A Dissertation Submitted to the Faculty
of
Xavier University
in Partial Fulfillment of the
Doctor of Psychology
by
Michael J. Biscaro
April 7, 2005
Approved:
Christine M. Dacey, Ph.D., ABPP Chair, Department of Psychology
Susan L. Kenford, Ph.D. Dissertation Chair
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Alcohol Expectancies, Coping, and Affect in Predicting College Student Alcohol Use: A
Cross-Sectional Examination of Freshmen and Seniors
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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Dissertation Committee
Chair Susan L. Kenford, Ph.D. Associate Professor of Psychology
Member Christine M. Dacey, Ph.D., ABPP Professor of Psychology
Member Debra Mooney, Ph.D. Director of Ignatian Programs
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Acknowledgments
Completing the dissertation was my final academic hurdle and now I have crossed
the finish line. I am on my way to a productive and prosperous professional career, and I
have many people to thank before I forge ahead in my journey as an independent
practitioner.
First and foremost, I would love to thank my beautiful wife, Kelley, as she has
given up many things to support me personally and professionally. Her patience,
understanding, and sacrifice are what have enabled to me to make it through the past 5
years. I will forever love her that much more for being with me during my graduate
school years. Oh, and lets not forget the hours she put in helping with data collection and
entry. I love you Kelley, let’s get on with our lives now!
Next, I would like to send my appreciation and thanks to my dissertation chair,
Dr. Susan Kenford. Dr. Kenford has been wonderful during this whole process. I am
grateful for all of the emails and the many hours she has spent working on the document.
She pleasantly put up with my procrastination, at least as far as I know, and continued to
encourage my persistence and dedication. I would also like to thank my committee; Dr.
Christine Dacey and Dr. Debra Mooney, your input and expertise were a blessing.
Last, but not least, I want to thank my family. Your emotional support and
encouragement has been my greatest motivator.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table of Contents
Page
Acknowledgements ...... i
Table of Contents ...... ii
List of Tables ...... üi
List of Appendices ...... iv
Chapter
I. Review of the Literature ...... 1
II. Rationale and Hypotheses ...... 19
III. Method ...... 22
IV. Proposed Analyses ...... 28
A. References...... 31
B. Appendices ...... 39
V. Dissertation ...... 53
A. References...... 82
B. Footnotes ...... 90
C. Tables...... 91
D. Appendices ...... 105
11
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. List of Tables
Chapter V
Table Page
1. Summary Table of the Demographic Variables by Class ...... 91
2. Means and Standard Deviations of Alcohol Consumption Variables by Class
and Gender...... 92
3. Means and Standard Deviations of the Predictor Variables of Interest by
C lass...... 93
4. Univariate Results for All Predictor Variables of Interest ...... 94
5. Summary of Hierarchical Stepwise Multiple Regression Analysis for
Variables Predicting Alcohol Consumption ...... 95
6. Summary of Hierarchical Stepwise Multiple Regression Analysis for Variables
Predicting Alcohol Consumption in Freshmen ...... 96
7. Summary of Hierarchical Stepwise Multiple Regression Analysis for Variables
Predicting Alcohol Consumption in Seniors ...... 97
8. Multiple Regression Values for Test of Motivational Model ...... 98
9. Correlation Matrix for Demographic Variables, Outcome Variables, and
Negative Consequences ...... 99
10. Comparison of Predictive Utility of Likelihood and Desirability Ratings for
Alcohol Expectancies ...... 101
111
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Proposal Page
A. Demographics and Outcome Survey ...... 39
B. Positive and Negative Affect Schedule (PANAS)...... 43
C. Comprehensive Effects of Alcohol (CECA) ...... 44
D. Three Factor Coping Scale ...... 47
E. Consequences Checklist ...... 50
F. Standardized Recruitment Script ...... 51
G. Informed Consent ...... 52
Chapter V
A. Approval Letter from Xavier University IRB ...... 105
IV
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Review of Literature
Introduction
The prevalence and incidence of alcohol use on college campuses have been of
great concern for decades. Past research has shown that alcohol use and abuse can have
many adverse effects, such as heart disease, memory impairment, immune and
reproductive disorders, social consequences, and economic problems (Broer, 1996).
Other detrimental effects are also evident for college students, such as being “seventeen
more times likely to miss a class, ten times more likely to vandalize property, and eight
times more likely to get hurt or injured” (Wechsler, 2002 p. xiv).
Alcohol is the drug of choice in the collegiate culture. According to Wechsler
(2002), the prototypical college culture has a pervasive alcohol problem. Colleges and
universities have a social culture in which there are drinking games, fake identifications
and a number of alcohol-based cultural myths (i.e., work hard play hard; drinking is my
business and does not hurt anyone else; increased sex drive, etc.). Problem drinking in
the college environment is further supported by the surrounding geographical area, which
is often populated by bars and establishments that cater to, and encourage, college
drinking. While students have the responsibility to choose, the surrounding culture
serves to enable their drinking (Wechsler, 2002).
In 1994 Presley, Meilman, and Lyerla developed the Core Alcohol and Drug
Survey, which was designed to assess substance use and abuse on university campuses.
The initial findings of the survey, based on a national sample of college students (N =
52,518) from 800 different universities, indicated that 85% of college students had
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. reported using alcohol in the previous 12 months. Compounding concern about the
widespread use of alcohol is the prevalence and incidence of binge drinking that occurs
on college campuses. Binge drinking is the consumption of large amounts of alcohol in a
short period of time. The most universal operational definition for binge drinking is five
or more drinks at one sitting (Wechsler & Nelson, 2001). This definition has been
adopted to facilitate the interpretation of results across alcohol related studies. Presley et
al. (1995) in their initial study found that nearly 40.4% of students were binge drinking
and this number has slightly risen over the years to 42% (Presley et al., 2001). Wechsler,
Lee, Kuo, Seibring, Nelson, and Lee (2002) reported that, nationally, 2 out of 5
undergraduate students were binge drinkers.
Research has revealed that students who drink excessively during their first year
in college are likely to continue this behavior into their second year (Wechsler, Isaac,
Grodstein, & Sellers, 1994, as cited in Broer, 1996). Therefore, students who have started
problem drinking keep it up, and universities would be wise to evaluate the extent of
early student drinking. Borsari, Neal, Collins and Carey (2001) suggested administrators
and researchers examine student drinking in terms of the number of drinks for both
typical and peak consumption, as typical and peak consumption appear to be most
strongly related to problematic drinking.
Universities and colleges are aware of the widespread drinking and have been
active participants in the movement to reduce the amount of alcohol consumption and
binge drinking. Early research focused on the extent and prevalence of drinking and was
most interested in quantifying the problem. However, while this has led to a firm grasp
of the scope of the problem, it has done less to identify the key factors related to college
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. drinking (Broer, 1996). The task of understanding the underlying dynamics of college
drinking is complicated by the multifaceted nature of the behavior. As Wechsler et al.
(2001) pointed out, no single measure, construct, or variable can measure the complexity
of excessive drinking. However, while knowledge of the précipitants of problematic
college drinking is still quite limited, several key domains have emerged as important
factors to assess and study further. Specifically, in the research to date, alcohol
expectancies, coping, and affect regulation have all shown promise for both
understanding and predicting college alcohol use.
Alcohol Expectancies
Social Learning Theory (SLT) (Bandura, 1969) posits that many behaviors are
observed, learned, and acquired from a person’s environment. During the acquisition
process, expectancies are formed that later guide and modify behavior. Expectancies are
cognitive frameworks that construe events in an “if-then” relationship, such that if a
certain event or behavior occurs then a certain event or behavior is expected to follow
(Goldman, Brown, & Christiansen, 1987). The role of expectancies in drinking behavior
has been widely studied. Jones et al. (2001), using a SLT framework, suggested
“behavior is explained by individuals having expectations of particular reinforcing effects
as the outcome of performing the behavior in question (p.59).” In terms of alcohol usage,
a person drinks alcohol because he or she has expectations about alcohol’s effects and
these expectations are molded by perceived and actual experiences with alcohol (Jones et
al., 2001).
Goldman et al. (1987) proposed that expectancies for alcohol are “intervening
variables” (p. 187) that link experience of the environment and alcohol use. Alcohol
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. expectancies are proximal variables that directly influence the decision to drink.
Proximal variables (e.g., beliefs and attitudes about alcohol) have been found to have
more predictive power than distal variables, such as social influences (Goldman et al.,
1987). Alcohol expectancies help mold the experience of drinking alcohol and are used
to decide whether to drink or to remain sober (Broer, 1996).
Brown, Tate, Vik, Haas, and Aarons (1999) found further support for the idea that
alcohol expectancies are a learned or acquired behavior when they showed that exposure
to an alcoholic family was predictive of future positive alcohol expectancies for
adolescents. Their results illustrated that alcoholic families had more positive alcohol
expectancies and modeled this assumption for the adolescents in the home, which
produced adolescents with more positive expectancies compared to adolescents from
nonalcoholic families.
Alcohol expectancies have been found to be related to alcohol use in multiple
ways (Hufford, 2001). Expectancies have been shown to be adequate predictors of
problematic drinking in college students (Brown, 1985a; Brown, 1985b); able to help
differentiate those at risk for problematic drinking (Christiansen, Smith, Roehling, &
Goldman, 1989); able to distinguish alcohol dependents from non dependents (Connors,
O’Farrell, Cutter, & Thompson, 1986); causally affect alcohol intake (Sharkansky &
Finn, 1998) and predict future drinking patterns (Carey, 1995).
Christiansen et al. (1989) examined the predictive utility of alcohol expectancies
for alcohol consumption in a longitudinal sample of 871 seventh and eighth grade
preadolescents. The participants were followed for one year. The authors found that
several alcohol expectancies were predictive of the amount of alcohol consumption. In
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. particular the factors that were consistently predictive of problematic alcohol use were
global positive expectancies, enhancement of social behavior, enhancement of sexuality,
arousal and relaxation.
The predictive power of alcohol expectancies was also shown in a sample of 924
preadolescents in Norway (Aas, Leigh, Anderssen, & Jakobsen, 1998). The participants
in this study were followed for three years (from 7* to 9* grade) and the authors found
some striking results. The number of students who reported drinking rose from 40% in
the 7*'’ grade to 64% in the 9* grade, and the proportion of students reporting being drunk
in the last 6 months rose from 10% to 40%. The authors also found that the expectation
of social enhancement was predictive of use and increased with age. Boys and girls were
not significantly different on any aspects of the model.
As learned and socially determined cognitive structures, expectancies have both
positive and negative forms. Numerous studies have investigated the effects of both
positive and negative expectancies (Jones et al., 2001). Positive expectancies, or the
beliefs about the enhancing effects of alcohol, have been the most widely studied. Global
positive expectancies (e.g., “Drinking makes the future seems brighter,” “Alcohol seems
like magic,” or “I feel more coordinated after I drink”) have been found to predict small
to significant amounts of the variance in alcohol expectancy models (Biscaro, Broer &
Taylor, 2004; Broer, 1996; Brown, 1985b; Brown, Christiansen, & Goldman, 1987;
Burden & Maisto, 2000; Carey, 1995).
Positive expectancies have been found to increase motivation to drink. Negative
alcohol expectancies have been associated with a reduction in drinking behavior, and
motivation to decrease problematic drinking (Jones et al., 2001). While negative
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. expectancies appear to be more crucial in predicting cessation rather than initiation of
alcohol use, negative expectancies should still be included in alcohol use research. For
example, the immediate effects of negative expectancies, such as impaired balance, need
to be assessed with distal effects (i.e., a hangover) to understand the impact on behavior
of the two types of beliefs (McMahon et al., 1994). Negative expectancies may be key
for future drinking behavior especially among the social, experimental drinker.
Consistent with this, Ramsey et al. (2000) found that individuals who had experienced
bad alcohol related events were more open to changing drinking behaviors than those
who had not.
An important and often neglected aspect in assessing alcohol expectancies is a
person’s subjective evaluation of the particular expectancy. Essentially, subjective
evaluations are when a person rates the desirability of particular alcohol expectancies.
Much research on alcohol expectancies involves only the measurement of the person’s
perceived likelihood of experiencing certain effects from alcohol (i.e., “If I were under
the influence of alcohol.. .1 would be brave and daring”). Hence, people are rating what
they expect alcohol will do to them rather than how favorably they view the effect.
Given that people may view outcome expectancies as highly likely but unappealing, a
subset of expectancy research has worked to capture the subjective perception of alcohol
effects (i.e., “this effect is...bad, slightly bad, neutral, good, etc.”)(Jones et al., 2001).
While there have been various methods suggested for calculating this subjective
expectation, the most widely used is to have participants provide a subjective evaluation
of a particular alcohol expectancy. This then provides a separate score from the
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. likelihood dimension and reflects how desirable an anticipated outcome is viewed
(Fromme, Stroot, & Kaplan, 1993; Jones et al., 2001).
While some research has found that combining subjective evaluations with
positive and negative alcohol expectancies significantly adds to the prediction of alcohol
use (Werner, Walker, & Greene, 1993), other studies support examining subjective
evaluations separately (Burden et al., 2000; Fromme et al., 1993). In support for
examining subjective evaluations and alcohol expectancies together, Werner et al. (1993)
found that higher likelihood ratings for the positive effects for alcohol and more
favorable subjective evaluations of negative expectancies were associated with more
problematic drinking and consequences. In contrast Burden et al. (2000) examined
likelihood and desirability evaluations separately and found in a sample of 171
undergraduate students that the participant’s subjective evaluations of expectancies
accounted for a large amount of the variance in predicting alcohol consumption above
and beyond alcohol expectancies. However, Fromme et al. (1993) found that while
subjective evaluations alone predicted typical quantity of alcohol consumed, when
combined with likelihood ratings, subjective evaluations of expectancies did not add any
predictive utility. Given the mixed finding to date, it appears useful to assess for both the
likelihood and favorability of positive and negative expectancies.
Expectancy research has shov/n that gender plays an important role in alcohol
use and outcome expectancies. Mooney and Corcoran (1989) studied the effects of social
assertiveness and alcohol expectancies on alcohol consumption in a sample of 277
undergraduate students. Consumption was defined in terms of typical quantity,
maximum quantity, and frequency. The authors found that there were gender differences
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in the prediction of alcohol consumption. For men who were low in social assertiveness,
expectancies of tension reduction predicted alcohol use. However, for women who were
low in social assertiveness, expectations of global positive changes, enhanced social
assertiveness and tension reduction all predicted alcohol consumption.
Mooney et al. (1987) conducted a study with a sample of 325 undergraduate
students which examined age, sex, and expectancies to predict alcohol consumption. The
authors found that age, sex, and social/physical pleasure and social assertion expectancies
were predictive of quantity of alcohol consumed. Age interacted with alcohol
consumption in women, such that younger women reported more alcohol use per
drinking occasion and older women were drinking more frequently. Social/physical
pleasure and social assertion were significant predictors for alcohol consumption in both
men and women. Additionally, men consumed more alcohol when they expected global
positive effects, while tension reduction added predictive power for alcohol use in female
participants. The authors argued that men drink more to gain the euphoric and positive
effects of alcohol, whereas women drink to reduce tension or negative affect states.
Coping
In addition to alcohol expectancies, coping has been a focus in the alcohol use
literature. Coping, or the ability to handle life stressors, is an important construct when
examining alcohol use or any problematic behavior. An interesting aspect of coping is its
implication as a mediator variable (Rohde, Lewinsohn, Tilson, & Seely, 1990) between
stress and problematic behaviors (i.e., excessive drinking). The more effective coping
resources a person has, the less likely he or she is to experience distress in the face of a
challenge, which in turn reduces the risk of maladaptive behavior.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. In order to cope with a stressful situation, one must decide how to broach the
stressor(s). Folkman, Lazarus, Gruen, and Delongis (1986) defined two general types of
coping; problem-focused and emotion-focused coping. In problem-focused coping the
goal is to be solution oriented and focus on solving a particular problem (i.e., engage in
active, rational problem-solving). Emotion focused coping aims to stabilize the
emotional dysregulation that occurs during a stressful event (i.e., engaged in isolation,
avoidance, escape, etc.). Folkman et al. (1986) found in a sample of 150 community
adults that people used both of these methods of coping with stressful situations and a
balance of these strategies was most beneficial. However, problematic situations arise
when the environment exceeds the available coping strategies a person has within his or
her repertoire (Cooper, Russell, Skinner, Frone, & Mudar, 1992; Folkman et al., 1986).
