Peer Education 1
Running head: PEER EDUCATION
Intervention Deliveries: The Role of Peer Educators in Reducing High-risk Drinking Among
First-year Students
Matthew J. Mayhew, New York University
Rebecca Caldwell, University of North Carolina Wilmington
Aimee Hourigan, University of North Carolina Wilmington
Annie W. Bezbatchenko, New York University
Michael Fried, New York University
Please direct all correspondence to Dr. Matt J. Mayhew, 239 Greene Street, Suite 300, New York
University, New York, NY 10012.
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Abstract
The purpose of this paper is to examine the differences between peer educators and student
affairs professional staff on presenting interventions designed to reduce high-risk drinking
among first-year students. The intervention involved an hour-long classroom presentation
exposing students to an educational video with gender-specific content related to alcohol
expectancies and behaviors, followed by facilitated discussions probing students’ gender-specific
issues and the relationship between these issues and the students’ own alcohol use. The
discussions were facilitated either by peer educators or professional staff, each trained with the
same set of materials, which was a process intended to isolate the effects of intervention delivery
- peers versus professional staff - on student high-risk drinking behaviors. We found that, at the
end of the semester, students enrolled in the courses receiving the intervention from peers
reported reductions in high-risk drinking behaviors to a greater degree than both students
enrolled in the courses receiving the intervention from professional staff and those students
receiving no intervention at all.
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Intervention Deliveries: The Role of Peer Educators in Reducing High-risk Drinking Among
First-year Students
University stakeholders are often challenged with creating educational environments
optimized for helping students achieve desired learning outcomes. As part of this process,
educators rely heavily on college impact research, which underscores the importance of
designing learning contexts that enable students to learn from their peers (e.g., Pascarella &
Terenzini, 2005) The effects of peers on helping students learn are so powerful that co-curricular
educators have allocated resources toward hiring and developing programs for training peer
educators. In short, peer education involves the “offering of credible and reliable information
about sensitive life issues” (Topping & Ehly, 1998, p. 7) by “people who are not professionally
trained educators but whose goal is to educate” (Finn, 1981, p. 91). Despite the growing number
of peer education programs across the country (Ender & Newton, 2000; Turner & Shepherd,
1999; Wawrzynski, 2009), their efficacy in influencing student behaviors has rarely been the
subject of scholarly pursuits that include an experimental longitudinal research design, which
would enable researchers to empirically link peer education to student learning. The purpose of
this study is to examine the efficacy of peer educators in helping first-year-students reduce their
high-risk drinking behaviors.
It is imperative that institutions of higher education use effective, evidence-based
strategies to addressing high-risk drinking behavior, including sanctions for underage student
use of alcohol and educational interventions designed to address high-risk binge drinking.
While the literature on these interventions vary across a number of design features, including
content (Baer, Kivlahan, Blume, McKnight, & Marlatt, 2001; Chiauzzi, Green, Lord, Thum, &
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Goldstein, 2005; Fournier, Ehrhart, Glindemann, & Geller, 2004; Jewell, Hupp, & Luttrell, 2004;
Maney, Theodorou, & Vasey, 2001; Neighbors, Larimer, & Lewis, 2004; Stamper, Smith, Gant,
& Bogle, 2004; Werch, et al., 2000), audience (Baer, et al., 2001; Elkins, Helms, & Pierson,
2003; Fournier, et al., 2004; Sheffield, Darkes, Del Boca, & Goldman, 2005), and mode of
delivery (Fournier, et al., 2004; McNally & Palfai, 2003; Moore, Soderquist, & Werch, 2005;
Walters, Bennett. Melanie, & Miller, 2000), few studies have employed experimental designs for
empirically assessing how the efficacy of interventions differs between student affairs
professional staff and peer educators.
Most of the research that has interrogated peer education has focused on the impact of the
peer education experience on the peer educator rather than on the targeted group of students
(Annis, 1983; Badura, Millard, Peluso, & Ortman, 2000; Benjamin, 2004; Chesler, Galura, Ford,
& Charbeneau, 2006; Ebreo, Feist-Price, Siewe, & Zimmerman, 2002; Khera, 1995). This is
somewhat surprising given the scope of these studies, ranging from peer education addressing
health issues in general (Li, et al., 2009; Mathie & Ford, 1998; Turner & Shepherd, 1999) to
specific topics such as nutrition (Buller, et al., 1999; Pérez-Escamilla, Hromi-Fiedler, BermúdezMillán, & Segura-Pérez, 2008), sexual health (Backett-Milburn & Wilson, 2000; Forrest,
Strange, & Oakley, 2002; Freeman, 2001) and substance abuse (Fromme & Corbin, 2004;
Harrin, 1997; Mastroleo, Mallett, Ray, & Turrisi, 2008). This study marks a departure from
previous efforts in its emphasis on understanding the role of peer educators and their influence
on reducing high-risk drinking behaviors among first-year students.
