Physicians Group and Professor (Research Scholar) in the Department of Psychiatry and Human Behavior at The Warren Alpert Medical School of Brown University. Her research focuses on the prevention and intervention for sexual assault across the lifespan.

Viswanathan Ramakrishnan, PhD, is a professor in the Department of Public Health Sciences at the Medical University of South Carolina. He is a biostatistician with expertise in clinical trials.

Debra Kaysen, PhD, is a clinical psychologist, and a professor in the Department of Psychiatry & Behavioral Sciences at Stanford University. Her area of specialty both in research and clinical work is in the care of those who have experienced traumatic events including treatment of PTSD and comorbid disorders. Her body of research is notable for the inclusion of underserved populations such as research with Native Americans, sexual minorities, and individuals in low- and middle-income countries.

Kelly Cue Davis, PhD, is a professor at Arizona State University as well as a licensed clinical psychologist. Dr Davis researches the effects of alcohol and drug consumption on sexual violence victimization and perpetration, sexual risk, and sexual health. She has served as Principal Investigator or Co-Investigator on several research projects related to sexual violence and sexual risk, with grant funding from the National Institutes of Health and Department of Defense totaling over $40 million, including the prestigious NIH MERIT award.

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