Abrams and Niaura (1987) stated that “coping skills are a critical determinant in
the decision to drink or not to drink and whether drinking is normal or maladaptive
(p. 161).” Coping in the context of alcohol use is a multi-dimensional construct. A
person has to develop alcohol specific coping abilities, the ability to say “no” to a drink,
as well as general coping skills or lifestyle balance, such that he or she performs well in
school, has adequate social support, and healthy peer relationships, etc. (Abrams &
Niaura, 1987).
Research has identified certain factors that influence assertive drink refusal skills.
Contextual and social factors, such as being in situations where alcohol is present (i.e.,
parties, bars, and other social gatherings) may increase pressures to drink via the need to
feel socially accepted. Biological factors also play a role in assertive drink refusal, as
alcohol can dampen the body’s ability to self regulate. For example, when a person
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drinks alcohol, his or her awareness of the rise in blood alcohol level decreases with
continued consumption, which can lead to intoxication of the brain and affect cognitive
functioning. Clearer cognitive functioning is necessary for assertive drink refusal. If a
person’s cognitive functions such as insight and judgment are impaired, the ability to
recognize personal impairment is limited. In stressful or challenging situations, if
drinking factors exceed available coping mechanisms, then drinking to cope is the
probable outcome (Abrams et al., 1987).
The transition to college is stressful and when students enter their first year of
college there are many demands placed on them intellectually, physically, socially, and
even financially. As a result, students are forced to develop and implement methods of
coping. Alcohol is often a part of coping with the newly encountered demands. This, in
itself, is not necessarily problematic. Some researchers have found that drinking alcohol
can be an adaptive device for the transition. For example, Zaleski, Levey-Thors, and
Schiaffino (1998) found in a sample of 95 freshman students that alcohol was an effective
coping mechanism when it was used in moderation, related to peer social support, and the
students had a positive outlook in regard to their future. The caveat the authors pointed
out was that alcohol was only adaptive in the subsample of students who were well
equipped to deal with the transition into college and, in the long run, alcohol can be
harmful if it is used for the reduction of stress. Therefore, for the majority of the
incoming college students, alcohol is not a suggested means to cope.
Due to its depressant qualities, alcohol can serve as a coping mechanism to
manage stress or tension states. Typically, alcohol is used to reduce stress only if
alternate coping resources were never in place or have been exceeded. Cooper et al.
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(1992) in a study of stress and alcohol use, found that men, specifically those with an
avoidant coping style who held strong positive alcohol expectancies, were particularly
vulnerable to heavy drinking patterns. Individuals who rely on avoidant means of
coping, such as denying or ignoring the problem, are more likely to drink in response to
stressful situations. In contrast, people with a more problem-focused and planned
approach to stressful situations are less likely to drink during periods of distress (Cooper
et al., 1992). Together, deficient coping mechanisms and the expectancy that alcohol has
positive effects increases the probability of excessive drinking (Cooper, Russell, &
George, 1988; Stewart, Zvolensky, & Eifert, 2002).
Understanding the underlying mechanisms of alcohol use in college is
complicated as alcohol serves multiple purposes. As discussed in an unpublished
manuscript by Broer (1996), college drinking can be conceptualized as a rite of passage
and is an expected behavior for all students. This creates greater complexity in
understanding the causes of problem drinking, as it can be difficult to distinguish among
students who are drinking to cope, drinking to escape, and/or drinking to uphold the
norm. However, while on the surface those types of drinkers may initially look similar,
they have been found to differ in important ways. Williams and Clark (1998) made a
distinction between escape drinking (or drinking that is negatively reinforcing) and social
drinking (which is positively reinforcing). They found that, in a sample of 300 university
students, escape drinking was more likely to predict excessive binge drinking, but it was
only indirectly related to alcohol consumption. Social drinking was more predictive of
alcohol consumption, with those who drank for social reasons consuming more alcohol
over time but less in a short, discrete period.
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Affect
Affect has been shown to have a key role in drug use across all substance
categories. Affect and affect regulation are important in the initiation and cessation of
alcohol consumption. Affect has been shown to have two broad dimensions. Positive
Affect (PA) and Negative Affect (NA). As defined by Watson, Clark, and Tellegen
(1988), Positive Affect is “the extent to which a person feels enthusiastic, active, and
alert (p. 1063)” and Negative Affect is a general distressed feeling marked by negative
mood states, such as anger, contempt, nervousness, fear, etc. These emotional
dispositions are manifested as states, traits, or both. Trait PA and NA refer to person’s
core personality traits, while state PA and NA refer to emotional responsiveness to
external and internal cues (Watson et al., 1988).
In general, affect dysregulation has been linked to a variety of psychological
disorders. Comorbid substance use disorders (e.g., alcoholism) are found in about 50%
of people with psychological difficulties (Reiger, Meyers, Kramer, Robins, Blazer,
Hough et al., 1984). Typically negative affect is associated with “psychiatric distress”
(Zack, Toneatto, & Macleod, 1999, p. 518) and it has been shown that negative affect is
closely associated with substance use relapse (Marlatt and Gordon, 1985).
Henderson and Galen (2003) examined the relationship between affect and
substance abuse severity in a sample of 147 male inpatient substance users. The
participants were divided into four subgroups (high substance use severity and high NA
affect, high severity and low NA, low severity and late age of onset with moderate PA
affect, and low severity with early age of onset with high PA). The authors found that the
participants in the high severity/high NA group were at greatest risk for depression (79%)
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in contrast to those in the low severity and high PA who were the lowest risk for
depression (33%). Thus, it appears that, when negative affect is coupled with severe use,
individuals are particularly prone to developing comorbid depression.
Wills, Sandy, Shinar, and Yaeger (1999) examined the contributions of positive
and negative affect in a 3-year longitudinal study of 1,702 ethnically diverse adolescents.
The authors found that positive affect was related to lower levels of substance use and
negative affect was related to higher levels of substance use. Negative affect was
“buffered” by positive affect in that increased positive affect decreased the influence of
negative affect on substance use. The authors also found that over time those with more
unpleasant affect used more substances. Colder and Chassin (1997) also supported the
role of negative affect in adolescent substance use, specifically alcohol use. The authors
found in a sample of 427 adolescents that negative affectivity was higher in participants
who used alcohol in excess compared to those who did not.
In addition to epidemiological data, affect has also been linked to many formal
hypotheses and models of alcohol and substance use, such as Tension Reduction Theory
(TRT), Automatic versus Nonautomatic processing, Two-Factor Avoidance Theory, and
A Motivational Model of alcohol use. TRT (Conger, 1956) holds that an environmental
stressor creates tension for which the human response is to seek relief. Persons who do
not have alternate ways of coping with the stressful situation turn to alcohol (Capped &
Greeley, 1987). In TRT, tension increases negative affect or negative emotional states
(e.g., confusion, anger, depression, etc.), which increases the person’s desire to seek relief
and reduce their negative feeling state. Tiffany (1990) discussed a model of automatic
and nonautomatic cognitive processing to explain substance use. This model posits that
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negative affect can trigger the urge to use alcohol, and consequently this urge interferes
with the controlled cognitive processes needed to resist the desire to drink. Stasiewicz
and Maisto (1993) discussed the Two Factor Avoidance Theory, which posits that
negative affect becomes a conditioned emotional response (CER) and the CER then
serves to motivate the person’s response to continue drinking. Therefore, when a person
is exposed to a negative emotion or cue in the future, that person is likely to continue to
respond using the substance due to the previous learned reinforcing effects.
Another theory that has been studied in the affect literature is the Motivational
Model posited by Cooper, Frone, Russell, and Mudar (1995). The authors examined in
two biracial samples (one consisting of 960 adults and one of f ,006 adolescents) the role
of positive and negative emotions in alcohol use. The authors hypothesized that alcohol
use serves a regulatory function for a person’s emotional state and individuals use alcohol
during negative affective experiences to reduce anxiety and tension, or drink to foster
positive emotions when feeling fatigued or depressed. As such, they proposed two
distinct pathways to alcohol use. One they labeled “Drinking to Cope” which predicted
people would use alcohol if they relied on maladaptive coping processes (avoidant
coping), held positive expectancies for alcohol’s ability to reduce tension, and had
negative affect; the other they labeled “Drinking to Enhance” which predicted people
would use alcohol for enhancement if they expected drinking to enhance social/emotional
experiences, increase positive affect, and if they engaged in sensation seeking (i.e., those
that seek high levels of stimulation and desire positive reinforcement). Results supported
the two hypothesized pathways and both drinking to enhance and drinking to cope were
predictive of alcohol use in both samples.
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Other studies have offered additional support for Cooper et al.’s (1995)
motivational models. Hussong et al. (2001) examined a sample of 74 community-based
adolescents. The authors found that increased alcohol consumption was related to
positive and negative affect and gender differences. There was a significant relationship
between affect and drinking over time. Negative affect was related to increased alcohol
consumption over time. Increased negative affect over the weekend, such as hostility,
predicted increased weekly drinking. Positive affect predicted more drinking whether it
was over the weekend or during the weekday. Men showed greater drinking on the
weekends, but not more overall drinking when compared to women. Consistent with
Cooper et al.’s (1995) model, participants’ emotions motivated their alcohol
consumption. Adolescents who had increased negative emotions on the weekend drank
more to reduce or cope with those emotions the following week, while those who had
more positive emotions, whether it was on the weekend or weekday, drank to enhance
those emotions.
Hussong and Chassin (1994) found in a three-year longitudinal study of 426
adolescents a relationship between anger (a negative emotional state) and both quantity
and frequency of alcohol use. The authors also found that stress was predictive of
quantity and frequency of drinking. However, the relationship between stress and
consumption decreased when anger was controlled. The authors suggested that, although
the mediational effects of anger and stress were not supported, negative affect (e.g.,
anger) should still be considered in adolescent alcohol use. Colder (2001) examined the
effects of negative emotionality and life stress on alcohol consumption in a sample of 80
college students. The author found that using a negative mood induction (i.e., viewing
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aversive pictures) produced higher levels of stress and negative affect and increased
participants’ alcohol consumption. Participants’ skin conductance response (SCR) was
used to measure negative emotional arousal. The author found that negative emotional
arousal led to more alcohol use for drinking to cope, drinking for enhancement, and
social reasons.
Armeli, Tennen, Affleck and Kranzler (2000) studied the impact of affect on
alcohol use in a sample of 108 community residents. This study differed from others as it
examined how daily events influenced affect change and how this was related to alcohol
use. The authors found that positive and negative daily events had an impact on positive
and negative affect change as well as on the desire to drink. The results showed that
those who experienced more negative nonwork events (problems with friends, significant
others, family, etc.) were more likely to drink than those who did not. However, negative
work events (i.e., problem with too much overtime) had no impact on alcohol use.
Therefore, those who experienced more negative interpersonal interactions were more
prone to develop negative affect and increase their drinking. Additionally, those who
experienced more positive nonwork events (i.e., kissed, had a pleasing physical
experience, or expressed love to someone), and increased positive affect, were more
likely to drink than those who did not have such experiences. The findings that both
negative and positive interpersonal events increased consumption supports the two
pathway (“drinking to cope” and “drinking to enhance”) model proposed by Cooper et al.
(1995).
While the present study is focused on person-factors (i.e., alcohol expectancies,
coping, and affect), peer influence on alcohol consumption has been found to be such a
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potent predictor that it requires inclusion in any model of young adult substance use.
Chassin, Pitts, and Frost (2002) examined predictors of substance use in a 5-7 year
longitudinal study. The authors found in a sample of 270 binge drinking adolescents that
higher peer alcohol use was related to more high risk drinking. Andrews, Tiidesley,
Hops, and Li (2002) examined peer influence on substance use in a sample of young
adults (N ^ 276) and found that peer alcohol use was predictive of increased binge
drinking as well. Peer alcohol use has also shown to be predictive of higher rates of
alcohol consumption in a sample of 3,222 ethnically diverse 7^*' graders followed over a
3-year period (Bray, Adams, Getz, & McQueen, 2003). Additionally, Latimer, Winters,
Stinchfield, and Traver (2000) found in a sample of 225 adolescents that pretreatment
peer substance use was predictive of posttreatment alcohol and marijuana use at both the
6 and 12 month follow up. Thus, increased peer usage predicted future drinking and
substance use behaviors.
The influence of peer use has been found to extend into the development and
impact of expectancies. Mooney & Corcoran (1991) provided data that illustrates how
peers influence alcohol expectancies and alcohol consumption. In this study, a sample of
183 college students reported their own alcohol consumption and alcohol expectancies
and also their perception of the consumption and expectancies of their friends (e.g.,
answered sets of items such as “alcohol makes me feel..." “alcohol enables my best
friend to..."). The authors found that both men and women were influenced by not only
their personal expectancies but also by their perceptions of their peers drinking and
expectancies. However, men and women differed in their perceptions and expectancies,
such that men thought that they drank equivalent amounts as their peers per drinking
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occasion but tended to think that their peers were drinking more frequently. Women did
not feel they drank similar to their peers in either domain. This study highlights the
importance of assessing perceived peer alcohol use, as peer relationships and peer
influence were predictive of drinking above and beyond alcohol expectancies.
While the preponderance of the literature on college student alcohol use focuses
on predicting behavior, few studies have focused on both cognitive (i.e., expectancies and
coping style) and emotional (affect) variables as predictors. Additionally, this study is
unique as it attempts to examine and predict alcohol use for both freshmen and seniors.
This will allow for an exploratory, cross-sectional examination of maturational factors on
alcohol consumption and drinking behaviors.
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Chapter II
Rationale and Hypotheses
Drinking is problematic on college campuses and the prototypic college campus
has pervasive alcohol problems (Wechsler, 2002). Eighty-five percent of college
students report drinking within the past 12 months (Presley et al., 1994). Forty percent of
students reported binge drinking in 1994 and 42% of students reported binge drinking in
2001 (Presley et al., 1994; 2001). Given the seriousness of the problems, efforts to
understand and curb college drinking are important and necessary. The aim of this study
is to better understand what predicts excessive drinking in order to promote the
development and increase the efficacy of programs targeting excessive drinking on
campus.
The predictor variables of interest are positive and negative alcohol expectancies,
coping style, and positive and negative affect. While peer alcohol use has shown to be
important in adolescent drinking (Andrews et al., 2002; Bray et al., 2003; Chassin et al.,
2002; Latimer et al., 2000; Mooney & Corcoran, 1991), it is not of key interest in this
study as the focus is on individual difference or person factors and, peer use will be
treated as a control or background variable. As such, the variables of interest will be
tested for their ability to predict alcohol use above and beyond peer use. Given the
preponderance of data that show the impact of peer use on drinking behavior, including
peer use as a control variable will provide a very stringent test of the key variables
The variables of interest were selected based on their documented relation with
alcohol consumption and foundation in SLT. SLT purports that behavior is maintained
and performed by the expectations people hold for the reinforcing effects of that
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particular behavior over time (Bandura, 1969). In terms of alcohol usage, a person drinks
alcohol because he or she has expectations about alcohol’s effects and these expectations
are molded by perceived and actual experiences with alcohol (Jones et al., 2001). Carey
(1995) argued that there are two important reasons for assessing alcohol expectancies: (1)
expectancies are useful in predicting future alcohol use, and (2) expectancies relate to and
predict alcohol consumption.
The construct of coping is of interest because of its role as a mediator in alcohol
use. Abrams and Niaura (1987) stated that “coping skills are a critical determinant in the
decision to drink or not to drink and whether drinking is normal or maladaptive (p. 161).”
The more coping resources a person has, the greater ability he or she possesses to manage
problematic situations.
Affect plays a critical role in alcohol use as well. Research has shown that
increased negative affect may lead to more problematic alcohol use. However, the
function of affect has been debated in different theories (i.e., TRT, Two-Factor
Avoidance, Automatic vs. Nonauthomatic processing, etc.). The Motivational Model of
alcohol use proposed by Cooper et al. (1995) indicated that affect has a motivational
affect on alcohol consumption, such that those that those who “drink to cope” are
motivated to use alcohol by increased negative affect, avoidant coping skills, and tension
reduction expectancies; and those who “drink to enhance” are motivated by positive
affect, sensation seeking behavior, and expectancies that alcohol will facilitate social and
emotional experiences.
