Descriptive and Injunctive Norms in College Drinking
Descriptive and Injunctive
Norms in College Drinking: A Meta-Analytic Integration
Borsari,
B., & Carey, K. B. (2003). Descriptive and Injunctive Norms in College
Drinking: A Meta-Analytic Integration. Journal
of Studies on Alcohol, 64(3),
331–341.
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Abstract
In the last decade, the “social norms approach” to reducing excessive
alcohol use on college campuses has enjoyed a swell of support (DeJong and Linkenbach, 1999; Keeling, 2000). This approach posits that the
majority of students overestimate the use and approval of alcohol by campus
peers; as a result, these students are less inclined to view their own alcohol
use as problematic (see also Perkins, 1997 and 2002 for reviews). The social norms
approach, then, proposes that correcting these misperceived norms will result
in students gaining a new perspective on the risks associated with their
personal alcohol use. This approach is often carried out on a large scale, such
as campus-wide media campaigns (e.g., Haines and Spear, 1996). In theory, this new
perspective will lead to reductions in alcohol use and the adoption of more
conservative attitudes towards drinking. In light of the significance of social
norms in alcohol abuse prevention efforts, greater attention to the variability
within the drinking norms literature is warranted.
Perceived Norms in the College Context
Two types of
norms have been assessed in the college drinking literature: descriptive and
injunctive norms.Descriptive norms refer to the perception of other’s
quantity and frequency of drinking (the norms of “is”), and are based largely
on observations of how people consume alcohol in discrete drinking situations.
Injunctive norms, on the other hand, refer to the perceived approval of
drinking (the norms of “ought”), and represent perceived moral rules of the
peer group. Injunctive norms assist an individual to determine what
is acceptable and unacceptable social behavior (Cialdini et al., 1990).
Norms are
constructed by evaluating the raw data from three primary sources: observable
behaviors, direct and indirect communications, and knowledge of the self (Miller and Prentice, 1996). The first source
of normative information, observable behavior, is often the most available
source of information about others, yet it is susceptible to the fundamental
attribution error. This refers to the tendency of individuals to view others’
behaviors as reflective of stable dispositional traits rather than influenced
by situational variables (Ross, 1977). The second source of normative
information, direct (what words mean) and indirect (what words imply)
communication, also has its flaws. Information may be distorted intentionally
or unintentionally. Finally, personal attitudes and behaviors also influence
the perception of norms. This phenomenon is labeled the false consensus effect,
in which people tend to think that others think and act as they do (see Mullen and Hu, 1988 for a review). These
different sources of information are combined in an additive fashion (Miller and Prentice, 1996), sometimes leading
to inaccurate estimates of others’ behaviors and attitudes. Therefore, the
information that one can utilize when evaluating others’ behaviors and
attitudes can be biased in a variety of ways.
It is not
surprising, then, that perceived descriptive and injunctive norms related to
drinking are often inaccurate. Surveys consistently report that students
overestimate the quantity and frequency of their peers’ alcohol consumption
(e.g., Baer and Carney, 1993). This overestimate
occurs regardless of the specific reference group used: close friends, best
friend, typical student, average student, or fellow fraternity/sorority house
member. Furthermore, students are remarkably consistent in reporting that they
drink the same or less than others (see Borsari and Carey, 2001); only male members of
Greek houses with reputations for heavy drinking have reported personal use as
higher than that of all other students (Larimer et al., 1997). Therefore, although the
hierarchy of drinking levels may change, students tend to believe that someone
else drinks more than they do. Similar discrepancies occur when students
evaluate other’s approval of heavy drinking or drunkenness: others are usually
seen as more accepting of such behaviors than are the raters themselves (Perkins and Berkowitz, 1986b; Prentice and Miller, 1993). Such normative
perceptions make heavy alcohol use appear to be common and socially acceptable
(Borsari and Carey, 2001).
