Annotated bibliography
Research Article
Testing a Model of How a Sexual Assault Resistance Education Program for Women Reduces Sexual Assaults
Charlene Y. Senn 1,2
, Misha Eliasziw 3 , Karen L. Hobden
1 , Paula C. Barata
4 ,
H. Lorraine Radtke 5 , Wilfreda E. Thurston
6 , and Ian R. Newby-Clark
4
Abstract The Enhanced Assess, Acknowledge, Act (EAAA) program has been shown to reduce sexual assaults experienced by university students who identify as women. Prevention researchers emphasize testing theory-based mechanisms once positive outcomes related to effectiveness are established. We assessed the process by which EAAA’s positive outcomes are achieved in a sample of 857 first year university students. EAAA’s goals are to increase risk detection in social interactions, decrease obstacles to risk detection or resistance with known men, and increase women’s use of effective self-defense. We used chained multiple mediator modeling to assess the combined effects of the primary mediators (risk detection, direct resistance, and self-defense self-efficacy) while simultaneously assessing the interrelationships among the secondary mediators (perception of personal risk, belief in the myth of female precipitation, and general rape myth acceptance). The hypothesized multiple mediation model with three primary mediators met the criterion for full mediation of the intervention effects. Together, the mediators accounted for 95% and 76% of the reductions in completed and attempted rape, respectively, demonstrating full mediation. The hypothesized secondary mediators were important in achieving improvements in personal and situational risk detection. The findings strongly support the benefit of cognitive ecological theory and the Assess, Acknowledge, Act conceptualization underlying EAAA. This evidence can be used by administrators and staff responsible for prevention policy and practice on campuses to defend the implementation of theoretically grounded, evidence-based prevention programs. Online slides for instructors who want to use this article for teaching are available on PWQ’s website at http://journals.sagepub.com/doi/suppl/10.1177/0361684320962561
Keywords sexual assault, sexual violence, prevention, resistance, women
For at least 40 years, people and communities affiliated with
feminist, health, and educational organizations and institu-
tions have been working to prevent sexual assault (e.g.,
Morrison et al., 2004; Women Against Rape, 1980), and since
the early 2000s, there has been increased interest in
evidence-based program development and evaluation to rig-
orously assess interventions’ successes and failures. Much of
this work has been accomplished on university campuses.
A number of qualitative and quantitative review articles and
meta-analyses have summarized the state of the field and
made recommendations for promising directions for aca-
demics and practitioners (Basile et al., 2016; DeGue et al.,
2012; DeGue et al., 2014; Ellsberg et al., 2015; Gidycz et al.,
2002; Lonsway et al., 2009; Schewe, 2002). As well, promi-
nent researchers have called for resources to be focused on
evidence-based, theory-driven, effective programs within a
comprehensive approach to sexual violence prevention
(e.g., Banyard, 2013; Banyard & Potter, 2017; Orchowski
et al., 2010; Orchowski et al., 2018). This approach includes,
and extends beyond, student programming to changing entire
campuses and communities. Included in current recommen-
dations by a consortium of independent sexual violence pre-
vention researchers and the Centers for Disease Control are
bystander-based interventions for students of all genders,
resistance education for female students, and continued
development of programming for male students related to a
1 Department of Psychology, University of Windsor, Ontario, Canada 2 Women’s and Gender Studies Program, University of Windsor, Ontario,
Canada 3 Department of Public Health and Community Medicine, Tufts University,
Boston, MA, USA 4 Department of Psychology, University of Guelph, Ontario, Canada 5 Department of Psychology, University of Calgary, Alberta, Canada
6 Department of Community Health Sciences, University of Calgary, Alberta,
Canada
Corresponding Author:
Charlene Y. Senn, Department of Psychology, University of Windsor,
401 Sunset Avenue, Windsor, Ontario, Canada N9B 3P4.
Email: [email protected]
Psychology of Women Quarterly 2021, Vol. 45(1) 20–36 ª The Author(s) 2020
Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0361684320962561 journals.sagepub.com/home/pwq
bystander and social norms education (Basile et al., 2016;
Orchowski et al., 2018).
These opinions are strongly supported by the prevention
science literature (e.g., Nation et al., 2003), where it has long
been recommended that all prevention work be comprehen-
sive in having multiple interventions targeted for different
audiences within a system and use prevention best practices
(e.g., include opportunities for active interaction and appli-
cation of skills). Researchers in academia and public health
have also recommended improvements to evaluation research
in order to answer more precise questions about what
works and why (Banyard et al., 2014; DeGue et al., 2014;
Orchowski et al., 2018). Published standards for reporting
randomized and nonrandomized evaluation trials (Des Jarlais
et al., 2004; Schulz et al., 2010) and calls for better reporting
of interventions so that they can be understood and imple-
mented with findings replicated and improved upon by others
(e.g., Hoffmann et al., 2014; Pinnock et al., 2017) have also
emerged. Specifically, within the sexual violence prevention
field, researchers have argued for more rigorous studies that
would allow the testing of theory-based mechanisms once
positive outcomes related to their effectiveness are estab-
lished (e.g., Norris et al., 2018).
Salazar et al.’s (2019) recent analysis of the mechanisms
for change in the RealConsent program for university men is
a good example of such an analysis. While high attrition in
the follow-up period and the short duration of the positive
outcomes make the authors’ conclusions tentative, it is an
important first attempt to understand how a theory-based
sexual assault program works. To our knowledge, no studies
of sexual assault resistance education programs for university
women have assessed the process by which positive out-
comes are achieved (Senn et al., 2018), despite increasing
calls for such analyses (Hollander, 2018; Norris et al.,
2018). This is our goal.
The current article focuses on the first author’s
Enhanced Assess, Acknowledge, Act (EAAA) sexual
assault resistance education program, which is also known
as the Flip the Script TM
program. EAAA is the only pro-
gram that in a randomized controlled trial (RCT) has been
shown to substantially reduce the sexual assaults that
women university students experienced over the subsequent
year (i.e., 50% reduction in attempted and completed rape as well as reductions in other forms of sexual assault;
Senn et al., 2015). In fact, positive outcomes occur for at
least 2 years (Senn et al., 2017). A few empowerment
self-defense or risk reduction programs for women have
also demonstrated positive sexual assault outcomes. Specif-
ically, assessment of a 30-hour empowerment self-defense
program using a quasi-experimental design indicated signif-
icant reductions in sexual victimization for college women
for at least 1 year after participating in the program
(Hollander, 2014). A shorter, 7.5-hour risk reduction pro-
gram, evaluated using an experimental design, also led to
significant reductions in sexual victimization for subsets of
college women who participated in the program for a few
months (e.g., Gidycz et al., 2006; for a review of theory and
evidence for the type of program more generally, see
Orchowski & Gidycz, 2018). Thus, the benefits of under-
standing how these types of programs work extend beyond
a single program.
We were ideally situated to provide answers to this ques-
tion for many reasons. EAAA was evaluated in a multi-site
RCT with a large sample of 893 women students. There were
prospective data for women who did and did not take the
program, which included information about their back-
grounds and baseline scores on key variables. Further, we
followed them with assessments across more than a year with
high retention. Data collection included measurement of
potential mediators (mechanisms) 1-week post-intervention
and sexual assaults in the 12 months following that assess-
ment, which allowed for prospective temporal conclusions
regarding the mediators’ influence on post-program sexual
assault outcomes. As such, we were able to go beyond the
goal of finding out whether a program works to decrease
sexual victimization to how and why the program works. This
article describes a chained multiple mediation analysis,
which allowed us to assess the joint processes that produced
treatment outcomes. Through this analysis, we tested the
model of theoretically postulated mechanisms that drove the
development of the sexual assault resistance education pro-
gram. This is important for scientific and practical reasons
and has not previously been reported.
Theoretical and Empirical Foundation of EAAA
The EAAA program’s name acknowledges that it is based in
large part on the recommendations of Rozee and Koss (2001),
who synthesized decades of theory and rape research to sug-
gest a theoretically driven, evidence-based approach for sex-
ual violence prevention programming for young women. 1
They named this conceptualization “Assess, Acknowledge,
Act (AAA).” AAA was conceived on a bedrock of theory and
feminist research, particularly the cognitive ecological theory
proposed by Norris and Nurius (e.g., Norris et al., 1996;
Nurius & Norris, 1996) and the evidence of effective sexual
assault resistance strategies provided by Ullman (1997, 1998)
as well as a long tradition of feminist grassroots activism,
advocacy, theory, and self-defense practice (e.g., Bateman,
1978; Rozee et al., 1991; Wen-Do Women’s Self Defence,
n.d.; Women Against Rape, 1980). These underpinnings are
described in more detail elsewhere (Rozee et al., 1991; Rozee
& Koss, 2001; Senn et al., 2015; Senn et al., 2017). Rozee and
Koss’s proposed approach challenged past practices that were
not theory- or evidence-based, tended to focus primarily on
stranger sexual assault, and were largely ineffective (see
Morrison et al., 2004, for review of research evaluations of
programs conducted prior to this period). They argued that,
given the continuing alarming rates of sexual violence expe-
rienced by young women, the complete lack of success in
Senn et al. 21
reducing perpetration, and the substantial evidence base
available, providing women with knowledge and skills to
prepare them to detect risk, overcome emotional obstacles
to acknowledging the danger, and to resist sexual coercion
or sexual assault by men they know was imperative.
In response to this call, the first author designed a resis-
tance program curriculum to bring the conceptualized pro-
gram into reality. The term “resistance” is used in its broadest
sense to represent any attitudes women hold or actions they
take to refuse to accept or comply with social norms or expec-
tations that (a) support woman-blaming explanations for sex-
ual violence, (b) undergird societal tolerance of rape culture,
and/or (c) undermine women’s sexual autonomy. Resistance
includes defensive actions women take to protect their
boundaries, their body, and sexual integrity in interactions
with others. For survivors, resistance also includes the refusal
to accept sexual violence perpetrators’ views of them and
what occurred. EAAA reduces the sexual victimization
women experience while holding perpetrators entirely
responsible for their actions (Senn et al., 2015; Senn et al.,
2017) and interrupts messages often perpetuated in a rape
culture (Radtke et al., 2020). The program has a gendered
framing, focusing on sexual assaults perpetrated by men who
are known to young women (i.e., it uses a broad definition of
acquaintances that includes family members, intimate part-
ners, classmates, neighbors, and other men they know).
EAAA is designed and implemented to recognize the diver-
sity of experiences of participants who self-identify as
women in terms of prior sexual victimization history (i.e.,
that there will always be survivors in the room), demo-
graphics (e.g., race, class, religion), abilities (e.g., physical
ability, ability to be loud), sexual identity (i.e., explicitly
acknowledges heterosexual, bisexual, lesbian, and asexual
identities), and relationship and sexual experience.