Following from this social learning framework, the following hypotheses will be
explored:
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(Hi) The constructs of Alcohol Expectancies, Coping, and Affect are expected to
be key to alcohol consumption (i.e., typical number of drinks consumed in one drinking
occasion multiplied by the number of days this behavior occurs in a typical week) in both
freshmen and seniors. A formal prediction model will be built to determine which
aspects of these constructs are most related to alcohol consumption.
(H2 ) Seniors will drink and binge less than Freshmen, as it is hypothesized that
Seniors will have moved out of the transitional phase where the effects of social pressure
and adjustment are most pronounced. However, it is hypothesized that the influence of
expectancies, coping, and affect will increase as fewer seniors will be drinking as a
normative rite of passage.
Additionally, the following exploratory hypotheses will be examined:
(H 3) Alcohol Expectancies (Positive), Coping (specifically Ineffective Escapism),
and Affect (Negative) will be predictive of alcohol consumption in both Freshmen and
Seniors. Persons who have more positive expectancies, more avoidant coping styles, and
more negative affect will report greater consumption.
(H 4) Men will consume a higher number of drinks and binge more frequently than
women.
(Hs) Consequences of alcohol, other drug use, and perceived peer drinking will
have an impact on alcohol use with more consequences and more drug use being
associated with higher drinking rates. Perceived peer drinking may have a greater
influence in freshmen alcohol users than senior drinkers.
(He) Desirability ratings of alcohol expectancies will be examined for predictive
utility beyond expectancy likelihood ratings.
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Chapter III
Method
Participants
Participants will be recruited from a private Midwestern university with about
2600 undergraduate students. The sample will not contain any individuals under the age
of 18. The sample size for each cohort will be approximately 150 Freshman and 150
Seniors who will be recruited either through the following undergraduate classes which
are comprised primarily of Freshmen and Seniors: Freshmen classes - Psychology 101,
English 101, Theology 111, Philosophy 100, Mathematics 120, SpanishlOl, and
Information 200; Seniors classes - Arts 441, Biology 498, English 499, Social Work 424,
Accounting 421, Accounting 431, Economics 300, Marketing 400, and Psychology 499
or through the dormitories.
The traditional guidelines for selecting sample size for multiple regression
analysis has been 10:1 (10 participants to 1 predictor); however, recently this method has
been criticized for underestimating the power needed (Maxwell, 2000). Maxwell (2000)
argued that sample sizes of up to 70:1 may be required to maximize power in multiple
regression analysis and acknowledges that there is no universally agreed upon manner to
calculate power for this type of analysis. Given these issues, this study will use a
conservative sample size of 150 students for each cohort (N = 300) to maximize the
statistical rigor of the multiple regression analyses and provide a ratio between 20:1 and
30:1 for each key construct of interest.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 23
Measures
Demographic and Outcome Survey
This is a self-report survey that was created by the author to assess information in
several key domains, such as demographics, drinking behaviors and preferences, and
drug use (See Appendix A). Certain questions were adapted from the Core Alcohol and
Drug Survey (Core: Presley et al., 1994). The Core survey was devised specifically to
examine alcohol and drug use on college campuses (Broer, 1996). The outcome variable
chosen for this study is typical quantity (as defined: the number of drinks consumed in a
typical drinking occasion multiplied by the number of drinking occasions per week).
Both maximum quantity (or the largest number of drinks consumed since the start of the
semester), and the number of binge episodes (having 5 or more drinks at one time) within
the past two weeks will be used as outcome variables in the exploratory analyses. The
aforementioned outcome variables were chosen, as these appear to be the most
parsimonious and generally accepted by the literature (Bosari et al., 2001; Mooney et al.,
1989; & Wechsler et al., 2001).
Consequences Checklist
This is a self report checklist that was adapted from the Core Alcohol and Drug
Survey, question 21, and is intended to assess the negative outcomes associated with
alcohol and drug use (See Appendix B). The participants rate a consequence on a 0-5
Likert type scale. This checklist is based on work by Rohsenow (1983) who found that
people who drank less did not expect pleasant consequences when using alcohol.
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However, heavy drinkers continued to drink despite negative consequences, which she
felt suggested that expected positive effects of alcohol outweigh the consequences.
Comprehensive Effects of Alcohol (CEOA)
The Comprehensive Effects of Alcohol (CEOA: Fromme, Stroot, & Kaplan,
1993) is a 76-item self-report measure (See Appendix C) that was designed to measure
both positive and negative alcohol expectancies (38 items), as well as a person’s
subjective evaluation of those expectancies (38 items). The measure was validated on
samples of primarily Caucasian, undergraduate students (N = 344 for the initial
exploratory analysis, and an additional 485 for the confirmatory factor analysis).
The measure is divided into two parts, (1) assessment of outcome expectancies
(e.g., “I would be outgoing” or “I would feel moody”), which are rated on a 4-point
Likert type scale (1 = disagree^ 4 = agree), and (2) the subjective evaluation of the
expected effect, which is rated on a 5-point Likert type scale (1 = bad, 3 = neutral, 5 =
good).
Factor analysis has shown that this measure has 4 positive expectancy factors
(Sociability, Tension Reduction, Liquid Courage, and Sexuality) made up of the 20
positive items and 3 negative expectancy factors (Cognitive Behavioral Impairment,
Risk/Aggression, and Self-Perception) containing the 18 negative items (Fromme, et al.,
1993). Factor loadings for the items in each factor ranged from .33-.79 for positive
factors and from .S5-.99 for negative factors. The measure demonstrated adequate
internal consistency, temporal stability, and construct validity. The temporal stability for
the expectancies and evaluations were as follows: .66-.72 for positive expectancies, .59-
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.78 for positive evaluations, .75-.81 for negative expectancies, and .53-.6S for negative
evaluations.
Three Factor Coping Scale
The Three Factor Coping Scale (Rhode et al., 1990) is a 48-item, self-report
measure using a Likert type 0-7 scale designed to clarify the dimensionality of coping
and various coping styles (See Appendix D). The measure has 3 major factors: Cognitive
Self Control (e.g., “I usually plan my work when faced with a number of things to do”),
Ineffective Escapism (e.g., “Keep away from people.”), and Solace Seeking (e.g., “Spend
time with friends.”). The authors did not report validity and reliability.
Positive and Negative Affective Schedule (PANAS)
The Positive and Negative Affective Schedule (PANAS: Watson, Clark, &
Tellegen, 1988) is an affect checklist developed to capture two dimensions of affect (See
Appendix E). The PANAS is 20-item self-report measure that asks the participant to rate
on a 5-point Likert-type scale (1 = very slightly or not at all, 3 = moderately, 5 =
extremely) the extent to which he or she has felt the particular mood descriptor (e.g.,
interested, alert, excited, upset, etc.). The participants are asked to rate the descriptor
within a given time frame (e.g., moment, today, past few days, past week, past few
weeks, year, and general). The normative sample sizes for each of the time frames were
n = 660 (moment), 657 (today), 1,002 (past few days), 586 (past few weeks), 649 (year),
and 663 (general).
The PANAS has good internal consistency with alpha coefficients ranging from
.86- 90 for PA and .S4-.87 for NA. Results showed that the reliability was not affected
by the time frame used. Test-retest reliability was highest for PA and NA assessed within
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the “in general” time frame (.68-.71 respectively) and lowest for the “today” time frame
(.47-.39 respectively). The authors found that both of the PANAS factors (PA and NA)
had convergent correlations that ranged from .89 to .95 and discriminant correlations that
ranged from -.02 to -.18
Procedure
Participants will be recruited one of two ways: (1) from undergraduate courses at
the end of the scheduled class time or (2) from the dormitories at a prescheduled
dormitory meeting. A standardized script will be read to each group during the
recruitment phase (see Appendix F). The participants recruited from classes will
complete the study at another time, but within 3 days of recruitment. They will not be
required to give their names to the investigator, instead, participants will choose from a
block of possible dates and times. Each person will take a slip and write down the date,
time, and room number (in Elet hall) for which they signed up. Participants recruited
from the dormitories will complete the study at the time of recruitment if they choose to
participate. Administration of the materials will be in a group format for both
recruitment samples. Prior to completing the packet of information, participants will
have the purpose of the study explained to them and informed consent will be reviewed.
Participants will keep the written informed consent; they will not be required to sign the
consent form to ensure that the data is anonymous.
Participants may be given extra credit (at the discretion of the professor), and
those who choose to, will be entered into a random drawing for four gift certificates of
$50.00 each from local venues (i.e., Kenwood Mall, Kroger, Block Buster, and Long
Horn Restaurant). All participants will be given a slip that confirms their completing the
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study and it will be the students’ responsibility to turn their slip into the professor for
extra credit if applicable. Participants will have the choice to opt in or opt out of the
drawing. Those interested in entering the drawing will write their name on a piece of
paper and place it in an enclosed box. Therefore, the only names that will be known will
be those that win a gift certificate. The drawing will take place immediately following
data collection and all names will be destroyed immediately after the drawing is
completed. Anonymity will be maintained further by using only pre-assigned subject
numbers, not names, on all data collected
At the time of data collection, each person will receive an envelope containing the
assessment measures; (a) Demographic and Outcome Survey, (b) Positive and Negative
Affective Schedule (PANAS), (c) Comprehensive Effects of Alcohol (CEOA), (d) Three
Factor Coping Scale, and (e) Consequences Checklist. The packets will be arranged so
that more involved measures will be separated by simpler measures. Each packet of
information will contain an assigned number that will be printed on the front of the folder
and on each assessment instrument. Packets that will be distributed in the dormitory will
be numbered 1-150 and packets completed by those recruited from class will be
numbered 151-300 to ensure that the two recruitment resources can be differentiated and
the similarity of the data can be assessed prior to combining. The packets containing the
surveys will be collected as each participant completes all of the enclosed materials. The
administration and completion of all forms should take approximately 1 hour. Data will
be stored in a secure place of the principal investigator’s choosing.
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Chapter IV
Proposed Analyses
The primary purpose of this study is to examine the predictive ability of alcohol
expectancies, coping style, and affect in college student alcohol use. Prior to the formal
analyses, the distributional properties of all variables will be assessed for normalcy. Any
nonnormal distributions will be transformed as required. All outliers three standard
deviations beyond the mean will be recoded to the most extreme value within the three
standard deviations.
For the purpose of this study the outcome variable of alcohol consumption will be
defined as the typical number of drinks consumed in one week. The outcome variable
will be computed by multiplying the number of drinks consumed in a typical drinking
occasion by the number of days in a week this behavior occurs. This outcome variable
will be computed for each individual and used in all regression analyses. Additionally,
perceived alcohol consumption for the participant’s best friend and other friends will be
computed as well. The peer use variable that is most related to the dependent variable
(participants’ weekly alcohol use) will be used as the peer use control variable.
Hypothesis 1 involves determining which aspects of Alcohol Expectancies,
Coping and Affect are most predictive of alcohol consumption (as defined above). A
formal prediction model will be built with the following steps: A series of univariate
tests will be conducted for all potential predictor variables. A relaxed rejection criteria of
. 15 will be used to ensure that all potentially important predictors will be retained.
Significant predictors will then be used to build a prediction model using hierarchical
step-wise multiple regression. Step 1 of the regression analysis will include the
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background/control variables of age, peer use (the more significant of perceived “best
friend” use and “other friends” use will be used) and gender. Step 2 will include the
predictor variables of interest - alcohol expectancies, coping, and affect. Non-significant
variables will be eliminated in an iterative manner until only significant predictors
remain. Once the significant predictors have been identified, the model will be rerun
including a third step to assess for interactions. Step 3 will test two-way interactions
between the control and significant predictor variables.
Hypothesis 2 states that Seniors will drink and binge less than Freshmen, as it is
hypothesized that Seniors will have moved out of the transitional phase when the effects
of social pressure and adjustment is most pronounced. However, it is hypothesized that
the influence of expectancies, coping, and affect will increase as fewer seniors will be
drinking as a normative rite of passage. The difference between freshman and senior
drinking rates and binge episodes will be analyzed by t-tests. The prediction model
derived in the entire sample (Hypothesis 1) will be tested separately in freshmen and
seniors to investigate how the influence of the predictors varies according to grade level.
Hypothesis 3 states that Alcohol Expectancies (Positive), Coping (specifically
Ineffective Escapism), and Affect (Negative) will be predictive of alcohol consumption in
both Freshmen and Seniors. Persons who have more positive expectancies, more
avoidant coping styles and more negative affect will have greater reported alcohol
consumption rates. To test this hypothesis the following steps will be taken: A
hierarchical stepwise multiple regression analysis will be used. In step 1 the control
variables of age, peer influence, and gender will be entered. Step 2 will include the
specific predictor variables - positive alcohol expectancies, escapist coping, and negative
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affect. Step3 will examine all two-way interactions between control and predictor
variables.
Hypothesis 4 proposes that men will consume a higher number of drinks and
binge more frequently than women. The data will be analyzed by t-tests.
Hypothesis 5 states that consequences of alcohol, other drug use, and perceived
peer drinking will have an impact on alcohol use with more consequences and more drug
use being associated with higher drinking rates. Perceived peer drinking is hypothesized
to have a greater influence on freshmen alcohol users than senidr drinkers. The data will
be analyzed by a correlation matrix.
Hypothesis 6 states that desirability ratings of alcohol expectancies will be
examined to see if they provide incremental validity in outcome beyond likelihood
ratings. This will be examined creating two adjusted multiple regression models. In both
models, on step one the control variables (age, sex, peers) will be entered. Then in the
first model likelihood ratings will be entered on step two, and desirability ratings will be
entered on step three. In the second model, the order of entry will be reversed. Results
will indicate if either predictor contains unique variance or if they are redundant.
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Appendix A Demographic and Outcome Survey (Some questions adapted from the Core Alcohol and Drug Survey, 1994)
1. Age:
2. Sex (circle one): M F
3. Class: Freshman Sophomore Junior Senior
4. GPA:______(If Freshman, list High School GPA)
5. Major: ______
6. Ethnicity: African American Caucasian American Indian/Alaskan Native
Asian Hispanic Other______
7. Marital Status: Single Married Divorced Separated Widowed
8 . Enrollment: Full-time Part-time
9. Residence: On-Campus Off-Campus (Independent) Off-Campus (Family Home)
10. Work: Full-time Part-time Assistantship Internship Not Working
11. Over the last two weeks, how many times have you had 5 or more drinks (a drink is defined as a bottle of beer, glass of wine, wine cooler, mixed drink, or a shot of liquor) at one sitting? Circle one please. None Once Twice 3-5 times 6-9 times 10+times
12- About how long does a single drinking occasion last? ______( hrs.)
13a. In general, how many drinks do you have in a typical drinking occasion ______, How
many days a week do you drink _____ ?
13b. In general, how many drinks do you think your best friend has on a typical drinking
occasion _____ , How many days in a week do you think they drink _____ ?
13c. In general, how many drinks do you think your other friendshave in a typical
drinking occasion ______, How many days in a week do you think they drink ?