Central to the
effectiveness of the social norms approach is addressing the discrepancy
between one’s own views and/or behaviors and those of others. Because students
tend to view others as drinking more and being more tolerant of alcohol use than
themselves, the new student may be unaware that a given level of drinking is
heavy or risky. Indeed, being surrounded by peers perceived to approve of heavy
drinking can directly influence one’s consumption even above other social
background factors such as age, year in school and number of close friends (Perkins, 2002). If students perceive others’
use to be higher than their own, reductions in drinking are unlikely because personal
use is viewed as less risky than the social norm. Conversely, if the students
perceive personal use to be higher than the norm, then re-evaluation of
personal drinking habits is likely. Such a re-evaluation is precisely what
social norms campaigns attempt to accomplish by educating students about the
actual drinking norms on campus, which are typically lower than the perceived
norms. The intuitive appeal of this concept has led to a veritable explosion of
norm education campaigns on campuses across the country. To date, the results
of these efforts have been mixed, with some reporting substantial reductions in
drinking (e.g., Haines and Spear, 1996) and others reporting
no changes (e.g., Werch et al., 2000).
Such disparate
findings suggest the need for a better understanding of the actual phenomenon
of interest: the perceived discrepancy between personal behaviors and attitudes
and those of others. To this end, we aim to increase the knowledge of drinking
norms on college campuses in three ways. First, we will perform a meta-analytic
integration of the existing research on (mis)perceived norms in order to
evaluate the presence and strength of self-other discrepancies (SODs). Second,
we will examine how several predictors derived from the research literature
influence SODs. Finally, we will discuss the implications of our findings in
regards to assessing norms and facilitating behavior change.
Potential Predictors of Self-Other Discrepancies
Previous
research has focused primarily on the presence of normative misperceptions,
with occasional speculation about mechanisms that might contribute to observed SODs.
Therefore, we identified five variables from the literature addressing
perceived norms that we hypothesized to significantly influence the magnitude
of SODs: type of norm assessed, gender, proximity of the reference group,
question salience, and campus size.
Norm Type
To our
knowledge, a comparative evaluation of SODs for injunctive vs. descriptive
norms had not previously been presented. Descriptive norms are related to the
observation of others’ overt behaviors (how much and how often they drink), while
injunctive norms are based on the inference of others’ approval of drinking.
Therefore, it is likely that estimation of descriptive norms involves the
encoding, storage and retrieval of others’ drinking behavior, whereas
injunctive norms estimation requires students to encode, store and retrieve
others’ statements of (dis)approval, and/or generate such inferences from
other’s behaviors. As mentioned earlier, combining different sources of
information may lead to inaccurate estimates of others’ attitudes (Miller and Prentice, 1996): this integration
may be more biased to the extent that greater inference is involved. Thus, we
predict that SODs for injunctive norms may be more exaggerated because they are
based on less direct information.
Gender
To date, six
studies have evaluated gender differences in norm perception. Some have found
that women perceive larger SODs than men (Baer and Carney, 1993; Prentice and Miller, 1993; Perkins and Berkowitz, 1986b; Larimer et al., 1997), whereas others studies
have found no differences (Read et al., 2001;Schroeder and Prentice, 1998). Despite such
mixed findings, it is possible that gender differences in alcohol use may
influence norm perception. Specifically, women consistently report drinking
less than do men (O’Malley and Johnston, 2002), yet most women
also drink in mixed groups (Orcutt, 1991; Rosenbluth et al., 1978). Such a combination
of lower personal use in the context of the more noticeable, heavier use of
males may result in the perception that others drink more, resulting in larger
SODs. Therefore, it is likely that women will perceive greater SODs than do
men.
Reference Group
The use of a
wide variety of possible reference groups, and the need to understand their
respective influence on personal behaviors, has plagued social norms research
for years (Miller and Prentice, 1994). The college
drinking literature is no exception, using reference groups that vary in their
proximity to the student: consider the variation of reference groups from “your
best friend” (Baer and Carney, 1993) to “a typical member of
your athletic team” (Thombs, 2000) to “most students” (Haines and Spear, 1996). Thus, it is likely
that each of these reference groups differ in their degree of familiarity and
specificity to the participant. Research has indicated that students’
perceptions become more distorted for groups that they know less well (Baer et al., 1991; Perkins, 1997) and that SODs are significantly
lower for familiar versus unfamiliar others (Prentice, 1990). Thus, estimates for proximal
reference groups (e.g., best friend) may be more factually based than more
distal groups (e.g., average student), resulting in lower SODs.