This study examines the differences in reported high-risk drinking behaviors among
students in first-year success courses that vary in their approach to delivering intervention
messages. The examined intervention included an hour-long classroom presentation exposing
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students to an educational video with gender-specific content related to alcohol expectancies and
behaviors, followed by facilitated discussions probing students’ gender-specific issues and the
relationship of these issues to the students’ own alcohol use. The discussions were facilitated
either by peer educators or professional staff, using the same intervention script, which was a
process intended to isolate the effects of intervention delivery - peers versus professional staff on student high-risk drinking behaviors.
Fourteen first-year seminar courses were studied: four enrolled students that received the
intervention from professional staff; four enrolled students that received the intervention from
peer educators; and the remaining six enrolled courses that received no intervention. The
treatment was randomized across this pool of fourteen courses, meaning four courses were
randomly chosen to receive the intervention by professional staff; four were randomly chosen to
receive the treatment from peer educators; and six were randomly chosen to serve as the control
group.
High-risk drinking was assessed through a series of items related to quantity and
frequency of use within certain time periods: 1) “Think back over the last two weeks, how many
times did you have five or more alcoholic drinks at a sitting?” 2) “How many drinks do you have
on average when you go out/party/socialize with other students?” 3) “How many drinks do you
consume in an average week?” 4) “During the last 30 days, on how many days did you consume
alcohol?” (Presley, Meilman, & Lyerla, 1994). We analyzed these items in the aggregate to
define our criterion, which was engagement in high-risk drinking behaviors; other studies (see
Mayhew, Caldwell, & Hourigan, 2008) have adopted a similar approach when examining these
behaviors. We anticipate that this study will be an important empirical first step for helping co-
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curricular educators justify hiring and training peer educators to deliver high-risk drinking
prevention messages to first-year students.
Theoretical Overview
We adopted a multi-pronged approach to reviewing the literature on peer education and
its effects on reducing high-risk drinking among first-year undergraduate students. First, we
examined social learning theories posited for explaining why peer education, as a form of
teaching and learning, works. Second, we turned to empirical studies of peer education and its
role in influencing a variety of behaviors, including those associated with wellness such as highrisk drinking. Third, we reviewed studies that specifically interrogated peer education by
examining peer learning as a result of delivery mode, particularly focusing on studies with
research designs that compared peers to professional staff.
Theoretical Orientation
There is no clear theoretical consensus supporting the use of peer educators, although
most programs evaluated in the literature do reference theories relating to social learning or
motivation (Topping & Ehly, 1998; Turner & Shepherd, 1999; Wight, 2008). Commonly cited
theories from the field of health promotion include 1) social learning theory (Benjamin, 2004;
McKegarney & Barnard, 1992; Peck, Cooke, & Apolloni, 1981; Wilton, Keeble, Doyal, &
Walsh, 1995), 2) social inoculation theory (Duryea, 1983; McGuire, 1964, 1974) and 3)
differential association theory (Sutherland & Cressey, 1974). Although a full review of these
theories is beyond the scope of this paper, their shared elements explain why peer education
works, that is, how peers help other students learn the information needed to affect behavior.
Across the three theories (see Benjamin, 2004; Duryea, 1983; McGuire, 1964, 1968;
McKegarney & Barnard, 1992; Peck, et al., 1981; Sutherland & Cressey, 1974; Wilton, et al.,
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1995) most frequently cited for explaining the efficacy of peer education in influencing student
behavior (Milburn, 1995; Turner & Shepherd, 1999), it appears as though individuals learn from
others through the process of modeling. Essentially, observed behaviors, when accompanied by
opportunities to engage in those behaviors, leads to a change in action, if positive reinforcement
is provided. When applied to peer health education settings, students assume that their peers not
only care about health-related behaviors, but enact them by taking positions as peer educators;
these assumptions underscore what Milburn (1995) calls “peer pressure resistance training” (p.
408). Undergirding these approaches is the Bandurian notion that peer educators need to be
perceived as “credible” (Turner & Shepherd, 1999, p. 237) for effective role modeling to occur1.
In an effort to understand that credibility, Brack et al. (2008) established that peer educators are
not substantively different from the students with whom they work. With regard to high-risk
drinking, students will not learn from their peers if they are perceived as hypocritical, which
would result from the peer educators engaging in high-risk drinking behaviors while advocating
for others not to do so.