The goals of the program are to (a) increase the likelihood
that empirically supported risk cues in social contexts (e.g.,
isolation, alcohol) and revealed in men’s behavior (e.g., per-
sistence, sexual entitlement) will be detected by women as
early as possible in social interactions, (b) decrease women’s
emotional or cognitive obstacles to risk detection or resistance
in situations involving known men, and (c) increase the like-
lihood that women will use defensive actions (e.g., leaving
when possible, forceful verbal and physical self defense) that
are most likely to lead to better outcomes (i.e., reduced severity
of the sexual assault, interruption of rape; Tark & Kleck, 2014;
Ullman, 1997) when threats are detected.
To accomplish these goals, the curriculum has four 3-hour
units. Unit 1, Assess, is designed to help women identify
situations and behaviors that signal a higher risk for sexual
violence. Unit 2, Acknowledge, was created to assist women
to overcome emotional barriers to acknowledging the threat
from men they know and provides practice in identifying and
resisting verbal coercion. Unit 3, Act, provides empowerment
verbal and physical self-defense training (based on Wen-Do
Women’s Self Defence) focused on effective strategies for
resisting common acquaintance tactics. Unit 4, Relationships
and Sexuality, adapted from the Our Whole Lives curriculum
(Goldfarb & Casparian, 2000; Kimball & Frediani, 2000),
offers high quality sexual information and a context for
exploring and talking about their own sexual desires and
relationship values. In other words, EAAA gives women
evidence-based information, skills, and practice within a pos-
itive sexuality framework to empower them to more quickly
identify a sexually coercive situation involving a male
acquaintance as dangerous and get out or use forceful resis-
tance if necessary. More detail on the program content is
provided elsewhere (Radtke et al., 2020; Senn et al., 2013).
The key findings for the registered, multisite (three uni-
versities), RCT (SARE Trial) evaluating EAAA have been
published elsewhere (Senn et al., 2015; Senn et al., 2017) but
are briefly summarized here. The reductions in sexual vio-
lence for young women who were assigned to the EAAA
program (Senn et al., 2015) were accompanied by positive
program effects on a number of other important outcomes
(Senn et al., 2017) measured 1 week after participation and,
for most, at 6 and 12 months (and up to 24 months). We
measured these additional outcomes because they were
hypothesized mediators; that is, they encompassed most of
the theoretical mechanisms targeted by the AAA approach to
increase women’s safety without limiting their freedom. In
this study, we go beyond our previous analysis of the pro-
gram’s positive effects on these outcomes to test whether,
together, they are mediators of the reductions in the sexual
assault across time. In other words, do improved scores on
these outcomes at post-test (1-week after participation) com-
bine to account for the reductions in sexual assault experi-
enced from that point until the 12-month follow-up?
In the following section, we explain the hypothesized mul-
tiple mediation model (Figure 1) and, specifically, the theory
behind our expectations that the possible mediators would
combine to lead to reductions in sexual assault. Given that
the model was built based on the best evidence available,
there are no competing theoretical models to be tested; rather,
we are assessing whether the model works as a whole and
whether the relationships for any hypothesized elements are
not supported. Any variable that is hypothesized to explain a
portion of the EAAA program’s effect on sexual assault vic-
timization through a direct link to the outcome, we refer to as
a “primary mediator.” These are the primary elements of the
AAA model. Any variable that is hypothesized to have an
indirect link to the outcome through its influence on a pri-
mary mediator, we refer to as a “secondary mediator.”
Mediators of Reductions in Sexual Assault
Risk detection is a key element of the primary appraisal pro-
cess outlined in Nurius and Norris’s (1996) cognitive ecolo-
gical model and hence also the theoretical underpinning of
the first unit (Assess). The program is designed to undermine
socialization processes about “stranger risk” that direct
22 Psychology of Women Quarterly 45(1)
women to use a wide range of precautionary strategies
involving restrictions on their freedom without protecting
them from sexual violence (e.g., not walking alone at night;
Gordon & Riger, 1989; Stanko, 1990). The curriculum pro-
vides information and practice in identifying empirically sup-
ported risk factors for acquaintance sexual assault and
encourages women to trust their own instincts and judgments
when they identify risk cues in social situations. Based on
past research (e.g., Marx et al., 2001) and theory, better risk
detection (i.e., more accurate, earlier) at post-test, which was
a positive outcome of participation in EAAA (Senn et al., 2017),
should be directly linked to reductions in sexual victimization
in the subsequent 12 months and hence a primary mediator.
The EAAA program also addresses obstacles women
encounter at secondary appraisal stages (i.e., after risk has
been detected and when they are making “determinations of
coping resources, options, and outcomes”; Nurius & Norris,
1996, p. 130) in interactions with coercive men. Content and
activities in the second unit of the EAAA program focus on
strengthening women’s belief in their own sexual and rela-
tionship rights and undermine the belief that relationships
must be preserved at all costs. Young women are provided
with a context in which they can practice asserting their needs
and confronting common verbal and physical acquaintance
perpetrator tactics. In the third unit, facilitators present
evidence that direct forceful verbal and physical resistance
strategies and leaving lead to better outcomes in sexual
assault situations. In any given situation, participants are then
able to select their own toolbox of effective strategies from
among the many techniques taught. Nurius and Norris (1996)
summarize the goal of intervention to improve the situation
for women as follows:
Thus, the extent to which a woman is prepared to see assertive
behavior as a reasonable resistance stance and is assisted to gain
assertiveness skills and habits may have an indirect effect
mediated through a woman’s cognitive structures operating at
the time of the coercion. (p. 122, emphasis added)
Thus, both increases in self-defense self-efficacy, that is,
confidence that she could assert and defend herself across a
range of situations, and the ability and willingness to use more
direct resistance strategies in a hypothetical situation should be
related to one another and be primary mediators of the EAAA
program’s effects on sexual assault. Notably, in our previously
published analysis, we found both variables to be positively
impacted by program participation (Senn et al., 2017).
Based on the research evidence (e.g., Vitek et al., 2018),
risk detection was a primary mediator expected to be influ-
enced by secondary mediators (i.e., other specific attitudes
Figure 1. Hypothesized Multiple Mediation Model.
Note. Primary mediators are variables that are hypothesized to explain a portion of the Enhanced Assess, Acknowledge, Act program’s (Group) effect on sexual assault victimization and have a direct link to the outcome (Sexual Assault). Secondary mediators are variables that are hypothesized not to have a direct link to the outcome themselves but rather are expected to influence the primary mediators. OwnRisk ¼ perceived risk of acquaintance rape; FPrecip ¼ belief in female precipitation of rape; RapeMyth ¼ rape myth acceptance; RiskDet ¼ risk detection; DResist ¼ direct resistance; SDSE ¼ self-defense self-efficacy.
Senn et al. 23
and beliefs directly affected by the EAAA program). Three
hypothesized secondary mediators that were included in the
RCT were (a) women’s perceptions of their own general risk
of sexual assault, (b) acceptance of rape myths, and (c) the
belief that women play a causal role in sexual assault. All
were affected in the desired direction by program participa-
tion at the post-test, and these effects were maintained for at
least 2 years (Senn et al., 2017). These attitudes and behaviors
were not expected to have direct effects on sexual victimiza-
tion (i.e., changes in attitudes and beliefs alone have never
been sufficient to reduce the incidence of sexual assault;
Morrison et al., 2004). Instead, they were included in the trial
precisely because any improvements in these attitudes and
beliefs were hypothesized to facilitate risk detection. Thus,
we hypothesized that in combination these three factors
would be related to each other and would lead to better out-
comes in sexual assault through their relationships with risk
detection. Each is described in more detail below.
An optimism bias, which is the belief that while others are
at risk of experiencing a particular negative outcome, we are
not ourselves at risk, can in some circumstances be protective
(e.g., against depression; Conversano et al., 2010). However,
“unrealistic optimism” (Nurius & Norris, 1996) is an obstacle
to detecting acquaintance sexual assault risk (Norris et al.,
1996). Unsurprisingly, an optimism bias is present in women’s
estimates of their sexual assault risk (Gidycz et al., 2006). The
problematic piece of this perception is not the judgment of risk
for other women who are similar to us—this tends to be rela-
tively accurate (i.e., there is a possibility the bad event could
occur)—but rather judgment for one’s self (i.e., it is unlikely to
occur to me). The RCT analyses showed that the EAAA pro-
gram increased women’s perceptions of their own general risk
of sexual assault (Senn et al., 2017). 2
We hypothesized that this
should be related to women’s risk detection in specific situa-
tions by making “danger cues” relevant and worthy of attention
as they arose in those situations.
Similarly and relatedly, commonly held myths about the
characteristics of rape, rape perpetrators, and rape victims
(e.g., that rape is most likely to be perpetrated by strangers)
may be psychologically self-protective (e.g., “only women
who do X, wear Y, or go to Z are raped and I would never
do those things”) but may also have negative consequences,
such as impairing perceptions of one’s own risk of sexual
assault (e.g., Bohner et al., 2009; Yeater et al., 2010).
Victim-blaming beliefs are thought to be particularly perni-
cious in this regard. We therefore hypothesized that the pro-
gram’s positive effects in reducing rape myths in general and
the specific incorrect belief that women cause rape by their
own actions (Senn et al., 2017) would be related to improved
risk perception. Further, we expected that reducing the belief
that women cause rape by their own actions, a belief that
when applied to the self can give one false sense of security
(e.g., If I don’t go there or do that, then it can’t happen to me),
would be related to increases in women’s perceptions of their
own personal risk because reducing these beliefs makes sali-
ent that any woman is potentially at risk.
The theory and evidence upon which EAAA was built
emerges from many different, primarily correlational studies
often focused on a single domain (e.g., risk perception or
self-defense strategies) that were related to positive outcomes
(Norris et al., 2018; Tark & Kleck, 2014; Vitek et al., 2018).
Although changes in individual domains can occur and can be
important in their own right (e.g., more high-quality informa-
tion about a phenomenon or more skill is usually better than
less), our focus is on how the combined domains of the whole
model are implicated in achieving the reductions in attempted
and completed rape 3
affected through participation in the
EAAA program.
We focused on the 1-year data from the SARE Trial RCT,
because a drop in effect sizes after 1 year and a decrease in
the sample size across 2 years reduced our ability to test these
relationships beyond this period. 4
We assessed mediation
prospectively using participants’ scores on the hypothesized
primary and secondary mediators that were measured 1-week
post-program and their experience of sexual assault in the
subsequent 12 months after the post-test. Given our large
sample size, we were able to test the mediation effects for
completed and attempted rape separately. It should be noted
that rape is broadly and behaviorally defined to include oral,
vaginal, and anal penetration by a man without the woman’s
consent through a range of perpetrator tactics including
threats, force, and taking advantage of or inducing women’s
incapacitation from drugs or alcohol (Koss et al., 2007).
