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This is to certify that the
dissertation entitled

COMPARING PATTERNS OF ALCOHOL USE IN FEMALE

ATHLETES AND THEIR TEAM CAPTAINS IN
INTERCOLLEGIATE SOFTBALL TEAMS

presented by
Amber L. Warners

has been accepted towards fulﬁllment
of the requirements for the

PhD. degree in Department of Kinesiolgqy

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COMPARING PATTERNS OF ALCOHOL USE IN FEMALE ATHLETES AND
THEIR TEAM CAPTAIN S IN IN TERCOLLEGIATE SOFTBALL TEAMS

Amber L. Warners

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Kinesiology

2005

ABSTRACT
COMPARING PATTERNS OF ALCOHOL USE IN FEMALE ATHLETES AND
THEIR TEAM CAPTAIN S 1N INTERCOLLEGIATE SOFTBALL TEAMS
By
Amber L.Wamers
The purpose of this investigation was to examine the patterns of alcohol use between
captains of college softball teams and their teammates. Participants were 618 female
intercollegiate softball players ages 18-23 (M = 19.83). Athletes completed the Core
Alcohol and Drug Survey (Presley, Leichliter, & Meilman, 1998). Four questions were
asked in regards to alcohol use among the teams: (a) Do team captains use less alcohol
and binge drink less than their teammates? (b) Does captains’ alcohol use predict the
alcohol use of other members on their teams? (c) Does a coach’s emphasis on alcohol
policy adherence predict the alcohol use of the non-captains on their teams? (d) Does a
team’s additional alcohol policy predict the alcohol use of the non-captains on the team
representing that institution? Alcohol use was operationalized as an index score that was
constructed from the average number of drinks consumed in the past week, the number of
times there were ﬁve or more drinks consumed in one sitting over the past 2 weeks, the
amount of alcohol consumed in the past year, and the number of drinks consumed within
the past 30 days. Binge drinking was operationalized as consuming ﬁve or more drinks
in one sitting. Coaches’ emphasis was measured by how many times the coaches talked
to their teams about adhering to an alcohol policy. Teams’ additional alcohol policy was
examined by distinguishing teams that had an added alcohol policy from just their

institution’s policy regarding alcohol use. Results showed that there was very little

difference in the pooled captain scores of alcohol use and the collective scores of team
members’ alcohol use. Using Hierarchical Linear Modeling (HLM), results showed there
was a moderate relationship between captains’ alcohol use and their teammates alcohol
use. However, no relationship between coach’s emphasis of adhering to an alcohol
policy and their team’s alcohol use. There was a slight relationship between a team’s

additional alcohol policy and the team’s alcohol use.

DEDICATION

To my husband Mark, and my sons, Emmett, Carson and Tanner with love

iv

ACKNOWLEDGMENTS

A special thank you to my advisor and dissertation committee chair Dr. Deborah F eltz.
Thank you to my dissertation committee members, Dr. Crystal Brandta, Dr. Marty
Ewing, and Dr. Amos Aduroja for providing guidance and direction on this project.

My heartfelt gratitude go to the many athletes and coaches who donated their time and
effort to participate in the study.

To Nick Meyer and Neil Carlson for giving their time helping analyzing the data.

To my colleagues and ﬁiends in the HPERDS department at Calvin College for
supporting me through the duration of this project.

To my parents and my parents-in-law who helped me with the mailings of the surveys
and providing childcare while I was working on this project.

To my softball and volleyball players who were so willing to allow me to put this project
ﬁrst many times.

Finally, I would like to express my deepest gratitude to my husband Mark, Who not only
took over in running our household but even more importantly, has encouraged me along
the way and enabled me to fulﬁll this lifelong goal. I could not have accomplished this

without your love and support.

TABLE OF CONTENTS

LIST OF APPENDICES ................................................................................ viii
GLOSSARY .................................................................................................. ix
CHAPTER 1
INTRODUCTION
Nature of the Problem ........................................................................ 1
Alcohol and the College Student .............................................. 3
Gender Differences in Alcohol Use .......................................... 5
Alcohol and the College Athlete ............................................... 6
Alcohol and Athlete Leadership ............................................... 11
Exploratory Questions ....................................................................... 16
Basic Assumptions ............................................................................. 17
Delimitations ...................................................................................... 1 7
Limitations ......................................................................................... 1 7
CHAPTER 2
REVIEW OF THE LITERATURE
Introduction ........................................................................................ 18
Alcohol and College Students ............................................................ 19
Five National Data Sets ............................................................ 19
Trends of Alcohol Use .............................................................. 23
Gender Differences in College Student Drinking ..................... 24
Factors Affecting Student Drinking .......................................... 25
Consequences of College Alcohol Use ..................................... 26
Peer Inﬂuence on College Drinking .................................................. 28
Prevention Strategies and Future Directions ...................................... 34
Alcohol and Athletics ........................................................................ 37
Patterns of Use .......................................................................... 37
Gender Differences in Athlete Alcohol Use ............................. 42
Alcohol Consumption Across Different Sports ........................ 43
University/College Divisions in Alcohol and Drug Use .......... 43
Athletes and Hi gh-Risk Behaviors ............................................ 44
Consequences Speciﬁc to Athletes ........................................... 48
Limitations to the Research ............................................................... 53
Future Directions and Considerations ................................................ 55
Conclusion ......................................................................................... 57
CHAPTER 3
METHODOLOGY
Participants ......................................................................................... 59
Measures ............................................................................................ 59
Procedures .......................................................................................... 60

vi

Treatment of the Data ........................................................................ 62

CHAPTER 4

RESULTS
Descriptive Statistics .......................................................................... 66
Alcohol Policies ................................................................................. 69
Research Question 1 .......................................................................... 69
Research Question 2 .......................................................................... 73
Research Question 3 .......................................................................... 73
Research Question 4 .......................................................................... 74

CHAPTER 5

DISCUSSION ................................................................................................ 75

APPENDICES ............................................................................................... 84

REFERENCES .............................................................................................. 100

vii

LIST OF APPENDICES

Page
Appendix A. Informed Consent Form ....................................................... 82
Appendix B. Administrator Direction Form ............................................. 83
Appendix C. Phone Script of Initial Contact of Coaches ......................... 84
Appendix D. Additional Questions to the Core Survey ............................ 85
Appendix E. Core Alcohol and Drug Survey ............................................ 86
Appendix F: Tables ...................................................................................... 88

viii

GLOSSARY

Operational Deﬁnitions and Abbreviations

Alcohol Use: An index score created by measuring four components of drinking
patterns: having ﬁve or more drinks within the past 2 weeks of completing the survey,
average number of drinks consumed in the past 30 days, frequency of alcohol use within
the past year, and number of drinks consumed in the past week.

Athlete: Division III college softball players from the Midwest.

Binge Drinking: Drinking ﬁve or more alcoholic drinks within the previous 2 weeks

of completing the survey.

Captain: Softball player who was either elected by her teammates and/or appointed by

his/her coach.

Coach’s Emphasis: The score given by athletes of how many times a coach talked about
obeying an alcohol policy.

CAS: Harvard School of Public Health College Alcohol Study

CDC: Centers for Disease Control and Prevention.

CORE: Core Alcohol and Drug Survey, Southern Illinois University

Dangerous Drinking: Another term used for binge drinking.

Formal Peer Leader: Captain

Frequent Episodic Drinking: Binge drinking three or more times within the previous 2
weeks.

Heavy Episodic Drinking: Another term used for binge drinking.

Informal Leader: Athletes on the team who demonstrate leadership qualities but are not

ix

in a formal leadership position.

MTF: Monitoring the Future, University of Michigan

NCHRBS: The National College Health Risk Behavior Survey (CDC).

N HSDA: The National Household Survey on Drug Abuse, Substance Abuse and Mental
Health Services Administration (SAMHSA).

NIAAA: National Institute on Alcohol Abuse and Alcoholism

Non-captain: Members of the softball team who were not a captain.

Prevalence Rate: Term used in the alcohol research to deﬁne the incidence rate of
alcohol use within 1 year.

SAMHSA: Substance Abuse and Mental Health Services Administration.

Team’s Additional Alcohol Policy: A policy of alcohol restrictions or rules that teams

or coaches create in addition to the institution’s alcohol policy.

Chapter 1
INTRODUCTION

Nature of the Problem

Research has shown that there is an enormous effect that alcohol has on the
college population. In fact, experts have labeled the widespread misuse of alcohol as one
of the most serious threats to our nation’s institutes of higher education (Higher
Education Center, 1997). Researchers have examined the prevalence of drinking patterns
of college students as well as identiﬁed some of the unique variables that make the
college population more vulnerable to alcohol problems than other subgroups. There are
certain subgroups of college students who are more at risk than the general college
student population including members of the Greek system and athletes (Cashin, Presley,
& Meihnan, 1998; Presley, Meihnan, & Lyerla, 1993; Wechsler, Dowdall, Davenport, &
Castillo, 1995a). Furthermore, trends in drinking show excessive drinking by female
college students is on the rise (Keeling, 2002). Despite the extensive lines of research
regarding alcohol use in the college population, there has been little done on the
relationship between alcohol use and the college athlete.

The research that has been examined on alcohol and athletes has merely found
general statistics comparing alcohol use by athletes vs. non-athletes with the addition of
sparse studies relating alcohol and athletes with gender, injury, performance, different
sports, and medical concerns. There has been no research examining alcohol patterns
within a team or group and how different variables such as social components within a

team’s environment might affect group members’ alcohol use. Furthermore, research has

not explored the relationship between athletes holding leadership positions, and their
teammates, within each team in regards to alcohol use. I .

There is a growing need for the intervention and education of college student
alcohol misuse and abuse. In particular, college athletes are in a unique culture when it
comes to the pressures of excessive alcohol use. Many students and student-athletes are
unaware of the long-term consequences of their lifestyle choices pertaining to alcohol
consumption. In order for the most effective intervention strategies or prevention plans
to be created, it would be important to not only understand what the problem is among
college athletes and the misuse of alcohol, but to examine the unique variables that play a
part in the college athlete’s life that inﬂuences excessive alcohol use. Once those
variables are understood and researchers have some answers to why college athletes are
more at risk, then proper strategies can be implemented to help reduce the misuse of
alcohol among the college-athlete population. More research studies within the sport
setting are needed to examine the unique culture of being a part of a team and how
different components within a team can affect a person’s choices in regards to alcohol
use.

The purpose of this study is to determine whether the drinking patterns of female
athletes in formal leadership positions (i.e., team captains) differ from the drinking
patterns of the other members on their team. Additionally, the relationship between
female team captains’ alcohol patterns and their team members’ alcohol patterns within
each team will be examined. This chapter provides a general overview of research on
alcohol and its relationship to the college student population and the college athlete

population. In addition, a brief summary is presented of the research examining social

learning theory applied to peer inﬂuence in alcohol use among college students, as well

as a conceptual background of peer leadership in regards to sport.

Alcohol and the College Student

Research on alcohol consumption of college students has increased over the past
few decades. This research has focused on prevalence rates, demographic characteristics
of alcohol users and nonusers, and the consequences of drinking among college students.
Data show that annual prevalence rates of drinking are 82 -85% among college students
(Johnston, O’Malley, & Bachman, 1994; National Institute on Drug Abuse, 1991;
Presley, Meihnan, & Cashin, 1996a; Tricker & Cook, 1989). Prevalence rates are
deﬁned as the incidence rate of alcohol use within 1 year. This high percentage rate of
alcohol use by college students within a 1-year period is not a major concern because it
tells very little about the quantity and frequency of alcohol consumed by college students
within a year. Furthermore, it does not suggest any ﬁndings about the misuse of alcohol
other than reporting under-age drinking. More of a concern is the problematic, “heavy
episodicdrinking” or “binge drinking” because it is this kind of drinking that causes most
of the harm associated with alcohol. The harm associated with alcohol misuse is
associated with the quantities consumed during a drinking occasion more than by the
frequency of drinking (Rehm et al., 1996).

Wechsler and his colleagues coined the term “binge drinker” and reﬁned the
concept to categorize students whose drinking comprised of four or more drinks for
women and ﬁve or more drinks for men at one sitting (Wechsler & Austin, 1998;

Wechsler, Davenport, Dowdall, Moeykens, & Castillo, 1994; Wechsler, Lee, Kuo, &

Lee, 2000). The literature has also used similar terms to refer to binge drinking that
include heavy drinking, dangerous drinking, excessive drinking, heavy episodic drinking
and episodic drinking. Although binge drinking is a term that has been widely used as a
“catch wor ”to designate college drinking that leads to serious problems, there is
acknowledged criticism of the term (DeJong, 2001; Goodhart, Lederman, Stewart &
Laitman, 2003; Gruenewald, Johnson, Light, Lipton & Saltz, 2003 ; Jung, 2003). Binge
drinking is the term that is used in the present study because of its widespread use in the
literature.

One of the most noted surveys of college alcohol use and its misuses was
conducted by the Harvard School of Public Health College Alcohol Study (CAS) in
which Wechsler and his colleagues surveyed a random sample of the college population
in 1993, 1997, 1999 and 2001. The results of the CAS, using over 140 colleges, found
that binge drinking among college students did not change between 1993 and 2001.
Rates of binge drinking stayed consistent between 40 - 45% within the last 2 weeks of the
survey (Wechsler, Lee, Kuo, and Lee, 2002). In addition, other research has shown
college students have been found to drink frequently and binge drink at similar rates
(Leichliter, Meihnan, Presley, & Cashin, 1998; Presley et al., 1996; Werner & Greene,
1992)

In another national survey from the Core Institute at Southern Illinois University,
Presley and his colleagues surveyed a national sample of college students every year
between 1990 and 1994 and found 45.6% of full-and part-time students at 2 and 4 year
institutions engaged in binge drinking over the previous 2 weeks (Presley et al., 1998). In

the latest (1994) survey, over 45,000 students participated.

Although Wechsler et a1. (2002) did not ﬁnd binge drinking rates to change
between 1993-2001, others found an actual increase in the prevalence rates of annual
abstainers of alcohol between 1993 (16%) to 2001(23%) for a difference of 7% (Knight,
Wechsler, Kuo, Seibring, Weitzman, & Schuckit, 2002). There has been a decline in the
percentages of college students who have taken a drink within the past 30 days between
the years 1982 (83%) to 1999 (70%) by 13% (Johnston, O’Malley, & Bachman, 2000).
However, the 2001 CAS (Wechsler et al., 2002) data showed more drinking in excess on
measures such as frequency in drinking, frequency in drunkenness, and frequency of
drinking to get drunk than ﬁ'om the previous data. These trends show that more students

are choosing not to drink alcohol but those that are drinking are binge drinking the same

or more frequently.

Gender Differences in Alcohol Use

Overall, statistics show that female college students drink less than male college
students (Everett-Jones, Oeltrnann, Wilson, Brener, & Hill, 2001; Johnston et al., 2000:
Keeling, 2002; Wechsler et al., 2002). Rates are more similar in regards to monthly
alcohol use (73% for males, 67% for females) but the difference expands as frequency
and quantity of alcohol increases (Johnston et al., 2000). Binge drinking rates in males
have been reported to range from 47-52% while in females rates have been reported to be
from 33- 35% (Everett—Jones et al., 2001; Johnson et al., 2000: Keeling, 2002; Wechsler
et al., 2002). Keeling’s (2002) examination of the literature of the ﬁve major data sets,
concluded that the gap between gender in regards to heavy drinking is narrowing as

female heavy drinking is on the rise. Female college student alcohol use is another area

of research that needs more attention. While there have been some studies that
differentiate statistics by gender, there needs to be more information to access reasons
why female binge drinking is increasing and to identify the unique variables that are

speciﬁc to both men and women regarding alcohol abuse in college.

Alcohol and the College Athlete

Alcohol and sport seem to go hand-in-hand: tail-gating before games, alcohol
sales in venues, sports bars, and celebrating victories with champagne. The alcohol
industry plays a major role in this relationship. It is estimated that the average child
views as many as 100,000 beer ads before reaching the legal age for drinking alcohol
(Gloede, 1988).

The economic impact of alcohol on sports cannot be overstated. According to
Top TV Sports Advertisers (1988), Anheuser-Busch spends two thirds of its advertising
budget on sports. In addition, the same company will sponsor, in broadcast television,
radio, and/or cable, 23 of the 24 domestic Major League Baseball teams; 18 of the 28
clubs in the National Football League; 22 of the 23 National basketball Association
franchises; 13 of 14 domestic National Hockey League teams, and 9 of 11 Major Indoor
Soccer League clubs. Anheuser—Busch also sponsors over 300 college teams (Gloede,
1988). There is no question that a symbolic relationship exists between the alcohol
industry and sport. Unfortunately, the athlete falls in the center of that relationship: the
athlete that is deemed—the role model (Wadler & Hainline, 1989).

Not only do the media and alcohol companies impact college athletes, there have

been several other areas identiﬁed by research concerning the unique culture that athletes

.— "1.
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live in, that might contribute to alcohol use. Because of their dual role of being student
and athlete, some may feel an enormous amount of pressure and stress (Parham, 1993;
Watson, 2002). These stressors may include balancing academics and athletics, feeling
pressure to please many people including coaches, teammates, professors, school
ofﬁcials, friends, relatives, fans and the media, and having an elevated status around
campus. For some athletes, alcohol consumption can be a way of relieving the stress they
are faced with on a daily basis (Archer, 1991; Archer & Cooper, 1998).

Another unique factor regarding college-athletes is the social environment
(Nelson & Wechsler, 2001). Athletes were found to be more likely than what non-
athletes to exhibit several social factors that have been linked to the increased risk of
binge drinking. These factors include: reporting that athletes have ﬁve or more close
friends than what non-athletes reported, placing a higher level of importance on parties as
compared to non-athletes, and spending at least 2 hours more per day socializing than
non-athletes. One reason for this unique social environment was reported by Stainback
(1997) who found that student-athletes were overly exposed to social settings that
promote alcohol use which include traveling frequently and engaging in social settings
with alumni and sports boosters.

College athletes also, in general, have been found to be higher risk-takers than
college non-athletes (Bakker, 1996; Nattiv & Puffer, 1997). These risk-taking behaviors
include not using seatbelts, not wearing hehnets when riding motorcycles, mopeds or
bikes, driving while under the inﬂuence of alcohol, riding in a car operated by a person
under the inﬂuence of alcohol, getting in physical ﬁghts, having multiple sexual partners,

not using contraception, and drinking heavy amounts of alcohol. Surprisingly, few

researchers have examined the association between intercollegiate athletics and drinking.
In one of the classic studies, Straus and Bacon (1953) used 15,747 students from 27
colleges. Researchers suspected that because athletes would strive to maintain top
physical ﬁtness and because they would be more disciplined and have less time to
socialize, they would be less likely to drink than non-athletes. Data revealed 87% of
male athletes used alcohol compared with 75-78% of all other male students. Of women
athletes 60% were found to drink alcoholic beverages as compared with 48-56% of all
other female students (Straus & Bacon, 1953).

In very few studies, athletes were found to be less likely to drink alcohol
(Kokotailo, Henry, Koscik, Fleming, & Landry, 1996; Koss & Gaines, 1993). But for
most of the previous research, dating back to the I980S and early 19905, researchers have
shown that participation as a student-athlete showed no differences in alcohol use (88-
92% annual prevalence rate) than the general college population (Anderson, Albrecht,
McKeag, Hough, & McGrew, 1991; Anderson & Snellman, 1986; Duda, 1984; Gay,
Minelli, Tripp, & Keilitz, 1990; Toohey, 1978; Toohey & Corder, 1981).

Alcohol use did not differ signiﬁcantly between athletes and non-athletes in a
study of students ﬁ'om two state universities and two private colleges (Overman & Terry,
1991). However, they found evidence that drinking patterns may vary between athletes
and non-athletes. They suggest that male non-athletes drink signiﬁcantly more during the
week than male athletes, who tended to drink more on weekends or special occasions.
Also, athletes reported drinking more beer than non—athletes, perhaps reﬂecting

inﬂuences of the marketing strategy of beer distributors or traditional values associated

with participation in sport. These ﬁndings were consistently replicated until the latter
part of the 19908 when trends in the data of student-athletes started to shift.

The research since the late 19905 to the present has shown that “athletes are as
likely, and in many instances more likely than the general student population, to engage
in deleterious alcohol consumption” (Leichliter et al., 1998, p. 257). Other studies
supported the research that athletes consume more alcohol than the general student
population (Leichliter et al., 1998; Nelson & Wechsler, 2001; Wechsler, Davenport,
Dowdall, Grossman & Zanakos, 1997).

Interestingly, trends in the data show a drop in the prevalence of college athletes
using alcohol while that of binge drinking increased. In other words, there are more
athletes abstaining from alcohol but the athletes who are drinking alcohol are consuming
it in greater frequency and quantity (Green, Uryasz, Petr, & Bray, 2001). It is because of
the harmful consequences to not only the student-athletes and non-athletes that are
engaging in heavy episodic drinking, but also to the entire college population that college
administrators and government ofﬁcials are concerned about these trends. '

Although studies on prevalence rates between athletes and non-athletes may be
equivocal, researchers generally support the fact that athletes are increasingly engaging in
binge drinking. Binge drinking rates among athletes increased from 36-43% between the
years 1985-1989 (Michigan State University, College of Human Medicine, 1989).
Wechsler et al. (1997) found 61% of the males involved in athletics (students who spent 1
or more hours per day in intercollegiate sports and thought participation in athletics was
important) engaged in binge drinking while 55% of those partly involved in athletics

(students who spent 1 or more hours per day in intercollegiate sports or thought

participation in athletics was important) binge drank within the previous 2 weeks of the
survey. Women’s results were similar with 29% of male athletes and 24% of female
athletes engaged in binge drinking three or more times within the past 2 weeks compared
to 18% of male non-athletes and 15% of female non-athletes. The authors found the
more one was involved in athletics the higher the binge drinking.

Similarly, Leichliter et al. (1998) used data from 51,483 students at 125
institutions and found binge drinking rose for men and women as the degree of athletic
involvement increased. For men, 45% of non-participants’ were binge drinkers, 61% of
athletes (non captains) were binge drinkers and 64% of athletic team leaders (captains)
were binge drinkers. For women, the binge rates were 31, 47 and 49% for non-
participants, team members, and team leaders, respectively.

In the most recent research published, Nelson and Wechsler (2001), using 12,770
college students from 130 colleges and universities, reported athletes binged at higher
rates than non-athletes. Among the male students, 57% of athletes reported binge
drinking at least once during the previous 2 weeks compared to 49% of the non-athletes.
Among the female students, 48% of the athletes reported binge drinking while 40% of the
non-athletes binge drank.

