Evaluation of a Social Norms Sexual Violence Prevention Marketing Campaign Targeted Toward College Men: Attitudes,Beliefs,and Behaviors Over 5 Years

Abstract

The article evaluates the effectiveness of a 5-year social norms sexual violence prevention marketing campaign designed specifically for men on a large public university in the Southeastern United States. From 2010 through 2014, 4,158 men were asked about their self-reported attitudes, beliefs, and behavior related to sexual violence as well as their perception of their peers’ attitudes, beliefs, and behaviors. Using social norms theory, a social norms marketing campaign was developed to target highly discrepant attitudes, beliefs, and behaviors. Results indicate that both self-reported and perception of peer attitudes and beliefs improved over time, and the discrepancy between the two reduced over time. In addition, the frequency of positive and prosocial self-reported behavior increased on five of the six indicators. This study represents a significant contribution to the literature, as it uses 5 years of data and includes behavioral indicators to add evidence for the efficacy of targeting misperceptions of social norms as a mechanism to engage men in gender-based violence prevention.

Keywords

sexual assault prevention anything related to sexual assault

Introduction

Campus sexual assault occurs at epidemic rates. Student surveys indicate that nearly half of all college women experience some form of sexual aggression during their matriculation, with a quarter indicating that they experienced an attempted or completed rape (Bradley, Yeater, & O’Donohue, 2009). An additional one in 20 men report rape or sexual assault during college (Cantor et al., 2015). One out of every 13 college men, on the contrary, reports having sexually assaulted a woman and more than a third of college men indicate that they would coerce a woman into having sex with them if they were assured that they would not get caught (Bradley et al., 2009). Despite decades of awareness and the implementation of thousands of campus-based sexual assault prevention programs, the rate of sexual assault on campus has been virtually unchanged for more than 50 years (Jozkowski, 2015). The purpose of this article is to evaluate the effectiveness of an innovative social norms marketing campaign implemented over a 5-year period designed to engage men in sexual violence prevention on a large public university campus in the Southeastern United States.

Literature Review

Approaches to Reducing Sexual Assault

Historically, college men were conceptualized as an audience for campus-based rape prevention programs in a limited way, teaching them about the boundaries of sexual consent and providing education to reduce their sexual aggression (Berkowitz, 2010; Davis, 2000; Fabiano, Perkins, Berkowitz, Linkenbach, & Stark, 2003). In reaction to these limitations, the sexual assault prevention field has made several innovative advances to proactively and positively engage both male and female audiences, with promising reductions in sexual violence (e.g., Edwards, 2006; Flood, 2006, 2011; Gibson, 2014). Bystander intervention has supplanted victim-centered sexual assault prevention, underscoring that the victim and perpetrator are not the only actors in the majority of violent acts and a greater awareness has been placed on the importance of social norms and cultural context in fostering environments which overtly or covertly condone sexual aggression and sexual violence.

Social Norms and Sexual Violence Prevention

The Centers for Disease Control and Prevention (CDC) recommend grounding sexual violence prevention more concretely in the ecological model (Basile et al., 2016; Casey & Lindhorst, 2009). Included in this shift is an emphasis on changing social norms to promote a culture that does not tolerate violence. When applied to the college population, research indicates that college men tend to overestimate their male peers’ adherence to rape myths (e.g., erroneous beliefs about the causes of sexual assault and stereotyped notions of both victims and perpetrators), underestimate their peers’ discomfort with sexually degrading or sexually inappropriate language and behavior toward women and their willingness to intervene when such language and behavior are encountered, and overestimate their peers’ willingness to use force to obtain sex (Berkowitz, 2003, 2004; Fabiano et al., 2003; Harvey, Garcia-Moreno & Butchart, 2007; Kilmartin et al., 2008; Lee, Guy, Perry, Sniffen, & Mixson, 2007). These problematic attitudes and beliefs are associated with both the perpetration of sexual assault (Thompson, Koss, Kingree, Goree, & Rice, 2011) and hesitancy in engaging in bystander intervention (Berkowitz, 2002).

Social norms approaches present an opportunity to engage men in efforts to reduce gender-based violence by challenging misperceptions related to sexual aggression and bystander intervention behavior (Berkowitz, Lederman, & Stewart, 2005). The goal of this type of intervention is to identify the actual norms related to sexual aggression and bystander intervention behavior and reinforce the positive, prosocial norm by marketing the norm to students. A number of evaluations support the efficacy of this type of intervention. This includes short-term successes of poster programs like Know Your Power (Potter, Moynihan, & Stapleton, 2011; Potter, Moynihan, Stapleton, & Banyard, 2009) which are associated with increases in willingness to take action and actually taking more action during concerning situations (Perkins, Craig, & Perkins, 2011). Short-term simple pretest/posttest design poster campaigns appear to produce an increase in willingness to intervene (Katz, Olin, Herman, & DuBois, 2013), and the impact of social norms programming has had positive results in gender homogeneous dormitory settings (Gidycz, Orchowski, & Berkowitz, 2011). Social norms messaging is also an integral component of several multifaceted sexual violence prevention programs that have demonstrated effectiveness (e.g., Mentors in Violence Prevention; Katz, Heisterkamp, & Fleming, 2011), although researchers caution that the individual components or ingredients of these programs cannot be isolated (Banyard, 2014). Although promising, these evaluations are limited in their short-term follow-up and lack of behavioral indicators (World Health Organization, 2009).

