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Cue reactivity and the role of social alcohol expectancies in the college-aged drinking population

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Title:
Cue reactivity and the role of social alcohol expectancies in the college-aged drinking population
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English
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Carter, Ashlee C
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University of South Florida
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Startle eyeblink
Alcohol use
Expectancy theory
Blunted response
Psychophysiology
Dissertations, Academic -- Psychology -- Masters -- USF
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bibliography   ( marcgt )
theses   ( marcgt )
non-fiction   ( marcgt )

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Abstract:
ABSTRACT: Research has shown alcohol expectancies to be critically important in understanding maladaptive drinking patterns within alcohol use disorders. Alcohol expectancies, thought to be automatically elicited in the presence of environmental alcohol-related cues, represent both cognitive and affective associations with drinking behavior. However, the automatic and affective properties of alcohol expectancies have not yet been thoroughly measured in the literature. Psychophysiological measures, including skin conductance, heart rate, and the acoustic startle response in particular, offer a uniquely powerful set of indices for the automatic affective processing of alcohol-related cues.^ ^Therefore, the present study was designed to examine how alcohol expectancies moderate affective processing of alcohol cues and how they relate to other known risk variables for alcohol use disorders.Fifty-eight college-aged participants viewed pictures from three categories (neutral, alcohol-nonsocial, and alcohol-social) and gave subjective ratings of valence, arousal, dominance, and craving for each cue. Skin conductance, heart rate and startle responses were obtained during picture viewing. The startle eyeblink reflex was probed early in the picture viewing sequence to assess arousing and attentional cue properties and late in order to address affective and motivational cue properties.Analyses indicated that participants reporting more positive, arousing, and social alcohol expectancies rated alcohol cues as more pleasant, arousing and craving-inducing.^ Individuals with greater positive/arousing alcohol expectancies displayed blunted cardiac deceleration during alcohol-related cues, indicating that they processed these cues as less aversive than other participants. In addition, individuals with greater social alcohol expectancies displayed greater skin conductance response to alcohol-related cues, indicating increased arousal during alcohol pictures. Startle response patterns indicated that individuals at greater risk for alcohol use disorders (i.e. family history positive, greater positive/arousing alcohol expectancies) displayed blunted processing of alcohol-related cues, while individuals at lower risk processed alcohol-related cues as more pleasing and attention-grabbing. Ultimately, alcohol-related cues were processed as more pleasing and appetitive among lower-risk individuals, lending support to affective and automatic processing component of alcohol expectancy theory.^ ^This study also lends further evidence to support blunted affective processing of alcohol-related stimuli among high risk individuals.
Thesis:
Thesis (M.A.)--University of South Florida, 2006.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
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by Ashlee C. Carter.
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Title from PDF of title page.
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Document formatted into pages; contains 85 pages.

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oclc - 182560628
usfldc doi - E14-SFE0001809
usfldc handle - e14.1809
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ABSTRACT: Research has shown alcohol expectancies to be critically important in understanding maladaptive drinking patterns within alcohol use disorders. Alcohol expectancies, thought to be automatically elicited in the presence of environmental alcohol-related cues, represent both cognitive and affective associations with drinking behavior. However, the automatic and affective properties of alcohol expectancies have not yet been thoroughly measured in the literature. Psychophysiological measures, including skin conductance, heart rate, and the acoustic startle response in particular, offer a uniquely powerful set of indices for the automatic affective processing of alcohol-related cues.^ ^Therefore, the present study was designed to examine how alcohol expectancies moderate affective processing of alcohol cues and how they relate to other known risk variables for alcohol use disorders.Fifty-eight college-aged participants viewed pictures from three categories (neutral, alcohol-nonsocial, and alcohol-social) and gave subjective ratings of valence, arousal, dominance, and craving for each cue. Skin conductance, heart rate and startle responses were obtained during picture viewing. The startle eyeblink reflex was probed early in the picture viewing sequence to assess arousing and attentional cue properties and late in order to address affective and motivational cue properties.Analyses indicated that participants reporting more positive, arousing, and social alcohol expectancies rated alcohol cues as more pleasant, arousing and craving-inducing.^ Individuals with greater positive/arousing alcohol expectancies displayed blunted cardiac deceleration during alcohol-related cues, indicating that they processed these cues as less aversive than other participants. In addition, individuals with greater social alcohol expectancies displayed greater skin conductance response to alcohol-related cues, indicating increased arousal during alcohol pictures. Startle response patterns indicated that individuals at greater risk for alcohol use disorders (i.e. family history positive, greater positive/arousing alcohol expectancies) displayed blunted processing of alcohol-related cues, while individuals at lower risk processed alcohol-related cues as more pleasing and attention-grabbing. Ultimately, alcohol-related cues were processed as more pleasing and appetitive among lower-risk individuals, lending support to affective and automatic processing component of alcohol expectancy theory.^ ^This study also lends further evidence to support blunted affective processing of alcohol-related stimuli among high risk individuals.
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Cue Reactivity and the Role of Social Alcohol Expectancies in the College-Aged Drinking Population by Ashlee C. Carter A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts Department of Psychology College of Arts and Sciences University of South Florida Major Professor: Mark Goldman, Ph.D. David Drobes, Ph.D. Cheryl Kirstein, Ph.D. Date of Approval: September 26, 2006 Keywords: startle eyeblink, alc ohol use, expectancy theory blunted response, psychophysiology Copyright 2006, Ashlee C. Carter

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Table of Contents List of Tables iii List of Figures iv Abstract v Introduction 1 Alcohol Use Disorders 2 Development of Expectancy Theory 3 Alcohol Expectancies an d Drinking Behavior 5 Social Influences on Alcohol Expectancies 7 Appetitive-Motivational Model of Drinking 9 Psychophysiological Measures 10 Startle Reflex and Affective Cue Processing 13 Preliminary Study 16 Specific Aims 17 Methods 19 Participants 19 Sample Description 20 Procedure 21 Measures 24 Data Processing 27 Results 28 Descriptive Statistics for Dependent Variables 28 Descriptive Statistics for Al cohol Expectancy Measures 29 Relationship between Alcohol Expe ctancies and Risk Variables 30 Relationship between Gender and Independent Variables 32 Subjective Cue Ratings 32 Cardiac Reactivity 37 Skin Conductance 40 Acoustic Startle Reactivity 43 Discussion 48 References 56 i

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Appendices 64 Appendix A: Figures 65 Appendix B: Measures 78 ii

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List of Tables Table 1 Descriptive Statistics for Dri nking Behavior and Sensation Seeking 28 Table 2 Family History for Alcohol Use Disorders 29 Table 3 Descriptive Statistics fo r Alcohol Expectancy Scales 30 Table 4 Zero-Order Correlations betw een Alcohol Expectancies and Risk Variables 31 Table 5 Descriptive Ratings for Subjective Cue Ratings 33 Table 6-A Zero-Order Correlations be tween Subjective Ratings and Alcohol Expectancies 36 Table 6-B Zero-Order Correlations be tween Subjective Ratings and Alcohol Expectancies 37 Table 7 Descriptive Statistics for Cardiac Reactivity 38 Table 8 Zero-Order Correlations between Cardiac Activity (D1) and Alcohol Expectancies 39 Table 9 Descriptive Statistics fo r Skin Conductance Reactivity 41 Table 10 Descriptive Statistics for Tr ansformed Skin Conductance Reactivity 41 Table 11 Descriptive Statistics for Early and Late Startle Reactivity 44 Table 12 Zero-Order Correlations betw een Startle Magnitudes and Alcohol Expectancies 45 iii

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List of Figures Figure 1 Subjective Affective and Craving Ratings 65 Figure 2 Arousal Rating Means Separated by Gender 66 Figure 3 Craving Rating Means Separated by Gender 67 Figure 4 Mean Cardiac Activity across Cue Type 68 Figure 5 Mean Startle Magnitudes during Early and Late Trials 69 Figure 6 Interaction of Cue Type by AEQ Aggression/Arousal Subscale 70 Figure 7 Interaction of Cue Type by AEMax Positive/Arousing Subscale 71 Figure 8 Interaction of Cue T ype by AEMax Negative Subscale 72 Figure 9 Interaction of Cue Type by AEMax Egotistical Subscale 73 Figure 10 Interaction of Cue Type by AEMax Horny Subscale 74 Figure 11 Interaction of Cue Type by AEQ Global Positive Subscale 75 Figure 12 Interaction of Cue Type by AEQ Tension Reduction Subscale 76 Figure 13 Interaction of Cue Type by Family History Status 77 iv

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Cue Reactivity and the Role of Social Alcohol Expectancies in the College-Aged Drinking Population Ashlee C. Carter ABSTRACT Research has shown alcohol expectanci es to be critically important in understanding maladaptive dri nking patterns within alcohol use disorders. Alcohol expectancies, thought to be automatically el icited in the presence of environmental alcohol-related cues, represent both cognitive and affective associations with drinking behavior. However, the automatic and affec tive properties of alcohol expectancies have not yet been thoroughly measured in the literature. Psychophys iological measures, including skin conductance, h eart rate, and the acoustic star tle response in particular, offer a uniquely powerful set of indices for th e automatic affective processing of alcoholrelated cues. Therefore, the present study was designed to examine how alcohol expectancies moderate affectiv e processing of alcohol cues an d how they relate to other known risk variables for al cohol use disorders. Fifty-eight college-aged pa rticipants viewed pictur es from three categories (neutral, alcohol-nonsocial, a nd alcohol-social) and gave s ubjective ratings of valence, arousal, dominance, and craving for each cue. Skin conductance, he art rate and startle responses were obtained during picture viewi ng. The startle eyebli nk reflex was probed v

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early in the picture viewing sequence to a ssess arousing and atten tional cue properties and late in order to address affectiv e and motivational cue properties. Analyses indicated that pa rticipants reporting more pos itive, arousing, and social alcohol expectancies rated alc ohol cues as more pleasant, arousing and craving-inducing. Individuals with greater positive/arousing alc ohol expectancies displayed blunted cardiac deceleration during alcohol-related cues, indicati ng that they processed these cues as less aversive than other participants. In add ition, individuals with greater social alcohol expectancies displayed greater skin c onductance response to alcohol-related cues, indicating increased ar ousal during alcohol pictures. St artle response patterns indicated that individuals at greater risk for alcohol use disorders (i.e. family history positive, greater positive/arousing alcohol expectancies) displayed bl unted processing of alcoholrelated cues, while individuals at lower risk processed alcohol-re lated cues as more pleasing and attention-grabbing. Ultimately, al cohol-related cues were processed as more pleasing and appetitive among lower-risk indivi duals, lending support to affective and automatic processing component of alcohol e xpectancy theory. This study also lends further evidence to support bl unted affective processing of alcohol-related stimuli among high risk individuals. vi

