AN ABSTRACT OF THE DISSERTATION OF
Laurel Sharmer for the degree of Doctor of Philosophy in Public Health presented on
April 17, 2000. Title: Evaluation of Alcohol Education on Attitude, Knowledge and SelfReported Behavior of College Students
Redacted for privacy
Abstract approved
Annette Rossignol
This research was conducted to evaluate the effectiveness of two different types of
alcohol education interventions on the attitudes about alcohol consumption in college,
knowledge about alcohol, and self-reported alcohol consumption behavior of college
students. The educational interventions were a student-centered CD-Rom interactive
program, and a teacher-centered motivational speaker. Each intervention took
approximately 60 minutes. The research was conducted at a small public university in
Northern New York. Nine classes with a total enrollment of 360 students were randomly
selected for the research. The demographic makeup of the sample was similar to that of
the overall university population, including gender, class level, membership in Greek
organizations and age. Three classes were randomly assigned to the CD-Rom program,
three classes were randomly assigned to hear a motivational speaker, and three classes
were randomly assigned to a control group. The instrument used was the Student Alcohol
Questionnaire (SAQ). Students in all classes completed the SAQ four weeks after the
Fall, 1999 semester began. The interventions were conducted the following week. The
SAQ was administered again four, eight and twelve weeks post-intervention. Two
measures of alcohol consumption behavior were used: A continuous variable measure of
both an-iount of alcohol consumed and consequences related to intoxication, and a
dichotomous variable for "heavy drinking," which is defined as more than five drinks in a
row at least once a week. Multivariate analysis of variance was used to test for
differences across attitude, knowledge and behavior and bivariate combinations of these
outcome variables by group. No statistically significant differences were found on any of
the post-interventions measures for any combination of aftitude, knowledge or behavior.
Analysis of covariance was used to test for behavior difference alone, using the preintervention questionnaire results as the covariate. No statistically significant differences
were found for behavior alone. Multiple regression techniques were used to determine if
alcohol consumption behavior, as measured on the continuous scale, could be predicted
by gender, grade point average, class level or religion. Gender (p
.000) was the only
predictor variable that was statistically significant, with men students consuming more
alcohol than women students.
©Copyright by Laurel Sharmer
April 17, 2000
All Rights Reserved
Evaluation of Alcohol Education on Attitude, Knowledge and
Self-Reported Behavior of College Students
by
Laurel Sharmer
A Dissertation
Submitted to
Oregon State University
Tn partial fulfillment of
the requirements for the degree of
Doctor of Philosophy
Presented April 17, 2000
Commencement June 2000
Doctor of Philosophy dissertation of Laurel Sharmer presented on April 17. 2000
APPROVED:
Redacted for privacy
Major Professor, representing Public Health
Redacted for privacy
Chair of Department of Public Health
Redacted for privacy
Dean of GjaIat'School
I understand that my dissertation will become part of the permanent collection of Oregon
State University libraries. My signature below authorizes release of my dissertation to
any reader upon request.
Redacted for privacy
Laurel Sharmer, Author
ACKNOWLEDGEMENTS
I would first like to acknowledge and thank the students at the State University of New
York at Potsdam who volunteered their time to participate in this research project.
I would also like to express my sincere appreciation and gratitude to my doctoral
committee members: Dr. Leslie Davis-Bums, my Graduate Council Representative; Drs.
Courtney Campbell, Anne Rossignol, and Rebecca Warner, from whom I learned more
than I ever thought possible; and the chairs of my committee, Dr. Timothy White, for his
immeasurable support and guidance; and Dr.Anne Rossignol, for her wisdom, integrity
and good humor. My gratitude goes as well to Dr. Anna Harding for her willingness to sit
as a member of my committee at the last minute.
At the State University of New York at Potsdam I would like to acknowledge and thank:
Kathleen O'Rourke for her collegiality and courageous inspiration;
Dr. Neil Johnson, Dean William Amoriell, and Provost Peter Brouwer for their
infinite patience and faith in me;
Drs. Dave Hanson and Ruth Engs (at Indiana University) for allowing the use of
their questionnaire, and for providing me with advice along the way;
Dr. Nancy Dodge-Reyome and the Office of Faculty Scholarship and Grants for
much needed and appreciated financial support;
All the professors, administrators, computer specialists, secretaries, and student
workers who gave so generously of their time and expertise;
And a special note of gratitude to Ms. Mindy Sheehan, my faithful assistant, for
her many hours of data entry.
Among my family, I would like to acknowledge:
My beloved father, Joe Sharmer, whom I knew for seven short but wonderful
years. In the brief time we had together before he died, he managed to give me
three priceless gifts: An unabashed joy of living, his tender and generous heart,
and unconditional love;
My grandmother, Katherine Sharmer, an immigrant who came to the United
States in 1884. She dreamed that in America, where social class didn't matter, her
children would be able to achieve success with little more than hard work and a
public education. She died as a young widow with four small children in a little
town in western Nebraska on a bitterly cold January day in 1906. Although at the
time of her death she was illiterate, destitute and alone, the completion of this
dissertation is proof that her dream is still alive;
And most importantly, I want to acknowledge two young men and a little girl who
are at once my magnum opus and my raison d'être, my connection to the past, my
hope for the future, and for whom all of this has been done: my sons Jacy and
Keith and my granddaughter Jade.
TABLE OF CONTENTS
Page
INTRODUCTION ............................................................................. 1
............................................................... 1
Research Questions .................................................................. 1
NullHypotheses ..................................................................... 2
Problem Definition .................................................................. 3
LITERATURE REVIEW .................................................................... 5
Introduction ........................................................................... 5
Motivation for Drinking ............................................................ 9
Negative Consequences of Drinking .............................................. 10
Prevention Strategies ................................................................ 12
METHODS .................................................................................... 15
The Instrument ........................................................................ 15
The Interventions .................................................................... 17
Subjects ............................................................................... 19
StudyDesign ......................................................................... 19
Question#1 ........................................................................... 20
Question#2 ........................................................................... 21
Question#3 ........................................................................... 22
Threats to Design Validity......................................................... 23
Additional Descriptive Data ....................................................... 24
Survey Anonymity.................................................................. 24
Statistical Analysis .................................................................. 25
RESULTS ..................................................................................... 26
Description of the Sample ......................................................... 26
Data Screening ...................................................................... 31
Research Question #1 ............................................................... 35
Statement of Purpose
TABLE OF CONTENTS (Continued)
Research Question #2. 37
Research Question #3 ............................................................... 40
...................................................... 42
DISCUSSION ................................................................................. 44
StudyLimitations .................................................................... 55
Recommendations ................................................................... 58
Preintervention Associations
BIBLIOGRAPHY............................................................................ 60
APPENDICES................................................................................ 67
Appendix A The Student Alcohol Questionnaire .............................. 68
Appendix B
Appendix C
Appendix D
Appendix E
Appendix F
Appendix G
Description of the Sample ........................................ 73
Data Screening Graphs and Charts .............................. 76
Data Screening Tables ............................................ 88
Tables of Data in the Analysis of the Research Questions 91
Means and Standard Deviations by Group and Stratified
By Gender, Age, Grade Point Average and Religion ......... 101
Institutional Review Board Applications and Approval ...... 127
LIST OF TABLES
Table
Page
Gender of the Sample
.
27
2.
Summary Results of Analysis of Covariance ................................. 36
3.
Summary Results of Multivariate Analysis of Variance
4.
Summary Results of Multivariate Analysis of Variance for
WomenStudents .................................................................... 39
5.
Coefficients for Multiple Regression
6.
Chi-Square Tests of Association Between Heavy Drinking and
Demographic Variables ............................................................ 43
......................
............................................
37
41
LIST OF APPENDIX FIGURES
Cl.
Histogram of the First Attitude Scores Overlain with a Normal Curve ....... 76
C2.
Histogram of the First Knowledge Scores Overlain with a Normal Curve
C3.
Histogram of the First Behavior Scores Overlain with a Normal Curve ..... 77
C4.
Histogram of the Second Attitude Scores Overlain with a Normal Curve ... 77
C5.
Histogram of the Second Knowledge Scores Overlain with a Normal
Curve............................................................................................................. 78
C6.
Histogram of the Second Behavior Scores Overlain with a Normal Curve. 78
C7.
Histogram of the Third Attitude Scores Overlain with a Normal Curve ...... 79
C8.
Histogram of the Third Knowledge Scores Overlain with a Normal Curve .79
C9.
Histogram of the Third Behavior Scores Overlain with a Normal Curve .... 80
C10.
Histogram of the Fourth Attitude Scores Overlain with a Normal Curve .... 80
C 11.
Histogram of the Fourth Knowledge Scores Overlain with a Normal
Curve............................................................................................................. 81
C12.
Histogram of the Fourth Behavior Scores Overlain with a Normal Curve.. 81
C 13.
Scatterplot of First Attitude Scores with First Knowledge Scores ............... 82
C14.
Scatterplot of First Attitude Scores with First Behavior Scores ................... 82
C15.
Scatterplot of First Knowledge Scores with First Behavior Scores ............. 83
Cl 6.
Scatterplot of Second Attitude Scores with Second Knowledge Scores ...... 83
Cl 7.
Scatterplot of Second Attitude Scores with Second Behavior Scores .......... 84
C 18.
Scatterplot of Second Knowledge with Second Behavior Scores ................ 84
C19.
Scatterplot of Third Attitude Scores with Third Knowledge Scores ............ 85
C20.
Scatterplot of Third Attitude Scores with Third Behavior Scores ................ 85
..
76
LIST OF APPENDIX FIGURES (Continued)
C21.
Scatterplot of Third Knowledge with Third Behavior Scores ...................... 86
C22.
Scatterplot of Fourth Attitude Scores with Fourth Knowledge Scores ......... 86
C23.
Scatterplot of Fourth Attitude Scores with Fourth Behavior Scores ............ 87
C24.
Scatterplot of Fourth Knowledge with Fourth Behavior Scores ................... 87
LIST OF APPENDIX TABLES
Table
Page
Bi.
YearinSchool ........................................................................... 73
B2.
Ethnicity of the Sample
................................................................ 73
B3.
Religions of the Sample
................................................................. 73
B4.
Importance of Religion of the Sample
B5.
Living Arrangement of the Sample ..................................................... 74
B6.
Number of Roommates who "Get Drunk" Each Week ............................ 74
B7.
Grade Point Averages of the Sample ................................................. 75
B8.
Greek Membership of the Sample
Dl.
Statistical Analysis of Normality for Outcome Variables for the
............................................... 74
.................................................... 75
FirstSurvey ............................................................................... 88
D2.
Statistical Analysis of Normality for Outcome Variables for the
SecondSurvey .......................................................................... 88
D3.
Statistical Analysis of Normality for Outcome Variables for the
ThirdSurvey ............................................................................
88
D4.
Statistical Analysis of Normality for Outcome Variables for the
FourthSurvey ............................................................................................... 88
D5.
Correlation Matrix for Outcome Variables for the First Survey ................... 89
D6.
Correlation Matrix for Outcome Variables for the Second Survey .............. 89
D7.
Correlation Matrix for Outcome Variables for the Third Survey ................ 89
D8.
Correlation Matrix for Outcome Variables for the Fourth Survey ............... 89
D9.
Correlation Matrix for the First Behavior Score (Covariate)
And Dependent Variables ............................................................... 89
DlO.
Tests of Between-Subjects Effects for Homogeneity of Regression
Dependent Variable: Second Behavior Score ........................................ 90
LIST OF APPENDIX TABLES (Continued)
Dli.
Tests of Between-Subjects Effects for Homogeneity of Regression
Dependent Variable: Third Behavior Score .................................................. 90
D12.
Tests of Between-Subjects Effects for Homogeneity of Regression
Dependent Variable: Fourth Behavior Score ................................................ 90
El.
Analysis of Covariance Dependent Variable: Second Behavior
Score............................................................................................................. 91
E2.
Analysis of Covariance Dependent Variable: Third Behavior
Score............................................................................................................. 91
E3.
Analysis of Covariance Dependent Variable: Fourth Behavior
Score............................................................................................................. 91
E4.
Box's Test of Equality of Covariance Matrices for Attitude,
Knowledge and Behavior for the Second Survey ......................................... 92
E5.
Multivariate Analysis of Variance for Attitude, Knowledge
And Behavior for the Second Survey ........................................................... 92
E6.
Box's Test of Equality of Covariance Matrices for Attitude and
Knowledge Second Survey ........................................................................... 92
E7.
Multivariate Analysis of Variance for Attitude and Knowledge
For the Second Survey .................................................................................. 93
E8.
Box's Test of Equality of Covariance Matrices for Attitude and
Behavior for the Second Survey................................................................... 93
E9.
Multivariate Analysis of Variance for Attitude and Behavior
For the Second Survey ................................................................................. 93
ElO.
Box's Test of Equality of Covariance Matrices for Knowledge
And Behavior for the Second Survey ........................................................... 93
Eli.
Multivariate Analysis of Variance for Knowledge and Behavior
For the Second Survey .................................................................................. 94
E12.
Box's Test of Equality of Covariance Matrices for Attitude,
Knowledge and Behavior for the Third Survey ............................................ 94
LIST OF APPENDIX TABLES (Continued)
E13.
Multivariate Analysis of Variance for Attitude, Knowledge
And Behavior for the Third Survey .............................................................. 94
E14.
Box's Test of Equality of Covariance Matrices for Attitude and
Knowledge for the Third Survey .................................................................. 95
E15.
Multivariate Analysis of Variance for Attitude and Knowledge
Forthe Third Survey ..................................................................................... 95
E16.
Box's Test of Equality of Covariance Matrices for Attitude
And Behavior for the Third Survey ............................................................. 95
El 7.
Multivariate Analysis of Variance for Attitude and Behavior
Forthe Third Survey ..................................................................................... 95
E18.
Box's Test of Equality of Covariance Matrices for Knowledge
And Behavior for the Third Survey .............................................................. 96
El 9.
Multivariate Analysis of Variance for Knowledge and Behavior
Forthe Third Survey ..................................................................................... 96
E20.
Box's Test of Equality of Covariance Matrices for Attitude,
Knowledge and Behavior for the Fourth Survey .......................................... 96
E21.
Multivariate Analysis of Variance for Attitude, Knowledge
And Behavior for the Fourth Survey ............................................................ 96
E22.
Box's Test of Equality of Covariance Matrices for Attitude and
Knowledge for the Fourth Survey ................................................................ 97
E23.
Multivariate Analysis of Variance for Attitude and Knowledge
Forthe Second Survey .................................................................................. 92
E24.
Box's Test of Equality of Covariance Matrices for Attitude
And Behavior for the Fourth Survey ............................................................ 97
E25.
Multivariate Analysis of Variance for Attitude and Behavior
Forthe Second Survey .................................................................................. 97
E26.
Box's Test of Equality of Covariance Matrices for Knowledge
And Behavior for the Fourth Survey ............................................................ 98
E27.
Multivariate Analysis of Variance for Knowledge and Behavior
Forthe Second Survey .................................................................................. 98
LIST OF APPENDIX TABLES (Continued)
E28.
Summary Results of Discriminant Analysis for the Second Survey ............ 98
E29.
Summary Results of Discriminant Analysis for the Third Survey ............... 99
E30.
Summary Results of Discriminant Analysis for the Fourth Survey ............. 99
E3 1.
Correlation Matrix for Predictor Variables ................................................... 100
E32.
ANOVA for Linear Fit of the Equation ........................................................ 100
F 1.
Means and Standard Deviations for the First Survey by Group ................... 101
F2.
Means and Standard Deviations for the Second Survey by Group ............... 101
F3.
Means and Standard Deviations for the Third Survey by Group ................. 102
F4.
Means and Standard Deviations for the Fourth Survey by Group ................ 102
F5.
Means and Standard Deviations for the First Survey by Group
ByGender .................................................................................................... 102
F6.
Means and Standard Deviations for the Second Survey by Group
ByGender ..................................................................................................... 103
F7.
Means and Standard Deviations for the Third Survey by Group
ByGender ..................................................................................................... 104
F8.
Means and Standard Deviations for the Fourth Survey by Group
ByGender ..................................................................................................... 105
F9.
Means and Standard Deviations for the First Survey by Group
ByAge.......................................................................................................... 106
FlO.
Means and Standard Deviations for the Second Survey by Group
ByAge.......................................................................................................... 107
F 11.
Means and Standard Deviations for the Third Survey by Group
ByAge.......................................................................................................... 109
F12.
Means and Standard Deviations for the Fourth Survey by Group
ByAge.......................................................................................................... 111
F 13.
LIST OF APPENDIX TABLES (Continued)
Means and Standard Deviations for the First Survey by Group
By Grade Point Average ............................................................................... 113
F14.
Means and Standard Deviations for the Second Survey by Group
By Grade Point Average ............................................................................... 114
F 15.
Means and Standard Deviations for the Third Survey by Group
By Grade Point Average ............................................................................... 116
F16.
Means and Standard Deviations for the Fourth Survey by Group
By Grade Point Average ............................................................................... 118
F17.
Means and Standard Deviations for the First Survey by Group
ByReligion ................................................................................................... 119
F18.
Means and Standard Deviations for the Second Survey by Group
ByReligion ................................................................................................... 121
Fl 9.
Means and Standard Deviations for the Third Survey by Group
ByReligion ................................................................................................... 123
F20.
Means and Standard Deviations for the Fourth Survey by Group
ByReligion ................................................................................................... 124
F2 1.
Means and Standard Deviations for the First Attitude and Behavior
Scores by Grade Point Average .................................................................... 126
DEDICATION
This dissertation is dedicated in loving memory to my grandmother,
Katherine O'Conner Sharmer
Evaluation of Alcohol Education on Attitude, Knowledge and
Self-Reported Behavior of College Students
CHAPTER 1
INTRODUCTION
Statement of Purpose
This research was conducted to evaluate the effectiveness of alcohol education
programs for undergraduate college students. It specifically examined undergraduate
students' self-reported alcohol consumption behavior, knowledge about alcohol, and
attitudes towards intoxication. These variables were measured four times: Four weeks
after the beginning of the Fall, 1999 semester and before the students' participation in
one of two types of alcohol education programs and again four, eight and twelve
weeks following the conclusion of the intervention. The intervention was either
participation in an interactive computer-based program about alcohol, or attendance at
a lecture about alcohol by a motivational speaker. One-third of the students in the
sample served as a control group and was not exposed to a program intervention. Also
examined for a potential relationship to alcohol were four variables: gender, grade
point average, class level, and religion.
Research Questions
1.
Is there a significant difference in self-reported alcohol consumption
behavior between undergraduate college students who participate in different types of
alcohol education programs?
2. Are self-reported alcohol consumption behavior, knowledge about alcohol,
and attitudes about alcohol significantly different between undergraduate college
2
students who have participated in different types of alcohol education programs? Are
any differences sustainable for a twelve-week period?
3.
Among undergraduate college students, can self-reported alcohol
consumption behavior be predicted from gender, grade point average, class level, or
religion?
Null Hypotheses
Question #1: Among undergraduate college students who participate in different types
of alcohol education programs, the means for the measurement of the self-reported
post-intervention behaviors will be equal.
(H0:
p1 =
2
i 3)
Question #2: Among college students who have participated in an alcohol education
program, the mean vector for knowledge, attitude and self-reported behavior for each
individual group will be equal to the mean vector for all groups. (H0: V1 = V2
Vk)
2b. Among college students who have participated in an alcohol education
program, the mean vector for knowledge and self-reported behavior for each
individual group will be equal to the mean vector for all groups. (H0: V1 = V2
Vk)
2c. Among college students who have participated in an alcohol education
program, the mean vector for attitude and self-reported behavior for each individual
group will be equal to the mean vector for all groups. (H0: V1 = V2
= Vk)
2d. Among college students who have participated in an alcohol education
program, the mean vector for knowledge and attitude for each individual group will be
equal to the mean vector for all groups.
(He: Vi
V2 = Vk)
3
Question #3:
Among undergraduate college students, self-reported alcohol
consumption behavior cannot be predicted from gender, grade point average, class
level, or religion.
(He: b =0)
Problem Definition
Within the past four years, publicity surrounding alcohol abuse and alcoholrelated deaths on college campuses has increased dramatically. In a recent report, the
percentage of college students who drink to get drunk increased from 39% in 1993 to
52% in 1997 (Wechsler, 1998). This is not a new problem. Alcohol abuse on the
college campus has been in existence for many years. (Sax, 1997), but college
campuses' willingness to discuss and address this issue may have been what currently
has led to more frank discussions of the problem.
The University Police Department of the State University of New York
(SUNY) at Potsdam recently issued a report about alcohol-related incidents during
1997-8 academic year (Hope, 1999). The campus includes approximately 3,500
students and during that year, the university police dealt with 192 incidents involving
students and alcohol. Of these, 149 were criminal in nature and 25 were medical
emergencies.
Increased enforcement by the campus and local police department seems to
have led to an acrimonious relationship between students and police, as evidenced by
a riot in October of 1997 between Potsdam Village police and college students.
Anecdotal evidence from students indicates that because of fear of law enforcement
they are currently less likely to seek medical care for potentially life threatening cases
of intoxication.
To compound the problem, discussions with emergency room administrators at
Canton-Potsdam hospital indicate that medical insurance carriers will not reimburse
4
for self-inflicted alcohol abuse problems. As a result, emergency room physicians
rarely record student cases as alcohol related. This makes data capture difficult, if not
impossible. Canton-Potsdam hospital emergency room administrators have estimated,
however, that approximately two students per week receive medical treatment or
emergency services related to intoxication. This is the equivalent of approximately 65
students per academic year. Historically, the community has experienced about 1
fatality per year related to alcohol. Although there are not specific local data to
support this estimate, it does reflect national statistics (Wright & Slovis, 1996).
In an attempt to deal with the alcohol abuse problem on campus, SUNY
Potsdam has developed a First Year Experience (FYE) for incoming freshmen, and
participation in the program involves students' willingness to live in alcohol and drug
free dormitories. In addition, the university's president has commissioned a group of
faculty, administrators
and students to explore alcohol abuse prevention and
treatment interventions for students. The committee is preparing a recommendation for
a required classroom experience for all students regarding education about alcohol.
Ideally, the committee would like to recommend a classroom intervention that would
have the greatest impact on student knowledge, attitudes and self-reported behavior
regarding alcohol. There is a dearth of previous research, however, regarding the
effectiveness of two of the most widely used classroom interventions for student
alcohol abuse prevention
the use of motivational speakers and the new "Alcohol
101" program. This research will provide the university with an important evaluation
of these programs before significant policy decisions are made about what classroom
interventions to implement.
5
CHAPTER 2
LITERATURE REVIEW
Introduction
The importance and health relevance of alcohol abuse in the United States are
numerous. Research regarding the long-term physical effects of alcohol is well
documented. Alcohol is the third leading cause of preventable mortality in the United
States (McGinnis and Foege, 1993). The United States suffers economically from
alcohol abuse as well: between 1985 and 1992, alcohol-related problems cost the
United States $148 billion dollars, a 42% increase during that time period over
previous time periods (NIAAA, 1998).