Method
Participants
Eight hundred and ninety-three first-year undergraduate stu-
dents who identified as women were recruited at three uni-
versities and enrolled in the SARE RCT. The full trial
protocol has been published (Senn et al., 2013), as have the
1- and 2-year primary and secondary outcomes (Senn et al.,
2015; Senn et al., 2017). The prospective analysis in the
present study required valid responses on potential mediators
measured post-intervention at a 1-week post-test and sexual
assault outcomes measured beyond that point. A total of 871
(97.5%) women completed the 1-week post-program survey. Among these, 857 (98.4%) completed one or both of the 6- and 12-month follow-up surveys (i.e., not lost to
follow-up) and were included in this study. The 36 partici-
pants who were excluded were not characteristically different
from the 857 who were retained in the present study (all ps
ns). The average age of the included women was approxi-
mately 19 years, almost all were heterosexual or bisexual,
one-quarter were women of color, one-half lived in a univer-
sity residence, one-third had previous self-defense training,
and approximately one-quarter had experienced the previous
victimization (see Table 1).
24 Psychology of Women Quarterly 45(1)
Intervention
EAAA. This small group (�20 participants) intervention was led by pairs of highly trained, slightly older peer (<30 years)
women facilitators. Women attended an average of 3.62 (SD
¼ 0.82) of four sessions, with most (91%) attending three or four sessions. Curriculum fidelity was high (average 94%) as measured by the assessment of randomly selected audio
recordings.
Control. To match the standard of care common to all univer- sity campuses at the time, brochures on sexual assault were
available for participants to take and read, with a friendly and
knowledgeable person available to answer any questions that
arose about sexual assault or available resources from the
group of participants. Brochures chosen were specific to the
campuses but had common elements, including the provision
of general sexual assault information, date rape drug facts,
legal and medical information for survivors, and local
resources.
Procedure
The detailed RCT protocol and procedures are published else-
where (Senn et al., 2013), but we provide a brief overview
here. Participants were recruited through a variety of means,
including posters, emails, tabling, and advertising in research
participant pools. Interested students made contact by phone or
email, were screened by a research assistant and given a
detailed explanation of the purpose of the study, the longitu-
dinal survey process and timing, and the randomization pro-
cedure. They then chose the timing of the baseline and EAAA
intervention sessions that matched their schedule without yet
knowing to which condition they would be randomly assigned.
All participants attended a baseline session to complete sur-
veys in a computer lab, were randomized (using Randomize.
net), and then directed to their intervention room. A meal was
provided, the randomization outcome was revealed, and the
session facilitated. Depending on their chosen schedule, those
students randomized to the EAAA program completed the
other units during the same weekend as the baseline session,
with two program units delivered each day, or across the next 3
weeks, with one program unit delivered immediately and the
other three in subsequent weeks. Control participants attended
their brief group brochure session and then did not return until
the post-test survey session. Both control and program parti-
cipants completed in-person, post-test surveys. For the pro-
gram participants, these occurred 1 week after the final
program session. Control participants completed these surveys
at the same time as the program participants with whom they
attended the baseline and randomization session. Thereafter,
all participants completed follow-up online surveys at 6
months, 12 months, 18 months, and for those enrolled in the
first year of the trial 24 months, after the baseline session. The
CONSORT flowchart is published elsewhere (Senn et al.,
2015; Senn et al., 2017).
In the original published article on the efficacy of the
program in improving sexual assault outcomes (Senn et al.,
2015), an intention-to-treat analysis was used. This required
that any sexual assaults occurring between the baseline and
the post-test be included in the assessment of efficacy even
though participants in the program condition had not yet
received the full dose of the intervention. This affected pro-
gram participants who chose the weekday format more since
there was more time between their baseline and post-test
survey sessions (average of 28 days) compared to those
choosing the weekend format (average of 8 days). For the
current prospective analysis, sexual assaults needed to have
occurred after completion of the post-test sessions where
potential mediators were measured. Therefore, while other
aspects of intention-to-treat were still used, we scored sexual
assaults occurring after the post-test as the first occurrence of
this outcome. As randomization was effective in ensuring
equality between groups on all potential mediators measured
at baseline (Senn et al., 2015) and two mediators were
assessed using single-use measures only at post-test, the cur-
rent analysis used only mediator data obtained at the post-test
survey.
Measures
Sexual assault was measured using the Sexual Experiences
Survey–Short Form Victimization (SES-SFV; Koss et al.,
Table 1. Between-Group Comparisons of Participant Characteristics at the Time of Randomization.
Participant Characteristic EAAA
(n ¼ 434) Control
(n ¼ 423) p
Age in years, M (SD) 18.5 (1.2) 18.5 (1.2) .90 White race, n (%) 316 (72.8) 313 (74.0) .69 Heterosexual identity, n (%) 399 (91.9) 390 (92.2) .89 Living in a university residence, n (%) 235 (54.1) 230 (54.4) .95 Sexually active, n (%) 268 (61.7) 259 (61.2) .87 Currently involved in a romantic
relationship, n (%) 197 (45.4) 189 (44.7) .83
Currently involved in a sexual relationship, n (%)
191 (44.0) 196 (46.3) .49
Previous sexual assault education, n (%)
16 (3.7) 18 (4.3) .67
Previous self-defense training, n (%) 147 (33.9) 140 (33.1) .81 Sexual victimization since the age
of 14 years, n (%) Completed rape 95 (21.9) 98 (23.2) .65 Attempted rape 107 (24.6) 120 (28.4) .22
Perceived risk of acquaintance rape, M (SD)
1.83 (1.03) 1.80 (0.99) .71
Belief in female precipitation of rape, M (SD)
15.0 (7.5) 15.3 (7.2) .56
Rape myth acceptance, M (SD) 31.8 (12.0) 31.8 (11.6) .92 Self-defense self-efficacy, M (SD) 43.9 (7.8) 44.9 (8.3) .09
Note. EAAA ¼ Enhanced Assess, Acknowledge, Act.
Senn et al. 25
2007). The SES-SFV provides participants with seven items
consisting of a stem that describes a sexually coercive or
assaultive act or attempted act (e.g., “A man put his penis
into my vagina or [someone] inserted fingers or objects with-
out my consent by . . . ”), followed by five descriptions of perpetrator tactics or strategies (e.g., “using force, for exam-
ple, holding me down with their body weight, pinning my
arms, or having a weapon”). The tactics range from verbal
pressure to physical force. Given the gender-specific focus of
the program, we removed the gender-neutral reference to
“someone” to ensure reports were victimization by men only.
Participants responded to each stem and tactic based on the
frequency of occurrence (a) since the age of 14, (b) since the
baseline (1-week post-program), and (c) since the last survey
for 6- to 24-month follow-ups. When participants reported an
attempted or completed rape, they were prompted to use a
pop-up calendar to pick the (approximate if necessary) month
and the day the incident happened. As such, the outcome/
dependent variable in the mediation model is analyzed as
time-to-event. Victimization by attempted or completed rape
between the 1-week post-program survey and 12-months of
follow-up is the focus of the current analysis and randomiza-
tion to the EAAA program or control group is the causal
variable.
Mediators. Figure 1 illustrates the hypothesized chained mul- tiple mediation model. Primary mediators are those variables
hypothesized to have a direct link to the outcome. Secondary
mediators are hypothesized to influence primary mediators
without direct relationships to the outcome. Responses to
these measures at a 1-week post-test are the focus of the
current analysis. All measures demonstrated good internal
consistency in the current sample (Senn et al., 2017).
Primary Mediators. These included situational risk detec- tion, direct resistance, and self-defense self-efficacy. Situa-
tional risk detection was assessed using Testa et al.’s (2006)
measure that provides a hypothetical acquaintance dating
scenario with escalating coercion revealed at two time points
(collapsed data used here) and asks the question, “How likely
is it that the situation just described will result in . . . ” fol- lowed by 10 positive (e.g., “an evening that ends pleasantly”)
and negative (e.g., “You being upset by Michael’s behavior”)
outcomes. Participants rated the likelihood of each on a
7-point scale. The 6 item Direct Resistance subscale (Testa
et al., 2006, built on items from Norris et al., 1999, and Davis
et al., 2004) was used to measure willingness to use effective
self-defense strategies (e.g., “Forcefully push him away”) in a
hypothetical situation. It was administered following the
coercive dating scenario described above on the same
7-point likelihood Response Scale with the data collapsed
across the two time points. Self-defense self-efficacy was
measured by responses on a 7-point Confidence Scale to
11 items adapted by (Senn et al., 2017) of Marx et al.’s
(2001) adaptation of Ozer and Bandura’s (1990) scale (e.g.,
“If a situation develops in which you feel you could be in
danger of sexual assault, how confident are you that you
could successfully think up ways to get out of that situation
and then execute your plan?”).
Secondary Mediators. These include (a) a single-item mea- sure of perception of one’s own general risk of acquaintance
rape, Perceived Risk of Acquaintance Rape (“What are your
chances of being raped by someone you know?”), rated on a
5-point scale from “very likely” to “very unlikely” (adapted
from Gray et al., 1990); (b) a specific measure of victim
blaming, the 6-item Female Precipitation subscale of the Per-
ceived Causes of Rape Scale (Cowan & Campbell, 1995; e.g.,
“Rape is caused by women allowing the situation to get out of
control”); and (c) a general measure of rape myth beliefs, the
Illinois Rape Myth Acceptance Scale–Short Form (Payne
et al., 1999; e.g., “Men from nice middle-class homes almost
never rape”).
Statistical Analyses
Path analyses were used to fit the chained multiple mediator
models. Weibull proportional hazards regression models
were used because the outcomes were time-to-first completed
rape and time-to-first attempted rape and as such yielded
hazard ratios which can be interpreted as relative risks (i.e.,
risk ratios). The proportional hazards assumption was
assessed by plotting log(�log[survival]) versus the log of survival time and by testing the time dependent covariate in
the regression models.
The total effect of the EAAA program was estimated by
calculating unadjusted hazard ratios (HR) from Weibull propor-
tional hazards regression models that included the intervention
variable as the only predictor in the models. The direct effect
was estimated by calculating adjusted hazard ratios from regres-
sion models that consisted of the intervention variable and the
mediators. The percentage of the mediated intervention effect
was calculated from the respective intervention regression coef-
ficients in the total effect and direct effect models as follows:
100 � btotal effect � bdirect effectð Þ=btotal effect½ � (MacKinnon et al., 2007). The interpretation of the model findings was aided by
converting the resulting pathway unstandardized regression
coefficients (b) to hazard ratios for the primary mediators and
semipartial Pearson correlation coefficients for the secondary
mediators.