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Introduction Alcohol use disorders, in cluding alcohol abuse and al cohol dependence, have a wide variety of negative effects on both so ciety and the individual. Therefore, understanding risk factors and individual proces ses associated with excessive drinking is critically important. One fact or that research has shown to be important in understanding maladaptive drinking, especially in young a dults, is alcohol expectancies. Alcohol expectancies represent both cognitive and affective associa tions with drinking behavior (Goldman, Darkes, Reich & Brandon, 2006). Al cohol expectancies are often thought of as automatically elicited in the presence of alcohol-related cues in the environment, which guide drinking behavior. A limitation of previous research is the focus on the explicit, cognitive component of alcohol expectancies, measured via paper-and-pencil questionnaires, while the automatic, affective pr operties of alcohol e xpectancies have not been as thoroughly measured. A powerful tool for examining affective cue processing is psychophysiological measurement. In particular, acoustic startle eyeblink reflex is effective in measuring the arousing and affective properties of salient cues. Because the arousing and affective properties of alcohol cues are a function of ones individual alc ohol expectancies, the startle eyeblink reflex offers a uniquely pow erful measurement of automatic affective processing of alcohol stimuli. Therefore, the goal of the current study was to employ psychophysiological indices of risk, particularly the startle eyeblink reflex, to further understand how alcohol 1

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expectancies moderate individua l processing of alcohol cues. In addition, it is important to understand how individual processing of alco hol cues is related to drinking behavior and other known risk variables for alcohol use di sorder. This current study is designed to contribute to the overall research examining ri sk factors and processes associated with problematic drinking in our society. Alcohol Use Disorders A recent national survey revealed that 17.6 million Americans suffer from an alcohol use disorder (alcohol abuse or alc ohol dependence) each year, making it one of the most prevalent mental disorders in th e United States (Grant, Dawson, Stinson, Chou, Dufour & Pickering, 2004). Annually, alcohol use disorders contribute to thousands of alcohol-related injuries and d eaths and cost the nation bill ions of dollars, with money allocated to medical expenses, specialty alcohol services, an d criminal justice proceedings (Hingson, Heeron, Zakocs, Kopstein & Wechsler, 2002; Harwood, 2000). On an individual level, heavy drinking cau ses profound deficits in cognitive functioning, physical health, and mental well-being, which often lead to negative consequences within an individuals family, caree r, and social networks. Understanding an individuals motivations to drink alcohol, despite negative consequences, and assessing indivi dual risk factors for future alcohol use disorders, have been a focus of research for many years. In particular, research on alcohol use disorders, alcohol expectancies, and motivations for drinking has targeted the college-aged population for a number of reasons. First of al l, individuals between the ages of 18 and 24, including both students and nonstudents, tend to drink more frequently and at higher quantities than any other age group. The variety of drinker types also is very rich, 2

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ranging from abstinent individuals, to social drinkers, to heavy drinkers, rendering this population a valuable data source for resear ch on alcohol use. Risky behaviors and socio-economic problems associated with h eavy drinking and alcohol use also emerge and peak in young adulthood, making this sample particularly valuable in understanding risk factors for heavy drinking (Hingson et al, 2002). Finally, this population is easily accessible and convenient, since the majority resides in close proximity to college and university settings, where rese arch is often conducted. Fo r these reasons, this study samples from a college-aged population in order to investigate the risk factors for alcohol use disorders and how they rela te to alcohol expectancies. Development of Expectancy Theory In 1932 Tolman first developed formal expectancy theory to describe the cognitive processes by which the environment impacts animal behavior. Tolman posited that organisms are goal-oriented and pur posefully combine cognitions about the environment and past experience to reach determinable ends (Tolman, 1932). Expectations are thought to moderate an indi viduals response to a stimulus in the environment in order to achieve a desired goal. Over the years, advances to expectancy theory have been made by MacCorquodale and Meehl (1954), Rotter (1954 ), and Bolles (1972), who elaborated on the learning processes by wh ich an organism observes a situation and stores this environmental information for later use. MacCorquodale and Meehl formalized expectancy theory into an equation that in cludes not only an orga nisms response to a stimulus (S-R), but the expect ed outcome of the response to a stimulus (S-R-S). Rotter further distinguished this expected outcome variable from a reinforcement value (S*), 3

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which he defines as the degree of preferen ce for possible outcomes given a stimulus. Bolles then suggested that a re sponse is dependent on three vari ables: the strength of the reinforcement value (S*), the expected out come of a stimulus (S-S* or learned expectancies) and the ex pected outcome of a response to that stimulus (R-S* or prior expectancies). Therefore, this model of exp ectancies proposes that an organisms learned and innate expectancies combine to predict the likelihood that an animal will respond to an environmental cue in a specific way. Expectations about an environmental cue not only involve cognitive assessments of a stimulus, but also emotional memories a ssociated with the stimulus (Goldman et al, 2006). In that regard, modern expectancy th eory employs both automatic, affective (this stimulus makes me feel good/bad) and explicit, cognitive (I know the causes and effects of my behavior) appraisals of environmenta l stimuli. An organism then can quickly assess whether salient stimuli is particularly threatening (i.e. a snake which bite can lead to death) or perhaps evolutionarily advantageous (i.e. a soci al gathering of ones peers, which can lead to reproducti on and gene proliferation). Expectancy theory as applied to alcohol research describes individual motivations and cognitions driving drinking behavior. Alcohol expectancies refer to an individuals reasons to drink (approach) or not drink (a void), as developed th rough experience and observation of alcohol use in the environmen t. Generally, alcohol expectancies are believed to develop by gathering informati on about alcohol from the environment and forming an automatic, subconscious system th at operates without awareness and drives drinking behavior (Goldman, Del Boca & Darkes, 1999). That is to say that an individuals drinking behavior on a given occasion is driven by past experience and 4

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memory associations about the effects of alc ohol, whether positive or negative, at a level below the surface of awareness and that is au tomatically evoked in the presence of an alcohol stimulus. Currently, measures of alcohol expectancies are mostly explicit and cognitive in nature (paper-and-pencil questionnaires) and they do not account for the more automatic, emotional motivations and expected rewards driving drinking behavior. Researchers have been successful in va lidating the cognitive compone nts to alcohol expectancy theory: drinkers self report of alcohol expectancies pred icts drinking behavior; when positive expectancies are activated, drinking be havior is produced; and free-associations to alcohol primes are correlated with dr inking behavior (i.e. Goldman & Darkes, 2004; Reich & Goldman, 2005). However, researcher s must address and effectively measure the more automatic, affective processing of al cohol stimuli in order to further understand how alcohol expectancies are asso ciated with drinking behavior. Alcohol Expectancies and Drinking Behavior Alcohol expectancies have proven one of the strongest predictors of drinking behavior, holding other variables constant such as race, gender and socioeconomic status (Goldman, 1994; Goldman & Rather, 1993). More specifically, the characteristics of alcohol expectations, including valence and arousal dimensions of drinking associations, best predict drinker type, in cluding heavy and light drinker status (Goldman, Del Boca & Darkes, 1999). Positive alcohol expectancies are those that reflect the more emotionally positive, arousing and reinforcing properties of alcohol consumption, such as feeling happy, social or horny. Alternatively, negativ e alcohol expectancies typically include more emotionally negative and sedating effect s of alcohol, such as feeling sick, sad or 5

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sleepy. Goldman and colleagues (1999) found th at heavier drinkers tend to endorse more positive, arousing effects of alcohol consump tion, while lighter drinkers endorse more negative and sedating effects of drinking. Expectancies and drinking behavior mainta in a reciprocal relationship, with one influencing the other, thus strengthening the relationship between alcohol expectancies and subsequent alcohol use (Smith, Gold man, Greenbaum & Christianson, 1995; Aas, Leigh, Anderssen & Jakobsen, 1998). Rather and Goldman (1994) suggest that heavy drinkers employ strong associations be tween positive and arousing outcomes for drinking, while light drinkers have a looser association network between drinking and positive outcomes. Although heavy drinkers may at times associate drinking with negative consequences, such as sickness or danger, these associations are much weaker than positive associations to alcohol. Therefore, when a heavy drinker is presented with a drinking opportunity, alcohol consumption b ecomes the most probable and reinforcing outcome behavior. Alcohol expectancies have also been s hown to mediate the relationship between antecedents of risk for alcohol use problems, such as family history, gender, race, age, and sensation seeking (Goldman, Darkes & Del Boca, 1999). Strong associations between positive outcomes and drinking alcohol serve to strengthen the risk for developing alcohol use disord ers or risky drinking behavi or. Since risky drinking behavior peaks among college-aged individuals, it is likely that pos itive and reinforcing alcohol expectancies play a cr ucial role in influencing heavy, binge drinking behavior in this population. Recently, it has been suggested that the phys ical and social co mponents of alcohol 6

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expectancies may best expl ain the elevated drinking pa tterns among the college-aged population. In an evaluation of the predictive validity of several expectancy subscales, including global positive exp ectancies and relaxation exp ectancies, the social and physical pleasure expectancy subscale maintained the highest predictive power for drinking in the young adult population (Goldman & Darkes, 2004). That is to say that the social aspects of drinking correlate highest w ith drinking behavior. It is likely that the overall positive effects of alcohol drive drinking behavior in the young adult population, but that more specifically the social and physical expected benefits of drinking may prove more appetitive and arousing to this group of individuals. Social Influences on Alcohol Expectancies When overall alcohol expectancies are c ontrolled for, the social situation, companions and physical setting best predic t drinking behavior in young adults (Senchak, Leonard & Greene, 1998). This is not surprisi ng as college-aged drinking occurs most frequently in a social context, such as ba rs, parties and sporting events. Senchak and colleagues further demonstrated that young adults are more likely to consume alcohol in large groups of mixed sex or small groups of the same sex in an act of bonding and forming friendships. Social c ontext, therefore, plays an important role in young adults drinking behavior. Alcohol expectancies can influence how much social context impacts drinking behavior in the young adult population. More specifically, alcohol expectancies have been shown to mediate the relationship between a populations normative beliefs of alcohol use, including prevalence and accep tance, and individual alcohol use (FearnowKenny, Wyrick, Hansen, Dyreg & Beau, 2001; Perkins, 2002). This is problematic, since 7

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the young adult population overestimates the inci dence of peer alcohol use. It is estimated that 73-80% of individuals between the ages of 16 and 29 overestimate the occurrence of heavy and binge drinking by at least 10% (Kypri & Langley, 2003). These misperceptions of the frequency of heavy dr inking among peers not only remain stable across time, but also serve to increase dri nking frequency through desire to conform to these norms (Neighbors, Dillard, Lewis, Be rgstrom, & Neil, 2006). Furthermore, individuals most susceptible to social influences and to m odeling peer behavior are more likely to endorse more positive alcohol expectancies and greater frequency of alcohol use (Novak & Crawford, 2001; Wood, Rea d, Palfai & Stevenson, 2001). The connection between social influences and alcohol expectancies has not only been shown to best predict drinking behavior but it also can distinguish between problem and non-problem alcohol use. Together, social patterns and social alcohol expectancies can predict quantity and frequency levels of alcohol consumption that place individuals at risk for developing alcohol use disord ers (Moulton, Moulton, Whittington & Cosio, 2000). Researchers have attempted to redu ce problematic consumption patterns in the college setting by providing accurate informa tion about the prevalence of drinking among peers and the risks associated with heavy drin king. However, this intervention strategy has proven unsuccessful, especially among the h eaviest drinkers, who are most resistant to reducing perceptions of h eavy drinking on campus or changing their current drinking behaviors (Granfield, 2002). Therefore, social alcohol expect ancies are held steadfast in the young adult population and are the greatest predictors of this generations alcohol use and problematic drinking behavior. 8