Literature Review on Peer Education
Studies examining the efficacy of peer educators on changing behavior demonstrate that
peer-led interventions are effective across a variety of populations and content areas. For
example, in Buller et. al.’s (1999) study of over 2000 low-income, multicultural adults working
together in labor setting, he found that peer education was effective in increasing the healthy
nutritional habit of eating more fruits and vegetables. Similarly, Mathie and Ford (1998) describe
two peer education efforts in the United Kingdom addressing HIV/AIDS education with older
teens. In both cases, the educational outcomes for the teen participants were positive and
Peer Education 8
measurable. The researchers caution, however, that many other project evaluations have not
demonstrated similar changes in participant behavior.
These generally positive results are also reflected in the few studies connecting peer
education to outcomes related to alcohol use in a college or university setting. For example, in a
longitudinal study of 2,000 randomly selected undergraduate students at University of California,
Santa Barbara, White, Park, Israel and Cordero (2009) found that students who had had contact
with a peer educator eventually plateaued in their consumption of alcohol while the alcohol use
of those students who did not have such contact continued to rise. In another example, Freeman
(2001) described an alcohol intervention planned in connection with the campus counseling
center at Rollins College that was aimed at students who had been sanctioned through the
campus judicial system. The intervention relied on a small-group experience in which a peer
educator would lead the sanctioned students through a reflective examination of values and
behaviors related to alcohol use. Sanctioned students who completed the peer intervention
program demonstrated a 9% recidivism rate for alcohol violations, representing a 50% decrease
in repeat alcohol offenses for the campus. Despite these select cases of effective and successfully
evaluated peer education programs, there continue to be calls for greater rigor in the evaluation
of such programs (Mastroleo, et al., 2008).
Other studies have compared peer-led educational efforts to professionally-facilitated
efforts. In a review of 13 different studies comparing the efficacy of peer educators vis-à-vis
professionals, Mellanby, Rees and Tripp (2000) concluded that peer educators are at least as
capable as professionals; however, methodological weaknesses in the studies reviewed included,
but were not limited to, a lack of clarity about the training received by educators and failure to
include information on effect size. Forrest et al. (2002) found differences between peer
Peer Education 9
educators and professional teachers in a study of 7,700 secondary school students participating in
a sex-education program in the United Kingdom. Respondents found the peer-led program to be
more satisfying, engaging and useful than the teacher-led programs, although students from both
groups reported learning from the program.
A limited number of studies have examined the differential success of peer educators and
professionals in addressing alcohol use and abuse in a college or university environment, usually
in the context of a judicial response. Fromme and Corbin (2004) examined the effect of a
Lifestyle Management Course (LMC) in reducing drinking episodes in college students. While
the LMC proved to be an effective intervention, there was no difference in efficacy between
students who had a peer or professional facilitator. Likewise, a study of first-year fraternity
members participating in a brief alcohol-use reduction intervention conducted by a peer or by a
professional researcher showed an overall positive impact for the intervention one year later, but
no difference between those who worked with a peer educator or a professional (Larimer, et al.,
2001).
While there are a few reports specifically examining the use of peer educators in firstyear seminar courses (Hamid, undated; Marsh & Friedman, 2009), these studies are practiceoriented pieces that have not appeared in peer-reviewed literature. This, of course, limits their
utility in informing this study’s design. Thus, this study departs from and extends the body of
work on peer education in many ways, enabling causal claims to be made concerning the effects
of peer education on reported high-risk drinking behaviors. First, we designed a longitudinal,
experimental study to investigate the efficacy of peer education on influencing high-risk drinking
among first-year students. By randomly assigning treatment conditions (professional versus peer
versus none) to students enrolled in first-year seminars, we were able to empirically link mode of
Peer Education 10
delivery to reported high-risk drinking behaviors. Second, because students did not enroll in
first-year seminars based on prior knowledge that there would be a presented alcohol
intervention or how this intervention would be delivered, we were able to execute a study that, as
part of its design, addressed selection bias often introduced by studying students in their natural,
albeit non-random learning environments. Third, by using the same intervention byboth
professional staff and peer educators, we were able to speak to the validity of treatment:
observed effects in high-risk drinking were likely due to mode of delivery (peer vs. professional)
rather than the intervention.
Method
We hypothesize that students exposed to the peer-led intervention will be the most likely
to report reductions in high-risk drinking behaviors than either students exposed to the
intervention facilitated by professional staff or those not exposed to an intervention at all. An
auxiliary hypothesis is that students exposed to the intervention facilitated by professional staff
will be more likely to report fewer high-risk drinking behaviors than those students not exposed
to an intervention at all.