We tested the primary mediators jointly using a likelihood
ratio test to establish whether they are the process through
which the effects of the program are realized. Full mediation,
defined as a non-significant direct effect, would suggest that
the mediators explain the impact of EAAA, whereas partial
mediation (a significant direct effect) would suggest that the
mediators are important to the EAAA outcomes but not suf-
ficient to explain the outcome. Given that both the EAAA
program and control were conducted in group sessions, all
regression models accounted for clustering of outcomes
within group sessions by using the generalized Huber/
26 Psychology of Women Quarterly 45(1)
White/sandwich estimator of the variances. The extent of
clustering was characterized by design effects. All analyses
were conducted using Stata Version 16 (StataCorp LLC, Col-
lege Station, TX, USA) and SAS Version 9.4 (SAS Institute
Inc., Cary, NC, USA), and results with p values less than .05
were considered statistically significant.
Results
As shown in Table 1, the randomization of a relatively large
number of women into the trial yielded two similar groups
with regard to demographics, sexual experience, and poten-
tial mediators (those assessed pre-randomization), and
therefore no adjustment for baseline covariates was neces-
sary in the analyses. Among the 857 women included in the
present study, 52 (6.1%) experienced a completed rape and
43 (5.0%) experienced an attempted rape between the time of completing the post-test survey and 12 months of
follow-up, and only 2.1% (9 of 434) in the EAAA program and 2.6% (11 of 423) in control were lost to follow-up. As both the outcome event rates and lost to follow-up rates
observed in the present study were low, it is permissible
to calculate the percentage of the mediated intervention
effect from the respective intervention regression coeffi-
cients without concern of bias (Burgos Ochoa et al.,
2020). With regard to model proportionality assumptions,
the plots of log(�log[survival]) versus the log of survival time yielded relatively parallel lines and the test of the time
dependent covariate in the regression models yielded
non-significant p values (.36 and .14 for completed and
attempted rape, respectively). As the EAAA program and
control sessions were conducted in 93 groups (clusters),
Figure 2. Total Effect Models and Final Chained Multiple Mediator Models for Completed Rape and Attempted Rape.
Note. (Panel A) The total effect, relating intervention group to completed rape without mediators, in terms of a hazard ratio was .55 (b ¼ �.601, relative risk reduction ¼ 45%, p ¼ .037). After accounting for clustering the p value was .055. The total effect, relating intervention group to attempted rape without mediators, in terms of a hazard ratio was .41 (b ¼�.893, relative risk reduction ¼ 59%, p ¼ .011). (Panel B) The direct effect, relating intervention group to completed rape with mediators, in terms of a hazard ratio was .97 (b ¼�.029, relative risk reduction ¼ 3%, p ¼ .933); the percentage of the mediated intervention effect was 95.2% (p < .001). The direct effect, relating intervention group to attempted rape with mediators, in terms of a hazard ratio was .80 (b ¼�.217, relative risk reduction ¼ 20%, p ¼ .595); the percentage of the mediated intervention effect was 75.7% (p < .001). Solid lines represent significant paths and dashed lines represent nonsignificant but hypothesized paths. CpltRape ¼ completed rape; AttmRape ¼ attempted rape; OwnRisk ¼ perceived risk of acquaintance rape; FPrecip ¼ belief in female precipitation of rape; RapeMyth ¼ rape myth acceptance; RiskDet ¼ risk detection; DResist ¼ direct resistance; SDSE ¼ self-defense self-efficacy.
Senn et al. 27
with an average of 9.2 participants in each group, the
within-group clustering resulted in design effects of 1.19 for
completed rape and 1.11 for attempted rape.
For this sample of 857 women, the total effect of the
EAAA program was a 45.0% reduction in the risk of com- pleted rape (HR ¼ 0.55, p ¼ .037: ignoring clustering, p ¼ .055: accounting for clustering; Figure 2, Panel A). For attempted rape, the total effect of the EAAA program was a
59.0% reduction (p ¼ .011). Results from the final chained multiple mediation analyses are displayed in the path diagram
(Figure 2, Panel B) and numerically summarized in Table 2.
The three primary mediators in the hypothesized model,
when tested jointly, were responsible for a significant reduc-
tion in the sexual assault outcomes (likelihood ratio test, p <
.001). Some of the relationships (hazard ratios) between the
primary mediators and the outcomes were nonsignificant
because of the interrelationships among the mediators. All
are critical to the overall mediation model as evidenced by
the significant likelihood ratio test. The hypothesized
secondary mediators related to each other as predicted, rape
myth acceptance and belief in female precipitation partially
mediated the intervention’s effect on the perceptions of one’s
own general risk, and perception of personal risk and rape
myth acceptance mediated the intervention’s effect on risk
detection. One hypothesized path was not supported; belief in
female precipitation did not have a significant path directly to
risk detection.
The model fully mediated the intervention effects for both
completed rape and attempted rape by yielding direct effects
of 3% (p ¼ .93) and 20% (p ¼ .59) reductions in risk, respec- tively. Specifically, the model mediated 95.2% (p < .001) of the intervention effect for completed rape and mediated
75.7% (p < .001) for attempted rape. In our theoretical model, we assumed that secondary med-
iators work solely through a primary mediator, so we also
examined a model with paths from these secondary mediators
to the outcome to test this presumption. The percentage of
mediation did not increase. In addition, we evaluated whether
Table 2. Regression Coefficients for the Primary and Secondary Mediators in the Final Path Diagram With Respective Hazard Ratios and Correlation Coefficients for Completed and Attempted Rape.
Completed Rape Attempted Rape
Global Primary a Likelihood Ratio Test p Likelihood Ratio Test p
RiskDet! DResist!Outcome LR3df ¼ 31.92 <.001 LR3df ¼ 20.50 <.001 SDSE!
Primary mediators b
bAdjusted HRAdjusted p bAdjusted HRAdjusted p
RiskDet ! Outcome �0.060 0.94 .016 �0.025 0.97 .281 DResist ! Outcome �0.042 0.96 .032 �0.039 0.96 .033 SDSE ! Outcome �0.035 0.96 .121 �0.059 0.94 .006 Group ! Outcome �0.029 0.97 .933 �0.217 0.80 .595
Completed and Attempted Rape
Secondary mediators b bAdjusted rSemipartial p
Group ! OwnRisk 0.679 .24 <.001 FPrecip ! OwnRisk �0.018 �.07 .026 RapeMyth ! OwnRisk �0.013 �.08 .017 Group ! FPrecip �5.845 �.39 <.001 Group ! RapeMyth �1.868 �.07 .009 FPrecip ! RapeMyth 1.125 .64 <.001 OwnRisk ! RiskDet 0.446 .07 .027 FPrecip ! RiskDet 0.075 .05 .114 RapeMyth ! RiskDet �0.211 �.23 <.001 Group ! DResist 1.128 .06 .023 RiskAsmt ! DResist 0.523 .50 <.001 SDSE ! DResist 0.243 .20 <.001 Group ! SDSE 6.572 .46 <.001
Note. RiskDet ¼ risk detection; DResist ¼ direct resistance; SDSE ¼ self-defense self-efficacy; OwnRisk ¼ perceived risk of acquaintance rape; FPrecip ¼ belief in female precipitation of rape; RapeMyth ¼ rape myth acceptance; HR ¼ hazard ratio. a Likelihood ratio test assessing the joint (global) significance of the three primary mediators. b Each row indicates each mediator’s contribution to the model beyond their interrelations with other mediators; estimated from the final chained multiple mediator models that adjusted for all primary and secondary mediators and clustering.
28 Psychology of Women Quarterly 45(1)
an all-paths model would improve mediation of the outcome
over our theoretical model. Again, the percentage of media-
tion did not increase.
Discussion
In sexual violence prevention practice, we generally have
presumed that effective programs work to achieve their out-
comes in the ways that we theorized; however, we cannot
move our theory and practice forward unless we test these
models or mechanisms directly. Until recently, sexual vio-
lence prevention programs have not been sufficiently effec-
tive to warrant this type of exploration nor have the
evaluation studies been sophisticated enough in design, sam-
ple sizes, quality of measured outcomes, and so on, to allow
it. The current findings contribute to the sexual violence pre-
vention field by advancing our understanding of how a sexual
assault resistance program for university women works to
reduce the sexual victimization that women experience.
Although mediation analyses often focus on one media-
tor at a time (Baron & Kenny, 1986; Preacher & Hayes,
2004), we used a chained multiple mediation analysis,
which accounts for the relationships among the mediators.
This analysis confirmed that the theoretical model we tested
fully mediates the program’s effects on sexual assault. In
other words, the direct program effect is no longer statisti-
cally significant when the mediators are included in the
model. More important, and surprising perhaps, the theore-
tical model tested accounts for 95% of the reduction in completed rape and 76% of the reduction in attempted rape. This is an unusually large mediation effect and provides
strong support for EAAA’s theoretical and evidentiary
underpinnings (Nurius & Norris, 1996; Rozee & Koss,
2001). The theory works extremely well to explain the pos-
itive outcomes of sexual assault resistance education for
women students in the early stages of their university
studies.
Primary Mediators of Program Reductions in Sexual Assault
Based on theory and prior evidence, we hypothesized that the
EAAA program would reduce completed and attempted rapes
through changes in three key mechanisms—risk detection,
self-defense self-efficacy, and direct resistance. As expected,
the three primary mediators worked together in producing the
program’s effects on sexual assault.
We explicitly included two of the hypothesized primary
mediators, risk detection and self-defense efficacy, because
they were key aspects of Nurius and Norris’s cognitive eco-
logical model, the theory upon which the AAA approach
and the EAAA program are built. Risk detection is involved
in the primary appraisal of a social situation involving an
acquaintance as dangerous and, therefore, in need of a
response. Self-defense self-efficacy is involved in the
secondary appraisal of a coercive sexual situation as some-
thing that can be overcome by, or coped with, using
women’s own resources. Improving risk detection is gener-
ally viewed as a necessary goal of an intervention but not
sufficient to lead to better outcomes (Vitek et al., 2018).
After all, one could see danger and not know what to do,
say, or the options available to take actions, leading to pas-
sivity or non-response (Macy et al., 2006; Nurius et al., 2004).
Self-efficacy is critical to people being able to implement
changes in their lives (Bandura, 1977), and past research has
shown that confidence is related to an increased likelihood of
women responding assertively in sexual assault situations
(Vitek et al., 2018).