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Appetitive-Motivational Model of Drinking In order to explain the mo tivation driving drinking beha vior in this population, an appetitive-motivational model of drinking characterizes alco hol consumption patterns for young adult drinkers. This model identifies eu phoric effects of alcohol cues as the driving force behind drinking behavior. Spec ifically, it is theori zed that alcohol cue exposure mimics pharmacological responses sim ilar to alcohol consum ption, particularly an increase in dopaminergic transmission, wh ich serve to motivate drinking behavior (Stewart, de Wit & Eikelboom, 1984). In laboratory settings, young adult social drinkers report higher arousal, more craving and positive affect when presented w ith alcohol cues than lighter-drinking peers (Johnson & Fromme, 1994). Specifi c characteristics of the alc ohol cue also impact urge to drink and appetitive response patterns among social drinkers. In particular, physiological response patterns to photographic cues of alcohol beverages in preparation for consumption are similar to reactivity dur ing pleasant affective cues (Mucha, Geier, Stuhlinger & Mundle, 2000). Pleasing cues alone, without alcoholic content, also indu ce motivations to consume alcohol. Social drinkers report incr eased desire to drink alcohol when viewing pleasant scenes and less desire to dri nk when viewing neutral and unpleasant cues (Mucha, Geier & Pauli, 1999). From the oppos ite direction, heavy drinkers particularly sensitive to rewards report increased urge to drink alcohol and greater positive affect in the presence of alcohol-related cues (Kam bouropolous & Staiger, 2001). These results, taken together, support the conditioned appetitive-motivational model of alcohol use among young drinkers. This suggests that positiv e affect and social alcohol expectancies 9

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are part of the same process and that both play a strong role in th e drinking patterns of young drinkers. Psychophysiological Measures Psychophysiology measurement might prove a powerful tool in identifying and assessing these reinforcing properties driving drinking be havior in the young-adult population. Psychophysiology measures, includi ng heart rate, skin conductance, and startle eyeblink reflex index automatic and affective processing of salient cues. In particular, these physiological measures have been used in psychopathology and addiction literature as indi ces for the emotional and arous ing nature of stimuli. Skin Conductance. Skin conductance responses (S CR) reflect changes in arousal while processing and attending to environmenta l stimuli. The expression of SCRs are dependent on the function of the amygdala, a brain structure key to the processing of emotional and arousing stimuli (Glascher & Adolphs, 2003). The S CR shares a strong correlation (0.81) with subjectiv e reports of arousal when vi ewing picture cues (Lang, Greenwald, Bradley & Hamm, 199 3). Both highly arousing unpleasant and pleasant cues elicit comparable levels of skin conductan ce activity, rendering this measure primarily sensitive to arousal and not valence-based pr ocessing. In addition, SCR levels increase during arousing tasks and decrea se during relaxation task performance (Nagai, Critchley, Featherstone, Trimble & Dolan, 2004). Cardiac Response. Cardiac activity reflects chan ges in both arousal and valence while processing and attending to stimuli (C acciopo, Klein, Berntson & Hatfield, 1993). Heart rate tends to decelerate, then accelerate, and finally decelerate back to baseline during cue exposure. The heart rate wave form is often i ndexed by four key variables: 10

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baseline, initial deceleration, acceleration, and secondary deceleration. The initial deceleratory cardiac response was first linke d with outward directed attention, or stimulus intake, while the acceleration phase was linked to the affective processing of the stimulus (Lacey & Lacey, 1970). For surviv al purposes, it benefits an organism to first orient to a potential threat, then allo w for emotional processing of the stimulus. During unpleasant stimuli, the initial decelerat ion is often potentiate d in the presence of unpleasant cues, compared to neutral and pleasant cues (Polomba, Angrilli & Mini, 1997). However, some studies show during pa rticularly aversive cues, particularly among phobic individuals, the heart wave pattern skips the initial orienting deceleration phase and immediately accelerates (Lumley & Melamed, 1992). The acceleratory phase of the heart rate wave form reflects the shift from the attentional processing to the emotional proce ssing of an external cue. Heart rate acceleration is associated with the intensity of the emotion, increasing more in the presence of more arousing cues (Witvliet & Vr ana, 1995). Therefore, heart rate patterns signal both the arousing and va lence properties of environmental stimuli. Researchers believe that cardiac activity reflects a comb ination of two competitive systems, the autonomic and cognitive processing of stimuli, and can be useful in determining both the affective and cognitive properties of cues (Lang, Bradley & Cuthbert, 1997). Startle Eyeblink Reflex. The acoustic startle eyeblink reflex has been used to measure human processing of the affective (appetitive vs. aversive) properties of environmental cues. A brief blast of noi se, presented during the exposure of an emotionally evocative cue, elicits an ey eblink magnitude response dependent on the valence of the stimuli. More specifically, when compared to a normal reaction, the startle 11

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eyeblink response is potentiated in the pr esence of aversive, unpleasant stimuli and inhibited when cues are pro cessed as pleasant an d appetitive (Lang, Bradley & Cuthbert, 1990). The eyeblink reflex serves as a defe nsive and protective response, which is enhanced when threatened and reduced when the organism feels safe. The startle eyeblink response, therefore, implicitly measures the affective propertie s of a stimulus. The latency between startling stimulus a nd the eyeblink reflex response is very short (average of 20 msec in humans), indicatin g a simple neural pathway (Davis, Walker & Lee, 1999; Davis, 1997). The proposed primary acoustic startle reflex pathway involves direct synapses on three main structures in the brainstem and spinal cord: cochlear root neurons in the auditory nerve; the nucleus reticularis pontis caudalis (PnC) at the base of the brain; and motorneurons in the facial motor nucleus (eyeblink reflex). Lesions to any of these structures lead to an absence in the acoustic startle response (Lee, Lopez, Meloni & Davis, 1996). The degree of acoustic startle reflex is modulated by a secondary neural pathway that is sensitive to affective cues in the envi ronment. Information from a visual stimulus converges onto nuclei in the central amygdala, which then project onto the PnC, the meeting point on the primary acoustic startl e pathway (Davis, 1997; Koch & Schnitzler, 1997). The amygdala is involved in the regula tion and perception of emotions such as fear. Therefore, in both animal and human st udies, the amplitude of the startle reflex has been shown to differentiate between pleasan t, neutral and unpleas ant stimuli (Bradley, Lang & Cuthbert, 1993; Schmid, Koch & Schnitzler, 1995; Cook, Hawk, Davis & Stevenson, 1991). Namely, pleasing stimu li produce inhibited startle reflex, and unpleasant and fearful stimuli enhances the st artle reflex. When the function of the 12

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amygdala is blocked via receptor antagonists or lesions, fear-poten tiation and pleasureattenuation of the startle is eliminated (Schauz & Koch, 2000). A startling stimulus pres ented early in the pict ure viewing sequence (250-350 ms) elicits a response magnitude and pattern that is distinguishable from a startling stimulus presented late in the picture vi ewing sequence (3-6 sec; Bradley, Cuthbert & Lang, 1993). Startle responses presented earlier exhibit a prepulse inhibition effect, in which eyeblink reflex magnitudes are smaller than those presented later in the pictureviewing sequence. The attention-orientat ion processing of the stimuli, presented immediately before the startling stimulus, directly impacts the magnitude of attention reserved for the startling stimuli. Specifi cally, more salient, provocative, and arousing picture cues elicit the lowest eyeblink magnit udes, regardless of affective properties. From a survival perspective, it is more a dvantageous to attend to more threatening (aversive) or pleasing (appetitive) cues th an a subsequent startle stimulus (Ohman & Mineka, 2001). Rather than immediate attentional and emotional processing of stimuli, later startle responses reflect more thoughtful consideration of the affective properties within visual content and the environmental contex t in which the stimuli is presented. In a typical laboratory environmen t, startle response magnitudes are often inhibited in the presence of pleasing, appeti tive cues and potentiated in the presence of unpleasant, aversive stimuli (Bradley, Moulder & Lang, 2005). Startle Reflex and Affective Cue Processing In addiction research, the startle reflex is often a ttenuated during pictures of alcohol consumption among alcoholics and dur ing pictures of smoking among smokers, 13

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suggesting an appetitive nature of the substance (Mucha, Geier, Stuhlinger, & Mundle, 2000; Mucha, Geier & Pauli, 1999 ). For the control individual, alcohol cues garner physiological and startle response magnitudes similar to neutral cues. However, alcohol cues are often processed as ar ousing and appetitive for the alcohol-dependent individual, resulting in increased heart rate and skin conductance and decreased startle eyeblink response. However, not all studies find startle inhibition during alc ohol pictures among alcohol-dependent individuals. For instance, in a recent study by Saladin and colleagues (2002), the authors investigated alcohol-depen dent individuals in different stages of abstinence. Each of these participants reporte d higher levels of urge to drink and greater salivation in the presence of alcohol cues than water cu es. However, the startle probe was potentiated in response to alcohol cues among those individuals early in abstinence, suggesting that alcohol cues are particularly aversive to th ese individuals, even in the presence of elevated craving and salivation. Saladin and colleagues propose that the alcohol cues, without a chance for consumption, either elicit a st ate of frustrative nonreward or a threat to abs tinence among early-abstinent alc oholics. These results are consistent with studies done on social dr inkers, in which availability of alcohol consumption increased subjective reports of craving and appetitive motivation, while the unavailability to consume alcohol heightened anxiety and aversive motivation (Kambouropoulos & Staiger, 2004). This woul d explain heightened aversive motivation coupled with increased craving a nd salivation in these individuals. Similar results were seen in a study conducted by Drobes and colleagues (2001), who examined the effects of food cues on f ood-deprived individuals. Startle response 14

