A randomized test of a small-group interactive social norms intervention
A
randomized test of a small-group interactive social norms intervention
| Please reference to source, this paper for note only |
Abstract
Social norms interventions are a
common approach to addressing the problem of college student drinking. An
increasingly popular but not yet well-validated social-norms-based intervention
consists of providing normative feedback to students in small groups.
Objective, Participants, and Methods: In this study, the authors used a
randomized design to test an interactive form of small-group social norms
correction with 502 first-year students during September and October 2001.
Because the unit of random assignment was at the level of the classroom, the
authors used hierarchical linear modeling to estimate variability. They
investigated whether small-group interactive social norms correction could
influence alcohol perceptions and behaviors above and beyond a non-interactive
social norms education approach. Results indicate that the approach
has a fairly substantial influence on student perceptions; however, the
findings do not support an influence of interactive small-group social norms
correction on measures of alcohol use behaviors. Conclusions. Given these findings,
the use of interactive small-group social norms approach to influence student
misperceptions may be considered as a primer for population-level preventive
interventions.
Keywords: alcohol
use, college health, social norms intervention
Recent research has identified college
student drinking as an important health issue. Estimates indicate that
approximately 1,700 students die, 500,000 are injured, and 600,000 are
assaulted while using alcohol or other drugs each year.1 Since 1993, the
Harvard School of Public Health has measured levels of heavy episodic-or
binge-drinking among college students with the College Alcohol Survey (CAS).2
In this study, heavy episodic drinking is defined for men as the consumption of
5 or more drinks in a single drinking session within the past 2 weeks and for
women as 4 of more drinks within the same time frame.2 CAS researchers have
consistently found that approximately 2 out of 5 students drink at binge
levels.3 In addition, they monitor frequent heavy episodic drinking, defined as
binge drinking 3 or more times in the past 2 weeks. Analyses with this subgroup
reveal that frequent heavy episodic drinkers were 21 times more likely than
were nonfrequent heavy episodic drinkers to experience 5 or more of the 12
alcohol-related problems included in the survey. The Monitoring the Future
Survey produced similar results.4 In this study, 40% of students reported
consuming 5 or more drinks on a single occasion at least once in the previous 2
weeks, a greater proportion than same-age, noncollege-attending peers (35%) or
high school seniors (31%).
Although most college student drinkers
begin drinking regularly prior to college, drinking rates increase
significantly during the transition from high school to college.5-7 Moreover,
students entering college show marked increases in alcohol use compared with
those who enter the workforce after graduation from high school.4
These findings have both theoretical
and practical implications. Theoretically, although some first-year students
arrive on campus with high-risk drinking patterns, many others develop these
patterns during the first-year transition. Thus, as suggested by the National
Institute on Alcoholism and Alcohol Abuse (NIAAA) Task Force, preventive
interventions that target incoming freshmen are of critical importance.8
Overview
of Social Norms Theory
One popular approach to addressing
this high-risk drinking culture is social norms prevention. Initial
correlational and theoretical articles from the late 1980s and early '90s established
a conceptual and theoretical basis for social norms approaches on college
campuses. Researchers9-11 in these studies found that college students have
strong misperceptions of peer drinking behaviors, typically over-estimating the
frequency and amount that other students drink. In a review of peer influences
on college student drinking, Borsari and Carey12 noted that in 29 of 30
studies, investigators observed misperceptions between actual and perceived
alcohol use rates. These misperceptions can be influenced by several factors,
including the type of norm (injunctive or descriptive), sex, reference group,
or campus demographics.13 Injunctive norms are perceptions of social approval
or disapproval of behavior and reference the cultural acceptance of behavior.14
Conversely, descriptive norms are perceptions of what others do. In this case,
descriptive norms refer to students' perceptions of other students' drinking
patterns.
Perkins and Berkowitz10 theorized that
providing students with feedback about the actual norms could reduce drinking
levels. On the basis of this premise, many university prevention programs
implement social norms interventions focusing on correcting misperceptions.