14. What is the most you have drank at one time (i.e., number of drinks) since classes started
this year______? What is the most you think your best friendhas drank since classes
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started this year ? What is the most you think your other friends have drank
since classes started this year
15. What percentage(%) of your friends drink on a regular basis ______?
16. What is your drink of choice?
Beer ( 12oz bottle) Draft Beer ( 12ozs) Wine (8ozs) Wine Cooler ( 12 ozs)
Mixed Drink (1.5 ozs of Liquor) Other ______
17. What do you usually drink?
Beer ( 12oz bottle) Draft Beer (12ozs) Wine (8ozs) Wine Cooler (12 ozs)
Mixed Drink (1.5 ozs of Liquor) Other ______
18. What is the average quantity of liquor, beer, or wine that you consume during a week (please circle or write in amount)? Liquor: 123456789 10 11 12 13 14 15 more (ounces) Beer (bottle): 123456789 10 11 12 13 14 15 more (bottles) Beer (draft): 1 23456789 10 11 12 13 14 15 more ___(glasses) Wine: 123456789 10 11 12 13 14 15 more ___(glasses) Wine Cooler: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 more ______(bottles) Other: , _ounces/bottles/glasses
19. How often have you used the following substances within the last year [checkbox]?
Drug None Once 6times Once Twice Once 34- Daily per per per per per times/ (include # Year Year Month Month Week Week of days) Tobacco (smoking) Other tobacco (chew or snuff) Alcohol (beer, wine liquor) Marijuana
Cocaine (i.e., crack) Amphetamine (i.e., speed)
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Drug None Once 6times Once Twice Once 34- Daily per per per per per times/ (include # Year Year Month Month Week Week of days) Sedatives (downers, ludes) Hallucinogens (LSD , PC ?) Opiates (heroin, smack) Inhalants(glue, gas, solvents) Designer Drugs (ecstasy) Steroids
Other Illegal Drugs
20. Please indicate, by checking the appropriate boxes, where you have used these substances:
Drug N/a Campus Residence Fraternity Bar or Where In Private Alone Events Halls or Sorority Restaurant you a parties live Car Tobacco (smoking) Other tobacco (chew or snuff)
Alcohol (beer, wine liquor) Marijuana
Cocaine (i.e., crack) Amphetamine (i.e., speed) Sedatives (downers, ludes)
Hallucinogens (LSD, PCP) Opiates (heroin, smack)
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Drug N/a Campus Residence Fraternity Bar or Where In Private Alone Events Halls or Sorority Restaurant you a parties live Car Inhalants(glue, gas, solvents) Designer Drugs (ecstasy)
Steroids
Other Illegal Drugs
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Appendix B
The PANAS-Weekly (Watson, Clark, & Tellegen, 1988)
This scale consists of a number of words that describe different emotions and feelings. Read each item and then mark the appropriate answer in the space next to that word. Indicate to what extent you have felt this way during the past week. Use the following scale to rate your answers, please.
1 2 very slightly a little moderately quite a bit extremely or not at all
interested irritable distressed alert excited ashamed upset inspired strong nervous guilty determined scared attentive hostile jittery enthusiastic active proud afraid
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Appendix C
Comprehensive EfTecti of Alcohol
This questionnaire assesses two things; 1) Wiat you would expect to happen if you were under the influence of alcohol, and 2) whether you think the effect is good or bad.
Instructions for Compktinn
1. Check from disagree to agree - depending on whether you expect the effect to hanoen to von if vou were under the influence of alcohol. The effects will vary, depending on the amount of alcohol you typically consume.
This is not a personality assessment. We want to know Wiat you expect to happen if you were to drink alcohol, not how you are Wren you are sober. Example: if you are always emotional, you would not check agree as your answer unless you expected to become MORE EMOTIONAL if you drank.
2. Check from bad to good - depending on whether you think the pèiticular effect is bad, neutral, good, etc.
We want to know if you think a particular effect is bad or good, «wurdlMs of whether or not you expect it to happen to you.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. -4- I f I WERE IIHOEK T1IE IHOJJEWCE fltOM DRINKING AUXNKW.
«lightly «ll&htly slig h tly s lig h tly diiagree dliagra» agree agree bad bad neutral good good c o 1. 1 would be outgoing ___ this effect la ___ in I/) 2. My aensea would be dulled ___ This effect la __ a> a. 3. 1 would be huBorous ___ This effect Is ___
4. My problème would «earn worse ___ This effect Is ___ ■o 5. It would be easier to express CD my feelings ___ This effect Is ___
6. My w riting would be ietpalred ___ This effect Is ___ 2 Q. c 7. 1 would feel sexy ___ This effect Is ___ g B. 1 would have difficulty TD3 thinking ___ This effect Is ___ 2 Q. 9. 1 would neglect my 2 obligations ___ , This effect is ___ ti 10. I would be dominent ___ This effect Is ___
11. My heed would fe e l futzy ___ This effect la ___ 12. 1 would enjoy sex more ___ This effect is ___ I 13. 1 would feel dizzy ---- This effect is ___ g This effect le ___ 14. 1 would be friendly ___ 8 15. 1 would be clumsy ___ This effect le ___
16. It would be easier to act out my fantasies ___ This effect le ___ CO 17. 1 would be loud, bolsteroua, or noisy ---- This effect Is ___ CD Q. IB. 1 would feel peaceful ___ This effect Is ___ ■D 8 "O3 2 Q. 0:CD 46
O
M — M X 5 M M * M W M M M g
a a &I II11a II |l II II i H H N (i ? ? S’ S 2 e ? r ? I s 5 ? t: f ? I Î : to I f I a r S. ? s c S’ S 1 1 : i ? ; i 4c 3 t I S’ 2 g I # Mm s 9 i I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I M I I I I I I I I II I I I I I I I I I I I I I I I I I I I I < 1 I II I I I I I M IIII I! I III
iiîîiîit I 2 Ito I I I I I 2 2 2 2 # Ml S» m 8 8 to n : 8 2 S 8 8 8 r t ft ff % I ff m f t » ; »
I I I I I I I I I I I I I I I I M i l I I I I I I I I I I I M i l l It I I I I I I I I I I I I I I III II II II M I II M i l l II I II II II II II II s
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Ai^KiidixD TItrtf fjltforCMtlBK SMlt (Rohde, Lewinaohn. Tilson, & Seeley, 1990)
N otatdl Moderately Extreme 1. when 1 am Aced with a difficult prohlem, 1 tty to 0 1 2 3 4 5 6 7 approach it! aohition in a ayitematic way. Not at all Moderately Extreme 2.1 uaually plan my worit udieo heed widt a number 0 1 2 3 4 5 6 7 of tfainga to do. N otatdl Moderetdy Extreme 3. In order to overcome bad fitelinga that accompany 0 I 2 3 4 5 6 7 bilure, I often tail myaelf that it it not lo eatattrophic and that 1 can to aomething aboiK it N otatdl Moderetdy Extreme 0 1 2 3 4 5 6 7 4. If 1 find it difficult to concentrate on a certain job, 1 divide the job into tmaller tcgmentt. N otatdl Moderetdy Extreme 5. When 1 am d^rew ed 1 try to keep myaelf buty with 0 1 2 3 4 5 « 7 thing# that 1 like. N o td d l Moderetdy Extreme 6. When 1 find it difficult to aettle down to do a certain 0 1 2 3 4 5 6 7 job, I look for way# to help me aettle down. ' N otatdl Moderetdy Extreme 7. When 1 have to do aomediing dtat ia anxiety- 0 1 2 3 4 5 6 7 arouting for me, 1 try to viaualiae how 1 will overcome my atutieliea while doing it N otatdl Moderetdy Extreme 8. When 1 am dqpreaaed, 1 try to thing about pleaaant thing#. 0 1 2 3 4 5 6 7 N otatdl Moderetdy Extreme 9. When I do a boring job, 1 think about the lea# boring 0 1 2 3 4 5 6 7 part# of the job and the reward that 1 will receive when I am finiahecL N otatdl Moderetdy Extreme 10. When I try to get rid of a bad habit I firat try to 0 1 2 3 4 5 6 7 find out all the Actor# that maintain thia habit N otatdl Moderetedy Extreme 11. When 1 Ad that 1 am loo impulaive, 1 tdl myadf 0 1 2 3 4 5 6 7 “Slop and think before you do acanething.” N otatdl Moderetdy Extreme 12. When I find that I have difficultiea in 0 1 2 3 4 5 6 7 oonoenlrating on nty reading. 1 look for way* to increaae my concentration. N otatdl Moderetdy Extreme 13. When an unplcaaant thought ia bothering me, I try 0 1 2 3 4 5 6 7 to diink about aomefhing pleaaant N otatdl Moderetdy Extreme 14. Firat of all I prefer to finiah a job that I have to do 0 1 2 3 4 5 6 7 and then atart tioing the diings I really like. N otatdl Moderetdy Extreme 15. My adf-eateem increaae* once 1 am able to over 0 1 2 3 4 5 6 7 come a bad habit N o td d l Moderetdy Extreme 16. When I plan to work. I remove all the thing# that 0 1 2 3 4 5 6 7 ate not relevant to my work. N o td d l Moderetdy Extreme IT. When la m in a low mood, 1 try to act cheerful ao 0 1 2 3 4 5 6 7 my mood will change. N o td d l Moderetdy Extreme It. Often by changing my way of thinking 1 am able 0 1 2 3 4 5 6 7 to change my fading# about almoat anything. N o td d l Moderetdy Extreme 19. Even when 1 am terribly angry with aomeone, 1 0 1 2 3 4 5 6 7 conaider ray acdona very careftdly.
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AftpendixD Three Factor Copbig Scale (Rohde, Lewimohn, Tilson, & Seeley, 1990) 20. When I am short of money. I decide to record all Not at all Moderately Extreme of my expenses in order to plan mors carefiilly for the 0 1 3 4 5 6 future.
21. When I feel pain in my body, I tty to divert my Not at all Moderately Extreme thoughts from it 0 I 3 4 5 6 fn rtf tm m t tfSum I mSMiMi 1. Keep sway from people. Not at all Moderately Extreme 0 1 3 4 5 6
2. Do something reckless (like driving a car fast). Not at all Moderately Extreme 0 1 3 4 5 6
3. Do something rather dangerous. Not at alt Moderately Extreme 0 I 3 4 5 6
4. Wait for someone to help. Not at all Moderately Extreme 0 I 3 4 5 6
5. Stay in bed. Not at all Moderately Extreme 0 1 3 4 5 6
6. Take tablets or medicine. Not at all Moderately Extreme 0 I 3 4 5 7. Avoid other people. Not at all Moderately Extreme 0 1 3 4 5 6
8. Quite often 1 cannot overoome unpleasant thoughts Not at all Moderately Extreme that bother me 0 1 3 4 5 6
9. Wish that you were a stronger person—more Not at all Moderately Extreme forceful and optimistie 0 I 3 4 5 6
10. Do nodting in particular. Not at all Moderately Extreme 0 1 3 4 5 6
II. Dayiiream about a better time or place. Not at all Moderately Extreme 0 I 3 4 5 6
12.1 often find it difficult to overoome my feelings of Not at all Moderately Extreme nervDusneaa and tcsuion without any outside help. 0 1 3 4 5 6
13. When I am faced widi a difficult decision, I prefer Not at all Moderately Extreme to postpone making a decision even if tdl the fà(M are 0 I 3 4 5 6 at my disposal.
14.1 cannot avoid thinking about mistakes I have NotataU Moderately Extreme made in the past. 0 I 2 3 4 5 6
13. Tty to get the attention of others. NotataU Moderately Extreme 0 1 3 4 5 6
16. Although it makes me fed batl, I cannot avoid NotataU Moderetdy Extreme dunking about all kinds of catastrt^hes. 0 1 3 4 5 6
17. If I had the pi Us with me, I would take a NotataU Moderately Extreme tranquilizsr when I felt tense or nervous. 0 I 3 4 5 6
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Appendix D Three Fnctor Coping Scnle (Rohde. Lewiatobn. Tilson, & Seeley, 1990) IaaieDràaM€ 1. Pian aomelhing pleaaanL NotataU Moderately Extreme 0 1 3 4 5 6 7 2. Spend time witb Mends. Not at all Moderately Extreme 0 1 3 4 5 3. Do something aqpyable. NotataU Moderately Extreme 0 I 3 4 5 6 4. Spend time with a relative or close friend. NotataU Moderately Extreme 0 I 3 4 5 5. Do something to raatoie your piide. Not at all Moderatdy Extreme 0 1 3 4 5 6 Do something to distract yourself from the problem. NotataU Moderately Extreme 0 1 3 4 5 7. Do somediing to get your mind off the situation. Not at all Moderately Extteme 0 I 3 4 5 8. Busy youDtaelf in your usual work. Not at all Moderately Extreme 0 I 3 4 5 9. TaHt over your pioiblems with someone you know. NotataU Moderately Extreme 0 I 3 4 5 10. Take on some new and challenging wotk or NotataU Moderately Extreme activity. 0 I 3 4 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 50 Appendix E Consequences Checklist (Adapted from the Core Alcohol and Drug Survey, 1994) Please indicate whether you have experienced any of the following due to your alcohol or drug use? (check one per line, please) Never Once Twice 3-5 Times 6-9 Times 10+ Times Hangover Performed poorly on a test or project Been in trouble with local police department or other authorities Been in trouble with campus police, or residences hall Damaged property, pulled fire alarm, etc Had a fight or argument Got nauseated or vomited Driven a car under the influence Missed a class Been criticized by someone you know Thought you might have a drinking or drug problem Memory Loss Did something you later regretted Been arrested for DUI Been taken advantage of sexually Taken advantage of another sexually Tried to stop using Lost or had a relationship damaged Been hurt or injured Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 51 Appendix F Standardized Script for Recruitment From Classes: Hello my name is Mike Biscaro and I am here today to see if you would help me with my dissertation project. I am interested in freshmen and senior drinking. The study involves filling out about a half hour of questionnaires. All of your answers will be completely anonymous - even I won’t know how you answered. I would truly appreciate your help. Participants who choose to, will be entered into a drawing to win 1 of 4 50$ gift eertificates (Kenwood Mall, Kroger, Block Buster, and Long Horn Restaurant). [if professor agrees... .Dr. ______has agreed to give pts extra credit for your participation as well.] For those who would like to participate, I will pass around a sheet of the times for you to complete the study. The study will take place in Elet hall. You will only be eligible for the drawing and/or extra credit if you show up for the experiment, so please take a slip or write down the room with the date and time you signed up for. From Dorms: Hello my name is Mike Biscaro and I am here today to see if you would help me with my dissertation project. I am interested in freshmen and senior drinking. The study involves filling out about a half hour of questionnaires. All of your answers will be completely anonymous - even I won’t know how you answered. I would truly appreciate your help. All participants will be entered into a drawing to win 1 of 4 50$ gift certificates (Kenwood Mall, Kroger, Block Buster, and Long Horn Restaurant). I will now pass out the materials to those of you who are interested in helping me. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 52 Appendix G Xavier University Department of Psychology Consent Form **You should not take part in this study if you are under 18 years of age** Alcohol Expectancies, Coping, and Affect in Predicting College Student Alcohol Use: A Cross Sectional Examination of Freshmen and Seniors Principal Investigator: Michael J. Biscaro, Department of Psychology, Xavier University, Home Telephone: (513) 871-0711, email: [email protected]. Supervisor: Susan L. Kenford, Ph.D., Department of Psychology, Office Telephone: (513) 745- 3451, email: [email protected]. This research project studies the relationship between Alcohol Expectancies (the things we expect alcohol to do to us). Coping (the ability to deal with stressors). Affect (positive and negative moods), and alcohol use. The results of this study may be useful in predicting alcohol use in the college population. In this study you will complete a packet of surveys, and the whole study should take approximately Vi hour or less to complete. Your participation is appreciated and, although there are no direct benefits for you, if you choose to participate you may help provide some additional information that could aid in a more complete understanding of undergraduate alcohol use on campus. All of the information in this study will be kept completely anonymous; your name will never be associated with the data or questionnaires. All data collected will be analyzed in a group form and not on an individual basis. This consent form will be kept separate from all the data and materials collected in this study. Some questions ask you about feelings and experiences that you have had, and it is possible that this may be distressing for some people. If you have any concerns with the experiment, you may withdraw at any time without any prejudice to you. Furthermore, should any student wish to speak with a psychologist or counselor, help is available at the Psychological Services Center (745-3531) or the Health and Counseling Center (745-3022). You may also contact the principal investigator, Mike Biscaro (see contact information below), if requiring assistance. **If you have any additional questions or concerns about this study, please contact Mike Biscaro at (513) 871-0711, email: [email protected], or Dr. Susan Kenford, Department of Psychology, Xavier University, at 745-3451 or email: [email protected]. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 53 Chapter V : Dissertation Abstract The primary focus of this study was to examine cognitive and emotional factors for alcohol consumption in Freshman and Senior college students. Alcohol Expectancies, Coping Style, and Affect were expected to predict alcohol consumption in the entire sample and for each cohort. Coping Style and Affect did not predict alcohol use in either group. Alcohol Expectancies, specifically Liquid Courage and Self-Perception, were related to drinking rates in the full sample. Only Self-Perception was predictive of both freshman and senior drinking. The effects of Self-Perception were moderated by level of peer use and seen only among participants with low-peer use rates. Perceived peer alcohol use was highly predictive of alcohol consumption and accounted for more than 40-50% of the variance. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 54 Alcohol Expectancies, Coping, and Affect in Predicting College Student Alcohol Use: A Cross-Sectional Examination of Freshmen and Seniors The prevalence and incidence of alcohol use on college campuses have been of great concern for decades. Past research has shown that alcohol use and abuse can have many adverse effects, such as heart disease, memory impairment, immune and reproductive disorders, social consequences, and economic problems (Broer, 1996). Other detrimental effects are also evident for college students, such as being “seventeen more times likely to miss a class, ten times more likely to vandalize property, and eight times more likely to get hurt or injured” (Wechsler, 2002 p. xiv). Alcohol is the drug of choice in the collegiate culture. According to Wechsler (2002a), the prototypical college culture has a pervasive alcohol problem and colleges and universities have a social culture in which there are drinking games, fake identifications and a number of alcohol-based cultural myths (i.e., work hard play hard; everybody does it; drinking is my business and does not hurt anyone else; increased sex drive, etc.). Problem drinking in the college environment is further supported by the surrounding geographical area, which is often populated by bars and establishments that cater to, and encourage, college drinking. While students have the responsibility to choose, the surrounding culture serves to enable their drinking (Wechsler, 2002a). Research has revealed that students who drink excessively during their first year in college are likely to continue this behavior into their second year (Wechsler, Isaac, Grodstein & Sellers, 1994, as cited in Broer, 1996). Therefore, students who have started problem drinking keep it up, and universities would be wise to evaluate the extent of early student drinking. Early research focused on the extent and prevalence of drinking Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 55 and was most interested in quantifying the problem. However, while this has led to a firm grasp of the scope of the problem, it has done less to identify the key factors related to college drinking (Broer, 1996). One of the key findings in alcohol consumption research to date has been the vast difference between male and female drinking rates. Males consistently have been found to consume more alcohol on average than their female counterparts (Biscaro, Broer & Taylor, 2004; Broer, 1996; Ham & Hope, 2003; Mooney & Corcoran, 1989). Additionally, men tend to have higher rates of binge drinking than women (Ham & Hope, 2003; Wechsler et al., 1994). Research has suggested that gender differences may lie in the socialization of men and women, where men choose activities for external rewards (i.e., looking “macho”, finding a sexual partner, affiliating with a certain group) and women participate in activities that are internally rewarding - to cope with emotions (Cooper et al., 1992; Ham & Hope, 2003). Biological differences, such as metabolism, absorption rates and body-fat ratios, have also been linked to the disparity in male and female consumption rates (Ham & Hope, 2003). The task of understanding the underlying dynamics of college drinking is complicated by the multifaceted nature of the behavior. As Wechsler et al. (2001) pointed out, no single measure, construct, or variable can measure the complexity of excessive drinking. However, while knowledge of the précipitants of problematic college drinking is still quite limited, several key domains have emerged as important factors to assess and study further. Specifically, in the research to date, alcohol expectancies, coping, and affect regulation have all shown promise for both understanding and predicting college alcohol use. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 56 Alcohol Expectancies Social Learning Theory - SLT (Bandura, 1969) — posits that many behaviors are observed, learned, and acquired from a person’s environment. During the acquisition process, expectancies are formed that later guide and modify behavior. Expectancies are cognitive frameworks that construe events in an “if-then” relationship, such that if a certain event or behavior occurs, then a certain event or behavior is expected to follow (Goldman, Brown & Christiansen, 1987). The role of expectancies in drinking behavior has been widely studied. Jones et al. (2001), using a SLT framework, suggested “behavior is explained by individuals having expectations of particular reinforcing effects as the outcome of performing the behavior in question” (p.59). In terms of alcohol usage, a person drinks alcohol because he or she has expectations about alcohol’s effects and these expectations are molded by perceived and actual experiences with alcohol (Jones et al-, 2001). Goldman et al. (1987) proposed that expectancies for alcohol directly affect drinking behavior and have more predictive power than less direct social influences. Alcohol expectancies help mold the experience of drinking alcohol and are used to decide whether to drink or to remain sober (Broer, 1996). Expectancies have been shown to be adequate predictors of problematic drinking in college students (Brown, 1985a; Brown, 1985b); able to help differentiate those who are at risk for problematic drinking from non-problem users (Christiansen, Smith, Roehling & Goldman, 1989); able to distinguish alcohol dependents from non-dependents (Connors, O’Farrell, Cutter & Thompson, 1986); causally affect alcohol intake (Sharkansky & Finn, 1998) and predict future drinking patterns (Carey, 1995). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 57 As learned and socially determined cognitive structures, expectancies have both positive and negative forms. Numerous studies have investigated the effects of both positive and negative expectancies (Jones et al, 2001). Positive expectancies, or the beliefs about the enhancing effects of alcohol, have been the most widely studied. Global positive expectancies (e.g., “Drinking makes the future seems brighter,” “Alcohol seems like magic,” or “I feel more coordinated after I drink”) have been found to predict small to significant amounts of the variance in alcohol expectancy models (Biscaro et al, 2004; Broer, 1996; Brown, 1985b; Brown, Christiansen & Goldman, 1987; Burden & Maisto, 2000; Carey, 1995). Positive expectancies have been found to increase motivation to drink. Negative alcohol expectancies have been associated with a reduction in drinking behavior, and motivation to decrease problematic drinking (Jones et al, 2001). While negative expectancies appear to be more crucial in predicting cessation rather than initiation of alcohol use, negative expectancies should still be included in alcohol use research. Negative expectancies may be key for future drinking behavior, especially among the social, experimental drinker. Consistent with this idea, Ramsey et al (2000) found that individuals who had experienced negative alcohol-related events were more open to changing drinking behaviors than those who had not. An important and often neglected aspect in assessing alcohol expectancies is the person’s subjective evaluation of the particular expectancy. Essentially, subjective evaluations are the perceived desirability of a particular outcome. Much research on alcohol expectancies has involved only the measurement of the perceived likelihood of certain effects following alcohol use (i.e., “If I were under the influence of alcohol. .1 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 58 would be brave and daring”). Hence, people are rating what they expect alcohol will do rather than how favorably they view the effect. Given that people may view outcomes as highly likely but unappealing, a subset of expectancy research has aimed to capture the subjective perception of alcohol effects - i.e., “this effect is... bad, slightly bad, neutral, good, etc.” (Jones et al., 2001). While some research has found that combining subjective evaluations of outcome with the assessment of alcohol expectancies significantly adds to the prediction of alcohol use (Werner, Walker & Greene, 1993), other studies have not found this result and suggest examining subjective evaluations separately (Burden et al., 2000; Fromme et al., 1993). Given the mixed findings to date, it appears useful to assess for both the likelihood and desirability of positive and negative expectancies. Coping In addition to alcohol expectancies, coping has been a focus in the alcohol use literature. Coping, or the ability to handle life stressors, is an important construct when examining alcohol use or any initially problematic behavior. An interesting aspect of coping is its implication as a mediator variable between stress and problematic behaviors - i.e., excessive drinking (Rhode, Lewinsohn, Tilson & Seely, 1990). The more effective coping resources a person has, the less likely he or she is to experience distress in the face of a challenge, which in turn reduces the risk of maladaptive behavior. Folkman, Lazarus, Gruen, and Delongis (1986) defined two general types of coping: problem-focused and emotion-focused coping. In problem-focused coping the goal is to be solution oriented and focus on solving a particular problem (i.e., engage in active, rational problem-solving). Emotion-focused coping aims to stabilize the Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 59 emotional dysregulation that occurs during a stressful event (i.e., engaged in isolation, avoidance, escape, etc.). Folkman et al. (1986) found in a sample of 150 community adults that a balance of these strategies was most beneficial. Problematic situations arise when the environment exceeds the available coping strategies a person has within his or her repertoire (Cooper, Russell, Skinner, Frone & Mudar, 1992; Folkman et al., 1986). Due to its mood altering effects, alcohol can serve as a coping mechanism to manage stress or tension states. Research on stress and alcohol use has found that people with a more problem-focused and planned approach to stressful situations are less likely to drink during periods of distress, whereas people with deficient coping mechanisms and the expectancy that alcohol has positive effects are more likely to drink excessively under periods of distress. (Cooper, Russell & George, 1988; Stewart, Zvolensky & Eifert, 2002 ). The transition to college is stressful and when students enter their first year of college there are many demands placed on them intellectually, physically, socially, and financially. As a result, students are forced to identify and implement methods of coping. Alcohol is often a part of coping with the newly encountered demands, and while this can be adaptive for a small minority, it is not recommended for the majority of students (Zaleski, Levey-Thors & Schiaffino, 1998). Abrams and Niaura (1987) stated that “coping skills are a critical determinant in the decision to drink or not to drink and whether drinking is normal or maladaptive” (p. 161). Williams and Clark (1998) made a distinction between escape drinking - or drinking that is negatively reinforcing — and social drinking — drinking that is positively reinforcing. In a sample of 300 university students, the authors found that escape Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 60 drinking was more predictive of excessive binge drinking, but it was only indirectly related to overall alcohol consumption. Social drinking was more predictive of alcohol consumption, with those who drank for social reasons consuming more alcohol over time but less in a short, discrete period. Affect Affect has been shown to play a key role in drug use across all substance categories (Marlatt & Gordon, 1985; Reiger, Meyers, Kramer, Robins, Blazer, Hough et al., 1984; Zack, Toneatto & Macleod, 1999). Affect and affect regulation are important in the initiation and cessation of alcohol consumption. Affect has been shown to have two broad dimensions, Positive Affect (PA) and Negative Affect (NA). Positive and negative affect are not polar ends of a single construct but rather two independent entities. As defined by Watson, Clark, and Tellegen (1988), Positive Affect is “the extent to which a person feels enthusiastic, active, and alert (p. 1063)” and Negative Affect is a general, distressed feeling marked by negative mood states, such as anger, contempt, nervousness, fear, etc. In general, affect dysregulation has been linked to a variety of psychological disorders. Comorbid substance use disorders (e.g., alcoholism) are found in about 50% of people with psychological difficulties (Reiger et al., 1984). Typically, negative affect is associated with “psychiatric distress” (Zack et al., 1999, p. 518) and it has been shown that negative affect is closely associated with substance use relapse (Marlatt & Gordon, 1985). In addition to epidemiological data, affect has also been linked to many formal hypotheses and models of alcohol and substance use, such as the Tension Reduction Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 61 Theory - TRT - (Conger, 1956), Automatic versus Nonautomatic processing (Tiffany, 1990), Two-Factor Avoidance Theory (Stasiewicz & Maisto, 1993), and a Motivational Model of Alcohol Use (Cooper, Frone, Russell & Mudar, 1995). TRT holds that an environmental stressor creates tension for which the human response is to seek relief and persons who do not have alternate ways of coping with the stressful situation turn to alcohol (Cappell & Greeley, 1987). The Automatic and Nonautomatic Cognitive Processing Model posits that negative affect can trigger the urge to use alcohol, and consequently this urge interferes with the controlled cognitive processes needed to resist the desire to drink. Two Factor Avoidance Theory proposes that negative affect becomes a conditioned emotional response (CER) and the CER then serves to motivate the person’s continued drinking. Of particular interest, is the Motivational Model proposed by Cooper et al. (1995), which posits that alcohol use serves a regulatory function for a person’s emotional state and individuals use alcohol both during negative affective experiences to reduce anxiety and tension, but also drink to foster positive emotions or experiences. As such, they proposed two distinct pathways to alcohol use. One pathway was labeled “Drinking to Cope,” which predicted people would use alcohol if they relied on maladaptive coping processes, held positive expectancies for alcohol’s ability to reduce tension, and experienced negative affect. The other pathway was labeled “Drinking to Enhance,” which predicted people would use alcohol if they expected drinking would enhance social/emotional experiences, increase positive affect, and if they engaged in sensation seeking (i.e., those who seek high levels of stimulation and desire positive Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 62 reinforcement). Results supported the two hypothesized pathways and both drinking to enhance and drinking to cope were predictive of alcohol use. Other studies have offered additional support for Cooper et al.’s (1995) motivational models. Hussong et al. (2001) found that participants’ emotions motivated their alcohol consumption. Adolescents who had increased negative emotions on the weekend drank primarily to reduce or cope with those emotions the following week, while those who had more positive emotions, whether it was on the weekend or weekday, drank to enhance those emotions. Colder (2001) examined the effects of negative emotionality and life stress on alcohol consumption in a sample of 80 college students using a negative mood induction (i.e., viewing aversive pictures); results found that higher levels of stress and negative affect increased participants’ alcohol consumption. Further support for the two-path model was found by Armeli, Tennen, Affleck and Kranzler (2000); in their sample, both negative and positive interpersonal experiences led to greater alcohol consumption. While much research on college student alcohol use has focused on person factors (i.e., alcohol expectancies, coping style, and affect), few studies have jointly examined both cognitive (i.e., expectancies and coping style) and emotional (affect) variables as predictors. While the present study is focused on these person-factors, peer influence on alcohol consumption has been found to be such a potent predictor that it requires inclusion in any model of young adult substance use. Longitudinal studies have found that higher peer alcohol use has proven to be predictive of increased alcohol use in young adults (Bray, Adams, Getz & McQueen, 2003; Chassin, Pitts & Frost, 2002). Peer use Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 63 has also shown to be highly predictive of increased binge drinking in young adults (Andrews, Tildesley, Hops & Li, 2002). Most young men and women entering college are beginning a major life transition and what may be perceived as one of the final maturational developmental milestones. According to Zaleski et al. (1998), the first year of college is a chance to develop social skills, individuate from parents and home, foster lasting relationships with peers, and develop a firm self-concept. However, this time is also often the student’s first experience away from home, parents, and a familiar environment. As such, this may be a stressful period for students, many of whom may cope by looking to social norms for behavioral guidance and peers for primary support. Sek (1991) posited that social support could be a protective factor against alcohol use and could act as a buffer from stressful events. However, if the social support networks are immersed in a culture of problem drinking, students will be more likely to engage in similar behavior (Zaleski et al., 1998). Over time, students are expected to develop more responsibilities, additional coping resources, and more maturity, thus becoming acculturated to collegiate life and hopefully transitioning out of the period when social influences on problem drinking are strongest (Sher & Gotham, 1999). This study attempts to depict this transitioning period by examining and predicting alcohol use for both freshmen and seniors. It is hoped that this will allow for an exploratory, cross-sectional examination of maturational factors on alcohol consumption and drinking behaviors. The following hypotheses were explored in this study; 1) Seniors will drink and binge less than freshmen, as they are expected to have moved out of the transitional phase Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 64 where the effects of social pressure and adjustment are most pronounced; 2) Men are expected to consume more alcohol