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magnitudes elicited during food cues among normal eaters were consistent with magnitudes elicited during pleas ant, appetitive cues. Howe ver, among those individuals who had refrained from eating up to 24 hours pr ior to testing, food cues elicited increased heart rate and startle magnitudes, more similar to unpleasant cues. The authors hypothesized that this was due to a frustrative, nonreward state activat ed at the sight of food, which is processed as aversive for a fooddeprived individual. In a second part of the same study, Drobes and colleagues comp ared the effects of food cues on fooddeprived, binge eater and rest rained eater groups. The f ood-deprived and binge eater groups rated the food cues more pleasant, yet showed potentiated st artle and heart rate responses, similar to the food-deprived gr oup in the first study. Even though these individuals rate the food cues as more pl easant than the normal and restrained-eater groups, an aversive pattern of startle responding was elic ited, presumably due to frustration and aversive arousal. Research focusing on the processing of affective cues, separate from substancerelated cues, shows that individuals at risk for future alcohol use disorders display a response pattern distinctive from that of low -risk controls. Adult children of alcoholics not diagnosed with a current alcohol use disorder often display the same blunted startle eyeblink response in the pres ence of unpleasant stimuli (Miranda, Meyerson, Buchanon & Lovallo, 2002; Zimmerman, Spring, Wittc hen & Holsboer, 2004). In addition, alcoholics diagnosed with Anti-Social Pers onality Disorder (ASPD ), highly correlated with substance use disorder diagnoses, also display this blunted startle response to both pleasing and unpleasing stimuli, when compar ed to alcoholic subjects without ASPD (Miranda, Meyerson, Ryan & Lovallo, 2002). This phenomenon may suggest a 15

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fundamental difference in the processing of arousing and affective cues, separate from alcohol-related cues, between individuals at ri sk for alcohol use disorders and those who are not at risk. Preliminary Study In a preliminary study, we used the star tle eyeblink paradigm to analyze the relationship between alcohol expectancies, affective cues (unpleasant, neutral and pleasant), and alcohol-related cues among 55 co llege-aged drinkers (Drobes, Carter & Goldman, in prep). Specifically, this study hypothesized that college -aged drinkers with positive, arousing expectancies would respond to emotionally evocative cues similarly to individuals at higher risk for alcohol abuse and dependence (i.e inhibited startle response and increased autonomic activity in the pr esence of unpleasant cu es; Miranda, Myerson, Buchanon & Lovallo, 2002). Additionally, this study hypothesized that college-aged drinkers with positive arousing expectancies would respond to alcohol related cues with increased arousal and appetitive motivati on (i.e. increased autonomic activity and inhibited startle probe respons e), when compared to indivi duals with negative, sedating alcohol expectancies. Regarding affective cues, early startle ma gnitudes to unpleasant stimuli shared a positive and significant relationship with social, positive and arousing alcohol expectancies. Individu als with higher positive, arousing, and social alcohol expectancies exhibited a blunted early star tle response to unpleasant stimuli. This finding indicates that affective processing of av ersive stimuli might be modulat ed by risk for future alcohol use disorders, consistent with previous research. Results from this study revealed modest relationships betwee n positive, arousing, 16

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and social alcohol expectancies and appetitiv e startle response patte rns to alcohol-related cues. However, the alcohol-related cue se t was limited in number (10 slides), with pictures ranging from a simple beer with a neutral background to a complex photograph of individuals partying and dri nking from a keg of beer. This preliminary study serves as a foundation for comparing alcohol expectancies and drinking behavior with individual startle eyeblink response patterns during a ffective and alcohol-related cues. Specific Aims The purpose of the present study is to further examine the relationship between alcohol expectancies and affec tive processing of alcohol cues. Further, the goal of this study was to validate and explore the affective component to alcohol expectancy theory. Since startle eyeblink reflex is a direct, automatic measure of emotional modulation, it was thought to be especially useful in m easuring the affective component of alcohol expectancies driving drinking behavior in college-aged adults. Further, this study proposed that social alcohol e xpectations would be particular ly salient to the emotional modulation of alcohol reactiv ity in this population. This study compared how young-adult dri nkers process arousing and affective properties of social alcohol cues to neutral cues and alcohol cues without a social context. Of particular interest were the emotional motivations and reinforcing properties that make drinking in the young adult population a determinable end. The specific aim of this study was to compare psychophysiological reactivity to alcohol/social, alcohol/nonsocia l and neutral cues within social, young-adult drinkers. Further, this study examined the relations hip between positive, arousing, and social alcohol expectancies and psychophysiol ogical reactivity to alcohol/social, 17

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alcohol/nonsocial and neutral cues. The following hypotheses were tested: Hypothesis 1.a (primary): College-aged drinkers exhibi t inhibited early and late startle eyeblink reflex in the presence of alcohol/social cues when compared to neutral cues and alcohol/ nonsocial cues. Gender differences were explored. Hypothesis 1.b (secondary): College-aged drinkers exhi bit increased autonomic reactions (heart rate, skin conductance) in the presence of alcohol/social cues when compared to neutral cues and alcohol/ nonsocial cues. Gender differences were explored. Hypothesis 2 (secondary): Social, positive, and arous ing alcohol expectancies positively relate to startle re flex attenuation, cardiac activ ity and skin conductance in the presence of alcohol/social cues and share no relationship to startle reflex attenuation, cardiac activ ity and skin conductance in the presence of alcohol/nonsocial cues and neutral cues. 18

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Methods Participants Approximately eighty college students between the ages of 18 and 24 were recruited and screened from the University of South Florida U ndergraduate Psychology subject pool during the spring 2006 semester. All drinkers were included in the study with the following exceptions: individuals reporting drinking an average of 4 or more drinks per day (problematic, heavy drinkers) or complete abstinence (abstainers) in the month prior to screening. Based on the National Institute on Alcoholism and Alcohol Abuse (NIAAA) definitions of drinker types, heavier college-aged drinkers meet binge drinking criteria: an average c onsumption level of 5 or more standard alcohol drinks (12 oz. beer, 5 oz. wine, 1.5 oz. spirits) on 4 or more occasions per month for men, or 4 or more standard alcohol drinks on 4 or more occasions for women (NIH, 2004). Lighter and heavier drinkers were oversampled in order to maximize the ra nge of drinker types included in the study. Specifically, equal numbe rs of light drinkers (reporting less than 12 drinks per month and no more than 3 dri nks per occasion), heavy drinkers (meeting minimum criteria for binge drinking), and mode rate drinkers (all other drinkers in between heavy and light) were recruited in to the study. In addition to the drinking criteria described above, part icipants were required to ha ve normal hearing and vision (based on self-report). In order to analyze potential differences in alcohol expectancies and cue reactivity between genders, an effort was made to in clude equal numbers of males and females in 19

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the study. While some previous studies show a gender difference within alcohol expectancies, other studies suggest minimal gender differences within alcohol expectancies (e.g. Des Rosiers, Noll, & Go ldman, 2002; Weinberger, Darkes, Del Boca, & Goldman, 2003.). There is evidence th at males and females endorse alcohol expectancies similarly, but that the sema ntic meaning behind expectancy words may differ between genders. Since the literature is unclear, this study looked into potential gender differences regarding alcohol expectancies and cue reactivity. Sample Description After screening for eligibility requirements, the final sample included fifty-eight college-aged students, with a mean age of 20.1 years (SD = 1.50). Fifty-five individuals were currently enrolled at the University of South Florida as full-time, undergraduate, college students, and three individuals were recent college graduate s, referred by college friends in the surrounding area. The sample was reflective of Tampa Bay Area demographics: 87.9 % Caucasian, 6.9% Black or African American, 5.2% Asian, and 13.8% Hispanic or Latino. Tw enty-seven males and 31 females were enrolled in the study, and gender groups did not differ in age [ t (56,1) = -.55, p > .05], race [ 2 (2, N = 58) = 4.10, p > .05], or ethnicity [ 2 (1, N = 58) = .04, p > .05]. Upon completion of the assessment por tion of the study, one participant was excluded due to heavy levels of reported drinking, rendering him no longer eligible (mean Total Drinking = 518 total drinks consum ed in the previous month; mean Average Drinking = 21.58 drinks per drinking occasion). The exclusion of this participant did not impact the final results or conclusions ma de from this study. After excluding this individual, fifty-seven particip ants (26 males) remained. 20

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Procedure Individuals interested in participatin g in this study were screened over the telephone to determine e ligibility status. Elig ible participants atte nded a one-time, twohour long laboratory session. Upon arrival to th e lab setting, participants read and signed an approved Informed Consent document. Laboratory picture viewing. Following Informed Consent participants were asked to sit in a comfortable chai r, and electrodes measuring st artle eyeblink response, skin conductance and heart rate were applied to the arms, hand, and face. Two large (8 mm) Beckman-type electrodes we re placed between the participants wrist and elbows to measure cardiac activity. One grounding electrod e was placed on the participants left arm between the previously a pplied electrode and the elbow. Two large electrodes were applied to the palm of th e participants non-dominant ha nd, directly underneath the smallest finger, as a measure of skin conductance response. Finally, two small (4 mm) Beckman-type electrodes were placed just be neath the lower eyelid of the left eye to record the contraction of th e orbicularis oculi muscle, in response to acoustic startle stimuli. Impedance levels were checked and kept below 5 K Ohms to ensure accurate startle measurement. Once the electrode a pplication process was complete, andiometric headphones were placed over th e participants ears. Following a five-minute acclimation pe riod, the researcher presented the participant with two neutral, sample pictures. Participants were then left alone in the room while watching a randomized sequence of 36 digitized pictures, with 12 from each of the three categories: neutral, alcohol/social (images of alcohol in a social context), and alcohol/nonsocial (images of alcohol in a nonsocial context). Neutral images were 21

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selected from the International Affective Pict ure System and consisted of images such as hairdryers and books (IAPS; CSEA, 2002). The alcohol-related pictures were collected from advertisements and the internet. For the purpose of consistency, only beer was shown in the alcohol-related pictures, sin ce beer is the most commonly consumed alcoholic beverage among the college-aged population (Wechsler, Kuo, Lee & Dowdell, 2000). Alcohol/nonsocial cues consisted of beer images with a neutral background, while alcohol/social cues consisted of beer images in the foreground and social gatherings displayed in the background. Picture cues were shown on a large (20-inch) computer monitor placed on a table directly in front of the participant using the following se quence: (1) 2-second baseline; (2) 6-second picture viewing; (3) 20 seconds to rate valence, arousal and craving using the Self-Assessment Manikin (L ang, 1980); (4) variable (15second average) inter-trial intervals prior to presentation of the next pict ure. The startle eyeblink reflex was elicited by a binaural acoustic stimulus (50 msec white noise, 100dB, instantaneous rise time) during ten of the twelve images in each category, and during seven of the inter-trial intervals. For five pictures within each cue category, the startle eyeblink was elicited early in the picture view ing sequence (250-350 ms), in order to gauge immediate attentional processing of the picture cue. For five different picture cu es in each category, acoustic startle eyeblink was elicited late in the pict ure viewing sequence (4-5.5 seconds), in order to gauge c ontextual affective processing and motivational properties of the picture cue. Heart rate and skin conductance were meas ured continuously throughout each picture-viewing interval. Subjective Ratings. Participant affective and craving ratings were assessed 22