Schools have typically implemented 3 types of social norms interventions:
social marketing media campaigns,15 normative correction in the context of
individualized feedback or brief motivational interventions,16-18 and
small-group social norms interventions.19-21 Findings from each of these 3
types of interventions are described in the next sections.
Social
Marketing Media Campaigns
Media campaigns are, by far, the most
widely used of these approaches. Using local survey data, these universal
preventive interventions advertise accurate information about the typical
quantity of alcohol consumed per drinking occasion via campus newspaper ads,
posters, flyers, and other mass media venues. It is theorized that corrected
misperceptions will lead to reductions of normative misperception of heavy
drinking, which will, in turn, lead to reduced levels of drinking and
alcohol-related negative consequences.
Following the Haines and Spear15
publication of promising case study results at one campus, social norms
marketing has arguably become the most highly publicized preventive intervention
on college campuses. It has been cited in The New York Times Magazine,22 and
Wechsler et al23 found that as many as 1 in 9 schools implement this prevention
approach. A handful of universities have reported similar success with this
approach. For example, the University of Arizona observed a 29% reduction in
binge drinking over a 4-year period.24 Hobart and William Smith colleges
reported a 12% decrease over 2 years, and Western Washington University
recorded an 8% decline in binge drinking during the first year the program was
initiated.25
Despite social marketing
interventions' strong popular appeal, peer-reviewed, rigorous tests of such an
approach are lacking, prompting the NIAAA Task Force to rate this approach as a
Tier 3 Intervention (ie, displaying "evidence of logical and theoretical
promise but requiring more comprehensive evaluation").8(p21) Studies
applying controlled experimental designs have suggested less promise. In a
study implementing a social norms intervention to first-year students, Werch et
al26 observed nonsignificant differences in alcohol use and alcohol use risk
factor measures at posttest between intervention and comparison groups. In a
test of a social norms marketing campaign within university residence halls at
treatment and comparison sites, Clapp et al27 observed no intervention effects
on drinking behaviors. Thombs and Hamilton28 obtained similar results when
comparing student athletes who had been exposed to a social norms media
campaign. In all 3 studies, students exposed to the social norms media
campaigns experienced a greater decrease in alcohol-related misperceptions than
did comparisons, but none of the researchers observed significant reductions in
alcohol use behaviors.
Individual-Level
Preventive Interventions
Brief motivational interventions have
been the most promising individual-level approach for reducing alcohol abuse
and alcohol-related problems among college students. 29 These interventions, as
well as the more pared-down individualized feedback approaches, focus on
correcting normative misperceptions of alcohol use and problems.30,31 These
approaches give students individualized feedback, comparing their drinking
rates with typical student perceptions and drinking patterns. Consistent with
social norms theory, it is hypothesized that personalized normative feedback
will correct misperceptions, which will then motivate the individual to
decrease drinking levels. Researchers in 2 studies16,30 have observed evidence
consistent with such a mediational role for perceived norms. This type of
personalized feedback has shown promise using both mail and computer
delivery.31-34 Despite the effectiveness of brief motivational interventions
and individualized feedback, however, they are comparatively resource- and time-intensive,
prompting some investigators to explore the utility of correcting normative
misperceptions in small-group settings.
Small-Group
Social Norms Interventions
The least used social-norms-based
intervention consists of providing normative feedback to students in groups.
Common settings typically consist of classrooms or presentation venues with
fewer than 50 students.20,35 The approach merges direct feedback and media
campaigns to reduce participants' resistance to social norming messages. This
approach often seeks to capitalize on a readily available reference group.
Facilitators present correct normative information and encourage students to
discuss the information. This approach recognizes that misperceptions may be
longstanding and that resistance to the messages will most likely be the
initial response. Small-group social norms intervention researchers theorize
that discussion of correct information with a reference group can reduce
participants' resistance to and facilitate their acceptance of the messages.