However, knowing more about one’s options and effective
responses and being willing to use them are also important to
action. Because expanding these available resources (i.e.,
women’s knowledge and capabilities) is theorized to reduce
barriers to resistance (Rozee & Koss, 2001), we also included
women’s selection of, and willingness to use, the resistance
strategies known to be the most effective in an acquaintance
sexual assault situation, namely, direct, forceful verbal and
physical strategies (e.g., Tark & Kleck, 2014).
This model supports the necessity of designing resistance
programming to influence all three primary mediator com-
ponents of the AAA model (Rozee & Koss, 2001). The
multiple mediation analysis shows how risk detection,
self-defense self-efficacy, and direct resistance strategies
operate when they are considered together. Risk detection
and direct resistance are correlated. After all, if danger is
not detected, assertive or forceful actions will not be taken,
and vice versa. Self-defense self-efficacy and direct resis-
tance are also correlated. This makes sense for exactly the
reason that we, and other researchers (Hollander, 2016,
2018; Rozee & Koss, 2001), argue for their inclusion in the
model. Specifically, they are both necessary for resistance
to be undertaken. A woman who lacks the general confi-
dence in her ability to take action to stand up for or defend
herself is unlikely to report that she would use defensive
actions in a specific situation. Similarly, high confidence
that she could problem-solve and defend herself in an
acquaintance situation could be misplaced, if she is unable
to detect risk in the early stages of the situation, when more
defensive options are available compared to later stages, or
if she lacks knowledge of likely effective strategies.
Altogether, these findings support Rozee and Koss’s
(2001) AAA conceptualization and claims that women
would benefit substantially from increased ability to assess
danger in acquaintance situations, overcome emotional
obstacles to acknowledge risk and feel prepared and confi-
dent knowing that resistance is possible, and then to take
action using their own judgment and the best strategies
available to them. Even though we measured risk detection
and direct resistance in response to hypothetical situations,
these factors together with self-defense self-efficacy
explained the lower levels of completed and attempted rape
Senn et al. 29
reported by the women across the year following program
participation. Therefore, the content and activities within
EAAA, which increased knowledge of sexual assault risk
cues in men’s behavior and in social situations, increased
theoretical and practical knowledge of effective resistance
strategies in acquaintance situations, and enhanced
women’s confidence in their own judgment and abilities
(Senn et al., 2017) all play important roles in reducing sex-
ual victimization.
Secondary Mediators of Program Reductions in Sexual Assault
Detection of danger is extremely difficult in acquaintance
social situations where building friendships or intimate rela-
tionships, studying, partying, or otherwise having fun are the
focus of the interactions, and coercive and controlling strate-
gies usually start slowly and escalate (Norris et al., 1996;
Norris et al., 1999; Nurius, 2000; Nurius & Norris, 1996).
Based on the research literature, we added three potential
secondary mediators affected by the EAAA program to the
theoretical model: women’s perceptions of their own general
risk of sexual assault, belief in rape myths, and the pernicious
myths that hold rape victims responsible. The analysis
strongly supported the indirect role of all three in achieving
program improvements in sexual victimization through
enhancing women’s ability to detect risk, one of the primary
mediators. However, unlike our test of mediation for the
sexual assault outcomes, which is based on prospective data,
our test of the mediation of the primary mediators was
cross-sectional, disallowing conclusions of causality. Never-
theless, these findings provide evidence of how improve-
ments in one of the primary mediators, risk detection,
might be accomplished by the program’s content and process.
We used only a single item measure of perception of own
general risk of sexual assault, which made underestimation of
effects more likely (e.g., Beal & Dawson, 2007). Despite this,
increasing women’s perceptions of their own general risk of
acquaintance sexual assault was an important link in the
chain to better risk detection in a specific situation. Vitek
et al. (2018) have suggested that the optimism bias may be
related to all three stages of the AAA model, not just risk
detection. In our test of the full (all paths) model, which failed
to improve mediation, paths from perception of general risk
to the other primary mediators, self-defense self-efficacy and
direct resistance (representing the final two stages of the
AAA conceptualization and secondary appraisal and coping
in the cognitive ecological model), were not supported.
Although a test of Vitek et al.’s hypothesis with a more
nuanced and robust measure should be attempted in the
future, our analysis suggests that the model works extremely
well when the benefits of increasing perception of one’s own
general risk modestly are presumed to act through increasing
risk detection.
As expected, the secondary mediators were inter-related.
Reducing women’s already low general rape myths, which
include but extend beyond victim-blaming attitudes, may
allow them to appreciate the gendered social reality and see
themselves as potentially vulnerable to acquaintance sexual
assault. In the analysis, lowered general rape myth accep-
tance was directly related to higher perception of one’s own
general risk, and then through that perception of personal risk
contributed to improvements in risk detection. We suspect
that undermining the general rape myths that focus on exclud-
ing known men from being considered as perpetrators could
be responsible for this contribution to risk detection. EAAA’s
ability to reduce woman-blaming beliefs specifically was also
important. It was indirectly related to increased risk detection
through women’s higher acknowledgment of their personal
risk of acquaintance sexual assault. Both the content and
philosophy of EAAA as well as the rigorous training process
for facilitators aim to ensure that woman-blaming is inter-
rupted and undermined as it arises during the group interven-
tion. This program feature proves to be very important in
improving participants’ risk detection through lower general
and specific rape myths.
To be clear, we are not calling for a return to the proble-
matic past practice of entirely, or primarily, focusing sexual
assault prevention on undermining rape myths (Morrison
et al., 2004). Unsurprisingly, given the complicated nature
of the cultural discourses about sexual assault and women’s
varied experiences, as well as the tenuous link between atti-
tudes and behavior (Fishbein & Ajzen, 2011), reducing neg-
ative attitudes about rape alone does not reliably increase
bystander behaviors or reduce victimization or perpetration
(DeGue et al., 2014; Fenton et al., 2016). This was confirmed
in our analysis as direct pathways from attitudes to the sexual
assault outcomes were not supported. Nevertheless, we have
shown that even though women hold relatively low levels of
belief in rape myths and victim-blaming and there is no direct
link to reduced sexual assault, reducing belief in rape myths
appears to have specific benefits for women’s resistance to
sexual assault. It is related to improved risk detection in
acquaintance situations. Faster and more accurate detection
of danger is necessary for the benefits of any resistance, risk
reduction, or self-defense program to be fully realized.
Attempted Versus Completed Rape
Our analyses were focused on two categories of sexual
assault. First, we applied the model to the completed (oral,
anal, and vaginal) rape outcome, which is central to most
studies of sexual assault prevention. The mediation model
explains the EAAA program’s effects across the diverse per-
petrator tactics assessed by the SES. Similar to other studies
of university students’ experiences, a large proportion of
these rape experiences involved alcohol (Abbey, 2011; Klein
et al., 2018; Krebs et al., 2009). Nonetheless, because past
research has demonstrated that alcohol consumption impairs
30 Psychology of Women Quarterly 45(1)
risk detection (e.g., Parks et al., 2016) and response/resis-
tance (e.g., Davis et al., 2004; Stoner et al., 2007) to sexual
coercion, future research could explore the specific ways in
which EAAA resistance education contributes to, and might
be limited in, reducing alcohol-involved sexual assaults
specifically.
Second, we tested the same theoretical model for
attempted rape. However, the model tested was based on
theory and evidence primarily derived from research on com-
pleted rape. Despite this, the same mediation model predicted
a large proportion of the program-produced reduction in
attempted rape. This suggests there is substantial overlap in
the mechanisms that explain EAAA’s positive effects in
reducing both completed and attempted rapes. A somewhat
lower percentage of mediated effect was found for attempted
rape (76% vs. 95%), which suggests that there may be room for other mediators to be added to the model when consider-
ing attempted rape. We provide some possible explanations
for the results involving attempted rape based on the current
study and past research to guide future research.
Women cannot control whether men in their social envir-
onments will be coercive, so reductions in attempted rape
victimization mean that some men who were coercive were
not able to execute their plans or increase their level of intru-
sion. Reductions in attempted rape may have been accom-
plished by women detecting early warning signs from verbal
indications of men’s attitudes (e.g., sexual entitlement) or
behavior (e.g., attempts to socially isolate them) and leaving
the situation before the men became coercive. This requires
trusting their instincts or perceptions at earlier stages, some-
thing that we did not directly measure. Further, they may
have used forceful verbal or physical strategies that inter-
rupted the trajectory of coercion (e.g., “you are crowding
me, MOVE AWAY” or a wrist-release to make him let go
as he grabbed her wrist to try to move her to a more isolated
location). Women tend to match their force to the force being
used against them (Tark & Kleck, 2014), so detailed study of
the forms of direct resistance corresponding with particular
instances of attempted rape may offer some clues to what
works some or most of the time. Alternatively, or in addition,
women may have engaged in other strategies to undermine
risk factors that enhance perpetrators’ advantages (e.g., iso-
lation) that are not included in the direct resistance measure
(e.g., called a friend to join them at the party when a guy who
was in attendance made them feel uncomfortable; Anderson
et al., 2016). Thus, our findings for attempted rape can be
explained (at least in part) by components of the AAA model.
However, because some (24%) of the program effect for attempted rape was not explained by the model, we likely
need to look beyond the AAA model to explain the program’s
success in reducing attempted rape. A combination of quan-
titative and qualitative research with women who have taken
resistance programs may be needed for further theory
development.
Directly measuring the benefits of the fourth unit’s posi-
tive sexuality enhancement of the AAA model could also
improve our understanding of how EAAA works to reduce
attempted rape. This unit contributes to resistance education
by challenging societal messages that women’s sexual desires
are of lesser importance than are those of men. It addresses
the absence of high-quality sexual education and discussion
of women’s sexual desires in society at large (Fine, 1988;
Fine & McClelland, 2006) and how normative (hetero)sexual
practices put men’s (presumed) sexual needs ahead of
women’s (Hollway, 1984). This latter discourse, in particular,
has been implicated in acquaintance sexual assault (Gavey,
2005). Due to participant burden, we did not measure
women’s awareness of their own desires and values or their
confidence in asserting these in various situations, although
earlier work has shown benefits (Senn et al., 2011). For het-
erosexual and bisexual women, who constituted the majority
of the sample, increases in sexual knowledge and confidence
would be expected to contribute to faster risk detection, par-
ticularly identification of sexual pressure and other coercive
tactics.
In general, it may be wise for future researchers to do what
we did not, that is, to think through the theoretical model for
attempted rape specifically from the start. In this way, addi-
tional constructs could be identified and measured. We
encourage researchers to include analysis of attempted rape
experiences and avoid treating them as “non-events”
(Cermele, 2010) or as less important (Hollander & Rodgers,
2014) when evaluating prevention programs and testing the-
oretical models so that we hone our broader sexual assault
prevention knowledge and skills.