Overall, male and female athletes show equal annual prevalence rates with
alcohol consumption, but male athletes tend to drink more often and binge drink more
than female athletes. The percentages of binge drinking among male collegiate athletes
range from 57- 61% while women collegiate athletes range from 46-50% (Leichliter et

al., 1998; Nelson & Wechsler, 2001; Wechsler et al., 1997). In addition, Wechsler et a1.

10

(1997) found 21% of the male athletes drank to get drunk compared to 12% of women

athletes.

Alcohol and Athlete Leadership

The risks and problems associated with alcohol use in college athletics will not be
adequately addressed by focusing only on student athletes. Attention must also be given
to the role of positive leadership for enhancing the health and total well-being of athletes.
There has been very little research conducted on team leaders and alcohol. Such research
would allow us to discover whether or not leaders tend to act more or less responsibly
and if the team’s leaders’ alcohol patterns have a positive or negative relationship to the
other team members’ drinking patterns. Carron (1980) found the role of athletic
leadership is a signiﬁcant factor in the life of a student athlete. In a study that examined
differences in alcohol use and consequences of use according to the leaders vs. the other
team members, Leichliter et a1. (1998) found no support for the hypothesis that athletic
leaders were more responsible than other team members in using alcohol. The study used
58,453 students ﬁom 125 colleges across the United States who participated in Core
Alcohol and Drug Surveys between 1994 and 1996. In fact male team leaders consumed
more alcohol, binged more often, and suffered more consequences than other team
members. Female team leaders, however, showed no differences from other team
members.

While the Leichliter et a1. (1998) research helps shed some light on the patterns of
alcohol use among athletes in leadership roles as compared to the general athlete

p0pulation, it fails to examine how each leader’s behavioral patterns might inﬂuence

ll

his/her team members’ alcohol use patterns because it did not consider the inherent
nesting involved with team captains and their team members. In order to examine if the
alcohol use of team captains predicts the alcohol use of their respective teammates, the
nesting of athletes within teams must be considered.

The topic of leadership has been heavily researched in the educational and
business literature but remains one of the least understood concepts (Todd & Kent, 2004).
Even while researchers can not agree on a consensus regarding the deﬁnition of
leadership, Chelladurai (1999) has synthesized this complex term as follows: “All
deﬁnitions of leadership imply three elements: (1) leadership is a behavior process, (2)
leadership is interpersonal in nature, and (3) leadership is aimed at inﬂuencing and
motivating members toward group goals” (p. 160). There have been a limited number of
research studies that have stressed the importance of leadership (Meindl, 1990; Pfeffer,
1977) but most have ascertained that leadership is a crucial and distinct aspect of
organizations and groups (Bass, 1990; Bennis, 1989; Kouzes & Posner, 1995).

Because leadership is important to the success of many different organizations
whether it be corporations, schools or athletic teams, it is important to understand its
intricate structure and development. By nature, groups consist of individuals who work
together to achieve goals that are both interpersonal and task-oriented. Kozub and Pease
(2001) state that the primary function of a leader is to inﬂuence members of the group
and help facilitate the achievement of the group’s goals. Bennis (1989) emphasizes that
leaders are responsible for the effectiveness of groups and that they provide integrity to
institutions. Leadership can come from any member of the team. According to Mabry &

Barnes (1980), leadership roles are labeled within a team as either formal or informal.

12

 

 

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..

 

Formal leadership is set apart from the group and is included in the organizational
structure. The coach and team captain would represent formal roles of leadership.
Informal leadership emerges over time as individual members of the group interact and
spend time together. The informal leader might be a star player or a veteran player who
might have signiﬁcant inﬂuence within the group members. Informal leadership can
have as much inﬂuence on the group, and sometimes more, compared to formal
leadership (Mabry & Barnes, 1980).

In support for the formal and informal leadership types, there is a small body of
literature that has recently dealt with peer leadership among adolescents regarding risk-
taking behaviors. While these studies have primarily used subjects that are of middle-
school and high-school age, it would be erroneous to overlook what researchers have
found. Luthar and McMahon (1996) found two contrasting patterns of admired, well-
liked teens. The ﬁrst group was characterized by conventionally valued behavior such as
academic achievement and prosocial behavior. The second group was characterized by
disruptive/aggressive behaviors and school performance. In a similar study, Rodkin,
Farmer, Pearl and VanAcker (2000) found two types of boys that were well-liked by their
peers, popular-prosocial boys and popular-antisocial boys. Each group rated themselves
as “cool” and athletic while the popular-prosocial group added the characteristics of
nonaggressive and academically competent; the popular-antisocial group rated additional
characteristics of aggressive. Both groups were well-liked and recognized as central
ﬁgures within their peer groups. Miller-Johnson, Costanzo, Coie, Rose, Browne and
Johnson (2003) found that a more unconventional peer group leader may be inﬂuential in

promoting norms that support involvement in risk-taking behaviors. The research team

13

concluded that reaching adolescents through peer leaders, including the use of more
unconventional controversial status peers should be considered and may have the most
impact to changing substance use patterns.

Data from alcohol research support that the best avenue for inﬂuencing athletes’
decisions regarding substance use is through peers. Additionally, peer leaders who
reinforce drug-free behavior acts as the best prevention strategy over other traditional
strategies such as social norms or educational programs (Elder, Barnes, Leaver-Dunn,
Nagy, & Leeper, 2002). Fitzgerald and Ardnt (2002) strongly encourage prevention
programs not only to focus on peer disapproval of drinking alcohol but also the
disapproval from students in school, parents, and the community for the most impact.
Unfortunately, very little if any research is being conducted in this area for the college
athlete population.

Almost all of the research related to leadership in sport has focused on the formal
leader—that of the coach. Although these studies have examined self-reported leadership
styles and preferred leadership behavior by athletes (e. g., Chelladurai & Saleh, 1980),
none have examined coaches’ leadership behavior and alcohol use by athletes. Research
that focused on peer leadership is even more sparse than coach leadership research. The
importance of leadership among group members has had many schools and sports
organizations identify it as a desire to develop peer leadership in future goals (Sage,
1973). Many times one can hear coaches calling for their athletes to lead their team.
Despite this hypothetical importance, sports psychologists have largely ignored peer
leadership. Not only does there need to be more studies to identify how peer leaders

develop or emerge but even more importantly, research is needed on how player or peer

14

leadership can inﬂuence members of the team in regards to performance or social '
behaviors. ’

Previous research suggests there are four social environments (peer, school, home
and neighborhood/community) that directly impact adolescents’ drinking behavior (Bahr,
Marcos, & Maughan, 1995; Mason & Windle, 2001; Ouellete, Gerrard, Gibbons, & Reis-
Bergan, 1999). In fact, studies that were designed to assess the signiﬁcance of each of
these four areas found peer attributes and inﬂuence to have the most inﬂuence on
adolescents (Beal, Ausiello, & Perrin, 2001; Fitzgerald & Arndt, 2002; Jenkins, 1996;
Olds & Thombs, 2001; Urberg, Degirmenciouglu, & Pilgrim, 1997).

Because peer attributes are shown to have the most inﬂuence on adolescents’
substance use and because athletes spend many hours within the same peer group, it is
speculated that the peer leader has a major inﬂuence on other members of his/her athletic
team on substance use patterns. Although, the literature involving adolescents indicates
that being a member of a group, particularly an athletic team, is a protective factor
against health risk behaviors, including preventing substance abuse, that may not be the
case for alcohol use (Pate, Heath, Dowda, & Trost, 1996; Page, Hammermeeister,
Scanlan, & Gilbert, 1998; Pate, Trost, Levin, & Dowda, 2002; Rainey, McKeown,
Sargent, & Valois, 1996; United States Department of Health and Hmnan Services
(DHHS), 2002; Winnail, Valois, McKeown, Saunders, & Pate, 1995). Pate et al. (2002)
found that adolescents involved in sports were signiﬁcantly less likely to smoke
cigarettes and marijuana but did not ﬁnd the same correlation for alcohol. One

explanation for this ﬁnding is our culture’s acceptance of alcohol use through the media

especially in relationship with sport.

15

These studies primarily involved adolescents in middle and high schools. Given
the fact that by the time athletes are attending college, substance abuse rates in athletes
are exceeding that of their non-athlete peers the following questions can be raised: What
makes the environment of athletics in college different and more prone to alcohol abuse?
What inﬂuence could peer leaders have within their athletic teams in regards to alcohol
use? The present study is an attempt to start the process of examining some of the
variables within teams that affect alcohol use, speciﬁcally the relationship between the
formal team leader and members of his/her team.

The sport chosen for the current study was collegiate softball teams. There was
nothing speciﬁcally intrinsic to the nature of softball for using this sport in the study
other than the fact that the investigator had access to softball coaches at the Division 111

level as well as the need for more research on female athletes and alcohol use.

Exploratory Questions

Speciﬁcally, the following research questions were examined:

1. Do team captains use less alcohol and binge drink less than non-captain
athletes?

2. Does captains’ alcohol use predict the alcohol use of the other members on
their teams?

3. Does a coach’s emphasis on alcohol policy adherence predict the alcohol use

of the non-captains on their teams?

4. Does a team’s additional alcohol policy predict the alcohol use of the non-

captains on the team representing that institution?

l6

Basic Assumptions
The study was conducted based upon several assumptions. First, it was assumed
that the sampling technique used for this study was appropriate. Secondly, it was
assumed that the administration of the questionnaire provided consistency of
measurement. Next, there was an assumption that the subjects answered all the questions
honestly. Finally, the study was conducted with the assumption that the Core Alcohol

and Drug Survey questionnaire was a reliable and valid instrument for measuring college

athlete alcohol pattems.

Delimitations
The study was delimited to Division III softball players in the Midwest. Results
cannot be generalized beyond this population. It should also be stated that the results
should be interpreted with caution for other levels of these teams including club, junior or

senior high school or elite players.

Limitations
The present study is based on subjects’ self-reports. Some athletes may
misrepresent their leadership roles. Some athletes may also misrepresent sensitive
information about their substance use and involvement in illegal acts, such as drinking
under the legal age or damaging property. To help reduce this from occurring, the

surveys were anonymous while providing the respondents with adequate protection.

17

Chapter 2
REVIEW OF LITERATURE
Introduction

Alcohol and its related risks have become a major concern in society. One
population affected greatly by alcohol is the college student. College life offers
opportunities for individuals to experiment with, and in some cases, abuse alcohol and
other drugs. Not surprisingly, alcohol consumption by college students has been the
focus of attention during the past few decades. Student-athletes are not immune to these
ﬁndings. Recent research has shown that “athletes are as likely, and in many instances
more likely than the general student population, to engage in deleterious alcohol
consumption” (Leichliter et al., 1998). The problem continues, despite more educational
programs directed at student athletes and stricter rules by coaches and universities as well
as expanded use of drug testing.

This literature review will examine the relationship between alcohol use and
college students including the ﬁve national data sets that have examined "college alcohol
use, trends of use, gender differences, factors affecting student drinking and the
consequences of college alcohol use. This review will also cover the area of peer
inﬂuence on college alcohol use and discuss prevention strategies that have been
researched. In addition, the literature review will examine one subgroup of college
students— student athletes. Speciﬁcally, student athletes and alcohol use including the
literature on athletes as risk-takers, athletes’ patterns of use, alcohols effect on

performance, gender differences, peer leadership and alcohol use, differences in college

divisions, and prevention efforts.

18

 

 

 

Fr

Finally, alcohol has been shown to have a direct link to many of the other risk
behaviors of college athletes. Because alcohol plays such an integral part in these
behaviors, it is important to include research pertaining to risk behaviors of college
students and student-athletes. Some of these behaviors include driving while under the
inﬂuence of alcohol or drugs, sexual intercourse without using condoms, property
damage, sexual assaults, consideration of suicide, attempted suicide and more. It is for
these reasons that more research needs to be conducted to better understand the broad
scope of alcohol in the college population—including athletics. This review will
conclude with a discussion on the limitations of the research, suggestions for ﬁxture

research and a discussion on future prevention of the abuse of alcohol by college athletes.

Alcohol and College Students
Research indicates that alcohol is the most commonly used drug on college
campuses with annual prevalence rates of approximately 82-85% (Johnston et al., 1994;
National Institute on Drug Abuse, 1991; Presley et al., 1996b; Tricker & Cook, 1989). In
addition, college students have been found to drink frequently and binge drink often
(Leichliter et al., 1998; Presley, Meilman, Cashin & Lyerla, 1996b; Werner & Greene,

1992). Much of the research ﬁndings have come ﬁ'om large, national data sets on college

student drinking.
Five National Data Sets on Alcohol Use By College Students

There are ﬁve key national sources of data that have been collected regarding

alcohol consumption among the college student population. Each of these sources has

19

conducted their research with slightly different characteristics related to their population,

data collection methodology, instrumentation, and period of data collection. These ﬁve

data sets are:

1.

The Harvard School of Public Health College Alcohol Study (CAS)
(Wechsler et al., 2002);

The Core Institute (Core), Southern Illinois University (Presley et al.,
1996a; Presley et al., 1996b);

Monitoring the Future (MTF), University of Michigan (Johnston et al.,
2000);

The National College Health Risk Behavior Survey (N CI-IRBS), Youth
Risk Behavior Surveillance, Centers for Disease Control and Prevention
(CDC) (Centers for Disease Control and Prevention, 1995);

The National Household Survey on Drug Abuse (NHSDA), Substance

Abuse and Mental Health Services Administration (SAMHSA) (National

Institute on Drug Abuse, 1991).

In the CAS study, ﬁmded by the Robert Wood Johnson Foundation, the principal

investigator (PI), Henry Wechsler and his colleagues conducted their survey over four

different years—1993, 1997, 1999, and 2001. All of these surveys were distributed to the

same colleges over the span of the four surveys. In 1993, 140 randomly selected, four-

year colleges participated. The complete 20-page, mailed questionnaire was completed

by 15,103 students (response rate of 69%). In 1997, 14,521 students (response rate of

60%) from 116 colleges completed surveys. In 1999, 14,138 students from 128 colleges

participated (response rate of 60%). In 2001, 10,446 students (response rate of 53%)

20

’1‘

 

from 114 colleges participated (Wechsler, 2003). The advantages of the CAS study
include large sample sizes which allow for subgroups to be identiﬁed, institution-level
variables can be examined and analyzed, repeated surveys to study change over time and
samples are randomly selected allowing the ﬁndings to be generalized to suggest national
estimates.

The PI for the CORE Survey was Cheryl Presley. The CORE was funded by the
Drug Prevention in Higher Education Program of the Fund for the Improvement of
Postsecondary Education of the US. Department of Education. The CORE Survey was
speciﬁcally designed for use with college students and the institutions participated on a
voluntary basis, so the sample was not randomly selected. More than 45,000 students
participated in the study’s fourth cycle, a period that covered 1992 to 1994. CORE’s
major advantages include large sample sizes, information about institutions, and
respondents grouped by institution, so institutional variables and policies could be
examined, and the inclusion of other drugs.

The MTF’s primary investigator was Lloyd Johnston and was funded by a series
of grants from the National Institute on Drug Abuse. The study conducted annual
nationwide surveys of about 17,000 high school seniors, with annual follow-up surveys
of representative subsarnplcs from all previously participating senior classes. There were
no colleges represented so no conclusions can be drawn from individual institutions. The
advantages of MTF are: availability of relatively long-term trend data, the study is
ongoing, the design is longitudinal including the transition period between high school
graduation and college, and the design includes both college students and same-age peers

who do not attend college, so comparisons between the two groups can be drawn.

21

The NCHRBS was a one-time study conducted between January and June of 1995
by the Division of Adolescent and School Health, National Center for Chronic Disease
Prevention and Health Promotion. More than 4,800 students from 136 colleges which
were relatively proportional of Black and Hispanic students, completed the questionnaire.
The major advantages of this sample include comparisons across ethnic groups, and data
on several health risk behaviors in addition to alcohol and drug use.

The NHSDA was conducted under government contract by the Research Triangle
Institute. This survey was conducted by using in-home interviews. The study included
more than 4,800 part-time and full—time college students and more than 7,000
respondents of college age (17 to 22) deﬁned as non-college students. The major
advantages of NHSDA are the study is on-going, comparing both college students and
same-age peers who do not attend college and a broad range of substance-abusing
behaviors is represented.

All of these sources identiﬁed extraordinarily high percentages of excessive
drinking. Findings from the ﬁve sources agreed that approximately two of three US.
college students participate in heavy episodic drinking (Wechsler & Austin, 1998). MTF
data showed a 70% prevalence rate of alcohol use within the previous 30 days among
full-time college students, ages 19-22. The same data set showed that 40% of the college
student sample binge drank within the previous 2 weeks. Therefore, more than half of
the students who drank in the past 30 days (70%) had been drinking heavily in the
previous 2 weeks (O’Malley & Johnston, 2002). CAS found prevalence rates of binge
drinking to be at 44% in 1993 and 43% in 1997 and 45% in 2001 within the 2 weeks of

the completed survey (Wechsler, Dowdall, Maenner, Glenhill-Hoyt, & Lee, 1998).

22

CORE reported binge drinking rates, deﬁned in the same way as in the CAS study, at
38% in the 1992-1994 survey (Presley et al., 1996a). The NCHRBS found binge
drinking rates to be 42% among college students (Everett-Jones et al., 2001).

In addition to the ﬁve key sources discussed, there are numerous other research
studies that add important ﬁndings in the area of college alcohol use. College drinking is
further reviewed using these ﬁve major data sources, in addition to other smaller data
sets. It is noteworthy that the estimates of prevalence rate of drinking in all of the data
sets are generally consistent with each other. This consistency suggests there is

considerable validity to the high drinking rates of college students.

Trends of Alcohol Use

The MTF study was the only national research data that extended over more than
4 years. The trend for alcohol use (past 30 days) showed a decline with rates peaking at
83% in 1982, down to 70% in 1999—a 13% difference. Binge drinking showed a
slightly smaller decline of 11% with reported heavy drinking at 29% in 1982, peaking at
45% in 1984 to 40% in 1999 (Johnson et al., 2000). Monthly prevalence rates have been
compared from one of the ﬁrst studies by Straus and Bacon (1953) to recent years.
According to Blane and Hewitt’s (1977) recalculation of Straus and Bacon’s data from
college students in 1949 to 1951, 65% reported drinking alcohol once a month or more.
The monthly rates in the 1990’s are slightly higher with rates in the MTF study (1995) to
be 68% of full-time students, the CAS study estimated 70% and the NCHRBS reported
68% of all students (73% of full-time students) drinking at least once in the past 30 days.

However, since 1953, there have been major changes in the demographics of college

23

students. There are higher proportions of females and ethnically diverse people attending
college in the 1990’s. There are also a lot more “non-traditional” students enrolled in
college presently. Because of these differences, and the fact that males are much more
likely to be frequent drinkers, the probability is high that there is a somewhat greater
change (O’Malley & Johnston, 2002).

Between 1993-1999 CAS data concluded that overall rates of abstainers rose (16
% in 1993 to 19% in 2001) as well as the percentage of frequent drinkers (20% in 1993 to
23% in 2001) (Knight et al., 2002). Overall, there has been a modest increase of
abstainers as well as a modest increase of binge drinkers ﬁ'om the CAS data through 2001
(Keeling, 2002). To put more simply, there are more college students choosing to not

drink any alcohol but those that are drinking alcohol are drinking alcohol more frequently

and in more quantity.

Gender Diﬂerences in College Student Drinking

The general consensus for alcohol rates found by almost all studies is higher for
male college students than female college students. The gaps generally get wider as
frequency and quantity goes up. In the MTF study in 1999, comparing drinking in the
past month, 73% of male students consumed alcohol compared to 67% of female students
for a difference of about 6%. However, 50% of male students reported having ﬁve or
more drinks in one sitting at least once as compared with 34% of female students for a
difference of 16% (Johnston et al., 2000). Using the NCHRBS data, Everett-J ones et a1.
(2001) indicated that 49% of males binge drank as compared to 34.8% of women. The

CORE data reported that 26% of males consumed 10 or more drinks per week compared

24

to 10% of females, or two and a half times more for males. According to MTF data,
trends in gender differences, particularly in regard to heavy drinking, include the
difference in 1986 of 24% (58% males vs. 34% females) and a difference in 1999 of 16%
(50% for males vs. 34% for females) (Johnston et al., 2000). According to the CAS
studies, the trends in frequent binge drinking among female college students are
substantially increasing (5% in 1993 to 12% in 2001) (Keeling, 2002).

Women need to be extra careful when it comes to how alcohol affects the body.
They have a smaller quantity of a protective enzyme in the stomach to break down
alcohol before it is absorbed into the bloodstream which causes them to absorb about
30% more alcohol into their bloodstream (White, J amieson-Drake, & Schwartzwelder,
2002). This blood travels directly to the brain and leads to women becoming intoxicated
much faster than males. Women will black out after consuming only half of the amount
of alcohol men will drink. They also may be more susceptible to alcohol-induced
memory problems when given the same amount of alcohol as men (White et al., 2002).
These inﬂuences on the body could easily lead females to engage in risky behavior such

as unprotected sex. They also may put themselves at risk of being victimized of

attempted rape, assault, and rape.

Factors Affecting Student Drinking

Factors that affect student drinking include three major categories: living
arrangements, college characteristics, and ﬁrst-year students. In terms of living
arrangements, drinking rates are highest among college students who are members of

fraternities and sororities, followed by students living in on-campus housing (Presley et

25

al., 1996a, 1996b; Wechsler et al., 1998, 2000). Students who live with their families
drink the least amount of alcohol (O’Hare, 1990; Wechsler et al., 2002). Colleges where
there is more excessive alcohol use include those where Greek systems are dominant,
schools with high proﬁle athletic programs, and schools located in the Northeast (Presley
et al., 1996a, 1996b; Wechsler et al., 1997, 1998, 2000; Werner & Greene, 1992).

Even though high school students who go on to college tend to drink less than
their non-college going peers, college students will surpass their non-college peers by the
ﬁrst year in college (Schulenberg et al., 2001). Researchers found the ﬁrst 6 weeks of a
freshman’s enrollment to college is the most critical time period for the risk of excessive
alcohol. This can have a major impact on the successful transition to college, in fact,

about one-third of ﬁrst-year students do not enroll their second year (Upcraft, 2000).

Consequences of College Alcohol Use

One of the main concerns resulting from the more ﬁequent, heavy drinking is the
health consequences. In fact, the National Institute on Alcohol and Alcoholism (NIAAA)
(2002) compiled results ﬁom most of the health studies conducted on alcohol use
outcomes and concluded that the consequences both drinking and nondrinking students
suffer due to alcohol use every year include: 1,400 college students die from alcohol-
related causes (1,100 from drinking and driving), 500,00 students suffer injuries that are
nonfatal, 400,000 students engage in unprotected sexual intercourse, more than 100,000
students do not remember if they gave consent for sexual intercourse, 1.2-1.5% of
students attempt suicide as a result of alcohol and other drug use, 11% of students

damage property, and 2.1 million students drive while under the inﬂuence of alcohol.