As with social marketing media
campaigns, few peerreviewed publications have published studies on smallgroup
social norms interventions. In one test with an experimental design, Barnett et
al35 found associations between perceptions and drinking patterns but did not
find reductions in drinking behaviors associated with the social norms
treatment approach at 4-month follow-up. Similarly, Smith20 described implementation
of a small-group social norms approach with classroom-level random assignment
to treatment and comparison groups. The author implied that he performed
analysis as if assignment was at the individual level. However, after
clarifying conversations, Smith stated that he performed interclass
correlations but that the results did not suggest the need for hierarchical
linear modeling (HLM; B.H. Smith, personal communication, October 18, 2004). In
posttests performed 1 month after intervention, Smith found that the treatment
was effective at reducing students' misperception of other students' drinking
but observed no evidence for reductions in drinking behaviors. Stamper et al21
replicated these findings 1 year later.
The
Current Study
Theoretically and anecdotally,
campuswide media campaigns appear to be a relatively cost-effective means to
reduce binge-drinking risks with the college-aged population. However,
peer-reviewed evaluations have yet to support their effectiveness. Brief
motivational interventions and individualized feedback approaches provide
experimentally measured effectiveness but are expensive, are labor-intensive,
and reach a limited number of students. Thus, we sought to test a hybrid
approach in the current study. Specifically, we investigated whether a
small-group interactive social norms correction could achieve the behavioral
outcomes of brief motivational interventions at greatly decreased cost and
labor levels. As described in the Methods section, the interactive component is
students' completion of the survey at the beginning of the class period and
provision of feedback on survey results in the same class period. With these
efficacy and cost-effectiveness goals in mind, we sought to answer 2 research
questions. First, can a small-group interactive social norms intervention
reduce normative alcohol use misperceptions above and beyond a noninteractive
social norms education approach? Second and more important, can a small-group
social norms intervention decrease alcohol use as compared with a
noninteractive social norms education approach?
METHODS
Procedure
We recruited participants from a
1-credit orientation course required of all first-year students at a
medium-sized New England public university. The course-which is broken up into
sections of fewer than 35 students-acquaints new students with the university.
Some sections discuss specific majors; all aim to promote a sense of community
among students.
One component of the course is a
health and safety presentation. Trained graduate students or peer leaders
facilitate this presentation, which the university's director of Substance
Abuse Prevention Services supervises. The facilitators provide prevention and
education information on alcohol and drugs, sexual assault, and violence, as
well as information on campus police, health services, and the counseling
center. In the current study, implementation of intervention and comparison
conditions occurred during the health and safety presentation.
We sent letters to the course's instructors
requesting participation. These letters informed instructors that we would
randomly assign sections to either an intervention or a comparison condition.
Students in the standard social norms correction (SSNC) health and safety
presentation condition received the standard health and safety presentation.
During the presentation, the section leaders provided students with prevention
information focusing on alcohol and drug issues, sexual assault and violence,
and health and personal safety. They also provided students in this condition
with campuswide statistics on average levels of alcohol use (70% of students
have 5 or fewer drinks when they consume), marijuana use (80% of students
abstain or use less then once a month), and sexual activity (70% of students
reported 0 or 1 sexual partner in the past year). We obtained this information
from data on previous-year, first-semester freshmen.36 Our intent in providing
this information was to illustrate the normalcy of sexual abstinence and
low-risk use of alcohol and marijuana.
Prior to the presentation, the section
leaders administered the survey, which queried students on alcohol use,
marijuana use, and the number of past-year sexual partners, in addition to
perceptions of other students' patterns on these same items. Distribution and
collection of the classroom survey lasted 5 to 10 minutes. For SSNC students,
section leaders did not encourage them to discuss the normative information
presented, nor did they provide feedback on the survey results.