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immediately following the presentation of each i ndividual picture cue. Valence, Arousal, and Dominance ratings were obtained using a computeri zed version of the selfassessment manikin (SAM; Bradley & Lang, 1 994). SAM, a cartoon of a human figure, was presented on the computer monitor, a nd participants were asked to manipulate SAMs figure representing each of the three affective dimensions. For the valence dimension, SAMs facial expressions range from happy/smiling, to neutral/unaffected, to unhappy/frowning. For the arousal dimens ion, SAMs figure can range from an excited/jumpy to relaxed/bored. For the dominance dimension, SAMs image can be transformed from close-up/large to far-away/sm all. During two initial practice trials, the extreme end of each affective dimension was fu rther described using several standardized adjectives. Craving ratings were assessed w ith the prompt My crav ing to drink alcohol right now is, with responses placed on a c ontinuous line ranging from Not at all to Extremely. All subjective ratings were coded on a scale from 0 to 20. Questionnaire and Assessment Portion. Upon completion of picture viewing, electrodes and headphones were removed. Participants completed several brief questionnaires and interviews, measuring dem ographic information, alcohol use data and expectancy levels. Breathalyzer. Each participant was asked to blow a breath sample into the breathalyzer to ensure sobriety at the time of the experiment No participant blew a blood alcohol level (BAC) higher than 0.00. The br eathalyzer was presented at the completion of the study, so that the part icipant was not primed on the nature of the experiment and did not focus on their own drinking behavior during the experiment. Debriefing Upon completion of questionnaires and interviews, participants were 23

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given further information regarding the pur pose/goal of the study and the opportunity to ask questions. Participants were awarded 3 extra credit points to ward an undergraduate psychology course for their time. Measures Demographic form. This form provided information regarding age, gender, ethnicity, race, education, marital status, occupation, and health status. Alcohol Expectancy Questionnaire (AEQ). This measure includes 68 statements in a True/False format about the various e ffects of alcohol, includi ng social, physical and sedating domains (Brown, Goldman, Inn & Anderson, 1980; Brown, Christiansen & Goldman, 1987; Goldman, Greenbaum & Darkes, 1997). Expectancy items on the AEQ correlate with alcohol consum ption, alcohol abuse and beha vior while drinking, with a mean reliability of 0.84. Factor analysis re vealed 6 separate subscales within this measure, including the following: global posi tive changes; sexual enhancement; physical and social pleasure; increased social assert iveness; relaxation and tension reduction; and arousal and aggression. The relative levels on each subscale were analyzed to provide further information into the type of alcohol expectancies endorsed by each participant. Special interest was given to the 9-item soci al/ physical pleasure subscale responses and how they relate to participant reactions to neutral and alcohol-related images during cue reactivity. Alcohol Expectancy MultiAxial Assessment (AEMax). This measure utilizes a comprehensive list of expectancy terms with the intent to capture the entire range of alcohol expectancies (Goldman & Darkes, 2004) The terms were generated in a study where college students and alcoholics co mpleted the open-ended sentence alcohol 24

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makes one, (Rather, Goldman, Roehrich & Brannick, 1992). After item selection, a total of 132 items were selected to represent a multidimensional network of alcohol expectancies, falling in a ci rcular pattern around arousal and valence axes. Factor analysis on these items revealed eight distinct first-order expectancy terms including the following: horny; social; egotistical; attractiv e; sick; sleepy; woozy; and danger. The shortened version of this measure, employe d in this study, includes 24 expectancy items, with three from each of the eight first order f actors. Participants were asked how often they believe the item best completes the sentence alcohol makes one, using a 7-point Likert Scale ranging from 0 = never to 6 = always. The measure is proven both reliable and valid and is an effective measure of the positive-negative and arousing-sedating dimensions of alcohol expectancies. Zuckerman-Kuhlman Personality Questionnaire Form III (ZKPQ III). The full version of the ZKPQ III consists of 99 True-False items, designed to measure five dimensions of personality: impulsive-sensati on seeking; neuroticism-anxiety; aggressionhostility; activity; and sociability (Zuckerman, Kuhlman, Joireman, Teta & Kraft, 1993). The reliability coefficients for the subscales range from 0.72 to 0.86. This study employed the 19-item impulsivity/sensationseeking subscale of the ZKPQ III, which measures more specifically an individuals risk-taking be havior and need for novel and risky experiences. Alcohol expectancies ha ve been shown to mediate the relationship between sensation seeking behavior and alcoho l use, and individuals who score higher on sensation seeking scales are more likely to engage in risky drinking behavior (Henderson, Goldman, Coovert & Carnevalla, 1994; Katz, Fromme, DAmico, 2000). Therefore, this scale is usefeul in evaluating the relations hip between alcohol expectancies, sensation25

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seeking and drinking behavior in college-aged individuals. Family Grid. The National Institute of Alcoho lism and Alcohol Abuse identified family history for alcohol problems as one of the primary risk factors for developing alcoholism and alcohol related problems (Gra nt, 2003). This family history interview measures the density of first and second degree biological relatives havi ng in the past or currently having significant dr inking problems. The family grid lists the following as signs of a drinking problem: legal problems (drunk driving violations); health problems (cirrhosis of the liver, alcohol withdraw al); relationship problems (objections about drinking from family members); work or school problems (absenteeism, poor performance due to alcohol use); and actual treatment (d etox, rehab, AA meetings). These data were used to examine whether family history is related to alcohol cue reactivity and alcohol expectancies in the college-aged population. Individuals were identified as 1 st -Degree Family History positive if one or more biological parents met criteria for alcohol use disorder, and 2 nd -Degree Family History pos itive if at least one biological parent and at leas t one biological grandparent met criteria for alcohol use disorder. Otherwise, the participant was identified as Fam ily History negative for alcohol use disorders. 30-Day Timeline Follow-Back (TLFB). This calendar-based interview was used to measure participant alcohol use (quantit y and frequency) in the month prior to assessment (Sobell & Sobell, 1992). Participan ts were asked to identify the amount of alcohol consumed per drinking day in the prev ious month, with drinks equaling standard alcoholic beverage amounts. While quantity and frequency measures are sensitive to time of year peaks and lulls in drinking, su ch as holidays and exam periods (Del Boca, 26

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Darkes, Greenbaum & Goldman, 2004), this interv iew is primarily used in this study to measure a participants typical drinking pattern. At the conclusion of the interview, participants were asked whether the calendar re presents a typical drinking month. If the month was not considered typical, particip ants were asked whether the prior month displayed an increase or decrease in their typical dr inking pattern. Data Processing For each participant, cue reactivity data were summed over trials within each picture category, in order to find an averag e response for each type of cue presented. Startle reflex data were stored offline, and each response was manually scored for peak amplitude (the maximum eyeblink elicited) an d onset latency (the length of time from acoustic startle probe onset to response initiation) us ing VPM software (Cook, 1999). Within each trial, startle responses were sc ored if peak amplitude was greater than 15 A/D units and if the onset fe ll between 20 msec and 80 msec after the tone was presented. Otherwise, startle data for that trial were c onsidered either missing or zero. Participants were excluded from the analyses if more than 50 percent of startle magnitudes within any cue type were missing. Ultimately, raw startle magnitude data were transformed to T scores to minimize variability across participants. Heart rate and skin conductance data were stored for offline editing and averaging. Of particular in terest within cardiac activity was the initial deceleration magnitude (compared to baseline), peak acceleration magnitude (compared to baseline), and the difference between deceleration and acceleration variables. For skin conductance, peak magnitude and average magnitude between 2-6 seconds following picture onset were scored. 27

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Results Descriptive Statistics for Dependent Variables Drinking Behavior. Drinking variables, including To tal Drinking (total standard alcoholic beverages consumed in the 30 days prior to assessment) and Average Drinking (average number of standard alcoholic beve rages consumed per drinking occasion in the 30 days prior to assessment) were included as indicators of risk for future alcohol use disorders (Table 1). College-aged individuals in this sample reported drinking an average of 31.80 (SD = 37.27) alcoholic beverages pe r month and 4.49 (SD = 2.62) alcoholic beverages per drinking occasion. Sin ce Total Drinking displayed a non-normal distribution, as indicated by el evated skewness and kurtosis values, this variable was subjected to a natural log transformation, whic h was used in all subsequent analyses. Sensation Seeking. S ensation-Seeking was also included as a measure of risk for future alcohol use disorders, with higher sc ores indicating higher levels of sensationseeking and impulsive behavior (Table 1). The average Sensation-Seeking score was 10.11 (SD = 3.51). Table 1 Descriptive Statistics for Drinki ng Behavior and Sensation Seeking N Min Max Mean SD Skewness Kurtosis Total Drinking 57 0 179 31.80 37.27 1.91 3.75 ln(Total Drinking +1) 57 0 5.19 2.92 1.12 -.20 .21 Average Drinking 57 0 11.90 4.49 2.62 .86 .54 Sensation-Seeking 57 2 16 10.11 3.51 -.52 -.58 28

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Family History. Family History for problems with alcoholism was included in this study as an indicator of biological risk for future alcohol use disorders. Approximately 75% of college-aged individual s in this sample were identified as Negative for Family History of alcohol use disorders (Table 2). Fourteen percent met criteria for 1 st Degree Family History Positive for alcoholism, and approximately 10 percent met criteria for 2 nd Degree Family History Positive for alcohol use disorders. Table 2 Family History for Alcohol Use Disorders Frequency Percent FH Negative 43 75.4 1 st FH Positive 8 14.0 2 nd FH Positive 6 10.5 Descriptive Statistics for Alcohol Expectancy Measures The college-aged drinkers included in this sample exhibited a wide range of alcohol expectancies, as measured by the Alcohol Expectancy Questionnaire (AEQ) and the Alcohol Expectancy Multi-Axial Assessm ent (AEMax; Table 3). Subscales of the AEQ included Global Positive, Sexual Enhancement, Social and Physical Pleasure, Social Assertion, Tension Re duction, and Aggression/Arousal. The AEMax included three second-order factors (Positive/Arousi ng, Negative, and Sedating) and eight firstorder factor subscales (Social, Woozy, Sic k, Egotistical, Horny, Attractive, Sleepy, and Dangerous). Individual subscale means were consistent with college-aged populations, showing higher than average social, positive and arousing subscale means. 29