Purpose

The purpose of this investigation is to evaluate the effectiveness of a 5-year social norms sexual violence prevention marketing campaign designed for men on a large public university campus in the Southeastern United States. Specifically, we explore the following research questions and test the following hypotheses:

Research Question 1: Do college men’s perception of peer attitudes and beliefs related to sexual aggression and bystander intervention behavior become more positive and prosocial during the intervention?

Hypothesis 1: Compared with Year 1, perception of peer attitudes and beliefs will be more positive and prosocial in Years 2, 3, 4, and 5.

Research Question 2: Do college men’s self-report attitudes and beliefs related to sexual aggression and bystander intervention become more positive and prosocial during the intervention?

Hypothesis 2: Compared with Year 1, self-report attitudes and beliefs related to sexual aggression and bystander intervention behavior will be significantly more positive and prosocial in Years 2, 3, 4, and 5.

Research Question 3: Is the intervention associated with reductions in discrepancies between (a) self-report attitudes and perception of peer attitudes and (b) self-report beliefs and perception of peer beliefs among college men?

Hypothesis 3a: Compared with Year 1, the discrepancy score between self-report attitudes and perception of peer attitudes will be smaller in Years 2, 3, 4, and 5.

Hypothesis 3b: Compared with Year 1, the discrepancy score between self-report beliefs and perception of peer beliefs will be smaller in Years 2, 3, 4, and 5.

Research Question 4: Does the frequency of positive and prosocial self-reported behavior related to sexual aggression and bystander intervention increase for college men during the intervention?

Hypothesis 4: Compared with Year 1, the frequency of positive and prosocial self-reported behavior will be higher in Years 2, 3, 4, and 5.

Method

Social Norms Sexual Violence Prevention Marketing Campaign

A social norms sexual violence prevention marketing campaign was developed and implemented at a large university in the Southeast United States. Data about self-reported and perception of peers’ attitudes, beliefs, and behaviors were collected from male students each spring semester from 2010 to 2014 (see “Instruments” section for more detail). Each year the social norms marketing campaign focused on four overarching themes: consent, bystander, rape myths, and sexual activity. The consent theme reinforced the message, “Most men understand the importance of getting consent before sexual intimacy.” The bystander theme reinforced the message, “Most men would intervene to prevent sexual harassment or sexual assault.” The rape myths theme used underscored the message, “Most men agree that blaming sexual assault victims is wrong.” Finally, the sexual activity theme reinforced the message that “Most men are not as sexually active as you might think.”

Normative data for each theme each year were pulled from the survey disseminated the prior spring semester. The intervention focused on misperceptions of attitudes and beliefs related to sexual aggression and bystander intervention behavior in accordance with social norms theory (Berkowitz et al., 2005). Each year two to three advertisements were developed. Posters, bus wraps, table tents, and billboards were placed around campus with a branded logo and catchy designs (contact the first author for an example). Members of the research team worked with students majoring in Mass Communication to develop messaging and media to ensure the advertisement was relevant and accessible to the intended audience. Campaign messages were marketed back to students the fall semester following data collection. For example, in 2012, survey data indicated that although 95% of men agreed or strongly agreed that that it was important to get consent before sexual intimacy, they perceived that only 76% of their peers agreed or strongly agreed that consent prior to intimacy was important. A visually appealing social norms marketing campaign read, “Most men understand the importance of getting consent before sexual intimacy.” This statement was advertised across campus and in the larger university community frequented by students.

Procedures

Data were collected using an online survey hosted by Qualtrics and disseminated to a random sample of male students enrolled at a large public university campus in the Southeastern United States. The survey took approximately 20 min to complete. The survey was delivered annually in the spring semester from 2010 to 2014. The survey remained open for 3 weeks each spring semester and a total of three reminders were sent to students who had not yet completed the survey. All data were anonymized through Qualtrics to protect the identity of respondents. Incentives were available and included 15 gift cards in the amount of US$50 raffled off to survey completers after the data collection window closed. All procedures were approved by the university Institutional Review Board.

Sample

A random sample of male students was identified in conjunction with university Office of Institutional Research every year. Eligible potential participants were identified as male in official university records and were enrolled in campus-based graduate or undergraduate programs during that spring semester. Potential participants were excluded if they were enrolled exclusively in distance learning courses that semester (and therefore did not live or study on campus) or were below the age of 18. A total of 3,000 students were sampled each year, yielding a sampling frame of 15,000 students over the five waves of data collection. This represented 21.5% to 22.8% of the total eligible male population (the total number of eligible males was 13,167 in Year 1; 13,525 in Year 2; 13,675 in Year 3; 13,837 in Year 4; and 13,925 in Year 5). A total of 4,158 students completed the survey, resulting in a 5-year response rate of 28%. Response rates varied by year: Year 1 = 30.1%, Year 2 = 24.5%, Year 3 = 26.0%, Year 4 = 33.1%, and Year 5 = 24.9%.