Strengths and Limitations
Our study’s prospective design provided many benefits and
allowed us to test the influence of mediators at one point in
time (post-test) on subsequent sexual victimization. As a
result, we could infer causality for that outcome. However,
we could only do a cross-sectional analysis of the relationship
of the secondary mediators with the primary mediator, risk
assessment. Although risk detection was related to the atti-
tudes and beliefs serving as secondary mediators and these
attitudes and beliefs improved after participation in the pro-
gram, we cannot conclude that the improvements in risk
detection were produced by the changes in attitudes and
beliefs. Further research is needed.
Our sample size was large, our retention was high (>97%), and our conclusions are based on the responses of women
with and without rape experiences prior to their participation
in the research. Despite these strengths, our sample was not
large enough to reliably evaluate the model separately for
women with and without prior sexual victimization experi-
ence (i.e., to test whether victimization moderates the media-
tion model). We explore similarities and differences in
EAAA’s program effects for individual outcomes by prior
Senn et al. 31
victimization elsewhere (Senn et al., in press), but await
future research with larger samples for this more complex
analysis.
Our test of the theoretical model was applied to a large and
diverse sample of university students who identify as women.
We are working now to expand the populations who may
benefit from resistance programming of this type and would
then be able to test whether the same or similar mediation
model applies. We are currently adapting EAAA for younger
girls and will be evaluating the adapted version in an RCT.
We are also working with other scholars to lay the ground-
work for an adaptation of the EAAA model specifically for
trans-identified students, if it is appropriate.
The field has many good measures but needs more in the
domains key to women’s resistance to sexual violence and
several measures, which we used as the best available, have
limitations. Perception of personal risk is clearly important to
women’s ability to detect risk as we were able to conclude
this even with an imperfect single-item measure. Still, there is
a need for a multi-item measure of perception of sexual
assault risk (and the related optimism bias) with good psy-
chometric properties. We join other researchers (e.g., Vitek
et al., 2018) in also calling for improved measurement of risk
detection. Testa et al. (2006), building on the work of others
(Davis et al., 2004; Norris et al., 1999), developed the strong
measures of risk detection and direct resistance used in our
research. However, participants are responding to a specific
two-part scenario of a dating interaction with a coercive man.
Scenarios for acquaintance situations that are relevant for
women who do not date men, due to their sexual identity or
cultural/religious/political background, are needed. More-
over, an ability to measure and then collapse across responses
to multiple situations and contexts would strengthen the mea-
surement of the constructs. Other available risk perception
measures (Messman-Moore & Brown, 2006) could also be
improved with more scenario options. Currently, once these
measures have been used in a longitudinal study, they cannot
be presented again because the “end of the story” is now
known. This is a limitation for understanding how program
effects are mediated for the longer term.
Our analysis was also limited by our failure to include
measures of implied mediators. For example, we presumed
that if women improved their risk detection and used more
direct, forceful resistance strategies, they had overcome at
least some of the known obstacles to assessing, acknowled-
ging, and acting to resist acquaintance sexual assault. Our
analyses would have been improved by measuring changes
in women’s endorsement of known obstacles and assessing
whether this process variable acts as a primary or secondary
mediator. We also did not measure what is variously
described as relationship investment or motivation to main-
tain relationships with men, yet this is the hypothesized origin
of one specific psychological barrier to acknowledging dan-
ger and/or resisting men they know, particularly for hetero-
sexual women (Macy et al., 2007; Norris et al., 2018; Nurius
et al., 2004). EAAA explicitly acknowledges this motivation
(and its positive roots) and uses various approaches to under-
mine its application in circumstances where risk cues have
been detected. Explicit measurement of this barrier for
acquaintance rape resistance may have improved the model.
Some researchers have suggested that the experience of
learning physical and verbal self-defense changes how
women experience their bodies, including their sense of inha-
biting and having ownership of them (i.e., embodiment; see
Piran, 2016) and that this can lead to increased demands that
boundaries be respected and resistance when boundaries are
violated (Hollander, 2004; Hollander, 2014). Inclusion of
measures of embodiment and of experiences setting and pro-
tecting boundaries might both be fruitful additions for future
research. Qualitative research with young women who have
experienced the program could also potentially expand our
knowledge of other ways in which this type of education
affects them.
Practice Implications
The current study builds on our previously published research
in offering important insights for practitioners of empower-
ment self-defense. Previous analysis showed that a relatively
small number of hours (3 of 12) of instruction focused on
verbal and physical self-defense in acquaintance situations is
sufficient to increase confidence and willingness to use
the strategies that research has shown are most likely to be
effective. Current findings show that these two benefits also
contribute to reductions in attempted and completed rape.
Detecting risk in social situations and men’s behavior is nei-
ther obvious nor easy because of the emotional obstacles to
seeing danger when it is present in acquaintance situations.
Our findings show, however, that significant attention must
be paid to this kind of risk detection to achieve these dramatic
benefits. Finally, our findings demonstrate the importance of
creating a self-defense learning environment that directly
contradicts woman-blaming and rape myths.
In recent years, sexual violence prevention researchers
have come together in calling for universities to develop
comprehensive sexual violence prevention plans, including
both targeted and universal (bystander) prevention program-
ming to achieve meaningful change (e.g., Bonar et al., 2020;
Orchowski et al., 2018). By contrast, in the current political
climate with burgeoning roles and responsibilities and limited
resources, university administrators who are responsible for
developing prevention policies and staff in prevention roles
may feel pressured to offer a single, one-size fits all, online or
in person prevention program for students. The current study
provides compelling evidence to defend the implementation
of theoretically grounded, evidence-based prevention prac-
tices. The findings show the specific mechanisms by which
resistance education on campus works to empower women
and reduce the likelihood that they will experience sexual
violence. Specifically, offering sexual assault knowledge and
32 Psychology of Women Quarterly 45(1)
challenges to rape myths and perceptions that sexual violence
can only occur to others and not oneself lays the foundation
for effective education. However, this is not enough. Achiev-
ing large reductions in attempted and completed rape requires
that program content and practices build on this foundation
by improving risk detection in social interactions with
acquaintances, providing a context within which women can
safely identify and reduce emotional obstacles to risk detec-
tion and resistance, and increasing women’s repertoire of
effective strategies and confidence to interrupt and resist sex-
ual coercion and sexual assault attempts. Providing even
more benefit than we demonstrated may be possible through
enhanced programming; providing less is not defensible.
Conclusion
The chained multiple mediation analysis showed that the
hypothetical model underlying the EAAA program explains
the dramatic reductions in sexual violence experienced by
program participants. Sexual assault is not inevitable
(Bevacqua, 2000; Radtke et al., 2020). Empowering students
who identify as women with knowledge and skills and
providing a place and time for application and practice can
make a profound difference in their lives. Although we await
cultural change and interventions that can prevent sexual
violence perpetration reliably and substantially, resistance
education for women should be one critical piece of all com-
prehensive sexual assault prevention plans.
Authors’ Note
This study was registered with ClinicalTrials.gov (Identifier
NCT01338428). This article is based on data published in Senn
et al. (2015) and Senn et al. (2017). The trial protocol was published
in Senn et al. (2013).
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: The study
was supported by an Operating Grant from the Canadian Institutes
of Health Research (FRN 110976) and by the University of
Windsor.
ORCID iD
Charlene Y. Senn https://orcid.org/0000-0002-3463-5704
Notes
1. Rozee and Koss (2001) also suggested a new direction for pre-
vention for young men which has not been taken up to our
knowledge.
2. This represents the important half of the two parts of the opti-
mism bias, the gap between own and other estimates (optimism
bias). This gap is being narrowed for women in the program
group only (p < .001) by the improvement in women’s own
perception of risk (unpublished analysis). As such, it is appropri-
ate to connect this change to the optimism bias.
3. Reduction in other forms of sexual assault was also observed.
Due to space limitations, we focus on attempted and completed
oral, vaginal, and anal rape due to their greater impacts on
women’s mental and physical health.
4. There was no evidence of sleeper effects.
References
Abbey, A. (2011). Alcohol and dating risk factors for sexual assault:
Double standards are still alive and well entrenched. Psychology
of Women Quarterly, 35(2), 362–368. https://doi.org/10.
1177%2F0361684311404150
Anderson, R. E., Brouwer, A. M., Wendorf, A. R., & Cahill, S. P.
(2016). Women’s behavioral responses to the threat of a
hypothetical date rape stimulus: A qualitative analysis. Archive
of Sexual Behavior, 45(4), 793–805. https://link.springer.com/
article/10.1007/s10508-015-0682-2
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of
behavioral change. Psychological Review, 84(2), 191–215.
https://doi.org/10.1037/0033-295X.84.2.191
Banyard, V. L. (2013). Go big or go home: Reaching for a more
integrated view of violence prevention. Psychology of Violence,
3(2), 115–120. https://doi.org/10.1037/a0032289
Banyard, V. L., Moynihan, M. M., Cares, A. C., & Warner, R.
(2014). How do we know if it works? Measuring outcomes in
bystander-focused abuse prevention on campuses. Psychology of
Violence, 4(1), 101–115. https://doi.org/10:1037/a0033470
Banyard, V. L., & Potter, S. J. (2017). Envisioning comprehensive
sexual assault prevention for college campuses. In C. B. Travis &
J. W. White (Eds.), APA handbook of the psychology of women
(Vol. 2). American Psychological Association. https://doi.org/
10.1037/0000060-013
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator
variable distinction in social psychological research: Conceptual,
strategic, and statistical considerations. Journal of Personality
and Social Psychology, 51(6), 1173–1182. https://doi-org.led
proxy2.uwindsor.ca/10.1037/0022-3514.51.6.1173
Basile, K. C., DeGue, S., Jones, K., Freire, K., Dills, J., Smith, S. G.,
& Raiford, J. L. (2016). STOP SV: A technical package to pre-
vent sexual violence. www.cdc.gov/violenceprevention/pdf/sv-
prevention-technical-package.pdf
Bateman, P. (1978). Fear into anger: A manual of self-defence for
women. Nelson Hall.
Beal, D. J., & Dawson, J. F. (2007). On the use of Likert-type
scales in multilevel data: Influence on aggregate variables.
Organizational Research Methods, 10(4), 657–672. https://doi.
org/10.1177/1094428106295492
Bevacqua, M. (2000). Rape on the public agenda: Feminism and the
politics of sexual assault. Northeastern University Press.
Bohner, G., Eyssel, F., Pina, A., Siebler, F., & Viki, G. T. (2009).