26

Health consequences are not the only harmful effects of alcohol use by college students.
About 25% of college students report academic problems such as missing class, lower
grades, doing poorly on tests or papers and falling behind as a result of alcohol use
(NIAAA, 2002).

Not only are these harmful effects happening to students who are engaging in
heavy episodic drinking, but also students who abstain from alcohol or who are moderate
drinkers are experiencing negative consequences (this is referred to as secondary effects).
Wechsler et a1. (2002) found a number of secondary effects reported by students, living
on campus or in sorority or fraternity houses, who abstain or drink moderately:

o 60.0% had study or sleep interrupted

o 48% had to take care of a drunken student

0 29% had been insulted or humiliated

o 20% of female respondents experienced an unwanted sexual advance

0 15 % had property damaged

0 9% had been pushed, hit, or assaulted

o 1% of female respondents had been a victim of sexual assault or

acquaintance rape

Alcohol has also been found to be the most signiﬁcant factor in sexual aggression among
male college students (Koss & Gaines, 1993). In addition, alcohol is a key contributor in
rioting, hazing, and other forms of nonsexual violence, many of which occur in

connection to sporting events (Axtman, 2002; O’Toole, 2002; Strauss, 2001).

27

Peer Inﬂuence on College Drinking

Researchers suggest four social environments, peers, the school, home, and
community that inﬂuence adolescents’ drinking behaviors (Bahr et al., 1995; Mason &
Windle, 2001; Ouellete et al., 1999). Of all of these four variables, it is the peer
environment that has proven to be the most inﬂuential on adolescents (Beal et al., 2001;
Fitzgerald & Amdt, 2002; Jenkins, 1996; Olds & Thombs, 2001; Urberg et al., 1997). As
adolescents get older they spend more time with their ﬁiends than they do with their
parents (Csikszentrnihaly & Larson, 1984), and as their peers become increasingly
important, the more they are independent of parental control (Brown, Dolcini, &
Leventhal, 1997). This process only intensiﬁes in. college especially for those students
who leave home to live on campus. A major shift in inﬂuence ﬁ'om parents to peers
occurs during the college years. Thus, college life makes for an ideal environment for
drinking patterns to start and/or intensify.

Not only is the absence of parental control a key component in the importance of
peer inﬂuence on individual attitudes and behaviors but also the amount of alcohol-based
social opportunities at college that exist. College life is a time period for many students
to live carefree before taking on the responsibilities of adulthood and a full-time job.
Combining this carefree lifestyle with meeting new peers, some of whom will likely be
drinkers given that four of ﬁve college students drink (Wechsler et al., 2000), creates a
potential inﬂuence on drinking patterns in college. In addition, college students are more

approving of alcohol use (Johnson, 1989).

In sum, peers play a considerable role in the development and maintenance of

alcohol use in college students. Because college students are establishing a new peer

28

network, and immersing themselves in social activities (Martin & Hofﬁnan, 1993), they
encounter greater peer-drinking levels and alcohol-related behavior (Schulenberg,
Bachman, O’Malley, & Johnston, 1994). Exposure to such environments has been
correlated with increased levels of drinking especially for students living in places where
“heavy drinking is approved and where alcoholic beverages and the places to consume
them are readily available” (Schall, Kemeny, & Maltzman, 1992, p. 134). Thus, personal
attitudes and behaviors in regards to alcohol consumption are related to peer alcohol-
related attitudes and behaviors (Brennan, Walﬁsh, & AuBuchon, 1986).

Literature on peer inﬂuence on college drinking patterns has been discussed
primarily from social-cognitive theory. Peer inﬂuences are those interpersonal
components present in the direct or potential drinking environment (Borsari & Carey,
2001). According to social-cognitive theory, peers can inﬂuence alcohol use by actively
shaping drinking behavior or through more cognitively based social inﬂuence processes
(Maisto, Carey, & Bradizza, 1999), which include three different variables: (3) active
offers of alcohol, (b) modeling of others’ drinking, and (c) perceived drinking norms.

For the purposes of this dissertation, the literature on peer inﬂuence on alcohol is
examined for—direct (or active) peer inﬂuence which includes peers focusing on getting
a student to drink and indirect (or passive) inﬂuences which include modeling and
perceived norms (Borsari & Carey, 2001). Direct peer inﬂuence includes anything from
polite gestures (e.g., offering to get a person a drink or buying a round) to command or
persistent encouragement to drink (e. g., forcing a person to drink during drinking games).

Indirect inﬂuences include what impact peers’ drinking behaviors play as well as what

29

drinking behavior is acceptable and admired and what is expected behavior within a
social setting that would lead to acceptance and reinforcement by a person’s peer group.

In the area of direct peer inﬂuence, Wood, Read, Palfai, and Stevenson (2001)
concluded that the number of direct offers of drinks had a positive relationship with
alcohol use and problems. Conversely, not drinking at social events was found to be
unusual behavior and could result in teasing and feelings of inferiority by peers. Using
qualitative research, Rabow and Duncan-Schill (1994) had subjects keep a drinking diary
for 28 days, subjects reported that not drinking was less common than drinking at social
events and being without a drink caused several offers of drinks as well as cormnents.
The researchers also found that refusal of drink offers led to exclusion from social events.
Researchers indicated students who are more socially secure have better resistance to
peer offerings of alcohol (Shore, Rivers, & Berman,1983) as well as socializing with an
established group of friends. Furthermore, year in school had a positive correlation with
refusing to drink alcohol (Klein, 1992). In other words, as college students advanced
each year in college the better their refusal skills became.

In the area of indirect peer inﬂuence, the research on modeling and perceived
norms has been the primary variables of interest. The term modeling has been
interchanged with words like imitation and observational learning (White, Bates, &
Johnson, 1991) and can be deﬁned as “the temporary and concurrent imitation of
another’s behavior” (Borsari & Carey, 2001, p. 395). There have been several laboratory
studies conducted in the 19708 and 19808 with modeling. A few of these studies are
mentioned here, but because the scope of this paper does not focus on modeling as one of

its primary foci, and because many of the studies found similar results, an overall

30

summary is presented for other research. In this type of laboratory research, the
participant is ﬁrst paired with another student who is actually a confederate trained to
consume alcohol at a certain rate. A modeling effect is demonstrated if the subject’s
alcohol consumption matches that of the confederate. Overall, the research indicates that
students exposed to heavy-drinking models consume more alcohol than students who
were exposed to light-drinking models or no models at all (Borsari & Carey, 2001).
Research on modeling of alcohol indicates three characteristics of the model
inﬂuence consumption. First, the participant matches the concurrent drinking behavior of
the confederate not previous observation of him or her (Cooper, Waterhouse, & Sobell,
1979; Hendricks, Sobell, & Cooper, 1978). The models were also found to increase or
decrease the subject’s rate of consumption (Dericco & Garlington, 1977; Garlington &
Dericco, 1977) as well as lead the participant in what kind of alcohol beverage to
consume (Corcoran, 1995). Secondly, composition of a group of models inﬂuences
participants’ alcohol use. When there is a slow drinking confederate and a fast drinking
confederate in the same group, participants will model the fast drinking confederate
(Dericco & Niemann, 1980). In a large group setting, the subjects drank at the same rate
as the majority rate of the confederates (Dericco, 1978). Third, modeling was inﬂuenced
by the sociability of the confederate. Heavy drinking occurs when a heavy drinking
sociable model is paired with a participant but not when paired with a light drinking
sociable model. When confederates are unsociable both the heavy and light drinking
confederates are associated with heavy drinking (Collins, Parks, & Marlatt, 1985). These
ﬁndings support the coping role of alcohol in social learning theory (Maisto et al., 1999)

by concluding that a participant may drink heavily in reaction to the negative

31

environment which may overwhelm the modeling effect of the confederate. Collins et a1.
(1985) found social status (popularity within a group) of the model to have no effect on

the modeling effect.

Three participant characteristics were identiﬁed by researchers as inﬂuencing the
modeling effect of alcohol use. Lied and Marlatt (1979) found heavy drinkers consume
signiﬁcantly more alcohol than light drinkers regardless of the modeling condition or
gender of the subject. Secondly, participants with a family history of alcohol problems
matched the confederate’s drinking level more than those without such a history
(Chipperﬁeld & Vogel-Sprott, 1988). Finally, the gender of the participant inﬂuences
modeling. Males consistently drank more than females, regardless of type of drinking
confederate or history of drinking (Cooper et a1, 1979; Dericco & Niemann, 1980; Lied &
Marlatt, 1970).

Research in the second type of indirect peer inﬂuence is perceived norms.
Because of the extensive research on perceived norms in the area of alcohol use, an
overall review of the literature is discussed by providing general ﬁndings of perceived
norms. Many studies, conducting survey research, found that the more the student
perceived others as drinking heavily or approving of drinking the more personal use there
was (e. g. Clapp & McDonnell, 2000; Liccione, 1980; Lo, 1995; Nagoshi, 1999; Perkins
& Wechsler, 1996; Tunisi, 1999; Werner, Walker, & Greene, 1996). Furthermore,
people-based norms, such as friends or parents, align more closely to personal drinking
pattenrs than those of institutional-based norms such as governmental or health

authorities (Nagoshi, 1999; Nagoishi, Wood, Cote, & Abbit, 1994; Wood, Nagoshi, &

32

Dennis, 1992). Gender differences showed that men perceive more permissive alcohol
norms than do women (Adams & Nagoshi, 1999; Lo, 1995; Nagoshi et al., 1994).
Regarding descriptive norms studies, students have been found to overestimate
the quantity and frequency of alcohol consumption of their peers, including close friends
(e. g. Baer & Carney, 1993; Baer, Stacy, & Larimer, 1991; Banks & Smith, 1980;
Larimer, Iruine, Kilrner, & Marlatt, 1997; Mooney & Corcoran, 1991) and typical college
students (Baer, 1994; Baer & Carney, 1993; Canter & Kalmweiler, 2000; Perkins,
Meilman, Leichliter, Cashin, & Presley, 1999; Thombs, 2000). Furthermore, researchers
indicate that subjects believe others always drink more than themselves (Canter &
Kahnweiler, 2000; Larimer et al., 2000). The perceived norms also show (a) students
perceive an overestimation of alcohol use by members of the Greek system (Baer &
Carney, 1993; Baer et al., 1991), (b) typical students are more comfortable with alcohol
use than personal attitudes (Perkins & Berkowitz 1986; Prentice & Miller, 1993), and,
(c) subjects reported perceiving close friends approval of excessive drinking as more than
the subjects themselves (Alva, 1998; Baer, 1994; Prentice & Miller, 1993). In sum, many
elevated descriptive and injunctive norms make excessive alcohol use seem common and
acceptable, which in turn, will likely inﬂuence behavior. Perkins (1997) summarized the
inﬂuence of norms on alcohol behavior by pointing out that the students who are
socializing with peers who are perceived to both participate in and approve of excessive
drinking may be at risk for increased levels of personal use. This does not mean to imply
that all students exposed to such norms will experience excessive drinking behaviors or

alcohol dependency. Instead there are many other psychological (e. g., religiosity) and

33

social (e.g., social support) moderators that play a role in inﬂuencing peer norms on

alcohol use.

Prevention Strategies and Future Directions

Many alcohol programs and prevention strategies have been implemented over
the past decade in colleges and universities in the United States. Based on data collected
during this past decade, heavy episodic drinking has continued to increase implying that
the prevention efforts have not been effective in regards to frequent binge drinkers
(Keeling, 2002). These prevention efforts may have helped in increasing college
students’ prevalence rates of abstinence but the problem of excessive drinking (which
leads to the harmful effects) has not been solved and has not shown a decline (Wechsler
et al., 2000). There has been a lot of effort on the part of administrators, community
leaders, and even students to change the patterns of dangerous drinking. These efforts
have included: peer educators, social marketing campaigns, “social norrning” campaigns,
educational materials and classes, student assistant programs and not without the
multitude of grants, campus-community coalitions, and concerned leaders.

The “hot” intervention program that almost half (48%) of all colleges and
universities have or are currently conducting is a social norms campaign (Wechsler,
2003). Social norms campaigns were developed and heavily marketed in the 1990’s.
This approach emphasizes that students over-estimate the number of peers who are
drinking and drinking heavily. The premise of this campaign is that if these
misperceptions are corrected and students are educated that there is a much smaller

percentage of actual alcohol use and abuse, the actual drinking percentages would

34

decline. In other words, the higher the perceived level of drinking, the more students will
engage in drinking alcohol. There have been equivocal ﬁndings in the research
conducted on “social norrning”. While evidence exists that social norm interventions
reduce alcohol consumption among college students (Barnett, Far & Mauss, 1996; Gilder,
Midyett, Mils-Novoa, Johannessen & Collins, 2001; Haines & Spear, 1996; Johannessen,
Collins, Mils-Novoa & Gilder, 2000; Peeler, F ar & Miller, 2000), there are others who
have not found it to have any signiﬁcant change in students’ drinking patterns (Clapp,
Russell, & DeJong, 2001; Granﬁeld, 2002; Werch, Pappas, Carlson, Diclemente, Chally,
& Sinder, 2000; Wechsler et al., 1997).

Evaluations of social norms marketing campaigns have been conducted on single
college campuses and have not used equal comparison groups. As well, design ﬂaws
such as lack of random sampling limit any kind of conclusions about the programs’
effectiveness. Scientiﬁc studies should be employed with acceptable and valid research
methods to determine the true effectiveness of social norms campaigns (Wechsler, 2003).
Using data from all four of the data sets from the CAS research studies and addressing
the ﬂaws of the previous research, Wechsler (2003) found almost all of the institutions
used in the studies employed social norms programming and showed no decreases in any
kind of alcohol drinking patterns.

So what will have a positive effect in helping to reduce dangerous drinking
patterns? Wechsler et al., (2002) argues for tougher penalties for alcohol-associated
violations of standards of conduct, limiting students' access to alcohol, and controlling
marketing practices of the alcohol industry. Such control measures have much greater

empirical support (Holder etal., 2000; Shults et al., 2001; Substance Abuse and Mental

35

Health Services Administration, 2001; Toomey & Wagenaar, 2002). Using data sets
from the CORE and the 1994 Fund for the Improvement of Post-Secondary Education
(F IPSE), Ziemelis, Bucknam, and Elfessi (2002) sponsored drug-prevention programs
that criticized Wechsler’s et al.’s (2000) ﬁndings that educational approaches had not
helped decrease binge drinking rates. Ziemelis et a1. problem with the CAS data set is
that accurate assessment of the effectiveness of prevention programs can not be measured
because the CAS could not detect whether or not schools had existing prevention
programs in place before the surveys were administered. However, the CORE data and
the F IPSE data do account for programs already in place. Ziemelis et a1. (2002) found
that signiﬁcant changes occurred in their sample of 94 institutions regarding alcohol use
from institution to institution. Their recommendations for alcohol programs included a
three-construct model consisting of student participation and involvement, educational
and informational processes, and campus regulatory and physical change efforts in
addition to alternative activities, curriculum infusion, social norms, and alcohol
restrictions/banning.

Keeling (2002) argues that the college environment needs to be changed along
with involving students in the environmental program model. He also points out that
there is room for combining the social-environmental approach that Ziemelis et a1. (2002)
are advocating as well as the regulation approach that has been identiﬁed by Wechsler et
al. (1997). Keeling (2002) encourages environmental strategies such as alternative late
night events and activities lasting well into the early morning hours, keg restriction,
legislation to eliminate drink specials, control over liquor licenses, restrictions on alcohol

advertising, and student leadership development programs.

36

Finally, the NIAAA Task Force on College Drinking (2002) has identiﬁed a 3-in-
l framework for a comprehensive program based on the research. Their
recommendations include implementing programs at three different levels: (a) the
individuals, including frequent, episodic drinkers, (b) the student population as a whole,
and (c) the institution and the community. The individual level should consist of
strategies to assist individuals who have been identiﬁed as a problem, at-risk or alcohol-
dependent drinker. These would include alcohol screenings and intervention services.
Strategies that address the second level, the student body as a whole, would include
hindering the availability of alcohol, preventing the widespread social and commercial
promotion of alcohol, ﬁlling large amounts of student free time with desirable activities
that students would be attracted to, enforcement of campus policies and laws, and social
norm campaigns. Lastly, the college and community must reinforce interventions
together allowing for alliances among student affairs ofﬁces, residence life directors,
local police, and retail alcohol establishments to work cooperatively in resolving student

alcohol issues (Hingson & Howland, 2002; Perry & Kelder, 1992).

Alcohol and Athletics

Patterns of Alcohol Use

The NCAA has taken the lead in examining the use of drugs and alcohol among
collegiate athletes with funding national studies published in 1984 (Anderson & McKeag,
1985), 1989 (Anderson, Albrecht, & McKeag, 1991), and 1993 (Anderson et al., 1993),
and 1997 (Green et al., 2001). These studies involved thousands of athletes from many

sports and from institutions from all throughout the United States. These studies provide

37

important data in documenting trends in the alcohol and drug use habits of college
athletes. Other major data sources that have examined college athletes include Wechsler
and his colleagues (CAS) and Presley and his colleagues (CORE). Results ﬁ'om these
nationally represented studies are examined throughout the literature review.

Though research has explored the relationship between sport participation and
alcohol use there is still much to be learned. In one of the only studies done before the
19808, Straus and Bacon (1953) theorized that athletes would be less likely to drink
alcohol than their non-athlete peers to maintain top physical ﬁtness and because they
would have less time to devote to social activities. Using 15,747 students from 27
colleges, the researchers found that athletes reported drinking more than their non-athletic
peers. Results showed 87% of male athletes compared to 77% of male non-athletes
consumed alcohol. More female athletes (60%) drank than female non-athletes (52%).

Research in the 19808 and early 19908 concluded overall that athletes' alcohol
patterns were similar to those of their non-athlete peers as well as the numbers that have
been found for society at large (Anderson & Snelhnan, 1986; Duda, 1984; Gay et al.,
1990; Toohey, 1978; Toohey & Corder, 1981). In one of the ﬁrst published studies of
college athlete drug use, Toohey and Corder (1981) reported the nonmedical use of drugs
of 50 female and 17 male swimmers at six American universities and compared their use
rates with 678 non-athletes. Ninety-two percent of the athletes reported they used
alcohol. The researchers found that the use of alcohol and drugs by athletes was similar
to use of their non-athlete peers. Other studies of athlete and non-athlete alcohol
consumption among college students lend support to the idea that alcohol use by athletes

and non-athletes is similar. Anderson and McKeag (1989) found 88% of the athletes

38

reporting alcohol use in the preceding 12 months. These ﬁndings were somewhat lower
but still comparable to alcohol use reported by college students in a national survey
conducted by Johnston et al., (1994). Overrnan and Terry (1991) found no signiﬁcant
differences in alcohol use between athletes and non-athletes in a study of students from
two state universities and two private colleges. However, they found evidence indicating
that drinking patterns may vary between athletes and non-athletes. They concluded that
male non-athletes drink signiﬁcantly more during the week than male athletes, who
tended to drink more on weekends or special occasions. Also, athletes reported drinking
more beer than non-athletes; perhaps this reﬂects the inﬂuences of marketing strategy of
beer distributors associated with participation in sport.

Furthermore, Anderson et al. (1991), in a survey of 2,282 varsity athletes,
contracted by the NCAA, found that the annual rate of athletes’ alcohol use was 90%
while the college population was 92%. Very few studies found athletes less likely to
drink alcohol (Kokotailo et a1, 1996; Koss & Gaines, 1993). Most recently, however,
Green et al. (2001) conducted an expansion of the NCAA surveys and found annual
alcohol use among athletes to have dropped to 81%. Still other studies found results
supporting the research that athletes consume more alcohol than the general student
population (Leichliter et al., 1998; Selby, Weinstien, & Bird, 1990; Toohey, 1978).

However, the trends in alcohol drinking patterns among college athletes have
shifted since the mid to late 1990’s. These trends include more athletes choosing to
abstain from alcohol while the smaller percentage of athletes that are using have shown
an increase in the frequency and amount of alcohol being consumed (Green et al., 2001;

Leichliter et al., 1998; Nelson & Wechsler, 2001).

39

Interestingly, there has been little research that addressed athletes’ alcohol use at
different times of the year. O’Brien (1993) found that despite a high reported use of
alcohol among athletes, the actual amount of alcohol consumed by athletes in training is
low. In another study, using 247 athletes from a major private university, 60% of male
athletes used alcohol at least once a week during their off season but decreased to 42%
during the competitive season. Results for women were similar, 41% drank during the
off-season and 26% drank during the competitive season (Selby et al., 1990). Finally,
Thombs (2000), using 297 athletes, representing 18 teams at a public university in the
Midwest, found 37% of the athletes abstaining during the season of competition.

The deﬁnition of binge drinking is heavy, episodic alcohol consumption usually
consuming ﬁve or more drinks in any one sitting for men and four drinks for women
(Wechsler et al., 1994). Although the annual prevalence rate of drinking from 1985 to
1989 decreased among athletes, the rate of binge drinking rose (Anderson et al., 1991).
Drinking three or more times a week was reported by 29% of the athletes in 1985 while
that percentage dropped to 20% in 1989. On the other hand, the quantity of alcohol
consumed at each sitting increased during the four year span: 36% drinking an average of
six or more drinks in 1985, compared with 43% in 1989. Wechsler et al., (1997), using
the CAS data set, surveyed 17,251 college students from 140 American colleges,
examined binge drinking and different levels of involvement in athletics. The researchers
found 61% of the men involved in athletics (those who spent at least 1 hour per day
involved in intercollegiate athletics and thought intercollegiate sports were important)
engaged in binge drinking while 55% of men partly involved in athletics (those who

spent 1 hour per day involved in intercollegiate athletics or thought intercollegiate sports

40

were important) were binge drinkers. Among the men not involved in athletics, only
43% were binge drinkers. Women’s results were similar. In addition, 29% of male
athletes and 24% of female athletes engaged in binge drinking three or more times within
the past 2 weeks compared to 18% of male non-athletes and 15 % of female non-athletes.
The authors found the more involved one was in athletics the higher the binge drinking.

Similarly, Leichliter et al. ( 1998) used data from 51,483 students at 125
institutions and found binge drinking rose for men and women as the degree of athletic
involvement increased. For males, 45 % of the non-participants reported binging, 61% of
athletic team members binged and 64% of athletic team leaders binged. For female non-
participants, the hinge rate was 31%, for athletic team members it was 47%, and for
athletic team leaders it was 49%.