Alcohol use and abuse among American college students has become a major
public health problem. Acute and life threatening intoxication, injuries, the
development of chronic liver disease, academic problems, and criminal behavior on
the college campus and surrounding communities are some of the consequences of this
health issue (Gfroerer et al., 1997; Johnston et al., 1997). Self-reported binge drinking,
which is defined as the consumption of five or more drinks at one sifting for men and
four or more drinks at one sitting for women (Wechsler et al., 1994), is highest in the
United States among young adults. Among this same population, high-risk alcohol
consumption is highest among college students (Gfroefer et al., 1997; Wechsler et al.,
1997).
The percentage of college students who drink to get drunk increased from 39%
in 1993 to 52% in 1997 (Wechsler, 1998). Forty one percent of college students report
having engaged in binge drinking in the past two weeks (Wechsler, et al, 1994).
There are also many negative social consequences associated with binge
drinking. Students who binge drink are more likely to damage property, have trouble
with authorities, miss classes, have hangovers, and experience injuries than those who
do not (Wechsler, et al, 1994; Wechsler & Isaac, 1992). It is not just the students who
participate in binge drinking who suffer the consequences. Wechsler, et al., (1995)
conducted a survey in which 87% of non-binge drinkers who live in dormitories,
fraternities or sororities have experienced one or more negative consequences as a
result of other students binge drinking.
A study through the New York State Office of Alcoholism and Substance
Abuse Services (OASAS, 1996) found that 48% of students in upstate New York
reported binge drinking. This compares to 41% statewide, 44% in suburban New York
State and 28% in New York City.
Research from the Core Alcohol and Drug Survey at 105 college campuses
between 1994 and 1996 showed that half of American college students consume one
drink of alcohol per week or less (Meilman et al., 1997). Of the other 50% of college
students who consume more than one drink of alcohol per week, a number of
demographic categories can identify those students who are at greater or lesser risk of
health and academic problems.
It is becoming increasingly difficult to use gender to predict drinking problems
in college. While being male has been a significant predictor of alcohol abuse in the
past, recent research has not been able to show gender as a predictor (Carey and
Correia, 1997; O'Hare and Tran, 1997). American college women appear to be
catching up with their male counterparts in the risk-taking consumption of alcohol and
are more likely to have problems related to alcohol consumption than are men
(Harrison et al., 1997).
College women with relatively high levels of self-esteem, however, are less likely to
engage in heavy drinking than are other women with lower self-esteem (Yeastedt et
al., 1998).
College women under the age of 20 have significantly greater expectations for
positive global effects related to heavy alcohol consumption than do college women
7
over the age of 20. A family history of alcoholism exacerbated the expectancies for
positive effects in these women under the age of 20 ( Lundahi et al., 1997). After
graduation, however, women are less likely to decrease the frequency of intoxication
per week than are men (Gotham et al., 1997).
Fraternities and sororities have been a part of college life for almost as long as
there have been universities in the United States. Research conducted over the last
decade has shown a consistent pattern of alcohol abuse among members of Greek
fraternal organizations on college campuses (Wechsler et al., 1998). Members of
fraternities and sororities drink more alcohol per week, are more likely to engage in
heavy drinking per episode, and are more likely to have personal health and academic
problems related to alcohol consumption than are students who are not members
(Harrington, et al., 1999). In addition, members of Greek fraternal organizations have
consistently higher positive expectations for excessive alcohol consumption than do
non-members (Cashin et al., 1998).
Cashin et al., (1998) further divided student involvement in fraternities and
sororities to determine what level of inclusion in Greek life was indicative of risky
alcohol consumption. They found that the leaders of the Greek fraternal houses were
as likely, if not more likely, than other members to have negative consequences related
to heavy drinking. Furthermore, these leaders are setting norms for heavy drinking
within the houses.
There is little evidence that students who engage in heavy drinking in their first
two years of college decrease the amount they drink when they are in their last two
years. There is a smaller percentage of college juniors and seniors who are heavy
drinkers, but those juniors and seniors who are heavy drinkers were also heavy
drinkers in their first two years (Gotham et al., 1997; Wechsler et al., 1995). The
reduced percentages of heavy drinkers in upper division classes may be related to the
role that alcohol plays in academic success (Wood et al., 1997; Sher et al., 1997).
8
Research comparing college students in California to those who completed the
Public Health College Alcohol Study, conducted by the Harvard School of Public
Health, found that California college students were less likely to engage in problem
drinking than were the students who were surveyed nationwide (Wechsler, 1997).
California college students surveyed, however, were, on average, older than their
national counterparts, were more likely to be married, and were more likely to live off
campus.
After college, research has shown that episodes of intoxication decrease
dramatically, particularly for men. In research conducted by Gotham et al., (1997) the
third year after the subjects received their bachelor's degrees had resulted in a
significant reduction in the frequency of weekly episodes of intoxication compared to
the subjects' senior year of college. The associations between reductions in frequency
of intoxication were strongest among men who had entered the workforce.
Research has found that compared to non-athletes, college athletes drink
significantly more alcohol, engage in more binge drinking episodes and suffer more
negative outcomes related to drinking (Leichliter, et al., 1998; Wechsler, et al., 1997;
Nattiv et al., 1997.) The research conducted by Leichliter (1998) did not fmd support
for the hypothesis that team leaders were more responsible for using alcohol than were
other team members, although male team leaders engaged in risky alcohol
consumption more often than did female team leaders. Additional research, however,
found that among female athletes, risk-taking behavior that involved variables for
alcohol consumption and unsafe sex was lower among the athletes than among their
non-athletic peers (Kokotailo et al., 1998).
Religion, ego involvement with the tenets of one's religion, and Christian
denomination appear to play a role in the alcohol consumption behavior of college
students. Patock-Peckham et al., (1998) found that students with no religious
affiliation consumed significantly more alcohol more often, engaged in binge drinking
more often, and drank to celebrate more often than did students with either Protestant
or Catholic affiliation. There were no differences across groups for negative outcomes
related to heavy drinking, and students with a Protestant affiliation expressed greater
levels of control in drinking behavior than did Catholics.
Further research showed that among students in a "bible belt" college, there
was no correlation between religiosity and alcohol consumption for men (Poulson, et
al., 1998).
Women students with strong religious beliefs, however, consumed
significantly less alcohol than did women students with weaker religious convictions.
Motivation for Drinking
In national surveys conducted to determine why students drink, students often
cite stress or tension reduction. (Sax, 1997; Cronin, 1997;). Common stressors
mentioned by students include homework and other academic expectations, loneliness,
and meeting other students in social situations (Perkins, 1999). Although students
frequently do cite stress relief as a motivational factor in alcohol consumption,
research has shown that at times when students could be expected to feel excessive
stress, such as final exam week and the week preceding final exam week, alcohol
consumption among students decreases (Noel and Cohen, 1997).
Drinking games have been identified as a method cited by students to relieve
stress through the use of alcohol (Johnson et al., 1998). At the same time, however,
drinking games accounted for a high percentage of negative outcomes related to
college student alcohol consumption. Furthermore, contrary to the hypothesis that
these games reduce tension, those participating in drinking games exhibited lower
social anxiety overall than those who did not play, and the game itself did not provide
any tension-reducing moderating effects (Ibid).
Social and/or sexual enhancement is also frequently cited by students as a
motivation for alcohol consumption (Thombs et al., 1997; Cronin, 1997; Hittner,
10
1997). Trends in alcohol consumption among college students over the last three
decades have shown declines in beer drinking and physical and emotional self
confidence and a corresponding increase in expectations about alcohol to increase
sexual intimacy and enhance social relationships through the release of inhibitions
(Sax, 1997; Lundahl, 1997).
Risk-taking behavior among adolescents, including late adolescent college
students, is a factor in heavy drinking. "Sensation seeking" within the context of heavy
alcohol consumption is particularly prevalent among male adolescents, who perceive
such behavior as a positive factor in their relationships with their peers (Parsons, et al.,
1997). Among male college students, those who are most likely to engage in risky
alcohol consumption are more likely to resemble Type I alcoholics (Johnson et al.,
1998).
Negative Consequences of Heavy Drinking
Numbers of students who use designated drivers when they are drinking
alcohol away from home have increased dramatically in the recent past (Barr and
MacKiimon, 1998; Douglas et al., 1997). As a result, automobile accidents involving
alcohol and college students have also decreased (Douglas et al, 1997). At the same
time, however, 27% of students surveyed in the 1995 College Health Risk Behavior
Survey reported drinking and driving a car within the last 30 days (Douglas et al.,
1997). Students who are designated as a sober driver for other students who are
drinking usually are able to abstain from drinking, or at the most consume one drink.
In addition, students who ordinarily binge drink indicate that they do not drink at a!!
when they are serving as a designated driver (DeJong and Winsten, 1999). The use of
designated drivers has had negative consequences related to college alcohol
consumption, however: Students who are using designated drivers are more likely to
binge drink when they are in a social setting where alcohol is being served (Ibid.).
11
As a means of examining variables related to alcohol server interventions, in
order to develop policies that would decrease the risk of drunken driving accidents,
researchers surveyed bar owners about which policies they considered favorable.
Policies considered favorable were those that focused on providing services to
customers, while unfavorable policies were those that limited the sale of alcohol
(Turrisi et aL, 1999).
Aggression and alcohol among college students is a major concern. Male
college students who are defined as "sensation seekers," exhibit more aggressive
tendencies after having consumed alcohol than do sensation seekers who have not
consumed alcohol (Cheong and Nagoshi, 1999). Firearm use among students has also
recently become a public health issue. Seven percent of college students surveyed
during the 1994/95 academic year indicated that they had carried a weapon during the
last 30 days. Those students who carry firearms are more likely to have been the
victims of violence, and the men who carry firearms consume significantly more
alcohol than their unarmed peers. Differences between armed and unarmed female
students were not as consistent (Presley et al., 1997). Students surveyed about
expectations related to alcohol consumption report that they perceive that they have
increased power and aggression while intoxicated (Lundahl et al., 1997).
Medical problems due to alcohol related injuries and illnesses are likely to be
under-reported due to the current financing structures of medical care (Wright &
Slovis, 1996). Research conducted by Wright et al., (1998) showed that during one
academic year at the University of Tennessee, 16% of students were admitted to the
emergency department of the local hospital for alcohol related emergencies. Although
there were equal numbers of male and female students, white students and freshmen
were over-represented. While the researchers estimated that one out of every fifteen
students at the University of Tennessee could be expected to come to the emergency
room with an alcohol related emergency during their four years in college, those data
may well be an underestimate.
12
College students report that when they drink alcohol they expect positive,
global effects from intoxication, including sexual enhancement (Lundahl et al., 1997).
Because of this, unintended sexual contact and unsafe sexual practices are associated
with alcohol consumption among college students (Noormohamed et al., 1998; Sax,
1997; McNair et al., 1998; Goldstein et al., 1998). At the same time, heavy alcohol use
has been shown to be a factor in sexual victimization of college women (Synovitz and
Byrne, 1998; Gross and Billingham, 1998). Among college women, alcohol
consumption and sexual victimization are strongly correlated, as are being a sorority
member and sexual victimization, while for college men, sexually permissive attitudes
and attitudes about rape were more strongly correlated with being the perpetrator of
sexual victimization (Tyler et al., 1998). Drinking games among men, however, are
strongly associated with instances of sexual victimization (Johnson et al., 1998).
Heavy alcohol consumption among college students also has been shown to
adversely affect memory and acquisition for both verbal and numerical domains (Sher
et al., 1997). Furthermore, research has indicated that individuals in the 21
24 year
age group had more significant memory impairment after episodes of intoxication than
did individuals in the 25 - 29 year age group (Acheson et al., 1998). This research
supports animal models that have shown that alcohol is a more potent antagonist of
memory in adolescent animals than it is in adult animals. Students who fall asleep in
class consume more alcohol than do students who do not fall asleep in class (JeanLouis et al., 1998). Additional research, however, has indicated that although there is a
strong relationship between alcohol consumption and academic problems, particularly
for freshmen students, much of the association appears to be attributable to preexisting
differences among students on admission to college (Wood et al., 1997).
Prevention Strategies
An attempt at changing false perceptions regarding binge drinking experienced
some success at Northern Illinois University. Sanders (1997) reported that a survey
13
conducted in 1988 revealed that 43% of the students engaged in binge drinking, while
students reported that they thought 69.7% engaged in binge drinking. The 43% figure
was reported in the campus newspaper and student volunteers gave $1.00 to each
student who gave the correct figure. A subsequent survey in 1995 revealed that 27.7%
of the students reported binge drinking, while students reported that they thought
42.9% engaged in the behavior. It appears as though a change in the perceived norms
has an impact on the actual norms. Although data regarding the success or failure of
other alcohol prevention programs on college campuses are limited, there are other
programs that are currently being implemented that involve the changing of college
drinking norms.
Cornell University in New York and Chapel Hill University of
North Carolina are implementing a three-phase program that involves the use of
surveys and media to address the alcohol related norms on campus.
Final
implementation of the program will take place in the year 2001.
The Village of Potsdam and SUNY Potsdam have responded to the local
alcohol abuse problem in several ways. The local police department has developed
the Canton-Potsdam Alcohol Enforcement Task Force.
This involves increased
enforcement of alcohol-related policies (sobriety-testing, alcoholic beverage control)
and employee training in alcohol enforcement. The Police Department believes the
increased presence of the police will discourage alcohol-related offenses. Village
police officers speak to freshman students and their parents during orientation, and
present those in attendance with a pamphlet detailing local ordinances related to
alcohol and other issues. Recently, Potsdam Village police have begun sending a letter
home to parents of students who are involved in an alcohol-related incident. For the
most part, according to the police department, parents are appreciative and supportive
of these letters. This increases communication between the parents and local officials,
they believe, and will decrease the number of repeat offenders.
Another local municipal initiative recently implemented is keg registration.
Local merchants who sell beer kegs are encouraged to ask those purchasing a keg of
beer to sign a release reminding them of the legal ramifications of underage drinking.
14
According to police officials there has been at least one instance of the individual
choosing not to purchase the keg based on this registration initiative. The department
also uses the keg registration form to identify households hosting parties with alcohol
and to speak with the hosts before the event, reminding them of local ordinances and
offering support if need be.
Potsdam Village police have been offering Employee Alcohol Awareness
Seminars since 1995, where servers of alcohol are trained in and what they can do
toreduce alcohol-related incidents. The Potsdam Village Police department claims to
have success with these programs. Additional approaches involve street signs warning
of regulations prohibiting open alcohol containers and other public notices regarding
information related to the services the Potsdam Village police provide.
15
CHAPTER 3
METHODS
Instrument
The instrument for this intervention was the Student Alcohol Questionnaire
(SAQ), which was developed by researchers at Indiana University and the State
University of New York at Potsdam. The questionnaire (Appendix A) consists of 84
items. Questions 1-8 ask about demographic information, items 9-32 ask about selfreported alcohol consumption behavior, items 33 and 34 ask about tobacco use, items
35-60 test the subject's knowledge about alcohol, and items 71-84 measure the
subject's attitudes towards alcohol. The SAQ was amended to meet the needs of this
research. Dr. David Hanson, one of the authors of the SAQ provided assistance with
these changes. The college majors were changed to reflect the majors at SUNY
Potsdam and an additional question about living arrangement was added. Other minor
changes were made in the demographic section of the SAQ. A question about drinking
cohorts and a question about coerced sexual activity were moved from the attitude
section to the behavior section. An additional question regarding the number of
roonmiates who drink to intoxication each week was added to the behavior section. No
changes were made to the knowledge section. The rest of the original questions
regarding attitudes were removed and six additional Likert-styie statements regarding
attitudes about alcohol were added to the bottom of the questionnaire. Those
statements are:
1. Drinking alcohol is an important part of college life.
2. Shy or inhibited people have an easier time meeting new people when they are
drunk.
3. In Potsdam there are many things to do besides drinking.
4. A party without alcohol is not much fun.
5. Getting drunk once or twice a week is okay.
16
6. Drinking alcohol is a good way to relieve the stresses of college life.
The attitude portion of the survey was constructed as Likert-style opinion
statements that produced a score relative to the subject's attitudes about drinking
alcohol in college. Scores for each item ranged from zero to three, with three being the
score most highly related to a positive attitude about alcohol consumption in college.
As there were six total items, a student could have a score as high as an eighteen (a
very positive attitude about college drinking), or as low as a zero (a very negative
attitude about college drinking).
Three SUNY Potsdam professors and a group of eight undergraduate students
assessed the validity of the six additional questions. The students recommended
changing the phrase "Drinking to intoxication" in statement five to "Getting drunk."
Originally there were five attitude statements and the students recommended adding a
statement about parties and alcohol (#4) for a total of six statements. Twenty-one
undergraduate students assisted in assessing the internal consistency of the attitude
scale. Their scores on the attitude scale were used to calculate Cronbach's alpha,
which yielded a coefficient of .86.
Knowledge scores for each subject were calculated as the number of correct
answers. On the knowledge portion of the survey subjects were instructed not to guess.
This was an attempt to minimize correct guessing on the part of the student so that the
knowledge score measured only what the student was sure he or she knew.
Behavior scores were a composite of scores for amount of alcohol consumed,
frequency of drinking and consequences related to intoxication. Items 10
15
measured amount of alcohol consumed at one time, and frequency of drinking. Each
item had 5 possible choices. For the frequency of consumption questions, choices
were "1. every day," 2. "at least once a week, but not every day," 3. "at least once a
month, but less than once a week," 4. "more than once a year but less than once a
month," and "5. once a year or less." Subjects received five points for each choice of
17
item number 1, 4 points for item number 2, 3 points for item number 3, 2 points for
item number 4, and 1 point for item number 5. For the amount of alcohol consumed in
one sitting questions, choices were 1. "more than six (beers, glasses of wine or shots
of liquor)," 2. "five or six...,,, 3. "three or four...," 4. "one or two... ," 5. "less than
one...." Subjects received five points for every answer of number 1, 4 points for
number 2, 3 points for number 3, 2 points for number 4, and 1 point for number 5.
Students who had a combination of number ones or twos for amount and frequency for
either beer, wine or hard liquor received an additional five points and were classified
as a "heavy drinker." This classification of "heavy drinking," i.e. more than five drinks
at a time at least once a week is an accepted public health definition (Greenfield, 1998;
Mikanik et al., 1996). Subjects received an additional five points if they answered
"yes" to item number 17 regarding sexual coercion. Behavioral consequences of
intoxication were included in items 19
36. Subjects received an additional five
points for every consequence item that they checked.
In addition, for identification and matching purposes, subjects were asked to
write in the last six digits of their social security number. Items 33 and 34, in regard to
tobacco use, were eliminated from the survey.
Reliability (Engs and Hanson, 1994) and validity (Engs, 1978) of the
instrument have been published. Permission to use the instrument was granted by the
authors. Reliability and validity of the last six statements were assessed by a group of
SUNY Potsdam students and faculty before the questionnaire was administered.
The Interventions
"Alcohol 101" is a new computer-based CD Rom interactive alcohol education
program for college students. The University of Illinois at Urbana/Champaign
developed it in collaboration with the Century Council, an organization funded by the
nation's leading distillers of alcoholic beverages. According to information that
18
accompanies the program, "Alcohol 101 was created to reduce the harm associated
with the misuse of alcohol. The program provides the physiological, psychological and
legal information to help college students make responsible decisions about drinking.
Or not drinking." The Century Council provided the CD Rom disks to SUNY Potsdam
to use as the university saw fit and without restrictions or obligations.
The program is presented to students as a cyber game. The setting for the game
is a college party where students at the party make decisions about alcohol and are
able to see the consequences of those decisions. For the classroom instruction, the
program uses an LCD projector with a computer interface. The Lesson Plan that
accompanies the program guides the instructor through the activities in a stepwise
fashion.
The use of motivational speakers is a popular method of providing information
about the hazards of drug or alcohol abuse to college students. The National Collegiate
Athletic Association (NCAA), for example, provides funding for participating schools
to engage speakers for their athletes about drug education or weilness programs. The
NCAA provides a list of potential speakers, and more than half of them focuses on
alcohol.
The motivational speaker for this research was Rick Waters, a counselor with
the St. Lawrence County Alcohol Services Agency. Mr. Waters is an experienced
teacher and alcohol counselor. His presentation was approximately 60 minutes in
length and covered the same subjects as the Alcohol 101 presentation - drunken
driving, overdose, aggressive behavior and unplanned sexual behavior. Dr. Neil
Johnson, the chair of the Community Health Department, was the facilitator for the
Alcohol 101 presentation. Dr. Johnson taught at SUNY Potsdam for 37 years. He is a
well-known and respected professor on campus.
19
Subjects
The unit of analysis for this research varies by the type of analysis. The
randomly selected class is the unit of analysis for the MANOVA and ANCOVA
procedures. The individual is the unit of analysis for the multiple regression
procedures. The SLJNY Potsdam Registrar provided a list of seventy-five minute
classes that begin at 9:30 am on Tuesday and have enrollments that include at least
10% freshmen students and 10% seniors. From this list, a random sample of nine
classes was selected, with a total enrollment of 370 students. The subjects for this
research were the undergraduate students over the age of 18 who were enrolled in the
classes. A tabular description of the demographics of the sample is found in Appendix
B.
The classroom professor served as the survey administrator. At the first
administration of the survey, student subjects were asked to participate in the study.
The classroom professor read the informed consent document to the students in his/her
class and provided a copy of the document to each student. The survey took about 15
minutes to complete.
Study Design
Research Questions #1 and #2 were conducted as pretest posttest control group
designs. The classroom was the unit of analysis. Research Question #3 was conducted
as descriptive research and the individual student was the unit of analysis. All subjects
completed the SAQ on Tuesday, September 21, 1999. This was the fourth week after
students returned to campus for the Fall, 1999 semester. Classrooms that were
randomly selected for the research were randomly assigned to one of the two
interventions or as a control classroom. The subjects in the control classroom did not
take part in an intervention and proceeded with regular classroom activities. The
20
interventions took place on September 23, 28, and 30, 1999. The survey was
readministered on October 26, November 16 and December 7, 1999.
Question #1
The design for this question was a pretest/posttest control group design. The
unit of analysis for this question was the class. This question was analyzed using
analysis of covariance (ANCOVA) for the mean self-reported alcohol behavior
posttest scores for each of the three groups. The pretest scores were used as the
covariate so that variability that can be attributed to differences in self-reported preintervention behavior was partitioned out of the analysis.
Separating self-reported alcohol behavior from knowledge and attitude for this
research can be defended. During the Demonstration Phase of the Alcohol 101
program, which was conducted by the University of Illinois at Urbana/Champaign,
measurement of alcohol consumption behavior only examined
intent
to engage in
alcohol consumption prevention behaviors. Actual behavior (self-reported or
otherwise) has not, as yet, been measured or analyzed for the Alcohol 101 program.
Examining any actual changes in self-reported behavior will provide important
information about the effectiveness of the program. There is scant research, as well,
that documents the effectiveness of motivational speakers to actually change risktaking behaviors.
A two-tailed level of significance was set at 0.05. Power was set at 0.80. Effect
size for this research had to be estimated from data gathered from the Alcohol 101
Demonstration Phase research (Reis, 1999). Comparing post intervention knowledge
of students who took part in the Alcohol 101 intervention to knowledge of the control
group students revealed statistically significant effect sizes ranging from 0.16 to 0.37.
Based on these preliminary data, effect size for this research was estimated at 0.20.