Students in the interactive
small-group social norms correction (ISNC) health and safety presentation
condition received the standard health and safety presentation plus feedback
and discussion of section-specific survey results. During the presentation,
upper-class mentors tallied classroom survey results. After the presentation,
the section leaders provided students with their section-specific norms
(generated by the same students just 30 minutes prior). The section leaders
encouraged discussion as to why observed discrepancies between actual and
perceived alcohol use norms may exist.
Both conditions received the classroom
survey at the beginning of the class period. However, only ISNC students
received their section-specific results. The ISNC method consisted of
approximately 5 more minutes of data feedback and 5 more minutes of class
discussion than the comparison condition. The university's institutional review
board approved all procedures and measures.
Participants
Forty-five of 90 (50%) section
instructors consented to participate in the study. We randomly assigned 22
sections to the SSNC and 23 to the ISNC. Not all section instructors who agreed
to participate returned pretests. Forty-two sections (93%; 22 SSNC and 20 ISNC)
returned pretests. We received 905 completed pretests: 471 SSNC participants
(52%) and 434 ISNC participants (48%).
We analyzed data for 502 students.
This number represents the usable number of matched responses. The high
attrition rate (44.5%) was due to either nonparticipation at follow-up (4
sections, n = 100, 24.8%) or to student absence at baseline (n = 101, 25.1%),
intervention (n = 80, 19.8%) or follow- up (n = 89, 22.1%). In addition, we
used self-generated codes (described in the Measures section) to anonymously
link pre- and posttest data, and some students provided unmatchable codes (n =
33, 8.2%). The final analyzed dataset consisted of 259 (51%) SSNC students and
243 (49%) ISNC students. A majority of the sample was female (55%) and white
(87%), followed by Hispanic (5.3%), Asian (3.8%), African American (3.6%),
Native American (1.2%), and 1.6% reporting another ethnicity. These numbers
closely match first-year student demographics at this university (56% female,
78% white, 3.9% Hispanic, 3.9% Asian, 3.7% African American, 0.5% Native
American, and 10% not reporting ethnicity). Comparisons between the final
sample and the incoming freshman population revealed nonsignificant differences
by sex or African American, Hispanic, Asian, and Native American ethnicities
(all ps > .05). White students, however, were significantly overrepresented
in the sample (χ^sup 2^[1, N = 437] = 7.55, p < .01), and the proportion of
the campus population not reporting ethnicity was significantly greater than in
the study sample (χ^sup 2^[1, N = 50] = 19.58, p < .0001). We suspect but
cannot verify that the significant overrepresentation of white students in our
sample (compared with overall university data) may be due to the
disproportionate number of white students in the campus population that opted
not to report race or ethnicity data. However, the final sample is a close
approximation, demographically, of the population of first-year students from
which it was drawn.
Measures
Section leaders administered pre- and
posttest batteries in a fixed order, as detailed later, using Teleforms-created
(Teleforms Inc, Manitoba, Canada) surveys that enabled scanning of participant
responses. Participants read, signed, and provided informed consent through
survey completion. Section leaders instructed students not to place their names
or student numbers on the surveys. A self-generated unique code number
procedure allowed for linking pre- and posttest surveys while maintaining
participants' anonymity: Students wrote down the first letter of their mother's
maiden name, followed by the month, day, and year of their birth. Using written
procedures that we provided, class instructors administered pre- and posttest
surveys. The pre- and posttest self-report surveys took approximately 10
minutes to complete. Section leaders administered pretest surveys in the first
class period and collected posttests in the last class period. Class durations
were 6, 10, or 12 weeks depending on how long each class met and how many times
a week the class was held. All health and safety presentations occurred at
least 2 weeks after pretest and 3 weeks before posttest. The focus of the
surveys was on alcohol use and perceptions of alcohol use by peers. The survey
contained additional content related to overall student health and safety that
are not included in the analyses presented here.