Question Specificity
It is possible
that variations in the specificity of questions assessing descriptive and
injunctive norms may contribute to the SODs reported in the literature.
Questions evaluating specific behaviors (e.g., how much did your friends drink
in the past week) may elicit more calculation by the student than questions
that are more vague (e.g., how many times did your friends drink in the past
year). Therefore, questions that assess specific information may result in
lower SODs than questions requiring information that is more difficult to
estimate.
Campus size
The size of the
campus may also play a role in norm misperception. If norms are based on
behaviors that are noticeable in the environment (Perkins, 1997), students at larger
universities may be less certain of their estimates of descriptive and injunctive
norms. Students on large campuses may be aware that they have never seen or met
most of the other students on campus. This may result in more erroneous
over-estimates, as these students have relatively little information on which
to base their estimates. On smaller campuses, where “everybody knows everyone
else”, students may be more confident in their estimates of others’ drinking
because they know a larger proportion of the total student body. As a result,
based on students that they know, their estimates may be more factually based.
Therefore, SODs may be greater on larger campuses.
To date, no systematic evaluation of these predictors on SODs has been
conducted. In an effort to address these issues inherent in the norms
literature, a meta-analytic integration (Glass et al., 1981; Mullen, 1989;Rosenthal, 1991) was conducted on research
evaluating the misperceptions of norms on college campuses.
Method
Standard
literature search techniques were utilized to conduct an exhaustive search for
studies evaluating perceived norms: on-line computer searches, ancestry and
descendancy approaches, and correspondence with researchers active in the
domain (the “invisible college”; see Mullen, 1989 for a discussion of
literature search techniques). Data available as of February 2002 were eligible
for inclusion.
Studies were
included if they met the following criteria. First, participants had to be
college students. Second, the study had to utilize a self-other comparison
using the same question stem with only the reference group being changed (e.g.,
how much do you drink during a typical drinking occasion; how
much does the average student drink during a typical drinking
occasion). Finally, studies had to report a test of the self-other difference
in norm perception. Third, for studies evaluating a norm intervention
(e.g., Haines and Spear, 1996), only baseline data
were included.
An extensive
literature reveals that perceived support of others for drinking is
consistently associated with personal alcohol use (Adams and Nagoshi, 1999; Agostinelli et al., 1995; Alva, 1998; Baer, 1994; Banks and Smith, 1980; Burrell, 1992; Clapp and McDonnell, 2000; Gomberg et al., 2001; Liccione, 1980; Lo, 1995; Nagoshi, 1999; Nagoshi et al., 1994; Peeler et al., 2000; Perkins and Wechsler, 1996; Sher et al., 2001; Turrisi, 1999; Walters, 2000; Walters et al., 2000; Wechsler and Kuo, 2000; Werner et al., 1996;Werch et al., 2000; Wood et al., 2001), and, to a lesser extent,
alcohol related problems (Nagoshi, 1999;Wood et al., 2001). Although suggesting a
strong link between perceived norms and alcohol use (see Borsari and Carey, 2001), this research was
not included in this meta-analysis because variables representing norms
combined items assessing both injunctive and descriptive norms (e.g., Perkins and Wechsler, 1996) and/or self-other
comparisons did not use identical question stems (e.g., Burrell, 1990).
Finally, lost data precluded the use of four studies (Baer et al., 1991; Barnett et al., 1996; Mooney and Corcoran, 1991; Thombs et al., 1997).