Sample size for an ANOVA analysis with an estimated effect size of .20, alpha at 0.05
21
and power at 0.80 would be approximately 81 subjects per group. For all but the
fourth survey, there were more than 90 subjects per group.
Question #2
The research for this question was conducted as an experimental pretest
posttest control group design. There was random assignment to either an intervention
group or a control group. The unit of analysis was the class.
There were three levels of the independent variable, which was exposure to an
alcohol education intervention An Alcohol 101 Group, a motivational speaker group
and a control group. The dependent variables were self-reported alcohol-consumption
behavior, knowledge about alcohol, and attitudes about alcohol. Individual subject
values for self-reported alcohol consumption behavior, knowledge about alcohol and
attitudes towards alcohol were scored and calculated.
Using the posttest scores, multivariate analysis of variance (MANOVA) was
used to test the null hypotheses for this question. Health behavior is often related to
the individual's attitudes and knowledge about the particular behavior. Research
(Marietta, 1999; Tessaro, 1997) has demonstrated that changes in knowledge can
influence both attitudes and behavior in college students. Because of this, knowledge
about alcohol, attitudes about college drinking and actual drinking behavior may not
be independent of each other. MANOVA techniques were used in answering this
question in order to account for the potential relationship between the dependent
variables. Because the dependent variables are capable of influencing each other,
MANOVA is able to provide a more powerful statistical analysis than would multiple
univariate analyses. Wilk's lambda and the corresponding F-value were reported. A
two-tailed alpha level of 0.05 was specified. Although random assignment should
theoretically provide for homogeneity of variance, the pretest scores were analyzed to
22
ensure that homogeneity of variance between groups did exist. Box's M was used to
test for this.
For post-hoc testing of the results, discriminant analysis was used to determine
if the values for the dependent variables were able to discriminate among the three
groups. Values of the independent variables were fitted into the discriminant function
for each subject. Subjects were then assigned to groups based on their discriminant
score (D). Accuracy of predicted group membership (Alcohol 101, motivational
speaker or control group) was reported and compared to the results of the MANOVA
analysis. The Scheffe Comparison was proposed to be used post hoc to determine
which population means were significantly different, if any. As recommended by
Scheffe (Scheffe, 1959), a significance level of 0.10 was specified to avoid excess
Type II error.
Since MANOVA is robust to modest violations of normality as long as the
violations are due to skewness and not outliers, any outliers that were more than three
standard deviations from the mean for that group were eliminated from the MANOVA
analysis using the "case selection" procedure in SPSS. Equal sample sizes,
homogeneity of variance and a sample size that produces more than 20 degrees of
freedom in the univariate case also allow for robustness of the test.
Question #3
This question was addressed as descriptive research, with an attempt to
determine the strength of the relationship between self-reported alcohol consumption
behavior and four predictor variables - gender, grade point average, class level, and
religion. Multiple regression techniques were used. The pretest scores for the entire
sample were analyzed. The unit of analysis was the individual student.
23
Self-reported alcohol consumption behavior was determined from the
responses to items 10-3 6 of the SAQ. To ensure that the assumption of linearity was
met between the predictor and outcome variables, a scatter plot of the residuals was
constructed. Visual analysis of the residuals assured that this assumption was met.
While it was not expected that the predictor variables will be highly correlated with
one another, multicollinearity was addressed by performing correlation analysis
between the predictor variables before the regression was run. The total variance of
self-reported alcohol consumption behavior that can be predicted by the regression
equation was reported as an R2 value. An F value for the analysis of variance for the
regression analysis was also reported. The F value determined if the equation provided
an explanation of self-reported alcohol consumption behavior that is better than
chance. Performing a test of significance (alpha
tested the null hypothesis H0: b = 0.
0.05) for each regression coefficient
Standardized beta weights were used to
determine the relative contribution of each attribute variable to self-reported alcohol
consumption behavior.
Dummy variables for the discrete predictor variables were constructed to code
for the presence or absence of the following categories: Gender (female = 1); Class
level (Sophomore status = 1, Junior status
1, Senior status
1); Religion (Roman
Catholic = 1, Member of a Protestant denomination that allows drinking = 1 Jewish =
1, Member of a Protestant denomination that does not allow drinking = 1) Variables
were not constructed for Freshman status or No Religion. Muslim students were not
represented in the sample.
Threats to Design Validity
Potential threats to internal validity for this research are minimized due to
randomization and the presence of a control group. Attrition was the greatest potential
threat to internal validity. Those students who engage in risky alcohol consumption
behavior would be those who are likely to be absent from class during the follow-up
24
surveys. The presence of a numerical identification number and cross checking of
subsequent surveys helped to minimize this threat. Graphical assessment of data
screening is found in Appendix C and a tabular presentation of the results of data
screening assessments is found in Appendix D. Summary results of the data analysis is
presented in tabular form in Appendix B.
The extent to which the results of this research can be generalized to other
populations is limited to undergraduate college students in the Northeastern or
Atlantic areas of the United States. Students at SUNY Potsdam are recruited from all
regions of the state of New York and Eastern United States.
Additional Descriptive Data
Descriptive data includes: Preintervention associations between self-reported
heavy drinking and age, gender, SUNY Potsdam School, grade point average,
membership in a Greek fraternal organization, on or off campus living arrangement,
class level, heavy drinking behavior of roommates, and coerced sexual encounters.
Chi square tests of independence were used to test the associations and a significance
level of 0.05 was specified. Also reported in tabular form in Appendix F are mean
scores for knowledge, attitude and self-reported behavior for the pretest responses for
the total sample and posttest by group. These mean scores are further stratified by
gender, age, grade point average and religion.
Survey Anonymity
Students who did not wish to participate in the research were given the choice
to decline to complete the survey. Only one student, on the third survey, did so. The
survey instrument specifies that the subjects not write their names on the survey. For
this research, each subject included the last six digits of his or her Social Security
25
Number at the top of the form. No other descriptors or identifiers were used. All
surveys and raw data will be destroyed at the completion of the research project.
Institutional Review Board applications and approvals for both Oregon State
University and the State University of New York are found in Appendix F.
Statistical Analysis
All statistical analysis procedures were conducted using the Statistical Package
for the Social Sciences (SPSS) for Windows, Version 9.0.
CHAPTER 4
RESULTS
This chapter will provide a description of the sample and data screening
techniques that were used to test statistical assumptions before the data analyses were
run. Also included in this chapter are the results of the data analysis for all three
research questions and a description of preintervention associations.
Description of the Sample
Sample size
A total of 370 students from nine different classes at the State University of
New York at Potsdam completed the Student Alcohol Questionnaire at least once
during the Fall, 1999 semester. To conform with Institutional Review Board
protections for minors, the data from two seventeen-year old students and one sixteen-
year old were deleted from the data matrix. In addition, since the research was
concerned only with undergraduate college students, six graduate students and one
student who listed his or her grade level as "other" were eliminated as well. Graduate
students were eliminated from the analysis through the "case selection" procedure in
SPSS. This left a final sample size of 360 undergraduate students. During the Fall,
1999 semester, there was a total of 3587 undergraduate students enrolled at the
university. The sample, therefore, comprises approximately 10% of the total
undergraduate students at the institution. There were 111 students in the three classes
that comprised the Alcohol 101 intervention, 147 students in the three classes that
made up the motivational speaker intervention and 102 students in the three classes
that comprised the control group.
27
Gender of the sample
According to the SUNY Potsdam Office of Assessment and Institutional
Research, approximately 61% of the students enrolled during the Fall, 1999 semester
were women and 39% were men. In this sample, 211 students (5 8.6%) were women
and 149 students (41.4%) were men. There was a slightly higher percentage of men
students in the Alcohol 101 group and a slightly higher percentage of women students
in the control group. Gender of the sample by group is presented in Table 1.
Table 1
Gender of the Sample by Group
Gender
Group
Total
Male
Female
Alcohol 101
51
Motivational Speaker
Control
63
35
149
60
84
67
211
Total
111
147
102
360
Ages of the sample
Ages for this undergraduate sample ranged from 18 to 51. Students between
the ages of 18 and 23 comprised 89.4% of the sample, however. The median age was
20. Those students who were either 18 or 19 years old comprised 38.7% of the sample,
20 year olds comprised 23%, 21 year olds comprised 16%, 22 year olds comprised 8%
and 23 year olds comprised approximately 3% of the sample. In the Alcohol 101
group 88.2% were between 18 and 23. In the motivational speaker group 86.2% were
between 18 and 23, and in the control group 95% of the students were between 18 and
23.
28
Undergraduate majors
At SUNY Potsdam, there are three schools: The School of Arts and Sciences,
The School of Education, and the Crane School of Music. In the Fail, 1999 semester,
55% of those undergraduates who had declared a major were in the School of Arts and
Sciences, 20% were in the School of Education, and 16% were in the Crane School of
Music. In the sample for this research, 53.5% of the students were in the School of
Arts and Sciences, 20.6% were in the School of Education and 8% were Crane
students. Students who had not yet declared a major comprised 17.5% of the sample.
One student declined to name a major. Similar percentages occurred in each of the
three groups. Approximately 10% of the students in the motivational speaker group
and the control were Crane students and there were 3.6% Crane students in the
Alcohol 101 group.
Year in school
Inclusion criteria for selecting classes for this research specified that the class
must have had at least ten percent of its enrollment made up of freshmen students, and
ten percent seniors. That criteria resulted in classes that yielded the following analysis
of class level for the study: Eighty-one students (22.5%) were freshman, 105 (29.2%)
were sophomores, 96 (26.7%) were juniors, and 78 (21.7%) were seniors. Similar
percentages were seen in the individual groups, with the exception of the 19 freshmen
students in the Alcohol 101 group, who made up 17.3% of that group.
Grade point average
Grade point averages (GPA) for this research were self-reported, and should be
considered as such. SUNY Potsdam grades are numerical and range from 0.0 to 4.0. In
the total sample, 5 students (1.4%) reported a 4.0 GPA, 57 (15.8%) reported a 3.5, 102
students (28.3%) reported having a GPA of 3.0, 78 (21.7%) reported a 2.5, 38 (10.6%)
reported a 2.0 and 6 students (1.7%) reported a GPA of less than 2.0. Fifty-nine first
semester freshmen, who comprised 16.4% of the sample, do not have a GPA yet.
Fourteen students, or 4% of the sample declined to report their GPA. Similar GPAs
were seen in the breakdown by individual group.
Ethnicity
According to the SUNY Potsdam Institutional Demographic Database, 2.8% of
the students are black, 1.8% are Latino, 0.8% are Asian Pacific Islanders, 1.8% are
Native Americans, and 83.7% are white. Approximately 9% of the students are nonresident foreign students or decline to state their ethnic background.
In the total sample for this research, 9 (2.5%) of the students are black, 8
(2.2%) are Latino, 10 (2.8%) are Native Americans, 2 (0.6%) are biracial or
multiracial and 320 (8 8.9%) are white. Students who describe themselves as "other" or
who declined to state their ethnicity comprised 2.8% of the sample.
Membership in fraternities or sororities
In the total sample, approximately 43 (12%) of the students belong to Greek
organizations. This compares to eleven percent of the students in the larger SUNY
Potsdam campus who belong to fraternities or sororities. Membership in Greek
organizations in individual groups included 24 students (16.3%) in the motivational
speaker group, 12 students (11%) in the Alcohol 101 group and 7 students (7%) in the
control group.
Religion
For the entire sample, 167 (46.4%) students were raised in the Roman Catholic
faith, 83 (23.1 %) were raised in a Protestant faith that allows the consumption of
alcoholic beverages, 15 (4.2%) were raised in a Protestant faith that does not allow the
consumption of alcoholic beverages, and 11 (3.2%) are Jewish. Seventy-one students
(19.7%) reported being raised with "none or other" religious faith. Thirteen students
(3.6%) declined to answer the question. Muslim students were not represented in the
sample.
For the entire group, 54 students (15%) considered religion to be "very
important" in their lives, 104 (2 8.9%) considered religion to be "moderately
important," 106 (29.4%) considered religion to be "mildly important," 90 (25%)
considered religion to be "not important" in their lives, and 6 students (1.7%) declined
to respond.
Living arrangement and drinking cohorts
More than half of the students in the sample live in either a dormitory double
room or off campus with other students (29.2% and 25% respectively). Fifty-eight
(16%) students in the sample live in a dormitory suite with other students, 49 (13.6%)
live off campus with family, 33 (9.2%) live in single dormitory rooms and 18 (5%)
live off campus alone. Approximately two percent of the students declined to state
their living arrangement. When the students in this sample drink alcohol, 295 (82%)
drink with their friends. Seven students (1.9%) drink with their parents. One student in
the total sample indicated that he or she drinks with a date. Approximately 15% of the
students surveyed do not drink alcohol.
Seventy-nine students (21.9%) in the total sample answered "none" to the
question "How many of your housemates/roommates get drunk each week?" Seventy-
31
eight students (21.7%) answered "one," 32 (8.9%) answered "two," 15 (4.2%)
answered "three," and 37 (10.3%) answered "four or more." Sixty-seven students
(18.6%) indicated that they do not live with other students. Fifty-one students (14.2%)
declined to answer the question. (Students who do not drink at all were instructed to
skip all of the questions regarding alcohol consumption behavior.)
Coerced sexual activity
During the Fall, 1999 semester, 4 students in the total sample (1.1%) indicated
that they had either forced sexual activity on another person or were forced into sex
themselves. Three of these students were in the motivational speaker group and one
was in the control group.
Heavy drinking
In the total sample, 117 students (32.5%) met the criteria for heavy drinking,
i.e., five or more drinks at one time at least once a week. Two hundred forty three
students (67.5%) did not. Individual groups revealed similar percentages.
Data Screening
Scores for aftitude, self-reported behavior and knowledge about alcohol were
calculated for each student in each group and entered into the data matrix. The
calculated attitude scores ranged from 0 to 18, with 18 the highest possible score. The
highest possible score on the knowledge part of the survey was 36, and the highest
score calculated during the research was 31. The highest possible score for the selfreported behavior part of the survey was 125, and the highest calculated score for any
one student during the research was 89.
32
Screening of the data for this research began with proofreading of the data
matrix. Scores that did not appear to be plausible were analyzed and corrected. One
case had ethnicity entered as a "2.5" for example. Another case had a zero instead of a
99 entered for a knowledge score. Means and standard deviations for all outcome
variables were examined by group to determine if they fell within reasonable limits.
Missing values
Missing value labels were examined to ensure that all outcome variables had
been correctly labeled. Not all of the students in the total sample completed the survey
every time it was administered. The scores for all three-outcome variables were
entered as missing values if a student was not present at the time of the survey
administration. Approximately 20% of the total sample was absent from class for the
first two survey administrations. Twenty five percent were absent for the third
administration and 31% were absent for the fourth administration. The similarity of
the means for all outcome measures from survey to survey did not reveal a nonrandom
pattern among student absences. Those students with high self-reported behavior
scores were not more likely to be absent than those with lower scores, for example.
All surveys were scored by hand. If a student answered the behavior section,
and did not complete the knowledge or attitude sections, it was assumed that the
student arrived in class late and did not have time to finish the survey. These students
were assigned missing values for their attitude and knowledge scores. Since the survey
instructs the subject to skip all of the self-reported behavior questions if the subject
does not drink alcohol at all, students who did not answer the behavior part of the
survey but did answer the attitude and knowledge sections were assigned a score of
zero rather than a missing value for behavior.
33
Outliers
Since multivariate procedures are sensitive to the presence of outliers, the data
were carefully scrutinized to find outliers and determine their fate for the purposes of
this research. Outliers in this study were determined to be those scores that were more
than three standard deviations from the mean. An examination of the means and
standard deviations for the outcome variables revealed that for the knowledge and
attitude scores, a score that is more than three standard deviations from the mean lies
beyond the limits of that individual data set.
For the self-reported behavior scores, stem and leaf plots were constructed to
explore for outliers. Outliers on the behavior scale were eliminated through the "case
selection" procedure in SPSS. For analysis of the first and second survey data, cases
were selected if the behavior score was less than or equal to 67, for the third survey
less than or equal to
65
and less than or equal to 61 for the fourth survey. The behavior
scores for two subjects on the first survey and two subjects on the fourth survey were
more than three standard deviations from the mean and were eliminated from the
analysis. Several behavior scores were identified as being
1.5
standard deviations from
the mean, but were left in the data analysis. In addition, stem and leaf plots for
behavior scores before and after case selections were examined.
Normality
Assessing whether the data were normally distributed, in order to meet
assumptions of normality, was conducted both visually and statistically. Histograms of
all outcome variables, overlain with a normal curve were constructed. Stem and leaf
plots and probability plots were also constructed. Graphs for the histograms overlain
with a normal curve were constructed. Stem and leaf plots and probability plots were
also constructed. No violations of normality were identified.
34
Statistical analysis of normality was conducted through an examination of
skewness and kurtosjs of the outcome variables. These data were close to zero for all
of the variables that were examined.
Homogeneity of variance
Correlation matrices were examined to explore for any possible inflated or
deflated correlations. The highest correlation (r
.6 for all groups) was between
attitude and self-reported behavior.) Correlations between knowledge and selfreported behavior, and knowledge and attitude were not strong. Homogeneity of
variance across all levels of the outcome variables was assessed through Box's M. For
all of the outcome variables of the first three surveys, Box's M was not significant at
the 0.05 level, and the null hypothesis was not rejected. Box's M was significant for
the fourth survey administration, however.
Linearity
An examination of correlations and scatterplots assessed linearity between
pairs of outcome variables. The strongest linear relationship was found between
attitude and self-reported behavior. Many subjects had high knowledge scores together
with low self-reported behavior and attitude scores. Since linearity is a statistical
assumption for MANOVA techniques, those dependent variables with knowledge in
the combination, therefore, may not provide as much information about the
effectiveness of the intervention. Any significant effects in the MANOVA procedure
would be expected from combinations of attitude and self-reported behavior scores
where the strongest correlations were found.
Univariate analysis of variance was performed on the knowledge scores for all
of the three post intervention surveys. Scores were not significantly different for any
35
of the three measures. (p
.360 for the second survey; p = .260 for the third survey;
and p = .158 for the fourth survey.) Means for the control group knowledge scores
were higher than the intervention groups for each post intervention measurement.
Research Question #1
Is there a significant difference in self-reported alcohol consumption behavior
between undergraduate college students who participate in different types of alcohol
programs?
This question was answered using Analysis of Covariance (ANCOVA)
procedures. The independent variable was one of two alcohol education programs or
the control group, the dependent variable was the self-reported post intervention
behavior score for each of the three post intervention measures, and the covariate was
the first pre-intervention measure of self-reported behavior. Since ANCOVA only
yields meaningful information when a number of assumptions are met, additional data
screening was performed before the analysis was conducted and is described below.
Linearity of the covariate
Analyzing the correlation between the covariate and the dependent variables
assessed linearity of the covariate. Correlations ranged from .897 for the first and
second behavior measures to .781 for third and fourth behavior measures.
Equality of slopes
Equality of slopes of the regression lines, in order to assume that the regression
of the post intervention behavior scores on the pre-intervention behavior scores for all
36
three groups was the same, was tested using ANOVA. Cases less than three standard
deviations from the mean were selected for the analysis. The interaction effects
between group and first behavior for each post intervention measure showed no
evidence of violation of the equal slopes assumption.
Independence of the covariate
In order to produce meaningful data from analysis of covariance, the covariate
must be related to the dependent variable, but must also be independent of the
treatment effect. The first behavior score as the covariate meets this assumption.
Analysis of covariance
Behavior scores for each post intervention measure were not significantly
different across groups. ANCOVA results are presented in Table 2.
Table 2
Summary Results of Analysis of Covariance
Measure
R squared
Df
Second
Third
Fourth
.805
.659
.620
2
2
2
Mean
Square
77.77
209.490
12.986
F
Sig.
1.934
2.99
.210
.15
.054
.81
37
Research Question #2
Are self-reported alcohol consumption behavior, knowledge about alcohol, and
attitudes about alcohol significantly different between undergraduate college students
who have participated in different types of alcohol education programs? Are any
differences sustainable for a twelve-week period?
Multivariate analysis of variance was performed on the post intervention
scores for each survey administration with the intervention group (Alcohol 101,
motivational speaker or control) as the independent variable. Four procedures were
performed each time, with different groupings of dependent variables: Posttest
attitude, knowledge and behavior; attitude and behavior; attitude and knowledge; and
knowledge and behavior.
There were no significant differences between groups for any of the
measurements. Wilk's lambda values ranged from .983 (p = .395) for the fourth
measurement of knowledge and self..reported behavior to .998 (p = .972) for the fourth
measurement of attitude and self-reported behavior. Summary results are presented in
Table 3.
Table 3
Summary results of Multivariate Analysis of Variance
Survey
Wilk 's
F value
Second
Second
(KA)
Second
(KB)
Second
Hypothesis
Error df
Sig.
df
Lambda
Value
.991
.349
6.0
460.0
.91
.989
.766
4.0
578.0
.55
.991
.651
4.0
582.0
.63
.996
.284
4.0
578.0
.89
38
Table 3, Continued
Third
(KAB)
.987
.580
6.0
514.0
.75
Third(KA)
.989
.987
.995
.982
.703
.862
.341
.702
4.0
4.0
4.0
6.0
518.0
522.0
516.0
454.0
.59
.49
.85
.65
.985
.983
.998
.857
1.022
.130
4.0
4.0
4.0
458.0
462.0
470.0
.49
.40
.97
Third (KB)
Third (AB)
Fourth
(KAB)
Fourth (KA)
Fourth (KB)
Fourth (AB)
The attitude arid behavior scores were given particular scrutiny apart from the
other scores, as these pairings were the only ones that met all the MANOVA
assumptions, including linearity. No trends were identified. (Second survey p = .888;
third survey p = .850; fourth survey p = .972.) Since preintervention associations
indicated an association between heavy drinking and gender, i.e., men drink more than
women do, the MANOVA analyses were conducted separately for women. Although
the analysis revealed higher Wilk's lambda values, and less likelihood that the
differences could have occurred by chance, none of the values was statistically
significant. An analysis of means for women by group, however, revealed a trend in
the measurement of attitude and behavior for the second survey (MANOVA p
.05 2).
Means for knowledge, attitude and behavior for women in the Alcohol 101 group were
essentially unchanged between the first survey and the second survey. For women in
the Motivational Speaker group, however, means for the second knowledge
measurement were 2 points higher than they were for the first knowledge
measurement, and mean behavior scores were 2.4 points lower. Mean attitude scores
were just slightly higher (7.66 for the first and 7.97 for the second). In the control
group, mean attitude scores were not changed from the first measurement to the
second, but mean knowledge scores for the second survey were almost four points
higher than for the first survey, and mean behavior scores were 2 points higher.
Results of MANOVA analyses for women are presented in Table 4.