Demographic characteristics of the sample are presented in Table 1. The average age of the sample was 20.2 years (SD = 2.0). Across all five waves of data collection, the majority of respondents identified as heterosexual (91%) and were living off-campus (71%). The modal racial category was non-Hispanic White (69%) and students most often identified as seniors (34%), although freshman, sophomores, and juniors were well represented. The χ² tests were used to compare sample demographics with population demographics by year on race and grade in school. The sample was significantly different from the population on grade in school, but not on racial distribution. Specifically, freshmen were underrepresented in Year 1, but overrepresented in the 4 intervention years.

Table 1.

Demographics.

	n
Year	(n = 4,158)	%
2010	902	21.7
2011	734	17.7
2012	780	18.8
2013	994	23.9
2014	748	18.0
Grade in School^a	(n = 4,129)		2010^b	2011^b	2012^b	2013^b	2014^b
Freshman	828	20.1	9.0	18.2	27.8	21.2	25.1
Sophomore	646	15.6	11.9	19.8	16.8	15.5	15.4
Junior	1,226	29.7	38.3	25.6	26.2	27.4	30.6
Senior	1,413	34.2	40.8	36.5	29.3	35.2	28.9
Graduate student	6	.1
Other	10	.2
Race/Ethnicity^c	(n = 4,118)		2010	2011	2012	2013	2014
African American	268	6.5	7.1	8.2	6.9	7.0	6.2
White non-Hispanic	2,847	69.1	77.2	75.5	74.9	73.0	74.0
Hispanic	685	16.6	15.7	16.3	18.2	7.0	19.7
Asian Pacific Islander	151	3.7
Other	167	4.1
Living Arrangement	(n = 4,125)
Live on-campus	1,155	28.0
Live off-campus	2,970	72.0
Sexual Orientation	(n = 4,122)
Heterosexual	3,778	90.9
Bisexual	105	2.5
Gay	225	5.4

Due to limitations in data provided by the university, only freshmen, sophomores, juniors and seniors were compared.

Sample distribution significantly different from population distribution using a χ² test at p < .05.

Due to limitations in data available from the university, only African American, White non-Hispanic, and Hispanic men were compared.

Instruments

A multidimensional survey was created for this project based on the attitudes, beliefs, and behavior correlated with sexually aggressive and bystander intervention behavior. The three domains included the following: (a) Attitudes toward victims of sexual violence and individuals who engage in bystander intervention behavior, (b) Beliefs in rape myths, and (c) Behavior related to both sexual aggression and bystander intervention. All items were rated twice. First, student’s own attitudes, beliefs, and behavior were measured (i.e., self-report). Then, students were asked to gauge their impression of their peers’ attitudes, beliefs, and behavior (i.e., perception of peer).

Attitudes

Three sets of items assessed attitudes toward victims of sexual violence and individuals who engage in bystander intervention behavior. The three sets of items were “I/Most male students would believe someone who reported being abused, sexually assaulted, or stalked,” “I/most male students would respect someone who reported being abused, sexually assaulted, or stalked,” and “I/most male students would admire someone who intervened to prevent abuse, sexual assault, or stalking.” Response options were 1 = strongly disagree, 2 = disagree, 3 = no opinion, 4 = agree, and 5 = strongly agree. For all items, higher scores indicated more positive attitudes. For the social norms marketing campaign development, discrepancy scores on individual items were calculated (i.e., frequency of agree/strongly agree for self-report vs. agree/strongly agree for peer perception). To evaluate the effectiveness of the intervention, mean scores on each domain were calculated. The attitudes domain demonstrated acceptable internal consistency (Cronbach’s α = .76 for the self-report; α = .82 for the perception of peer subscale).

Beliefs

Eleven items adapted from the Illinois Rape Myth Acceptance Scale (Payne, Lonsway, & Fitzgerald, 1999) assessed beliefs about the causes, victims, and consequences of sexual violence (i.e., endorsement of rape myths). Response options were 1 = strongly disagree, 2 = disagree, 3 = no opinion, 4 = agree, and 5 = strongly agree. Items included “If a woman is raped while she is drunk, she is at least somewhat responsible for letting things get out of control,” “Rapes are usually committed by strangers,” and, “It is only women who dress suggestively that are raped.” For all items, higher scores indicated greater endorsement of rape myths. For the social norms marketing campaign development, discrepancy between agree/strongly agree endorsement was compared for self-report and peer perception of individual items. To evaluate the effectiveness of the intervention, mean self-report and perception of peer scores were computed and compared. The beliefs domain demonstrated excellent internal consistency (α = .97 for the self-report scale; α = .99 for the perception of peer scale).