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Table 3 Descriptive Statistics for Alcohol Expectancy Scales N Min Max Mean SD Skewness Kurtosis AEQ Global Positive 57 1 17 7.88 4.79 .51 -.95 Sexual Enhancement 57 0 7 2.23 2.08 .70 -.61 Social/Physical Pleasure 57 3 9 7.16 1.51 -.70 -.18 Social Assertion 57 0 10 7.04 2.76 -1.05 .54 Tension Reduction 57 1 9 5.93 2.09 -.60 -.07 Aggression/Arousal 57 0 9 4.70 2.15 -.15 -.63 AEMax Positive/Arousing 57 15 54 32.79 7.15 -.10 .73 Negative 57 0 30 18.28 6.20 -.58 .59 Sedating 57 14 52 30.25 7.63 .01 -.02 Social 57 7 18 13.93 2.58 -.51 .16 Sick 57 2 18 9.12 3.26 .06 .27 Woozy 57 4 16 10.68 2.73 -.31 -.69 Egotistical 57 0 15 10.14 3.14 -1.04 1.28 Horny 57 4 18 11.21 2.84 .15 -.02 Attractive 57 0 18 7.65 3.82 -.29 .11 Sleepy 57 3 18 10.44 3.30 .03 .01 Dangerous 57 0 17 8.14 4.19 -.02 -.62 Relationship between Alcohol Exp ectancies and Dependent Variables Several alcohol expectancy subscales we re significantly correlated with drinking and sensation-seeking variables (Table 4). Most positive, arousing, and social expectancy subscales were positively and significantly relate d to total drinking, average drinking, and sensation-seeking. In contrast, negative and se dating expectancies tended to be negatively correlated with total drinking, average drinking, and sensation-seeking variables. 30

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Table 4 Zero-Order Correlations between Alcohol Expectancies and Risk Variables Ln(Total Drinking+1) Average Drinking Sensation Seeking AEQ Global Positive .41** .33* .34* Sexual Enhancement .40** .26* .35** Social/Physical Pleasure .19 .16 .31* Social Assertion .35** .26* .00 Tension Reduction .44** .42** .37** Aggression/Arousal .28* .15 .35** AEMax Positive/Arousing .18 .12 .03 Negative .13 -.16 .24 Sedating -.33* -.32* .01 Social .03 .06 -.03 Sick -.28* -.38** .01 Woozy -.28* -.26 .02 Egotistical .33* -.01 .23 Horny -.05 -.02 .05 Attractive .35** .20 .03 Sleepy -.25 -.16 -.01 Dangerous -.06 -.23 .18 p < .05, ** p < .01 A series of independent-samples t-tests we re conducted to determine if there were mean differences in alcohol expectancy subs cales due to Family History status. There were no significant differences in expectanci es when comparing Family History Negative and both 1 st Degree and 2 nd Degree Family History Positive groups ( ps > .21). After collapsing 1 st and 2 nd Degree Positive groups, again there were no significant differences between Family History Negative and Positive groups ( ps > .24). Therefore, individual alcohol expectancies were not related to family history stat us for alcohol use disorders. 31

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The Relationship between Gender and Independent Variables A series of one-way analysis of vari ance (ANOVA) comparing means for alcohol expectancies, sensation seek ing, and Total Drinking yielde d no significant differences due to gender (ps > .21). In addition, chi-square comparisons between gender and family history revealed no significant differences (ps > .50). However, males drank significantly more alcoholic beverages per drinking occasion (Average Drinking = 5.70, SD = 2.86) compared to females (Average Drinking = 3.49, SD = 1.92; F (1,56) = 12.0, p < .01). The data shows that females spread their drinking out acr oss the months more than males, who drink more than females per drinking occasion. Therefore, among the risk variables, males and females shared similar alcohol expectancies, sensation seeking, family history, and total drinking per month, but they diffe red in average drinks per occasion. Subjective Cue Ratings Descriptive Statistics. The means for valence, arousal, and craving ratings across cue types displayed a linear trend, with neut ral cues rated the lowest, alcohol-nonsocial cues in the middle, and alcohol-social cues the highest (Table 5, Figure 1). Dominance ratings were lowest for alcohol-social cues and highest for alcohol-nonsocial cues. 32

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Table 5 Descriptive Statistics for Subjective Cue Ratings N Min Max Mean SD Valence Neutral 57 6.36 14.21 10.65 1.69 Alcohol-NS 57 6.00 17.58 11.61 2.57 Alcohol-S 57 6.67 17.92 12.35 2.63 Arousal Neutral 57 .21 11.86 6.33 3.00 Alcohol-NS 57 .00 18.08 9.35 3.93 Alcohol-S 57 .75 17.42 10.25 3.27 Dominance Neutral 57 4.50 20.00 13.15 3.40 Alcohol-NS 57 6.75 20.00 13.46 3.74 Alcohol-S 57 5.25 20.00 12.48 3.56 Craving Neutral 57 .00 10.50 2.67 3.05 Alcohol-NS 57 .00 18.42 6.90 5.77 Alcohol-S 57 .00 16.50 7.18 5.33 *Note: All ratings were recorded on a 0-20 scale. A series of repeated measures ANOVAs we re conducted to determine whether the differences between ratings within cue types were significant. Th ere was a significant, increasing trend for Valence [ F linear(1,56) = 16.20, p < .01, = .72], Arousal [ F linear(1,56) = 56.87, p < .01, = .71], and Craving [ F linear(1,56) = 56.21, p < .01, = .67] ratings, with Neutral cues rated the lowest and Alcohol-Social cues rated the highest. Therefore, participants rated Alcohol-Soci al cues as the more pleasing, arousing and craving-inducing than Alcohol-N onsocial cues and Neutral cu es, with Neutral rated the least. Differences between cue types for do minance ratings were not significant. All paired t-test comparisons were significant ( t s > 2.3, ps < .03), with the exception of three: Craving ratings for Alc ohol-Social cues did not significantly differ from craving ratings for Alcohol-Nonsocial cues ( t = -1.13, p = .26), although craving ratings for both alcohol-related cue type was significantly great er than craving ratings for 33

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Neutral cues; Dominance ratings for both Alcohol-Nonsocial a nd Alcohol-Social cue types did not significantly differ from dominance ratings for Neutral cues ( t = -.61, p = .55; t = 1.53, p = .13; respectively), although domin ance ratings for Alcohol-Nonsocial cues were significantly higher than Alcohol-S ocial cues. Therefore, participants found both Alcohol-related cue types to be significantly more craving-inducing than Neutral cues, but the craving ratings be tween the two Alcohol cue types did not differ as a factor of social context. In addition, participan ts felt more in control, as reflected in dominance ratings, during alc ohol cues without a social context when compared to alcohol cues within a social context. The Relationship between Gender and Subjective Ratings. In order to test for gender effects on subjective rati ngs of alcohol-related cues, a series of repeated measures ANOVAs were completed with gender as th e between-subjects factor and cue type (neutral, alcohol/social, and alcohol/nonsocial) as the rep eated measure. Significant differences were found between males a nd females within Arousal [F(1,56) = 3.66, p < .05, = .72] and Craving [F(1,56) = 4.17, p < .01, = .68] ratings, as shown in Figures 2 and 3, but not for Valence and Dominance ratin gs. Therefore, the patterns of arousing and craving ratings differed as a function of gender, with what appears to be males finding alcohol-related cues as more arous ing and craving-inducing than females. A series of independent ttests were conducted to fi nd specific differences in ratings due to gender. Compared to Neutral cues, males rated Alcohol -Nonsocial cues as significantly more positive, arousing, and craving-inducing than female college-aged participants (Valence: t (56,1) = -2.13, p < .05; Arousal: t (56,1) = -2.23, p < .05; Craving: t (56,1) = -2.30, p < .05). Males also found Alcohol-Soc ial cues as significantly more 34

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craving-inducing than females ( t (56,1) = -2.17, p < .05). There were no differences in dominance ratings between Alcohol-Nonsocial cues to Neutral cues due to gender. In addition, there were no significant differences between dominance, arousal, and valence ratings for Neutral or Alcohol-Social cue type s due to gender. Overall, however, males rated alcohol-related cues as significantly more positive, arousing, and craving-inducing than females. The Relationship between Subjective Ratings and Alcohol Expectancies. Correlations between subjective ratings and alcohol expectan cy subscales are presented in Tables 6-A and 6-B. Valence ratings for alcohol-related cues were significantly correlated with AEQ Global Positive, Sexual Enhancement, Social Assertion, Tension Reduction, and Aggression/Arousal subscales. Arousal Ratings for al cohol-related cues were significantly correlated with AEQ Global Positive, Sexual Enhancement, Social/Physical Pleasure, Tension Reducti on, and Aggression/Arous al subscales and AEMax Global Positive, Egotistical, and Attr active subscales. Dominance ratings of alcohol-related cues were not si gnificantly correlated with alcohol expectancies, with one exception: Dominance ratings in the presen ce of Alcohol-Social cues significantly and negatively correlated with AEMax Social expectancies ( r = -.29, p < .05). Craving ratings to alcohol-related cu es were significantly correlate d with AEQ Global Positive, Social/Physical Pleasure, Social Assertion subscales and AEMax Global Positive and Attractive subscales. Se veral ratings for neutral cues were significantly related to alcohol expectancy subscales; however, the patte rns behind these relationships were not consistent. Overall, subjective ratings of Alcohol-Nonsocial and Alcohol-Social cues were positively and significan tly correlated to most pos itive subscales of alcohol 35

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expectancy measures, as was expected. Table 6-A Zero-Order Correlations be tween Subjective Ratings and Alcohol Expectancies Valence Arousal Neutral A-Non A-Soc Neutral A-Non A-Soc AEQ Global Positive -.39** .37** .30* -.08 .48** .33* Sexual Enhancement -.19 .24 .26* -.04 .25 .24 Social/Physical Pleasure -.22 .24 .07 .20 .39** .16 Social Assertion -.03 .30* .27* .03 .40** .32* Tension Reduction -.25 .18 .27* -.05 .36** .32* Aggression/Arousal -.07 .29* .30* -.09 .34** .25 AEMax Positive/Arousing -.22 .10 .02 -.07 .32* .11 Negative -.01 .23 .17 .05 .21 .08 Sedating .11 -.14 -.11 .18 -.13 -.07 Social -.10 -.05 -.23 -.05 .14 -.08 Woozy .17 -.08 -.04 .06 -.20 -.16 Sick .03 -.01 -.05 .21 .04 .00 Egotistical -.03 .22 .15 -.15 .34** .11 Horny -.07 .02 .02 .07 .19 .08 Attractive -.30* .20 .17 -.15 .37** .20 Sleepy .08 -.24 -.17 .18 -.13 .00 Dangerous .01 .19 .14 .18 .05 .03 p < .05, ** p < .01 36