Additionally, Nelson and Wechsler (2001), using another CAS data set, analyzed
responses from 12,770 college students from 130 colleges and universities and reported
that athletes binged at higher rates than non-athlete students. Among the male students,

5 7% of athletes reported binge drinking at least once during the previous 2 weeks
compared to 49% of the male non-athletes. Among the females, 48% of athletes reported
binge drinking, while 40% of non-athletes did so. They concluded that athletes are more
likely than non-athletes to be surrounded by the type of social environment that is
associated with binge drinking. These include having ﬁve or more close friends,
considering parties as important to them, spending an average of 2 or more hours per day

socializing, and having more friends that are binge drinkers.

41

Gender Diﬁ'erences in Athlete Alcohol Use

Overall, research shows that male athletes tend to drink more often and binge
drink more than female athletes. Wechsler et al. (1997) found 61% of the men involved
in athletics engaged in binge drinking compared to 50% of women athletes. In addition,
21% of the male athletes drank to get drunk compared to 12% of women athletes.
Nelson and Wechsler (2001) found similar results. Using 12,770 college athletes from
130 different institutions, 57% of male athletes reported binge drinking during the past 2
weeks compared to 48% of female athletes. Selby et al. (1990), using 247 varsity
athletes at a major private university from 27 varsity athletic teams, found there were
signiﬁcant sex differences in alcohol use during the off season. Sixty percent of male
athletes and 41% of female athletes used alcohol at least once a week during their off
season. During the competitive season, alcohol use decreased to 42% for the men and
26% for the women.

In a study using 271 athletes at two Midwestem universities, gender differences
showed the male athletes had a higher prevalence of risk behaviors (swimming under the
inﬂuence of alcohol, driving under the inﬂuence of alcohol, riding in a car with a driver
who was under the inﬂuence of alcohol) than their male non-athlete counterparts, while
female athletes had fewer risk behaviors than their female non-athlete counterparts
(Kokotailo etal., 1996). Overman and Terry (1991) found no differences between male

and female athletes in frequency or in amounts of alcohol consumed.

42

Alcohol Consumption Across Diﬁ’erent Sports

There has been little research conducted examining differences in alcohol
consumption across different sports. Future research needs to focus on the differences
between sports speciﬁcally to determine if any patterns emerge among certain types of
sports (individual sports vs. team sports, contact sports vs. noncontact sports, aerobic
sports vs. anaerobic sports, media driven sports vs. nonmedia driven sports, and sports
with a long length of season vs. sports that have a short length of season). Of the few
studies that have aimed to separate the sports, they have found that different sports tend
to have different drinking patterns. Lyons (1998), in a study in Great Britain, found
traditional ﬁeld sports such as rugby, cricket, hurling, soccer, and Gaelic football had
athletes who consumed the most alcohol compared to other sports like cycling, horse
racing, and tennis.

In a replicated NCAA study of 2,282 athletes from colleges across the country,
Anderson et al. (1991), found that the highest rates of alcohol use were from male tennis
players (96%) and the lowest were ﬁ'om female tennis players (83%). Other sports to
note included a low rate of alcohol use in men’s basketball (78%) and a high rate of use

in men’s football (90%) and women’s swimming (93%). Explanations for these sport—

speciﬁc patterns were not investigated.

University/College Divisions in Alcohol and Drug Use

Green et al. (2001), using data item the NCAA Study in 1997, found the
likelihood of athletes using alcohol, amphetamines, marijuana and psychedelics was

highest among Division III schools (82.6%) compared to Division II (79.7%) and

43

Division I (79.2%). The NCAA (2001) found mostly the same result in their 2001 data.
These alcohol percentages are based on alcohol use within the previous year not binge
drinking. Clearly, there are different variables involved in drug and alcohol use when
comparing different sizes of schools. Schools that are smaller have also been reported to
have higher drinking patterns than schools that are larger (NIAAA, 2002). It could be
speculated that Division HI athletes have more time to socialize because they spend less
amount of time in their sport since they are attending a college that promotes being a
student ﬁrst. Not being paid to play (being on scholarship) might also contribute to some
athletes feeling that they do not feel as much responsibility to their sport or do not take it
as seriously as others who would be on scholarship. There is a growing number of
schools that are becoming members of Division III. There is a plethora of applications
from NAIA schools that are seeking to become a part of Division III in NCAA because
they are not satisﬁed with the operations of NAIA. In fact, Division III membership in
NCAA has arisen to 435 member schools with projections by the year 2010 to be around
450 member schools (NCAA Report, 2003). Because of this continual growth, the

variables that cause Division III athletes to drink more alcohol need to be identiﬁed and

examined with future research.

Athletes and High-Risk Behaviors

Research has examined whether athletes, in addition to college students, may also
be at an increased risk for other unhealthy lifestyle behaviors. Anderson et al. (1993)

compared the results ﬁom their previous two studies in 1985 and 1989 on substance use

anda

NCA

 

 

 

 

 

and abuse habits of college student-athletes. In this study, 2,505 varsity athletes from 11

NCAA institutions were surveyed. The authors found the following trends:

1)

2)

3)

4)

5)

While the number of occasions that athletes reported drinking was
fewer, the amount of alcohol consumed on each occasion
increased.

Use of anabolic steroids had increased in Division II and Division
III colleges.

Smokeless tobacco use dropped slightly among baseball, football,
and softball athletes but increased among basketball, tennis, track
and swimmers.

Over 26% of male athletes and nearly 6% of female athletes
reported having at least four different sexual partners in the
preceding 12 months. Of the sexually active student-athletes,
approximately 22% reported they “rarely or never” used a condom
when they had sexual intercourse.

Approximately 10-12% of the student-athletes reported a history of

at least one sexually transrrritted disease.

Nattiv and Puffer (1997) using a total of 2,298 athletes from around the country

and 683 randomized non-athlete controls, found male athletes had more risk-taking

behaviors than female athletes. Also, athletes involved in contact sports demonstrated

more risk-taking behaviors than did athletes in noncontact sports. Overall, athletes

demonstrated signiﬁcantly higher risk taking behaviors than non-athletes in the following

ways: less likely to always to use seatbelts; less likely always to use helmets with

45

motorcycles, moped, and bicycles; more often drive as a passenger with a driver under
the inﬂuence of alcohol or drugs; greater quantity and frequency of alcoholic beverages;
greater frequency of smokeless tobacco and anabolic steroid use; less-safe sex; greater
number of sexual partners; less contraceptive use; and more involvement in physical
ﬁghts.

In a study of 271 athletes and 775 non-athlete peers from two large Midwestern
universities, Kokatailo et a1. (1996), found risk-taking behaviors varied by gender. Male
athletes reported higher risk behaviors than their male non-athlete peers while female
athletes were found to have fewer risk behaviors than their female, non-athletic peers.

Bakker (1996) using 1,539 athletes in fall sports seasons from Division HI schools
in the Midwest similarly found the differences in high-risk behavior scores were
signiﬁcantly higher for males than for females. Also, high-risk behavior scores were
higher for athletes than non-athletes. Nattiv and Puffer (1991) examined the health risk
behaviors of athletes and non-athletes at UCLA. In the area of alcohol, athletes
consumed greater quantities of alcohol per sitting, drove more frequently while
intoxicated, and rode with a driver who was intoxicated more ﬁ'equently. One limitation
to the study was that it was conducted at only one university. Another weakness to this
study was that the control group of non-athletes consisted of students in an Introduction
to Psychology course. Thirty percent of the population ﬁom the control group was of
Asian ethnicity while only 4% of the athlete’s population was Asian. In addition, the

non-athlete group consisted of mostly freshmen while the athlete group was composed of

mostly upperclassmen (Nattiv & Puffer, 1991).

46

 

 

WI

U12

The research shows that athletes, in general, demonstrate higher risk behaviors
than the general college population. However, this research is only descriptive in nature.
It does not provide the reasons behind the behaviors. For prevention strategies to be
successful, researchers must examine the underlying reasons for risk-taking behaviors

Some athletes turn to drugs to improve their level of performance (Wadler &
Hainline, 1989). This is one area for reasons why athletes are at a greater risk. However,
this paper will not address the issue of performance enhancing drugs but instead focus on
recreational or social drug use—speciﬁcally alcohol. One theory that has been
researched as to why athletes demonstrate greater risk behaviors is the notion that they
are under more pressure or stress than non-athletes. These would include pressures to
perform, missed class, academics, time commitments, stress, and dealing with pain
(Chappel, 1987; Clement, 1983; Ogilvie, 1981). Athletes are expected to maintain high
levels of performance, often in the face of tremendous stressors. They are under constant
scrutiny by the public, ﬁiends, family, and the media.

Tricker, Cook, and McGuire (1989) discussed a number of hypotheses regarding
how the sports experience may place college athletes at a higher risk for alcohol and drug
abuse. Athletes experience many risks directly related to the rewards and ﬁ'ustrations of
athletic competition. Additionally, athletes’ lifestyles often involve excessive travel and
exposure to social settings to represent the school that frequently include the use of
alcohol.

Social settings provide athletes with increased opportunities for using alcohol as
well as other drugs. Because a natural part of sports includes risk-taking, some athletes

may regard the risks of drug abuse inconsequential (Thibault, Lambert, Rivard, Brodeur,

47

& St. Jacques, 1984). As risk-takers, some athletes may feel invulnerable, believing that
no harm will come to them (Tricker et al., 1989). ). Leichliter et al., (1998) speculated
that athletes may experience a “work hard, play hard” ethic to a greater extent than non-

athletes.

Consequences Specific to Athletes

Not only have college athletes been found to have higher prevalence rates of
alcohol consumption and drink signiﬁcantly more per occasion than non-athletes, they
also have been found to experience more drinking-related consequences including
engaging in more sexual violence than their non-athletic peers (Frintner & Rubinson,
1993; Nattiv & Puffer, 1991). Nattiv and Puffer (1991) surveyed athletes and non-
athletes from a major collegiate institution and found signiﬁcantly more athletes (49%)
engaged in driving under the inﬂuence of alcohol and riding with intoxicated drivers than
non-athletes (12%). The athletes also reported having more sexual partners (athletes,
28%; non-athletes, 12.7%) as well as contracting sexually transmitted infections (STI)
than non-athletes (athletes, 11.6%; non-athletes, 2.8%), and less frequent seatbelt use
(athletes, 47%; non-athletes, 26%). Frintner and Rubinson (1993) found that although
male athletes made up less than 2% of the male campus population at a large Midwestern
university, they were involved in 20% of the reported attempted sexual assault cases and
sexual assault cases, 14% of the cases on campus sexual abuse, and 11% of the battery
cases.

Leichliter et al. ( 1998), using 58,453 students from the CORE data set from

between 1994-1996, found that athletes experienced 18 of 19 consequences signiﬁcantly

48

more than non-athletes. These included hangover, impaired academic work, trouble with
police, vandalism, arguments or ﬁghts, nauseated or vomited, driving under the inﬂuence,
missed class, memory loss, regretting actions, arrested for DUI, been taken advantage of
sexually, taken advantage of someone sexually, and been hurt or injured. The only
consequence that was not found to have a signiﬁcant difference was feelings and attempts
of suicide. Interestingly, male athletes who were in formal leadership positions (captains)
were found to have experienced more consequences than the member male athletes and
the non-athletes. For the females, there were 14 signiﬁcant differences between athletes

and non-athletes but few differences between female athletes in formal leadership

positions and member female athletes.

A particular consequence of alcohol use for athletes is its effect on physical
performance. The American College of Sports Medicine (1982) conducted a
comprehensive analysis on the effects of alcohol on physical performance. Findings
showed that acute ingestion of alcohol has a deleterious effect on many psychomotor
skills. Researchers concluded that in sports involving rapid reactions to changing stimuli,
small to moderate amounts of alcohol will impair reaction time, hand-eye coordination,
accuracy, balance, and complex coordination of gross motor skills. According to the
American College of Sports Medicine (1982), alcohol appears to have little or no
beneﬁcial effect on the metabolic and physiological responses to exercise. In the studies
reporting signiﬁcant effects, the change appears to be detrimental to performance.
Alcohol consumption does not substantially inﬂuence physiological function crucial to
physical performance (maximal oxygen uptake, respiratory dynamics, and cardiac

function). Alcohol ingestion will not improve muscular work capacity and may decrease

49

performance levels. O’Brien (1991) found that the consumption of alcohol in the 24
hours prior to athletic activity signiﬁcantly hindered aerobic performance by 11.4%.
Finally, results showed that alcohol may impair temperature regulation during prolonged
exercise in a cold environment. Other research suggests that the acute ingestion of
alcohol also decreases performance levels. Bond, Franks, and Howlett (1983) found that
total cycling time to exhaustion was always shorter after alcohol use compared to the
subjects in the placebo group. Another study found serum alcohol concentrations over
IOOmg/dl weakened the pumping force of the heart (Lang, Borow, & Neumann, 1985).
Houmard, Langenfeld, and Wiley (1987) examined 18 male runners who underwent a 5
mile treadmill run and found the average running time was 28 seconds longer after
alcohol consumption.

Acute ingestion of alcohol should be discouraged to avoid the negative effects on
athletic performance. The acute ingestion of alcohol before exercise or competition
should be discouraged, as it adversely affects sports performance. These practices are
probably most prevalent in recreational athletes in traditional sports such as slow-pitch
softball, rugby, and football (Fox, 1984; O’Brien & Lyons, 2000). When interpreting the
results of these studies it is important to keep in mind several precautions. First, there are
varying reactions of alcohol consumption, not only among individuals, but also within an
individual depending on the circumstances. Second, it is ahnost impossible to do double-
blind placebo research with alcohol because subjects can usually tell when alcohol has
been consumed and when they were given the placebo.

A reason for concern of acute alcohol consumption before activity is that it can be

a prelude for many medical problems as well as resulting in possible death. The use of

50

alcohol before any aquatic sport should be outlawed; as there is always the potential for a
catastrophic outcome to an accident or emergency in the water. Branche, Sniezek, and
Sattin (1991) found that alcohol was reported to be a signiﬁcant factor in spinal injuries.
The people involved in spinal cord injuries while doing recreational water sports were
shown to have consumed alcohol signiﬁcantly more than a control group.
Michalodimitrakis and Patsalis (1987) found that when using alcohol, scuba divers
experienced the potentially fatal ‘nitrogen narcoses at shallower depths than did scuba
divers who abstained from alcohol. In a study of 753 drowning victims, 53% tested
positive for alcohol and 38% had blood alcohol concentrations of 100mg/100ml of blood
or greater (Patetta & Biddinger, 1988). Other acute effects of alcohol include vestibular
system dysﬁmction which affects activities that require excellent balance (O’Brien &
Lyons, 2000), weakening of the left ventricle contraction (Strauss, 1991), and exercise
induced asthma (Nichols, 1992). Also, Heath, Ford, and Craven (1991) found that male
runners who consumed alcohol reported greater incidence of upper respiratory tract
infections than those runners who did not consMe alcohol.

The pattern of a long-term chronic abuse of alcohol may have its beginning in the
post-match social sports setting (O’Brien, 1993). This trend could continue after the
athletes’ years in competition end and continue with social events surrounding sporting
events but from a spectator’s perspective. Athletes are not immune to long-term effects
of alcohol later in life. These chronic conditions include liver toxicity, endocrine
dysfunction, decreased serum testosterone, seizures, and altered lipid metabolism

(O’Brien & Lyons, 2000). Furthermore, when alcohol use turns to abuse and possibly

dependence, there is serious risk of mortality.

51

Alcohol and injury have also been examined. O’Brien and Lyons (2000) reported
that there is a signiﬁcant difference in injury rates between athletes who consumed
alcohol and those who did not. Athletes who drank alcohol at least once per week had a
much higher injury rate (54.8%), more than double that of athletes who were nondrinkers
(23.5%). These ﬁndings included every sport. The study which included 423 athletes,
showed that 58% of the elite athletes surveyed consumed an alcoholic beverage before
competition or scheduled training (Lyons, 1998; O’Brien, 1993). Caution needs to be
taken in making conclusions, for it is important to consider which variable could be the
cause and effect. Does regular alcohol use increase chance of injury or could athletes
who become injured consume more alcohol on a regular basis than their non-injured
teammates? Could athletes who drink alcohol be more prone to injury because they are
prone to have more risk-taking tendencies compared to athletes who do not drink
alcohol? There is much more research that needs to be conducted in this area. If it were
indeed concluded that light or moderate alcohol use during the competitive season or
during training causes an increase in injury or hurts performance, this could be a major
incentive for athletes to abstain from drinking alcohol. Wechsler et al. (1999) found the
number one reason for athletes not drinking alcohol was because of effect on
performance.

In a study of post-alcohol ﬁtness assessments (O’Brien, 1993), rugby players
were asked to consume their normal Friday night quantity of alcohol. No particular
quantity of alcohol was speciﬁed. All volunteers had a similar night’s sleep, and all had a
similar food intake for breakfast. They were asked to return to training 16 hours later,

and post-alcohol (hangover) ﬁtness assessments were then performed. The amount of

52

alcohol consumed was calculated in standard units of alcohol. The results of the
experiment showed that alcohol hangover had a signiﬁcantly negative effect on aerobic
performance. On average, the athletes performed 11% worse in the hangover phase.
Any quantity of alcohol produced a negative effect on aerobic performance. Anaerobic
performance was unaltered by the consumption of alcohol. O’Brien concluded that the
hangover effect of alcohol produced a signiﬁcant decrease in aerobic performance after
varying amounts had been consumed. O’Brien postulated that the decrease in aerobic
performance observed can be explained by the metabolic effects of alcohol which
include: (a) the effect on the citric acid cycle which slows aerobic metabolism, (b) the
effect on the lactate and pyruvate ratio which is a factor in poor aerobic performance, (c)
the dehydrating effect which is associated with reduction in aerobic performance, (d) the
effect on available carbohydrates for fuel needed for energy production, and (e) the
psychological effect of not feeling like they can compete to their potential. Similar
ﬁndings of the hangover effect were found in a group of pilots who were tested for

visual-motor co-ordination assessment before and a day after a small amount of alcohol

had been consruned (Y esavage & Leirer, 1986).

Limitations to the Research

There are some limitations to the studies reviewed. Many of the studies on
college athletes have been conducted on a single college campus or a few college
campuses in close proximity to each other and thus may not be generalized to the whole
population of intercollegiate athletes. This could account for the variation in ﬁndings.

The reported ﬁndings from the few existing multicollege studies may also not be

53

generalized because random sampling was not used. Other studies sampled athletes from
only one sport or used data ﬁom colleges in one state only.

Another limitation to the research is the different deﬁnitions of alcohol use when
reporting percentages of alcohol use by athletes and non-athletes. Some studies have
reported alcohol use as consuming any amount of alcohol within the last year. Another
study (O’Hare, 1990) used the deﬁnition of alcohol user if subjects drank 2 times within
the last year. While yet others used the scale of drinking within the last month or 2
weeks. When interpreting the data, it is important to ﬁnd out what criteria were used to
determine the subject’s rating as being a drinker or nondrinker. It is crucial that the
percentages of these studies using different criteria should not be compared in the same
way. Furthermore, most of the studies conducted did not take into consideration the time
of the year for the athletes. O’Brien (1993) and Selby et a1. (1990) found that athletes
consumed signiﬁcantly less alcohol during their competitive season. If these ﬁndings are
true for the entire athletic population, then the time of the study as well as what athletes
from what sports athletes are being surveyed could end up with drastically different
results. Other limitations of most of the research studies included self-reported surveys in
which subjects could have misinterpreted questions. Also, the subjects were asked to
provide sensitive and personal information, which could cause underreporting or over-
reporting.

Although many of these studies were important initial efforts, it remains difﬁcult
to draw valid conclusions about the current alcohol and drug habits of all college athletes.
Comparisons among the studies are difﬁcult because many of them were conducted 5 to

15 years ago when alcohol and drug use were deﬁned differently, surveyed different

54

types of drugs, used different surveying instruments and procedures, and because as
social disapproval/acceptance of drug use changes so will the trends of use change. In
addition, as mentioned previously, most of the research on alcohol use patterns in college
student populations and college athletes is only descriptive. The research does not
examine the reasons behind the differences in alcohol use patterns, which is necessary to

developing successful prevention programs.

Future Directions and Considerations

The research ﬁndings up to the present time indicate that college healthcare
providers and educators need to pay more attention to the alcohol use habits of student-
athletes. Although coaches and team regulations almost always prohibit alcohol use
during the playing season or before competition, the research shows that, as a group,
athletes drink more, binge drink more, and drink more often than do non-athletes. The
majority of research in the area of alcohol and athletics has compared athletes’ alcohol
consumption rates to those of the student population. The results have varied with some
studies ﬁnding the percent of athletes’ use slightly above the percent of the student
population and some have found the percent to be the same or slightly lower than that of
the student population. It cannot be disputed that regardless of the ﬁndings, athletes are
consuming alcohol at a high percent, and there are many questions yet to be answered in
regard to this topic. There has only been one study to examine alcohol use in athletes at
different divisions in colleges/universities (Green et al., 2001). There has also been only
one study conducted to look at leaders/captains alcohol use compared to team members’

use (Leichliter et al., 1998). Furthermore, it would be important to examine the

55

relationship between leaders’ alcohol use and its relationship to their speciﬁc team
members’ alcohol use. There has not been any research conducted in this area. To go a
little ﬁrrther, how would the leaders’ alcohol use affect new members of the team’s
alcohol use? Are the new members’ decisions to use alcohol inﬂuenced by the leaders of
the team?

Few studies have been conducted examining alcohol use in speciﬁc sports and
why the differences between sports. An investigation of students’ substance use and
related consequences, according to not only the speciﬁc sports but also the type of sport
(team vs. individual, contact vs. non-contact) could possibly prove to be of considerable
interest. As indicated, the research has only begun to tap into the complicated puzzle of
athlete alcohol use and abuse. There also needs to be more research on the speciﬁc
genders with alcohol use and what is unique about each gender that might inﬂuence
alcohol use or help inhibit the abuse of alcohol. Finally, now that researchers have a
good outlook on the patterns of alcohol use within certain subgroups, it is time to
examine and identify different variables within these subgroups that promote positive
decisions regarding drinking. The success of existing and future programs of alcohol use
prevention and intervention will rely particularly upon the cooperative and collective
efforts of athletes, captains, coaches, trainers, athletic administrators, health educators,

and sport psychologists. Future research could also include alcohol information with

intramural athletes.