Alcohol
Use
We assessed alcohol use with 2
items-which have demonstrated reliability (eg, internal consistency, 18-month
test-retest) and validity (strong associations with other measures of
consumption) in a number of our previous studies37-39-regarding typical
quantity and frequency of alcohol consumption per week. We then multiplied
these items to produce a weighted quantity-frequency index of weekly consumption.
We used number of drinks consumed in a typical week as our primary measure. All
surveys provided clear definitions of a standard drink: 12 oz of beer, 4 oz of
wine, and 1.25 oz of liquor in a shot or a mixed drink.
Perceptions
of Others' Alcohol Use
We measured perceived norms with a
widely used measure, the Drinking Norms Rating Form,9 which has demonstrated
reliability and validity in our own work,37,39 as well as in several previous
studies.9,40,41 The items assessed perceptions of others' drinking practices
for the typical same-sex student at the study university (eg, "How often
do you think a typical student of your gender consumes alcohol?"). We
assessed perceived quantity (number of drinks when drinking, ranging from 1 to
12 or more) and perceived frequency (number of drinking days, ranging from 0 to
7) of alcohol consumption. We multiplied these items to produce a similar
quantity-frequency perception index of weekly consumption.
RESULTS
Overview
of Data Analysis
Because the unit of random assignment
was at the level of the classroom and not the individual, we used HLM to
estimate classroom-level variability.42 We used 2 two-level models to test
whether the ISNC condition influenced normative misperceptions and behavior. We
constructed models for posttest outcomes of alcohol perception and alcohol use.
All models contained Level 1 covariates of sex and corresponding individual
pretest scores. Level 2 models contained the type of intervention assigned.
Descriptive
Statistics for Participant Alcohol Use
We observed no baseline differences
between the 2 intervention groups on either self-reported alcohol use (t[495] =
0.40, ns) or perceived norms (t[495] = -0.49, ns). Therefore, we aggregated
these data across the sample to describe normative perceptions and alcohol use.
Pretest data revealed significant sex differences in both reported drinks per
week (t[312] = -4.83, p < .0001) and perceived drinks per week (t[335] =
-6.05, p < .0001). Men reported an average of 11.74 drinks (SD = 15.59) per
week versus women's reported 6.03 drinks (SD = 8.51). Both men and women
substantially overestimated how much alcohol other students consumed; men
estimated that other male students drank an average of 18.10 (SD = 12.20) and
women estimated that other female students drank an average of 13.16 (SD =
7.32) drinks per week.
Attrition
Analyses
We conducted attrition analyses to
examine whether students who were not available at follow-up (n = 403) differed
on variables of interest at baseline from those who remained in the study. We
observed no significant differences between attriters and nonattriters on
baseline alcohol use measures, but some differences did emerge on normative
perceptions. We observed group differences for drinking frequency perceptions
(t[890] = 2.059, p < .040, d = .14) and past-week alcohol use perceptions
(t[885] = 2.451, p < .014, d = .17), with the attriters reporting more
perceived drinks per week (M = 18.03, SD = 0.54) than did nonattriters (M =
16.33, SD = 0.44). Cross-tabulation of attriters by treatment type revealed no
evidence of experimental mortality (F[1, 903] = 0.134, p < .714), with 207
(44%) attriters in the SSNC condition and 196 (45%) in the ISNC condition.
Tests
of Substantive Research Questions
RQ1:
Can an Interactive Social Norms Correction Influence Misperceptions?
We obtained a substantial interclass
correlation for alcohol perceptions, which indicated variability for alcohol
perceptions by section (ρ = .15) and justified HLM. The interclass correlation
for alcohol use was less extreme (ρ = .07); nonetheless, we used HLM for
analyses with each of our outcome variables.