Behavior

Six items assessed behavior related to both sexual aggression (three items) and bystander intervention (three items). Response options were 1 = never, 2 = rarely, 3 = occasionally, 4 = frequently. For self-report items, students were also given a response option of “have not been in that situation.” Sexual aggression items were “I/most male students stopped sexual activity when asked to, even when you/they were already aroused,” “I/most male students stopped the first time your/their date said no to sexual activity,” and “I/most male students got consent before sexual intimacy.” Bystander intervention items were “I/most male students indicated your/their disapproval when you heard sexist comments,” “I/most male students intervened when you/they witnessed someone ‘hitting on’ a person, when you/they know that person didn’t want it,” and “I/most male students intervened when you/they witnessed a situation in which it looked like a female would end up being taken advantage of.”

For the social norms marketing campaign development, the discrepancy between the self-reported frequencies of each item were compared with the peer perception frequency (i.e., the frequency that the response option “frequently” was endorsed). To evaluate the effectiveness of the intervention, mean self-report frequency scores were computed for individuals who reported being in each situation, where higher scores indicated more positive/prosocial behavior. Each item was treated as a unique dependent variable and analyses were limited only those individuals who self-reported being in each situation, with the total n for each behavior question ranging between 273 and 728. As behaviors do not represent a latent construct, a reliability coefficient was not computed.

Analytic Plan

Anonymized responses were imported from Qualtrics directly into SPSS, version 22, for analysis. One-way between subjects ANOVAs were used to compare Year 1 with each of the 4 intervention years on the mean scores of outcome variables. ANOVAs assume random, independent samples from the population, normally distributed dependent variables, and equal variances. Assumptions were checked for each outcome variable and no violations were evident. Tukey HSD (honest significant difference) tests were used for post hoc comparisons, comparing Year 1 scores with scores in follow-up years. Results were considered significant if the p value fell below .05. Missing data were handled using casewise deletion. If the participant did not offer a response on the dependent variable under investigation, they were excluded from the analysis of that dependent variable. No more than 1.06% of data were missing for any dependent variable in any given year. See Tables 2, 3, and 4 for specific amounts of missing data for each dependent variable by year.

Table 2.

Descriptive Statistics for Attitude Outcome Variables.

	Self-Report			Perception of Peer			Discrepancy
	n	M	SD	n	M	SD	n	M	SD
Year 1	884	4.42	0.59	884	3.77	0.83	884	0.66	0.80
Year 2	719	4.41	0.62	716	3.82	0.79	711	0.59	0.86
Year 3	776	4.50	0.62	772	3.98^a	0.80	770	0.52^a	0.74
Year 4	893	4.52^a	0.56	898	3.97^a	0.80	886	0.55^a	0.75
Year 5	737	4.49	0.58	738	3.89^a	0.85	730	0.60	0.88

Significantly different from Year 1 at p < .05.

Table 3.

Descriptive Statistics for Belief Outcome Variables.

	Self-Report			Perception of Peer			Discrepancy
	n	M	SD	n	M	SD	n	M	SD
Year 1	878	2.23	0.70	857	3.05	0.79	844	0.77	0.72
Year 2	713	2.23	0.73	696	2.95	0.87	695	0.73	0.78
Year 3	754	2.16^a	0.72	753	2.82^a	0.89	748	0.67^a	0.78
Year 4	848	2.17^a	0.78	827	2.74^a	0.90	819	0.58^a	0.81
Year 5	737	2.15^a	0.76	735	2.78^a	0.92	724	0.64^a	0.84

Significantly different from Year 1 at p < .05.

Table 4.

Descriptive Statistics for Behavior Outcome Variables.

	Stopped When Asked After Arousal			Got Consent Before Sexual Intimacy			Stopped the First Time Date Said No			Voiced Disapproval of Sexism			Intervened—Taken Advantage			Intervened—Unwanted “Hitting on”
	n	M	SD	n	M	SD	n	M	SD	n	M	SD	n	M	SD	n	M	SD
Year 1	374	3.04	0.93	666	3.76	0.66	375	3.46	0.80	728	2.26	0.86	483	2.62	0.92	589	2.25	0.88
Year 2	307	3.05	1.02	507	3.81	0.61	306	3.46	0.90	574	2.24	0.93	344	2.56	0.98	427	2.23	0.93
Year 3	310	3.29^a	0.89	579	3.84^a	0.55	350	3.60^a	0.70	623	2.40^a	0.90	356	2.79	0.97	480	2.29	0.96
Year 4	372	3.25^a	0.93	652	3.85^a	0.53	409	3.47	0.83	707	2.46^a	0.96	423	2.81^a	0.96	531	2.38	0.96
Year 5	273	3.33^a	0.85	562	3.84^a	0.52	291	3.61^a	0.83	614	2.35	0.93	348	2.69^a	0.92	455	2.35	0.92

Significantly different from Year 1 at p < .05.