In the course
of conducting this literature search, more than 40 published and unpublished
articles, reports, and theses were examined. Of these, the selection criteria
rendered a total of 23 includable studies (Baer and Carney, 1993; Borsari and Carey, 2000; Bourgeois and Bowen, 2001; Brown et al., 2000; Carter and Kahnweiler, 2000; Collins, Carey and Sliwinski, 2002; Corbin and Fromme, 2000; Dreer et al., 2000;Fabiano et al., 1996; Haines and Spear, 1996; Larimer et al., 1997; Neal and Carey, in press; Perkins and Berkowitz, 1986 a,b; Perkins et al., 1999; Prentice and Miller, 1993, three
studies; Read, et al., 2002;Schroeder and Prentice, 1998; Steffian, 1999; Thombs 2000; Wood et al., 2000). Self-other discrepancies
were defined as differences between (a) personal drinking and/or approval of
alcohol use and (b) estimates of drinking and/or approval of alcohol use by a
reference group. These studies rendered 102 separate tests of SODs in
descriptive and injunctive norms, representing the responses of 53,825
participants
In addition to
providing the requisite statistical information, each hypothesis test was coded
for direction of effect (+ = reference group’s approval or drinking behaviors
was greater than that of the self ; − = less thanthat
of the self), gender (% male), and school size: these three predictors were
directly coded by two judges with perfect agreement. Campus size was
obtained from undergraduate populations reported in campus websites or in Custard et al. (2000). Two additional
predictors addressed methodological features: reference groups and question
specificity. Four judges were asked to rate all 28 of the reference
groups used in the included studies on a scale of 0 (proximal –
defined as “close by, next or nearest to the participant”) to 100 (distal –
defined as “farthest away from the participant”; mean interjudge r =
.759; Spearman-Brown effective reliability R = .925). Each reference group was
assigned the mean rating of the four judges and this value used as a predictor.
For question specificity, the judges also rated the 34 different
types of questions used to assess norms in each study on a scale of 0
(“specific attitudes or behaviors”) to 100 (“vague attitudes or behaviors”;
mean interjudge r = .849; Spearman-Brown effective reliability R =
.957).
Each hypothesis
test and its corresponding predictor information for the meta-analytic database
are presented in Table 1. Effect sizes used
in this meta-analysis represent the within-subject mean difference between self
and other ratings. All analyses were conducted using Mullen’s Advanced BASIC
meta-analytic database management system (Mullen 1989), which employs Rosenthal and
Rubin techniques (Rosenthal 1991): the significance level of an
effect is provided by Z, or standard normal deviate, and its
associated p value; ZFisheris used as an indicator of effect size; and relationships between
predictors and effect sizes are provided by the correlation coefficient r.
Hypothesis tests included in the meta-analytic database.
Results
General Effects
The combined
results of the 102 tests of the self-other discrepancy, leaving each hypothesis
test unweighted (i.e., weighting by unit 1) revealed a significant (Z = 91.847,
p = 2.94E–39), medium (ZFisher = 0.342) effect. Of the 102 hypothesis tests, 93 (91%) reported a
positive self-other discrepancy (participants viewed others as drinking more or
having more tolerant views of alcohol use than themselves). An extremely
substantial failsafe number of Nfs(p=.05) = 317, 878.8 indicates that close
to 318,000 studies reporting no SODs would be required before the results of
this meta-analysis could be ascribed to sampling error. Thus, there appears to
be substantial evidence supporting the existence of self-other norm discrepancy
among college students.
Two considerations
should be noted regarding these analyses. First, unweighted analyses were
necessary because of an inordinate discontinuity on sample size: one of the
studies (Perkins et al., 1999) had a much larger sample
size (N=45,853) than any of the other studies included in the meta-analysis
(whose mean sample size was N=362). Weighting by sample size would have
resulted in the SODs from this study overwhelming the effects from other studies.
However, it should be noted that the effect rendered by thePerkins et al. (1999) study was
functionally equivalent (mean ZFisher = .439) to the mean effect of the remaining 22 studies (mean ZFisher = .476).
Second, the included studies reported a varying number of hypothesis tests, and
each was treated as an independent observation: this assumption of independence
is patently false. However, without making this assumption, we would have been
forced to choose the “best” hypothesis test from each study or to pool the
results from all the hypothesis tests to create a single test. Both of these
alternatives create more problems with assumptions and arbitrariness than the
present assumption of independence.