As anticipated, the Level 1 covariate
of baseline perceptions was significantly related to drinking perceptions at
posttest (t[469] = 6.05, p < .0001), such that higher baseline perceptions
were associated with higher perceptions at follow-up. There was a trend toward
sex differences in perceptions at posttest (t[469] = 1.76, p < .08), with
men reporting a mean of 12.1 (SD = 7.24) and women reporting a mean of 10.3 (SD
= 7.9) perceived drinks per week. After controlling for pretest alcohol use
perceptions and sex, results of the full 2-level HLM model show that
interactive social norms intervention for small groups effectively reduces
perceptions of drinking amounts (t[469] = -3.976, p < .001). As can be seen
in Figure 1, we observed pre- to posttest reductions in the ISNC condition,
falling from 16.8 (SD = 10.91) to 11.1 (SD = 7.56) drinks, whereas the SSNC
condition decreased from 16.3 (SD = 9.61) to 15.4 (SD = 9.79) drinks.
Computation of the intervention effect size using the posttest means and a
pooled standard deviation43 yielded a d index of .41. Cohen defined effect
sizes44 as small (d = .2), medium (d = .5), and large (d = .8); thus, the
intervention effect for correcting normative misperceptions would be considered
moderate.
RQ2:
Can an Interactive Social Norms Correction Influence Behaviors?
Consistent with expectations and the
previous analyses, the Level 1 covariate of baseline alcohol use was
significantly related to reported alcohol use at posttest (t[485] = 7.67, p
< .0001), such that higher reported baseline use was associated with higher
reported postintervention use. We also observed significant sex differences in
alcohol use at posttest (t[485] = 2.95, p < .005), with men reporting a
posttest mean of 10.6 (SD = 12.30) and women reporting a mean of 5.9 (SD = 7.9)
drinks per week. After we controlled for pretest alcohol use perceptions and
sex, RQ2 was not supported (t[485] = 0.433, p < .665). We observed a modest
decrease in reported drinks per week among SSNC students, from a pretest mean
of 8.74 drinks (SD = 13.19) to a posttest mean of 7.71 drinks (SD = 9.80; see
Figure 2). Reported drinks per week did not decrease for ISNC students, with a
mean of 8.31 (SD = 11.50) at pretest and 8.31 (SD = 10.21) at posttest.
Computation of the effect size using posttest means and a pooled standard
deviation yielded an index of d = .06, well below an effect size determined to
be small (d = .2). These results do not support the major intervention aim of
decreasing alcohol use.
COMMENT
Our results support the general belief
that misperceptions of alcohol use exist among the college student population
and that small-group interactive social norms correction can have a fairly
substantial influence on these perceptions. However, consistent with an
emerging body of research, we found no evidence that small-group interactive
social norms correction effectively reduced alcohol use among incoming college
students. It is important to note that we specifically compared interactive and
noninteractive social norms approaches. Thus, we gave students in both
conditions some normative feedback, but we observed changes in misperceptions
only in the INSC condition, in which section leaders provided and interactively
discussed survey results.
The SSNC condition closely
approximated the interventions done by Barnett et al35 and by Smith,20 which
involved disseminating campuswide statistics highlighting the norms of low-risk
alcohol use. In our interactive social norms comparison condition, however, we
introduced the novel innovation of using the classroom to provide real-time
feedback on class norms. The large reduction in misperceptions among this group
supports the heightened salience of this approach in correcting normative
misperceptions.
Participation in the ISNC (vs the
SSNC) condition did not result in lower levels of alcohol use (RQ2). These
results add to a small but increasing body of research suggesting that although
small-group social norms influences appear to affect normative perceptions,
they do not affect actual drinking behavior.19-21,35 Although college students'
alcohol use trajectories vary, the transition into college is typically
associated with increased alcohol use and alcoholrelated problems.45,46 Our
intervention conditions may have altered this trajectory somewhat, as evidenced
by the relatively stable levels of alcohol consumption we observed; however,
given that we did not include a nonintervention condition-which would have
provided a comparison from which to better support this conclusion-we make this
suggestion tentatively.