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Table 6-B Zero-Order Correlations be tween Subjective Ratings and Alcohol Expectancies Dominance Craving Neutral A-Non A-Soc Neutral A-Non A-Soc AEQ Global Positive -.32* -.15 -.20 .33* .49** .46** Sexual Enhancement -.27* -.06 .03 .08 .17 .18 Social/Physical Pleasure -.25 -.13 -.15 .24 .34** .29* Social Assertion -.20 -.09 -.22 .32* .42** .46** Tension Reduction -.26 -.25 -.15 .21 .25 .32* Aggression/Arousal -.16 -.17 -.22 .02 .16 .17 AEMax Positive/Arousing -.13 -.08 -.18 .23 .30* .30* Negative .15 -.11 .00 .16 .18 .12 Sedating .27* .00 .11 -.10 -.12 -.0 Social -.17 -.07 -.29* .17 .12 .04 Woozy .32* .13 .20 -.11 -.16 -.11 Sick .26* .10 .10 .00 .06 .05 Egotistical .16 -.10 .01 .21 .21 .14 Horny .04 .02 .05 .17 .20 .20 Attractive -.15 -.11 -.18 .19 .34** .39** Sleepy .10 -.20 -.02 -.11 -.16 -.14 Dangerous .10 -.09 -.01 .08 .11 .07 p < .05, ** p < .01 Cardiac Reactivity Descriptive Statistics for Cardiac Reactivity. Average heart rate patterns across the three cue types are presented in Figure 4. The wave pattern includes baseline, D1 (initial deceleration phase), A1 (peak accelera tion phase), and D2 (s econdary deceleration phase) within the 6-second picture-viewing period for each cue type. Mean magnitudes for D1, A1, and D2, compared to baseline magnitude, and the difference between the peak acceleration and deceleration phase of cardiac activity (A1-D1) are presented in Table 7. 37

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Table 7 Descriptive Statistics for Cardiac Reactivity Cue Type N Min Max Mean SD D1 Neutral 58 -9.72 -.41 -4.26 1.78 Alcohol-Nonsocial 58 -8.88 -.30 -3.79 1.94 Alcohol-Social 58 -8.99 -.45 -3.80 1.89 A1 Neutral 58 -.98 5.86 2.64 1.84 Alcohol-Nonsocial 58 -.88 9.13 3.00 2.12 Alcohol-Social 58 -1.59 10.78 2.76 2.41 D2 Neutral 58 -9.11 1.69 -3.74 2.33 Alcohol-Nonsocial 58 -8.65 1.05 -3.38 2.26 Alcohol-Social 58 -9.52 3.77 -3.60 2.47 A1-D1 Neutral 58 .72 14.98 6.90 2.34 Alcohol-Nonsocial 58 .89 15.03 6.79 2.40 Alcohol-Social 58 .75 11.38 6.56 2.25 A series of repeated measures ANOVAs were conducted to determine if cardiac response magnitudes (D1, A1, D2, A1-D1) differed within subjects an d across cue types. No significant differences were found among A1, D2, and A1-D1 magnitudes. However, significant differences between cue types in D1 magnitudes did appear within subjects, with greatest initial cardiac deceleration o ccurring in neutral cues when compared to alcohol-related cues (F = 4.04, p < .05, = .99). A series of pair ed sample t-tests were performed to test the significance in the diffe rences in initial decel eration (D1) within subjects. For the initial deceleration phase, there was significantly less cardiac deceleration for Alcohol-Social relative to Neutral [ t (57) = -2.01, p < .05], and there was a trend for response magnitudes to Alcohol-Nonsocial cues to be lower than Neutral [ t (57) = -1.91, p = 0.06]. Since greater initial cardi ac deceleration is often associated with cues displaying threat, then participants responded to alcohol-related cues as significantly less threatening (or more appetitive) than neutral cues. 38

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The Relationship between Cardiac Ac tivity and Alcohol Expectancies. Mean magnitudes of the initial deceleration phase (D1) of cardiac activity during AlcoholNonsocial cues were significantly, positively correlated to Sexual Enhancement and negatively correlated to Sedati ng, Woozy, and Dangerous alcohol expectancies (Table 8). No significant relationships were found betw een alcohol expectanci es and the initial deceleration phase during Neutral and Alc ohol-Social cue presentation. In addition, alcohol expectancies were not significantly related to the acceleration phase (A1), the difference variable (A1-D1), or the secondary deceleration (D2) in cardiac activity. Table 8 Zero-Order Correlations be tween Initial Card iac Deceleration (D1) and Alcohol Expectancies D1 Neutral A-Non A-Soc AEQ Global Positive -.02 .16 -.08 Sexual Enhancement .01 .26* .05 Social/Physical Pleasure .03 .17 .03 Social Assertion -.07 .09 -.05 Tension Reduction .06 .03 .01 Aggression/Arousal .14 .10 .04 AEMax Positive/Arousing .15 .17 .02 Negative -.19 -.17 -.01 Sedating .07 -.32* -.11 Social .23 .23 .02 Woozy -.02 -.37** -.08 Sick .08 -.20 -.11 Egotistical -.09 .02 .10 Horny .05 .04 -.09 Attractive .09 .14 .10 Sleepy .11 -.22 -.08 Dangerous -.21 -.27* -.10 p < .05, ** p < .01 39

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The Relationship between Cardiac Activity and Risk Variables. Bivariate correlations between drinking va riables, sensation seeking, a nd cardiac activity variables yielded only a significant pos itive relationship between Tota l Drinking and D1 magnitude during Alcohol-Nonsocial cues ( r = .28, p < .05). These data s uggest that individuals who drink more alcoholic beverages per month respond to alcohol cues as less threatening (less initial cardiac deceleration) than individuals who drink less per month. In addition, a series of rep eated measures ANOVAs, with cue type as the repeated measure, resulted in no significant differences in D1, A1, D2, or A1-D1 means due to gender or family history status Overall, risk variables we re not significantly associated with cardiac activity, with the ex ception of total drinking per month. Skin Conductance Descriptive Statistics for Skin Conductance Reactivity. Descriptive statistics for skin conductance reactivity, including aver age magnitude (Mean), peak magnitude (Peak), and the average difference between peak magnitude and baseline (Diff) are presented in Table 9. Due to increased skew ness and kurtosis values across all variables of interest, skin conductance data was transf ormed in a linear natural log transformation and presented in Table 10. 40

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Table 9 Descriptive Statistics for Skin Conductance Reactivity Cue Type N Min Max Mean SD Skewness Kurtosis Mean Neutral 58 -1.08 .90 .07 .27 -.61 6.58 Alcohol-Nonsocial 58 -.78 .44 -.04 .20 -1.31 5.60 Alcohol-Social 58 -.41 .72 .03 .20 .67 2.77 Peak Neutral 58 -.61 1.55 .25 .40 1.48 2.73 Alcohol-Nonsocial 58 -.39 .85 .11 .24 1.37 2.23 Alcohol-Social 58 -.11 1.22 .18 .25 1.96 5.59 Diff Neutral 58 -.28 1.96 .29 .43 1.98 4.27 Alcohol-Nonsocial 58 -.05 .99 .18 .27 1.57 1.58 Alcohol-Social 58 -.05 1.29 .22 .26 1.83 4.60 *Note: Skin Conductance values expressed in microsiemens ( S) Table 10 Descriptive Statistics for Transf ormed Skin Conductance Reactivity Cue Type N Min Max Mean SD Mean Neutral 58 -.33 .64 .07 .19 Alcohol-Nonsocial 58 -1.53 .36 -.07 .29 Alcohol-Social 58 -.53 .54 .01 .19 Peak Neutral 58 -.93 .93 .17 .30 Alcohol-Nonsocial 58 -.49 .61 .08 .20 Alcohol-Social 58 -.12 .80 .15 .19 Diff Neutral 58 -.33 1.08 .21 .28 Alcohol-Nonsocial 58 -.05 .69 .14 .20 Alcohol-Social 58 -.05 .83 .18 .19 A series of paired sample t-tests were performed to test the significance in the differences of mean skin conductance magnit udes across cue types. The average skin conductance magnitude elicited during Alcohol -Nonsocial cues was significantly lower than Neutral cues [ t (57) = -3.54, p < .01] and Alcohol-Social cues [ t (57) = -2.36, p < .05]. The peak skin conductance magnitude elic ited during Alcohol-Nonsocial cues was significantly lower than Neutral cues [ t (57) = -2.55, p < .05] and Alcohol-Social cues 41

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[ t (57) = -2.72, p < .01]. The difference between peak magnitude and baseline elicited during Alcohol-Nonsocial cues was signi ficantly lower than Neutral cues [ t (57) = -3.03, p < .01] and Alcohol-Social cues [ t (57) = -2.24, p < .05]. Differences between AlcoholSocial and Neutral cues for each skin c onductance variable were not statistically significant. Overall, Alcohol -Social cues and Neutral cues elicited significantly greater skin conductance responses than Alcohol-Nons ocial cues, implying that both AlcoholSocial cues and Neutral cues were more arousing to participants than the AlcoholNonsocial cues. The Relationship between Skin Con ductance and Alcohol Expectancies Skin conductance peak, average, and difference ma gnitudes during Neutral and Alcohol-Social cues were not significantly correlated to alc ohol expectancies. Ho wever, during AlcoholNonsocial cues, the AEMax social subscale wa s significantly and posit ively correlated to the average (r = .29, p < .05), peak (r = .32, p < .05), and difference score (r = .29, p < .05) in skin conductance responses. These da ta suggest that indi viduals with greater social alcohol expectancies were more aroused by Alcohol-Nonsocial cues than individuals with lower social alcohol expectancies. The Relationship between Skin Conductance and Risk Variables. A series of repeated measures ANOVAs, with cue type as the repeated measure, resulted in no significant differences in Average, Peak, or Difference means due to gender or family history status. Bivariate co rrelations between drinking vari ables, sensation seeking, and skin conductance reactivity yielded significan t, negative relationships between Total Drinking and Peak ( r = -.30, p < .05) and Total Drinking and Difference ( r = -.31, p < .05) magnitudes during Alcohol-Non social cues. These data s uggest that individuals who 42

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drank more in the previous month responded to non-social alcohol cues as less arousing than individuals who drank less. Again, as with initial cardia c deceleration, Total Drinking emerges as the one risk variable asso ciated with skin conductance response. Acoustic Startle Reactivity Descriptive Statistics for Acoustic Startle Reactivity. The startle data for four participants were omitted from the analyses due to an insufficient number of scorable startle responses within each cue category. For the remaining 53 participants, the means for acoustic startle reactivity during Neutral, Alcohol-Nonsoc ial, and Alcohol-Social cues presented both early (250 350 ms) and late (4-5.5 sec) in the picture viewing sequence are presented in Table 11. Mean early star tle magnitudes appear to be attenuated during both Alcohol-related cue types, when compared to neutral cues (Fi gure 5). Mean late startle magnitudes appear to be attenuated only with Alcohol-Social cues compared to neutral cues. Therefore, early startle re sponse magnitudes suggest that individuals processed alcohol-related cues, both with and without a social contex t, as more arousing and attention-grabbing than neutral cues. The late startle response magnitudes suggest that participants processed Alcohol-Social cu es, in particular, as more appetitive than both Alcohol-Nonsocial cu es and Neutral cues. 43