Consider the
results of a supplemental meta-analysis of wholly independent effects, in which
multiple hypothesis tests from each study were combined into a single test
(e.g., the 24 hypothesis tests fromBourgeois and Bowen (2001) were combined
into a single effect size). This provided 23 distinct, wholly independent
hypothesis tests, one from each study. The results of this supplemental
meta-analysis (unweighted mean ZFisher = .474) are somewhat greater in
magnitude than those of the meta-analysis of the entire main database
(unweighted mean ZFisher = .342). As the effect sizes for both the main and supplemental
meta-analyses are both in the moderate range (Cohen, 1977), the degree of distortion
engendered by the assumption of independence in the original 102 hypothesis
tests in the main database is (at worst) tolerable.
Predictors of SODs
Norm Type
A significant
(Z = 84.713, p = 2.94E–39), small (ZFisher = .291)
effect was obtained for the 65 hypothesis tests that tested SODs in descriptive
norms. A significant (Z = 40.218, p = 2.94E–39), medium (ZFisher = .433)
effect was obtained for the 37 hypothesis tests based on comparisons involving
injunctive norms. The difference between the magnitudes of these two effects
was significant (Z=5.587, p=1.315E–08), indicating that SODs in student’s
perceived approval of alcohol use (injunctive norms) exceeded those in drinking
behaviors (descriptive norms).
Gender
SODs varied as
a function of gender (r = −.181, Z = 4.331, p = 7.51E–06). In
general, then, women report greater SODs than men when evaluating norms. To
test whether this was the case for both injunctive and descriptive norms, a
supplementary analysis was performed. Studies that used single-gender samples
were eligible for this analysis, and effect sizes derived from men- or
women-only statistical tests (e.g.,Bourgeois and Bowen, 2001). For injunctive
norms, a significant (Z = 28.406, p = 2.94E–39), medium (ZFisher = .460)
effect was obtained for the 18 hypothesis tests that tested women’s SODs. A
significant (Z = 24.109, p = 2.94E–39) but smaller (ZFisher = .392)
effect was obtained for the 18 hypothesis tests that evaluated men’s SODs. The
difference between the magnitudes of these two effects was significant (Z =
1.567, p= .058), indicating that there were greater SODs in women’s
perceived injunctive norms than for men. For descriptive norms, women exhibited
greater SODs (18 hypothesis tests; Z=26.367; p = 2.94E–39; ZFisher = .295)
than did men (29 hypothesis tests; Z=14.231; p = 2.58E–32; ZFisher = .186),
and the difference between the magnitudes of these two effects was also
significant (Z = 3.024, p = .001). In sum, women exhibit greater SODs
when reporting both injunctive and descriptive norms.
Greek membership
The influence
of Greek membership on these results must be considered, for two reasons.
First, members of the Greek system tend to perceive non-members’ drinking as
being less than their own. Second, comparisons of Greek and
non-Greek members’ norm perceptions are confounded by norm type. Specifically,
all Greek-only studies evaluated descriptive norms (Baer and Carney, 1993; Carter and Kahnweiler, 2000; Larimer et al., 1997), and all non-Greek only
studies evaluated injunctive norms (Prentice and Miller, 1993; Schroeder and Prentice, 1998). To explore the
influence of Greek membership on SODs, two supplementary analyses were
performed. A comparison of the norm perception of Greeks versus non-Greeks
revealed a significant tendency for SODs to decrease as a function of Greek
membership. Specifically, a significant (Z = 7.89, p = .832E-15) but
small (ZFisher = .058)
effect was found for the 26 hypothesis tests that used Greek members. The 10
hypothesis tests using non-Greek samples produced a significant (Z =
14.587, p = 3.48E-33), moderate (ZFisher = .375) effect. The SODs
in the 66 hypothesis tests using mixed samples (i.e., contained both members
and non-members of the Greek system) were also significant (Z =
103.55, p = 2.94E-39), demonstrating a moderate (ZFisher =.449)
effect size. As expected, the difference between the magnitude of Greek versus
non-Greek SODs was quite significant (Z = 7.167, p= 9.45E-13), indicating
that Greek members perceive significantly smaller SODs.