A particular strength of this study
was the use of grouplevel random assignment in conjunction with a statistical
approach (ie, HLM) to compare variability within sections. Previous
researchers20,21,35 have reported using grouplevel random assignment and
individual-level data analyses without consideration of the importance of
controlling for within-group variability. As noted, with respect to the
intraclass correlations observed in our study, random grouplevel assignment
necessitates statistical modeling of withingroup variability.42
Several study limitations merit
discussion. First, there was a considerable degree of attrition in this study.
Student absence for this 1-credit course was consistently about 20% per section
per time point (pretest, presentation, posttest). Absence at any time point
resulted in incomplete data. This degree of attrition could potentially have
major effects on the validity of our findings. These concerns are somewhat
mitigated by attrition analyses demonstrating no differences between attriters
and nonattriters on the main outcome measure, alcohol use. However, we observed
significant differences when comparing attriters and nonattriters on normative
perceptions, with attriters having a higher perception of drinks per week at
baseline than did nonattriters. Given the lack of differential attrition by
group, however, the threat to internal validity appears modest.
An additional limitation is the use of
self-reported data, although self-report procedures are by far the most common
method to obtain alcohol use data from students. Researchers47,48 have
recommended that investigators make assurances of anonymity or confidentiality,
stress the importance of truthful responding, and adopt a nonjudgmental
data-collection perspective as ways to increase the reliability and validity of
self-reports. Moreover, recent research has suggested that students'
self-reports of alcohol use are underestimated.49 However, White et al49 found
that providing students with specific definitions of a standard drink reduced
this influence. In the present study, we used definitions of a standard drink for
all survey instruments. Most importantly, we had no reason to suspect that
tendencies to under- or overreport alcohol use would interact with intervention
condition, which would be necessary to constitute a threat to internal
validity.
An additional limitation includes the
relative lack of ethnic and racial heterogeneity in our sample. Although our
sample closely approximated the population of first-year students at the
predominantly white campus, future researchers must examine the potential
efficacy of small-group social norms approaches with more ethnically diverse
populations. Furthermore, although the use of an experimental design in this
study is a strength, the lack of a true control group is a limitation. Most
notably, it prohibits comparison between the 2 experimental conditions and a
natural history18 comparison group during a developmental transition (college
matriculation) typified by increased drinking.
As stated earlier, neither the
population-level social norms media campaigns nor small-group approaches have
yet demonstrated efficacy in studies using experimental design or
quasiexperimental approaches that adequately control for threats to internal validity.50
Future researchers examining small-group social norms or population-level
social marketing studies would profit from using experimental or well-designed
quasiexperimental designs, to allow for strong inferences about the causes of
any observed effects. Incorporation of theory-based mediators (eg, changes in
normative misperceptions) into study designs and analyses would further
strengthen researchers' ability to make causal inferences about mechanisms of
effect.51 Reductions in alcohol use and problems observed in studies of brief
motivational interviewing29,31 and individualized feedback31-34 suggest
potential efficacy for social norms approaches in group and environmental
preventive interventions. Even stronger inferences can be drawn about the potential
importance of social norms from the few studies in which investigators have
identified changes in normative perceptions as mediators of intervention
effects.16,30
In conclusion, our results do not
support small-group interactive social norms intervention as being effective as
a stand-alone intervention to achieve behavioral change. Given these findings,
along with the methodological issues raised previously, one strategy for future
work may be the use of interactive small-group social norms approaches to
influence student misperceptions as a primer for populationlevel (universal)
preventive interventions.
Finding ways to influence college
student drinking and associated negative consequences remains an important
health concern in our society. Current research and theory suggest that
multiple interventions at the individual, group, and environmental levels are
needed to yield meaningful progress in reducing alcohol-related harm among the
college population. Currently, beyond the individual level, little is known
about effective interventions. Therefore, identifying the most effective
approaches at the group and population level through the use of theory-based
empirical research is of critical importance. Social norms approaches appear to
be an important component of successful individual-level preventive
interventions, but much research remains to be done in validating and
transferring these successes to larger groups and the overall college
population.
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