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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)

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Tallahassee, FL, 32306-1530.
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Abstract
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

Introduction
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.
Literature Review
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).
Hypotheses
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 
beverages excessively.
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
Methods
Participants
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.
Procedures
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 
SurveyPro software.
Measures
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 
research (1978).
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).
Results
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.
Discussion
	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.
Limitation
	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
Variables
Mean
s.d.
alpha
Campaign Exposure
Attitude
Perceived Norm
Self-Efficacy
Personal norm for campaign
Personal norm for behavior
Behavioral Intention
3.08
3.41
2.90
3.87
2.68
3.23
4.56
3.92
0.75
1.01
     1.04
     1.01
     1.54
1.07

0.71
0.85
0.92
0.86
0.91




















Table 2. Pearson Zero-Order Correlation
Exposure
Attitude
Perceived norm
Personal norm (campaign itself)
Personal norm (individual behavior)
Self-efficacy
Attitude
Perceived norm
Personal norm
(campaign itself)
Personal norm
(individual behavior)
Self-efficacy
Likelihood of drinking
0.065
0.119
-0.189*

0.122

-0.113
0.126

0.553**
-0.192*

0.539**

-0.355**
0.410**


-0.334**

0.618**

-0.295**
0.432**




-0.390**

0.187*
-0.194**






-0.336**
0.470**







-0.225*
* p<0.05 (two-tail),** p<0.01(two-tail)

















Table 3. Likelihood of Drinking as a Function of Modeled Variables: 
Hierarchical Regressiona
Step
Variable added to regression
R2
R2 Change
Regression coefficient (_)
1. Controls


2. Attitude
3. Perceived Norm
4. Self-Efficacy
5. Personal Norm (for campaign itself)
6. Personal Norm
   (for individual behavior)
Gender
School Year
Religious Affiliation


0.020
0.178
0.253
0.262
0.274
0.324


0.020
0.158**
0.075**
0.009
0.012
0.050**
0.183
-0.003
-0.011
0.402*
0.193
-0.064
-0.079
0.214**
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.
















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