Because Greek
membership is confounded with norm type, we compared the effect sizes of SODs
for injunctive and descriptive norms in mixed samples. A significant (Z =
14.395, p = 1.026E–32), small (ZFisher = .146) effect was obtained for
the 36 hypothesis tests that tested descriptive norms. A significant (Z = 102.92, p =
2.94E–39), larger (ZFisher = .446) effect was obtained for the 39 hypothesis tests from the
injunctive norms studies. The difference between the magnitudes of these two
effects was significant (Z = 36.461, p = 2.94E–39). Thus, these
analyses confirm that greater SODs in injunctive norms than in descriptive
norms were observed in the subset of studies that utilized mixed samples, just
as in the main analyses.
Reference Group
SODs also
varied as a function of the proximity of the reference group (r = .139, Z
= 3.589,p = 1.66E–4). As the reference group becomes more distant (e.g.,
the average student on campus), the magnitude of the SODs becomes greater.
Question Specificity
A significant
(r = −.121, Z = 3.206, p = 6.735E-4) negative relationship
emerged between the specificity of the question and the magnitude of the SOD.
The more specific the behavior assessed by the question, the smaller the
self-other discrepancies. Therefore, SODs become more extreme when evaluating
behaviors or attitudes defined in vague or general terms.
Campus Size
A corresponding
campus size could be obtained for 98 hypothesis tests. The Perkins et al. (1999) study was excluded
because it used aggregate data from over 140 different schools. A significant
inverse relationship emerged between SODs and the size of the campus (r =
−.419, Z = 10.125, p = 2.7197E–21). Thus, students on larger campuses
report smaller SODs than students on smaller campuses.
Discussion
This
meta-analysis provides a quantification of the extent of the discrepancy
between students’ descriptions of their own drinking behaviors and attitudes
towards drinking, and their perceptions of others’ drinking behaviors and
attitudes. The findings confirm that most students view themselves as drinking
less and being less approving of alcohol use than peer reference groups;
overall, the effect size was medium, according to guidelines established
by Cohen (1977). However, the magnitude of norm
misperception is influenced by several factors related to the type of norm
assessed, the students, campus and the framing of the question. First,
self-other discrepancies in injunctive norms are larger than those for
descriptive norms. Second, women tend to overestimate descriptive and
injunctive norms to a greater extent than do men. Third, self-other
discrepancies increase as the reference group becomes more distal. Fourth,
specific questions tended to result in smaller SODs than more vague ones.
Fifth, large campuses were found to have smaller SODs than smaller campuses.
Thus, many different factors contribute to the (in)accuracy of perceived norms.
The findings of this study have implications for future social norms research.
One conclusion
that can be drawn from this meta-analysis is that the degree of norm
misperception may be, in part, a result of how the norm is assessed.
Specifically, the proximity of the reference group to the individual and the
specificity of the information being obtained should both be carefully
considered when assessing drinking norms. To clarify these effects, a
supplemental analysis was performed comparing studies that assessed norms of
distal targets using a non-specific question (conditions that should result in
greater SODs) versus studies that assessed norms of proximal targets using
specific questions (conditions that should result in smaller SODs). Indeed, the
fourteen SODs derived from distal targets with non-specific questions were
significantly larger (mean ZFisher = .441) than the fourteen SODs derived from proximal targets with
specific questions (mean ZFisher = .285; Z = 3.544, p = .0002). Thus, using non-specific
questions with distal reference groups will result in larger self-other
differences than using specific questions with proximal reference groups.
Researchers should carefully select their reference groups and assess specific
behaviors and attitudes in order to gather information relevant to the students
that are trying to influence. Such efforts will reduce inflated SODs that may
be a result of challenging questions rather than a genuine misperception of
norms.
