This paper was presented at the Association for Education in Journalism and
Mass Communication in San Antonio, Texas August 2005.
If you have questions about this paper, please contact the author
directly. If you have questions about the archives, email
rakyat [ at ] eparker.org. For an explanation of the subject line,
send email to
[log in to unmask] with just the four words, "get help info aejmc," in the
body (drop the "").
Contributions of Personal Norms
on the Integrated Framework of College Students' Alcohol Consumption Behavior
Taejin Jung (FSU doctoral student)
Megan Fitzgerald (FSU doctoral student),
Xiao Wang (FSU doctoral student)
FSU College of Communication
Suite 432, Diffenbaugh Building
Tallahassee, FL, 32306-1530.
E-mail: [log in to unmask]
The traditional behavioral predictive attempt of Ajzen's theory of
planned behavior and its' application on the health arena named of
integrative model of behavioral prediction has been under critique on
the lack of comprehensiveness in that it overlooked "an individual's
internalized moral rules" which contradict with perceived norm
construct. This study tried to investigate whether the separate
addition of measures of personal norms in evaluating FSU alcohol
campaign may substantially improve prediction of individual
intentions on drinking.
Contributions of Personal Norms
on the Integrated Framework of College Students' Alcohol Consumption Behavior
Previous researches have observed that binge drinking, defined as men
who consume five or more drinks at a single setting and women who
consume four or more drinks in a row, continues to pose challenges
for the college campuses in the United States (Wechsler et al., 1994;
2000). The problems associated with binge drinking or excessive
alcohol consumption are many, including traffic violations and
fatalities (Wechsler & Issac, 1992; Wechsler et al., 1995), unplanned
and unsafe sexual activity, physical and sexual assault (Abbey et
al., 1996), physical injuries or cognitive impairment (Hanson & Engs,
1992), poor academic performance (Presley, Meilman, & Lyerla, 1993),
and trouble with law enforcement authorities (Youth Risk Behavior
Survey Report, 1991). The consequences of college student alcohol
abuse are severe and costly.
Several reasons are commonly mentioned when explaining why college
students drink alcohol beverages excessively. These include peer
pressures, easy access to alcohol, and greater exposure to drinking
opportunities (McEneaney & Fishbein, 1983; Futch et al., 1984,
Strickland & Pittman, 1984; Atkin, 1989). Many colleges and
universities expect or tolerate reasonable amount of alcohol
consumption among students, but find the negative consequences of
excessive alcohol consumption problematic (wolburg, 2001). Campaign
initiatives have been used to decrease binge drinking instead of
infusing a sense of total abstinence.
Following the rationale of the Perkins and Berkowitz (1986)'s
approach to college drinking behavior, which initiated the social
norm approach that students overestimated their peer students'
support of permissive drinking behaviors, and that this miscalculated
estimation correlated with college students' drinking behavior, lots
of colleges and universities identified the effectiveness of social
norm strategies and confidently applied the methods to reduce campus
alcohol consumption. Florida State University is also committed to
ensuring that FSU students have a safe and responsible experience
with alcohol through a multitude of media outlets that were
specifically accessible to FSU students (www.therealproject.fsu.edu).
Even though the FSU alcohol campaign is mainly focus on communicating
with student on the proper norms of alcohol consumption in campus,
employing an established theoretical framework is pertinent when
evaluating the campaign outcome.
The traditional behavioral predictive attempt of Ajzen (1985)'s
theory of planned behavior and its' application on the health arena
(Fishbein & Yzer, 2003) named of integrative model of behavioral
prediction suggested that behavioral intention is the best predictor
on subsequent individual behavior.
But there has been critique on the comprehensiveness of the theory of
planned behavior in that it overlooks "an individual's internalized
moral rules (personal norms)" which contradict with perceived norm
construct (Parker, Manstead, & Stradling, 1995). Personal norm
reflects an individuals' decision on the rightness of subsequent
behavior based on their moral standards while perceived norm reflects
the individual's perception about what important others would want
them to do (Schwartz & Fleishman, 1978). In advance, an individual's
moral sympathy with health campaign itself is entirely different with
his or her submissive compliance on the following behavioral
guideline suggested by the campaign. In the campus alcohol campaign,
if a student morally comply with the gist of campaign, it is well
likely that he or she is more likely to change their behavioral
intentions on alcohol consumption that may in accordance with the
purport of campaign.