Results

Descriptives

Tables 2, 3, and 4 report the means and standard deviations for each dependent variable across years. The mean score for self-report attitudes ranged from a low of 4.41 in Year 2 to a high of 4.52 in Year 4. The perceptions of peer attitudes were lower, ranging from 3.77 in Year 1 to 3.98 in Year 3. The highest discrepancy between self-reported attitudes and perceived attitudes was found in Year 1. The range of self-reported beliefs was from 2.15 in Year 5 to 2.23 in Years 2 and 3. Perception of peer beliefs were higher than self-reported beliefs, ranging from 2.74 in Year 4 to 3.05 in Year 1. Discrepancies between self-reported beliefs and perception of peer beliefs ranged from 0.58 to 0.77. In general, individuals reported engaging in behaviors related to sexual consent more frequently than behaviors related to bystander intervention. The least frequently reported behavior related to sexual activity was in Year 1, with a mean of 3.04 on the “stopped when asked after arousal” item. The behavior that was reported at the highest frequency was “Got consent before sexual intimacy,” with a mean score of 3.85 in Year 4. Comparatively, frequency of bystander intervention behaviors ranged from 2.23 (“intervened—unwanted ‘hitting on’” in Year 2) to 2.81 (“intervened—taken advantage of” in Year 4).

To explore whether grade in school needed to be included as a covariate to control for maturation or to detect cumulative effects, ANOVAs were performed for attitudes and beliefs (Table 5) and behavior (Table 6) outcomes across years by grade in school. There were no significant differences on behavioral outcomes within year between grades in school. Within Year 5, self-reported beliefs for sophomores were lower than self-reported beliefs of juniors, which were higher than self-reported beliefs of seniors. In Year 3, self-reported attitudes of juniors were lower than self-reported beliefs of freshmen. If a cumulative effect existed, we would expect to see significantly lower self-reported beliefs scores, higher self-reported attitudes scores, and greater frequencies of behaviors for seniors in Years 4 and 5 compared with other grades in school within the same intervention year. There was one significant correlation which supported this notion (self-reported beliefs for seniors in Year 5 were significantly lower than self-reported beliefs for juniors in the same year). However, examination of the associations suggests that the significance is rooted in the fact that juniors in Year 5 scored higher, not that seniors scored lower (because the score for seniors in Year 5 is the same as the score for freshmen in Year 5). This was the only potential evidence for a cumulative effect. If a maturation effect existed, we would expect to see higher scores for seniors across all years of the intervention, which were not present.

Table 5.

Attitude and Belief Outcomes by Grade in School.

	Attitudes Self-Report		Attitudes Peer		Attitudes Discrepancy		Beliefs Self-Report		Beliefs Peer		Beliefs Discrepancy
	M	SD	M	SD	M	SD	M	SD	M	SD	M	SD
Freshman
Year 1	4.36	.55	3.57	.83	.80	.92	2.34	.68	3.13	.75	.76	.68
Year 2	4.40	.58	3.88	.82	.51	.92	2.35	.77	2.99	.94	.68	.79
Year 3	4.56	.63	4.06	.79	.51	.66	2.20	.74	2.72	.90	.53	.77
Year 4	4.43	.58	3.91	.77	.52	.73	2.18	.72	2.70	.87	.50	.73
Year 5	4.53	.56	3.94	.88	.60	.88	2.21	.71	2.77	.92	.58	.84
Sophomore
Year 1	4.44	.50	3.79	.76	.64	.83	2.35	.67	3.10	.69	.76	.73
Year 2	4.39	.70	3.80	.81	.59	.86	2.25	.79	3.05	.90	.81	.90
Year 3	4.48	.60	4.01	.77	.48	.75	2.23	.76	2.90	.89	.63	.80
Year 4	4.58	.48	4.07	.81	.51	.76	2.24	.91	2.68	.98	.44	.85
Year 5	4.55	.50	3.89	.77	.66	.65	2.04	.73	2.78	.89	.76	.81
Junior
Year 1	4.43	.58	3.77	.82	.66	.78	2.30	.72	3.09	.84	.80	.67
Year 2	4.49	.50	3.83	.81	.66	.80	2.18	.74	2.90	.86	.73	.75
Year 3	4.42^a	.64	3.94	.76	.48	.72	2.19	.65	2.90	.84	.72	.72
Year 4	4.56	.55	4.01	.77	.55	.72	2.10	.76	2.75	.94	.65	.79
Year 5	4.48	.54	3.87	.85	.61	.95	2.26^b	.79	2.87	.95	.62	.85
Senior
Year 1	4.42	.63	3.80	.86	.62	.80	2.23	.69	2.97	.78	.75	.66
Year 2	4.38	.66	3.80	.75	.58	.86	2.20	.67	2.92	.82	.71	.72
Year 3	4.53	.57	3.93	.87	.60	.80	2.03	.70	2.82	.91	.79	.81
Year 4	4.51	.58	3.93	.80	.58	.78	2.18	.77	2.80	.84	.65	.84
Year 5	4.44	.69	3.87	.77	.57	.91	2.06^c	.76	2.68	.92	.64	.85

Significantly different from Year 3 Freshmen at p < .05.

Significantly different from Year 5 Sophomore at p < .05.

Significantly different from Year 5 Junior at p < .05.

Table 6.

Behavior Outcomes by Grade in School.