Sample
In the fall semester of 2009, seventy percent of first-year students within the institution
under examination were enrolled in University 101 (UNI 101), a first-year seminar. Fourteen
UNI 101 instructors agreed to allow the alcohol prevention and evaluation team to longitudinally
assess their students through the use of two theoretically-derived and empirically-validated
instruments (discussed below) and to present the intervention to their students. Interventions
were randomly delivered to students enrolled in one of these fourteen seminars: four courses
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with interventions presented by peers, four with interventions presented by professional staff,
and the remaining six with no intervention presented at all.
Students were enrolled in a first-year success course during the fall 2009 semester and
were administered the assessments in the first and last week of the course. The response rate for
the entire sample reached 92.86%, with 320 of 350 students providing responses to pre or
posttest assessments.
To increase accuracy of reported findings, we adopted a conservative approach to
approaching missing data. Only students who provided information on pre and posttests were
included in the analytic sample. Thirty-five students provided only pretest information and an
additional 22 students provided only posttest information. Thus, data from 263 of a possible 320
students were used to calculate our longitudinal response rate of 75.14%.
Because our study specifically focused on high-risk drinking, we analyzed only those
students who engaged in high-risk drinking behaviors. Assessment of these behaviors were based
on the Harvard School of Public Health’s controversial but widely recognized measure of “binge
drinking,” defined at 5 drinks in one sitting for men and 4 drinks in one sitting for women in the
past two weeks (Weschler, Dowdall, Davenport, & Rimm, 1995). At the time of pretesting, any
student who responded that he or she had never had five or more alcoholic drinks at a sitting
within the last two weeks was discarded from the sample. Therefore, an additional 135 students
were purged from the sample.
The analytic sample contained a total of 128 high-risk students, distributed across firstyear success courses. Seventy of these students were enrolled in the courses that received no
intervention; 19 students were enrolled in courses that received the professionally-led
intervention; and the remaining 30 students were enrolled in the courses that received the peer-
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led intervention. Students enrolled in the courses that received the interventions resembled those
students enrolled in the control courses across a number of demographic variables. See Table 1
for descriptions of the student characteristics by delivery mode: intervention presented by
professional, peer, or not at all.
Context for the Study
The [information deleted for blind review] is a mid-size university, enrolling 10,711
undergraduate and 1,200 graduate students. It is one of the 16 public institutions within the
University System [information deleted for blind review] and is located on the southeastern coast
of [information deleted for blind review] within a small city of approximately 75,000 residents.
Nearly three in five (58%) [information deleted for blind review] students are female, and 89%
of students are white.
Students enrolled at [information deleted for blind review] tend to engage in more highrisk drinking behaviors than their counterparts at other colleges and universities. In 2009, 237
female and 104 male students took a comprehensive assessment that measured their experiences
with and perceptions of alcohol on campus. The assessment’s results indicated that binge
drinking rates were 62.5% for male and 42.2% for females. The results from the assessment also
showed that students reported experiencing negative consequences related to their drinking. Such
consequences ranged from experiencing a hangover (52.4%) to driving while under the influence
of alcohol (16.3%). Not surprisingly, significantly more males than females report consequences
from drinking. However, men and women experience also different types of consequences and
use different types of protective strategies when they drink. For example, men are more likely to
attend class hungover than women (33.7% versus 19.4%) and women are more likely to keep
track of number of drinks than men (74.7% versus 51.7%). This finding suggests the need to
Peer Education 13
consider gender in the development of curricular-based interventions designed to reduce
outcomes related to high-risk drinking.
For over two decades, the university has worked to educate students about substance
abuse and prevention through a department with dedicated resources, including staff positions.
The department is dedicated to a harm reduction approach including a non-use message, an
assessment culture, and collaborating with on and off-campus partners to address substance
abuse from an environmental management perspective. Educating a student group of peer
educators is an important part of the department’s work.
Description of the Intervention
Each year, incoming students take first-year seminar courses on various topics with the
aim of familiarizing students with campus resources and easing their transition to the campus
environment. These seminar courses are highly recommended by first-year advisors;
approximately 70% of new students enroll in these courses. Instructors range from tenured
faculty to academic advisors to university staff from student affairs, library, and other
departments on campus. Alcohol and drug abuse is one of the required sessions2; approximately
half of the instructors invite the alcohol and drug prevention professionals to make this
presentation. When invited, the substance abuse and prevention department either sends a peer
educator or student affairs professional staff member to lead the session.
This alcohol and drug abuse session is designed specifically to cover issues of gender
roles and how they contribute to high-risk drinking. During this session, three segments of
Ridberg’s (2004) Spin the Bottle: Sex, Lies, and Alcohol featuring Jackson Katz and Jean
Kilbourne are shown. These segments serve as the basis for the curricular-based intervention.