This study tried to investigate whether the separate addition of
measures of personal norms in evaluating FSU alcohol campaign may
substantially improve prediction of individual intentions on
drinking. Normally, personal normative and moral influence is an
important factor in shaping intentions to perform behaviors that are
socially controversial (Parker, D., Manstead, A., & Strandling, 1995).
This article begins with a few common social intervention strategies
followed by the description of main variables of protective health
campaign that compose the integrative model of behavioral prediction.
The separated application of personal norm factors will implement the
integrated health model that will be used as a framework to evaluate
the effectiveness of alcohol campaign of FSU. The investigation of
underlying theoretical explanations and of effectiveness of the
separated personal norm approaches would render us new possible
strategies of media health campaign.
Integrated theoretical model
A lot of theories have been applied to health-related behavioral
research as diverse as health-belief model (Becker, Maiman, Kirscht,
Haefner, &, Drachman, 1987), protection motivation theory (Rogers,
1975), stage of change (Prochaska, et al., 1994), elaboration
likelihood model (1981), and theory of planned behavior (Ajzen,
1985). Although many theories have been applied to health-related
behavioral research and to the development of behavioral
interventions, there are limited number of variables that need to be
considered in predicting and understanding any given behavior (Slater, 1999).
Three critical determinants of a person's intentions and behaviors
are as follows: (a) the person's attitude toward the behavior, which
is based on one's salient beliefs about the consequences of
behavior weighed by evaluation of each of those consequences; (b)
self-efficacy, which reflects the degree of control the individual
perceives himself/herself to have over performance of behavior; and
(c) perceived norms, which include the perception that those of
important others support the person's adoption of the behavior
(Fishbein & Yzen, 2003).
Fishbein argued that attitude, perceived norms, and self-efficacy
variables solidify intention to perform the health protective
behavior and he continued if a person has formed a strong intention
to perform a given behavior and has the necessary skills and controls
over performing the behavior, and if there are no environmental
constraints to prevent the behavior, it is highly probable that the
behavior will be performed (2000).
Perceived norms & personal norms
Researchers asserted that the recently formulated integrated health
behavioral model omitted individuals' personal beliefs about what is
wrong and what is right (Parker, Manstead, & Stradling, 1995).
According to the perceived norm approach, those objective aspects of
normative force (i.e., prevalence of specific norms) are mainly
balanced by perceived approval and disapproval by significant others
and motivation to comply with other's opinions. It means that the
more a person believes that specific others think he or she should or
should not perform the behavior in question, and the motivation a
person is to comply with those specific others, the stronger the
perceived norms to perform or not perform the behavior will be.
But the perceived norm approach overlooks the importance of each
individual's moral decision that is originated from innate
determination. The morale innate decision is the personal
determination of rightness or wrongness of the specific behavior,
which has nothing to do with social pressures originated from expect
of important others. Abstaining from excessive alcohol consumption
may come from the innate moral decision that binge drinking is
immoral and violation of internalized behavioral rules. Several
studies of a moral dimension of personal norm acknowledged that the
inclusion of personal norms increase the amount of behavioral
variance explained, after controlling for widely accepted predictor
variables like, attitudes, perceived norms, and self-efficacy (Beck &
Ajzen, 1991; Gorsuch & Ortberg, 1983; Raats, Shepherd, & Sparks,
1995). Personal norm constructs have contributed to the understanding
of behavior in diverse areas, mainly in anti-social behaviors such as
shoplifting (Beck & Ajzen, 1991), and traffic violations (Manstead,
1998). Another research extracted personal norm construct to explain
altruistic behavior such as donation and giving alms (Schwartz &
Howard, 1981). Personal norms are more related with the magnitude of
emotion than precise calculation of later behavioral outcomes
(Parker, Manstead, & Stradling, 1995).