	Stopped When Asked After Arousal		Got Consent Before Sex		Stopped the First Time Date Said No		Voiced Disapproval of Sexism		Intervened—Taken Advantage		Intervened—“Hitting on”
	M	SD	M	SD	M	SD	M	SD	M	SD	M	SD
Freshman
Year 1	3.25	0.94	3.78	0.58	3.50	0.81	2.22	0.99	2.76	1.01	2.25	0.97
Year 2	3.09	0.99	3.76	0.70	3.54	0.95	2.25	0.99	2.57	1.11	2.13	1.01
Year 3	3.35	0.92	3.84	0.53	3.61	0.70	2.40	0.85	2.94	0.95	2.32	0.97
Year 4	3.27	0.94	3.88	0.49	3.66	0.61	2.41	0.94	2.80	0.91	2.38	1.00
Year 5	3.33	0.85	3.78	0.64	3.52	0.78	2.27	0.94	2.63	0.99	2.28	0.98
Sophomore
Year 1	3.33	0.94	3.83	0.59	3.51	0.64	2.20	0.88	2.73	0.99	2.22	0.93
Year 2	2.98	1.01	3.85	0.48	3.37	0.93	2.34	0.92	2.59	0.98	2.24	1.00
Year 3	3.35	0.93	3.84	0.54	3.62	0.72	2.51	0.99	2.97	0.95	2.35	1.04
Year 4	3.14	0.98	3.86	0.50	3.55	0.83	2.50	0.93	2.99	0.96	2.45	0.89
Year 5	3.39	0.90	3.38	0.84	3.38	0.84	2.37	0.88	2.78	0.86	2.54	0.86
Junior
Year 1	2.96	0.94	3.77	0.67	3.45	0.84	2.27	0.86	2.59	0.93	2.21	0.92
Year 2	3.06	1.11	3.82	0.64	3.58	0.85	2.24	0.96	2.53	0.99	2.26	0.89
Year 3	3.24	0.86	3.85	0.55	3.53	0.73	2.28	0.86	2.73	0.96	2.25	0.93
Year 4	3.20	0.99	3.84	0.56	3.61	0.69	2.48	1.01	2.81	0.97	2.39	0.99
Year 5	3.32	0.78	3.35	0.90	3.35	0.90	2.39	0.89	2.75	0.89	2.38	0.92
Senior
Year 1	2.96	0.90	3.72	0.68	3.46	0.82	2.27	0.82	2.59	0.86	2.30	0.81
Year 2	3.04	0.97	3.79	0.60	3.39	0.89	2.20	0.89	2.56	0.93	2.24	0.87
Year 3	3.25	0.88	3.85	0.58	3.61	0.68	2.42	0.92	2.63	1.00	2.27	0.96
Year 4	3.32	0.85	3.84	0.54	3.62	0.69	2.45	0.96	2.73	0.96	2.34	0.97
Year 5	3.31	0.89	3.86	0.51	3.53	0.77	2.34	0.98	2.62	0.95	2.26	0.89

Note. There were no significant differences in behavior outcomes by grade in school within each intervention year at p < .05.

Hypothesis 1: Perception of Peer Attitudes and Beliefs

Perception of peer attitudes and beliefs were more positive in later years. There were significant differences in perception of peer attitude scores by intervention year, F(4, 4003) = 11.03, p < .01. Post hoc testing showed that perceived attitudes were significantly higher in Years 3, 4, and 5 when compared with Year 1. See Table 2 and Figure 1 for further detail. There were also significant differences in perception of peer beliefs scores by intervention year, F(4, 3863) = 17.63, p < .01. A Tukey HSD test indicated that perception of peer beliefs in Year 1 were significantly higher compared with perception of peer beliefs in Years 3, 4, and 5. See Table 3 and Figure 2 for more detail.

Hypothesis 2: Self-report Attitudes and Beliefs

Participant’s self-report attitudes and beliefs were more positive in later years (see Tables 2 and 3 and Figures 1 and 2). There were significant differences in self-report attitude scores by year, F(4, 4004) = 4.92, p < .01. Post hoc testing identified that when compared with Year 1, self-report attitudes were significantly higher in Year 4. There were also significant differences in self-report belief scores by intervention year, F(4, 3925) = 4.40, p < .01. A Tukey HSD test indicated that beliefs in Year 1 were significantly higher than beliefs in Years 3, 4, and 5.

Hypothesis 3: Discrepancy Between Self-Report and Perception of Peer

The discrepancy score between self-report and perception of peer attitudes and beliefs decreased in later intervention years. See Figure 1 and Table 2 for attitudes and Figure 2 and Table 3 for beliefs. The discrepancy score between self-report attitudes and perception of peer attitudes differed significantly by year, F(4, 3962) = 3.68, p < .01. A Tukey HSD test indicated that the Year 1 mean discrepancy score was significantly larger when compared with the Year 3 and Year 4 mean discrepancy scores. The discrepancy score between self-report beliefs and perception of peer beliefs also differed significantly by intervention year, F(4, 3805) = 7.54, p < .01. A Tukey HSD test showed that the mean discrepancy score for Years 3, 4, and 5 were significantly smaller when compared with mean discrepancy score for Year 1.