and binge more frequently than women; 3) Alcohol expectancies, coping and affect are expected to be predictors of alcohol consumption in both freshmen and seniors; 4) The influence of alcohol expectancies, coping, and affect will increase in the senior cohort, as fewer seniors will be drinking as a normative right of passage; and 5) Greater positive alcohol expectancies, increased negative affect, and an avoidant coping style will lead to more alcohol consumption. In addition to the specified hypotheses, two exploratory hypotheses were examined: 1) Consequences of alcohol, other drug use, and perceived peer drinking has an impact on alcohol use with more consequences and more drug use being associated with higher drinking rates. Perceived peer drinking may have a greater influence on freshmen alcohol users than senior drinkers; and 2) Desirability ratings of alcohol expectancies would be examined to see if they provide incremental validity in outcome beyond likelihood ratings. Method Participants Participants were recruited from a private Midwestern university with about 4000 undergraduate students. The sample did not contain any individuals under the age of 18. A total of 285 participants were recruited; 33 students were excluded because they were either a Sophomore or Junior and 2 other students were excluded because they were not characteristic of the entire sample (i.e., they were married, had children, and were enrolled only part-time). Thus, the sample sizes for the cohorts were 120 Freshmen (56 male and 64 female; M = 18.5 years, SD = .52.) and 130 Seniors (57 male and 73 female; M = 21.7 years, SD = .89). The sample was 84% Caucasian, 7% African American, 4% Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 65 Asian, 3% Hispanic, and 2% Other. Participants were treated in accordance with American Psychological Association (APA) guidelines and ethical standards (APA, 2002 ). Materials Demographic and Outcome Survey This is a self-report survey that was created to assess information in several key domains, such as demographics, drinking behaviors and preferences, and drug use. Many questions were adapted from the Core Alcohol and Drug Survey (Core: Presley et al., 1994). The Core survey was devised specifically to examine alcohol and drug use on college campuses (Broer, 1996). The outcome variables used in this study are (1) typical quantity of alcohol consumed (operationally defined as the number of drinks per week), (2) maximum quantity of alcohol consumed (operationally defined as the largest number of drinks consumed at one time over the past month), and (3) the number of alcohol binge episodes (operationally defined as having 5 or more drinks at one time) within the past two weeks. These formulations were selected as they cover both distributed and aggregated use and are consistent with prior research (Bosari et al., 2001; Mooney et al., 1989; & Wechsler et al., 2001), which allowed for cross study comparisons. The measure was also used to collect data on perceived peer use. Participants were asked to report on alcohol consumption and maximum alcohol consumption values for both their best friend (Peer use) and other friends (Other Peer Use). Summary scores were created for Peer Use and Other Peer Use. ’ 'Data were collected for both perceived best-friend consumption and for perceived other friends consumption. Tests were conducted to determine the most potent predictor. While both the perceived best friend consumption, P = .294, t (1, 249) = 8.253, p < .001 and perceived other friend consumption. P = .473, t (2, 249) - 5.126, p < .001 were predictive of participant’s alcohol use, best friend use had a stronger relation with outcome and was used as the control variable. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 66 Positive and Negative Affective Schedule (FANAS) The Positive and Negative Affect Schedule (PANAS: Watson, Clark & Tellegen, 1988) is a paper and pencil checklist developed to capture two dimensions of affect - Positive Affect (PA) and Negative Affect (NA). It is a 20-item self-report measure that asks the participant to rate on a 5-point Likert-type scale (1 = very slightly or not at all to 5 = extremely) the extent to which they have felt a particular mood descriptor (e.g., interested, alert, excited, upset, etc.) within a specified time frame (i.e., this moment, today, past few days, past week, past few weeks, year, and general). The PANAS has good internal consistency with alpha coefficients ranging from .86-.90 for PA and .84-.87 for NA. Results have shown that reliability is not highly affected by the time frame used. Participants completed the “past week” version of this measure for the present study. Comprehensive Effects of Alcohol (CEOA) The Comprehensive Effects of Alcohol (CEOA: Fromme, Stroot, & Kaplan, 1993) is a 76-item self-report measure designed to measure both positive and negative alcohol expectancies (38 items), as well as the subjective evaluation ratings of those expectancies (38 items). The measure is divided into two parts: (1) assessment of outcome expectancies (sample items, “I would be outgoing” or “I would feel moody”), which are rated on a 4-point Likert type scale (1 = disagree, 4 = agree), and (2) the subjective evaluation of the expected effect, which is rated on a 5-point Likert-type scale (1 = bad, 3 = neutral, 5 = good). Factor analysis has shown that this measure has 4 positive expectancy factors (Sociability, Tension Reduction, Liquid Courage, and Sexuality) made up of 20 items and 3 negative expectancy factors (Cognitive Behavioral Impairment, Risk/Aggression, and Self-Perception) containing 18 items (Fromme et al., Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 67 1993). The measure has demonstrated adequate internal consistency, temporal stability, and construct validity. Consequences Checklist This is a self-report checklist that was adapted from the Core Alcohol and Drug Survey Question 21 and is intended to assess the negative outcomes associated with alcohol and drug use. Participants indicated the frequency at which a particular consequence occurred (never, once, twice, 3-5 times, 6-9 times, 10+ times). This checklist serves as a measure of the number of negative consequences a person has experienced as a result of alcohol and/or drug use. While research has shown that light drinkers do not expect pleasant consequences when using alcohol, heavy drinkers continue to drink despite negative consequences, which suggests that expected positive effects of alcohol outweigh the consequences. Three Factor Coping Scale The Three Factor Coping Scale (Rhode, Lewinsohn, Tilson & Steeley, 1990) is a 48-item, self-report measure that elicits ratings of coping strategies on a 0-7 Likert-type scale with regard to likelihood of strategy use. The measure has 3 major factors: Cognitive Self-Control (e.g., “I usually plan my work when faced with a number of things to do”). Ineffective Escapism (e.g., “Keep away from people.”), and Solace Seeking (e.g., “Spend time with friends.”). The measure has been shown to have adequate psychometric properties. Procedure Participants were recruited one of two ways: (1) from undergraduate courses at the end of scheduled class time or (2) from the dormitories at a prescheduled dormitory Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 68 meeting. A standard script was read to each group during the recruitment phase. During recruitment, students were informed that their information was desired whether or not they consumed alcoholic beverages. The participants recruited from classes completed the study at another time — within approximately 3 days of recruitment. To maintain anonymity, no names were collected; rather, participants were given a slip of paper with dates, times, and room numbers to complete the study. Participants who were recruited from the dormitories completed the study at the time of recruitment. Freshmen participants were recruited from introductory psychology courses and the dormitories and senior participants were recruited from upper level business and psychology courses. All participants were offered some incentive to complete the study. Participants who were recruited from classes were given extra credit at the discretion of the professor. All participants had the opportunity to participate in a random drawing for four gift certificates of $50.00 each from local venues. Participant contact information was kept in an enclosed box and destroyed immediately after the winning names were drawn at the completion of data collection. Administration of the materials was in a group format for both recruitment samples. Prior to completing the packet of surveys, participants had the purpose of the study explained to them and informed consent was reviewed. To ensure anonymity, participants kept the written informed consent document and were not required to return a signed copy. At the time of data collection, each person received an envelope containing the five assessment measures. The packets were arranged so that the more involved measures were separated by simpler measures. In order, each packet contained the Demographic and Outcome Survey, Positive and Negative Affective Schedule (PANAS), Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 69 Comprehensive Effects of Alcohol (CEO A), Three Factor Coping Scale, and Consequences Checklist. There was no counterbalancing of measures. Each packet of information was assigned a subject number and coded to designate dormitory or classroom setting; no names were collected or used. Analytic Plan Prior to the formal analyses, the distributional properties of all variables were assessed for normalcy. All non-normal distributions were transformed as required. Outliers three standard deviations beyond the mean were recoded to the most extreme value within the three standard deviations. A total of two participants required recoding in the following three variables: Alcohol consumption, perceived best friend alcohol consumption, and other friend alcohol consumption. For the reported analyses, the primary alcohol consumption outcome variable was the typical number of drinks consumed in one week. This outcome variable was computed for each individual by multiplying the number of drinks consumed in a typical drinking occasion by the number of drinking occasions per week and used in all regression analyses. A secondary outcome variable of binge episodes was computed for each individual and used when examining group (freshman/senior) and gender differences. T-tests were used to assess for mean /group differences. The primary hypotheses were tested in the following manner: A formal prediction model was built to determine which aspects of Alcohol Expectancies, Coping and Affect are most predictive of alcohol consumption. A series of univariate tests were conducted for all potential predictor variables, A relaxed rejection criterion of .15 was used to ensure that all potentially important predictors were retained. Significant predictors were Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 70 then used to build a prediction model using hierarchical step-wise multiple regression. Step 1 of the regression analysis included the background/control variables of age, peer use and gender. Step 2 included the predictor variables of interest - alcohol expectancies, coping, and affect. Non-significant variables were eliminated in an iterative manner until only significant predictors remained. Once the significant predictors were identified, the model was rerun including a third step that assessed for interactions. Step 3 examined all two-way interactions between the control and significant predictor variables. Finally, the parsimonious, derived model was then tested separately in freshmen and seniors to investigate how the influence of the predictors varied according to grade level. The a-priori Motivational model, which predicted that Positive Alcohol Expectancies (calculated as the average of all Positive Expectancies), Ineffective Escapist Coping and Negative Affect would be related to alcohol consumption in both Freshmen and Seniors was tested with a stepwise multiple regression analysis. In step 1, the control variables of age, peer influence, and gender were entered. Step 2 included the specific predictor variables - positive alcohol expectancies total, escapist coping, and negative affect. Step 3 examined all two-way interactions between control and predictor variables. Pearson product-moments correlations were used to explore the relationships between drinking rate and consequences of alcohol use, other drug use, and perceived peer drinking. Multiple regression was used to test if desirability ratings of alcohol expectancies provided incremental predictive power beyond likelihood ratings. Two regressions were created for each expectancy variable. In the first regression, on step 1 gender, age and peer use were entered as control variables; on step 2 the likelihood rating was entered and on step 3 the desirability rating was entered. In the second regression. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 71 step 2 and step 3 were reversed and desirability ratings were entered prior to likelihood ratings. Examination of both orders of entry reveals if there is unique variance in desirability ratings or if the predictive information is redundant with likelihood. Results Table 1 shows a summary of the demographic variables by class. Significant differences were observed for age, major, work status, residency, and recruitment venue. The senior sample was not normally distributed with respect to major, as 71% were declared Business majors and 22% were in the Social Sciences. The means and standard deviations of all alcohol consumption variables by class are presented in Table 2. T-tests were used to analyze the differences between classes. Contrary to prediction, results indicated that there were no statistical differences between Freshmen and Seniors with regards to drinking rate, t (1, 248) = -.508, p = .612 or number of binge episodes, t (1, 248) = -1.731,/? = .085. Results further indicated that there were no differences between classes for any alcohol consumption variable. Table 3 shows the means and standard deviations of all alcohol consumption variables by gender. T-tests were used to analyze the differences between men and women. Drinking rates for men and women were significantly different, with men reporting both more drinking, t (248) = 4.237,/? < .001, as well as more binge episodes, t (248) = 6.569, /? < .001. Further analyses revealed that binge episodes were not uniform within each group. For example, while the average number of biweekly binge episodes for women was 2.51, 40% reported never binging, 10% reported binging once biweekly, 17% binging twice biweekly, 23% binging 3-5 times biweekly, 8% binging 6-9 times biweekly, and 1% binging 10+ times biweekly. Men also reported non-uniform binge Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 72 drinking rates. On average, men binged 3.35 times over a 2-week time period with 25% never binging, 10% binging once biweekly, 10% binging twice biweekly, 24% binging 3- 5 times biweekly, 23% binging 6-9 times biweekly, and 8% binging 10+ times biweekly. There were no significant differences between men and women when separated by class with regard to the number of binging episodes and drinking rate. Table 4 includes the means and standard deviations for the predictor variables of interest. Results showed significant differences between cohorts for 9 variables: Ineffective Escapist Coping, Total Positive Expectancies, Sociability, Liquid Courage, Total Negative Expectancies, Cognitive-Behavioral Impairment, Risk and Aggression, Self-Perception, and Self-Perception Effects. Univariate tests were performed on all potential predictors to assess their relation with outcome. Table 5 contains the univariate test results. Fourteen predictors met the relaxed rejection criterion of .15 for retention. These included five Positive Expectancies (Positive Expectancies Total, Positive Expectancies Effects, Liquid Courage, Tension Reduction, and Sociability Effects), 6 Negative Expectancies (Negative Expectancies Effects, Cognitive-Behavioral Impairment, Cognitive-Behavioral Impairment Effects, Risk and Aggression, Self-Perception, Self-Perception Effects), Positive Affect, and Ineffective Escapist Coping. Using hierarchical, step-wise multiple regression the most parsimonious, best- fitting model was derived from retained predictors. Step 1 of the regression analysis included the background/control variables of age, peer use and gender; these variables accounted for a considerable amount of outcome: R = .66 and R? = .44. The contribution of Gender and Peer Use was statistically significant, F (3, 245) = 64.54, j? <.001. Step Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 73 two included all retained predictors. Predictors were eliminated in an iterative manner until only significant predictors (p < .05) remained. Table 6 contains the final parsimonious model. Liquid Courage (LG) and Self-Perception (SP) were retained in the final model and the obtained increased from .44 to .48. The contributions of Liquid Courage (a positive alcohol expectancy - “I would feel courageous,” “I would feel unafraid,” etc.) and Self-Perception (a negative alcohol expectancy - “I would feel moody,” “I would feel guilty,” etc.) were significant, F (2,243) = 10.05, j? < .001. In Step 3, all two-way interactions between the control and significant predictor variables were tested. Only the interaction between Self-Perception and Peer Use was significant, F (1, 242) = 29.12,p < .001; including the interaction term increased to .54. Examination of the interaction term revealed that self-perception was predictive of decreased alcohol consumption only when peer drinking was low; when perceived peer drinking was high, self-perception was unrelated to alcohol consumption. Next, the derived parsimonious model was tested separately in both freshmen and seniors. Table 7 shows the results for the model tested in the Freshman sample. The control variables of Gender, Age, and Peer Use were entered in Step 1 ; the obtained R was .57 and R^ was .32. The contribution of the control variables was significant, F (3, 116) = 3.11, p < .001. Peer Use and Gender significantly contributed to the outcome of the regression equation. In Step 2, Liquid Courage and Self-Perception were entered and resulted in a change in of .09; the contribution of the variables was significant, F (2, 114) = 8.54,y; < .001. As in the model for the full sample, Liquid Courage and Self- Perception were significant predictors of alcohol consumption. Step 3 tested the interactions between the control and predictor variables. As in the derived parsimonious Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 74 model, the only significant interaction was between self-perception and peer use. The interaction yielded a significant A of .06, F (2, 112) = 6.11), p = .002. The derived model was tested in the Senior sample. Table 8 contains the results of the derived model in the Senior sample. Step 1 included the control variables of Gender, Age, and Peer Use. In this step, the obtained R was .76 and was .58 and the contribution of the control variables was significant, F (3, 125) = 56.62, p < .001. Results indicated Peer Use and Gender were predictive of outcome. In step 2, the addition of Liquid Courage and Self-Perception resulted in a A of .02; the contribution of Liquid Courage and Self-Perception was significant, F (2, 123) = A.