This video was selected because it presents both male- and female-specific issues and also
Peer Education 14
features students appropriately modeling how to discuss personal issues, such as peer pressure,
alcohol, and sexual behavior.
Through this video, Katz and Kilbourne offer a critique of the role that contemporary
popular culture plays in glamorizing excessive drinking and high-risk behaviors by contrasting
these hyperbolic representations with the ways that alcohol consumption affects the lives of real
young men and women. The video puts forth numerous media illustrations in an effort to show
students how these media images shape gender identity and how this relationship is linked to
alcohol use. Interviews with campus health professionals and students shown in the video
provide a clear picture of how drinking impacts student health and academic performance. Spin
the Bottle concludes with strategies for countering the ubiquitous presence of alcohol propaganda
and encourages young people to make conscious, deliberate decisions about their own lives.
After students screen the video, either peer educators or personnel from the department
facilitate a discussion with the first-year students, specifically probing the gender-specific issues
regarding alcohol use. Additional didactic information is covered, including how to identify
alcohol poisoning, how alcohol affects men's and women's bodies, signs of addiction, how to
help a friend, and other signs of drug abuse.
Description of the Training
Peer educators co-facilitate this curricular-based intervention as part of a unique
leadership experience. In order to effectively lead the session, the peer educators receive both
content and communications training. In terms of content, these upper-classmen students are
trained in overall concepts of gender construction, media literacy on alcohol and gender, as well
as the findings of the extant literature about the relationship between gender and alcohol. The
peer educators also receive training on social norms theory, environmental management theory,
Peer Education 15
and effective interventions to change individual behavior. Further, they become aware of the role
of their specific intervention in the overall framework of this multi-tiered alcohol education
strategy. In order to effectively communicate with the first-year students, the peer educators
receive explicit training on facilitating group dialogue, gender specific styles of communication,
multicultural competency, and presentation skills. The training aims to help develop a team
identity among the peer educators, so they can easily pair with each other to co-present and also
observe more experienced peer educators present before presenting themselves.
Each year, after the training and interventions have taken place, the peer educators
participate in in-depth interviews with evaluators about their experiences. Several key themes
have emerged related to what they learn from their involvement: (a) reasons they got involved
(desire to be part of the program, family history of addiction, related to career goals); (b)
balancing social pressures and being a role model, (c) learning how to present and facilitate
discussion, (d) awareness of diverse perspectives, (e) leadership and engagement in campus, and
(f) recognizing the cultural knowledge about gender, alcohol, and advertising that they share
around them.
Measure
We also administered an abridged version of the Core Alcohol and Other Drug Survey
(Presley, Austin, & Jacobs, 1997), which is designed to assess the nature, scope, and
consequences of alcohol and other drug use in colleges and universities. This assessment tool
boasts high validity and reliability in its implementation with postsecondary populations
(Presley, et al., 1997). The assessment uses the following items to measure quantity and
frequency of use: annual prevalence of use for all drugs and alcohol, 30-day use for all drugs and
alcohol, average number of drinks per week, binge drinking within the last two weeks, and
Peer Education 16
changes in drinking and drug use in the last 12 months. Of these items, four items in particular
were used as outcomes for this study as these items are most frequently used in alcohol
assessments aimed at determining quantity and frequency of alcohol use. These items included:
1) “Think back over the last two weeks, how many times did you have five or more alcoholic
drinks at a sitting?” 2) “How many drinks do you have on average when you go
out/party/socialize with other students?” 3) “How many drinks do you consume in an average
week?” and 4) “During the last 30 days, on how many days did you consume alcohol?” Higher
scores on each of these four items indicated a higher quantity and frequency of alcohol use. Of
the four items, the first, “Think back over the last two weeks, how many times did you have five
or more alcoholic drinks at a sitting?”, was used to create the analytic sample for this study.
Since we were interested in targeting high-risk drinking, we discarded any students who replied
“Never” to this item.
The remaining three items were used to construct the high-risk drinking scales. We
conducted confirmatory factory analyses for the pre and posttest high-risk drinking scales by
using principle axis factoring and orthogonal rotation methods. Factor loadings containing a
score of at least .764 or higher were used in the development of subsequent summated scales.
Internal validity for each of these scales was high, with Cronbach’s alpha reliabilities ranging
from .808 to .817. See Table 2 for factor loadings and alpha reliabilities for these scales.