39
Table 4
Summary results of Multivariate Analysis of Variance for Women Students
Survey
Wilk 's
F value
Lambda
Second
(KAB)
Second
(KA)
Second
(KB)
Second
(AB)
Third
(KAB)
Third(KA)
Third (KB)
Third(AB)
Fourth
(KAB)
Fourth (KA)
Fourth(KB)
Fourth(AB)
Hypothesis
Error df
Sig.
df
Value
.941
1.709
6.0
332.0
.12
.988
.520
4.0
334.0
.72
.957
1.877
4.0
336.0
.11
.945
2.376
4.0
334.0
.052
.948
1.431
6.0
316.0
.20
.971
.952
.955
.965
1.17
2.00
1.866
.866
4.0
4.0
4.0
6.0
318.0
322.0
318.0
292.0
.32
.09
.12
.52
.982
.963
.970
.672
1.411
1.159
4.0
4.0
4.0
294.0
296
300.0
.61
.23
.33
Although none of the results was significant, post-hoc discriminant analysis
was performed to determine if was possible to determine individual students' groups
based on their survey scores. For the second survey, 41.6% of the original grouped
cases were correctly classified; for the third survey, 3 9.6% were correctly classified;
and for the fourth survey, 37.2% were correctly classified. For all three measurements,
the first discriminant function consisted of the knowledge and behavior scores, and the
attitude scores comprised the second discriminant function. None of the functions was
significant at the 0.05 level of significance.
Means for knowledge, attitude and self-reported behavior were examined to
ascertain any possible non-significant trends in the results. For the attitude scores, only
slight differences were seen. Mean scores ranged from 7.9 for the third measurement
40
among the Alcohol 101 group to 9.1 for the fourth measurement among the control
group. For the knowledge measurements, the mean score for the control group was
approximately 1.5 points lower than the intervention groups on the first survey. On the
three post intervention surveys, however, the mean knowledge score for the control
group was slightly higher than the intervention groups.
For the self-reported behavior scores, the mean scores for the two intervention
groups was approximately 2.5 points higher than the control group on the first survey.
On the second survey, self-reported behavior scores for the two intervention groups
were slightly lower than the control group. On the third survey, the self-reported
behavior scores for the control group were still higher, but only slightly so. On the
fourth survey, all self-reported behavior mean scores were within 0.3 points of each
other.
Research Question #3
Among undergraduate college students, can self-reported alcohol consumption
behavior be predicted from gender, grade point average, class level, or religion?
Multiple regression procedures were used to answer this question. The
predictor variables were regressed on the first behavior score. Dummy variables were
created for gender (female = 1), class level and religion. Variables were not created for
Freshman status or "No religion," i.e. students who indicated that they were not raised
in a religious faith. Outliers that were more than 3 standard deviations from the mean
were eliminated from the analysis by using the "case selection" procedure in SPSS.
Two subjects had behavior scores that were more than three standard deviations from
the mean, and were eliminated from the analysis.
The independent variables in this regression equation provide approximately
10% of the variance in self-reported alcohol consumption behavior of this sample of
41
undergraduate college students. Only the variable "gender" and membership in a
Protestant faith that allows drinking resulted in significant values.
An examination of the standardized coefficients reveals that, in this analysis, selfreported grade point average, religion and class level contribute relatively little to the
explanation of self-reported alcohol consumption behavior. Coefficients are presented
in Table 5.
Table 5
Coefficients for Multiple Regression
Standardized
Unstandardized
B
1
(Constant)
Gender
Grade Point
Average
Sophomore status
Junior Status
Senior Status
Roman Catholic
Jewish
Protestant Allows
31.270
-6.058
t
Sig
Std. Error
6.238
Beta
1.923
-.211
5.013 .00
-3.151 .00
-2.029
1.403
-.098
2
-1.446 .15
1.695
4.519
4.530
4.543
2.317
7.160
2.571
.056
.094
.072
.042
-.039
-.166
.375
.630
.485
.506
-.574
-2.043
6.455
-.066
-.954
2.854
2.201
1.172
-4.110
-5.253
.71
.53
.63
.61
.57
.04
Drinking
Protestant No
-6.160
.34
The linear fit of the equation was tested using ANOVA procedures (j, = .043).
This model provided an explanation of self-reported alcohol consumption behavior
that is better than chance.
A scafterplot of standardized residuals against standardized predicted scores
was constructed to examine whether assumptions of normality, linearity and
homoscedasticity were met. The plot did not reveal any violations of these
assumptions.
42
Preintervention Associations
Associations between a number of demographic variables and drinking
behavior were explored for this research. The dichotomous variable "Heavy Drinking"
was used as the measure for alcohol consumption behavior. Students who met the
criteria for heavy drinking, i.e. five or more drinks in a row at least once a week, were
considered heavy drinkers. Chi square tests of independence were used to test
associations between drinking behavior (heavy drinking or not heavy drinking) and 1.
Age of the student; 2. Gender; 3. SUNY Potsdam School; 4. Grade point average; 5.
Membership in a Greek organization; 6. On or off campus living arrangement; 7. Class
level; and 8. Number of roommates who get drunk at least once a week. Religion and
ethnicity were not analyzed due to counts less than five in at least one of the cells.
Only one Jewish student was a heavy drinker and only 3 students who were members
of a Protestant faith that does not allow drinking were heavy drinkers. Of the
categories of non-white students, only three were heavy drinkers. For the age
association, only students between the ages of 18 and 22 were included in the analysis
due to small cell counts for all the other ages. First semester Freshmen were not
included in the grade point average analysis. In the living arrangement analysis, the
only off campus students who were counted were those living with other students.
Only five students in the sample reported that they had a 4.0 grade point average (and
one was a heavy drinker), so associations between grade point average and drinking
behavior were calculated for GPAs below a 4.0.
For this sample, heavy drinking was associated with gender, grade point
average, membership in a Greek organization, the number of roommates who drink to
intoxication at least once a week, and year in school. An association between heavy
drinking and SUNY Potsdam School was significant when the Crane School of Music
was included in the analysis. In this sample, however, only 3 Crane students were
heavy drinkers. When Crane students are removed from the analysis, the chi square
statistic is no longer significant at the .05 level of significance. Summary results are
presented in Table 6.
43
Table 6
Chi-Square Tests of Association Between Heavy Drinking and Demographic
Variables
Demographic
Variable
Gender
GPA
Greek Membership
Intoxicated
Roommates
Year in School
Chi-Square Value
Df
Sign flcance
26.672
20.260
4.874
1
3 0.065
4
.00
.00
.03
.00
10.261
3
.02
4
1
44
CHAPTER 5
DISCUSSION
This research was conducted to evaluate the effectiveness of two different kinds
of classroom-based educational interventions that are intended to positively affect
attitudes about alcohol consumption, knowledge about alcohol and patterns of alcohol
use among undergraduate college students. This research showed that for the students
at the State University of New York at Potsdam, these interventions were not effective
for the purposes for which they were intended.
Human health behavior is a complex set of physical, psychological, cultural,
social, economic and organizational factors. Programs that are intended to change
health behavior must consider as many of these factors as possible. In addition,
programs that focus on unhealthful behaviors of adolescents must address factors of
physical and emotional development as well. Beginning with early behavior change
models constructed in the l930's and continuing to the detailed human health behavior
theories being developed by current researchers, there has not, as yet, been developed
a model that can be effectively used to address the problem of college alcohol use and
abuse. It is clear from this research that simple education is not such a model.
Two different types of classroom education were used. One was "Alcohol 101,"
a state-of-the-art computer based CD Rom educational program that is intended to be
almost completely student-centered. The other was a more traditional teacher-centered
lecture-based "motivational speaker" presentation. Both presentations covered the
same topics
drunken driving, sexual assault, and health consequences of
intoxication.
The University of Illinois at Urbana/Champaign is conducting demonstration
phase research regarding the effectiveness of the Alcohol 101 program. Specifically,
the research is concerned with students' attitudes about drinking, and intentions about
drinking alcohol or not drinking. A survey for students to use is embedded in the
45
Alcohol 101 program, and in the fall, 1997 semester, 55 university campuses
nationwide participated in the demonstration research project. This research has not
been published.
In addition, a group of 643 undergraduate students at the University of Illinois
participated in a research project for a short-term evaluation of the effectiveness of the
program. In a method similar to the SUNY Potsdam research, the students were
divided into three groups: an Alcohol 101 group, a traditional education group and a
control group. Students were questioned about which method of learning they
preferred, and the Alcohol 101 students were overwhelmingly favorable to the CD-
ROM type of learning. Students were also asked how much they believed they had
learned, and there was a statistically significant difference in how much the Alcohol
101 students believed they had learned compared to the other groups. The Alcohol 101
students were also more likely to say that they understand important concepts related
to alcohol use and abuse. In terms of changing behavior, students were questioned
about how likely they were to change their alcohol consumption behavior in the next
month. Approximately 4% more of the Alcohol 101 students indicated that they were
considering changing their behavior. This research has not been published.
The SUNY Potsdam research, on the other hand, measured actual knowledge
(as opposed to asking students how much they believed they had learned) and self
reported behavior (as opposed to intentions to change behavior). When considering
that only 4% more of the Alcohol 101 students at the University of Illinois indicated
that they had intentions to change their behavior, compared to those who received
traditional alcohol education, however, there do not appear to be serious conflicts in
the results of both research projects.
For Research Questions #1 and #2, the classroom was the unit of analysis. The
individual was the unit of analysis for Research Question #3. Using printouts from the
SUNY Potsdam's Registrar's Office nine different classes that met inclusion/exclusion
criteria were randomly selected. In order to reach as many students as possible,
46
inclusion criteria required that the student registration for the class must include at
least 10% freshmen and 10% seniors. As a result, most of the classes were General
Education 200 level classes. Grade levels were almost evenly divided among the
classes. Three of the classes were randomly assigned to the Alcohol 101 intervention,
three were randomly assigned to the motivational speaker, and three were randomly
assigned to a control group that did not receive any kind of alcohol education
presentation.
All of the educational programs went smoothly. "Smart classrooms" with the
required computer equipment were used for the Alcohol 101 presentations. A
computer technician was on "standby" to troubleshoot any potential problems with the
equipment or software during each of the computer presentations. In order to ensure
high attendance and prevent students from "skipping" class during the days of the
interventions, students in classes that received interventions were not informed ahead
of time about the presentation.
Informal reports from students regarding the
presentations were positive and enthusiastic. According to the professor who
facilitated the Alcohol 101 classes, students were actively engaged in the
presentations, and many remarked afterward that the presentation was "cool." At least
two students who heard the motivational speech said that it was the best presentation
on alcohol that they had ever heard.
Classroom professors acted as survey administrators for each of the four survey
administrations. They were sent electronic mail reminders the Friday before the
survey, and were provided with surveys on the day before each of the scheduled
survey days. Surveys were returned through campus mail. Some of the professors
scheduled exam reviews or quizzes on the days of the survey in order to have as many
students in class as possible. Approximately 50 students declined to enter the last six
digits of their Social Security Number on the survey each time it was administered.
For these subjects, it was necessary to match their demographic data each time.
47
The sample of students in this research compared favorably to the larger
campus population in terms of gender, age, religion, membership in Greek fraternal
organizations and ethnicity. Mean grade point average (2.91) for the sample was
higher than the larger campus (2.25) but was probably representative of self-reported
grade point average for the rest of the campus. SUNY Potsdam students are
overwhelmingly white and Christian, and the sample for this research represented that
ethnic group. All of the Roman Catholic students knew their faith, but many Protestant
students listed "Methodist" or "Presbyterian" or "Episcopalian" under the category
"none or other (please write in)." During hand scoring of the surveys, these students
were classified as "Protestant that allows drinking."
Statistical analysis showed no differences across groups that could be attributed
to the interventions. Not only were there no statistically significant differences
between the intervention groups and the control group, the means for attitude,
knowledge and behavior across groups were almost identical on the first and
subsequent post intervention surveys.
The results of the second (first post intervention) survey were carefully
scrutinized since, if there were differences, they would most likely occur in that
survey. The mean attitude scores (range = 0 18) across all three groups were just 0.28
points apart. The lowest attitude mean score was for the control group. Mean behavior
scores (range = 0
67) were just 0.5 points apart, although the highest mean was in
the control group.
After the third survey, mean attitude scores were still less than 0.4 points apart.
This time, the highest mean attitude score was in the control group. The mean
behavior score for the control group was 2 points higher than the two intervention
groups.
After the fourth survey, mean attitude scores were still unchanged. Mean
behavior scores for the Alcohol 101 group and the control group were almost
identical, and a slightly higher mean score was seen in the motivational speaker group.
In Research Question #1, analysis of covariance was unable to show a
statistically significant difference across groups on the behavior measure alone.
ANCOVA procedures, using the first behavior score as the covariate, were used to
control for any unidentified confounding effects on behavior scores. The first behavior
scores were artificially equated and post intervention scores were assessed based on
what the scores would have been under equivalent conditions. Because statistical
associations showed a statistically significant association between gender and drinking
behavior, post intervention drinking behavior scores for women were calculated
separately, on the assumption that there may have been gender differences in the
response to the educational interventions. Although there was less of a probability that
the differences in scores for women could have occurred by chance than for both men
and women together, the differences were still not statistically significant.
Most statistical assumptions for MANOVA for the second research question
were met. One exception was linearity between knowledge scores and other outcome
variables. This research showed that students' knowledge about alcohol and the
consequences of intoxication are not related to either their attitudes about college
drinking or their actual drinking behavior. Because data gleaned from MANOVA
procedures are more meaningful when dependent variables are somewhat correlated,
those measurements that met all of the assumptions, including linearity, i.e., those that
did not include knowledge in the grouping, were examined carefully. There were no
significant differences in the grouping of these dependent variables across groups for
any of the post intervention measures.
Because scores from the first survey administration showed an association
between gender and heavy drinking, MANOVA procedures were conducted for
women students alone. As with Research Question #1, although Wilk's lambda values
were higher for women, indicating that the differences were less likely to have
occurred by chance, none of the results was statistically significant.
The third research question was intended to determine if various demographic
variables could be used to predict drinking behavior among undergraduate college
students. Speaking again to the complexity of the problem of alcohol use and abuse
among college students, less than 10% of the variability in drinking behavior could be
attributed to gender, age, grade point average and religion. Gender and membership in
a Protestant faith that allows drinking were the only independent variables that were
statistically significant.
This research used two different measures of drinking behavior
a continuous
measurement based on a composite score from both amount of alcohol consumed and
consequences related to intoxication, and a dichotomous measurement of "heavy
drinking." Heavy drinking was defined as the consumption of more than five drinks in
a row at least once a week (Greenfield, 1998; Midanik et al., 1996). This kind of
heavy drinking is also called "binge drinking." For this research, it was possible for
students to be a heavy drinker and have a relatively low behavior score. A student who
consumed five drinks at one time once a week, would have a continuous behavior
score of 10, for example, but would be classified as a "heavy drinker." At the same
time, if a student consumed a relatively large amount of alcohol during the week, or
suffered consequences related to drinking, but never consumed more than 5 drinks at a
time, it was also possible for that student to have a relatively high behavior score and
not be defined as a "heavy drinker."
Other research has shown that younger students in the lower class levels, in
comparison to upper-class students, do relatively more of the drinking on college
campuses (Wechsler, 1997; Sax, 1997). This research at SUNY Potsdam showed that
the mean behavior scores from the continuous variables that measured both amount of
alcohol consumed and consequences related to intoxication, were similar across ages
up to age 22, and across class levels. Students in this research do not drastically reduce
I1I]
the amount of alcohol they consume once they turn 21, and, for them, alcohol is no
longer "forbidden fruit." The percentage of heavy drinkers for each age and class
level, however, did not reveal consistent trends related to age and class. While 24% of
the 21 year-olds in this research were heavy drinkers, 27% of the twenty-two year-olds
were heavy drinkers. At the same time, the percentage of 19 year-olds who were
heavy drinkers (47%) was greater than the percentage of 18 year-olds (40%) who were
heavy drinkers. Mean behavior scores dropped as much as 5 points between the ages
of 22 and 23. Percentages of heavy drinkers also dropped when students turned 23
years old.
Approximately one percent (4) of the students in this sample reported that they
either forced sex on another student while intoxicated, or had sex forced upon them.
Although any percentage of coerced sexual activity is unacceptable for any group,
particularly in an age of life-threatening sexually transmitted infections, the number of
students reporting sexual coercion in this sample was too small to be statistically
meaningful.
Although recent research has not been able to show gender as a predictor of
heavy drinking among college students (Carey and Correia, 1997; O'Hare and Tran,
1997) this research showed that, in general, SUNY Potsdam women students had
lower mean scores for all measures across all groups. The largest differences were in
behavior scores, followed by attitude scores, and finally knowledge. Mean attitude
scores for women were consistently 1.5 points lower than those for men students.
Behavior scores ranged from 5 points lower for all groups after the third survey to 6
points lower after the fourth survey. The only variation in this trend was a higher
behavior score for women students for the first survey in the control group. Women's
scores were only 1.5 points higher at that time for that group, however.
The association between gender and heavy drinking is clearly related to the
relatively lower behavior scores for women students. These results are consistent with
other research that has shown the male gender to be a predictor of heavy drinking in
51
college (Greenberg et al., 1999; Perkins, 1999). In addition, research has indicated that
stressful conditions in college and risk and sensation seeking are strongly associated
with harmful alcohol consumption patterns among men students, and less so for
women. (Dawson, 1992; Beck et al., 1995). Men students are more likely to drink in a
context of "sex seeking," while women students are more likely to drink to deal with
emotional pain (Beck, et al., 1995).
This research showed an inverse relationship between grade point average and
both attitudes about drinking and drinking behavior. While 12% of students with a
self-reported GPA of 3.5 were heavy drinkers, 50% of those with a GPA of 2.0 were
heavy drinkers. There was a 12% reduction in the number of heavy drinkers for every
0.5 increase in grade point average. Although grade point average contributes a
relatively small amount of explanation to the variance in drinking behavior, mean
behavior scores dropped from between 3 to 7 points for every 0.5 increase in grade
point average.
The association between grade point average and heavy drinking in this
research is related to this inverse relationship. At SUNY Potsdam, students who are
heavy drinkers are more likely to have a relatively lower grade point average than his
or her non-heavy drinking fellow students. Research (Wood et al., 1997) has indicated
that students who are heavy drinkers are also more likely to have been admitted to the
college with other factors that have been traditionally associated with academic
failure. This research suggests, then, that academically talented students may be able
to drink excessively without having their drinking habits adversely affect their
academic progress. This phenomenon may help to explain why grade point average
was not a significant predictor of drinking behavior in research question #3, which
used the continuous measure of drinking behavior, but was strongly associated with
heavy drinking, which used the dichotomous variable. The actual difference between
alcohol consumption and grade point average may lie not in amount of alcohol
consumed over time, but the amount of alcohol consumed at one sitting.
52
For attitudes, there was as much as a 5-point decrease (28%) in mean scores
between a 2.0 and a 4.0 GPA. While students might suggest that poor grades result in
heavy drinking to "drown their sorrows," they would have a relatively difficult time
making a case for poor grades resulting in positive attitudes about college drinking.
Since attitude and behavior are correlated among this sample, this research shows that
a high behavior score and a high score regarding positive attitudes about college
drinking can have a negative effect on students' academic performance. Mean
knowledge scores revealed a 1 2 point increase for every 0.5 increase in GPA.
In this research, forty-six percent of the students who have not declared a major
are heavy drinkers. Although there was not an association between SUNY Potsdam
school and heavy drinking when only the School of Arts and Sciences and the School
of Education are counted, the association becomes significant when the Crane School
of Music is included. Crane students are less likely to be heavy drinkers than students
in the other two schools. Only 3 Crane students in the survey met the criteria for
"heavy drinker." Admission requirements for Crane are different than those of the rest
of the college, and students rarely are admitted to the school with a high school GPA
of less than 3.5. In addition, Crane students must perform a musical audition as part of
the admission process. Once matriculated, Crane students immediately declare a major
and carry between 18 and 21 units per semester.
Students in this research were surveyed about the religion in which they were
raised. The numbers of Jewish students and students who were raised in Protestant
faiths that do not allow drinking were too small to provide meaningful data. However,
there were significant numbers of students who were raised Roman Catholic, in a
Protestant faith that allows drinking, or who were not raised in a religious faith. For all
four surveys, Protestant students had the lowest mean behavior scores and the highest
mean knowledge scores. Roman Catholic students had the highest mean behavior
scores for all surveys except the fourth. Similar differences were seen in mean attitude
scores. Although there is research demonstrating that social norms associated with
membership in the major US religions provide preventive effects against harmful
53
drinking patterns (Patock-Peckham et al., 1998; Smith, 1990) this research did not
show that this holds true for the SUNY Potsdam students. The mean behavior and
attitude scores for those who were not raised in a religious faith were similar to Roman
Catholic and Protestant students. Of the seven students who were raised in a Protestant
faith that does not allow drinking, three were classified as heavy drinkers.
There is much research showing that membership in a college fraternity or
sorority is positively associated with harmful alcohol consumption patterns (Wechsler
et al., 1998). According to the Harvard Alcohol Study (ibid), as many of 85% of
students who belong to Greek fraternal organizations are binge drinkers. In this
research conducted at SUNY Potsdam, half of all members of fraternities and
sororities are heavy drinkers. Although this figure is considerably less than what the
Harvard Study showed, the percentage of heavy drinkers is still 18% higher among
members of Greek fraternal organizations than nonmembers. On the Student Alcohol
Questionnaire, the question about Greek fraternal membership was fitted among other
demographic questions so as not to raise a "red flag," as students are well aware of the
current negative image of Greek fraternal campus organizations. Chi square tests
showed an association between membership and heavy drinking, with students who
are members of Greek organizations more likely to be heavy drinkers. Cashin et aT,
(1998) showed that college students who are members of Greek fraternal organizations
drink significantly more alcohol than their non-Greek fellow students, and drink
heavily more often, and, in addition, are more likely to suffer negative consequences
related to drinking. Furthermore, the leaders in the Greek houses appear to set the
heavy drinking norms for their fraternal members.
Lo and Globetti (1995) indicated in research conducted in the Midwestern
United States, that heavy drinking patterns among Greek members is associated with
the subcultural support inherent in the Greek system. In addition, they found that
students who fraternized with their heavy drinking peers in this Greek system
subculture were more likely to be heavy drinkers themselves. Furthermore, these
researchers determined that excessive alcohol drinking patterns in high school could
54
be used to explain students' decisions to join Greek organizations. If this is the case, it
may not be the Greek organization subculture that results in heavy drinking students,
but rather the heavy drinking subculture attracts students who already have problems
with alcohol.
At SUNY Potsdam, students must live on campus for their first four semesters.
Part of the rationale for this regulation includes the legal liability for the university, for
students who are enrolled and living away from home. Legally, the university is
expected to take on the role of the absent parent.
This regulation assumes that
students who live on campus will be better controlled in situations involving risky
behaviors such as heavy alcohol consumption. Older resident assistants live in
dormitories and are on call to watch over younger students. Although this research
showed an association between living arrangement and heavy drinking, i.e. those
students who live on campus are more likely to be heavy drinkers, living arrangement
may actually be a confounding variable, as students who live on campus are also
younger and more likely to be freshmen and sophomores and the association may
actually be with the variables of age and class level.