Lots of studies on the role of personal norms are mainly concerned
about how to increase an individual's strategy of defensive denial of
socially aversive behaviors, particularly in situation where the
expected negative sympathetic consequences are contradict with
socially accept norms, such as binge drinking. But until now personal
norm studies ignored the individual's different sympathy level of
personal norm on the social campaign itself and moral consent levels
on the subsequent behavioral intention. In a social campaign context,
even though a person consents morally on the campaign theme (e.g.,
reduction of excessive alcohol consumption in college), it is well
understood that the person has another version of argument of their
behavior that is opposite with campaign theme. For example, even
though a student have sympathy on the alcohol campaign theme that
excessive drinking should be regulated, he or she could develop
individualized argument that excessive drinking is inevitable and he
or she can control their behavior within the morally controlled
manner. If an individual's personal norm will not be affect by social
campaign, let alone the sympathetic consent on the legitimacy of
campaign, the amount of behavioral intention variance explained will
hardly be changed.
The FSU alcohol campaign
Like other universities, FSU is committed to ensuring that FSU
students have a safe and responsible experience with alcohol. The
Real Project of FSU advocates the legal and responsible consumption
of alcohol for those students who choose to drink. The Real Project
ads were placed in a multitude of media outlets that were
specifically accessible to FSU students. The target areas included
the student newspaper, FSView, ads on campus buses, FSU student
computer labs, the residence halls and residence hall laundry
facilities, and various information kiosks and bulletin boards across
the FSU campus (http://www.therealproject.fsu.edu).
Our hypotheses represent the relationships that the selected
components of the integrated health model and personal norm construct
have with students' intention to consume alcoholic beverages. We also
expect that those students who have been exposed to the college
alcohol campaign of the FSU Real Project are more likely to adjust
their intentions to be consistent with the theme presented in the
campaign. So, we suggest that:
H1: The more students have been exposed to the college alcohol
campaign, the less likely they will intend to consume alcoholic
The literature review suggests that personal attitudes toward the
consequences of drinking and other personality variables explain
students' intention to drink. We expect students who perceive alcohol
consumption as harmful, and who have more control over their drinking
behaviors are less likely to drink alcoholic beverages or to engage
in binge drinking. Those who perceive friends or family members as
approving of their alcohol consumption are more likely to consume
alcoholic beverages or to engage in binge drinking. Students may also
base their drinking decisions on personal norm, which are composed of
personal norm for "campaign itself" and for "individual behavioral
intention". We also expect that individual personality variables such
as religious affiliation, sex, and grade will increase the amount of
behavioral intention variance explained. Therefore, we propose that
students' intention to binge drink will be associated:
H2: positively with positive attitudes toward the alcohol consumption
H3: positively with perceived norms (approval)
H4: positively with personal norm for campaign itself
H5: positively with personal norm for individual behavior
H6: negatively with self-efficacy
The 132 participants were answered out of 820 random sampled Florida
State University undergraduate students. So, the response rate was
16.1 percent. A researcher in the admissions office used Business
Objects software to generate a list of the entire population of
currently enrolled FSU undergraduate students. The data was then
exported to SPSS in order to draw the random sample. SPSS generated a
list of 820 undergraduate students' email addresses.
Participants were predominately female (70.5 %) and ranged in age
from 18 to 24. Year in school distribution was balanced with freshmen
constituting 17.4%, sophomore 23.5%, junior 29.5%, and senior 29.5%.
The mode of students GPA was within 3.0 to 3.5.
A pilot study was conducted during the summer of 2004. We used the
results from this study to refine our questionnaire and assess our
measures. After revising the survey, SurveyPro software was used to
convert the survey from paper-based to web-based. This software was
then used to email our sample a link to the survey. On September 23,
2004, the first email link to the survey was sent. We received 98
responses. Three days later, we resent the email link—indicating in
bold brightly colored text that anyone who had already completed the
survey should not do so again—and we received 26 additional
responses. On September 29, we emailed a link to the survey for the
final time and received eight additional responses (N=132). The
questions in our survey were based on both prior research and the
pilot study. The data was automatically exported into an SPSS file by
After collecting the data, we created an attitude index. Attitude
index (alpha = 0.71) consisted of eight items such as the likelihood
of upsetting parents and caregivers, getting in trouble with the law,
losing control of myself, being more relaxed, having good time with
friends, feeling better, feeling like I fit in, and upsetting
boyfriend/girlfriend/spouse when drinking four or more drinks in a
row over the next month. The five-point response scale for the
attitude items was anchored with the labels "very likely" and "very unlikely."