Hypothesis 4: Behavior

With one exception, self-report behavior was more prosocial in later years. See Table 4 and Figure 3 for mean scores on behavior items by intervention year. There were significant differences by year for all three self-report sexual aggression behavior items. “Stopped sexual activity when asked to, even when you were already aroused,” F(4, 1631) = 7.26, p < .01; “Got consent before sexual intimacy,” F(4, 2961) = 3.15, p < .01; and “Stopped the first time your date said no to sexual activity,” F(4, 1726) = 3.80, p < .01. Post hoc analysis using the Tukey HSD test revealed that when compared with Year 1, mean frequency scores in Years 3, 4, and 5 were significantly higher on the “Stopped when asked after arousal” and “Got consent before sexual intimacy” items; likewise, when compared with Year 1, frequency scores were significantly higher in Years 3 and 5 for the “Stopped the first time date said no” item.

There were significant differences by intervention year for two out of three bystander intervention behavior self-report items. “Indicated your disapproval when you heard sexist comments,” F(4, 3241) = 6.48, p < .01; and “Intervened when you witnessed a situation in which it looked like a female would end up being taken advantage of,” F(4, 1949) = 4.99, p < .01. Post hoc analysis using the Tukey HSD test indicated that when compared with Year 1, mean frequency scores in Years 3 and 4 were significantly higher on the “Voiced disapproval of sexism” item. In addition, when compared with Year 1, mean frequency scores in Years 4 and 5 were significantly higher on the “Intervened—taken advantage” item. There were no significant differences by year on the “Intervened—unwanted ‘hitting on’” item.

Discussion

The goal of this social norms marketing campaign intervention was to increase college men’s positive and prosocial attitudes, beliefs, and behavior related to sexual aggression and bystander intervention by changing the perception of the norms on campus. The intervention targeted men’s own attitudes, beliefs, and behavior as well as their perception of their male campus peers’ attitudes, beliefs, and behavior. Results from the current analyses suggest that the social norms marketing campaign intervention was successful. Over 5 years of data collection, men’s perception of their peer’s attitudes and beliefs improved, the discrepancy between perceptions and self-report decreased, and their own beliefs (more so than attitudes) improved. That is to say, perception of the norm became closer to the actual norm, while at the same time, the actual norm improved. In addition to gains on measures of both self-reported beliefs and perception of peer attitudes and beliefs, men’s self-reported behavior also improved throughout the course of the intervention. Men reported sexually aggressive behavior less frequently during later years of the intervention, and indicated that they engaged in bystander intervention behavior more frequently.

A strength of this study is the repeated cross-sectional survey design and 5-year data collection window. These features of the methodology allowed us to track men’s social norms related to sexual aggression and bystander intervention behavior over time. As the overarching goals of the social norms marketing campaign intervention were to identify existing social norms related to sexual aggression, shift behavior to become increasingly prosocial over time, and change the culture of an entire college campus in relation to sexual violence, it is important to note that the point-in-time counts presented reflect the attitudes, beliefs, and behavior of college men, and do not track individuals behavior over time.

No significant differences were observed between Years 1 and 2. This finding is important as the majority of social norms intervention studies focus on immediate outcomes (pre–post) or examine outcomes at 1 year postintervention. Results from the current study suggest that the effects of social norms marketing campaign interventions are time-delayed and nonlinear. Statistically significant changes in attitudes, beliefs, and behavior were not detected until Year 3. The fact that some attitudes, beliefs, and behaviors become nonsignificant during Year 5 may be explained by an on-campus sexual assault case involving university athletics which made the national news. This case produced a chilling effect and changed the narrative about how sexual violence was defined and described. It is possible that the social norms related to sexual aggression and student’s behavior became worsened in Year 5 as a result of this abrupt, but powerful culture shift.

The changes noted in men’s self-reported and perception of peer attitudes were less robust than changes observed for the beliefs domain. Men’s perception of peer endorsement of rape myths moved from the “no opinion” range into the “disagree” range. Self-reported attitudes were maintained over time in the “agree” response range, although perception of peer attitudes failed to crest the “no opinion” response range. One of the bystander intervention behavior items (i.e., whether a student would intervene when they witnessed someone “hitting on” a person they knew didn’t want it) did not significantly change over time. Making gains on this behavior may require more nuanced bystander intervention training to build student’s skills in recognizing potentially dangerous situations, identifying the appropriate intervention strategies, and reducing the perception of barriers to action. These skills are beyond the scope of a stand-alone social norms marketing campaign intervention.

Limitations

Several limitations warrant cautious interpretation of the results. First and foremost, there was not a no-treatment control or comparison group for analysis. The lack of a comparison group hampers our ability to confidently conclude that the reported increases in attitudes, beliefs, and behavior related to sexual aggression and bystander intervention on a large public university campus in the Southeastern United States results were due to the social norms marketing campaign intervention. In addition, there is a threat of dependence. Although each year’s sample was treated as independent, there is a potential that some individuals were sample multiple times. The threat of maturation limits our attempt to establish a relationship between the intervention and the reported outcomes. Although there is no evidence of maturation by grade in school within this sample, it is possible that attitudes, beliefs, and behavior would have improved over time regardless of the intervention due to the increased awareness about sexual violence on college campuses across the country. In addition, the results cannot causally be solely attributed to this specific intervention, as other interventions could have been happening across campus or in the local community concomitantly which contributed to the improvements. Because the changes are not linear, it is possible that improvements between years represent a particularly effective campaign year.