\\,p< .05. However, examination of the beta values indicated that Liquid Courage was not predictive of Seniors’ alcohol consumption, P= .0\,t (5,128) = .09, p > .10. The increase in model fit was due to Self- Perception, = -.17, t (5,128) = -2.87, < .01. All interactions were tested in step 3 and, as in the previous models, the only significant interaction was between Self-Perception and Peer Use. The interaction resulted in a significant A of .03, F (3, 122) = 6.22,p < .001. A three-step Hierarchical Multiple Regression tested the a-priori hypothesized Motivational model which posited that more positive expectancies, greater avoidant coping styles and increased negative affect would be related to higher alcohol consumption (see Table 9). Step 1 included the control variables of Age, Peer use, and Gender. In this step, R was .67 and R^ was .44 with Gender and Peer Use exerting significant effects, F (3, 243) = 64.11, < .001. Positive Alcohol Expectancies Total, Ineffective Escapism, and Negative Affect were added to the equation in step 2. The addition of these variables produced a change in R} of .02; however, the contribution was Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 75 not significant, F (3, 240) = 2.26, p > .05. Examination of the beta values indicated that only Total Positive Expectancies was predictive of participants’ alcohol consumption, p = .11, / (6, 246) = 2.14,/? < .05. The effect was not great enough to improve model fit. Contrary to what was hypothesized, escapist coping and negative affect were not significant predictors of participant alcohol consumption. In step 3, all two-way interactions were tested. The only significant interaction was between Peer Use and Positive Expectancies, P = -.86, t (8, 246) = -2.06, p < .05. The interaction produced a nonsignificant change in of .01, F (2, 238) = 2.06,p > .10. Pearson product-moment correlations were computed for class, alcohol consumption, peer use, negative consequences, and other drug use (see Table 10). Results showed that both negative consequences and other drug use were positively correlated with alcohol use. The strongest relationships were found with having a hangover, doing poorly on a test, missing a class, experiencing memory loss, and doing something that was later regretted (r > .50, p < .001). Contrary to prediction, perceived peer drinking was equally related to consumption both for freshman and seniors, r = .04, p > .05. Hierarchical stepwise multiple regression was used to examine the incremental validity for desirability ratings of alcohol expectancies beyond likelihood ratings. Desirability ratings that predicted above and beyond likelihood ratings were Negative Expectancies Total Effects, Cognitive-Behavioral Impairment Effects, Risk and Aggression Effects, and Self-Perception Effects (see Table 11). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 76 Discussion The purpose of this study was to examine the effects of selected cognitive and affective variables on drinking behavior in a sample of Freshman and Senior college students. Variables examined in this study were positive and negative alcohol expectancies, coping style, and positive and negative affect. The current study also examined the freshman and senior cohorts in a cross-sectional manner to analyze differences between groups in drinking rate, number of binge episodes and predictors of alcohol use. In this study, 91% of the participants reported consuming alcohol. Comparable prevalence rates for alcohol consumption have been reported in other studies on college student alcohol use. Broer (1996) found that 94% of students reported consuming alcohol, where as Presley, et al. (1995) and Biscaro, et al. (2004) reported prevalence rates of 85% and 87% respectively. CORE (Presley et al., 1994) data collected at this University in 2001 showed 86% of students reported using alcohol. With regard to binge drinking, results from the present study indicated that 77% of students reported a binge drinking episode within the previous two weeks. As with prevalence rates for alcohol consumption, this rate is highly similar to those found in past research. For example, Biscaro, et al. (2004), Broer (1996), and Vik, Tate, Carrello & Field (2000) reported binge drinking rates of 73%, 63%, and 84% respectively. Also consistent with prior research (Biscaro et al., 2004; Bosari et al., 2001; Broer, 1996; Ham & Hope, 2003; Mooney, 1987; Mooney et al., 1989; Wechsler et al., 2001; Wechsler, Lee, Kuo, Seibring, Nelson & Lee, 2002b), results from this study showed that men are drinking significantly more than women. Men reported drinking Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 77 approximately two times the amount of alcohol of women (22 drinks per week for men and 10 drinks per week for women) and engaging in more frequent binge drinking. While the average biweekly rates of binge drinking in this sample were 2.51 times for women and 3.35 times for men, a closer analysis of the data revealed that these numbers are somewhat misleading as binge rates - especially for women — were not uniform. Among women, 40% reported no binge episodes, while 9% reported binging 6 or more times in the prior two weeks. Similarly among men, 24% reported no binge drinking, while 31% reported binging 6 or more times in the prior two weeks. While a binge is typically defined as any high-consumption drinking episode - without regard to duration — the risks associated with binge drinking greatly increase when the length of the drinking occasion is shorter. Clearly consuming 5 drinks within 3 hours is very different than consuming 5 drinks over the course of 8 hours. In this sample, men reported their drinking occasions lasted about 4 hours and women reported drinking occasions lasting 3.5 hours. For both men and women, this equals 1.25 or more drinks per hour, clearly in excess of the body’s metabolic and excretion abilities. However, while the overall binge rates are high, the number of students using alcohol in a more responsible manner is not insignificant. Given the preponderant influence of perceived peer use on drinking behavior, interventions that highlight the number of non binge drinkers may serve to increase the salience and ability of such individuals to serve as role models. Contrary to prediction, seniors and freshmen showed no differences in pattern or amount of alcohol use. While it had been hypothesized that seniors would use less alcohol, as a group seniors actually drank one more drink per week than freshmen and Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 78 had about one half more binge episodes per week. These results do not support the concept of drinking behavior as a “transitional phase” purported to occur during students’ freshman year when the effects of social pressure and adjustment may be most pronounced. Alcohol use was prominent for students in both years. Results showed that 18 freshmen (15 %) and 6 seniors (5%) abstained from alcohol. Fifty percent of Freshmen and Seniors reported consuming more than 10 drinks per week and 25 % of Freshmen and Seniors reported drinking more than 20 drinks per week. Abstinence rates were somewhat lower for this sample than what have been observed in other studies examining abstinence rates. For example, Wechsler et al. (2002b), aggregating across a variety of studies, found abstinence rates in the range of 16-19%. Wechsler’s study differed from the current study by examining all class cohorts and using data collected from a number of institutions. The consumption rates for this sample are doubly concerning, not only due to the number of drinks that are consumed per week (especially by men), but because there is no significant reduction in overall drinking rates and patterns over the collegiate years. The seniors are drinking and binging at the same rates as freshmen. These findings support the idea that problem drinking patterns are established early and those students who engage in problem drinking early in college continue to do so throughout their collegiate experience (Wechsler, et al. 1994) and university administration and counseling centers would be wise to develop and encourage early intervention strategies as part of a comprehensive alcohol policy. Consistent with previous research (Clements, 1999; Wechsler et al., 1994; Wechsler, 2002a) and another area for concern, was an increase in alcohol related Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 79 problems with higher levels of alcohol consumption. In this study, students who consumed more alcohol were much more likely to experience increased physiological and behavioral consequences. Physiological consequences that were most related to increased alcohol use were having a hangover, experiencing memory loss, and vomiting, as these are common withdrawal symptoms of intoxication. Common behavioral consequences related to higher alcohol use were missing class, doing poorly on a test, doing something they later regretted, getting hurt or injured, fighting, damaging something, and driving under the influence. Students who missed a class were more likely to experience both physiological and behavioral consequences. Participants were more likely to view their drinking as problematic if they tried to stop before or had been in trouble with the police. While other drug use was positively correlated with increased alcohol consumption, the relationship was weak. The weak relationship is probably due to the low prevalence of illicit drug use in this sample. Examination of hypothesized predictors of participant’s alcohol use produced mixed results. Contrary to what was hypothesized, coping style and negative affect were not related to outcome in the overall sample or in either individual cohort. In general, the cohorts reported adequate coping, considerable positive affect and minimal negative affect. The minimal variance observed in these constructs may explain why the directional model was not supported. The directional model in this study, based on Cooper et al.’s Motivational Model of Alcohol Use (1995), hypothesized that greater positive alcohol expectancies, increased negative affect and escapist or avoidant coping would yield increased alcohol consumption. In this sample, only positive expectancies were predictive of increased alcohol consumption. The predictive importance of Total Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 80 Positive Expectancies is consistent with previous research (Biscaro et al., 2000; Broer, 1996; Fromme et al., 1993; Jones et al., 2001; Mooney et al., 1987). The most potent predictor of alcohol consumption in both the entire sample and each cohort was peer use (assessed by the participant’s perception of their best-friend’s use). Peer usage accounted for 44% of the variance in the entire sample, 32% of the variance in the Freshman sample, and 58% of the variance in the Senior sample. Perceived peer use and participants’ reported use were directly related. The higher the perceived peer use the greater the participant’s alcohol consumption, the lower the perceived peer use the lower the participant’s consumption. Interestingly - and contrary to developmental theories — the influence of perceived peer use was greatest in the senior sample. While it may be that over time, students develop a pattern of behavior and the behavior is reinforced by the student’s social milieu, these results could also be interpreted as meaning that student’s who drink heavily select friends who will share in this behavior. In other words, peer pressure may not be causing students to drink; rather, “drinking pressure” may be causing students to pursue certain relationships over others. While general positive expectancies (measured as a summary of all individual positive expectancies) was mildly related to outcome, examination of the individual components revealed that this was due to the powerful effects of one particular element: “Liquid Courage”. Liquid Courage is the expectation that alcohol will make the user feel more courageous, daring, fearless, and powerful. This belief was predictive of drinking behavior for the entire sample and for the freshmen cohort. It was not related to outcome in the senior cohort. This finding does fit with developmental models of excessive use. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 81 as it suggests that while Freshmen use alcohol as a way to augment self-confidence, and Seniors do not. Among the Negative Expectancies, Self-Perception, or the view that alcohol would increase the likelihood that one would feel moody, guilty, self-critical, or magnify existing problems, was related to participant alcohol use for the entire sample and in both cohorts. Self-perception was inversely related to participant alcohol use. Most importantly, however, this relationship was moderated by perceived peer use and it was only predictive when perceived peer use was low. When friends were perceived as drinkers. Self-perception was not related to alcohol consumption. This result suggests that one of the ways that peer use exerts its influence is through self-appraisal. Seeing one’s friends as light/minimal drinkers serves as a protective factor against alcohol consumption. It may be that, within such a peer group, there is concern that consuming alcohol could lead to ostracism or becoming an outcast. The individual who chooses to drink in a group of non-drinkers may become acutely aware of how their behavior is deviating from the group’s norms. Alternately, when friends are seen as drinkers, alcohol consumption becomes normative as do all of its effects, including those that are negative in nature. As such, there is little reason to monitor or perceive oneself in a negative light. This finding, while important, does not illuminate the nature of the link between peer group and drinking behavior, as it is consistent with both peer pressure and friend selection explanations. This study examined the incremental validity for desirability ratings of alcohol expectancies beyond likelihood ratings. Fromme et al. (1993) stated the importance of assessing desirability ratings separately from likelihood ratings, such that the amount one Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 82 chooses to drink may be largely influenced by the desirability of alcohol’s effects. The desirability ratings that predicted above and beyond likelihood ratings were Negative Expectancies Total Effects, Cognitive-Behavioral Impairment Effects, Risk and Aggression Effects, and Self-Perception Effects. Only the desirability ratings of negative outcomes were significant, which suggests that if one deems the negative effects of alcohol as desirable there is more likely to be an additive effect on outcome. Thus, if students rated being more impaired, aggressive, and moody as desirable, it increased the likelihood of higher alcohol use. The results of this study should be interpreted with the limitations of the study in mind. First, the study was correlational and cross-sectional in nature, which prohibits any statements about causality or true developmental patterns. Future research might focus on experimental designs looking at interventions aimed at preventing problem use and use a longitudinal design to examine whether or not interventions have an effect over time. Data were self-report only and are therefore subject to participant exaggeration or deception. The sample size was small given the number of variables of interest in the study, which ultimately reduced statistical power and may have led to type II error. Additionally, the sample was limited to a small private university and consisted primarily of Caucasian students, thus, limiting the generalizability of the findings to other students across cultures and the country. Other researchers may want to consider examining a cohort from a number of different universities. Moreover, the Senior cohort in this study was not normally distributed across majors, with considerable over-representation of business majors (92 of the 130 Seniors recruited). This is not representative of most university student bodies and may have undersampled students who are most likely to Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 83 seek graduate or advanced degrees (i.e., those in the social sciences, arts, humanities, and sciences). Thus, it is possible that a more representative Senior sample may have yielded lower alcohol consumption rates. Another limitation is the length of time for the data collection process, as data were collected at times when reported alcohol use may have been skewed in a greater direction (i.e., after Winter Break, after Spring break, during March Madness, etc.). Results showed that only 47 -63% of the variance was accounted for, which leaves a significant amount of variance unexplained. Future research may want to focus on other variables that may maximize explained variance, such as Greek affiliation, availability of alcohol, finances, genetic predisposition, and a more focused analysis of alcohol related consequences related to alcohol use. An improvement from the current literature on college student alcohol use was that the current study examined two groups in diametrically different places in the college experience - entry and exit. It was hoped that this would help shed some light on developmental aspects of drinking on college campuses. Although the findings were contrary to what was expected, important information was obtained, as the study found few students abstaining from alcohol use and no difference in drinking patterns and binge episodes between college freshmen and seniors. College administrators, residence life staff, and counselors should keep this in mind when developing interventions. While the life stressors and demands may be very different on these two cohorts, their alcohol related behavior is very similar. Additionally, it was found that perceived peer alcohol consumption has considerable influence on students’ alcohol consumption, which suggests that students may be more inclined to use alcohol if their peers are drinking. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 84 This provides support for Wechsler (2002a) who suggested students need to be the main vehicle for change on college campuses and they can no longer be overlooked as catalysts for change. Wechsler (2002a) proposed a 12-point action plan for schools to decrease problem drinking on campuses. His plan calls for colleges and universities to recognize alcohol use on college campuses as a problem and then examine the depth of the problem. He encourages a campus-wide effort to curtail the drinking problems on campus, starting at the highest levels of administration (i.e., the President) to the student body and surrounding communities. Above all, students should be involved in the planning, execution, and evaluation of the interventions used. Interventions to be used may include, but are not limited to alcohol free residence halls, implementing a code of conduct and alcohol policy and enforcing it completely and forming agreements with the local communities to assist in limiting underage drinking via decreasing availability of “cheap, high volume alcohol (p. 233).” Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 85 References Abrams, D. B., & Niaura, R. S. (1987). Social learning theory. In H. T. Blane & K. E. Leonard (Eds.), Psychological Theories of Drinking and Alcoholism (pp. 131- 178), New York, NY : The Guilford Press. American Psychological Association. 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Further reproduction prohibited without permission. 92 Table 1 Summary Table of the Demographic Variables by Class Variable Freshmen Seniors M(SD)M(SD) A ge 18.5 (.52) 21.7 (.89)** GPA 3.42 (.46) 3.32 (.38) N (%) N (%) Gender Male 56 (46.7) 57 (43.8) Female 64 (53.3) 73 (56.2) Maior Undecided 25 (20.8) 0 (0.0)** Social Sciences 17(14.2) 28 (21.5)** Arts 25 (20.8) 5 (3.8)** Sciences 21 (17.5) 5 (3.8)** Business 32 (26.7) 92 (70.8)** Residencv On campus 112(93.3) 25 (19.2)** Off Campus Living Independently 2 (1.7) 90 (69.2)** Off Campus Living with Family 6 (5.0) 15(11.5)** Work Status Full-time 3 (2.5) 8 (6.2) Part-time 44 (36.7) 77 (59.2)** Internship 1 (0.8) 19(14.6)** Not Working 72 (60.0) 26 (20.0)** Ethnicity African American 8 (6.7) 9 (6.9) Caucasian 99 (82.5) 112(86.2) American Indian 0 (0.0) 1 (0.8) Asian 4 (3.3) 5 (3.8) Hispanic 4 (3.3) 2(1.5) Other 5 (4.2) 1 (0.8) Recruitment Venue Residence Halls 60 (50.0) 128 (98.5)** Classes 60 (50.0) 2(1.5)** ** P < 0 1 . Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 93 Table 2 Means and Standard Deviations of Alcohol Consumption Variables by Class Variable Freshmen Seniors Total Mean (SD) Mean (SD) Mean (SO) Avg No. of Drinks/week 14.80(15.00) 15.80(15.98) 15.31 (15.50) Binge Episodes (prior 2 weeks) 2.71 (1.57) 3.01 (1.65) 2.89(1.62) Quantity Total (ounces/weekf) 12.90(10.98) 15.49(13.65) 14.24 (12.49) Peer U se (perceived weekly number of 19.73 (18.98) 21.28(17.94) 20.53 (18.43) drinks for best friend) Percentage of friends drinking 68.65 (29.54) 71.18(29.96) 69.98 (29.72) Length of time per drinking episode 3.57 (2.26) 3.88(1.98) 3.73 (2.12) (in hours) Maximum drinks on single drinking 10.09 (6.96) 11.37 (7.16) 10.75 (7.08) occasion (for the year) Maximum drinks on a single 12.01 (7.60) 13.37(7.74) 12.72 (7.69) drinking occasion for best friend (for the year) Note, f Quantity Total is a summary score for total amount of beer/alcohol consumed per week in ounces. *p<.OI. **p<.001 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 94 Table 3 Means and Standard Deviations of Alcohol Consumption Variables by Gender Variable Men Women Mean (SD) Mean (SD) No. of Drinks/week 21.87(17.91) 9.91 (10.50)** Binge Episodes (prior two weeks 3.35(1.70) 2.51 (1.45)** Quantity Total (ounces/weekf) 19.07 (14.07) 10.26 (9.32)** Peer U se (perceived weekly number of drinks for best friend) 28.00(21.24) 14.37(12.87)** Percentage of friends drinking 74.91 (27.85) 65.87 (30.69)* Length of time per drinking episode (in hours) 4.10(2.23) 3.41 (1.99)* Maximum drinks on single drinking occasion (for the year) 14.21 (7.46) 7.89 (5.26)** Maximum drinks on a single drinking occasion for best friend (for 15.94 (7.75) 10.06 (6.56)** the year) Note. tQuantity Total is a summary score for total amount of beer/alcohol consumed per week in ounces. *p<.01. **p<.001 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 95 Table 4 Means and Standard Deviations of the predictor variables of interest by Class Variable Freshmen Seniors Positive Affect (PA) 3.45 (.68) 3.44 (.79) Negative Affect 2.12 (.70) 2.09 (.67) Cognitive Self-Control 4.25 (.81) 4.27 (.80) Ineffective Escapism 3.05 (1.18) 2.75(1.07)* Solace Seeking 4.67(1.09) 4.49 (.96) Positive Expectancies Total (PET) 2.86 (.45) 2.71 (.43)** PET Effects 3.41 (.66) 3.40 (.50) Liquid Courage (LC) 2.76 (.71) 2.55 (.64)** LC Effects 3.07 (.92) 2.97 (.79) Sociability 3.46 (.49) 3.29 (.48)** Sociability Effects 4.05 (.69) 4.01 (.55) Tension Reduction (TR) 2.75 (.65) 2.67 (.60) TR Effects 3.45 (.83) 3.58 (.70) Sexuality 2.48 (.83) 2.31 (.71) Sexuality Effects 3.09 (.97) 3.10 (.80) Negative Expectancies Total (NET) 2.57 (.49) 2.36 (.44)*** NET Effects 2.15 (.66) 2.28 (.71) Cognitive-Behavioral Impairment 3.02 (.57) 2.86 (.56)* (CBI) CEI Effects 1.91 (.70) 2.01 (.70) Risk and Aggression (RA) 2.57 (.73) 2.35 (.70)** RA Effects 2.42 (.87) 2.44 (.79) Self-Perception (SP) 2.11 (.65) 1.57 (.56)*** SP Effects 2.12 (.81) 2.38 (.93)** Note. Likert-Type Scale ratings for the variables were: Affect (1 = very slightly or not at all, 5 = extremely), Coping Styles (0 = not at all, 7 = extremely). Alcohol Expectancies (1 = disagree, 4 = agree). Subjective Evaluations - Effects ( 1 = bad, 5 = good). *p<.05. **p<.01. ***p<.OOI Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 96 Table 5 Univariate Results for All Predictor Variables of Interest t p-value Peer Use .47 8.25 <.001* Positive Affect .22 3.58 <.001* Negative Affect .08 1.26 .208 Ineffective Escapism .09 1.48 .140* Solace Seeking .04 .70 .490 Cognitive Self Control -.03 -.50 . 616 Liquid Courage .29 4.49 <.001* Liquid Courage Effects .07 1.12 .256 Sociability .13 1.38 .170 Sociability Effects .10 1.87 .063* Sexuality .09 1.28 .203 Sexuality Effects .20 3.00 .003* Cognitive Behavioral Impairment (CBI) -.13 -1.92 .056* CBI Effects .22 3.33 .001* Risk and Aggression (R/A) .19 3.05 .003* R/A Effects .20 3.25 .001* Self-Perception -.11 -1.69 .092* Self-Perception Effects .23 3.53 < .001* Tension Reduction .11 1.52 .130* Tension Reduction Effects .03 .43 .668 Positive Expectancies Total .23 3.41 .050* Positive Expectancies Effects .13 1.94 <.001* Negative Expectancies Total -.01 -.03 .979 Negative Expectancies Effects .28 4.50 <.001 p < .15 and was included in iterative process of regression analysis Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 97 Table 6 Summary of Hierarchical Stepwise Multiple Regression Analysis for Variables Predicting Variable B SEE p R" AR^ Step 1 Age -1.8E-02 .43 -.002 Sex -5.25 1.60 -.17 ** Peer Use .49 .04 .58 ** .44 .44** Step 2 Age 6.24E-03 .42 -.001 Sex -3.91 1.58 -.13 ♦ Peer Use .46 .04 .53 ** Liquid Courage 3.82 1.11 .17 ** Self-Perception -3.86 1.18 -.15 ** .48 .04** Step 3 (Interaction Effects) Age -7.20E-02 .42 -.008 Sex -3.29 1.49 -.11 * Peer Use 1.18 .14 1.40** Liquid Courage 3.71 1.05 .16** Self-Perception 1.84 1.54 .07 Self-Perception x Peer Use -.35 .07 -.89** .54 .06** p < .05. ** p < .001. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 98 Table 7 Summary of Hierarchical Stepwise Multiple Regression Analysis for Variables Predicting Variable B SEE P Step 1 Age 1.10 2.25 .04 Sex -5.78 2.40 -.19* Peer Use .37 .06 .47 ** .32 .32** Step 2 Age 1.07 2.25 .04 Sex -3.62 2.32 -.12 Peer Use .35 .06 45 ** Liquid Courage 6.04 1.57 29 ** Self-Perception -3.34 1.68 -.15 * .41 .09** Step 3 (Interaction Effects) Age .32 2.06 .01 Sex -2.58 2.25 -.09 Peer Use 1.04 .22 1.32** Liquid Courage 5.66 1.51 .27** Self-Perception 1.79 2.30 .09 Self-Perception x Peer Use -.31 .10 -.90* .47 .06* p<.05. **p<.001. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 99 Table 8 Summary of Hierarchical Stepwise Multiple Regressiort Artalysis for Variables Predicting Variable B SEE P R" AR^ Step 1 Age -1.09 1.05 -.60 Sex -4.08 2.08 -.13 * Peer Use .62 .06 .69 ** .58 .58** Step 2 Age -1.06 1.03 -.06 Sex -3.36 2.08 -.13 Peer Use .62 .06 .70 * * Liquid Courage .13 1.53 .01 Self-Perception -4.68 1.63 -.17 * .60 .02** Step 3 (Interaction Effects) Age -.86 1.00 -.05 Sex -3.62 1.99 -.11 Peer Use 1.17 .18 1.31** Liquid Courage .80 1.50 .03 Self-Perception .15 2.20 .01 Self-Perception x Peer Use -.30 .10 -.67** .63 .03** p < .05. ** p < .001. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 100 Table 9 Multiple Regression Values forTest of Motivational Model (N = 250) Variable B SEE p R: AR^ Step 1 Age -1.5E-02 .43 -.00 Sex -5.41 1.61 -1 7 ** Peer Use .49 .04 .58 ** .44 .44* Step 2 Age .21 .44 .02 Sex -5.38 1.61 - 17 ** Peer Use .46 .05 .55 ** Negative Affect -.76 1.25 -.04 Ineffective Escapism .78 .77 .06 Positive Expectancies Total (PETOT) 3.87 1.81 .11* .46 .02 Step 3 (Interaction Effects) Age .21 .43 .02 Sex 3.48 9.81 .11 Peer Use 1.15 .34 1.36** Negative Affect -.62 1.24 -.03 Ineffective Escapism .80 .77 .06 PETOT 12.38 6.40 .36* PETOT X Peer Use -.24 .12 -.86* .47 .01 p < .05. ** p < .001. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table 10 Correlation Matrix fi^D e m o f^ ^ic Vahabies, Outcome Variables, and Negative (N-250) Consegtsences Class ETOH Peer Other Tobac. Drug Hangover Poorly Tiouh TnOb Damaged Fight Vomiled DUI Missed Use Use Poem Use Use 00 w/ w/ Sometbii* Class Use Test Police Campus OâM 1.0 .032 .042 -.063 • 034 -.02» .357" 117" .139* .1*0" 129** 124" 113** .349" 515" ETOH .032 1.0 .647" 574" 554" .1*0" 493" 493" 524" .427" 455 * .4*0** .450" 443" 565" CoMumplkm (/>(/) PeerUK .042 .647" 1.0 .593" 550" 143* .391" 5*6" 540" 564" 594" 431" .407** .420" .436" Other Peer -.063 .574" 593" 1.0 140" 119" 552" .3*0** 306 " .329" .311" 560" .339" 541" .430" CD *p<.05. •*p<.01. Q. "O 83 "O 2 Q. Q1CD (N O Table 10 (Cooliiaied) Correlation Matrix fo r Demograi^c Variables, Outcome Variables, and Negative Consequences (tt=û50) Bees Tboughtyou Memtey Lorn Did Anested for Titcaadv. Tuck adv. of Tried Lost! Hwtor criticized hadiproblcn eomethiag DUI ofeeniaily mother to atop iclitiocukÿ nymed by regretted aetuaHy eomeooe C üa» .096 .062 .067 .174** .03) .098 .003 -.034 .091 .112 ETOH 43)** 399** .539** .506** .091 374** 1)2* 327** .300" .457" I/) CoMumplicm m PeerUie J23** 344** 397** 393** .146* 18)** .123* .171** 3 2 2 " 3 1 2 " Other Peer J2I** 306** 397** 37)** 141* 138* .149* .162* .227" 3 2 4 " CD Uk Q. Tobecxo Uee .292** .281** 394** 303** 112 .183** 319** .2)7** .172" 3 )5 " DmgUte .156* .148* .1)4* .1)5* -.012 .082 182** 136* .174" .142* H a^orer .413** 397** .623** .592** .1)0* 1)9* .065 3 0 6" 3 0 7 " 3 ) 9 " Poorly oo teat .4*** 394** 390** .483** 367** .181** ,148* .136* .325" 3 9 7 " T3 TiauMeW .296** .478** .4)0** 363** 306** .1)9* 324** .281** 3 0 5 " 3 6 9 " CD pohoe .212** .268" .444" TmwhkW .419** 383** .422** .468** .116 3«** .157* 2 Q. 396» J71** 34)** 376** 380** .102 .042 .098 .145* 3 57 " C o FigM .601** 351** .500** .568** .1)9* 372** .117 .179** 3 7 4" .492" "G3 Vomited .504** 370** 3)4*' .5)3** .188** 371** .103 .170** 3 12 " .427** T3 OUI .464** 349** .479** .514** .183** .117 .182** .161* 3 1 9" .431" 2 Missed Cisss .476** .428** .490** 377** .188** 376** .179** 305** 3 7 6" .409" Q. 1.0 3)1** .495** .477** 319** 387** .140* .175" 3 9 4" .420" 2 Criticized by G Thought you 3)1** 1.0 349** .3)8** 340** 373** .208** .500" .253" 3 2 2 " had problem Memory Loet .49)** 349** 1.0 .628** .182** 3)2** .156* 203" 33 2 " .401" Regretted .477** 358** .628** 1.0 .193** 310** 184** 3 1 5 " .415" .426" Aliened for 319** 340** .182** .19)** 1.0 346** 322** .171" .120 .145* DUI Tekeaadv of 367** 373** 3)2** 310** 346** 1.0 362** 3 2 1 " 3 3 3 " 3 9 6 " sexuaBy Took adv. of .140* 308** 1)6* .184** 322** 362** 1.0 .171" .298" .233" 8 Tried to Itop .17)** 300** 303** 31)** .174** 321** .171** 1.0 .202" 306** Loett 394** 353** 332** .41)** .120 333** .296** .202" 1.0 3 8 9 " Rriitioiahip Hurt or .420** .322** .401** .426** .145* 396** .233** 3 0 8 " 3 8 9 " 1.0 CO irÿaed CO CD *p<.05. ♦*p<.01. Q. "O 8 "O3 2 Q. Q1CD 103 Table 11 Comparison of Predictive Utility of Likelihood and Desirability Ratings for Alcohol Expectancies (N = 250) ______ Variable B SEB P R: AR: Cognitive-Behavioral Impairment Regression 1 Step 1 Age -.06 .42 -.01 Gender -5.21 1.59 -.17** Peer Use .49 .04 .58** .44 .44** Step 2 Age -.17 .43 -.02 Gender -4.75 1.60 -.15* Peer Use .48 .04 .58** Cognitive-Behavioral Impairment (CBI) -2.37 1.33 -.09 .44 < .01 Step 3 Age -.24 .42 -.03 Gender -4.24 1.61 -.14* Peer Use .48 .04 .57** CBI -1.36 1.38 -.05 CBI Effects 2.71 1.13 .12* .46 .02* Regression 2 Step 1 Age -.06 .42 -.01 Gender -5.21 1.59 -.17** Peer Use .49 .04 .58** .44 .44** Step 2 Age -.18 .42 -.02 Gender -4.41 1.59 -.14* Peer Use .48 .04 .57** Cognitive-Behavioral Impairment Effects 3.05 1.07 .13* .46 .02* Step 3 Age -.24 .42 -.03 Gender -4.24 1.61 -.14* Peer Use .48 .04 .57** CBI Effects 2.71 1.12 .12* CBI -1.36 1.38 -.05 .46 < .01 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 104 Table 11 (Continued) Variable B SEB P R" AR" Risk and Aggression Regression 1 Step 1 Age -.03 .42 -.004 Gender -5.27 1.59 -.17** Peer Use .49 .04 .58** .44 .44** Step 2 Age .09 .43 .01 Gender -5.03 1.60 -.16* Peer Use .48 .04 .57** Risk and Aggression 1.47 1.05 .07 .44 < .01 Step 3 Age .01 .427 .001 Gender -4.90 1.58 -.16* Peer Use .47 .04 .56** Risk and Aggression 1.40 1.05 .07 Risk and Aggression Effects 2.11 .88 .11* .46 .02* Regression 2 Step 1 Age -.03 .42 -.004 Gender -5.27 1.59 -.17** Peer Use .49 .04 .58** .44 .44** Step 2 Age -.11 .42 -.01 Gender -5.12 1.58 -.17** Peer Use .48 .04 .57** Risk and Aggression Effects 2.15 .88 .12* .46 .02* Step 3 Age .009 .43 .001 Gender -4.90 1.58 -.16* Peer Use .47 .04 .56** Risk and Aggression Effects 2.11 .88 .11* Risk and Aggression 1.40 1.05 .07 .46 <.01 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 105 Table 11 (Continued) Variable BSEB P R" AR: Self-Perception Regression 1 Step 1 Age -.03 .42 -.004 Gender -5.27 1.59 -.17** Peer Use .49 .04 .59** 44 .44** Step 2 Age -.24 .42 -.03 Gender -4.79 1.58 -.15* Peer Use .49 .04 .58** Self-Perception -3.30 1.20 -.13* .46 .02* Step 3 Age -.38 .43 -.04 Gender -4.38 1.58 -.14* Peer Use .48 .04 .58** Self-Perception -2.66 1.22 -.11* Self-Perception Effects 1.91 .87 .11* .47 .01* Regression 2 Step 1 Age -.03 .42 -.004 Gender -5.27 1.59 -.17** Peer Use .49 .04 .59** .44 .44** Step 2 Age -.26 .43 -.03 Gender -4.64 1.59 -.15* Peer Use .48 .04 .57** Self-Perception Effects 2.37 .86 .14* .46 .02* Step 3 Age -.38 .43 -.04 Gender -4.38 1.58 -.14* Peer Use .48 .04 .58** Self-Perception Effects 1.91 .87 .11* Self-Perception -2.66 1.22 -.11* .47 .01* Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 106 Table 11 (Continued) Variable BSEB P R" AR" Negative Expectancies Total Regression 1 Step 1 Age -.06 .42 -.006 Gender -5.21 1.59 -.17** Peer Use .49 .04 .59** .44 .44** Step 2 Age -.18 .44 -.02 Gender -5.09 1.60 -.16* Peer Use .49 .04 .59** Negative Expectancies Total -1.94 1.59 -.06 .44 < .01 Step 3 Age -.32 .43 -.04 Gender -4.49 1.58 -.14* Peer Use .49 .04 .57** Negative Expectancies Total Effects -1.14 1.59 -.04 Negative Expectancies Total 3.34 1.11 .15** .46 .02* Regression 2 Step 1 Age -.06 .42 -.006 Gender -5.21 1.59 -.17** Peer Use .49 .04 .59** .44 .44** Step 2 Age -.25 .42 -.03 Gender -4.53 1.58 -.15* Peer Use .48 .04 .57** Negative Expectancies Total Effects 3.48 1.10 .15* .46 .02* Step 3 Age -.32 .43 -.04 Gender -4.49 1.58 -.14* Peer Use .48 .04 .57** Negative Expectancies Total Effects 3.34 1.11 .15* Negative Expectancies Total -1.14 1.59 -.04 .46 < .01 p < .05. ** p < ,001. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 107 Appendix A WER UNIVERSITY lutftutloiMl Rttriiw leaid 3100 Victoiy hrkwijF Cincinnati. Ohio 4SZ0T-7361 Phone 513 745-2*70 Fax 513 745-4267 September 24,2003 Michael Biscara, M.A. 1031 Delta Avenue #21 Cincinnati. OH 43208 Dear Mr. Biacaro: The IRB received your Protocol #0237-3, Alcohol E^q)ectemcles, Coping, and Affect in Predicting College Student Alcohol Use,on September 18. Your protocol was reviewed at the September 22 meeting. Your research is approved by XU’s IRB in the Expedited Review category. A Final Report is due upon completion of your study or, if not yet completed one year from this date, a Status Report must be filed. A form is enclosed for your convenience. The form is also available at wwwjni.edu/IRB/lRBfonnsJitm. If there are any adverse events or modifications to the research, please notify the IRB immediately. We wish you every success wifi: your research. Sincerely, Robert C. Baumiller, S J. IRB Chair and Administrator RCB'Jun cc Dr. Susan Kenfbrd, ML 6411 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.