These
assessment considerations aside, perhaps the most important aspect of norm
(mis)perception is its relevance for behavior and attitude change. To date, the
inclusion of norm education in interventions aimed at reducing college drinking
has had promising results. Interventions that attempted to change descriptive
norms have reported significant reductions in norm perception (Barnett et al., 1996; Borsari and Carey, 2000;Haines and Spear, 1996; Steffian, 1999; Walters, 2000; Walters et al., 2000); furthermore,
self-reported alcohol use decreased following most of these interventions.
Therefore, descriptive norm education, administered in a variety of formats,
appears to be an effective method of changing student perceptions of others’
drinking. It is unclear whether similar changes occur with injunctive norms;
only two interventions have been published. One large scale study found that
four weeks after receiving norm education, both dormitory residents and Greek
members reported decreases in the perceived approval of alcohol use of close
friends and the typical student (Barnett et al., 1996). In contrast, Schroeder and Prentice (1998) did not
detect any group differences in norm perception at a longer (4–6 month)
follow-up. These studies indicate that correcting misperceived norms may have
some influence on behavior; however, precisely how this may occur is unclear.
Therefore, this meta-analytic integration offers some guidance to future
interventions using descriptive and injunctive norms.
First, although
the magnitude of SODs increases as the reference group becomes more distal, it
is possible that the relevance of the reference group decreases as well.
Information relating what the “typical student” does may be easier for the
student to dismiss than the norms of a more relevant group, such as best
friends or fellow Greek members. Thus, it is possible that norms from groups
that are more proximal, and presumably more relevant to the student will be
more likely to result in behavior change than the norms from less relevant
groups. Evidence supporting this hypothesis comes from research indicating that
local norms play more powerful role in self-evaluation than global norms
(Prentice and Miller, 1994). Indeed, everyone is not weighted equally when
creating norms. Instead, personal behaviors and attitudes will be influenced
most by individuals that “are highly similar to the self, share an important
category membership with the self, are reference others [whose behaviors and
attitudes are valued], and place the self in a positive light” (Miller and Prentice, 1996, p. 813). For
example, Agostinelli and colleagues (in press) have
suggested that increases in the problem recognition in personal alcohol use may
occur when college students evaluate the drinking habits of immediate peer
groups instead of more distal individuals. Therefore, social norms
interventions may better serve students by focusing on the drinking of more
proximal, relevant groups (e.g., male freshmen). Although the self-other
discrepancies may be smaller, the information may be impactful. These are
empirical questions that await formal testing.
Second, the
gender of the recipients of norm interventions deserves further consideration.
The results of this meta-analysis suggest that women endorse greater SODs than
men. However, previous research suggests that women are more resistant than men
to changing their misperceptions. For example, Prentice and Miller (1993) found that, at
8 week follow-up, men had reduced their self-other discrepancies, but women
showed no such change. Schroeder and Prentice (1998) replicated
these results, observing that women maintained their injunctive norm
discrepancy over time. An untested hypothesis proposes that gender differences
in the use of alcohol in socialization may have accounted for this change.
Specifically, men may be more visible in the drinking environment than women:
drinking groups tend to be all male or mixed genders. As a result, men assume
that normative information applies to other men, and may have to reconcile
their personal use with perceived norms. Although women tend to report greater
SODs, they may perceive norms to be more descriptive of men’s behavior than
their own. Thus, generic normative feedback may have a lesser influence on
women’s drinking (Read et al., 2001). The implication of this finding is that
normative information may have to be gender-specific to have an effect on
women’s alcohol-related behaviors and attitudes.
Third, the size
of the campus may also influence the effects of social norms campaigns on
behavior. The finding that the larger the campus, the smaller the SODs reported
by students was counter-intuitive; however, this may have been a function of
the way students estimate the descriptive and injunctive norms. Students on
small campuses may consider their friends as representative of the campus in
general. Therefore, these students would have a vested interest in estimating
that others on campus drink more and are more approving of alcohol use than
they. To think otherwise would imply that they were among the heaviest drinkers
on campus, a realization that would make many students uncomfortable.