56

Conclusion

The major focus of prevention techniques for any college population must provide
more than just information about risk factors. Education must also include information
on dealing with motivations, non-chemical alternatives, the decision-making process, and
the effects on human performance (Gay et al., 1990). College athletes have been targeted
for education programs that address alcohol use. The NCAA has developed and
sponsored drug and alcohol education programs and a speakers’ program targeted
speciﬁcally for athletes in their member schools. The NCAA also runs a program called
the Professional in Residence program at the Betty Ford Center. This program educates
university ofﬁcials and coaches on alcoholism and drug addiction which gives athletic
administrators and coaches, ﬁrst hand, an understanding of the warning signs of an
alcohol abuser as well as education on what athletes and students need to do to get help if
they have a dependency on alcohol and/or other drugs. Another program the NCAA has
established to help athletic programs with alcohol, tobacco, and other drugs is the
Athletic Prevention, Programming and Leadership Education (APPLE) model. This
prevention program is tailored speciﬁcally for college athletic departments to help
develop a comprehensive, site-and-team-speciﬁc program to educate athletes on
substance abuse and to encourage responsible decision-making (Grossman & Smiley,
1999)

However, education alone has not sufﬁciently impacted the problem. The
ﬁndings in the last few years indicate that the percentage of athletes using alcohol is
decreasing slightly but the rate of binge drinking among athletes is increasing. Binge

drinking by athletes is becoming a growing concern. Nelson and Wechsler (2001) found

57

that athletes who received education on both the acute and chronic risks of alcohol were
not less likely to binge drink than those who did not receive education. In addition to
education, future prevention efforts targeted for athletes should address the unique social
and environmental inﬂuences on athletes. Programs need to take advantage of motives of
athletes for self-limiting alcohol intake. One topic that needs to get more attention is the
relationship between alcohol use and injury.

Prevention efforts need to also address the colleges’ policy making decisions
regarding alcohol use and abuse. Stricter reinforcement of alcohol policies, helping
lessen the availability of alcohol around campuses, and restricting the alcohol industry to
promote alcohol on campus and around athletic events are just a few of the things that
would help to change the culture involving alcohol among the college population.

Alcohol and drug abuse in sport must be considered within the context of the
drugs in society at large. Alcohol continues to be the most commonly used drug in the
athletic community. It is a depressant drug that, with inappropriate use, is associated
with both short term and long term morbidity and possible mortality. Education of young
athletes and coaches, along with addressing the unique social and environmental
variables of college athletics, could be a cornerstone in dealing with this epidemic of

alcohol abuse on college campuses.

58

Chapter 3

METHOD
Participants

The study included athletes from 42 Division III 4-year colleges throughout the

Midwest. The athletes used for the study were members of women’s softball teams.
Each team consisted of 16-22 softball players and their head coach. Athletes ranged in
age ﬁom 18-23 (M = 19.83) years. The athletes consisted of 36.6% freshmen, 28%
sophomores, 21.8% juniors and 13.3% seniors. These athletes competed at the national
level against other players from Division 111 teams. Ethnic origin was primarily white
Caucasian (94%). Almost 70% of respondents lived on campus and all were full-time
students except for one. It should be noted that since the subjects were all from Division

HI they were not given scholarships to play softball.

Measures

All participants completed the short form of the Core Alcohol and Drug Survey
(Presley et al., 1998), which is designed to assess various factors related to students’ drug
and alcohol use on college campuses (See Appendix E). The surveys were given to the
participants near the end of their softball season. The short form questionnaire consists
of 23 items and covers a variety of substantive areas, including demographics,
extracurricular activities, alcohol and drug use, perceptions of the campus environment,
campus climate, campus violence, and negative consequences that result from use of
alcohol or drugs. The questions involve various ordinal scales, with the exception of a

few of the demographic questions which are yes/no questions.

59

 

There were an additional ﬁve questions that pertained to the athletes’ perception
of their coach’s emphasis of obeying an alcohol or drug policy, perception of their
coach’s enforcing an alcohol or drug policy, if their team had additional restrictions to
any school alcohol or drug policy, consuming alcohol out-of-season, and if they were a
team captain. The questions pertaining to being a captain, and having additional
restrictions to any school alcohol or drug policy were answered on a yes/no scale. The
question asking how much emphasis the coach has placed on obeying an alcohol or drug
policy was on an ordinal scale of no emphasis, has emphasized on one occasion, has
emphasized on 2-3 occasions or has emphasized on 4 or more occasions. The question
asking the players to predict their coach’s enforcement of an alcohol and drug policy
included responses that the coach would look the other way, would confront and turn in
the player(s), or that they did not know. The surveys were anonymous -- no name or

identiﬁcation number was put on any forms. The survey is included in Appendix E.

Procedures

Following approval from the Institutional Review Board, 63 head coaches of
women’s collegiate Division III softball teams were contacted to explain the purpose of
the research and to seek permission allowing their athletes to participate. Coaches were
informed that the one-time survey would take 10-15 min. to complete and the
questionnaire should be administered by a team manager or athletic trainer near the
completion of their season. Once coaches had given their approval, the investigator
asked coaches for the contact person’s name and address so the questionnaires could be

sent out via mail. Also, coaches were asked a few questions which included:

60

How many members are on your softball team? This question was asked
to be able to determine response rate and to know how many
questionnaires needed to be sent.

How many team captains are on your team? This question was asked to
ﬁnd out if a team did indeed have captains and to determine response rates
of captains.

How were your captains chosen- were they elected by their teammates,
were they appointed by the coach or were they chosen by a combinations
of elected and appointed? This question was asked to be able to further
understand the nature of the captains on each team in relationship with

their teammates.

Questionnaire packets were mailed to the contact person, who then distributed the

questionnaires to the athletes. The contact person had the athletes complete the survey in

a classroom, monitoring that there was no talking while the survey was being completed,

and that the athletes were isolated enough to assure privacy. After the athletes completed

the consent form, they were given the questionnaire and an envelope. When the survey

was completed, athletes were asked to place the completed questionnaire in their personal

envelope and seal it and then put the envelope in a self-addressed, prepaid larger

envelope held by the administrator. When the last survey was completed, the onsite

administrator sealed the envelope and personally put it in the mail.

Coaches were contacted in Mid-March of 2004. Sixty three coaches were

personally contacted via telephone; 60 agreed to have their team be a part of the study.

61

Sixty were chosen so that the response rate would be a minimum of 40 teams to ensure
that the sample size was large enough for statistical power to analyze the data.
Participating coaches were selected from a national softball directory as well as from
coaches who were colleagues of the author. Participants were all from schools located in
a six-state Midwest region including: Illinois, Iowa, Michigan, Minnesota, Ohio, and
Wisconsin. Questionnaire packets were mailed between April 15 and May 15, 2004.
Questionnaire packets that were sent back were received between April 30 and May 31,
2004. Of the 60 questionnaire packets sent to the teams, there was a 73% response rate.
After taking a careful examination of the data, two teams were eliminated from the data
set for not being able to identify all of the captains.

Once the questionnaires were all sent to the investigator, the packets were given a
team and an individual number. They were then sent to the Core Institute at Southern
Illinois University to be scanned for the data analysis. The scanned data were then

returned to the investigator via ﬂoppy disk.

Treatment of the Data

Research Question 1. To answer Research Question 1: “Do team captains use
less alcohol and binge drink less than non-captain athletes?” a comparison of means and
percentages was conducted separately for determining binge drinking rates (Items 14)
and average number of drinks per week (Item 15). In addition, a factor analysis using
principal components with no rotation was conducted to create an index score for alcohol
use. A one-factor score measure on alcohol was produced using four items from the

survey including binge drinking (Item 14), average number of drinks consumed per week

62

(Item 15), annual rate of drinking (Item 17b), and number of times over the past 30 days
they consumed alcohol (Item 18b). Inspection of the eigenvalues from the factor analysis
suggested the presence of one large factor (3.06) which accounted for 76.5% of the
variance. A principal component factor analysis of the factor showed high loadings
which included: (a) past 30 day alcohol use (.92), (b) ﬁve or more drinks in the past 2
weeks (.88), (c) average number of drinks per week (.85), and ((1) alcohol use in the last
year (.85). Cronbach’s Alpha was reported at .68. A series of chi-square analyses were

conducted to examine negative consequences related to alcohol use (Item 21a-218).

Research Questions 2-4. To examine Research Questions 2, 3, and 4, alcohol use
data among the non-captains were aggregated to the team level for analysis using
hierarchical linear modeling (HLM: Raudensbush & Bryk, 2002). HLM was used
because it does not ignore the variability within teams that occurs when data are
aggregated, and investigators can examine both within team and among team variances
simultaneously. The team members’ data will be referred to as the non-captains’ data in
the analyses and results to make it clear that captains’ data are excluded in the team
means.

The ﬁrst step in the HLM process was to calculate the intraclass correlation
coefﬁcient (ICC) for non-captain use (the dependent variable of interest) to determine the
proportion of variance that is due to between team differences. If the proportion of the
variance in non-captain use is due to within team differences, this indicates that non-
captain use is inﬂuenced by the team and HLM is warranted. The ﬁrst model to be tested

in HLM is the individual-level model or unconditional model from which the ICC is

63

calculated. For the unconditional model of alcohol use, the within group or individual
level parameters ([3 coefﬁcients) were allowed to randomly vary across groups, resulting
in the following level model:

Level 1: ng (non-captains’ alcohol use) =/3 o,- + rij, where
, ﬂoj = the mean of non-captain use for team j,

rg- = the unique effect of athlete i for team 1'.

Level 2:]30j = 700 + “0}. where
_ 7’00 = the average team mean of non-captain use,

uoj = the unique effect of team j on the average team non-captain use mean.
Of particular interest in this model was the variance of r.) (the within team variance), and

the variance of uoj (the between team variance). These variances were used to estimate

the ICC of non-captain use.

The second model to be tested was the conditional model where the individual
level parameter ([30,) became the dependent variable in the team-level model. Because
Questions 2-4 posed three different predictors (captains’ alcohol use, coach’s emphasis,
and team alcohol policy) on the same dependent variable (non-captains’ alcohol use),
only one simultaneous multiple regression analysis was used instead of conducting three
separate regression analyses and increasing the possibility of making a Type I error.
Therefore the following conditional model was tested:

Level 1 Ya- (non-captains’ alcohol use) =ﬂ0j (non-captain mean for team j) + "ij
Level 2 ﬂo; = 700 + 701 + 702 + 703 + qu , where

700 = the weighted mean for ﬂojs’

701 = captains’ alcohol use,

1’02 = coaches’ emphasis,

64

7’03 = teams’ additional alcohol policy, and

uoj = the random effect.
Captains’ alcohol use was the predictor variable for Research Question 2 (Items 14, 15,
17b and 18b on the Core survey), coaches’ emphasis was the predictor variable for
Question 3 (Item 26 on the Core survey), and the teams’ additional alcohol policy was the
predictor variable for Question 4 (Item 25 on the Core survey).

A comparison of means and percentages was used to analyze binge drinking (Item

14), average number of drinks consumed per week (Item 15), annual rate of drinking
(Item 17b), and number of times over the past 30 days they consumed alcohol (Item 18b)
Analysis was conducted separately for items numbered 14 and 15. In addition, analysis

was conducted using all four items to produce an index, using factor analyses, to produce

a one-factor score on alcohol use.

65

Chapter 4
RESULTS
The results are organized around descriptive statistics and the four research
questions. The ﬁrst section describes some of the descriptive: statisticsstemming from
the Core Survey. This is followed by sections that analyze the four questions. Within
each question, descriptive statistics are presented ﬁrst, followed by inferential statistics.

All statistical analyses are reported at the .05 level of signiﬁcance unless otherwise

speciﬁed.

Descriptive Statistics

The ﬁrst use of alcohol was determined from responses on a 9-point ordinal scale
(See Item #16 in Appendix E). The average mean of the ﬁrst use of alcohol by all
players was between 15-16 years of age (M = 5.39, SD = 1.94). Captains’ mean average
age of ﬁrst alcohol use (M = 5.37, SD = 2.04) was very similar to non-captains’ age of
ﬁrst alcohol use (M = 5.40, SD = 1.92), F (1,614) = .03, p = .87. The highest percentage
of both captains’ and non-captains’ age of ﬁrst use of alcohol was between the ages of
18-20 (captains’ = 36.5%, non-captains’ = 31.6%) (See Table 1 in Appendix F).

The annual prevalence rate of alcohol use was determined ﬁ'om responses on a 9-
point ordinal scale (See Item 17 in Appendix E) of how often within the last year alcohol
was used. The average response by all players was between once or twice a month (M =
4.43, SD = 2.01) with the annual percentage rate being 85.6%. Using a comparison of
means, there was no signiﬁcant difference between captain use (M = 4.53, SD = 2.04) and

non-captain use (M = 4.40, SD = 2.00), F (1, 616) = .33, p = .57. When examining the

66

frequency of annual alcohol use, 12.3% of non-captains reported consuming alcohol three
times per week compared to 6.7% of captains. Conversely, 36.5% of captains drank
alcohol once a week compared to 26.3% of non-captains (See Table 2 in Appendix F).
For captains and non-captains, 33.1% reported no drinking in the past 30 days. Non-
captains (28.0%) reported a higher percentage of drinking 1-2 days compared to captains
(17.5%) but non-captains (20.0%) reported a lower percentage of drinking 3-5 times in
the past 30 days compared to captains (25.2%) In other words, there was a higher
percentage of captains drinking more often than non-captains even though the overall
percentage rates of drinking within the past 30 days were similar between groups (See
Table 3 in Appendix F).

In Table 4 in Appendix F, the data presented indicate the percentage of captains
and non-captains by how many drinks per week they had as well as the total percentage
for the entire sample. Players’ collective binge drinking (those who binged at least once)
in the previous 2 weeks of completing the survey was 46.9% (Captains = 50%, Non-
captains = 46.3%). Of interest, 16.3% of captains reported binge drinking 3-5 times over
the previous 2 weeks of the survey compared to 11.5% of the non-captains (See Table 5
in Appendix F). Athletes also responded to typical frequency of binge drinking out of
season. A comparison of percentages showed that captains' binge drank (71.2%) slightly
more than the non-captains (70.2%) with a total rate of 70.3% binge drinking when not in
season (See Table 6 in Appendix F). Of most interest, when comparing binge drinking in
season and out of season, 11.5% of the non-captains reported binge drinking 3-5 times

during the season compared to 25.0% when not in season. Table 7 in Appendix F

67

presents a summary of the percentages of drinking patterns between both the captains and

non-captains.

A series of chi-square analyses was conducted to examine negative consequences
related to alcohol use. The 18 consequences listed on the survey represented a variety of
personal, acaderrric, legal, health-related, and disciplinary outcomes. Findings for each of
the consequences, by team membership (team captain and non-captain) and the entire
sample, are shown in Table 8 (Appendix F). In general, there was one negative

consequence that was found to be signiﬁcantly different and that was experiencing a
memory loss with captains reporting higher rates (46%) than non-captains (38%) ( 12 (5)
= 14.76, p <.05). Having had an argument or ﬁght was close to being signiﬁcant with
captains reporting higher rates (41%) than non-captains (37%) (12 (5) = 10.54, p =.06).
The following consequences had no signiﬁcant differences between captains and
non-captains: hangover ([2 (5) = 1.63, p > .05), poor test score (12 (5) = 4.96, p >.05),
trouble with police (12 (5) = 8.42, p >.05), damaged property (12 (5) = 6.28, p >.05),
being nauseated or vomited ( 12 (5) = 1.76, p >.05), driving under the inﬂuence ( 12(5) =
10.02, p >.05), missed class (12 (5) = 3.07, p >.05), been criticized ([2 (5) = 9.16, p
>.05), thought I had a problem (12 (5) = 6.78, p >.05), later regretted action (12 (5) =
2.99, p >.05), arrested for DWI or DUI (12 (2) = 1.97, p >.05), been taken advantage of
sexually ( ,‘(2 (4) = 4.27, p >.05), have taken advantage of someone sexually ( 12(4) =
5.81, p >.05), tried—failed to stop (12(4) = 3.57, p >.05), thought about suicide(/1’2 (4) =

1.64, p >05), and been hurt or injured (12 (5) = 1.42, p >.05), Of all 18 consequences,

hangover (69.2%), nauseated or vomited (60.7%), regretted action later (41.7%), had a

68

memory 1088 (39.5%), and had an argument or ﬁght (37.6%) were reported the most often

(See Table 8 in Appendix F).

Alcohol Policies

All 42 schools reported having alcohol policies. The NIAAA website provides a
direct link to all colleges’ alcohol policies available online
(http://www.collegedrinkingprevention.gov/policies/mapresults.aspx?D1=MI). The
information that was collected from this website included 39 of the 42 schools that were
surveyed. The additional three policies were found on the schools’ website. All 42
schools reported a policy that consisted of two components: (a) No persons under the age
of 21 will be allowed to consume alcoholic beverages and (b) All persons 21 years or
older shall drink alcohol responsibly without disrupting any person around them or serve
alcoholic beverages to minors. Of the schools that were not alcohol-free campuses (N =
29) the policy allowed the consumption of alcohol within a person’s residence hall room
or campus house if over the age of 21 years. In addition to the school alcohol policy, 11
of the 42 teams reported an additional team policy regarding alcohol use. Nine of the 11
teams with an additional alcohol policy reported an abstinence stand during the season
while the remaining two had a policy that players who were of legal age could not use

alcohol within 24 hours of a practice or a game.

Research Question #1

The ﬁrst research question “Do team captains use less alcohol and binge drink

less than their teammates?” was answered by examining three drinking variables which

69

included the average number of drinks per week, number of times an athlete had ﬁve or
more alcoholic drinks during the past 2 weeks and an overall alcohol use index that
combined the ﬁrst two variables with how often during the past year the athlete used

alcohol and how often in the past month the athlete used alcohol.

Average number of drinks per week. To ﬁnd out whether or not differences
existed in the average number of drinks per week between all captains and non-captains
with disregard to nesting, a comparison of means was conducted. Results showed that
there was little difference between the two group’s average number of drinks per week.
Team captains reported that they drank slightly more than the non-captains, F (1, 615) =

.24, p = .63. See Table 9.

TABLE 9

Comparison of Alcohol Patterns Between Captains and N on-Captains.

 

Captains Non-Captains

1N=104L (N=514)
Average drinks per
week 4.13 3.82
SD 6.64 5.69
Average binge drinking
in Last 2 Weeks 2.00 1.89
SD 1.21 1.18
Average alcohol index
Score 0.08 -0.01
SD 1.05 0.99

 

Note. Average times binge drinking in the last 2 weeks (Item 14), 1= none, 2 = once, 3 =
twice, 4 = 3 -5 times, 5= 6 - 9 times, 6 = 10+ times.

70

Binge drinking. In addition to exploring the difference in average number of
drinks between captains and non-captains, the number of times binge drinking
(operationally deﬁned as the consumption of ﬁve or more alcoholic drinks in a sitting)
occurred during the last 2 weeks was also examined. Results showed no signiﬁcant
differences, F (1, 617) = .76, p =.38). Team captains reported that they binge drank once
over the past 2 weeks while non-captains’ reported on average slightly less than once
over the previous 2 weeks (See Table 9).

Alcohol use. Alcohol use by captains and non-captains also was examined with
the alcohol use index. Results showed no difference between the captains’ scores and the
non-captains’ scores, F (1, 614) = .80, p = .37 (See Table 9).

Overall, ﬁndings suggest that there is no signiﬁcant difference in the alcohol
patterns between the collective scores of captains and non-captains. Even though
statistically the results were not signiﬁcant, captains’ scores were all slightly higher in all

three categories: average number of drinks per week, binge drinking, and overall alcohol

use.

Research Questions #2-4

Descriptive statistics. To examine Research Questions 2, 3, and 4, alcohol use
data among the non-captains were aggregated to the team level. To better understand the
range of means from the 42 teams that were included in this study, a number of mean
comparisons were made (See Table 10). The average team mean score for average
number of drinks per week was about four drinks per week. The means ranged ﬁ'om no

drinks per week to 11 drinks per week. Average binge drinking over the past 2 weeks

71

‘ _-E
I'.

across teams was one time. Team mean binge drinking ranged from no binge drinking
over the past 2 weeks to binge drinking 2-3 times. There were three teams that reported
no binge drinking while two teams averaged 2-3 times of binge drinking over the past 2
weeks. The average use index also indicates a wide range of team scores. All three of
these variables show that the team's alcohol patterns ranged from abstinence to drinking

quite frequently with a high quantity of alcohol (See Table 10).

TABLE 10

Summary of the Mean Comparisons of Team Drinking Patterns

 

Range Minimum Maximum .11 SD
Average drinks per
weeks by team 10.87 0.00 10.87 3.87 2.61
Average binge
drinking in the last
2 weeks by team 2.33 1.00 3.33 1.93 0.63
Average alcohol index
score by team 2.28 -1.12 1.16 0.01 0.55

 

N = 42
Note. Average times binge drinking in the last 2 weeks (Item 14), 1= none, 2 = once, 3 = '
twice, 4 =3 -5 times, 5= 6 - 9 times, 6 = 10+ times.

HLM The Intraclass Correlation (ICC) for non-captain use was calculated to
determine the proportion of variance that was due to between team differences. The ICC
was .22, which suggests that 78% of the variance in team members’ alcohol use was due
to within-team differences. This means that non-captain’s alcohol use was inﬂuenced by
their unique team environment and HLM was appropriate to use. Table 11 lists the

results of the multilevel model for non-captain’s alcohol use. The conditional model was

72

subjected to a simultaneous multiple regression analysis with captains’ use, coach’s
emphasis, and team’s additional alcohol policy as predictors of (excluding captains)

aggregated non-captains’ alcohol use.

Research Question #2

Does captains ’ alcohol use predict the alcohol use of other members on their
teams? Results indicated that the only signiﬁcant predictor of non-captains’ use was
captains’ use. Because the data were standardized, the size of the beta was .38 which can
be interpreted as moderate. Therefore, within each team, the captains’ alcohol use had a

moderately sized relationship with non-captains’ use on average. (See Table 11).

Research Question #3

Does a coach ’8 emphasis on alcohol policy adherence predict the alcohol use of
the non-captains on their teams? The coach’s emphasis did not have a signiﬁcant size
beta (-.09) which is interpreted as the number of times the coach talked about adhering to
the alcohol policy and how a coach would follow up if she/he had knowledge of a

violation. The coach’s emphasis showed no relationship with non-captains’ alcohol use.

73

TABLE 11

Hierarchical Linear Models in Which Alcohol Use of Non Captains Was the
Dependent Variable

 

Final estimation of ﬁxed effects "

 

Model Coefﬁcient SE t df p
Captain’s Alcohol Use“ 0.38 0.07 4.96 38 0.00
Coach’s Emphasis -0.09 0.12 -0.75 38 0.46
Team Alcohol Policy -0.20 0.18 -1.11 38 0.28

 

Final estimation of variance components
for random effects

 

 

SD Variance df x p
Intercept 1 0.32 0.10 38 98.87 0.00
Level 1 0.88 0.77

 

*p < .05.