Analysis
Several analytic methods were used to understand the efficacy of the intervention on the
outcomes under investigation. First, descriptive and factor analyses were used to understand the
defining characteristics of enrolled students and in the development of measurement scales,
respectively. Next, paired samples t-tests with Bonferroni adjustments were performed to
Peer Education 17
understand whether mean pre and posttests differences existed across outcome measures for each
sample. Finally, a 2 (Time) x 3 (Delivery mode) repeated measured ANOVA was performed to
isolate the effects of the delivery mode of the intervention on high-risk drinking. As a final step,
means analyses were again performed to aid with data interpretation. See Table 3 for operational
definitions for variables used in this study.
Limitations
Undoubtedly, this study has limitations. First, as a result of sample size constraints, we
were unable to include specific demographic variables that have been identified in the extant
research as important when studying alcohol use among college students (see Globetti, 1996;
Korn & Maggs, 2004) for a list of examples of these demographic variables). Second, we did not
assess the extent to which the varying skills among the facilitators of the intervention may have
confounded the findings. Third, all of the behaviors and expectancies included in this study were
self-reported by students, so the data relied on students’ honesty and accuracy in reporting,
although recent research has shown that this is less of a threat than it used to be (see Borsari &
Carey, 2005; Connors & Maisto, 2003; Del Boca & Noll, 2000; Marlatt, et al., 1998; Polich,
1982; Walker & Cosden, 2007). Fourth, we measured students at only two points in time and
therefore cannot say much about the stability of change over time based on exposure to the
intervention. Finally, this study was conducted at a single institution, so generalizations from
these results must be interpreted with caution.
Results
Exploratory and Descriptive Analyses
Results from the series of exploratory and descriptive analyses verified that student
characteristics did not vary across intervention delivery modes. That is, there were no significant
Peer Education 18
differences in gender, race, age, expected grade point average, enrollment status, hours spent at
work, or student status between students enrolled in success courses with no intervention, with
professionally-led interventions, or with peer-led interventions. Of course, these results are
expected, given that the intervention delivery mode was randomly assigned to the success
courses examined for this study. See Table 4 for results from relevant descriptive and
exploratory analyses.
Repeated Measures ANOVA
Results from a 2 (Time) x 3 (Delivery mode) mixed-model repeated-measures ANOVA
indicated that high-risk drinking was related to, but not dependent upon, the specific ways the
alcohol intervention was delivered to first-year students. Specifically, results showed that the
main effect for delivery mode was significant F (2, 125) = 3.773, p < .05, eta-squared = .057.
Thus, there were overall differences in high-risk drinking scores of students enrolled in success
courses with no intervention (Δ Time 2 High-risk drinking – Time 1 High-risk drinking = .450) compared to those
enrolled in the success courses with professional-led interventions (Δ Time 2 High-risk drinking – Time 1
High-risk drinking
= 0.059) compared to those enrolled in the success courses with peer-led
interventions (Δ Time 2 High-risk drinking – Time 1 High-risk drinking = -0.583). Note that only those students
enrolled in the success courses with the peer-led interventions reported an average reduction in
high-risk drinking behaviors.
Post-hoc analyses of mean differences showed that significant between-subject
differences were likely due the changes reported between students enrolled in the success
courses without the intervention and those enrolled in the success courses with the peer-led
interventions. While students enrolled in success courses without the intervention reported
increases in high-risk drinking over the term, those in the success courses with the peer-led
Peer Education 19
intervention reported decreases. These change score differences reached statistical significance
at p < .05. See Figure 1 for a graphic presentation of the between-subjects results.
The main effect for Time failed to reach statistical significance. This indicates that,
regardless of delivery mode, there were no significant average changes in high-risk drinking
behaviors reported by students in this sample. This is probably due to summing the average
increases in high-risk drinking reported by students in the success courses with no intervention
and with the professional-led interventions with the average decreases in high-risk drinking
reported by students in the success courses with the peer-led interventions. Adding average
increases to decreases likely neutralized the potential main effects of Time.
The interaction term, Time x Delivery mode, also failed to reach statistical significance,
indicating that average high-risk drinking change scores were not dependent upon delivery
mode. That is, the average change scores of students within each delivery mode did not
significantly change from pre to posttest periods. Taken together, these results suggest that
differences in high-risk drinking were related to how interventions were delivered, but not
dependent upon it.
Discussion
This study takes a small but important step toward understanding the roles peers play in
shaping student outcomes. Specifically, we investigated if alcohol prevention messages,
embedded in first-year success courses and presented by peer educators, helped curb high-risk
drinking among first-year students. Results from this study suggest that, when compared to
students enrolled in first-year courses with no intervention messages, those enrolled in courses
with peer-led interventions reported lower occurrences of high-risk drinking at the end of one
semester.