The perceived norm index is a four-item index (alpha = 0.85).
Responses could range form "1- completely disapprove" to
"5-completely approve." The important others suggested were as
follows: people most important to you, your friends, your parents and
caregivers, and your boyfriend/girlfriend/spouse. Respondents were
asked: How do you think …. would feel about you drinking four or
more drink in a row on a typical night out? Both attitude and
perceived norm items were borrowed from NIDA (National Institute on
Drug Abuse) survey questionnaire.
The next measure used was the self-efficacy index. This is an 8-item
scale adapted from Sklar and Turner's (2003) research. It included
questions about how confident participants are that they could resist
the urge to drink; if I were angry at the way things had turned out,
if I have trouble sleeping, if I remember something bad that had
happened, if I want to find out if I could drink occasionally without
getting hooked, if I unexpectedly found some booze or happened to see
something that reminded me of drinking, if other people treat me
unfairly or interfered with my plans, if I were out with friends and
they kept suggesting to go somewhere and drink, and if I want to
celebrate with a friend. This scale demonstrates an alpha of 0.92.
The responses for the self-efficacy scale ranged from "1—not at all
confident" to "5—completely confident."
The index for personal norm for campaign itself is a three-item index
(alpha = 0.86). The index have questionnaire such as "I would sign a
petition to be published in the newspaper supporting the alcohol
campaign", "I will vote for a candidate who promised to promote the
alcohol campaign", and "I will give my free time to the alcohol
campaign organization which does not have enough resource to use."
The statements was borrowed from Schwartz & Fleishman's personal norm
The personal norm for individual behavior is two item index (alpha =
0.91). The index include statements like "It would be quite wrong for
me to have four or more drinks in a row, even once or twice over the
next week" and "Having four or more drink in a row, even once or
twice over the next week would make me feel sorry for doing it",
which were excerpted from Parker, Manstead, & stradling's research (1995).
The data analysis was conducted by using the Statistical Package for
Social Sciences (SPSS), mainly employing hierarchical multiple
regression. Mean, standard deviations, and alpha coefficients are
reported in Table 1 for all indexes used.
Insert Table 1 here
Pearson product-moment correlations are summarized in Table 2. To
test each hypothesis, I divided the independent variables as six
blocks: (1) a set of demographic (gender, school year, religious
affiliation), (2) attitude, (3) perceived norm, (4) self-efficacy,
(5) personal norm for campaign, and (6) personal norm for behavior.
Results of the hierarchical regressions are summarized in Table 3.
The hierarchical multiple regression analysis allows the researchers
to recognize the additional variances explained by the later blocks
that are embedded in the hypothesized model. The indexes were entered
one at a time, in the causal order specified by the theoretical
discussion. Following the previous literature the index that explain
more variance will enter ahead. Demographic variables were entered
together in the first step as controls, followed by additional key
variables shown above.
Insert Table 2 here
Exposure to the alcohol campaign was not correlated with the
students' estimation of likelihood of drinking (r = 0.126, p > 0.05),
indicating that exposure to the campaign was not directly related
with the intention on alcohol consumption. The low exposure to the
campaign (M = 3.08, per a week) could be a logical explanation on the
non-significant relation with likelihood of drinking as well as
attitude (r = 0.07, p > 0.05), perceived norm (r = 0.119, p > 0.05),
and self-efficacy (r = -0.113, p > 0.05). Unexpectedly, we found a
negative relation between campaign exposure (r = -0.19, p < 0.05) and
personal norm (for campaign itself), accompanied with the
non-significant positive relation with personal norm for individual
behavior (r = 0.122, p > 0.05).