Research Question #4

Does a team ’3 additional alcohol policy predict the alcohol use of the non-
captains on the team representing that institution? On average within each team, the
team’s alcohol policy beta (-.20) had a very small-sized relationship with non-captain’s
use. This was measured by differentiating between teams that had an additional alcohol

policy in addition to that of the institution and those that did not.

74

Chapter 5
DISCUSSION

The main contribution of this study to the literature is that team captains’ alcohol
use signiﬁcantly predicts the alcohol use of members of their team. Past research has
failed to consider the unique inﬂuences that occur within teams. Although Leichliter et
al. (1998) found that female team captains and other team members used alcohol to a
similar extent, they could not determine if captains use predicted team members’ use
because they ignored the within team differences. In addition, although captains’ alcohol
use does moderately predict alcohol use of members of their team, there are other
variables that inﬂuence team members alcohol use that need to be investigated and
identiﬁed. One of these other variables might involve social factors. Athletes tend to
socialize 2 more hours per day than non-athletes (Nelson & Wechsler, 2001) and are
continually exposed to more social settings that promote alcohol use than non-athletes
(Stainback, 1997). Another variable that could account for team members’ alcohol use is
the overpowering message that the alcohol industry portrays of alcohol with sports
(W adler & Hainline, 1989). Because of the correlational nature of this study, it is
possible that the correlational inﬂuence was reversed. That is, non-captains could be the
ones who inﬂuenced captains to drink. However, given the nature of the literature on
peer leaders and their inﬂuence, the predictive ordering of leaders inﬂuencing followers
seems justiﬁed.

It should also be noted that this relationship could show a positive correlation
with the inﬂuence of upperclassmen (who are usually the captains) on drinking behaviors

of underclassmen. That is, maybe the athletes who are inﬂuencing underclassmen to

75

drink are actually the upperclassmen and not the captains. After taking a closer look at
the data on the level of grade of the captains, it came as no surprise that the highest
percentage of the captains were upperclassmen (Seniors = 45; Juniors = 38). However,
there were also underclassman represented (Sophomores = 19; Freshmen = 3). It should
be also noted that softball teams typically will have more underclassmen on their rosters
because most college programs do not run junior varsity programs.

There were three teams in which its members reported not drinking alcohol. After
examining these three teams there were no consistent characteristics among the teams.
One of the two teams represented a private, Christian school; one of the three teams had a
head coach who was the dean of students in charge of discipline; all three had a different
make up of classes of players; all three were from different states; one of the teams had
an additional alcohol policy besides the athletic department policy. It might be important
in future research to case study these teams and talk with individuals on these teams to
ﬁnd out the reasons for choosing not to engage in alcohol drinking. However, this
purpose of the present study was to see if there was a correlation between captains and
non-captains drinking patterns. Further research should address some of the reasons why
this correlation exists

The ﬁndings regarding Question #1- “Do team captains use less alcohol and binge
drink less than their teammates?” indicate that the number of drinks that these female
softball players consumed per week was similar to what previous studies had found
(Leichliter et al., 1998; Wechsler et al., 1998) with female athletes in general but around
two drinks more on average compared to what has been found with college non-athletes

(Leichliter et al., 1998; Wechsler, 2003). Binge drinking occurred at a similar rate (46%

76

and 50%, respectively) to other research studies that measure binge drinking in athletes
and athletes in leadership positions (Leichliter et al., 1998; Nelson & Wechsler, 2003),
but less than what has been found with female sorority members (56%) (Meilman,
Leichliter, & Presley, 1999; Plucker & Teed, 2003). These trends were similar to the
results of this study in binge drinking rates as well (captains 50%, non-captains 46.3%).
The only study that addressed alcohol patterns in athletes in leadership roles among
several sports, reported that female captains binge drank 49% of the times they consumed
alcohol during the previous 2 weeks while their non-captain counterpart binged 47% over
the same time period (Leichliter et al., 1998). Thus, this sample was not atypical of
female athletes in other sports and at different institutions. However, the prevalence rate
is still alarming and indicates the need for more inﬂuential programs. While the results
of the present study suggest that much work needs to be completed to reduce alcohol
abuse in the female college athlete population, examining the relationship of athletes
within their team would be an important step for the future. For instance, captains may
inﬂuence their teammates’ drinking directly and/or indirectly (Borsari & Carey, 2001).
They may command, encourage, or discourage directly or model indirectly. Teammates’
perceived norms about drinking behavior within the team may also play a role. These
variables would be important next steps to examine using HLM methodology before
attempting to design prevention strategies.

The ﬁndings regarding Question #3- “Does a coach’s emphasis on alcohol policy
adherence predict the alcohol use of the non-captains on their teams?” provide no support
for the relationship between how many times a coach emphasized an alcohol policy and

the team’s alcohol use. In other words, it did not matter how many times a coach talked

77

to his/her team about an alcohol policy. One would hope that the more times the coach
stressed obeying an alcohol policy or talked to his/her players about not drinking alcohol
the less likely the team would engage in alcohol use. One explanation for this result is
that the survey did not address how much the players liked or respected their coach. One
could speculate that on the teams where the players liked and respected their coach there
would be a relationship with the coach’s emphasis. Another explanation could be that the
college drinking culture is not inﬂuenced much by adults. These are issues that need to be
addressed in future research.

Results for Question #4 — “Does a team’s additional alcohol policy predict the
alcohol use of the non-captains on the team representing that institution?” showed very
little correlation between a team’s additional alcohol policy and the team’s alcohol use.
All teams reported a school alcohol policy while there were 11 teams that instilled an
additional alcohol policy during the season. Nine of the schools reported an abstinence
policy during the season for all members of their team while the remaining two teams had
a policy for players of legal age of no drinking within 24 hours of a game or practice.

The current ﬁndings make an important contribution to the understanding of
alcohol patterns at the individual and team level in Division III softball teams. These
ﬁndings advance the literature on the topic of college athletes’ alcohol patterns,
particularly among female athletes and teams. Female college students, including female
college athletes are showing increases in heavy, problematic drinking (Leichliter et al.,
1998; NIAAA, 2002; Presley et al., 1998; Wechsler, et al., 2003). This is particularly
disconcerting given the facts that alcohol consumption makes women more intoxicated

quicker than men and therefore more vulnerable to experiencing alcohol-related

78

consequences including rape, unprotected sexual intercourse, assault, pregnancy, and
many more.

To date, research has shown that there are few successﬁrl prevention techniques
or programs that have helped decrease heavy episodic drinking by college athletes
(Barnett et al., 1996; Haines & Spear, 1996; Peeler et al., 2000). However, most
prevention programs have failed to use a comprehensive program that targets the
institution as a whole, includes the subgroups of students including freshmen, members
of athletic teams, members of the Greek system, and individual problem drinkers
(NIAAA, 2002).

In step with the NIAAA, the ﬁndings from the current study suggest that
prevention programs that focus on team captains and their inﬂuence on team members
could be more successﬁrl in curbing heavy alcohol use by athletes. Therefore, prevention
strategies with college athletes need to start with addressing the captains’ alcohol
patterns. Prevention and intervention researchers might take their one from research on
peer education. Academic and student affairs leaders have advocated for the
development of peer education for a long time. In fact, Hunt (2004) states:

“Academic and student affairs leaders long have acknowledged that much of
students’ learning takes place in cocurricular and extracurricular settings dominated by
their peers. That fact has quietly grown in importance in recent years as educators,
student affairs leaders, and student health ofﬁcials increasingly have recognized that

peers can play a particularly important role in dealing with students’ problems involving
such things as alcohol abuse, drug use, sexual assaults, and sexually transmitted diseases’

(p. 40).
The NIAAA (2002) also had some recommendations for peer leadership in

9

helping with problem drinking on campuses because peers not only have ﬁrst-hand
experience about their peers’ behavior but because they are also the most trusted by their

classmates. This trust may especially hold true in an athletic team group. According to

79

Hunt (2004), peer leadership has also been targeted for funding by the Centers for
Disease Control and Prevention, the US. Department of Education, and the National
Highway Trafﬁc Safety Administration.

In peer education programs, peer leaders can assist in the multiple “teachable
moments” that occur on a day-to-day basis by informally talking to classmates,
teammates, and roommates. These informal settings that might include sports ﬁelds,
dorm rooms, classrooms, and parties as well as other social events can have an enormous
positive impact (Hunt, 2004). Peer leaders also coordinate the discussions and activities
in more formal settings as well. In one such successful program, female high school
athletes participated in a season-long peer-led pro gram to encourage healthy behaviors
and target issues such as disordered eating, diet pill use, drug use, body dissatisfaction,
depression, and the media’s portrayal of women. Those who participated in the program
were less likely to participate in these unhealthy behaviors and thought patterns (Eliot et
al., 2004). Botvin, Baker, Renick, F ilazzola, and Botvin, (1984), using 7th graders
conducted a 20-session substance abuse prevention program to reduce interpersonal
pressure to smoke, drink excessively, or use cannabis. Results showed the peer-led
programs were statistically superior to teacher-led and control groups in reducing
pressure to use all substances. In another study conducted in four different countries,
using peer-led intervention groups and teacher-led groups, researchers found peer-led
programs demonstrated signiﬁcantly lower alcohol scores than from the teacher-led or
control groups (Perry & Grant, 1988).

In addition, the literature on resistance skills should also be incorporated within

the group setting. Since it has been found that students who are more socially secure and

80

have an established group of ﬁiends have better resistance skills to alcohol (Shore et al.,
1983) alcohol educators and coaches could promote and help develop a high level of
cohesion between teammates within the group. These approaches tailored to the speciﬁc
issues of female. athletes, may help to decrease the alcohol use patterns in this group.
Along with focusing on captains and peer leadership in athlete prevention
programs, it would be important to also educate athletes on the effects of alcohol use on
performance. Researchers have found that even small to moderate alcohol use decreases
performance of pyschomotor skills (American College of Sports Medicine, 1982) and
aerobic activity (O’Brien, 1991). It also has been found to impair temperature regulation
during prolonged exercise in cold environment (O’Brien, 1991), weaken the pumping

force of the heart (Lang et al., 1985), and an increase in injury rates (O’Brien & Lyons,

2000)

Finally, researchers have also found that athletes tend to drink less often than non-
athletes but when they drink they drink more. F urtherrnore, non-athletes drink through
the whole week while athletes tend to mainly drink on the weekends. One reason why
this might be could be because there is not much time during the week due to the amount
of time taken for training, traveling to away contests, and ﬁtting in school work. Then

when they have a little extra time on the weekend they make up for the lack of drinking

during the week.

Limitations

A few limitations in this study are worth noting. First, as with most survey

research, a common method bias may be present because all data were self-reported. The

81

classiﬁcation of respondents into the categories of captain or non-captain was based on
students’ self-reports. Some athletes may have misinterpreted or misrepresented their
leadership roles, although if this occurred it is expected that it happened in only a few
cases. In addition, the survey required athletes to provide sensitive information about
their alcohol use and involvement in illegal acts such as underage drinking. This
information, if revealed, could result in their suspension of athletic involvement and
possibly legal action taken. If this were the case, the data would be affected in under—
reporting. The survey questionnaires were anonymous to provide the respondents with
adequate protection. Secondly, it is important to state that because the teams were not
randomly selected, one should not interpret that these results can be transferred to all

teams in every sport and in athletes in all divisions.

Future Recommendations

In addition to the noted implications for future research already addressed, the
ﬁndings of this study suggest avenues for future research in the area of gender. Women
may consider the group structure and following the lead of their captains to be more
important than male athletes. It is known that men and women think differently about
group membership and being on a team. Generally for women, being a part of the team
can mean that relationships that form extend outside of the court or ﬁeld and are
interwoven in social settings; whereas for men, being a part of a team means that there
are colleagues who share the same goals but in social settings the relationships mainly

stay focused on the activities of the team (DeBoer, 2004). Future studies using a

82

representation of the different sports, different divisions of colleges and including both
genders need to be conducted to replicate these ﬁndings.

Future research might also broaden the scope of the study to include team
cohesion. An investigation examining alcohol patterns within teams and how team
cohesion would affect the relationship of captains’ alcohol use to their non-captains’ use
might moderate the relationship. One could speculate that the more cohesive a team is
the stronger the relationship of alcohol use between captains and non captains. If they
enjoy being together, they will spend more time together outside of the athletic ﬁeld
socializing.

A follow-up to the ﬁndings from this dissertation is to conduct qualitative
research to pinpoint some reasons why this relationship exists as well as other reasons
athletes may or may not decided to misuse alcohol. Other questions to ask would include
with whom athletes drink with, what might cause them to drink more or less, and why

athletes who do abstains from alcohol choose to do so.

83

APPENDICES

 

84

Appendix A

Alcohol and Drug Survey
Informed Consent Form

You are being asked to participate in a study being conducted by graduate student Amber
Warners under the supervision of Dr. Deborah F eltz from Michigan State University. The
primary purpose of this study is to exarrrine the different alcohol and drug patterns of Division III
softball players in the Midwest. It is hoped that this research project will allow for a better
understanding of alcohol and drug patterns in softball athletes at a Division III level.

As part of this study, you are being asked to complete the following questionnaires. It should
take approximately 10 minutes to complete. The questions will be speciﬁc to the alcohol and
drug use and perceptions of group environment over the past year.

Your responses to the questionnaires will remain anonymous; no one will see the responses
except for the statisticians from the Core Institute at South Illinois University who will be
inserting the questionnaires into the data bank. Results will be based on the answers given by the
athletes as a group insuring anonymity of individual responses and particular universities will not
be identiﬁed. Overall results of the study will be made available to those who are interested at
the completion of the project. Your participation in this study does not guarantee any beneﬁcial
effects and there will be no risks involved. Your privacy will be protected to the maximum extent

allowable by law.

IF YOU ANSWER THE QUESTIONS ON THE ATTACHED QUESTIONNAIRE, SEAL IT DI
THE ATTACHED ENVELOPE, AND RETURN IT TO THE PERSON WHO GAVE IT TO
YOU, YOU ARE GIVING YOUR CONSENT TO PARTICIPATE IN THIS STUDY.

However, please know that you may withdraw from participation at any time without penalty and
you can refuse to answer any questions you want to skip. If you have any questions concerning
participation in this study, please contact the study’s principal investigator, Dr. Deborah Feltz, at
(517) 355-4730 [dfeltz@msu.edu] or Amber Warners at (616) 526-6223 [awamers@calvin.edu].
If you have any questions regarding your rights as a study participant, or are dissatisﬁed at any
time with any aspect of this study, you may contact- anonymously, if you wish, the UCRHIS
Chair, Peter Vasilenko, Ph. D., at 517-355-2189 or ucrihs@msu.edu, or regular mail: 202 Olds

Hall, East Lansing, MI 48824.

Thank you for your time and cooperation,

Date

 

 

Dr. Deborah Feltz, Principal Investigator

Date

 

 

Amber Warners, Graduate Student

85

 

 

Appendix B

Administrator Direction Form

*****PLEASE READ CAREFULLY*****

Instructions for the on-site administrator

I.

2.

a.

b.

Please use #2 pencils for completing the surveys.

Have athletes take the survey in a controlled setting such as a quite
classroom.

Have athletes sit far enough apart from to ensure conﬁdentiality
and to promote honesty in answering the questions.

Do not allow athletes to talk during the taking of the survey or to
discuss any portion of the survey while it is being completed.

Procedures

Distribute surveys, one pencil and one white envelope to each
player.

Once the survey is completed have the athlete put only their
surveys into their own envelope and seal it followed by putting it
in the larger, group self-addressed, prepaid envelope. They
should not include the cover letter (pink) or the page with the

attachment questions (yellow).
Once all surveys are turned in, seal the envelope and personally

put in the mail.

Thank youlllllllllllllllllllll

86

 

Appendix C

Phone Script of Initial Contact of Coaches

“Hello, my name is Amber Warners. I am the softball coach at Calvin College in Grand
Rapids, Michigan. I am also a graduate student at Michigan State University in the
process of completing my Ph.D. I am interested in researching alcohol and drug patterns
in Division HI softball players. I am wondering if you would be willing to have your
team be a part of my research study. The survey would be anonymous and it would take
about 15 minutes to complete. I would ask that you have someone like the team manager
or athletic trainer administer the survey instead of yourself to minimize the risk of the
athletes being afraid the coach will ﬁnd out or see their responses. May I have a name
and contact information for the person who will be administering the survey so I can send
them a packet that will include an instruction sheet for the administrator, consent forms,
survey and a prepaid, self—addressed envelope for the surveys to be sent? Upon the
completion of the surveys, the administrator will need to put it in the mail themselves.
The surveys will be sent to the Core Institute who specializes in collecting data on
alcohol and drugs. The surveys would be then scanned and the data collected from all the
schools would be then sent to me in SPSS data form. I would be happy to send you the
overall results of the study when completed.”

87

Appendix D

Additional Questions to the Core Survey

Bubble in the appropriate response at the top, right-hand comer of the Core and Alcohol
Survey located in the “For additional use”.

A.

Are you a team captain or co-captain?

0 Yes
1 No

Does your team have its own restrictions in addition to any athletic department
alcohol or drug policy?

0 Yes
1 No

How many times during the year has your coach talked to the team about obeying
an alcohol or drug policy?

0 Zero times

1 one time

2 2-3 times

3 4 or more times .

If your coach found out any team members had violated the team or school
alcohol or drug policy would your coach be more likely to:

look the other way

conﬁont the member(s) and turn them in

conﬁ'ont the member(s) and not turn them in

confront the member(s) and punish them outside of the school

WND—lc

Think back to when you were out of season. How many times did you have four
or more drinks at one sitting over a typical two week span?

0 none

1 once

2 twice

3 3-5 times

4 6-9 times

5 10 or more times

88

 

Appendix E
Core Alcohol‘and Drug Survey

Form 151"!

 

 

68

Care Aicehel and Drug Servey

For use by two- and four—year institutions

 

Please use a number 2 Pencil.

Core institute
‘ Student Health Programs
l Southern Illinois University
Carbondale, IL 62901

 

Fer additional use:

 

 

 

 

 

 

 

 

 

 

 

1. Classification: 2. Age: 3. Ethnic origin: 4. Marital status:
Freshman ............ C) [E American Indian/ Single ................ C)
Sophomore ............ 0 Alaskan Native ........ 0 Married .............. {:3
Junior ................ O @ (a) Hispanic .............. O Separated ............ C3
Senior ................ O G) (3 Asian/Pacific Islander . . . . O Divorced .............. Cf:
Grad/professional ...... C! @ ® White (non-Hispanic). . . . . O Widowed .............. O
Not seeking a Q) ‘3) Black (non-Hispanic) ..... O '
degree .............. O Q) (‘9 Other ................. O 7- Are you working?
Other ................ O (9 ® - Yes, full—time .......... O
(9 ® 6. Is your current residence Yes, part-time . , g ,,,,,,, Q
5. Gender: 6) (7} as a student: No ,,,,,,,,,,,,,,,,,, 0
Male .............. , . . O E. On-campus ............ 0
Female ............ ' . . O (9 @ Off-campus ............ O 3- LIVING arrangementS: .
A. Where: (mark best answer)
9. Approximate cumulative grade point average: (choose one) House/apartment/etc ..... C)
O O O O O O O O O O Residence hall .......... O
. A+ A A- B+ B B- C+ C C- D+ D D- F Approved housing ...... O
Fraternity or sorority . . . . O
10. Some students have indicated that alcohol or drug use at parties they attend in and Other ................ O ,
around campus reduces their enjoyment, often leads to negative situations, and

therefore, they would rather net have alcohol .anddrugs available and-usedr-Other B" w'th whom:

 

 

 

 

 

 

 
  
   
    

students have indicated that aicohoi and drug use at parties increases their (mark all that apply) .
enjoyment, often leads to positive situations, and therefore, they would rather have With roommate(s) ...... O
alcohdl and drugs available and used. Which of these is closest to your own View? Alone ................ 0
Have available Not have available With parent(s) .......... 0
With regard to drugs? .............................. With spouse .......... C}
With regard to alcohol? ..... ........ O .............. C With children .......... C)
- Other ................ O
11.Student status: 12. Campus situation on alcohol and drugs: yes no don’t know
Full-time (12+ credits) . . . . Q a. Does your campus have alcohol and drug policies? ...... C2 . . . . O ...... _
Part-time (1—11 credits) , _ O b. If so, are they enforced? ............................ O . . . . O ...... O
c. Does your campus have a drug and alcohol
13.Place of permanent prevention program? ...................... ....... Q . . . . O ...... Q
residence: d. Do you believe your campus is concerned about
ln~state .............. O the prevention of drug and alcohol use? ................ O . . . . C) ...... C}
USA, but out of state . . . . O e. Are you actively involved in efforts to prevent dnrg
Country other than USA . . O . and alcohol use problems on your campus? ............ O . . .. Q
.- 14. Think back over the last 15. Average # of 15. At what age did you 9;
two weeks. How many drinks* you first use... ?,>.

times have you had
five or more drinks*
at a sitting?

consume a week: (mark one for each line)

Tobacco (smoke, chew, snuff) . . "
Alcohol (beer, wine, liquor)* ......

   

   
 
  

(If less than Mari‘uana of hash, hash oil . . . .
Once ................ O 10 code Cocaine (crack, rock, freebase) . . L,
Twice ................ 0 answers as Amphetamines (diet pills, speed). . O
3 to 5 times ............ O 00 01 02 Sedatives downers, ludes ...... C)
6 to 9 times ............ 8 81$) ’ ’ Hallucinogens (LSD, PCP) ......

10 or more times ........ ‘

 

Opiates (heroin, smack, horse)
inhalants (qlue, solvents, gas) . . . .
Designer drugs (ecstasy, MDMA). . O

O

 

oeo

Steroids
Other illegal drugs ............ O

“Other than a few sips

@®@@@®@®®©
@@@@@®®®®@
ran-”.2“? The 9.0 1:72»

 

 

 

 

© Core Institute: 1989, 1990, 1991, 1992, 1993, 1994, 2000.

a m

 

 

KO
0

 

 

t7.Within the last Ear

about how often have

you used...