This research did not show a linear relationship between heavy drinking and the
drinking behavior of roommates or housemates. Eighteen percent of those who have
zero roommates who drink to intoxication at least once a week are heavy drinkers,
while 68% of those who have four or more roommates who drink to intoxication at
least once a week are heavy drinkers. However, thirty-seven percent of those with two
roommates who drink to intoxication once a week are heavy drinkers, while 50% of
those with either one roommate or three roommates who drink to intoxication once a
week are heavy drinkers. While the research showed an association between having
roonimates who drink to intoxication and heavy drinking in the individual subject, it
appears to be an "all or nothing" relationship. The actual number of intoxicated
roommates does not seem to matter as much as simply having at least one intoxicated
member of the subject's household. Among all those subjects with at least one
intoxicated roommate, 51% are heavy drinkers. Although this research did not explore
55
whether the subject influenced the drinking behavior of his or her roommates or
whether the roommates' behavior influenced the subject, it does appear that peer
influence plays a relatively important role in drinking behavior among these students.
Research conducted by Rose (1999) at Western Kentucky University showed similar
results. Peer cluster theory and six psychosocial characteristics were used to explain
adolescent alcohol use among college students. Those students with heavy drinking
friends were those most likely to be heavy drinkers themselves.
This research helped to provide significant information regarding the
complexity of the problem of alcohol abuse on college campuses. Although both
traditional and state-of-the-art educational interventions were employed, neither
appeared increase students' knowledge about alcohol or to affect alcohol consumption
behavior or attitudes about college drinking among these undergraduate college
students.
Study Limitations
Although several limitations to the validity of the research results were
anticipated, numerous methods of controlling for these limitations were incorporated
into the research methodology. The validity of self-report data is always a concern in
surveys and questionnaires. For this research the data most suspect are those that
measure drinking behavior, grade point average and membership in Greek fraternal
organizations. Most statistical tests that are sensitive to outlying scores specify an
outlier as a score that is more than three standard deviations from the mean. For this
research, only four subjects were considered outliers for the behavior scores. None of
the students' scores for either knowledge or attitude was an outlier. The mean grade
point average for this sample was 0.66 higher than the overall GPA for the campus.
This is not considered to be a serious threat to the validity of the results as GPA was
not a dependent variable in either of the statistical tests that sought to evaluate the
effectiveness of the interventions. Over the last several decades, Greek fraternal
56
campus organizations have developed a negative image both on the campus itself and
in the surrounding communities. As a result, students who are members of fraternities
or sororities might have been less inclined to absolutely truthful about their
membership. Again, this is not considered to be a serious threat to the validity of the
results, as Greek fraternal membership was not a dependent variable in the evaluation
of the effectiveness of the interventions.
Demographic data for each student was compared with each survey
administration. It is assumed that if a student were inventing data about him or herself,
the answers would not be consistent from survey to survey. The survey of just one
student had to be eliminated from the data analysis due to implausible demographic
data, i.e., the student was a Latino Muslim with a very high behavior score.
A small sample size, particularly for some subgroups, was a limitation to the
study as well. Some religious and ethnic groups were not represented in numbers high
enough to make meaningful conclusions about their relationship to outcome variables.
Although music majors were represented in the study, the fact that their numbers did
not reflect the percentage of music majors on campus requires that any study results
regarding music students and outcome variables be approached with caution. The fact
that the sample was relatively homogeneous, however, contributed to potentially less
variability of intersubject differences. The presence of a control group provided a
baseline of comparison to interpret the effectiveness of the educational intervention.
Generalizability of results would be limited to college campuses with similar
demographics to SUNY Potsdam
a midsize Northeastern rural public liberal arts
university. Large or urban campuses or private universities would possibly have
different outcome results.
The Student Alcohol Questionnaire has been previously tested for reliability
and validity. Dr. David Hanson, one of the survey authors, is a professor at SUNY
Potsdam and made himself freely available for assessing necessary changes to the
SAQ. In addition, he provided valuable assistance in explaining the scoring criteria.
57
Nevertheless, some changes were made to the end of the SAQ, and while the amended
survey was assessed for reliability and validity, these results were not published.
Although multivariate statistical techniques were employed to provide more
information, it was difficult to specify power for the research since there currently has
been no similar research conducted from which a plausible effect size could be
estimated. Research conducted at the University of Illinois at Urbana Champaign
provided some information for an effect size, and a power of 0.80 was specified for
the ANCOVA procedures. For all but the fourth survey, the sample sizes for each
group were sufficient.
Attrition was a concern in this research with as many as 31% of the students in
the
total sample being absent from class on the day of the fourth survey
administration. Attrition appeared to be random, however. In comparison to the first
survey, and as measured by their behavior scores, those students who were absent
during the second, third and fourth surveys were not more likely to be absent due to
alcohol consumption.
Potential testing effects on the knowledge part of the survey were explored.
Mean knowledge scores increased 4% from the first survey to the last. Among
individual groups, however, increases in knowledge were random. Only the Alcohol
101 group showed a consistent increase in mean knowledge scores from the first
survey (19.1) to the last (20.5). This is just a 2% increase in number of correct
answers, however. With few changes in mean attitude and behavior scores from first
to last survey administrations, testing effects are not considered a serious limitation.
The lack of statistical significance in research questions 1 and 2, and the
relatively small amoimt of variance in drinking behavior explained by the four
predictor variables in research question 3, may indicate that even small findings in this
research may not be important. The remarkable similarity of means for all outcome
58
variables for all four administrations of the SAQ should suggest that consideration of
any effects demonstrated by this study be approached with caution.
Recommendations
Learning about the consequences of alcohol abuse did not alter these students'
attitudes about college drinking or their alcohol consumption behavior. The college
alcohol abuse problem clearly has roots in social, political, economic, cultural and
psychological factors (Douglas et al. 1997; Gfroerer et al., 1997). Not the least of
these factors is adolescent development related to peer influence and approval (Perkins
et aL, 1999b). Further research is recommended. In particular, a long-term follow-up
cohort study is strongly recommended, with measurements not only of alcohol
consumption patterns, attitudes and knowledge, but those psychological, cultural and
social factors that result in harmful alcohol consumption among adolescents. Such a
research project should ideally begin in middle school and be able to follow a cohort
of student through college and beyond. Research is also recommended for young men
with an undeclared major and a low grade point average
those students most likely
to have a problem with drinking. Research regarding second semester freshmen is also
recommended. While these first semester freshmen did not drink as much as their
sophomore counterparts, it is important to find out if that relationship changes as the
freshmen students move into their second semester on campus
after having had a
chance to make new friends. It would also be important to find out what happens when
a college student turns 23 years of age, as 23 year olds are less likely to have high
behavior scores and be heavy drinkers.
A new technique that employs social marketing of campus drinking norms has
demonstrated remarkable success at the University of Southern Illinois (Sanders,
1997) and at SUNY New Paltz. The technique is based on the idea that many students
believe the percentage of students who abuse alcohol on campus is much higher than it
actually is. Surveys are conducted on campus to determine the actual amount of
59
alcohol abuse among students, and the results are socially marketed to the students.
The results usually employ a phrase such as "The majority of students on this campus
do not abuse alcohol. Join the majority!" Binge drinking at SIU dropped from 43%
before to 28% after the program. Comparable results were seen at SUNY New Paltz
when that university incorporated a similar program.
The SLTNY Potsdam President's Committee on Alcohol is planning a program
like those instituted at SIU and SUNY New Paltz. Students will be surveyed about
their drinking behavior on the first day of classes in the Spring, 2000 semester. The
results will tabulated and, if they are similar to what was shown in this research, i.e.,
only 37% of students are heavy drinkers, this will provide a powerful social marketing
tool. Students will be involved as program administrators from beginning to end.
At the same time, it is critically important to continue to search for answers to
this serious public health problem. Simple education provided by these two
interventions appeared to be a rational solution, but unfortunately it is not. Social,
cultural, political, economic and psychological factors related to alcohol use that play
out through the lives of young people as they are attending college and in the years
before college must be explored and studied simultaneously so that effective programs
can be developed and implemented.
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APPENDICES
68
Appendix A
The Student Alcohol Questionnaire
STUDENT ALCOHOL QUEsTIONNAIREa
and the
ALCOHOL ATTITUDE QUESTIONNAIRIEb
a © R.C. Engs, 1975 b ©D.J. Hanson, 1971
This is a survey of college students' knowledge, attitudes and behaviors
concerning alcohol. We hope that you will volunteer to complete this
questionnaire.
Please write in the last six digits of your social security number.
DO NOT WRITE YOUR NAME on this questionnaire as we wish to retain your anonymity.
PLEASE CIRCLE THE NUMBER THAT APPLIES TO YOU.
1. Male 2. Female
Your Sex:
(write in)
2.
Your Age:
3.
Your major: 1. Music 2. Sociology 3. Physical Sciences 4. Mathematics
5. ArtfDrama/Dance 6. Psychology 7. Education (Please do not circle your second major)
8. Community Health 9. Anthropology 10. Computer Science 11. Business and Economics
12. Politics 13. History 14. Philosophy 15. Language 16. Undeclared
4.
Year in School:
5. Graduate
5.
3. Junior 4. Senior
1. Freshman 2. Sophomore
6. Other __________________(write in)
Grade Point Average:
3.5
3.0
4.0
2.5
2.0
under 2.0
first semester freshman
6.
Ethnicity: 1. White 2. Black or African-American 3. Latino American
4. Asian American 5. Native American 6. Biracial/multiracial
7. Other:
7.
During the past year have you been a member or a pledge of a fraternity/sorority?
1.yes 2.no
8.
1. Roman Catholic 2. Jewish
In what religion were you raised?
Protestant (religion allows drinking of alcoholic beverages)
3.
Protestant (religion does not allow drinking) 5. Muslim
4.
6. None or other:
8.
How important is religion to you? 1. very important 2. moderately important
3. mildly important 4. not important
9.
What is your living arrangement?
2. dorm double 3. dorm suite 4. off campus alone 5. off campus with one
1. dorm single
(write in)
or more additional students 6. off campus with family 7. other
WE WOULD LIKE TO ASK YOU ABOUT YOUR DRINKING PATTERNS
10.
Let's take beer first. How often, on the average, do you usually have a beer?
(If you do not drink beer at all, go to question 12)
1.
everyday
at least once a week but not every day
2.
at least once a month but less than once a week
3.
more than once a year but less than once a month
4.
once a year or less
5.
70
11.
When you drink beer, how much, on the average, do you usually drink at
any one time?
1.
more than I six pack (6 or more cans or tavern glasses)
2.
5 or 6 cans of beer or tavern glasses
3.
3 or 4 cans of beer or tavern glasses
4.
1 or 2 cans of beer or tavern glasses
5.
less than 1 can of beer or tavern glass
12.
Now let's look at table wine. How often do you usually have wine?
(If you do not drink wine at all, go to question 14)
1.
everyday
2.
at least once a week but not every day
3.
at least once a month but less than once a week
4.
more than once a year but less than once a month
5.
onceayearorless
13.
When you drink wine, how much, on the average, do you usually drink
at any one time?
1.
over 6 wine glasses
2.
5 or 6 wine glasses
3.
3 or 4 wine glasses
4.
1 or 2 wine glasses
5.
less than 1 glass of wine
14.
Next we would like to ask you about liquors and spirits (whiskey, gin, vodka,
mixed drinks, etc.). How often do you usually have a drink of liquor?
(If you do not drink liquor at all, skip questions 14 and 15.)
1.
everyday
2.
at least once a week but not every day
3.
at least once a month but less than once a week
4.
more than once a year but less than once a month
5.
once a year or less
15.
When you drink liquor, how many drinks, on the average, do you usually
drink at any one time?
1.
over 6 drinks
2.
5 or 6 drinks
3.
4.
5.
3or4drinks
lor2drinks
less than 1 drink
IF YOU DO NOT DRINK ALCOHOL AT ALL, PLEASE GO TO QUESTION
37.
16. Whom do you drink with most often?
1. friends 2. parents 3. brother(s)/sister(s)
5. alone 6. a date 7. never drink
4. other relative
8. some other person
(write in)
17. After drinking during the last two weeks, did you force someone or did someone force you to have sex?
l.yes
2.no
18. If you live with other students, how many of your room/housemates get drunk at least once each week?
1. none 2. one 3.two 4. three 5. four or more 6. don't live with other students
71
The following are common results of drinking alcohol that students have reported. In the last
TWO WEEKS, have you: (Please circle any that apply to you.)
19. had a hangover
29. had trouble with the law because
20. been nauseated and
of drinking
vomited from drinking
30. lost ajob because of drinking
21. driven a car after having several drinks
31. got a lower grade because of drinking
22. driven a car when you knew
32. been in trouble with the school administration
you had too much to drink
because of behavior resulting from drinking
23. driven a car while drinking
too much
24. come to class after having several drinks
33. been in a fight after drinking
25. "cut a class" after having several drinks
34. thought you might have a problem with
26. missed a class because of a hangover
your drinking
27. arrested for DWI (Driving While Intoxicated) 35. damaged property, pulled a false fire alarm
28. been criticized by someone you were
or other such behavior after drinking
dating because of your drinking
36. participated in a drinking game
WE WOULD NOW LIKE TO ASK YOU SOME INFORMATION ABOUT ALCOHOL
The answers to the questions will either be TRUE or FALSE.
Please circle the correct answer. If you do not know the answer to the question, DO NOT GUESS. Leave the item
blank.
T F 37. Drinking milk before drinking an alcoholic beverage will slow the absorption of alcohol into
the body.
T F 38. Wines are made by fermenting grains.
T F 39. Alcoholic beverages do not provide weight-increasing calories.
T F 40. In America, drinking is usually considered an important socializing custom in business, for
relaxation and for improving interpersonal relationships.
T F 41. Gulping of alcoholic beverages is a commonly accepted drinicing pattern in this country.
T F 42. Alcohol is usually classified as a stimulant.
T F 43. Alcohol is not a drug.
T F 44. A blood alcohol content of 0.1% is the legal defmition of alcohol intoxication in most states,
in regards to driving.
T F 45. Approximately 10% of fatal highway accidents are alcohol related.
T F 46. Alcohol was used for centuries as a medicine in childbirth, for sedation and surgery.
T F 47. Table wines contain from 2
12% alcohol by volume.
T F 48. It is estimated that approximately 85% of the adult Americans who drink, misuse or abuse
alcoholic beverages.
T F 49. Many people drink to escape from problems, loneliness and depression.
T F 50. Liquor mixed with soda pop will affect you faster than liquor drunk straight
T F 51. The most commonly drunk alcoholic beverages in the United States are distilled liquors
(whiskey, gin, vodka).
T F 52. A 150 pound person, to keep his blood alcohol concentration below the legally intoxicated
level, would have to drink fewer than 3 beers in an hour.
T F 53. A person cannot become an alcoholic by just drinking beer.
72
T F 54. To prevent getting a hangover, one should sip one's drink slowly, drink and eat at the same
time, space drinks over a period of time, and not drink over one's limit.
T F 55. Responsible drinking can result in relaxation, enhanced social interactions, and a feeling of
well-being.
T F 56. Distilled liquors (whiskey, gin, vodka) usually contain about 15-20% alcohol by volume.
T F 57. Moderate consumption of alcoholic beverages is generally not harmful to the body.
T F 58. It takes about as many hours as the number of beers drunk to completely burn up the alcohol
ingested.
T F 59. Mi ounce of whiskey contains about 60 calories.
T F 60. Many people drink for social acceptance, because of peer pressures, and to gain adult status.
T F 61. A blood alcohol concentration of .02% causes a person to be in a stupor.
T F 62. Liquors such as gin, scotch and whiskies are usually distilled from mashes made from
fermenting grains.
T F 63. Proof on a bottle of liquor represents half the percent of alcohol contained in the bottle.
T F 64. The United States lacks a national consensus on what constitutes the responsible use of
alcoholic beverages.
T F 65. There is usually more alcoholism in a society that accepts drunken behavior than in a society
that frowns on drunkenness.
I F 66. Beer usually contains from 2 12% alcohol by volume.
T F 67. Eating while drinking will have no effect on slowing down the absorption of alcohol in the
body.
T F 68. Drinking coffee or taking a cold shower can be an effective way of sobering up.
T F 69. Wines throughout history have been commonly drunk at religious ceremonies and family
gatherings.
T F 70. Drinking of alcoholic beverages has been common in the USA since the Puritans first settled
here.
T F 71. Alcohol has only been used in a very few societies throughout history.
T F 72. Liquor taken straight will affect you faster than liquor mixed with water.
WE WOULD NOW LIKE TO ASK YOU ABOUT SOME OF YOUR FEELINGS ABOUT
DRINKING
Please circle the response that most closely represents your opinion.
73. Drinking alcohol is an important part of college life.
a. strongly agree b. agree c. disagree
d. strongly disagree
74. Shy or inhibited people have an easier time meeting new people when they are drunk.
a. strongly agree b. agree c. disagree
d. strongly disagree
75. In Potsdam, there are many things to do besides drinking.
a. strongly agree b. agree c. disagree
d. strongly disagree
76. A party without alcohol is not much fun.
a. strongly agree b. agree c. disagree
d. strongly disagree
77. Getting drunk once or twice a week is okay.
a. strongly agree b. agree c. disagree
d. strongly disagree
78. Drinking alcohol is a good way to relieve the stresses of college life.
a. strongly agree b. agree c. disagree
d. strongly disagree
73
Appendix B
Description of the Sample
Table Bi
Year in School
Frequency
Valid
Freshman
Sophomore
Junior
Senior
Total
81
105
96
78
360
Percent
22.5
29.2
26.7
21.7
100.0
Valid Percent
22.5
29.2
26.7
21.7
100.0
Cumulative Percent
22.5
51.7
Valid Percent
90.4
2.5
Cumulative Percent
90.4
93.0
95.2
98.0
98.6
100.0
78.3
100.0
Table B2
Ethnicity of the Sample
Frequency
Valid
Missing
Total
White
Black
Latino-American
Native American
Biracial/Multiracial
Other
Total
99.00
321
9
8
10
2
Percent
89.2
2.5
2.2
2.8
5
.6
1.4
355
98.6
5
1.4
360
100.0
2.3
2.8
.6
1.4
100.0
Table B3
Religions of the Sample
Frequency
Valid
Roman Catholic
Jewish
Protestant (allows drinking)
Protestant (does not allow
drinking)
None or other
Total
Missing
99.00
Total
167
Percent
46.4
Valid Percent
48.1
11
3.1
3.2
83
23.1
4.2
23.9
4.3
19.7
96.4
3.6
100.0
20.5
100.0
15
71
347
13
360
Cumulative Percent
48.1
51.3
75.2
79.5
100.0
74
Table B4
Importance of Religion of the Sample
Valid
Very important
Moderately important
Mildly important
Not important
Total
Missing
99.00
Total
Frequency
54
Percent
Valid Percent
15.0
15.3
15.3
104
106
28.9
29.4
25.0
98.3
29.4
29.9
25.4
100.0
44.6
74.6
90
354
6
Cumulative Percent
100.0
1.7
100.0
360
Table B5
Living Arrangement of the Sample
Valid
Frequency
Percent
Dorm single
Dorm double
Dorm suite
Off campus alone
Off campus with students
Off campus with family
Other
33
105
58
9.2
29.2
Valid Percent
9.2
29.2
16.1
16.1
18
5.0
90
49
25.0
5.0
25.0
13.6
13.6
7
1.9
1.9
Total
360
100.0
100.0
Cumulative Percent
9.2
38.3
54.4
59.4
84.4
98.1
100.0
Table B6
Number of Roommates who "Get Drunk" Each Week
Valid
Frequency
Percent
79
71 9
2
78
32
3
15
4ormore
38
67
21.7
8.9
4.2
10.6
18.6
0
1
Missing
Total
Don't live with other
students
Total
99.00
309
51
360
85.8
14.2
100.0
Valid Percent
25.6
25.2
10.4
4.9
12.3
21.7
100.0
Cumulative Percent
25.6
50.8
61.2
66.0
78.3
100.0
75
Table B7
Grade Point Averages of the Sample
Valid
Frequency
Percent
Valid Percent
Cumulative Percent
6
1.7
38
78
102
57
10.6
2.1
13.3
27.3
100.0
13.3
40.6
76.2
96.2
97.9
1.25
2.0
2.5
3.0
3.5
4.0
Total
Missing
1.00
First Semester Freshman
99.00
Total
Total
5
286
21.7
28.3
15.8
1.4
79.4
1
.3
59
35.7
19.9
1.7
100.0
14
16.4
3.9
74
360
100.0
Frequency
Percent
Valid Percent
Cumulative Percent
43
11.9
88.1
11.9
88.1
100.0
11.9
100.0
20.6
Table 1B8
Greek Membership of the Sample
Valid
Yes
No
Total
317
360
100.0
Appendix C
Data Screening Graphs and Plots
100
80
60
40
Std. Dev = 3.68
20
i)
Mean = 8.2
ci)
N = 278.00
I-
0
00
10.0
5.0
2.5
7,5
15.0
17.5
12.5
First Attitude Score
Figure Cl
Histogram of First Attitude Scores
Overlain with a Normal Curve
70
60
50
40
30
Std.Dev
5.71
Mean = 18.6
N = 280.00
12.5
2
17.5
15.0
22.5
20.0
27.5
25.0
30.0
'ledge Score
of First Knowledge Scores
vith a Normal Curve
77
40
30
20
0
10
Std. Dev= 14.61
Mean = 22.6
N=279.00
0
10.0 20.0 30.0 40.0 50.0 60.0
0.0
5.0
15.0 25.0
70.0
35.0 45.0 55.0 65.0
First Behavior Score
Figure C3
Histogram of First Behavior Scores
Overlain with a Normal Curve
Std. Dev =
0
Mean = 8.4
cD
N = 293.00
00
50
2.5
10.0
7.5
20.0
15.0
12.5
17.5
Second Attitude Score
Figure C4
Histogram of Second Attitude Scores
Overlain with a Normal Curve
3.55
78
70
60
50
40
30
20
Std. Dev
0
C
Mean =
10
i.i.
5.92
19.8
N = 295.00
0
0.0
5.0
2.5
10.0
7.5
15.0
12.5
20.0
17.5
25.0
22.5
30.0
27.5
Second Knowledge Score
Figure C5
Histogram of Second Knowledge Scores
Overlain with a Normal Curve
50
40
30
20
Std. Dcv =
10
I)
15.22
Mean = 22.4
N = 295.00
0
.o.o.o.o.o.o.o.o.o.o.o.o.a.o.o.o
Second Behavior Score
Figure C6
Histogram of Second Behavior Scores
Overlain with a Normal Curve
79
Std.Dev= 3.65
Mean = 8.1
N=263.00
0.0
4.0
2.0
8.0
6.0
16.0
12.0
10.0
14.0
18.0
Third attitude score
Figure C7
Histogram of Third Attitude Scores
Overlain with a Normal Curve
70
60
50
40
30
20
Std. Dev = 5.74
C)
Mean = 20.1
10
a)
N=266.00
0.0
5.0
2.5
10.0
7.5
15.0
12.5
20.0
17.5
25.0
22.5
30.0
27.5
Third knowledge score
Figure C8
Histogram of Third Knowledge Scores
Overlain with a Normal Curve
80
50
40
30
20
Std. Dev = 14.86
10
Mean = 21.3
2
N=265.00
0
Third behavior score
Figure C9
Histogram of Third Behavior Scores
Overlain with a Normal Curve
Std. Dev = 3.61
C.)
C)
Mean = 9.1
C)
N=240.00
0.0
100
5.0
2.5
7.5
20.0
15.0
12.5
17.5
Fourth Attitude Score
Figure C 10
Histogram of Fourth Knowledge Scores
Overlain with a Normal Curve
81
80
70
60
50
40
30
...