Insert Table 3 here
First, the demographic control variables–gender, school year, and
religious affiliation- make a negligible contribution to the model.
Second, confirming the hypothesis 2, table 2 showed that positive
attitude toward alcohol drinking is positively associated with
students' intention to drink alcohol in the near future (_ = 0.042, p
< 0.05). Attitude index also made an additional substantial
contribution to explaining variance in alcohol drinking intention,
with a variance of 15.8% (p < 0.01).
Third, perceived approval from parents, friends, and significant
others are on the border significant relation with intention to drink
alcohol in the near future (_ = 0.193, p < 0.1). Given the controls,
the perceived norm index also made a non-negligible contribution on
the variance (7.5%) explained for drinking intention (p < 0.01).
Fourth, self-efficacy, hypothesized to influence alcohol
consumption, was not significantly related with individual intention
to drink alcohol, even though it showed negative effect, which
indicates students who perceive the capability to exercise control
over motivation are less likely to drink excessively in the near
future. Self-efficacy index also made a negligible contribution to
the variance explained, given controls of prior indexes.
Lastly, given controls of previous steps, the personal norm for
individual behavior index had a significant relation with intention
to drink alcohol (_ = 0.214, p < 0.01) and made a significant
contribution to explaining variance (5%) in intention to drink
alcohol (p < 0.01). On the contrary, the personal norm for campaign
index showed non-significant relation with the intention to drink
alcohol (_ = -0.079, p > 0.05) as well as made a little amount of
contribution on the variance explained for alcohol drinking intention.
The results of present study provided further evidences of
additional contribution to the prediction of behavioral intentions by
the personal norm, especially by the personal norm for the behavior
(5 %). In accordance with the integrated health behavior model, the
present findings illustrated that attitude (15.8 %) and perceived
norm (7.5%) indexes are main contributors to the variance of alcohol
consumption intention in the suggested model when controlled other
prior indexes. It could be argued that the personal norm for behavior
is simply another facet of attributes to the behavioral intention,
insofar as the anticipation of negative effect of drinking alcohol
(attitude), the thoughts of important others (perceived norm) still
have their own predictive power on the behavioral intention.
As literature review suggested, the personal norm for campaign
itself showed no relation with the intention of alcohol consumption
and gave little contribution to the variance explained, indicating
that the alcohol campaign itself does not have an impact on the
students' intention on alcohol drinking, even though it has
significant correlation with campaign exposure. Those separate
results (significant correlation between campaign exposure & personal
norm for campaign itself, and significant relation between personal
norm for behavior & intention to drink alcohol) gave us an insight
that limited amount of exposure to the alcohol campaign could give us
reasonable explanation. An analysis of Nielsen data conducted by
Emerry, Sczcypka, and Terry-McElrath (2002) showed that normal
exposure to the tobacco and pharmaceutical ads did not influence
youth audiences' attitude about the concerned behavior. At the
present study, the low campaign exposure (M = 3.08, per a week) set a
limit on the change of behavioral intention.
The media priming approach indicates that frequent exposure to the
media messages increases attitude accessibility to an object, which
may have an effect on people's later behavior (Roskos-Ewoldsen,
Roskos-Ewoldsen, & Carpentier, 2002). If we are to expect frequently
exposed messages to be indicators of ensuing behavioral intention
suggested by network model of media priming, the messages should be
memorized in our brain as knowledge. In order to be saved as
knowledge for later behavioral indicators, the exposed campaign
messages should draw attention in advance and be understood
cognitively by the target audience. The cognitively processed
messages are more likely to be retained in the memory as an
attitudinal indicator. So, exposed college alcohol campaign messages
should be processed the cognitive-behavioral procedure (i.e.,
exposure-attention-cognition-retention) in order to be indicators of
later behavioral intention. To achieve anticipated campaign outcomes,
higher exposures to anti-alcohol messages are prerequisite, which
leads to higher recall of campaign message and higher likelihood of
abstaining alcohol drinking.