Rape myth acceptance: Cognitive, affective and behavioral
effects of beliefs that blame the victim and exonerate the perpe-
trator. In M. Horvath & J. Brown (Eds.), Rape: Challenging
Senn et al. 33
contemporary thinking (pp. 17–45). Willan. https://doi.org/10.43
24/9781843927129
Bonar, E. E., DeGue, S., Abbey, A., Coker, A. L., Lindquist, C. H.,
McCauley, H. L., Miller, E., Senn, C. Y., Thompson, M. P., Ngo,
Q. M., Cunningham, R. M., & Walton, M. A. (2020). Prevention of
sexual violence among college students: Current challenges and future
directions. Journal of American College Health, 1–15. Advance
online publication. https://doi.org/10.1080/07448481.2020.1757681
Burgos Ochoa, L., Rijnhart, J. J., Penninx, B. W., Wardenaar, K. J.,
Twisk, J. W., & Heymans, M. W. (2020). Performance of meth-
ods to conduct mediation analysis with time-to-event outcomes.
Statistica Neerlandica, 74(1), 72–91. https://doi.org/10.1111/
stan.12191
Cermele, J. (2010). Telling our stories: The importance of women’s
narratives of resistance. Violence Against Women, 16(10),
1162–1172. https://doi.org/10.1177%2F1077801210382873
Conversano, C., Rotondo, A., Lensi, E., Della Vista, O., Arpone, F.,
& Reda, M. A. (2010). Optimism and its impact on mental and
physical well-being. Clinical Practice and Epidemiology in
Mental Health, 6, 25–29. https://doi.org/10.2174/17450179010
06010025
Cowan, G., & Campbell, R. R. (1995). Rape causal attitudes among
adolescents. The Journal of Sex Research, 32(2), 145–153.
https://doi.org/10.1080/00224499509551784
Davis, K. C., George, W. H., & Norris, J. (2004). Women’s
responses to unwanted sexual advances: The role of alcohol and
inhibition conflict. Psychology of Women Quarterly, 28(4),
333–343. https://doi.org/10.1111/j.1471-6402.2004.00150.x
DeGue, S., Simon, T. R., Basile, K. C., Yee, S. L., Lang, K., &
Spivak, H. (2012). Moving forward by looking back: Reflecting
on a decade of CDC’s work in sexual violence prevention,
2000–2010. Journal of Women’s Health, 21(12), 1211–1218.
https://doi.org/10.1089/jwh.2012.3973
DeGue, S., Valle, L. A., Holt, M. K., Massetti, G. M., Matjasko, J. L.,
& Tharp, A. T. (2014). A systematic review of primary prevention
strategies for sexual violence perpetration. Aggression and
Violent Behavior, 19(4), 346–362. https://doi.org/10.1016/j.avb.
2014.05.004
Des Jarlais, D. C., Lyles, C., & Crepaz, N., & the Trend Group.
(2004). Improving the reporting quality of nonrandomized eva-
luation of behavioral and public health interventions: The
TREND statements. American Journal of Public Health, 94(3),
361–366. https://doi.org/10.2105/AJPH.94.3.361
Ellsberg, M., Arango, D. J., Morton, M., Gennari, F., Kiplesund, S., Con-
treras, M., & Watts, C. (2015). Prevention of violence against women
and girls: What does the evidence say? The Lancet, 385(9977),
1555–1566. https://pubmed.ncbi.nlm.nih.gov/25467575/
Fenton, R. A., Mott, H. L., McCartan, K., & Rumney, P. N. S.
(2016). A review of evidence for bystander intervention to
prevent sexual and domestic violence in universities. Public
Health England. https://eprints.uwe.ac.uk/28656/1/PHE_Publish
edLitReviewApr2016.pdf
Fine, M. (1988). Sexuality, schooling, and adolescent females: The
missing discourse of desire. Harvard Educational Review, 58(1),
29–53. https://doi.org/10.17763/haer.58.1.u0468k1v2n2n8242
Fine, M., & McClelland, S. I. (2006). Sexuality education and
desire: Still missing after all these years. Harvard Educational
Review, 76(3), 297–338. https://doi.org/10.17763/haer.76.3.
w5042g23122n6703
Fishbein, M., & Ajzen, I. (2011). Predicting and changing behavior:
The reasoned action approach. Taylor & Francis. https://doi.org/
10.4324/9780203838020
Gavey, N. (2005). Just sex? The cultural scaffolding of rape.
Routledge. https://doi.org/10.4324/9780429443220
Gidycz, C. A., McNamara, J. R., & Edwards, K. M. (2006).
Women’s risk perception and sexual victimization: A review
of the literature. Aggression and Violent Behavior, 11(5),
441–456. https://doi.org/10.1016/j.avb.2006.01.004
Gidycz, C. A., Rich, C. L., & Marioni, N. L. (2002). Interventions to
prevent rape and sexual assault. In J. Petrak & B. Hedge (Eds.),
The trauma of adult sexual assault: Treatment, prevention and
policy (pp. 235–259). Wiley.
Gidycz, C. A., Rich, C. L., Orchowski, L., King, C., & Miller, A. K.
(2006). The evaluation of a sexual assault self-defense and
risk-reduction program for college women: A prospective study.
Psychology of Women Quarterly, 30(2), 173–186. https://doi.
org/10.1111%2Fj.1471-6402.2006.00280.x
Goldfarb, E. S., & Casparian, E. M. (2000). Our whole lives: Sexu-
ality education for grades 10—12. Unitarian Universalist
Association.
Gordon, M. T., & Riger, S. (1989). The female fear: The social cost
of rape. The Free Press.
Gray, M. D., Lesser, D., Quinn, E., & Brounds, C. (1990). The
effectiveness of personalizing acquaintance rape prevention:
Programs on perception of vulnerability and on reducing risk-
taking behavior. Journal of College Student Development, 31(3),
217–220.
Hoffmann, T. C., Glasziou, P. P., Boutron, I., Milne, R., Perera, R.,
Moher, D., Altman, D. G., Barbour, V., Macdonald, H., & John-
ston, M. (2014). Better reporting of interventions: Template for
intervention description and replication (TIDieR) checklist and
guide. British Medical Journal, 348, g1687. https://doi.org/10.
1136/bmj.g1687
Hollander, J. A. (2004). I can take care of myself—The impact of
self-defense training on women’s lives. Violence Against
Women, 10(3), 205–235. https://doi.org/10.1177/1077801203
256202
Hollander, J. A. (2014). Does self-defense training prevent sexual
violence against women? Violence Against Women, 20(3),
252–269. https://doi.org/10.1177/1077801214526046
Hollander, J. A. (2016). The importance of self-defense training for
sexual violence prevention. Feminism & Psychology, 26(2),
207–226. https://doi.org/10.1177/0959353516637393
Hollander, J. A. (2018). Empowerment self-defense. In L. M.
Orchowski & C. A. Gidycz (Eds.), Sexual assault risk reduction
and resistance (pp. 221–244). Elsevier. https://doi.org/10.1016/
b978-0-12-805389-8.00011-6
Hollander, J. A., & Rodgers, K. (2014). Constructing victims: The
erasure of women’s resistance to sexual assault. Sociological
Forum, 29(2), 342–364. https://doi.org/10.1111/socf.12087
34 Psychology of Women Quarterly 45(1)
Hollway, W. (1984). Women’s power in heterosexual sex. Women’s
Studies International Forum, 7(1), 63–68. https://doi.org/10.
1016/0277-5395(84)90085-2
Kimball, R. S., & Frediani, J. (2000). Our whole lives: Sexuality
education for adults. Unitarian Universalist Association.
Klein, L. B., Rizzo, A. J., Cherry, L. H., & Woofter, R. C. (2018).
Addressing alcohol’s role in campus sexual assault: A toolkit by
and for prevention specialists. Campus Advocacy and Preven-
tion Professionals Association and Prevention Innovations
Research Center. https://cola.unh.edu/sites/cola.unh.edu/files/
media/SAAlcToolkit
Koss, M. P., Abbey, A., Campbell, R., Cook, S., Norris, J., Testa, M.,
Ullman, S. E., West, C., & White, J. (2007). Revising the SES:
A collaborative process to improve assessment of sexual aggres-
sion and victimization. Psychology of Women Quarterly, 31(4),
257–270. https://doi.org/10.1111/j.1471-6402.2007.00385.x
Krebs, C. P., Lindquist, C. H., Warner, T. D., Fisher, B. S., &
Martin, S. L. (2009). College women’s experiences with physi-
cally forced, alcohol- or other drug-enabled, and drug-facilitated
sexual assault before and since entering college. Journal of
American College Health, 56(6), 639–647. https://doi.org/10.3
200/JACH.57.6.639-649
Lonsway, K. A., Banyard, V. L., Berkowitz, A. D., Gidycz, C. A.,
Katz, J. T., Koss, M. P., Schewe, P. A., & Ullman, S. E. (2009,
January). Rape prevention and risk reduction: Review of the
research literature for practitioners. VAWnet: A Project of the
Online Resource Center on Violence Against Women. https://
vawnet.org/sites/default/files/materials/files/2016-09/AR_Eva
luationCampusProgramming.pdf
MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation
analysis. Annual Review of Psychology, 58, 593–614. https://doi.
org/10.1146/annurev.psych.58.110405.085542
Macy, R. J., Nurius, P. S., & Norris, J. (2006). Responding in their
best interests: Contextualizing women’s coping with acquain-
tance sexual aggression. Violence Against Women, 12(5),
478–500. https://doi.org/10.1177/1077801206288104
Macy, R. J., Nurius, P. S., & Norris, J. (2007). Latent profiles among
sexual assault survivors: Implications for defensive coping and
resistance. Journal of Interpersonal Violence, 22(5), 543–565.
https://doi.org/10.1177/0886260506298841
Marx, B. P., Calhoun, K. S., Wilson, A. E., & Meyerson, L. A.
(2001). Sexual revictimization prevention: An outcome evalua-
tion. Journal of Consulting and Clinical Psychology, 69(1),
25–32. https://doi.org/10.1037//0022-006x.69.1.25
Messman-Moore, T. L., & Brown, A. L. (2006). Risk perception,
rape and sexual revictimization: A prospective study of college
women. Psychology of Women Quarterly, 30(2), 159–172.
https://doi.org/10.1111/j.1471-6402.2006.00279.x
Morrison, S., Hardison, J., Mathew, A., & O’Neil, J. (2004). An
evidence-based review of sexual assault preventive intervention
programs (Technical Report No. 207262). U.S. Department of
Justice. https://www.ncjrs.gov/pdffiles1/nij/grants/207262.pdf
Nation, M., Crusto, C., Wandersman, A., Kumpfer, K. L., Seybolt, D.,
Morrissey-Kane, E., & Davino, K. (2003). What works in
prevention: Principles of effective prevention programs.