20
Std. Dev= 5.31
Mean = 20.1
10
N = 236.00
I-
u.
0
2.5
7.5
5.0
12.5
10.0
17.5
15.0
22.5
20.0
27.5
25.0
30.0
Fourth Knowledge Score
Figure Cli
Histogram of Fourth Knowledge Scores
Overlain with a Normal Curve
60
50
40
30
20
Std. Dev= 13.73
Mean = 21.2
N = 243.00
0
5
10
0.0
10.0 20.0 30.0 40.0 50.0 60.0 70.0
5.0
15.0 25.0 35.0 45.0 55.0 65.0 75.0
Fourth Behavior Score
Figure C12
Histogram of Fourth Behavior Scores
Overlain with a Normal Curve
82
0
0
0
0
0
0
0
0080 0
0
000000 00 0
0 anna 0000
O
00 00000000 0000
0
0
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0
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10
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00
ci
0
a
Ii
000
0)
0
C)
CID
0008
000
0
0
0
00
0
0
00
0
0
00
0
-'
0
LI
0000
CI
(10000
00
00 000(100
0
00
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0000
011
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Ii
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0
00
o
LI
0
0
0
as
00
no
a
0
1)
0
Di)
00
0
11)
In
5-
-10
0
10
20
30
40
First Knowledge Score
Figure C13
Scatterplot of First Attitude Scores with
First Knowledge Scores
20
0
0
O
aIr
LI
((fl)
LI
CI
Dcii
CI 0 CEO 0 0
LU
0
0 (ID 0 LU) Ci] CO (1 1)
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Figure C14
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Figure C15
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40
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Scatterplot of Second Knowledge Scores with
Second Behavior Scores
85
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Figure C19
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Third Knowledge Scores
20
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Figure C20
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Third Behavior Scores
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Figure C22
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Fourth Knowledge Scores
40
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Figure C23
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40
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Figure C24
Scatterplot of Fourth Knowledge Scores with
Fourth Behavior Scores
80
88
Appendix D
Data Screening Tables
Table Dl
Statistical Analysis of Normality for Outcome Variables for the First Survey
First Attitude Score First Knowledge Score
N
Valid
Missing
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
277
2
-.113
.146
.012
.292
279
Ffrst Behavior
Score
279
0
0
.313
.146
-.545
.146
-.428
-.574
.291
.291
Table D2
Statistical Analysis of Normality for Outcome Variables for the Second Survey
N
Valid
Missing
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
Second Attitude
Score
235
44
-.195
.159
-.20 1
.316
Second Knowledge
Score
235
44
-.600
.159
-.175
.316
Second Behavior
Score
235
44
.501
.159
-.214
.316
Table D3
Statistical Analysis of Normality for Outcome Variables for the Third Survey
Thfrd attitude score Thfrd knowledge score
N
Valid
Missing
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
220
59
-.147
.164
-.332
.327
Third behavior
score
222
57
-.937
221
58
.688
.164
.136
.326
.163
.470
.325
Table D4
Statistical Analysis of Normality for Outcome Variables for the Fourth Survey
N
Skewness
Std. Error of Skewness
Kurtosis
Std. Error of Kurtosis
Valid
Missing
Fourth Attitude
Score
205
Fourth Knowledge
Score
200
Fourth Behavior
Score
207
74
-.100
.170
.337
.338
79
-.766
.172
.510
.342
72
1.049
.169
1.472
.337
89
Table D5
Correlation Matrix for Outcome Variables for the
First Survey
Correlation
First Attitude Score
First Knowledge Score
First Behavior Score
First Attitude Score
First Knowledge
Score
First Behavior
Score
1.000
.193
.698
.193
1.000
.142
.698
.142
1.000
Table D6
Correlation Matrix for Outcome Variables for the
Second Survey
Second Att itude
Score
Correlation
Second Attitude Score
SecondKnowledge Score
Second Behavior Score
1.000
.139
.605
Second Knowledge Second Behavior
Score
Score
.139
.605
1.000
.134
.134
1.000
Table D7
Correlation Matrix for Outcome Variables for the
Third Survey
Thfrd attitude score
Third knowledge
score
Correlation
Third attitude score
Third knowledge score
Third behavior score
1.000
.161
.662
.161
1.000
.226
Third behavior
score
.662
.226
1.000
Table D8
Correlation Matrix for Outcome Variables for the
Fourth Survey
Correlation
Fourth Attitude Score
Fourth Knowledge Score
Fourth Behavior Score
Fourth Attitude
Score
Fourth Knowledge
Score
Fourth Behavior
Score
1.000
.061
.634
.061
1.000
.076
.634
.076
1.000
Table D9
Correlation Matrix for the First Behavior Score (Covariate) and Dependent Variables
Correlation
First Behavior Score
Second Behavior Score
Third behavior score
Fourth Behavior Score
First Behavior
Second
Third
Fourth
Score
Behavior Score behavior Behavior Score
score
1.000
.897
.788
.790
.897
.788
.790
1.000
.852
.792
.852
1.000
.781
.792
.781
1.000
Table D10
Tests of Between-Subjects Effects for Homogeneity of Regression
Dependent Variable: Second Behavior Score
Source
Corrected Model
Intercept
GROUP
Bi
GROUP * Bi
Error
Total
Corrected Total
Type III Sum of Squares
43844.286
96560.395
44.029
34824.467
2793.167
3767.825
157946.000
47612.111
df
118
1
2
53
63
116
Mean Square
371.562
96560.395
22.014
657.065
44.336
F
11.439
2972.804
.678
20.229
1.365
Sig.
.000
.000
.510
.000
.075
32.481
235
234
R Squared = .921 (Adjusted R Squared = .840)
Table Dli
Tests of Between-Subjects Effects for Homogeneity of Regression
Dependent Variable: Third behavior score
Source
Corrected Model
Intercept
GROUP
BI
GROUP * Bi
Error
Total
Corrected Total
R Squared
Type III Sum of Squares
35578.290
78864.449
219.799
28198.184
2969.137
6380.637
137890.000
41958.927
1
Mean Square
326.406
78864.449
2
53
54
110
109.900
532.041
54.984
58.006
df
109
F
5.627
1359.596
Sig.
.000
9.172
.948
.000
.155
.000
.579
1.895
220
219
.848 (Adjusted R Squared = .697)
Table D12
Tests of Between-Subjects Effects for Homogeneity of Regression
Dependent Variable: Fourth behavior score
Source
Corrected Model
Intercept
GROUP
Bi
GROUP *Bl
Error
Total
Corrected Total
Type III Sum of Squares
25661.511
71596.682
69.473
20989.477
2711.778
693 1.117
117424.000
32592.627
df
101
1
2
45
54
102
204
203
R Squared = .787 (Adjusted R Squared = .577)
Mean Square
254.074
71596.682
34.737
466.433
50.218
67.952
F
Sig.
3.739
1053.634
.000
.000
.511
.601
6.864
.739
.000
.889
91
Appendix E
Tables of Data in the Analysis of the Research Questions
Table El
Analysis of Covariance
Dependent Variable: Second Behavior Score
Source
Corrected Model
Intercept
Type III Sum
of Squares
df
Mean Square
F
Sig.
3
12774.915
106.692
38320.052
77.770
40.205
3 17.744
.000
.105
.000
.147
Bi
38324.745
106.692
38320.052
GROUP
Error
Total
Corrected Total
155.541
2
9287.366
157946.000
47612.111
231
1
1
235
234
R Squared = .805 (Adjusted R Squared = .802)
Alcohol 101 n = 79; Motivational Speaker n = 67; Control n
Table E2
Analysis of Covariance
Dependent Variable: Third behavior score
Source
Type III Sum ofSquares
Corrected Model
Intercept
B!
GROUP
Error
Total
Corrected Total
29356.064
708.940
29042.295
418.979
15204.108
143074.000
44560.172
2.654
953.115
1.934
89
df
Mean Square
F
3
9785.355
708.940
29042.295
209.490
70.065
139.661
10.118
1
1
2
217
221
220
414.505
2.990
Sig.
.000
.002
.000
.052
R Squared .659 (Adjusted R Squared = .654)
Alcohol 101 n = 81; Motivational Speaker n = 53; Control n = 87
Table E3
Analysis of Covariance
Dependent Variable: Fourth Behavior Score
Source
Type III Sum ofSquares
Corrected Model
Intercept
B1
GROUP
Error
Total
Corrected Total
20209.602
666.775
20097.652
25.972
12383.026
117424.000
32592.627
df
Mean Square
F
Sig.
3
6736.534
666.775
20097.652
108.803
10.769
324.600
.210
.000
1
1
2
200
204
203
12.986
61.915
R Squared = .620 (Adjusted R Squared = .6 14)
Alcohol 101 n = 70; Motivational Speaker n = 66; Control n
68
.001
.000
.811
Table E4
Box's Test of Equality of Covariance Matrices for Attitude, Knowledge and Behavior
for the Second Survey
Box'sM
11.255
F
.920
dfl
12
d12
231530
Sig.
.525
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups.
Design: Intercept+GROUP
Table E5
Multivariate Analysis of Variance for Attitude, Knowledge and Behavior for the
Second_Survey
Ljjéct
Value
F
Error df Sig.
Hypothesis df
Intercept
Wilks' Lambda
.057
1279.954
3.000
230.000
.000
Wilks' Lambda
.991
.349
6.000
460.000
.911
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 94; Motivational Speaker n = 103; Control n =96
Table E6
Box's Test of Equality of Covariance Matrices for Attitude and Knowledge for the
Second Survey
Box'sM
F
10.656
1.758
dfl
6
d12
2017170
Sig.
.103
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
93
Table E7
Multivariate Analysis of Variance for Attitude and Knowledge for the
Second_Survey
Value
F
Hypothesis df
Wilks' Lambda
.059
2324.368
2.000
289.000
.000
Wilks' Lambda
.989
.766
4.000
578.000
.548
Effect
Intercept
Error df Sig.
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 94; Motivational Speaker n = 103; Control n =96
Table E8
Box's Test of Equality of Covariance Matrices for Attitude and Behavior for the
Second_Survey
Box'sM
7.947
F
dfl
1.311
6
df2
Sig.
2017170
.248
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table E9
Multivariate Analysis of Variance for Attitude and Behavior for the Second Survey
Effect
Value
F
Hypothesis df Error df Sig.
Intercept
Wilks' Lambda
.150
8 15.965
2.000
289.000
.000
Wilks' Lambda
.996
.284
4.000
578.000
.888
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 94; Motivational Speaker n = 103; Control n =96
Table ElO
Box's Test of Equality of Covariance Matrices for Knowledge and Behavior for the
Second Survey
BofsM 9.758
F
dfl
dt2
Sig.
1.610
6
2007682
.140
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
94
Table Eli
Multivariate Analysis of Variance for Knowledge and Behavior for the
Second_Survey
Value
F
Wilks' Lambda
.073
1843.109
Wilks' Lambda
.991
.651
Effect
Intercept
Hypothesis
Error df
Sig.
2.000
291.000
.000
4.000
582.000
.627
df
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 94; Motivational Speaker n = 103; Control n = 96
Table E12
Boxts Test of Equality of Covariance Matrices for Attitude, Knowledge and Behavior
for the Third Survey
Box'sM
F
13.781
1.129
dfl
12
d12
310655
.330
Sig.
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table El3
Multivariate Analysis of Variance for Attitude, Knowledge and Behavior for the
Third Survey
Effect
Value
F
Hypothesis df Error df Sig.
Intercept
Wilks' Lambda
.059
1360.511
3.000
257.000
.000
Wi1ks Lambda
.987
.580
6.000
514.000
.746
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 93; Motivational Speaker n = 79; Control n
90
95
Table E14
Box's Test of Equality of Covariance Matrices for Attitude and Knowledge for the
Third Survey
Box'sM
dfl
df2
Sig.
8.530
1.406
6
1470594
.208
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Tntercept+GROUP
Table E15
Multivariate Analysis of Variance for Attitude and
ge for the Third Survey
Error df Sig.
Value
Intercept
Wilks' Lambda
.060
2020.174
2.000
259.000
.000
Wilks' Lambda
.989
.703
4.000
5 18.000
.590
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 93; Motivational Speaker n = 79; Control n =90
Table E16
Box's Test of Equality of Covariance Matrices for Attitude and Behavior for the
Third Survey
Box'sM
F
5.378
.886
dfl
6
dt2
1469988
.504
Sig.
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table E17
Multivariate Analysis of Variance for Attitude and Behavior for the
Third Survey
Effect
Value
F
Hypothesis df
Error df
Sig.
Intercept
Wilks' Lambda
.168
637.149
2.000
258.000
.000
Wilks' Lambda
.995
.341
4.000
5 16.000
.850
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 93; Motivational Speaker n = 79; Control n =90
Table E18
Box's Test of Equality of Covariance Matrices for Knowledge and Behavior for the
Third Survey
Box'sM
10.336
F
1.704
6
1553622
.116
dfl
dt2
Sig.
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table E19
Multivariate Analysis of Variance for Knowledge and Behavior for the
Third Survey
Value
F
Hypothesis df
Wilks' Lambda
.072
1677.534
2.000
26 1.000
.000
Wilks' Lambda
.987
.862
4.000
522.000
.486
Effect
Error df Sig.
Intercept
GROUP
Design: Intercept+GROUP
Alcohol 101 n 93; Motivational Speaker n = 81; Control n = 91
Table E20
Box's Test of Equality of Covariance Matrices for Attitude, Knowledge and Behavior
for the Fourth Survey
Box'sM
F
33.734
2.758
dfl
12
df2
Sig.
244157
.001
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table E21
Multivariate Analysis of Variance for Attitude, Knowledge and Behavior for the
Fourth Survey
Effect
Value
F
Hypothesis df Error df Sig.
Intercept
Wilks' Lambda
.043
1693 .009
3.000
227.000
.000
Wilks Lambda
.982
.702
6.000
454.000
.648
GROUP
Design: Jntercept+GROUP
Alcohol 101 n = 74; Motivational Speaker n = 85; Control n = 73
97
Table E22
Box's Test of Equality of Covariance Matrices for Attitude and Knowledge for the
Fourth Survey
Box's M
F
13.977
2.300
dfl
6
df2
Sig.
1190851
.032
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table E23
Multivariate Analysis of Variance for Attitude and Knowledge for the
Fourth Survey
Value
F
Hypothesis df
Wilks' Lambda
.043
2544.082
2.000
229.000
.000
Wilks' Lambda
.985
.857
4.000
458.000
.490
Effect
Intercept
Error df Sig.
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 74; Motivational Speaker n = 85; Control n
74
Table E24
Box's Test of Equality of Covariance Matrices for Attitude and Behavior for the
Fourth Survey
Box'sM
F
7.948
1.308
dfl
6
df2
Sig.
1222976
.249
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table E25
Multivariate Analysis of Variance for Attitude and Behavior for the
Fourth Survey
Effect
Value
F
Hypothesis df Error df
Sig.
Intercept
Wilks' Lambda
.134
759.392
2.000
235.000
.000
Wilks' Lambda
.998
.130
4.000
470.000
.972
GROUP
Design: Intercept±GROUP
Alcohol 101 n 79; Motivational Speaker n = 87; Control n = 73
98
Table E26
Box's Test of Equality of Covariance Matrices for Knowledge and Behavior for the
Fourth Survey
Box'sM
F
21.985
3.618
dfl
6
df2
Sig.
1194071
.001
Tests the null hypothesis that the observed covariance matrices of the dependent
variables are equal across groups. Design: Intercept+GROUP
Table E27
Multivariate Analysis of Variance for Knowledge and Behavior for the
Fourth Survey
Value
F
Hypothesis df
Wilks' Lambda
.056
1944.826
2.000
231.000
.000
Wilks' Lambda
.983
1.022
4.000
462.000
.395
Effect
Intercept
Error df Sig.
GROUP
Design: Intercept+GROUP
Alcohol 101 n = 76; Motivational Speaker n = 86; Control n = 73
Table E28
Summary Results of Discrirninant Analysis for the Second
Predicted Group
Total
It'Iemherchin
Original
Count
%
Group
Alcohol 101
Alcohol 101
36
Motivational Speaker
32
29
42
103
Control
28
16
52
96
Alcohol 101
38.3
25.5
36.2
100.
0
Motivational Speaker
31.1
28.2
40.8
100.
Motivational Speaker Control
24
34
94
0
Control
29.2
16.7
54.2
100.
0
39.9% of original grouped cases correctly classified.
Table E29
Summary Results of Discriminant Analysis for the Third Survey
Predicted Group
Membership
Original
Count
%
Total
Group
Alcohol 101
Alcohol 101
23
Motivational Speaker
22
26
31
79
Control
21
22
47
90
Alcohol 101
24.7
26.9
48.4
100.0
Motivational Speaker
27.8
32.9
39.2
100.0
Control
23.3
24.4
52.2
100.0
Motivational Speaker Control
25
45
93
36.6% of original grouped cases correctly classified.
Table E30
Summary Results of Discriminant Analysis for the Fourth Survey
Group
Alcohol 101
Original
Count
%
Predicted Group
Membership
Alcohol 101
Total
Motivational Speaker
26
Control
17
31
74
Motivational Speaker
17
35
33
85
Control
12
26
35
73
Alcohol 101
23.0
35.1
41.9
100.0
Motivational Speaker
20.0
41.2
38.8
100.0
Control
16.4
35.6
47.9
100.0
3 7.5% of original grouped cases correctly classified.
100
Table E31
Correlation Matrix for Predictor Variables
Correlation
Gender
Grade
Point
Average
Freshman
status
Sophomor
e status
Junior
Status
Senior
Status
Roman
Catholic
Jewish
Protestant
Allows
Drinking
Protestant
No
drinking
Gender Grade Freshman SophPoint
status omore
Average
status
Junior Senior Roman Jewish Protestant - Protestant Allows
Status Status Catholic
1.000
.061
.061
1.000
.033
.102
-.044
-.070
.064
-.002
-.058
.029
.041
.026
-.029
-.053
.064
.057
-.148
.080
.033
.102
1.000
-.175
-.156
-.144
-.001
-.034
-.072
.107
-.044
-.070
-.175
1.000
-.494
-.456
.003
-.007
-.008
.026
.064
-.002
-.156
-.494
1.000
-.406
-.065
.002
.032
-.068
-.058
.029
-.144
-.456
-.406
1.000
.054
.020
.035
-.011
.041
.026
-.001
.003
-.065
.054
1.000
-.137
-.523
-.196
-.029
.064
-.053
.057
-.034
-.072
-.007
-.008
.002
.032
.020
.035
-.137
-.523
1.000
-.089
-.089
1.000
-.031
-.127
-.148
.080
.107
.026
-.068
-.011
-.196
-.031
-.127
1.000
Table E32
ANOVA for Linear Fit of the Equation
Model
Sum of Squares
df
1
Regression
Residual
Total
3666.488
42829.535
46496.023
9
208
217
Drinking
Mean Square
407.388
205.911
F
1.978
°.
drinking
Sig.