Therefore, there is a distinct advantage of misperceiving norms on smaller
campuses. On larger campuses, however, students may realize that they don’t
personally know most of the other students. As a result, the behaviors of the
other students may not be seen as relevant, or even knowable. Estimating the
behaviors and attitudes of a large campus may be a much more difficult task. As
a result, when making their estimates, students on larger campuses may rely
more on their personal behaviors and attitudes and those of their friends as a
point of reference. Both the decreased relevance of others’ behaviors and
attitudes and the difficulty of making norm estimates may result in the lower
SODs on large campuses. If this is the case, then norms campaigns may be more
effective on smaller campuses because the impact of learning that “most of the
students on this small campus drink this way” may be more influential.
Finally, the
intention of the social norms approach is to convey that the actual levels of
alcohol use and attitudes towards drinking on campus are more moderate that
most students suppose (Perkins, 2002). This information challenges
students’ personal beliefs and behaviors that heavy drinking is prevalent and
acceptable, and “as students begin to adhere to more accurately perceived norms
that are relatively more moderate, the actual norms become even more moderate
as the process of misperception leading to misuse is reversed” (Perkins, 2002, p. 169). However, given the
limitations of the evaluation research conducted thus far, it is difficult to
ascertain what is responsible for observed campus-wide reductions in drinking
following a norms intervention (e.g., Haines and Spear 1996). Such reductions may be
a reflection of actual behavior and/or attitude change or a norm-driven
response bias. Being educated on accurate drinking norms on campus may make
students wary of reporting their own use as exceeding those norms. Therefore,
it is important to establish the relationship between SODs and personal alcohol
use to determine precisely how these interventions have influenced behavior.
These questions
reflect the paradox that faces researchers as they attempt to develop social
norms messages that can be effective and influence the
greatest number of students. Dissemination of accurate normative information to
correct large SODs may encourage individuals to change personal approval of
alcohol use and/or drinking behaviors. Such a monotonic relationship between
the size of SODs and behavior/attitude change would recommend the use of
injunctive norms, distal reference groups, and non-specific questions as the
most effective ways to provoke the largest SODs that would prompt
self-evaluation in students. However, it is unclear that normative information
addressing these SODs would be effective; to the contrary, it may be relatively
easy for the student to dismiss. In particular, the relevance of the reference
group being conveyed also must be considered: Information about peer groups of
little importance to the individual may not bring about much re-evaluation of
one’s drinking. This presents a problem, as smaller SODs exist among the
reference groups that are likely to be the most proximal (and likely more
relevant) to the student. Therefore, future research needs to address the
relationship between SODs and perceived relevance of the normative comparison
in order to develop the most effective means of communicating to the students
the notion that others don’t drink as much as they originally supposed.
Some
limitations of this meta-analytic integration should be noted. First, norm type
and Greek membership were confounded, making it difficult to determine the
respective influence of these two variables on SODs. Second, the interrater
reliabilities for the proximity of the reference group and question
specificity, while acceptable, were not perfect. The challenge deriving
proximity ratings from the literature suggests that future research using SODs
should make explicit their assumptions about the proximity of reference groups.
Third, because we used group means to calculate SODs, we were unable to test the
relationship among the predictors, SODs, and personal alcohol use. As a result,
we cannot test the question of whether the relationship between SODs and
alcohol use is equally strong at all levels of potential predictors. Prior
research has shown that the SOD-consumption relationship is robust, even when
all the factors that might affect the size of the SOD (our predictors) are left
to vary. Therefore, a systematic evaluation of these potential moderating
relationships is the logical next step for research in this field.
In sum, a
variety of factors influence the perception of self-other discrepancies in
drinking behavior and alcohol-related attitudes. The social norms approach is a
promising prevention strategy because it is based on actual data about alcohol-related
attitudes and drinking behaviors on campus. That said, the results from this
meta-analysis reveal that the respondent gender, type of norm assessed,
reference group, question specificity, and campus size all influence the size
of the SOD. Social norms correction efforts should consider factors related to
the assessment methods, person variables, and the campus context to maximize
their effectiveness.
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