(mark one for each line)
a. Tobacco (smoke, chew, snuff) . . ;
b. Alcohol (beer, wine, liquor) . . .. ' '
c. Mari‘uana ot, hash, hash oil
d. Cocaine (crack, rock, freebase)
e. Amphetamines (diet pills, speed)
i. Sedatives downers,ludes
g. Hallucinogens (LSD, PCP) . . . .
h. Opiates (heroin, smack, horse)
i. inhalants lue, solvents, as
j. Designer drugs (ecstasy, MDM
k. Steroids ..................
l. Other illegal drugs .......... O; _

 
  
 
 
     
   
 
 
  
 

   

   

18.3uring the past 30 days

on how many days

did you have:

(mark one for each line)
a. Tobacco (smoke, chew, snuff) . . . g ,
'0. Alcohol (been-wine, liquor) ...... 3 "
c. Mari'uana ot, hash, hash oil . . . . :,
d. Cocaine (crack, rock, freebase) .
e. Amphetamines (diet pills, speed).
f. Sedatives (downers, ludes) ......
g. Hallucinogens (LSD, PCP) ......
h. Opiates (heroin, smack, horse)
i. inhalants lue, solvents, as . . .
j. Designer drugs (ecstasy, MDMA).
k. Steroids ..................
l. Other illegal drugs .............

    
    
    
 
 
  
  

1%
at) 6

QQOtggJ

  

 
 
      

      

 

     
 

 

19.How often do you
think the average student
on your campus uses... '
(mark one for each line)
a. Tobacco (smoke, chew, snuff) . .
b. Alcohol (beer, wine, liquor) . . . .
c. Mari'uana ot, hash hash oil
d. Cocaine (crack, rock, freebase) 0
e. Amphetamines (diet pills, speed)8

 
 
 
 
 
 
     
 
    
 
 
      
      

f. Sedatives downers ludes .. ..
g.. Hallucinogens (LSD, PCP) . . . . 01'.
h. Opiates (heroin, smack, horse) 0.

 

   
 
 
    
       

 
    

      
   
 

    

21 .Piease indicate how often
you have experienced
the following due to
your drinking or drug use
during the last year... '
(mark one for each line)
a. Had a hangover ................
b. Performed poorly on a test
or important project .............. O O
0. Been in trouble with police,
residence hall. or other

  
 
  
   
  
   
  
  
   
  

, college authorities .............. O O O Q

i. inhalants lue solvents, as . . O; CO d. Damaged property, pulled ;
j. Designer drugs (ecstasy, MDMA)O=‘. ’ fire alarm, etc. . . . . . . . . . . . .' ...... OO} @iOO
k. Steroids .................. 02‘ 1 e. Got into an argument or fight ...... O O? ,00
-i. Other illegal drugs ....... '-.~ . . O“! f. Got nauseated or vomited ........ OO :00

g. Driven a car while under
the influence .................. O 0: U0
h. Missed a class .................. O O” O
20- Where have YOU i. Been criticized by someone ‘
used... 1 know ..................... _. . . 00 00
(mark all that apply) 9 j. Thought i might have a drinking -
, ‘5'» 5°; or other drug problem .- ........... O '90 O
3. Tobacco (smoke, chew, snuff) . . Oi 00 k. Had a memory loss .............. O O O
b. Alcohol (beer, wine, liquor) . . . . O. OO - l. Done something 1 later regretted . . . . CO
C. Mari'uana " O O m. Been arrested for DWI/DUI ........ O O
00 n. Have been taken advantage
of sexually .................... O O
,5 0. Have taken advantage of‘
g. Hallucinogens (LSD, PCP) . . . . 033 M another sexually . . . ............ 00
h. Opiates (heroin, smack, horse) 02.“, ‘00 p. Tried unsuccessfully to stop using 0 O
i. inhalants lue solvents as . . 0.5%: ‘ '0 q. Seriously thought about suicide .. .. 300
3. Designer drugs (ecstasy, MDMA)OW§ r. Seriously tried to commit suicide . . . . O 00
k. Steroids .................. O? i "t ,3. Been hurt or injured .............. O 00
l Other illegal drugs .......... O ”,0 O

 

 

22. Have any of your family had alcohol or other
drug problems: (mark all that apply)

 

23. if you volunteer any of your time on or off campus
to help others, please indicate the approximate

 

 

 

 

 

number of hours per month and principal activity:
0 Mother 0 Brothers/sisters O Spouse O Don’t volunteer, or ‘ C) 10—15 hours
O Father 0 Mother’s parents 0 Children less than 1 hour O 16 or more hours
0 Stepmother 0 Father’s parents O None 0 1—4 hours Principal volunteer activity is:
O Stepfather O Aunts/uncles ' 0 5-9 hours
Mark Reflex© by NCS MM235019‘1 6 EDGE Printed in U.S.A.
I I I I

 

 

Appendix F

TABLES

91

 

TABLE 1

Percentage of Reported Age of First Use of Alcohol

 

 

 

Percentage
The Reported Age
Of First Alcohol Use Non-Captain Captain Total
(N=513) (N= 104) (N=617)

Never 12.5 14.4 12.8
Under 10 0.6 0.0 0.5
10-11 1.0 0.0 0.8
12-13 4.5 8.7 5.2
14-15 17.8 14.4 17.2
16-17 30.7 24.0 29.5
18-20 31.6 36.5 32.5
21-25 1.4 1.9 1.5

 

92

TABLE 2

Percent of Frequency of Alcohol Use in the Past Year

 

 

 

Percentage
Frequency of
Reported Alcohol Use Non-Captain Captain Total
Within the Past Year (N =5 14) (N = 104) (N = 618)
Never used 14.0 16.3 14.4
Once/year 7.4 3.8 6.8
6 times/year 13.2 10.6 12.8
Once/month 8.8 7.7 8.6
Twice/month 16.9 15.4 16.7
Once/week 26.3 36.5 28.0
3 times/week 12.6 6.7 11.7
5 times/week 0.8 2.9 1.1

 

93

TABLE 3

Percentage of Alcohol Use in the Past 30 Days

 

 

 

Percentage
Number of Times
Reported Drinking in Non-Captain Captain Total
Past 30 Days (N =513) (N = 104) (N = 617)
0 Days 32.7 35.0 33.1
1-2 Days 28.0 17.5 26.3
3-5 Days 20.0 25.2 20.9
6-9 Days 13.2 12.6 13.1
10-19 Days 5.8 8.7 6.3
20-29 Days 0.2 1.0 0.3

 

94

TABLE 4
Percentages of Collegiate Softball Players by Number of Drinks Per Week

 

 

 

Percentage
Drinks Non-Captain Captain Total
Per week (N =513) (N = 104) (N = 617)

0 39.0 32.7 37.9

1 13.1 9.6 12.5

2 8.0 9.6 8.3

3 4.9 9.6 5.7
4 3.7 6.7 4.2

5 7.8 8.7 7.9

6 3.1 2.9 3.1

7 1.9 3.8 2.3

8 2.3 1.9 2.3

9 0.8 2.9 1.1
10 5.5 3.8 5.2
11 0.8 0.0 0.6
12 1.8 2.9 1.9
13 0.4 0.0 0.3
14 0.6 0.0 0.5
15 2.7 1.9 2.6
16 0.2 1.0 0.3
18 0.4 0.0 0.3
20 1.2 0.0 1.0
21 0.4 0.0 0.3
22 0.2 0.0 0.2
24 0.2 0.0 0.2
25 0.2 0.0 0.2
26 0.2 0.0 0.2
30 0.2 0.0 0.2
35 0.4 0.0 0.3
40 0.2 1.0 0.3
45 0.0 1.0 0.2

 

95

TABLE 5

Binge Drinking Percentages Within the Past 2 Weeks

 

 

 

(In Season Binge Drinking)
Percentage

Number of Times
Reported Binge Drinking Non-Captain Captain Total
Past Two Weeks (N =513) (N = 104) (N = 617)
None 53.7 50.0 53.1
One Time 21.2 20.2 21.0
Twice 10.9 11.5 11.0
3-5 Times 11.5 16.3 12.3
6-9 Times 2.1 1.9 2.1
10 or More Times 0.6 0.0 0.5

 

96

TABLE 6
Binge Drinking Percentages Out of Season

 

 

 

Percentage
Number of Times
Reported Binge Drinking Non-Captain Captain Total
Out Of Season (N =513) (N = 104) (N = 617)
None 29.8 28.8 29.7
One Time 16.8 14.4 16.4
2 Times 20.9 32.7 22.9
3-5 Times 25.0 19.2 24.0
6-9 Times 5.8 3.8 5.5
10 or More Times 1.8 1.0 1.6

 

97

TABLE 7
Percentages of Alcohol Use of College Softball Teams

 

 

 

Percentage
Type of Drinking Non-Captain Captains Total
Behavior (N =513) (N = 104) (N = 617)
Use of Alcohol Within Last Year 86.0 83.7 85.6
Use of Alcohol Within Past 30 Days 67.3 65.0 66.9
Five or More Drinks in One Sitting
Within the Past Two Weeks 46.3 50.0 46.9

(In Season Binge Drinking)

Five or More Drinks In Once Sitting
Within A Typical Two Week Period 70.2 71.2 70.3

Out of Season

 

98

TABLE 8
Percentage of Softball Players Experiencing Consequences Resulting From Alcohol
Use in the Last Year

 

Non-Captain Team Captain Total

 

 

 

Hangover 68.4 73.1 69.2
Poor Test Score 23.0 18.3 22.2
Trouble with Police 19.1 12.5 18.0
Damaged Property 4.7 7.7 5.2
Argument or Fight 37.0 40.6 37.6
Nauseated or Vomited 59.6 66.3 60.7
Driven Under Inﬂuence 22.8 24.0 23.0
Missed Class 33.9 36.9 34.4
Been Criticized 32.4 31.7 32.3
Thought I Had A Problem 7.3 1.9 6.4
Had a Memory Loss“ 38.2 46.2 39.5
Later Regretted Action 42.0 40.4 41.7
Arrested for DWI or DUI 0.6 1.0 0.6
Have Been Taken Advantage

of Sexually 10.8 9.6 10.6
Have Taken Advantage of

Someone Sexually 2.3 3.9 2.6
Tried- Failed to Stop 2.9 5.8 3.4
Thought About Suicide 2.5 1.0 2.3
Been Hurt or Injured 14.4 12.5 14.1
*p<.05

99

 

REFERENCES

100

REFERENCES

Adams, C., & Nagoshi, CT. (1999). Changes over one semester in drinking game
playing and alcohol use and problems in a college sample. Substance Abuse, 20,

97-106.

Alva, SA. (1998). Self-reported alcohol use of college fratemity and sorority members.
Journal of College Student Development, 39, 3-10.

American College of Sports Medicine (1982). American College of Sports Medicine
position statement on the use of alcohol in sport. Medical Science of Sports and

Exercise, 14, ix-x.

Anderson, W.A., Albrecht, R.R., & McKeag, DB. (1993). Second Replication of a
National Study of the Substance Use and Abuse Habits of College Student-Athletes.
Report to the NCAA. Mission, KS: National Collegiate Athletic Association.

Anderson, W.A., Albrecht, R.R., McKeag, D.B., Hough, D.O., & McGrew, CA. (1991).
A national survey of alcohol and drug use by college athletes. The Physician and

Sportsmedicine, 19(2), 91-104.

Anderson, W.A., & McKeagh, DB. (1985). Substance use and abuse habits of college
student athletes. Mission, KS: National Collegiate Athletes Association.

Anderson, W.A., & McKeagh, DB. (1989). Replication of the national study of the
substance use and abuse habits of college student athletes. Mission, KS: National

Collegiate Athletes Association.

Anderson, W.A., & Snellman, M.A. (1986). 1984-85 NCAA sponsored study of alcohol,
drug, and tobacco use among college athletes. East Lansing, MI: Michigan State
University College of Human Medicine.

Archer, J. (1991). Counseling College Students. New York: Continuum.

Archer, J ., & Cooper, S. (1998). Counseling and Mental Health Services on Campus.
San Francisco, CA: J ossey-Bass Publishers.

Axtman, K. (2002). Colleges struggle to stem rioting after games. Christian Science
Monitor, November 29.

Bahr, S.J., Marchos, A.C., & Maughan, S.L. (1995). Family, educational and peer
inﬂuences on the alcohol use of female and male adolescents. Journal of Studies on

Alcohol, 56, 457-469.

101

Baer, J .S. (1994). Effects of college residence on perceived norms for alcohol
consumption: An examination of the ﬁrst year in college. Psychology of Addictive

Behaviors, 8, 43-50.

Baer, J .S., & Carney, MS. (1993). Biases in perceptions of the consequences of alcohol
among college students. Journal of Studies on Alcohol, 54, 54-60.

Baer, J .S., Stacy, A., & Larimer, M. (1991). Biases in perception of drinking norms
among college students. Journal of Studies on Alcohol, 52, 580-586.

Bakker, D.L. (1996). Religious practices and high-risk behaviors of college student
athletes and non-athletes. Dissertation Abstracts International: Section B: The

Sciences and Engineering, 57(l-B), 0266

Banks, E., & Smith, MR. (1980). Attitudes and background factors related to alcohol
use among college students. Psychological Reports, 46, 571-577.

Barnett, L., Far, J ., & Mauss, A. (1996). Changing perceptions of peer norms as a
drinking reduction program for college students. Journal of A lcohol and Drug

Education, 41, 39-62.

Bass, BM. (1990). Bass & Stogdill ’s handbook on leadership: Theory, research, and
managerial applications (3rd ed.). New York: The Free Press.

Beal, A.C., Ausiello, J ., & Pern'n, J.M. (2001). Social inﬂuence on health-risk behaviors
among minority middle school students. Journal of Adolescent Health, 28, 474-

480.

Bennis, W.G. (1989). On becoming a leader. Cambridge, MA: Perseus Books.

Blane, H.T., & Hewitt, LE. (1977). Alcohol and youth: An analysis of the literature,
1960-75. (Prepared for the National Institute on Alcohol Abuse and Alcoholism),
PB-268 698, Springﬁeld, VA: National Technical Information Service, PB-268 698.

Bond, V., Franks, B.D., & Howlett, ET. (1983). Effects of small and moderate doses of
alcohol on sub-maximal cardiorespiratory ﬁmction, perceived exertion and
endurance performance in abstainers and moderated drinkers. Journal of sports

Medicine and Physical Fitness, 23, 221-229.

Borsari, B., & Carey, KB. (2001). Peer inﬂuences on college drinking: A review of the
research. Journal of Substance Abuse, 13, 391-424.

Botvin, G.J., Baker, E., Renick, N.L., Filazzola, A.D., & Botvin, EM. (1984). A
cognitive-behavioral approach to substance abuse prevention. Addictive Behavior,

9, 137-147.

102

Branche, C.M., Sniezek, J.E., & Satin, R.W. (1991). Water recreation-related spinal
injuries: risk factors in natural bodies of water. Accident Annual Preview, 23, 13-

17.

Brennan, A.F., Walﬁsh, S., & AuBuchon, P. (1986). Alcohol use and abuse in college
students, 11: Social/environmental correlates, methodological issues, and
implications for intervention. International Journal of Addictions, 21, 475-493.

Brown, B.B., Dolcini, M.M., & Leventhal, A. (1997). Transformations in peer
relationships at adolescence: implications for health-related behavior. In J.
Schulenberg, J .L. Maggs, & K. Hurrelman (Eds.), Health risks and development
transitions during adolescence. New York: Cambridge University Press.

Canter, C.A., & Kahnweiler, W.M. (2000). The efﬁcacy of the social norms approach to
substance abuse prevention applied to fratemity men. Journal of American College

Health, 49, 66—71.
Carron, A.V. (1980). Social Psychology of Sport. Ithica, NY: Mouvement.

Cashin, J.R., Presley, C.A., & Meihnan, P.W. (1998). Alcohol use in the Greek system:
Follow the leader? Journal of Studies on Alcohol, 59, 63-70.

Centers for Disease Control and Prevention (1997. Youth risk behavior surveillance:
National College Health Risk Behavior Survey—United States 1995. Morbidity
and Mortality Weekly Report, 46(SS6):1—56.

Chappel, IN. (1987). Drug use and abuse in the athlete. In R]. May & J.J. Asken
(Eds.), Sport Psychology (pp.135-148). NY: PMA.

Chelladurai, P. (1999). Human resource management in sport and recreation.
Champaign, IL: Human Kinetics.

Chelladurai, P., & Saleh, S.D. (1980). Dimensions of leader behavior in sports:
Development of a leadership scale. Journal of Sport Psychology, 2, 34-45.

Chipperﬁeld, D., & Vogel-Sprott, M. (1988). Family history of problem drinking among
young male social drinkers: Modeling effects on alcohol consumption. Journal of
Abnormal Psychology, 97, 423-428.

Clapp, J .D., & McDonnell, AL. (2000). The relationship of perceptions of alcohol
promotion and peer drinking norms to alcohol problems reported by college
students. Journal of College Student Development, 41, 19-26.

Clapp, J.D., Russell, C., & DeJong, W. (2001). Done 4 did zip: Evaluating a failed social
norms marketing campaign. Paper presented at the Fourth National Conference on

the Social Norms Model, Anaheim, CA.

103

Clement, DB. (1983). Drug use survey: Results and conclusions. The Physician and
Sportsmedicine, 9(11), 64-67.

Collins, R.L., Parks, G.A., & Marlatt, G.A. (1985). Social determinants of alcohol
consumption: The effects of social interaction and model status on the self
administration of alcohol. Journal of Consulting and Clinical Psychology, 53, 189-

200.

Cooper, A.M., Waterhouse, G.J., & Sobell, MB. (1979). Inﬂuence of gender on drinking
in a modeling situation. Journal of Studies on Alcohol, 40, 562-570.

Corcoran, K.J. (1995). Cognitive and situational factors predict alcoholic beverage
selection. Addictive Behaviors, 20, 525-532.

Csikszentmihalyi, M., & Larson, R. (1984). Being adolescent. New York: Basic Books.

DeBoer, K]. (2004). Gender and competition: How men and women approach work and
play diﬂerently. Monterey, CA: Coaches Choice.

DeJong, W. (2001). Finding common ground for effective campus-based prevention.
Psychology of Addictive Behavior, 15, 292-296.

Dericco, DA. (1978). Effects of peer majority on drinking rate. Addictive Behaviors, 3,
29-34.

Dericco, D.A., & Garlington, W.K. (1977). The effect of modeling and disclosure of
experimenter’s intent on drinking rate of college students. Addictive Behaviors, 2,

135-139.

Dericco, D.A., & Niemann, J.E. (1980). In vivo effects of peer modeling on drinking
rate. Journal of Applied Behavioral Analysis, 13, 149-152.

Duda, M. (1984). Drug testing challenges college and pro athletes. The Physician and
Sportsmedicine, 12, 109-116.

Elder, C., Barnes, J ., Leaver-Dunn, D., Nagy, S., and Leeper, J. (2002). The inﬂuence of
group membership on multiple substance use. Journal of Alcohol & Drug

Education, 47(2), 42-5 7.

Everett-Jones, S., Oeltmann, J ., Wilson, T.W., Brener, N.D., & Hill, CV. (2001). Binge
drinking among undergraduate college students in the United States. Journal of

American College Health, 50(1), 33-49.

Fitzgerald, J .L., & Amdt, S. (2002). Reference group inﬂuence on adolescent alcohol
use. Journal of Alcohol and Drug Education, 47(2), 42-57.

104

Fox, EL. (1984). Sports Physiology. Philadelphia, PA: CBS College Publishing.

Frintner, M.P., & Rubinson, L. (1993). Acquaintance rape: The inﬂuence of alcohol,
fraternity membership, and sports team membership. Journal of Sex Education and

Therapy, 19, 272-284.

Garlington, W.K., & Dericco, DA. (1977). The effect of modeling on drinking rate.
Journal of Applied Behavioral Analysis, 10, 207-21 1.

Gay, J .E., Minelli, M.J., Tripp, D., & Keilitz, A. (1990). Alcohol and the athlete: A
university’s response. Journal of Alcohol and Drug Education, 35(2), 81-86.

Glider, P., Midyett, S., Mills-Novoa, B. J ohannessen, K. & Collins, C. (2001).
Challenging the collegiate rite of passage: A campus-wide social marketing media
campaign to reduce binge drinking. Journal of Drug Education, 31(2), 207-220.

Gloede, B. (1988). What if beer were banned? Sports Inc., February 29, 1988.

Goodhart, F .W., Lederman, L.C., Stewart, L.P., & Laitrnan, L. (2003). Binge drinking:
not the word of choice. Journal of American College Health, 52(1), 44-47.

Granﬁeld, R. (2002). Believe it or not: Examining to the emergence of new drinking
norms in college. Journal of Alcohol & Drug Education, 47(2), 18-32.

Green, G.A., Uryasz, F.D., Petr, T.A., & Bray, D. (2001). NCAA study of substance use
and abuse habits of college student-athletes. Clinical Journal of Sport Medicine,

11(1), 51-56.

Grossman, S.J. & Smiley, EB. (1999). APPLE: Description and evaluation of a
substance abuse education and prevention program for collegiate athletics. The
Journal of Primary Prevention, 20(1), 51-59.

Gruenewald, P.J., Johnson, F .W., Light, J .M., Lipton, R., & Saltz, RF. (2003).
Understanding college drinking: Assessing dose response from survey self-reports.
Journal of Studies on Alcohol, 64(4), 500-515.

Haines, M., & Spear, A. (1996). Changing the perception of the norm: A strategy to
decrease binge drinking among college students. Journal of American College

Health, 45, 134-140.

Heath, G.W., Ford, E.S., & Craven, T.E. (1991). Exercise and the incidence of upper
respiratory tract infections. Medicine Science of Sport and Exercise, 23,152-157.

Hendricks, R.D., Sobell, M.B., & Cooper, A.M. (1978). Social inﬂuences on human
ethanol consumption in an analogue situation. Addictive Behaviors, 3, 253-259.

105

Higher Education Center (1997). Be vocal, be visible, and be visionary:
Recommendations of college and tmiversity presidents on alcohol and other drug
prevention. Available from the Higher Education Center for Alcohol and Other

Drug Prevention, 55 Chapel Street, Newton, MA.

Hingson, R.W., & Howland, J. (2002). Comprehensive community interventions to
promote health: Implications for college-age drinking problems. Journal of Studies
on Alcohol Supplement, 14, 226-240.

Houmard, J .A., Langenfeld, M.E., & Wiley, R.L. (1987). Effects of the acute ingestion
of small amounts of alcohol upon 5-mile run times. Journal of Sports Medicine and

Physician, 27, 253-257.
Hunt, D. (2004). Peer to peer: Effective college learning. Change, 36(3), 40-45.

Jenkins, J .E. (1996). The inﬂuence of peer afﬁliation and student activities on adolescent
drug involvement, Adolescence, 3 1( 122), 297-307.

J ohannessen, K., Collins, C., Mills-Novoa, B. & Glider, P. (2000). A Practical Guide to
Alcohol Abuse Prevention: A Campus Case Study in Implementing Social Norms
and Environmental Management Approaches. Tucson, Arizona: The University of

Arizona.

Johnson, RB. (1989). Reactions, expectancies, and college student’s drinking.
Psychology Report, 65, 1245-1246.