.043
Predictors: (Constant), Protestant No drinking, Junior Status, Grade Point Average,
Jewish, Gender, Protestant - Allows Drinking, Freshman status, Senior Status, Roman
Catholic
Dependent Variable: First Behavior Score
101
Appendix F
Means and Standard Deviations by Group and
Stratified by Gender, Age, Grade Point Average and Religion
Table Fl
Means and Standard Deviations for the First Survey by Group
Group
First Attitude Score
Alcohol 101
Mean
N
Std. Deviation
Motivational Speaker
Mean
N
Std. Deviation
Control
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
8.3226
First Knowledge
Score
19.1720
First Behavior
Score
23.7634
93
93
93
3.5970
8.4615
5.3418
19.0108
15.1596
23.1304
92
14.2229
20.8191
94
14.4304
22.5627
279
14.6133
91
93
3.8015
7.7979
94
3.6414
8.1906
278
3.6779
6.0496
17.7553
94
5.6790
18.6429
280
5.7124
Table F2 Means and Standard Deviations for the Second Surve
Group
Second Attitude Score Second Knowledge
Score
Alcohol 101
Mean
8.4681
19.1915
N
94
94
Std. Deviation
3.6121
6.4563
Motivational Speaker
Mean
8.5340
19.5810
N
103
105
Std. Deviation
3.4466
6.2107
Control
Mean
8.2500
20.53 13
N
96
96
Std. Deviation
3.6216
4.933 1
Total
Mean
8.4198
19.7661
N
293
295
Std. Deviation
3.5478
5.9163
Second Behavior
Score
22.1915
94
14.3364
22.2286
105
15.7537
22.7083
96
15.6043
22.3729
295
15.2165
102
Table F3 Means and Standard Deviations for the Third Survey by Group
Group
Third attitude score
Third knowledge
score
Alcohol 101
Mean
7.9247
19.7312
N
93
93
Std. Deviation
3.4774
6.2834
Motivational Speaker
Mean
8.1266
19.4691
N
79
81
Std. Deviation
5.4729
3.8443
Control
Mean
8.3187
20.9022
N
91
92
Std. Deviation
3.6814
5.3351
Total
Mean
8.1217
20.0564
N
263
266
Std. Deviation
3.6508
5.7371
Table F4
Means and Standard Deviations for the Fourth Survey by Group
Group
Fourth Attitude Score Fourth Knowledge
Score
Alcohol 101
Mean
9.0380
20.5526
N
79
76
Std. Deviation
3.4285
5.1079
Motivational Speaker
Mean
19.3372
8.9080
N
87
86
Std. Deviation
3.8988
6.1177
Control
Mean
9.2568
20.6757
N
74
74
Std. Deviation
3.4997
4.3765
Total
Mean
9.0583
20.1483
N
240
236
Std. Deviation
3.6149
5.3099
Table F5
Means and Standard Deviations for the First Survey by Group by Gender
Group
Gender
First Attitude Score First Knowledge
Score
Alcohol 101
Male
Mean
10.0000
19.7805
N
41
41
Std. Deviation
3.3392
5.1842
Female
Mean
7.0000
18.6923
N
52
52
Std. Deviation
3.2479
5.4648
Total
Mean
8.3226
19.1720
N
93
93
Std. Deviation
3.5970
5.34 18
Motivational
Male
Mean
9.4750
20.5610
Speaker
N
40
41
Std. Deviation
4.0761
5.6659
Third behavior
score
21.0108
93
13.6990
20.3827
81
16.5042
22.3407
91
14.5528
21.2755
265
14.8593
Fourth Behavior
Score
21.0610
82
14.5070
21.3409
88
14.6867
2 1.0274
73
11.6571
21.1523
243
13.7272
First Behavior
Score
32.5366
41
14.3859
16.8462
52
11.8989
23.7634
93
15.1596
25.5366
41
16.1340
103
Table F5, continued
Female
Total
Control
Male
Female
Total
Total
Male
Female
Total
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
7.6667
51
3.4039
8.4615
17.7885
52
6.1144
19.0108
21.1961
51
19.5 152
12.3029
23.1304
92
14.2229
19.7273
33
5.7507
16.8033
15.1106
21.4098
91
93
3.8015
8.3030
33
3.6270
7.5246
6.0496
33
61
61
61
3.6497
7.7979
5.4523
17.7553
94
5.6790
19.9826
14.1414
20.8191
94
14.4304
26.3652
94
3.6414
9.3246
114
115
115
3.7262
7.4024
5.4932
15.9607
19.8963
17.7091
164
165
3.4405
8.1906
278
3.6779
5.6923
18.6429
280
5.7124
164
12.9883
22.5627
279
14.6133
Table F6
Means and Standard Deviations for the Second Survey by Group by Gender
Group
Gender
Second Att itude Second Knowledge Second Behavior
Score
Score
Score
Alcohol 101
Male
Mean
9.8636
19.2500
28.6136
N
44
44
44
Std. Deviation
3.5932
6.8442
15.1875
Female
Mean
7.2400
19.1400
16.5400
N
50
50
50
Std. Deviation
3.1852
6.1644
10.8651
Total
Mean
8.4681
19.1915
22.1915
N
94
94
94
Std. Deviation
3.6121
14.3364
6.4563
Motivational
Male
Mean
9.2667
19.3043
25.5652
Speaker
N
45
46
46
Std. Deviation
3.7983
7.4442
18.8770
Female
Mean
7.9655
19.7966
19.6271
N
58
59
59
Std. Deviation
3.0606
5.1050
12.3622
Total
Mean
8.5340
19.5810
22.2286
N
103
105
105
Std. Deviation
3.4466
6.2107
15.7537
Control
Male
Mean
9.1515
21.4848
21.5758
N
33
33
33
Std. Deviation
3.5979
5.3626
14.3 135
Female
Mean
7.7778
20.0317
23.3016
104
Table F6, Continued
Total
Total
Male
Female
Total
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
63
3.57 16
8.2500
63
4.6593
96
3.62 16
20.53 13
96
4.933 1
9.4508
19.8699
Motivational
Speaker
Male
Female
Total
Control
Male
Female
Total
Total
Male
Female
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
22.7083
96
15.6043
25.5854
122
123
123
3.6547
7.6842
6.7423
19.6919
16.5569
20.0756
171
172
172
3.2872
8.4198
293
3.5478
5.2664
13.7760
22.3729
295
15.2165
19.7661
295
5.9163
Table F7
Means and Standard Deviations for the Third Survey by Group by Gender
Group
Gender
Third attitude score Third knowledge
score
Alcohol 101
Male
Mean
9.2927
21.2439
N
41
41
Std. Deviation
3.3034
5.6071
Female
Mean
6.8462
18.5385
N
52
52
Std. Deviation
3.2502
6.5782
Total
Mean
7.9247
19.7312
N
Std. Deviation
Mean
63
16.3 190
Third behavior
score
26.9512
41
15.1393
16.3269
52
10.3937
21.0108
93
93
93
3.4774
9.2414
6.2834
20.0000
13.6990
23.3448
29
4.1718
7.4800
29
5.6379
19.1731
50
52
29
20.4665
18.7308
52
3.5239
8.1266
5.4114
19.4691
20.3827
13.7671
79
81
81
3.8443
9.1667
30
5.4729
22.2903
3.93 12
5.6462
20.1967
16.5042
21.5000
30
14.3569
22.7541
7.9016
31
61
61
61
3.5105
8.3187
5.0722
20.9022
92
14.7486
22.3407
5.335 1
14.5528
24.2700
91
3.68 14
91
9.2400
21.2079
100
3.7230
7.4356
101
5 .6415
19.3515
16.6435
19.4606
163
165
165
100
105
Table F7, Continued
Total
Std. Deviation
Mean
N
Std. Deviation
3.4409
8.1217
263
3.6508
5.6975
20.0564
266
21.2755
265
5.7371
14.8593
13.3953
Table F8
Means and Standasd Deviations for the Fourth Survey by Group by Gender
Group
Gender
Fourth Attitude Fourth Knowledge Fourth Behavior
Score
Score
Score
Alcohol 101
Male
Mean
20.5806
29.0000
10.5000
N
31
32
33
Std. Deviation
4.7524
15.0416
3.4078
Female
Mean
20.5333
15.7143
8.0426
45
N
49
47
Std. Deviation
5.3919
11.4801
3.0995
Total
Mean
20.5526
21.0610
9.0380
N
76
82
79
Std. Deviation
5.1079
14.5070
3.4285
Motivational
Male
Mean
19.3438
23.5882
9.0909
Speaker
N
34
32
33
Std. Deviation
4.1334
7.3248
16.5897
Female
Mean
19.3333
19.9259
8.7963
N
54
54
54
Std. Deviation
5.3518
13.3202
3.7837
Total
Mean
19.3372
21.3409
8.9080
N
86
88
87
Std. Deviation
6.1177
14.6867
3.8988
Control
Male
Mean
21.7143
10.3333
21.0500
N
21
21
20
Std. Deviation
5.6493
10.6201
3.7193
Female
Mean
8.8302
20.2642
21.0189
N
53
53
53
Std. Deviation
3.3497
3.7424
12.1220
Total
Mean
9.2568
20.6757
21.0274
N
74
74
73
Std. Deviation
3.4997
4.3765
11.6571
Total
Male
Mean
25.0575
9.9186
20.3929
N
84
87
86
Std. Deviation
15.0088
3.7892
6.0640
Female
Mean
18.9744
20.0132
8.5779
N
154
152
156
Std. Deviation
12.4853
3.4334
4.8596
Total
Mean
20.1483
21.1523
9.0583
N
243
240
236
Std. Deviation
5.3099
13.7272
3.6149
106
Table F9
Means and Standard Deviations for the First Survey by Groun by Ae
Group
Age
First Attitude Score First Knowledge
Score
Alcohol 101
18.00
Mean
9.2857
18.0714
19.00
20.00
21.00
22.00
23.00
Total
Motivational
Speaker
18.00
19.00
20.00
21.00
22.00
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Control
Std. Deviation
23.00
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
18.00
Mean
N
Std. Deviation
19.00
Mean
First Behavior
Score
29.0714
14
14
14
3.4065
7.2353
5.9286
13.7363
20.2941
18.2941
17
17
17
3.4009
7.9565
23
4.0168
8.8125
6.7894
19.4783
23
5.6558
19.5000
13.4618
24.5652
23
17.4299
25.1875
16
16
16
3.2704
10.2222
3.8123
18.5556
15.3589
26.2222
9
9
9
2.2236
7.2500
4
5.1235
8.4096
6.6916
20.5000
4
2.3805
12.4778
27.2500
4
19.8893
24.8795
83
18.95 18
83
3.5717
8.7059
5.5566
17.5000
83
15.0822
21.5000
17
18
18
4.4408
9.7333
6.4739
19.2667
13.7467
28.0714
15
15
14
3.8631
8.3182
22
3.9567
7.5714
4.1139
18.4348
15.8525
24.4348
23
14.8472
21.5000
23
6.8545
19.2857
14
14
14
2.7376
9.0000
7.4568
22.0000
4
2.8284
22.5000
2
3.5355
18.8289
76
6.1653
16.7917
24
5.0818
16.0625
11.7653
32.2500
4
18.7861
23.0000
2
4.2426
24.2400
75
14.1954
21.0833
24
15.3053
24.4375
4
.8165
11.0000
2
5.6569
8.6622
74
3.7609
7.7083
24
3.7819
8.6250
107
Table F9. Continued
20.00
21.00
22.00
23.00
Total
Total
18.00
19.00
20.00
21.00
22.00
23.00
Total
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
16
16
16
4.1932
8.2000
20
4.3842
8.1333
5.3225
18.4500
20
14.2078
19.6500
20
13.7008
22.4667
6.525 1
19.4000
15
15
15
3.0907
6.5455
4.8374
19.5455
14.85 10
11
11
11
2.1149
7.6667
5.3172
10.6667
14.2408
10.3333
22.0000
3
3
3
1.1547
7.9101
89
3.6483
5.1316
17.6067
89
5.6339
17.3393
56
5.6866
17.8542
48
5.6191
18.8030
66
6.2787
19.4000
45
5.3700
19.5833
24
5.5082
17.6667
1.5275
21.3483
89
8.4182
55
3.8953
8.4792
48
3.8812
8.1538
65
4.05 14
8.2000
45
3.0271
8.3333
24
2.5988
8.2222
9
9
4.0859
8.3049
246
3.6557
6.2048
Table FlO
Means and Standard Deviations for the Second Surve
Group
Age
Second Au itude
Score
Alcohol 101
18.00
Mean
9.2500
N
12
Std. Deviation
2.8002
19.00
Mean
7.5500
N
20
Std. Deviation
3.7343
20.00
Mean
8.4545
N
22
Std. Deviation
3.6610
18.43 15
248
5.7866
14.183 1
23.2143
56
14.5823
24.0213
47
14.4936
23.0303
66
15.4063
23.1333
45
13.9294
25.2917
24
14.2233
20.6667
9
14.6373
23.4130
247
14.52 16
Second Knowledge Second Behavior
Score
Score
18.6667
26.0833
12
12
7.4019
18.4500
20
6.3285
19.2273
22
6.0705
14.0548
20.7500
20
16.7705
22.8182
22
14.9145
108
Table F 10. Continued
21.00
22.00
23.00
Total
Motivational
Speaker
18.00
19.00
20.00
21.00
22.00
23.00
Total
Control
18.00
19.00
20.00
21.00
22.00
23.00
Total
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
23.3750
8.6250
18.6250
16
16
16
3.5379
9.7778
7.2007
18.7778
12.8056
23.5556
9
9
8.3333
21.7500
4
1.7078
18.9157
2.7285
7.7500
4
4.7170
8.4940
9
10.8641
23.2500
4
16.1735
23.0000
83
83
83
3.4724
7.7619
6.5522
17.8182
14.2272
21.8636
21
3.9231
9.3333
22
7.0213
21.2105
22
14.9293
18
19
19
3.6299
8.3750
24
5.6133
18.9583
24
5.3850
20.7143
18.0138
21.7500
24
18.3830
22.7857
14
10.032 1
3.28 12
8.2857
28.9474
14
14
2.3996
10.3750
7.1836
20.5000
8
8
8
4.6579
8.0000
7.5593
21.0000
12.9222
12.0000
2
2
1.4142
19.6180
89
6.3057
19.2692
7.0711
8.5862
87
3.5912
8.3462
26
3.3934
9.3529
26
4.7544
18.3529
17.8750
2
.0000
22.9101
89
15.7975
23.0000
26
17.165 1
24.7059
17
17
17
3.9519
8.6818
22
3.8345
7.8000
4.4150
21.8182
22
4.3822
21.6667
15.0448
22.5909
22
16.0614
22.7333
15
15
15
3.7071
7.1111
5.5119
23.0000
15.4941
9
9
9
2.6667
7.0000
4.8477
13.5000
7.4181
12.0000
2
2
.7071
2.8284
8.3736
20.3516
25.4444
2
.0000
23.1758
Table FlO, Continued
Total
18.00
19.00
20.00
21.00
22.00
23.00
Total
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
91
91
91
3.5673
8.3220
59
3.4713
8.6909
4.9696
18.6167
60
6.1454
15.1119
23.2000
60
15.6007
24.7321
56
16.7663
22.3676
68
16.3341
22.9778
45
12.7324
22.4615
26
10.6065
17.6250
68
19.3571
56
5.6228
19.9706
68
3.5387
8.2444
20.2889
55
3.8000
8.5000
5.403 1
45
45
3.2344
9.0385
26
6.6559
20.7692
26
6.9989
19.5000
3.583 1
7.6250
8
8
8
4.2405
8.4828
261
3.5329
3.9279
19.6502
263
5.9681
12.1765
Table Fl 1
Means and Standard Deviations for the Third Survey by Group by Age
Group
Age
Third attitude score Third knowledge
score
Alcohol 101
18.00
19.00
20.00
21.00
22.00
23.00
Total
Motivational
Speaker
18.00
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
9.1429
19.4286
23.0304
263
15.0211
Third behavior
score
25.2857
14
14
14
3.7796
7.1579
5.4591
13.6688
21.0000
20.5789
19
19
19
3.4361
7.7143
7.0263
18.7619
14.9666
23.4762
21
3.5234
8.4118
21
7.5 160
21
16.2561
20.2353
21.5882
17
17
17
3.2027
8.3333
4.3808
17.8333
13.1437
19.3333
6
3.0111
6.6000
6
6
9.4534
20.2000
8.8468
15.2000
5
5
5
4.0988
7.9512
7.0852
19.6220
6.8337
22.0122
82
82
3.4602
8.9091
6.4991
19.7273
82
13.8693
19.2727
11
11
11
110
Table Fil. Continued
19.00
20.00
21.00
22.00
23.00
Total
Control
18.00
19.00
20.00
21.00
22.00
23.00
Total
Total
18.00
19.00
20.00
21.00
22.00
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
3.7271
8.8750
4.3610
21.0000
14.7993
27.5000
16
16
16
3.7572
7.4500
20
4.3100
8.7857
4.1952
19.5909
22
5.7210
23 .4464
19.3636
22
16.8595
19.3571
24.2143
14
14
14
2.4862
10.6667
5.8652
15.0000
12.8253
16.0000
3
3
3
2.0817
7.5000
9.1652
22.0000
11.1355
16.5000
2
2
1.4 142
7.7782
8.4697
66
3.7137
9.0000
26
3.4525
8.6000
15
4.256 1
8.7368
19
4.0803
8.0000
19.7647
68
5.2749
20.5769
26
5.2928
19.5333
15
5.083 1
21.5500
20
4.9997
21.7857
2
3.5355
22.0294
68
17.1734
26.4000
25
18.0 139
21.0667
15
10.6467
20.0500
20
12.9634
22.8571
14
14
14
3.7622
7.2222
6.6469
23.0000
14.9967
25.7778
9
9
9
3.3082
7.0000
4.1231
13.0000
6.8698
11.0000
2
2
2.8284
8.4706
1.4 142
2
1.4142
20.8953
22.9529
85
3.7 180
86
5.3841
9.0196
20.0784
51
51
3.5298
8.1400
5.0827
20.4000
50
5.5915
19.9365
50
3.8012
7.9500
60
3.9464
8.4000
85
14.1202
24.5200
50
16.1665
23.1000
50
17.0955
20.9524
63
63
6.1902
20.4444
3.1363
8.1667
45
5.5823
19.9444
15.3732
22.8000
45
13.3818
22.0000
18
18
18
45
111
Table Fl!, Continued
23.00
Total
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
3.1483
6.8889
7.4 160
8.73 13
19.0000
14.5556
9
9
9
4.1366
8.2876
6.1441
20.1271
233
236
5.7723
5.4339
22.3574
235
14.9266
3.6209
Table F12
Means and Standard Deviations for the Fourth Survey by Group by Age
Group
Age
Fourth Knowledge Fourth Behavior
Fourth Attitude
Score
Score
Score
Alcohol 101
18.00
Mean
10.3636
18.3636
25.7273
N
11
11
11
Std. Deviation
2.1574
4.2255
14.0221
19.00
Mean
18.8125
19.7647
8.8750
N
16
17
16
Std. Deviation
3.6674
3.9870
15.7024
20.00
Mean
20.7222
8.7647
22.7500
N
17
16
18
Std. Deviation
5.8481
16.7395
3.7338
21.00
Mean
9.4000
22.3077
23.4000
N
13
15
15
Std. Deviation
4.3853
12.6875
2.6939
22.00
Mean
24.7143
10.1429
23.3333
N
7
6
7
Std. Deviation
15.6068
4.4 132
3.5024
23.00
Mean
16.6667
22.3333
10.0000
N
2
3
3
Std. Deviation
1.4142
11.1505
7.7675
Total
Mean
20.723 1
22.2958
9.3676
N
65
71
68
Std. Deviation
3.2732
5.2723
14.5665
Motivational
18.00
Mean
18.6250
19.3125
8.5333
Speaker
N
15
16
16
Std. Deviation
3.7960
7.3292
11.8249
19.00
Mean
10.3333
19.6000
28.4667
N
15
15
15
Std. Deviation
4.8648
4.8226
2 1.2867
20.00
Mean
8.6667
19.9444
22.5556
N
18
18
18
Std. Deviation
3.8957
6.1498
14.7018
21.00
Mean
19.2000
9.4667
22.7333
N
15
15
15
Std. Deviation
6.6246
13.2959
2.7482
22.00
Mean
11.3333
14.0000
21.5000
N
6
6
6
Std. Deviation
7.3485
12.0955
3.6 148
23.00
Mean
11.0000
3.0000
25.0000
N
1
1
1
Std. Deviation
.
.
112
Table F12. Continued
Total
Control
18.00
19.00
20.00
21.00
22.00
23.00
Total
Total
18.00
19.00
20.00
21.00
22.00
23.00
Total
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
22.8592
9.3143
70
18.9859
71
71
3.9 178
6.4020
21.8333
15.1886
20.8889
9.7222
18
18
18
3.3573
8.4545
4.0037
19.0909
14.9544
21.3636
11
11
11
3.9335
9.4737
4.7213
22.2105
12.5720
20.2632
19
19
19
3.5803
9.1818
3.3263
18.9091
9.3502
22.1000
11
11
10
4.423 1
5.6649
20.5556
7.5785
22.3333
8.8889
9
9
9
3.5158
8.5000
3.7786
17.5000
2
4.9497
20.7571
70
4.3487
19.8444
45
5.5920
19.1667
42
4.3947
21.6038
13.7204
16.0000
2
5.6569
21.0145
69
11.5688
21.5111
45
13.6059
23.2093
43
17.2676
21.1636
55
13.6528
22.8250
40
11.6088
22.8636
22
13.3391
18.3333
2
.7071
9.2286
70
3.5841
9.4773
44
3.2813
9.2857
42
4.1748
8.9815
54
53
3.6832
9.3659
5.2490
20.1538
39
5.7516
19.4762
41
3.1761
9.9545
22
3.7982
8.0000
5
3.0000
9.3029
208
3.5874
21
6.0218
18.3333
6
8.0911
20.1359
206
5.4532
6
7.2847
22.0664
211
13.8404
113
Table F13
Means and Standard Deviations for the First Survey by Grade Point Average
Group
Grade Point
First Attitude First Knowledge First Behavior
Average
Score
Score
Score
Alcohol 101
1.25
23.0000
49.5000
Mean
12.5000
2.0
2.5
3.0
3.5
Total
Motivational
Speaker
1.25
2.0
2.5
3.0
3.5
Total
Control
1.25
2.0
2.5
3.0
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
2
.7071
9.8000
2
2
2.8284
20.6000
26.1630
37.8000
5
5
5
3.1145
8.6400
25
2.9422
8.4211
4.2778
18.8000
7.563 1
25
4.9666
20.3684
26.2000
25
14.0119
23.3158
19
19
19
3.6865
7.0833
3.7448
17.7500
11.6240
20.0000
12
12
12
4.3788
8.4921
7.3 128
19.3492
15.4390
25.8095
63
3.5 189
63
63
5.0900
7.0000
2 1.3333
14.5068
29.3333
2
.0000
9.3750
3
3
2.5 166
10.9697
21.2500
16.2500
8
8
8
3.0677
8.8333
6.0886
18.3889
13.1230
26.8235
18
18
17
4.0620
8.8400
25
3.6706
8.7143
7.1795
19.6800
25
5.6842
20.4286
14.1122
26.1600
25
15.9522
17.7143
7
7
7
3.7733
8.8333
60
3.5993
10.0000
6.6797
19.0164
6.1927
10.0000
8.8452
24.8667
60
14.1654
49.0000
1
1
1
9.5455
18.5455
32.2727
11
11
11
3.7779
8.6429
3.8305
16.8571
14.2484
26.6429
61
.
14
14
14
2.9511
8.2000
4.5380
19.4400
12.2009
19.9600
114
Table F13. Continued
3.5
4.0
Total
Total
1.25
2.0
2.5
3.0
3.5
4.0
Total
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
25
2.8137
4.9167
25
5.9587
17.0000
25
11.8338
11.0833
12
12
12
3.7769
5.0000
7.1351
21.0000
8.7330
13.0000
1
1
1
7.8906
64
3.4784
9.8000
18.1406
64
22.2 187
64
13.7834
20.0000
5
6
2.7749
9.5417
24
3.2834
8.7018
57
3.2785
8.4928
69
3.3503
6.6129
5.3666
18.2083
24
4.8453
18.1930
57
5.6234
19.7826
69
5.2716
18.0645
5.61 14
39.3333
6
17.4662
29.7500
24
13.8885
26.5000
56
13.3743
23.1304
69
13.4939
16.0323
31
31
31
4.1688
5.0000
6.9997
21.0000
12.1559
13.0000
1
1
1
8.3957
18.8298
187
188
24.278 1
187
3.5338
5.6363
14.1603
Table F14
Means and Standard Deviations for the Second Survey by Group by Grade Point Average
Group
Grade Point
Second
Second Att itude
Second
Average
Knowledge Score Behavior Score
Score
Alcohol 101
1.25
30.0000
Mean
12.0000
22.0000
2.0
2.5
3.0
3.5
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
1
1
.
10.8333
6
2.4833
8.4167
24
18.6667
6
8. 1404
40.8333
6
2.8880
8.9500
20
2.8924
7.5333
18.9167
24
5.7250
19.5500
20
6.6052
19.4667
14.2045
24.1667
24
11.2353
23.8500
20
13.9860
18.4000
15
15
15
115
Table F14, Continued
Total
Motivational
Speaker
2.0
2.5
3.0
3.5
Total
Control
1.25
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
2.0
2.5
3.0
3.5
4.0
Total
Total
1.25
2.0
2.5
3.0
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
4.8531
8.65 15
66
3.4485
11.2727
6.9268
19.2576
66
6.3253
15.9 167
16.1723
24.3636
66
14.4058
23.3333
11
12
12
3.7441
8.3750
7.4157
19.6250
14.3675
24.1875
16
16
16
3.4230
8.7857
28
3.0835
7.7692
4.8836
21.5357
28
6.1673
20.6154
16.2408
25.0000
28
18.7557
18.8462
13
13
13
3.2 185
4.6822
19.9420
8.8971
68
3.4126
9.0000
69
6.0946
24.0000
9.6596
23.3623
69
15.9022
28.0000
1
1
1
10.0909
22.5455
3 1.5455
11
11
11
3.5904
9.6000
3.1421
19.6667
13.3069
30.5333
.
15
15
15
3.0892
8.3750
24
2.6835
4.6085
21.4583
24
5.1498
14.8894
24.1667
24
14.6574
5.5385
20.0000
11.4615
13
13
13
3.4063
2.0000
6.1101
21.0000
8.9220
14.0000
1
1
1
20.9692
24.2462
.