In the actual application of theory to the campaign situation, the
additional variance explained by the personal norms provides a clue
as to how the problem of irresponsible drinking could be tackled in
the future. Safe drinking education campaign might an attempt to
foster among college students a sense of the inherent wrongness of
exposing oneself and others to abuse drinking. Frequently emphasizing
negative feelings of binge drinking though various media (Internet,
poster, newspaper, billboards, etc.) could make the current binge
drinkers feel bad, even if he or she does not change behavior in the
near future, and remind them of duties of careful drinking in campus.
The low response rate (16.1%) of online survey employed for this
study provoked the problem of non-response error. Non-response error
arises through the fact that not all people included in the sample
are willing or able to complete the survey (Cooper, 2000). Couper,
Blair, and Triplett (1999) have compared response rates from e-mail
studies to mail surveys of the same population and found that for all
but one study, the e-mail survey failed to reach the response rate
levels of mail surveys. The first reason for the low response rate
may attribute to the lack of motivation tools used in mail surveys
(e.g., advance letters, letterhead, incentives, etc.). A second
possible reason for lower response rate may be related to
confidentiality concerns with respect to electronic mail. Some person
may be reluctant to make public their personal tendency on alcohol
consumption that is particularly sensitive. The problems of
non-responsive rate will likely become increasing prominent and
effective measures should be resorted.
Table 1 Means, Standard Deviations, and Reliabilities of Indexes
Personal norm for campaign
Personal norm for behavior
Table 2. Pearson Zero-Order Correlation
Personal norm (campaign itself)
Personal norm (individual behavior)
Likelihood of drinking
* p<0.05 (two-tail),** p<0.01(two-tail)
Table 3. Likelihood of Drinking as a Function of Modeled Variables:
Variable added to regression
Regression coefficient (_)
3. Perceived Norm
5. Personal Norm (for campaign itself)
6. Personal Norm
(for individual behavior)
a Significance is tested for increment to R2 and regression
coefficients for the indicated step only. The increment to R2
provides a measure of the indicated variable's contribution to the
model's explanatory power, controlling for the variables indicated in
the previous steps (Cohen & Cohen, 1983).
* p<0.05, **p<0.01.
Ajzen, I. (1985). From intentions to actions: A theory of planned
behavior. In J. Kuhl & J. Beckmann (Eds), Action Control: From
Cognition to Behavior, pp. 11-39. Berlin: Springer-Verlag.
Abbey, A., Ross, L. T., McDuffie, D., & McAuslan, P. (1996). Alcohol
and dating risk factors for sexual assault among college women.
Psychology of Women Quarterly, 20(1), 147-169.
Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the
theory of planned behavior. Journal of Research in Personality, 25, 285-301.
Becker, M. H., Maiman, L. A., Kirscht, J. P., Haefner, D. P., &
Drachman, R. H. (1977). The health belief model and prediction of
dietary compliance: A field experiment. Journal of Health and Social
Behavior, 18(4), 348-366.
Binge Drinking Blows Campaign. (2001). www.scpinet.org downloaded on
April 19, 2001.
Cohen, J., & Cohen, P. (1983). Applied multiple regression analysis.
Hillsdale, NJ: Erlbaum.
Cooper, M. P. (2000). Web surveys: A review of issues and approaches.
Public Opinion Quarterly, 64 (4), 464-494.
Cooper, M. P., Blair, J., & Triplett, T. (1999). A comparison of mail
and e-mail for a survey of employees in federal statistical agencies.
Journal of official statistics, 15 (1), 39-56.
Emery, S., Sczcypka, G., & Terry-McElrath (2002). Youth smoking
behavior and exposure to television anti-smoking advertising. Funded
by State and Community Tobacco Control Initiative, National Cancer
Institute, and The National Initiative on Drug Abuse.
downloaded on Nov 14, 2004.
Fishbein, M. & Yzer, M. C. (2003). Using theory to design effective
health behavior interventions. Communication Theory, 13(2), 164-183.
Futch, E. J., Lisman, S. A., & Geller, M. I. (1984). An analysis of
alcohol portrayal on prime-time television. The International Journal
of Additions, 19, 403-410.