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Theoretically, results from this study echoed some from previous research that
investigated the efficacy of peer educators on helping students achieve desired learning outcomes
related to alcohol use on a college campus (Freeman, 2001; Mastroleo, et al., 2008; White, et al.,
2009). Our central hypotheses was supported, that, at the end of the semester, students enrolled
in the courses receiving the intervention from peers would report a greater decrease in high-risk
drinking behaviors than either students enrolled in the courses receiving the intervention from
professional staff or those receiving no intervention at all. Exposure to peer messages within the
context of first-year course may not only reinforce the didactic information about alcohol and its
negative consequences, but may have also increased the likelihood of creating and sustaining
social learning environments that maximize opportunities for students to learn from each other, a
suggestion that finding theoretical support in the work of Bandura (1977) and his contemporaries
(see Benjamin, 2004; Duryea, 1983; McGuire, 1964, 1968; McKegarney & Barnard, 1992; Peck,
et al., 1981; Sutherland & Cressey, 1974; Wilton, et al., 1995).
Somewhat surprising were the results comparing students in courses with intervention
messages presented by peers versus professional staff. In some ways our results concur with
those offered by others, that peer educators are at least as capable as professionals at delivering
prevention messages (Mellanby, et al., 2000); students in the first-year success courses with no
intervention messages showed the greatest increases in average high-drinking scores, when
compared to change scores reported by students exposed to professional or peer-led intervention
messages. Although these patterns were observed, results comparing average high-risk drinking
between students exposed to peer versus professionally-led interventions failed to reach
statistical significance—a finding supported by the work of Fromme and Corbin (2004) and
Larimer, et al. (2001). These mixed findings may suggest a need to re-examine how questions
Peer Education 21
related to alcohol intervention messages are framed; rather than asking if high-risk drinking
among students differs based on the educational agent delivering the intervention message,
perhaps, we should interrogate the specific ways students learn about high-risk drinking from
both professionals and peer educators. Future mixed method studies may help in further
exploring these relationships.
Many of the theories offered for explaining the link between peer education and student
learning have been criticized for failing to provide evidence concerning their structural
assumptions underscoring these relationships, that learning takes place through social
interactions and that perceptions of credibility among learning participants plays an important
role in modeling leaning behaviors (see Turner & Shepherd, 1999). The same criticisms can be
levied against this study, as one that neither directly tested the mechanisms students used to learn
from each other nor perceptions of peer credibility in delivering intervention messages.
However, through its use of an experimental research design, this study can make causal claims
linking peer education to reduced reported incidents of high-risk drinking among first-year
students—a finding that, until recently, had struggled to find empirical footing (Mellanby, et al.,
2000). Establishing this link may serve as an important first step in guiding future efforts that
examine the theoretical mechanisms responsible for this link.
Implications
Colleges and universities frequently turn to peer educators to convey messages to other
students on topics ranging from diversity to academic integrity to substance abuse. The efficacy
of using peer educators seems intuitive as they are closer in age and experience to the students
with whom they work. However, many peer education programs are implemented based on
convenience, cost considerations or simply the prevalence of the practice in higher education.
Peer Education 22
Pascarella (2006) cautions against programmatic reliance on “rational myths” (p. 513), or those
practices or assumptions that continue despite a lack of supporting evidence for their utility. This
study provides such evidence, linking student exposure to alcohol intervention messages
presented by peer educators to reduced reported incidents of high-risk drinking.
It is highly notable that this analysis is based on first-year students who are actively
engaged in high-risk drinking during the first-half of their first semester at college. Peer
education programs that attract convenience audiences (such as by advertisement or in a
residence hall) are often only offering reinforcing peer messages to students who do not drink or
only drink moderately, rather than attracting the highest risk students. This study expands the
findings on peer education as a credible intervention for high-risk drinking students.
To curb high-risk drinking among first-year students, institutions may want to provide
resources for peer education programs, including funds for their implementation and rigorous
assessment. It may not be enough to just hire peers; after all, of equal important is how peers are
trained and assessed in terms of their influence on student learning. Professionals at this
institution make a commitment to recruiting and training peer educators with high social capital,
who are visible and connected student leaders in other social arenas. Peer leaders are expected to
be committed to the stated goal of harm reduction and safe behavior, not necessarily nondrinking; thus, they have credibility with an audience to which they are similar (Brack 2008) . In
this study, peer educators were trained not only on didactic information relating to the delivered
alcohol intervention but on how to best communicate this information to students. Although
robust explanations of these training activities exceed the scope of this paper, we offer our
training manuals to others committed to peer education and its importance on helping curb highrisk drinking among first-year students (contact Author for materials).