8.2923
65
3.4629
10.5000
65
65
4.8957
23.0000
14.8924
29.0000
2
2
2
2.1213
10.7143
28
3.3759
8.7273
1.4142
19.0000
29
6.7823
19.3273
55
5.1210
20.9583
72
5.9586
1.4142
30.0690
29
15.0165
25.9091
55
3.0939
8.6944
72
2.8711
55
13.8808
24.4028
72
15.9988
116
Table F14, Continued
3.5
4.0
Total
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
16.3415
6.9756
20.0000
41
41
41
3.9780
2.0000
5.8992
21.0000
12.4411
14.0000
1
1
1
8.6181
199
3.4326
20.0500
200
5.8273
23.9800
200
15.0243
Table F15
Means and Standard Deviations for the Third Survey by Group by Grade Point Average
Group
Grade Point
Third attitude Third knowledge Third behavior
Average
score
score
score
Alcohol 101
1.25
30.0000
Mean
12.0000
6.0000
1
1
1
N
Std. Deviation
2.0
36.0000
Mean
10.4444
20.5556
9
9
N
9
19.2808
5.7033
Std. Deviation
2.3511
2.5
20.9167
Mean
20.1250
7.7083
24
24
N
24
11.3594
Std. Deviation
2.9559
6.5230
3.0
20.4211
19.6842
Mean
7.7368
19
19
N
19
11.0758
Std. Deviation
3.2118
4.7530
3.5
18.1538
Mean
6.5385
19.6154
13
13
N
13
13.4774
Std. Deviation
4.1556
6.7273
Total
22.2121
Mean
7.9242
19.9545
N
66
66
66
13.8548
Std. Deviation
3.3710
6.0674
Motivational
1.25
Mean
7.0000
41.0000
Speaker
1
1
N
Std. Deviation
2.0
Mean
22.1429
20.1429
9.4286
N
7
7
7
Std. Deviation
2.9921
2.2678
2 1.3263
2.5
Mean
8.5000
18.0769
19.3077
13
13
N
12
10.8119
Std. Deviation
3.6556
5.0409
3.0
19.8519
24.4074
Mean
8.5185
27
27
N
27
Std. Deviation
3.7042
5.6207
16.0438
3.5
20.8333
21.2500
Mean
7.5833
N
12
12
12
Std. Deviation
2.9683
5.1669
23.293 1
Total
Mean
8.43 10
19.7167
22.4500
60
N
58
60
17.1844
Std. Deviation
3.4290
5.3744
Control
1.25
Mean
26.0000
27.0000
8.0000
117
Table Fl 5. Continued
2.0
2.5
3.0
3.5
4.0
Total
Total
1.25
2.0
2.5
3.0
3.5
4.0
Total
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
1
1
1
10.9091
22.1818
31.4545
11
11
11
3.6730
9.1818
3.6005
19.1667
11.8606
28.9167
11
12
12
3.1565
8.2609
5.1139
21.9130
10.3173
23
23
3.0632
5.2500
5.6722
20.6667
22.1739
23
13.5903
12.5000
12
12
12
3.3063
5.0000
6.5690
23.0000
8.1296
14.0000
1
1
1
21.2500
23.2333
60
13.0233
32.6667
.
8.2542
59
3.6369
10.0000
60
5.3698
13.0000
2
3
3
2.8284
10.3704
27
3.0527
8.2553
47
3.1792
8.2174
69
3.3337
6.4595
37
3.5637
5.0000
11.2694
7.3711
30.0370
27
17.6907
21.6296
27
4.0964
19.3469
49
5.7863
20.6957
69
5.4 105
22.4490
49
11.3909
22.3623
69
13.9400
6.0609
23.0000
17.3243
37
16.1143
14.0000
I
1
1
.
.
8.1913
20.2957
22.6183
183
186
5.6381
14.6936
3.4643
20.3514
37
186
118
Table F16
Means and Standard Deviations for the Fourth Survey by Group by Grade Point Average
Group
Grade Point
Fourth
Fourth Attitude
Fourth
Average
Knowledge Score Behavior Score
Score
Alcohol 101
1.25
20.0000
Mean
9.0000
21.0000
1
1
1
N
Std. Deviation
2.0
50.4000
Mean
13.8000
21.2500
4
N
5
5
11.2827
Std. Deviation
3.0332
5.9090
2.5
20.2381
9.3500
20.9000
Mean
21
N
20
20
12.1857
Std. Deviation
2.7773
5.6186
3.0
19.3529
Mean
9.0667
21.2500
16
17
N
15
10.6239
Std. Deviation
2.9873
5.5558
3.5
17.6667
Mean
8.2500
20.0000
12
12
12
N
3.7447
13.2893
Std. Deviation
6.3960
Total
22.1071
Mean
9.4340
20.8302
53
53
56
N
3.3311
14.5686
Std. Deviation
5.5979
Motivational
2.0
23.5556
Mean
9.5556
17.7778
Speaker
N
9
9
9
9.043 1
Std. Deviation
2.65 10
8.9969
2.5
9.8667
17.4000
26.6667
Mean
15
N
15
15
17.89 12
Std. Deviation
3.7007
6.9980
3.0
25.0417
Mean
10.0833
19.5417
24
N
24
24
Std. Deviation
4.2927
5.19 18
17.8386
3.5
15.8000
Mean
8.0000
22.2000
10
N
10
10
9.0406
Std. Deviation
4.0277
3.2249
Total
9.5862
19.1724
23.6379
Mean
58
N
58
58
15.6661
Std. Deviation
3.8618
6.2215
Control
2.0
25.4286
Mean
9.1429
21.5714
N
7
7
7
1.7728
2.9358
9.4843
Std. Deviation
2.5
Mean
10.2308
20.8462
27.0000
13
13
13
N
11.0000
Std. Deviation
2.0878
4.2 199
3.0
9.5909
20.2727
19.0000
Mean
21
N
22
22
Std. Deviation
3.6340
5.0632
8.8769
3.5
Mean
7.4444
19.0000
15.3333
N
9
9
9
Std. Deviation
4.9018
4.7697
8.1854
4.0
14.0000
Mean
1.0000
22.0000
119
Table F16. Continued
Total
Total
1.25
2.0
2.5
3.0
3.5
4.0
Total
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
Table F17
Means and Standard Deviations for the First Survei
Group
Religion
Alcohol101
RomanCatholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
1
1
1
9.1538
20.4038
21.1765
52
3.5776
9.0000
52
51
4.4689
21.0000
10.1286
20.0000
1
1
1
10.4286
19.8000
20
6.7715
19.7917
48
5.8780
20.2419
62
5.1999
20.4194
30.5714
21
3.0589
9.7500
48
2.9063
9.6557
61
3.7322
7.9355
31
21
14.6580
24.0000
49
14.0119
21.4355
62
13.5569
16.3871
31
4.0656
31
5.09 10
1.0000
22.0000
10.4041
14.0000
1
1
1
9.3988
20.1043
22.3576
163
163
165
3.5876
5.5206
13.7402
First Attitude
Score
8.6857
First Knowledge First Behavior
Score
Score
28.1143
18.057l
35
35
35
2.8156
7.8000
4.3585
20.0000
14.1 167
5
5
5
2.7749
3.7417
20.0000
5.5408
8.739 1
20.8000
20.39 13
23
23
23
4.1034
8.3333
5.9084
16.6667
12.7198
34.6667
3
3
3
4.0415
7.1250
11.1505
19.6875
34.0196
23.1250
16
16
6.935 1
17.4 122
4.2091
8.3293
82
3.5173
18.9878
82
5.5810
16
24.7683
82
15.1407
120
Table F 17. Continued
Motivational
Speaker
Control
Total
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
Noneorother
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
9.1290
18.12 12
26.5455
31
33
33
3.9978
6.0000
5.8457
14.3333
14.1997
21.3333
3
3
3
7.0000
8.0588
10.2632
19.7647
22.3681
2 1.3750
17
17
16
3.2301
7.0000
7.1198
21.5000
13.2105
16.0000
2
2
2
1.4142
8.5882
6.3640
19.4118
4.2426
21.2353
17
17
17
3.7426
8.5429
14.7798
23.5915
3.8247
8.3182
44
3.6138
8.0000
5.4893
18.7500
72
6.2230
16.3182
44
5.6229
10.0000
1
1
1
20.3846
18.7692
70
71
14.2303
23.1364
44
15.4598
24.0000
.
6.8462
13
13
13
3.8481
9.3333
6.0489
22.6667
13.8874
25.3333
3
3
3
5.6862
7.6364
22
3.6193
7.9398
3.2 146
10.5987
20.9545
22
13.2215
21.9639
18.4545
22
5.0495
17.6747
83
83
83
3.6771
8.6636
5.7150
17.3929
14.2884
25.6964
110
112
112
3.4833
7.2222
5.3547
17.0000
14.7109
21.3333
9
9
6.9101
20.0 189
11.8954
20.2885
4.1164
8.0566
53
53
3.7847
6.2342
9
52
12.9408
121
Table Fl 7. Continued
Protestant (does
not allow
drinking)
Noneorother
Total
20.1250
26.5000
Mean
8.3750
N
Std. Deviation
Mean
N
Std. Deviation
Mean
N
Std. Deviation
8
8
8
3.8891
7.7818
55
3.8088
8.2553
235
3.6601
7.2592
20.6398
21.6727
19.1091
55
5.7014
18.4557
237
5.8334
55
14.7586
23.4280
236
14.5590
Table Fl8
Means and Standard Deviations for the Second Survey by Group by Religion
Group
Religion
Second
Second
Second Att itude
Knowledge Score Behavior Score
Score
Alcohol101
RomanCatholic
Mean
17.1429
27.2571
9.1143
35
N
35
35
Std. Deviation
5.6524
14.6113
3.1227
Jewish
22.0000
Mean
22.8000
7.8000
N
5
5
5
3.2404
Std. Deviation
2.2804
4.5497
Protestant (allows
20.8333
Mean
19.4583
8.7083
drinking)
Motivational
Speaker
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
24
3.5445
6.7500
24
6.2252
16.5000
24
11.4853
14.0000
4
4.1130
6.9286
4
8.8506
20.3571
4
16.2481
14
14
14
3.9509
8.4268
82
3.4392
8.9524
7.3653
19.0854
17.1054
22.7927
82
82
14.1881
42
3.8947
6.3333
6.4064
19.3023
43
6.5339
18.3333
20.1429
25.1395
43
17.1764
19.6667
3
3
3
4.0415
4.7258
20.0000
24.5425
21.1111
8.1111
18
18
18
2.7416
8.0000
5.6464
27.0000
13.5555
19.0000
3
3
3
122
Table F18. Continued
Std. Deviation
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
None or other
Control
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Total
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
1.0000
8.4118
1.7321
19.0000
6.5574
19.3333
17
18
18
4.1692
8.5301
6.8599
19.6235
14.9863
22.6471
83
85
85
3.6437
8.3556
45
3.5685
8.0000
6.3320
19.1778
45
5.5115
14.0000
15.8855
24.1333
45
16.1816
1
1
1
7.6667
22.9333
20.9333
22.0000
15
15
15
3.8483
10.3333
4.0790
22.3333
17.7622
25.0000
3
3
3
2.0817
8.4348
1.5275
20.52 17
23
14.7986
23.0435
4.1327
20.2299
13.4620
23.2989
87
15.4356
25.3740
23
3.7998
8.3218
87
3.5975
8.7787
87
5.0156
18.6423
23
122
123
123
3.5525
7.3333
5.9549
20.3333
9
9
2.6926
8.2456
5.1235
21.1228
16.0345
21.2222
9
12.5377
20.3684
57
3.3662
8.2000
57
5.5744
21.4000
57
13.7641
18.8000
10
10
10
3.0478
8.0370
54
3.9380
8.4246
252
6.9793
19.9818
13.0111
3.5491
55
5.9426
19.6575
254
5.9348
21.0909
55
14.7601
22.9173
254
15.1427
123
Table F19
Means and Standard Deviations for the Third Survey by Groun by Relinion
Group
Religion
Third attitude Third knowledge Third behavior
Alcohol 101
Motivational
Speaker
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
Noneorother
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
None or other
Total
Roman Catholic
Jewish
score
score
19.5000
34
5.2063
2 1.0000
23.3529
34
13.3890
22.2000
5
5
5
3.3615
8.2727
4.9497
20.7727
11.3666
2 1.0909
22
3.7945
8.3333
22
5.5885
14.3333
22
11.3344
18.0000
3
3
3
4.04 15
10.4083
18.7059
19.0788
19.1765
7.4118
17
17
17
4.0936
7.8765
9.3793
19.5802
16.3983
81
81
81
3.4 146
8.843 8
6.5285
19.2424
13.42 18
21.5926
24.4848
32
33
33
3.7855
10.0000
2
5.6569
5.7229
14.5000
2
7.7782
21.7692
19.7280
28.5000
2
24.7487
19.6923
6.923 1
13
13
13
3.4025
6.3333
2.3507
24.0000
14.9632
8.6667
N
3
3
3
Std. Deviation
Mean
N
Std. Deviation
Mean
3.055 1
3.6056
18.5385
7.5719
17.0769
N
Control
score
8.0294
34
2.8336
6.4000
Std. Deviation
Mean
N
Std. Deviation
Mean
8.6667
12
13
13
4.0973
8.3226
62
3.7799
8.5349
6.0775
19.6875
64
12.0448
5.395 1
19.3256
43
43
3.4527
8.0000
6.2516
14.0000
21.3906
64
17.2706
24.3023
43
14.8813
24.000a
124
Table Fl 9. Continued
Total
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
1
1
1
7.9231
23.7692
16.2308
13
13
13
4.0919
13.0000
4.3235
24.3333
11.0314
30.6667
3
3
3
4.3589
7.8571
4.0415
21.7727
22
3.2650
20.8049
19.8578
22.8571
21
3.9785
8.4198
21
14.6297
22.8642
81
82
81
3.7579
8.4679
5.4827
19.3545
14.4376
24.0636
109
110
5.735 1
3.3626
7.5000
18.5000
110
15.9404
24.0000
8
8
8
3.7033
5.8797
7.8 125
2 1.8542
13.0165
19.3958
48
3.7397
9.2222
48
4.6585
20.8889
48
12.2383
19.1111
9
9
4.4659
7.9000
50
3.9911
8.1964
224
3.6355
7.6558
19.9615
9
17.1861
20.1569
52
51
6.5678
20.0529
227
5.8565
14.5717
21.9912
226
14.9035
Table F20
Means and Standard Deviations for the Fourth Survey by Group by Religion
Group
Religion
Fourth Attitude
Fourth
Fourth
Score
Knowledge Score Behavior Score
Alcohol 101
Roman Catholic
Mean
9.7308
20.79 17
23333
26
N
24
27
Std. Deviation
3.0667
5.2913
12.0384
Jewish
Mean
7.1667
20.1667
16.3333
N
6
6
6
Std. Deviation
2.9269
5.3448
5.3 166
Protestant (allows
Mean
9.3810
21.1364
21.0000
drinking)
N
21
22
22
125
Table F20. Continued
Std. Deviation
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
None or other
Motivational
Speaker
Control
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
drinking)
N
Protestant (does
not allow
drinking)
Total
Std. Deviation
Mean
N
Std. Deviation
None or other
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
Roman Catholic
Mean
N
Std. Deviation
2.7835
9.2857
5. 1018
20.0000
13.0894
24.6667
14
12
15
4.2141
9.2985
67
3.2474
8.9655
6.2668
20.7031
21.1176
5.3 115
2 1.9000
70
14.2820
19.0690
23.2069
29
29
6.0882
9.0000
29
16.8298
11.0000
4.3 792
6.5000
2
2. 1213
9.8333
18
3.5 189
7.0000
64
3
3
7.0000
20.4444
10.5830
26.5000
18
18
5.8634
24.6667
16.0156
13.0000
3
3
3
3.6056
9.7143
4.0415
2.6458
17.7 143
14
19.857 1
14
10.6544
22.3881
67
15.1117
23.6667
9.0000
6.3298
18.9552
67
6.4325
19.4412
34
4.4463
14.0000
7.7273
21.7273
15.2727
11
11
11
3.9266
10.0000
3. 1966
8. 1865
25.6667
19.6667
14
3.85 16
9. 1970
66
3.9466
9.8235
34
3.3 164
33
11.7889
14.0000
3
3
3
2.6458
9.2500
4.0415
21.6250
9.5044
21.7500
16
16
16
3.7506
4.1932
20.5692
12.9897
21.4063
64
11.6001
23.1124
9.3231
65
65
3.4915
9.5169
89
3.6122
4.4158
19.6897
87
5.2569
89
13.5566
126
Table F20. Continued
Jewish
Mean
N
Std. Deviation
Protestant (allows
Mean
7.2222
16.2000
9
10
10
2.5386
9.1800
7.4207
21.0196
6.8516
21.7059
50
3.3545
8.5000
51
51
4.9900
25.1667
13.7903
16.3333
14.5000
drinking)
N
Std. Deviation
Protestant (does
Mean
not allow
drinking)
N
Std. Deviation
Noneorother
Mean
N
Std. Deviation
Total
Mean
N
Std. Deviation
6
6
6
3.2711
9.4091
3.6560
7.2296
22.1333
45
15.3898
21.9055
44
3.8478
9.2727
19.8571
42
5.6980
20.0612
198
196
3.5547
5.4918
Table F21
Means and Standard Deviations for the First Attitude and Behavior Scores by
Grade Point Average
Grade Point Average
First Attitude Score First Behavior Score
1.25
Mean
9.8000
39.3333
N
6
5
Std. Deviation
17.4662
2.7749
2.0
Mean
9.4615
28.6923
N
26
26
Std. Deviation
14.1217
3.1652
2.5
Mean
8.7937
25.8226
N
63
62
Std. Deviation
3.1885
13.4048
3.0
Mean
21.9241
8.3544
N
79
79
Std. Deviation
14.2 161
3.5084
3.5
Mean
6.3333
16.0256
N
39
39
Std. Deviation
12.2463
4.0415
4.0
Mean
10.0000
6.0000
N
5
5
Std. Deviation
4.0620
7.03 56
Total
Mean
22.9954
8.2304
N
217
217
Std. Deviation
14.4182
3.5981
201
13.7214
127
Appendix G
Institutional Review Board Applications and Approvals
INSTITUTIONAL REVIEW BOARD APPLICATION FOR HUMAN SUBJECTS RESEARCH AT
OREGON STATE UNIVERSITY
AN EVALUATION OF THE EFFECTS OF ALCOHOL EDUCATION PROGRAMS FOR COLLEGE
STUDENTS
1. SIGNIFICANCE OF THE RESEARCH
The purpose of this research is to evaluate the effectiveness of two different alcohol education programs
for college students a motivational speaker and the new "Alcohol 101" program that has been
developed by the Century CounciL The research will address alcohol abuse among university students
at the State University of New York at Potsdam. Specifically, the program will be evaluated through
four administrations of a survey during the Fall, 1999 semester.
2. METHODS AND PROCEDURES
Twelve classrooms at SUNY Potsdam that begin at 9:30 am on Tuesday, will be randomly selected for
the research. The unit of analysis will be these classrooms. Students in each class will be asked to
complete a 90 item survey four weeks after classes begin (September 21, 1999). The survey items cover
self-reported alcohol behavior, knowledge about alcohol and attitudes about alcohol.
In the week following the first administration of the survey, one third of the students (four classes) will
participate in the Alcohol 101 program, a computer based game that educates students about potential
hazards associated with alcohol consumption. Four other classes will attend a motivational speech
covering the same subjects as the Alcohol 101 program. The final four classes will be a control group
and will not take part in an intervention.
The survey will be re-administered three additional times during the Fall semester
four, eight and twelve weeks after the first administration of the survey.
approximately
3. A DESCRIPTION OF THE BENEFITS AND/OR RISKS TO THE SUBJECTS iNVOLVED IN
THIS RESEARCH.
No risks or immediate benefits to students are anticipated.
4. SUBJECT POPULATION AND METHOD OF SELECTION.
Subjects will be undergraduate students attending the State University of New York at Potsdam. They
will be selected based on a random selection of classrooms. Approximately 300 360 students will
participate in the research. Students under the age of 18 will be excluded from the research.
5. INFORMED CONSENT.
Please see enclosed.
6. METHODS FOR OBTAINING INFORMED CONSENT.
Classroom professors will be provided with the informed consent documents and will read the
document to the subjects before the research begins. Each subject will be provided with a copy of the
informed consent document.
128
7. METHODS FOR ANONYMITY
Students will be instructed orally by their professor and in writing on the survey that they are not to
put their names anywhere on the survey. For purposes of being able to match pre and post intervention
surveys, students will be asked to include the last six digits of their Social Security Numbers at the top
of the survey.
8. COPY OF THE QUESTIONNAIRE
Please see enclosed.
9. OTHER iNSTITUTIONAL REVIEW BOARD APPLICATIONS.
The IRB at SUNY Potsdam has approved the research.
129
INSTITUTiONAL REVIEW BOARD APPLICATION FOR HUMAN SUBJECTS RESEARCH AT
SUNY POTSDAM
1. TITLE
AN EVALUATION OF THE EFFECTS OF ALCOHOL EDUCATION PROGRAMS FOR
COLLEGE STUDENTS
2. STATEMENT OF PURPOSE OF THE RESEARCH
The purpose of this research is to evaluate the effectiveness of two education programs that address
alcohol use among university students at SUNY Potsdam. Specifically, the program will be evaluated
through four administrations of a survey in twelve classrooms during the Fall, 1999 semester.
3. COPY OF THE QUESTIONNAIRE
Please see enclosed.
4. PROVIDE A COPY OF THE iNFORMED CONSENT FORM
Please see enclosed. Students will be asked to read and sign the informed consent document prior to
completing the survey.
5. WHAT IS THEIR COMPETENCE TO CONSENT?
The audience that will be completing the questionnaire will be undergraduate college students.
6. VOLUNTARY PARTICIPATION
Students will be informed that completing the survey is completely voluntary.
7. ELEMENTARY AND HIGH SCHOOL STUDENT
Students will not be elementary or high school students.
8. ANONYMITY
No names will be used with the survey. Students will be asked to write the last six digits of their Social
Security Number at the top of each survey. This is for the purposes of matching pre and post
intervention surveys.
9. MAILED QUESTIONNAIRES
The survey will not be mailed.
10. ADMINISTRATION OF THE SURVEY.
Classroom professors will assist with the administration of the survey.
Students will be told that completion of the questionnaire is voluntary and that if they wish to
participate, they will be assisting with research dealing with health issues of college students.
130
11. NAMES OR OTHER IDENTIFIERS.
No names or other identifiers will be used on the survey. The survey will remind the students that they
should not include their names on it.
12. OTHER IDENTIFICATION.
It will not be possible to identif3 those completing the survey by any specific subgroup or other
classification to which they may belong.
131
State University of New York
College at Potsdam
School of Education
Department of Community Health
Dear SUNY Potsdam Student:
You are being asked to participate in a research project being conducted by Laurel Sharmer of the
Community Health Department of SUNY Potsdam. The purpose of this study is to survey health issues
among college students.
The information used in this study will be obtained by your answers to a series of questions pertaining
to this topic. The questions you will be asked to answer should take you approximately 20 minutes to
complete. Your answers to these questions will be kept confidential and none of the information
gathered in this study will be used to describe any one individual or his/her family. Additionally, you
may drop out of the survey at any time if you feel that you do not want to continue to answer the
questions.
This study, which has been approved by SUNY Potsdam's President and the Institutional Review
Board, is similar in design to many other studies of this type. Approval by the College President and
Institutional Review Board attests that appropriate safeguards, which protect human subjects, have been
included in the research design. The approval does not imply college endorsement of the content of the
research or conclusions that might be drawn from the project. The study involves no risk to the people
who choose to participate.
Any questions you have about the study will gladly be answered prior to you participation. You can
call Laurel Sharmer at (315) 267-3136 is you wish to know more about the study.
I hereby agree to participate in the study being conducted by Laurel Sharmer surveying health issues
among college students.
Signature
Date