Johnston, L.D., O’Malley, P.M., & Bachman, J .G. (1994). National survey results on
drug use ﬁom the monitoring the future study, 1975-1994: Vol. 2 College students
and young adults. Washington DC: US. Government Printing Ofﬁce, NIH

Publication 94-3 809.

Johnston, L., O’Malley, P., & Bachman, J .D. (2000). National survey results on use from
the monitoring the ﬁrture study, 1975-1999 (Vol. 2). BetheSDa, MD: Dept of

Health and Human Resources.

Jung, J .R. (2003). Changing the focus of college alcohol prevention programs. Journal
of American College Health, 52(2), 92-96.

Keeling, RP. (2002). Binge drinking and the college environment. Journal of American
College Health, 50, 197-201.

Klein, H. (1992). College student’s attitudes toward the use of alcoholic beverages.
Journal of Alcohol and Drug Education, 37, 35-52.

106

Knight, J .R., Wechsler, H., Kuo, M., Seibring, M., Weitzman, E.R., & Schuckit, MA.
(2002). Alcohol abuse and dependence among US. college students. Journal of
Studies on Alcohol, 63(3), 263-270.

Kokotailo, P.D., Henry, B.C., Koscik, R.E., Fleming, M.F., & Landry, G.L. (1996).
Substance use and other health risk behaviors in collegiate athletes. Clinical
Journal of Sports Medicine, 6, 183-189.

Koss, M.P., & Gaines, J .A. (1993). The prediction of sexual aggression by alcohol use,
athletic participation and fraternity afﬁliation. Journal of Interpersonal Violence,
8(1), 94-108.

Kouzes, J .M., & Posner, B.Z. (1995). The leadership challenge: How to keep getting
extraordinary things done in organizations, San Francisco: J ossey-Bass.

Kozub, S.A., & Pease, D.G. (1993). Coach and player leadership in high school
basketball. Journal of Sport Pedagogy, 7, 1-15.

Larimer, M.E., Iruine, D.L., Kihner, J .R., & Marlatt, G.A. (1997). College drinking and
the Greek System: Examining the role of perceived norms for high-risk behavior.
Journal of College Student Development, 38, 587-598.

Lang, R.M., Borow, K.M., & Neumann, A. (1985). Adverse cardiac effects of acute
alcohol ingestion in young adults. Annual Internal Medicine, 102, 742-747.

Leichliter, J .S., Meihnan, P.W., Presley, C.A., & Cashin, J .R. (1998). Alcohol use and
related consequences among students with varying levels of involvement in college
athletics. Journal of American College Health, 46(6), 257-262.

Liccione, W.J. (1980). The relative inﬂuence of signiﬁcant others on adolescent
drinking: An exploratory study. Journal of Alcohol and Drug Education, 25, 55-62.

Lied, E.R., & Marlatt, G.A. (1979). Modeling as a determinant of alcohol consumption:
Effect of subject sex and prior drinking history. Addictive Behaviors, 4, 47 -54.

Lo, CC. (1995). Gender differences in collegiate alcohol use. Journal of Drug Issues,
25, 817-836.

Luther, S.S., & McMahon, T.J. (1996). Peer reputation among inner-city adolescents:
Structure and correlates. Journal of Research on Adolescence, 6, 581-603.

Lyons, RP. (1998). Can regular alcohol consumption increase the risk of injury?
Exeter: University of Exeter.

Mabry, E.A., & Barnes, R.E. (1980). The dynamics of small group communication.
Englewood Cliffs, NJ: Prentice Hall.

107

Maisto, S.A., Carey, K.B., & Bradizza, CM. (1999). Social learning theory. In K.E.
Leonard, & H.T. Blane (Eds.), Psychological theories of drinking and alcoholism
(2nd ed.). New York: Guilford Press.

Martin, C.M., & Hoffman, M.A. (1993). Alcohol expectancies, living environment, peer
inﬂuence, and gender: A model of college-student drinking. Journal of College

Student Development, 34, 206-21 1.

Mason, W.A., & Windle, M. (2001). Family religious, school and peer inﬂuences on
adolescent alcohol use: A longitudinal study. Journal of Studies on Alcohol, 62,

44-53.

Meilman, P.W., Leichliter, M.A., & Presley, CA. (1999). Greeks and athletes: Who
drinks more? Journal of College Health, 47, 187-190.

Meindl, J .R. (1990). On leadership: An alternative way to the conventional wiSDom.
Research in Organizational Behavior, 12, 159-203.

Michalodimitrakis, E., & Patsalis, A. (1987). Nitrogen narcosis and alcohol
consumption: A scuba diving fatality. Journal of Forensic Science, 32, 1095-1097.

Michigan State University, College of Human Medicine (1989). Replication of the
National Study of the Substance Use and Abuse Habits of College Student-athletes:
Final Report. East Lansing, MI: Michigan State University.

Miller-Johnson, S., Costanzo, P.R., Coie, J .D., Rose, M.R., Browne, D.C., & Johnson, C.
(2003). Peer social structure and risk-taking behaviors among Aﬁican American
early adolescents. Journal of Youth and Adolescence, 32 (5), 375-385.

Mooney, D.K., & Corcoran, L.J. (1991). Personal and perceived peer alcohol
expectancies: Their inﬂuences on alcohol consumption. Psychology of Addictive

Behaviors, 5, 85-92.

Nagoshi, CT. (1999). Perceived control of drinking and other predictors of alcohol use
and problems in a college student sample. Addiction Research, 7, 291-306.

Nagoshi, C.T., Wood, M.D., Cote, C.C., & Abbit, SM. (1994). College drinking game
participation within the context of other predictors of other alcohol use and
problems. Psychology of Addictive Behaviors, 8, 203-213.

National Collegiate Athletic Association (NCAA) (1997). Study of Substance Use and
Abuse Habits of College Student-Athletes. Overland Park, KS.

108

National Institute on Alcohol Abuse and Alcoholism (NIAAA) (2002). A Call to Action:
Changing the Culture of Drinking at US. Colleges, Retrieved March 10, 2005 from

http://www.collegedrinkingprevention.gov/reports/tltask.

National Institute on Drug Abuse (1991). National Household Survey on Drug Abuse:
Main Findings 1990, Rockville, MD: DHHS Publication 91-1788.

Nattiv, A., & Puffer, J.C.D. (1991). Lifestyles and health risk of collegiate athletes.
Journal of Family Practice, 33(6), 585-590.

Nattiv, A., & Puffer, J .C. (1997). Lifestyles and health risks of collegiate athletes: A
multi-center study. Clinical Journal of Sports Medicine, 7(4), 262-272.

Nelson, T.F., & Wechsler, H. (2001). Alcohol and college athletes. Medicine & Science
in Sports & Exercise, 33(1), 43-47.

Nichols, A.W. (1992). Exercise-induced anaphylaxis and urticaria. Clinical Sports
Medicine, 11, 303-312.

O’Brien, GP. (1991, March 22). The demon drink. Rugby News, p. 24.

O’Brien, CF. (1993). Alcohol and sport: Impact of social drinking on recreational and
competitive sports performance. Sports Medicine, 15(2), 71-77.

O’Brien, C.P., & Lyons, F. (2000). Alcohol and the athlete. Sports Medicine, 29(6),
295-300.

O’Hare, TM. (1990). Drinking in college: Consumption patterns, problems, sex
differences and legal drinking age. Journal of Studies on Alcohol, 51, 536-541.

Olds, R.S., & Thombs, D.L. (2001). The relationship of adolescent perceptions of peer
norms and parent involvement to cigarette and alcohol use. Journal of School

Health, 71, 223-228.

Olgilvie, BC. (1981). The emotionally disturbed athlete: A round table. The Physician
and Sportsmedicine, 9, 67-80.

O’Malley, P.M., & Johnston, L.D. (2002). Epidemiology of alcohol and other drug use
among American college students. Journal of Studies on Alcohol Supplement, 14,

23-39.

Ouellette, J .A., Gerrard, M., Gibbons, F ., & Reis-Bergan, M. (1999). Parents, peers and
prototypes: Antecedents of adolescent alcohol expectancies, alcohol consumption,
and alcohol-related life problems in rural youth. Psychology of Addictive
Behaviors, 13, 183-197.

109

O’Toole, T. (2002). Celebratory riots’ creating crises on campus. USA Today, April 9.

Overman, S.J. & Terry, T. (1991). Alcohol use and attitudes: A comparison of college
athletes and non-athletes. Journal of Alcohol and Drug Education, 21(2), 107-1 17.

Page, R.M., Hammermeeister, J ., Scanlan, A., & Gilbert, L. (1998). Is school sports
participation a protective factor against adolescent health risk behaviors? Journal

of Health Education, 29(3), 186- 1 92.

Parharn, W. (1993). The intercollegiate athlete: A 1990’s proﬁle. The Counseling
Psychologist, 21, 411-429.

Pate, R.R., Heath, G.W., Dowda, M, & Trost, S.G. (1996). Associations between
physical activity and other health behaviors in a representative sample of US.
adolescents. The American Journal of Public Health, 86(1 1), 1577-1582.

Pate, R.P., Trost, S.G., Levin, S., & Dowda, M. (2002). Sports participation and health-
related behaviors among US youth. Archives of Pediatrics &Adolescent Medicine,

154, 904-911.

Patetta, M.J., & Biddinger, P.W., (1988). Characteristics of drowning deaths in North
Carolina. Public Health Reports, 103(4), 406-411.

Peeler, C., Far, J ., & Miller, J. (2000). An analysis of the effects of a program to reduce
heavy drinking among college students. Journal of Alcohol and Drug Education,

45, 39-54.

Perkins, H.W. (1997). College student misperceptions of alcohol and other drug norms
among peers: Explaining cases, consequences and implications for prevention
programs. The Higher Education Center for Alcohol and Other Drug Prevention,

US. Department of Education.

Perkins, H.W., & Berkowitz, AD. (1986). Perceiving the community norms of alcohol
use among students: Some research implications for campus alcohol education
programming. International Journal of Addictions, 21, 961-976.

Perkins, H.W., Meihnan, P.W., Leichliter, J .S., Cashin, J .R., & Presley, CA. (1999).
Misperception of the norms for the frequency of alcohol and other drug use on
college campuses. Journal of American College Health, 47, 253-258.

Perkins, H.W., & Wechsler, H. (1996). Variation in perceived college drinking norms
and its impact on alcohol abuse: A nationwide study. Journal of Drug Issues, 26,

961-974.

Perry, C.L., & Grant, M. (1988). Comparing peer-led to teach-led youth alcohol
education in four countries. Alcohol Health Research World, 12, 322-326.

110

Perry, C.L., & Kelder, SH. (1992). Prevention. In Langenbucher, J .W. (Ed.), Review of
addictions: Research and treatment (V 01. 2). New York: Pergamon Press, 453-472.

Pfeffer, J. (1977). The ambiguity of leadership. The Academy of Management Review,
January, 104-112.

Plucker, J .A., & Teed, CM. (2004). Evaluation of an alternative methodology for
investigating leadership and binge drinking among sorority members. Addictive
Behaviors, 29(2), 381-388.

Prentice, D.A., & Miller, D.T. (1993). Pluralistic ignorance and alcohol use on campus:
Some consequences of misperceiving the social norm. Journal of Personality and

Social Psychology, 64, 243-256.

Presley, C.A., Leichliter, J .S., & Meilman, P.W. (1998). Alcohol and drugs on American
college campuses: A report to college presidents. Third in a series: 1995, 1996, and
1997, Carbondale, IL: Core Institute, Southern Illinois University.

Presley, C.A., Meihnan, P.W., & Leichliter, J .S. (2002). College factors that inﬂuence
drinking. Journal of Studies on Alcohol, 63(2), 82-91.

Presley, C.A., Meilman, P.W., & Cashin, J .R. (1996a). Alcohol and drugs on American
college campuses: Use, consequences, and perceptions of the campus environment,
Vol. 4: 1992-1994. Carbondale, IL: Core Institute, Southern Illinois University.

Presley, C.A., Meilman, P.W., Cashin, J .R. & Lyerla, R. (1996b). Alcohol and drugs on
American College Campuses: Use, Consequences, and Perceptions of the Campus
Environment, Vol. 3: 1991-1993. Carbondale, IL: Southern Illinois University.

Presley, C.A., Meihnan, P.W., & Lyerla, R. (1993). Alcohol and drug use among
residents of Greek houses. Discoveries: A Bulletin of the Core Institute.
Carbondale, IL: Southern Illinois University.

Rabow, J ., & Duncan-Schill, M. (1994). Drinking among college students. Journal of
Alcohol and Drug Education, 40, 52-64.

Rainey, C.J., McKeown, R.E., Sargent, R.G., & Valois, R.F. (1996). Patterns of tobacco
and alcohol use among sedentary, exercising, non-athletic and athletic youth.
Journal of School Health, 66(1), 27-33.

Raudenbush, S.W. & Bryk, AS. (2002). Hierarchical Linear Models: Applications and
Data Analysis Methods (2“‘1 Ed.). London: Sage Publications, Inc.

Rehm, J., Ashley, M., Room, R., Single, E., Bondy, S., F errence, R., & Giesbrecht, N.

(1996). On the emerging paradigm of drinking patterns and their social and health
consequences. Addiction, 91, 1615-1621.

111

Rodkin, P.C., Farmer, T.W., Pearl, R., & Van Acker, R. (2000). Heterogeneity of
popular boys: Antisocial and prosocial conﬁgurations. Developmental Psychology,
36, 14-24.

Sage, GR (1973). The coach as management: Organizational leadership in American
sport. Quest, 19, 35-40.

Schall, M., Kemeny, A., & Maltzman, 1. (1992). Factors associated with alcohol use in
university students. Journal of Studies on Alcohol, 53, 122-136.

Schulenberg, J ., Bachman, J .G., O’Malley, P.M., & Johnston, L.D. (1994). High school
educational success and subsequent substance use: A panel analysis following
adolescents into young adulthood. Journal of Health and Social Behavior, 35, 45-

62.

Schulenberg, J ., & Maggs, J .L. (2002). A developmental perspective on alcohol use and
heavy drinking during adolescence and the transition to young adulthood. Journal

of Studies on Alcohol Supplement, 14, 54-70.
Schulenberg, J ., Maggs, J .L, Long, S.W., Sher, K.J., Gotham, H.J., Baer, J .S., et al.

(2001). The problem of college drinking: Insights from a developmental
perspective. Alcoholism: Clinical and Experimental Research, 25(3), 473-304.

Shore, E.R., Rivers, P.C., & Berman, J .J . (1983). Resistance by college students to peer
pressure to drink. Journal of Studies on Alcohol, 44, 352-361.

Selby, R., Weinstein, H.M., & Bird, TS. (1990). The health of university athletes:
attitudes, behaviors, and stressors. Journal of American College Health, 39, 11-18.

Shults, R.A., Elder, R.W., Sleet, D.A., Nichols, J .L., Alao, M.O., Carande-Kulis, V.G. et
al. (2001). Reviews of evidence regarding interventions to reduce alcohol-impaired
driving. American Journal of Preventative Medicine, 21(4), 66-88.

Stainback, RD. (1997). Alcohol and Sport. Champaign, IL: Human Kinetics Publishers.

Straus, R., & Bacon, S.D. (1953). Drinking in College. New Haven: Yale University
Press.

Strauss, RH. (1991). Sports Medicine. Philadelphia: W.B. Saunders Co.

Strauss, V. (2001). College towns, school ofﬁcials seek end to post-game rioting: String
of disturbances part of growing trend, observers say. Washington Post, April 4.

112

Substance Abuse and Mental Health Services Administration. (2001). Preventing
problems related to alcohol availability: Environmental approaches prevention
enhancement protocols system (PEPS) Series, No. 3, DHHS Publication No. (SMA)
99-3298, Bethesda, MD: Center for Substance Abuse Prevention, Department of
Health and Human Services, (available at: http://www.health.org/govpubs/PHD822/

aar.aspx).

Thibault, G., Lambert, J ., Rivard, M., Brodeur, J.M., & St. Jacques, B. (1984).
Utilization of erogenic aids and the attitude toward safety in marathon runners. In
F .L. Katch (Ed.), Sport, Health, and Nutrition: The 1984 Olympic Scientific
Congress Proceedings (V 01. 2, pp. 205-211), Champaign, IL: Human Kinetics.

Thombs, D.L. (2000). A test of the perceived norms model to explain drinking patterns
among university student athletes. Journal of American college Health, 49(2), 75-

83.

Toomey, T.L., & Wagenaar, AC. (2002). Environmental policies to reduce college
drinking: Options and research ﬁndings. Journal of Studies on Alcohol, Supplement
No. 14, 193-205.

Toohey, J .V. (1978). Nonmedical drug use among intercollegiate athletes at ﬁve
American universities. Bulletin of Narcotics, 30(3), 61-64.

Toohey, J .V., & Corder, B.W. (1981). Intercollegiate sports participation and
nonmedical drug use. Bulletin of Narcotics, 33 (3), 23-27.

Top TV Sports Advertisers. Sports Inc., February 29, 1988.

Tricker, R., & Cook, D. (1989). The current status of drug intervention and prevention in
college athletic programs, Journal of Alcohol and Drug Education, 34(2), 38-45.

Tricker, R., Cook, D.L., & McGuire, R. (1989). Issues related to drug abuse in college
athletics: Athletes at risk. Sport Psychologist, 3, 155-165.

Turrisi, R. (1999). Cognitive and attitudinal factors in the analysis of alternatives to
binge drinking. Journal of Applied Social Psychology, 29, 1512-1535.

United States Department of Health and Human Services (DHHS) (1991). Adolescent
transitions: Alcohol and other drug use prevention (ADAM91-1725). Washington,

DC: Steinberg, L.

United States Department of Health and Human Services (DHHS) (2002). The NHSDA
report: Team sports participation and substance use among youths (SMASHA
Publication). Research Triangle Park, NC: Author.

113

Upcraﬁ, ML. (2000). Today’s ﬁrst-year students and alcohol. Paper prepared for the
Task Force on College Drinking, National Advisory Council on Alcohol Abuse and

Alcoholism, Bethesda, MD.

Urberg, K.A., Degirmenciouglu, S.M., and Pilgrim, C. (1997). Close ﬁiend and group
inﬂuence on adolescent cigarette smoking and alcohol use. Developmental

Psychology, 33, 834-844.

Wadler, G.I., & Hainline, B. (1989). Drugs and the Athlete. Philadelphia: FA Davis Co.

Watson, J .C. (2002). Assessing the potential for alcohol-related issues among college
student-athletes. Athletic Insight: The Online Journal of Sport Psychology, 4(3). 1-
14, http://www.athleticinsight.com/v0l4Iss3/alcoholassessmenthtm.

Wechsler, H. (2003). Watering down the drinks: The moderating effect of college
demographics on alcohol use of high-risk groups. American Journal of Public
Health, 93, 1929-1933.

Wechsler, H., & Austin, SB. (1998). Binge drinking: The ﬁve/four measure. Journal of
Student Alcohol, 59, 122-123.

Wechsler, H., Davenport, A.E., Dowdall, G.W., Grossman, S., & Zanakos, S. (1997).
Binge drinking, tobacco, and illicit drug use and involvement in college athletics: A
survey of students at 140 American colleges. Journal of American College Health,

45, 195-200.

Wechsler, H., Davenport, A.E., & Dowdall, G.W., Moeykens, B., & Castillo, S. (1994).
Health and behavioral consequences of binge drinking in college: A national survey
of students and 140 campuses. Journal of American Medical Association, 272,

1672-1677.

Wechsler, H., Dowdall, G.W., Davenport, A., & Castillo, S. (1995a). Correlates of
college student binge drinking. American Journal of Public Health, 85982-985.

Wechsler, H., Dowdall, G.W., Davenport, A., & Rirnm, E.B., (1995b). A gender-speciﬁc
measure of binge drinking among college students. American Journal of Public
Health, 85, 982-985.

Wechsler, H., Dowdall, G.W., Maenner, G., Gledhill-Hoyt, J ., & Lee, H. (1998).
Changes in binge drinking and related problem among American college students
between 1993-1997: Results of the Harvard School of Public Health College
Alcohol Study. Journal of American College Health, 47(9), 57-68.

Wechsler, H., Lee, J .E., Kuo, M., & Lee, H. (2000). College binge drinking in the
1990’s: A continuing problem. Journal of American College Health, 48, 199-21 1.

114

Wechsler, H., Lee, J .E., Kuo, M., & Lee, H. (2002). Trends in college binge drinking
during a period of increased prevention efforts: Finding ﬁ'om four Harvard School
of Public Health study surveys, 1993-2001. Journal of American College Health,

50(5), 203-217.

Werch, C.E., Pappas, D.M., Carlson, J .M., DiClemente, C.C., Chally, P.S., & Sinder, J .A.
(2000). Results of a social norm intervention to prevent binge drinking among ﬁrst-
year residential college students. Journal of American College Health, 49, 85-92.

Werner, M.J., & Greene, J .W. (1992). Problem drinking among college freshmen.
Journal of Adolescent Health, 13, 487-492.

Werner, M.J., Walker, L.S., & Greene, J .W. (1996). Concurrent and prospective
screening for problem drinking among college students. Journal of Adolescent

Health, 18, 276-285.

West, J .W. (1997). The Betty Ford Center Book of Answers. New York: Pocket Books.

White, A.M., J amieson-Drake, D.W., & Schwartzwelder, DH. (2002). Prevalence and
correlates of alcohol-induced blackouts among college students: Results of an email
survey. Journal of American College Health, 51(3), 1 17-130.

White, H.R., Bates, M.E., & Johnson, V. (1991). Learning to drink: Familial, peer, and
media inﬂuences. In DJ. Pittman, & H.R. White (Eds.), Society, culture, and
drinking re-examined. New Brunswick: Alcohol Research Documentation.

Winnail, S.D., Valois, R.F., McKeown, R.E., Saunders, R.P., & Pate, RR. (1995).
Relationship between physical activity level cigarette, smokeless tobacco, and
marijuana use among public high school adolescents. Journal of School Health, 65,

438-432.

Wood, M.D., Nagoshi, C.T., & Dennis, DA. (1992). Alcohol norms and expectations as
predictors of alcohol use and problems in a college student sample. American
Journal of Drug and Alcohol Abuse, 18, 461-476.

Yesavage, J .A., & Leirer, V.O. (1986). Hangover effects on aircraft pilots 14 hours after
alcohol ingestion: A preliminary report. American Journal of Psychiatry, 143,
1 546-1 5 50.

Ziemelis, A., Bucknam, R.B., & Elessi, A.M. (2002). Prevention efforts underlying
decreases in binge drinking at institutions of higher education. Journal of American

College Health, 50(5), 238-252.

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