Peer Education 23
Turning to assessment, the adoption of the experimental design for examining the
efficacy of peer-led interventions on first-year students high-risk drinking required buy-in from a
number of institutional stakeholders, including alcohol intervention specialists responsible for
designing the intervention and training the peers; first-year success course instructors who
embedded time within their courses for pre and posttesting students; and higher education
scholars with expertise in research design and quantitative methods. Results from this study
imply that such collaboration is indeed worthwhile, with first-year students reporting lower
incidents of high-risk drinking as a result of being exposed to intervention messages led by peers.
Conclusion
Given a growing dependence on specially trained student educators to have an impact on
general student behavior, the need for empirical evaluation of peer education programs is
becoming ever more acute. Through its use of an experimental research design, this study takes
an important first step in establishing the empirical link between peer education and reported
reduced high-risk drinking among first-year students. It is our hope that others use similar
strategies for addressing the important roles that students play in teaching each other; doing so
may help educators migrate to more holistic, student-centered approaches to teaching and
learning.
Peer Education 24
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Author Note
This research is funded by a grant from the U.S. Department of Education. However,
contents do not necessarily represent the policy of the U.S. Department of Education, and
endorsement by the federal government should not be assumed.
Footnote
Peer Education 33
1
Turner and Shepherd (1999) found some support the tenets of social learning theory in
their review of the peer education literature, but cautioned that many of the structural
assumptions of the theory had not been demonstrated.
2 All first-year seminars include alcohol prevention messaging. However, students
enrolled in the seminars comprising our study's control group received the intervention messages
after posttesting. None of the students enrolled in the seminars labeled as "receiving no
intervention" had been exposed to any alcohol-related intervention messages before the posttest.
Peer Education 34
Tables
Table 1
Descriptive Information for Students by Delivery Mode
Gender
Age
Race
Expected G.P.A
Living Status
Number of hours of
work per week
Enrollment status
Student status
Percent female
Percent 18 or
under
Percent white
Percent at least
3.0 or higher
Percent oncampus
Percent 0 hours
Percent full-time
Percent first-year
Success courses
with no
intervention
(n=70)
42.9
75.7
Success courses
with professional
staff intervention
(n=19)
52.6
73.7
Success courses with
peer educator
intervention
(n=39)
57.9
86.8
80.3
65.2
78.9
63.2
94.9
81.5
94.2
89.5
100.0
84.1
73.7
89.5
98.5
100.0
100.0
100.0
100.0
100.0
Table 2
Items, Factor Loadings, and Reliabilities for Alcohol Behavior Scale
Factor and Survey Items
High-risk drinking behavior (alpha)
How many drinking do you consume on an average week? a
How many drinks do you have on average when you go
out/party/socialize?b
During the last 30 days, on how many days did you consume alcohol? c
a
Factor Loading
Pretest
Posttest
.817
.808
.931
.915
.845
.789
.867
.764
Item measured through use of the following scale: 1=0, 2=1-3, 3=4-6, 4=7-10, 5=11-15, 6=16-20, 7=21-30, 8= 30 or more.
Item measured through use of the following scale: 1=0, 2=1-2, 3=3, 4=4, 5=5, 6=6-7, 7=8-9, 8=10-14, 9=15 or more.
c
Item measured through use of the following scale: 1=0, 2=1-3, 3=4-6, 4=7-10, 5=11-15, 6=16-20, 7=21-30, 8=every day.
b
Peer Education 35
Table 3
Operational Definitions and Descriptive Statistics
Pretest covariate
Pretest high-risk drinking
Delivery Mode
Operational Definition
Mean
SD
Min.
Max
Pretest high-risk drinking scale
0.000
1.000
-2.533
2.520
0.758
0.894
0.000
2.000
0.000
1.000
-2.470
2.671
0 = Enrolled in success courses
without intervention,
1 = Enrolled in success courses with
professional-led intervention
2 = Enrolled in success courses
with peer-led intervention.
Dependent measure
Posttest high-risk drinking
Posttest high-risk drinking scale
Table 4
Means and Standard Deviations for Pre- and Posttest High-risk Drinking by Delivery Mode
Delivery Mode
Success courses without intervention
Success courses with professional-led intervention
Success courses with peer-led intervention
Total
Pretest High-risk Drinking
Mean
(SD)
Posttest High-risk Drinking
Mean
(SD)
-0.218
(1.052)
0.251
(1.080)
0.291
(0.848)
0.006
(1.021)
-0.173
(1.018)
0.267
(0.935)
0.232
(0.994)
0.016
(1.013)
Peer Education 36
Figure Caption
Figure 1. Interaction of average high-risk drinking change score by intervention delivery
mode.
Peer Education 37