The sample was majority White and heterosexual, which limits the generalizability of the findings to more diverse institutions. In addition, it is possible that the findings are attributable to sampling and response rate issues. For example, there were no significant differences on the outcome variables between Year 1 and Year 2, and Year 2 also had the lowest response rate. Furthermore, Years 2, 3, 4, and 5 had disproportionately high respondents from the freshmen grade, which could explain why significant differences were detected those years, as freshmen may be more positive and prosocial than upperclassmen.

Implications for Research and Practice

The implementation and evaluation of the social norms sexual violence prevention marketing campaign both indicate implications for future research and practice. The ultimate goal of any campus-based sexual violence prevention program is to prevent sexual assault. Therefore, it is important to note that even the incremental changes reported in the current evaluation have tangible, meaningful consequences for human lives. Current trends in sexual violence prevention research and practice suggest pairing social norms marketing campaigns with skills-based training component for men in the target population. Unfortunately, a comprehensive skills-based training was not implemented or measured in tandem with the social norms marketing campaign. Skills-based training designed to reduce sexually aggressive behavior and increase bystander intervention may represent the essential complement to a campus-based social norms marketing campaign to prevent sexual violence. Although many campuses do not have the resources to deliver skills-based training to large cohorts of students, we suggest integrating skills-based training wherever possible. For example, recruiting student ambassadors (e.g., leaders of student organizations and social clubs) to serve as trainers for more homogeneous groups of students would likely be more feasible and may also increase student participation and buy-in more broadly.

Based on our analysis of the collected data, we have several suggestions to ensure that the data collected and the campus context are represented as completely as possible. The survey emailed to men on campus asked them to reflect on their perception of the frequency with which their peers’ engaged in a range of behavior. However, it may be more useful to ask men how many (or what percent) of their peers they believe are engaging in sexually aggressive or bystander behavior. In addition, it is extremely difficult to isolate the true effects of a social norms marketing campaign from the potential effects of a range of other campus- and community-based sexual violence prevention efforts. When implementing a campaign and evaluation, care should be taken to be apprised of relevant educational and activist-oriented activities, and to keep track of cases of sexual violence (both on campus and in the national news) which may intersect with the outcomes of interest. Future research could explore the impact of the campus, regional, and national environmental context on interventions, which could influence their effectiveness. Integrating students from a range of campus-based leadership and service organizations into the design, implementation, and evaluation of a social norms marketing campaign may increase the effectiveness of the campaign as well as foster longer term culture shifts on sexually aggressive and bystander attitudes, beliefs, and behavior.

Finally, objective and long-range measures of behavior should be integrated into the evaluation process whenever possible. It is of vital importance that changes in both self-report and perception of peer attitudes and beliefs (and the discrepancies therein) are linked to behavior to estimate whether a campus-based social norms marketing campaign is correlated to decreased incidence and prevalence of sexually aggressive behavior and increased bystander intervention on college campuses. Although there are issues with underreporting sensitive information via self-report data collection procedures due to both selection and social desirability bias, this information is critical to measuring culture shifts and identifying gaps. Likewise, administrative data and official reporting statistics on the incidence and prevalence of campus-based sexual assault are also biased and limited to incidents which surpass a legal threshold and therefore become reportable. However, as these data represent the safety and wellness of our students, they should be integrated and examined to better describe the state of sexual violence on campuses. Campus climate surveys may also be linked to social norms marketing campaign evaluation efforts to assess whether observed differences in standardized measures are perceptible to students more broadly and are resulting in positive behavior change.

Conclusion

Results from this research suggests that social norms marketing campaigns can be used to positively engage men in violence prevention. Men have historically been left out of the conversation or erroneously blamed for the bad behavior of a select few problematic men. This research suggests there is utility in positively and proactively engaging men in primary prevention campaigns using social norms theory. Specifically, reinforcing actual norms related to their own positive and prosocial attitudes, beliefs, and behaviors can influence their perception of their peers’ and ultimately improve their own attitudes, beliefs, and behaviors. Although the resulting shifts may not be monumental, culture change is incremental. This type of intervention appears to be useful and could supplement other forms of prevention and intervention.

Footnotes

Acknowledgments

This project would not have been possible without the tireless efforts of the Principal Investigator, Richard Howell for the Florida Center from Prevention Research. In addition, contributions from social work students Lindsey MacConnie and Amy Belekas were essential in the early stages of manuscript development.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Implementation of this intervention was made possible with funds provided by the Florida Department of Health through the Rape Prevention Education program of the Centers for Disease Control and Prevention.

Author Biographies

Annelise Mennicke is an assistant professor in the School of Social Work at the University of North Carolina at Charlotte.

Stephanie C. Kennedy is an assistant professor at the School of Social Work at the University of Connecticut.

Jill Gromer is an independent researcher and a member of the BCE.

Mara Klem-O’Connor is a BSW graduate of the School of Social Work at the University of North Carolina at Charlotte.

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