American Psychologist, 58(6–7), 449–456. https://doi.org/10.
1037/10455-005
Norris, J., Nurius, P. S., & Dimeff, L. A. (1996). Through her eyes:
Factors affecting women’s perception of and resistance to
acquaintance sexual aggression threat. Psychology of Women
Quarterly, 20(1), 123–145. https://doi.org/10.1111/j.1471-6402.
1996.tb00668.x
Norris, J., Nurius, P. S., & Graham, T. L. (1999). When a date
changes from fun to dangerous: Factors affecting women’s abil-
ity to distinguish. Violence Against Women, 5(3), 230–250.
https://doi.org/10.1177/10778019922181202
Norris, J., Zawacki, T., Cue Davis, K., & George, W. H. (2018). The
role of psychological barriers in women’s resistance to sexual
assault by acquaintances. In L. M. Orchowski & C. A. Gidycz
(Eds.), Sexual assault risk reduction and resistance (pp. 87–110).
Elsevier. https://doi.org/10.1016/b978-0-12-805389-8.00005-0
Nurius, P. S. (2000). Risk perception for acquaintance sexual
aggression: A social-cognitive perspective. Aggression and Vio-
lent Behavior, 5(1), 63–78. https://doi.org/10.1016/S1359-
1789(98)00003-2
Nurius, P. S., & Norris, J. (1996). A cognitive ecological model of
women’s response to male sexual coercion in dating. Journal of
Psychology and Human Sexuality, 8(1–2), 117–139. https://doi.
org/10.1300/J056v08n01_09
Nurius, P. S., Norris, J., Macy, R. J., & Huang, B. (2004). Women’s
situational coping with acquaintance sexual assault: Applying an
appraisal-based model. Violence Against Women, 10(5),
450–478. https://doi.org/10.1177/1077801204264367
Orchowski, L. M., Edwards, K. M., Hollander, J. A., Banyard, V. L.,
Senn, C. Y., & Gidycz, C. A. (2018). Integrating sexual assault
resistance, bystander and men’s social norms strategies to
prevent sexual violence on college campuses: A call to action.
Journal of Trauma, Violence, & Abuse, 21(4), 811–827. https://
doi.org/10.1177/1524838018789153
Orchowski, L. M., & Gidycz, C. A. (2018). Sexual assault risk
reduction and resistance. Elsevier. https://doi.org/10.1016/
C2015-0-04668-8
Orchowski, L. M., Gidycz, C. A., & Murphy, M. (2010). Preventing
campus-based sexual violence. In K. L. Kaufman (Ed.), The
prevention of sexual violence: A practitioner’s sourcebook
(pp. 415–448). NEARI Press.
Ozer, E. M., & Bandura, A. (1990). Mechanisms governing empow-
erment effects: A self-efficacy analysis. Journal of Personality
and Social Psychology, 58(3), 472–486. https://doi.org/10.1037/
0022-3514.58.3.472
Parks, K. A., Levonyan-Radloff, K., Dearing, R. L., Hequembourg, A.,
& Testa, M. (2016). Development and validation of a video mea-
sure for assessing women’s risk perception for alcohol-related sex-
ual assault. Psychology of Violence, 6(4), 573–585. https://doi.org/
10.1037/a0039846
Payne, D. L., Lonsway, K. A., & Fitzgerald, L. F. (1999). Rape myth
acceptance: Exploration of its structure and its measurement
using the Illinois Rape Myth Acceptance Scale. Journal of
Senn et al. 35
Research in Personality, 33(1), 27–68. https://doi.org/10.1006/
jrpe.1998.2238
Pinnock, H., Barwick, M., Carpenter, C. R., Eldridge, S., Grandes,
G., Griffiths, C. J., Rycroft-Malone, J., Meissner, P., Murray, E.,
& Patel, A. (2017). Standards for reporting implementation stud-
ies (StaRI) statement. British Medical Journal, 356, i6795.
https://dx.doi.org/10.1136/bmjopen-2016-013318
Piran, N. (2016). Embodied possibilities and disruptions: The emer-
gence of the Experience of Embodiment construct from qualita-
tive studies with girls and women. Body Image, 18, 43–60.
https://doi.org/10.1016/j.bodyim.2016.04.007
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures
for estimating indirect effects in simple mediation models. Beha-
vior Research Methods, Instruments, & Computers, 36(4),
717–731. https://doi.org/10.3758/BF03206553
Radtke, H. L., Barata, P. C., Senn, C. Y., Thurston, W. E., Hobden, K. L.,
Newby-Clark, I., & Eliasziw, M. (2020). Countering rape culture
with resistance education. In D. Crocker, J. Minaker, & A. Nelund
(Eds.), Violence interrupted: Confronting sexual violence on univer-
sity campuses (pp. 349–370). McGill-Queen’s University Press.
Rozee, P. D., Bateman, P., & Gilmore, T. (1991). The personal
perspective of acquaintance rape prevention: A three-tier
approach. In A. Parrot & L. Bechhofer (Eds.), Acquaintance
rape: The hidden crime (pp. 337–354). John Wiley & Sons.
https://doi.org/10.1192/s0007125000036424
Rozee, P. D., & Koss, M. P. (2001). Rape: A century of resistance.
Psychology of Women Quarterly, 25(4), 295–311. https://doi.
org/10.1111/1471-6402.00030
Salazar, L. F., Vivolo-Kantor, A., & Schipani-McLaughlin, A. M.
(2019). Theoretical mediators of RealConsent: A web-based sex-
ual violence prevention and bystander education program.
Health Education & Behavior, 46(1), 79–88. https://doi.org/10.
1177/1090198118779126
Schewe, P. A. (2002). Guidelines for developing rape prevention
and risk reduction interventions. In P. A. Schewe (Ed.), Prevent-
ing violence in relationships (pp. 107–136). American Psycho-
logical Association. https://doi.org/10.1037/10455-005
Schulz, K. F., Altman, D. G., & Moher, D. (2010). CONSORT 2010
statement: Updated guidelines for reporting parallel group ran-
domised trials. BMC Medicine, 11(32), 1–8. https://doi.org/10.
1186/1745-6215-11-32
Senn, C. Y., Barata, P. C., Eliasziw, M., Hobden, K. L., Radtke, H. L.,
Thurston, W. E., & Newby-Clark, I. R. (in press). Sexual assault
resistance education’s benefits for survivors of attempted and
completed rape. Women and Therapy.
Senn, C. Y., Eliasziw, M., Barata, P. C., Thurston, W. E., Newby-
Clark, I. R., Radtke, H. L., & Hobden, K. L. (2013). Sexual assault
resistance education for university women: Study protocol for a
randomized controlled trial (SARE trial). BMC Women’s Health,
13(25), 1–13. https://doi.org/10.1186/1472-6874-13-25
Senn, C. Y., Eliasziw, M., Barata, P. C., Thurston, W. E., New-
by-Clark, I. R., Radtke, H. L., & Hobden, K. L. (2015). Efficacy
of a sexual assault resistance education program for university
women. New England Journal of Medicine, 372(4), 2326–2335.
http://www.nejm.org/doi/full/10.1056/NEJMsa1411131
Senn, C. Y., Eliasziw, M., Hobden, K. L., Newby-Clark, I. R.,
Barata, P. C., Radtke, H. L., & Thurston, W. E. (2017). Second-
ary and 2-year outcomes of a sexual assault resistance program
for university women. Psychology of Women Quarterly, 41(2),
147–162. https://doi.org/10.1177/0361684317690119
Senn, C. Y., Gee, S. S., & Thake, J. (2011). Emancipatory sexuality
education and sexual assault resistance: Does the former enhance
the latter? Psychology of Women Quarterly, 35(1), 72–91.
https://doi.org/10.1177/0361684310384101
Senn, C. Y., Hollander, J. A., & Gidycz, C. A. (2018). What works?
Critical components of effective sexual violence interventions
for women on college and university campuses. In L. M. Orch-
owski & C. Gidycz (Eds.), Sexual assault risk reduction and
resistance (pp. 245–289). Academic Press. https://doi.org/10.
1016/C2015-0-04668-8
Stanko, E. A. (1990). When precaution is normal: A feminist cri-
tique of crime prevention. In L. Gelsthrope & A. Morris (Eds.),
Feminist perspectives in criminology: Women & criminal justice
(Vol. 2., pp. 3–26). https://doi.org/10.1300/J012v02n02_02
Stoner, S. A., Norris, J., George, W. H., Davis, K. C., Masters, T. N.,
& Hessler, D. M. (2007). Effects of alcohol intoxication and
victimization history on women’s sexual assault resistance inten-
tions: The role of secondary cognitive appraisals. Psychology of
Women Quarterly, 31(4), 344–356. https://doi.org/10.1111%2Fj.
1471-6402.2007.00384.x
Tark, J., & Kleck, G. (2014). Resisting rape the effects of victim self-
protection on rape completion and injury. Violence Against Women,
20(3), 270–292. https://doi.org/10.1177/1077801214526050
Testa, M., VanZile-Tamsen, C., & Livingston, J. A. (2006). The role
of women’s alcohol consumption in managing sexual intimacy
and sexual safety motives. Journal of Studies on Alcohol, 67(5),
1–10. https://doi.org/10.15288/jsa.2006.67.665
Ullman, S. E. (1997). Review and critique of empirical studies of
rape avoidance. Criminal Justice and Behavior, 24(2), 177–204.
https://doi.org/10.1177/0093854897024002003
Ullman, S. E. (1998). Does offender violence escalate when rape
victims fight back? Journal of Interpersonal Violence, 13(2),
179–192. https://doi.org/10.1177/088626098013002001
Vitek, K. N., Lopez, G., Ross, R., Yeater, E. A., & Rinehard, J. K.
(2018). Women’s appraisals of victimization risk: Current status,
methodological challenges, and future directions. In L. M.
Orchowski & C. A. Gidycz (Eds.), Sexual assault risk reduction
and resistance (pp. 67–86). Elsevier. https://doi.org/10.1016/
b978-0-12-805389-8.00004-9
Wen-Do Women’s Self Defence. (n.d.). www.wendo.ca
Women Against Rape. (1980). “Community action strategies to stop
rape”: A rape prevention program in an urban area. Signs:
Journal of Women in Culture & Society, 5(3), S238–S241.
https://doi.org/10.1086/495724
Yeater, E. A., Treat, T. A., Viken, R. J., & McFall, R. M. (2010).
Cognitive processes underlying women’s risk judgments: Asso-
ciations with sexual victimization history and rape myth accep-
tance. Journal of Consulting and Clinical Psychology, 78(3),
375–386. https://doi.org/10.1037/a0019297
36 Psychology of Women Quarterly 45(1)
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