Gorsuch, R. L., & Ortberg, J. (1983). Moral obligation and attitudes:
Their relation to behavioral intention. Journal of Personality and
Social Psychology, 44, 1025-1028.
Hanson, D. J., & Engs, R. C. (1992). College students' drinking
problems: A national study. Psychological Report, 71, 39-42.
Manstead, A. S. R. (1998). The role of moral norm in the
attitude-behavior relationship. In D. J. Terry & M. A. Hogg (Eds.),
Attitudes, behavior, and social context: The role of norms and group
membership. Mahwah, NJ: Lawrence Erlbaum.
Marcus, D. L. (2000). Drinking to get drunk: Campuses still can't
purge binging behavior, U.S. News & World Report, 128(12), 53-54.
McEneaney, K., & Fishbein, P. (1983). Drug abuse among young
adolescents. PTA Today, 8, 9-13.
O'Sullivan, S. (2001). Drinking habits die hard at University of
downloaded on May 30, 2001.
Parker, D., Manstead, A. S. R., & Stradling, S. G. (1995). Extending
the theory of planned behavior: The role of personal norm. British
Journal of Social Psychology, 34, 127-137.
Perkins, H. W., & Berkowitz, A. D. (1986). Perceiving the community
norms of alcohol use among students: Some research implications for
campus alcohol education programming. International Journal of the
Additions, 21(9), 961-976.
Petty, R. T., & Cacioppo, J. T. (1981). Attitudes and Persuasion:
Classical and contemporary approaches. Dubuque: IA: William C. Brown, Co.
Presley, C. A., Meilman, P. W., & Lyerla, R. (1993). Alcohol and
drugs on American college campuses: Use, consequence, and perceptions
of the campus environment, 1, Carbondale, IL: The Core Institude.
Prochaska, et al. (1994). Stages of change and decisional balance for
12 problem behaviors, Health Psychology, 13, 39-46.
Raats, M. M., Shepherd, R., & Sparks, P. (1995). Including moral
dimensions of choice within the structure of the theory of planned
behavior. Journal of Applied Social Psychology, 25, 484-494.
Rogers, R. W. (1975). A protection motivation theory of fear appeals
and attitude change. The Journal of Psychology, 91, 93-114.
Roskos-Ewoldsen, D. R., Roskos-Ewoldsen, B., & Carpentier, F. (2002).
Media priming: A synthesis. In J. Bryant & D. Zillmann (Eds.), Media
effect (2nd ed., pp. 427-451). Lawrence Erlbaum Associates, NJ: Mahwah
Schwartz, S. H., Fleishman, J. A. (1978). Personal norms and the
mediation of legitimacy effects on helping. Social Psychology, 41(4), 306-315.
Schwartz, S. H., & Howard, J. A. (1981). A normative decision-making
model of altruism. In J. P. Rushton & R. M. Sorrentino (Eds.),
Altruism and helping behavior: Social, personality, and developmental
perspectives (pp. 189-211). Hillsdale: Lawrence Erlbaum.
Sklar, S., & Turner, N. (1999). A brief measure for the assessment of
coping self-efficacy among alcohol and other drug users. Addition,
Strickland, D. E., & Pittman, D. J. (1984). Social learning and
teenage alcohol use: Interpersonal and observational influences
within the sociocultural environment. Journal of Drug Issues, 14, 137-150.
Wechsler, H., Davenport, A., Dowdall, G. W., Moeykens, B., &
Castillo, S. (1994). Health and behavioral consequences of binge
drinking in college. Journal of the American Medical Association,
Wechsler, H., Kelly, K., weitzman, E. R., Giovani, J.P.S., & Seibrig,
M. (2000). What colleges are doing about student binge drinking: A
survey of college administrators. Journal of American College Health,
Wolburg, J. M. (2001). The "risky business" of binge drinking among
college students: Using risk models for PSAs and anti-drinking
campaigns. Journal of Advertising, 30(4), 23-29.
Youth Risk Behavior Survey Report (1991). Florida Department of
Education, Tallahassee, FL.