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Table 11 Descriptive Statistics for Early and Late Startle Reactivity Cue Type N Min Max Mean SD Early Neutral 53 41.44 57.22 49.17 3.18 Alcohol-Nonsocial 53 42.29 61.52 48.07 3.91 Alcohol-Social 53 39.14 57.64 48.57 3.45 Late Neutral 53 42.05 60.20 51.19 4.03 Alcohol-Nonsocial 53 44.51 61.16 51.00 3.86 Alcohol-Social 53 42.44 65.60 50.07 4.27 *Note: startle magnitudes are ex pressed in the standardized tscore metric by using the individual mean and SD from each participant across all three cue types. Repeated measures ANOVAs revealed no significant trends for acoustic startle magnitudes presented early or late in the pict ure sequence. A series of paired sample ttests performed within early and late startl e reactivity revealed no significant differences in means. However, the reduction in early startle reactivity ma gnitudes during AlcoholNonsocial cues compared to Neutral cues approached significance [ t (53) = 1.76, p = .08]. The Relationship between Startle Reac tivity and Alcohol Expectancies. No significant correlations were found between alcohol expectancies and early startle reactivity in the presence of Neutral and Alcohol-Social cues (Table 12). However, early startle reactivity to Alcohol-Nonsocial cues was positively and significantly correlated with Positive/Arousing, Negative, Ego tistical, Horny, and Dangerous alcohol expectancies. That is to say that indi viduals endorsing more positive and negative alcohol expectancies proce ssed Alcohol-Nonsocial cues as less arousing and attentiongrabbing than individuals endorsing fewer alcohol expectancies. For late startle reactivity, no significant correlations were found with alcohol expectancies in the presence of Neutral or Al cohol-Nonsocial cues. However, late startle 44

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reactivity to Alcohol-Social cues was positivel y and significantly correlated with Global Positive and Tension Reduction alcohol expectancies. Therefore, individuals who endorse more positive and relaxing alcohol e xpectancies processed Alcohol-Social cues as less appetitive than other individuals, as shown by greater startle response magnitudes during the Alcohol-Social cues. Table 12 Zero-Order Correlations be tween Startle Magnitudes a nd Alcohol Expectancies Early Late Neutral A-Non A-Soc Neutral A-Non A-Soc AEQ Global Positive -.06 .13 -.03 -.14 -.03 .33* Sexual Enhancement -.13 .20 -.05 .03 .13 .18 Social/Physical Pleasure -.22 .06 .02 -.14 .12 .20 Social Assertion -.13 .17 .18 -.03 -.05 .23 Tension Reduction -.06 .21 .04 -.07 -.01 .34* Aggression/Arousal .02 .28* -.16 -.10 .25 .26 AEMax Positive/Arousing .01 .30* -.20 .02 .00 -.01 Negative -.02 .40** -.07 -.08 .08 .20 Sedating .11 .15 -.06 -.01 .12 -.06 Social .05 -.03 -.11 .09 -.06 -.12 Woozy .04 .16 .00 .11 .01 -.12 Sick .13 .22 -.04 -.14 .14 -.07 Egotistical -.05 .32* -.14 .10 -.03 .20 Horny .10 .53** -.21 -.07 .02 .05 Attractive -.08 .18 -.14 .03 .04 .04 Sleepy .10 .00 -.10 -.01 .14 .04 Dangerous .00 .32* .01 -.18 .13 .14 p < .05, ** p < .01 A series of repeated measures ANOVAs, w ith cue type the repeated factor and expectancy subscale as the covariate, were conducted to determine the influence of alcohol expectancy subscales on the pattern of startle reactiv ity presented both early and late across the three cue types. For visual purposes, median splits of the expectancy 45

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subscales that significantly interacted with early or late startle magnitudes are presented in Figures 6-12. For early startle magnitude patterns, ther e were significant in teractions between cue type and the AEQ Aggression/Arousal subscale [F(2,102) = 3.13, p < .05, = .96], AEMax Positive/Arousing [F(2,102) = 3.96, p < .05, = .96], Negative [F(2,102) = 4.43, p < .05, = .96], Egotistical [F(2,102) = 3.84, p < .05, = .96], and Horny [F(2,102) = 10.22, p < .001, = .99] subscales. The greatest difference in early startle magnitude between expectancy groups occurred during Alcohol-Nonsocial cue presentation, where individuals with greater alcohol expectancies produced less of a startle reduction (i.e. higher st artle magnitude) during these cues. It appears from these graphs that individuals with greater alcohol expectancies, across both valence and arousal domains, process Alcohol-Nonsocial cues as less arousing and a ttention-grabbing than individuals with lower alcohol expectancies. Regarding late startle response patterns there was a signif icant interaction between late startle magnitudes and the AE Q Global Positive subscale [F(2,102) = 3.40, p < .05, = .97] and a nearly significant interac tion between late startle magnitudes and the AEQ Tension Reduction subscale [F(2,102) = 2.86, p = .06, = .97]. The greatest difference in late startle magnitudes betw een expectancy groups occurred during Alcohol-Social cue presentation. Therefore, individuals with more positive and relaxing alcohol expectancies process Al cohol-Social cues as less ap petitive than individuals with lower positive and tension-re duction alcohol expectancies. 46

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The Relationship between Startle Re activity and Risk Variables. A series of repeated measures ANOVAs within early and late startle magnitude s, across cue types revealed no significant differences due to gende r, sensation seeking, or drinking behavior. However, there was a significant interaction be tween family history status and cue types for early startle magnitude patterns (F = 3.35, p < .05, = .89). Participants with a positive family history for at least one parent with an alcohol use disorder display reduced startle response during Neutral cues and a potentiated startle magnitude during Alcohol-Social cues when compared to individuals with a negative family history for alcoholism (Figure 13). The graph suggests th at individuals positive for a family history of alcohol use disorder, and therefore at greater risk for developing an alcohol use disorder, process Alcohol-Social cues as le ss arousing or attention-grabbing than other participants. 47

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Discussion The relationship between alcohol expectancies, risk variables for future alcohol use disorders and cue reactivity was measur ed in a sample of college-aged social drinkers. The primary purpose of this study was to examine the affective component to alcohol expectancy theory, by using startle eyeblink reflex as an index for affective processing of and reactions to drinking cues. Further, this study examined the relationship between risk variables and cue reactivity measures in the presence of alcohol-related cues compared to neutral cues. Of particular intere st was the relationship between social, positive, and arousing alcohol expectancies and cue reactivity to alcohol cues in both social and non-social contexts. Overall, cue reactivity measures revealed expected relationships between alcohol expectancies and risk variables. Subjective ratings indicated that individuals with more positive, arousing, and social alcohol expectan cies found alcohol cues in both social and nonsocial settings more pleasing, arousing, and craving-inducing than individuals with less positive and arousing expect ancies. Correlations between heart rate deceleration and alcohol expectancies revealed that individuals with less po sitive/arousing expectancies reacted to alcohol-related cues, particularly in the nonsocial setting, as more aversive than individuals with more positive expectancies. Finally, skin conductance response patterns showed that individuals with greater social alcohol expe ctancies found alcohol-nonsocial cues more arousing than individuals endor sing less social alc ohol expectancies. Therefore, college-aged students in this samp le who have greater positive, social, and 48

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arousing alcohol expectancies not only rated alcohol -related cues as more pleasant, they physiologically processed alcohol -related cues as less aversive and more arousing than those with more negative expectancies. Thes e results confirm that alcohol expectancies and the autonomic processing of alcohol-related cues are not only related, but they also are part of the same mechanism. Individual expectations about alc ohol can be indexed by psychophysiological reactions to alcohol cu es, such as skin conductance and cardiac response. However, the relationship between alc ohol expectancies and startle eyeblink response indicated a more complicated relations hip between motivations to drink and risk variables. Although this sample consisted of a wide range of college -aged drinkers with varying alcohol expectancies, the eyeblink star tle reflex results indicated two types of individuals: those not at risk for future alcohol use di sorders, and those with increased risk for future alcohol use disorders, as m easured by family histor y status and alcohol expectancy levels. Specifically, individuals with no family history for alcoholism and less positive/arousing alcohol expectancies displayed more of the expected psychophysiological reaction patterns to alc ohol-related cues, m eaning their startle magnitudes were attenuated in the presence of alcohol-related cues compared to neutral cues. However, high-risk individuals disp layed a more blunted response pattern to alcohol-related cues. Low-risk individuals clearly responded to alcohol-related cues as appetitive compared to neutral, during both early and late startle probes. This is consistent with research that shows most college-aged indivi duals find alcohol to be appealing, resulting in increased prevalence of drinking among this population compared to other age groups. 49

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In a study looking at brain wave activity in response to expectancy statements, both heavy and light college-aged drinkers automatically processed positive alcohol expectancy statements as consistent and congruent with their own alcohol-expectancy associations (Fishman, Goldman & Donchin, 2006). Interestingly, among low-risk individual s early startle reflex magnitudes were inhibited during alcohol-nonsocial cues and not alcohol-social cues, while late startle reflex magnitudes were inhibited during alc ohol-social cues and not alcohol-nonsocial cues. This suggests that the immediate processing of alcohol cues is most effective during simple pictures of beer, without a complex social background. However, given time to process the social context of alc ohol-social cues, the later startle reflex magnitudes reflect the greater appetitive natu re of alcohol cues in a social setting, compared to alcohol cues alone. These results are consistent with expectancy theory and social norm literature among college-aged i ndividuals, who find social aspects of drinking behavior mo st reinforcing. However, high-risk individuals in this sa mple did not respond to alcohol-related cues as expected. It was hypothesized th at the stronger ones positive, social, and arousing alcohol expectancies, the more st artle inhibition would result during alcoholrelated cues. However, the participants positive for 1 st or 2 nd degree family history and endorsing more positive/arousing alcohol expectancies displayed a flat, or blunted, response pattern to alcohol-re lated cues, with magnitudes in startle response similar to those elicited during neutral cues. While ea rly startle reflex magnitudes during alcoholsocial cues appear to be inhibited compar ed to neutral cues, the relationship between alcohol expectancies and response magnitude s to early alcohol-so cial cues is not 50

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significant. The overall pattern of response in these high-ri sk individuals consistently shows only modest differences within early or late startle magnitudes between alcoholrelated and neutral cues. Therefore, while lo w-risk individuals in this sample displayed the expected startle responses inhibition to al cohol-related cues comp ared to neutral cues, the higher risk individuals di splayed a blunted startle res ponse pattern across all picture cues. Blunted processing of affective and arousi ng properties of stimuli is consistent with other research looking at startle eyeblink response patter ns among individuals at risk for future alcohol use disorders (Miranda et al, 2002a). This tre nd is also observed in research examining the brain wave activity of at-risk populations during cognitive tasks. Specifically, compared to controls, alcoholic s display decreased amplitude event-related potential (ERP) waveform during both re sponse activation and response inhibition conditions on Go/No-Go tasks (Kamaraj an, Porjesz, Jones, Choi, Chorlian, Padmanabhapillai, Rangaswamy, Stimus & Be gleiter, 2005). Specifically, the P300, or positive peak that occurs around 300 ms after stimulus onset, which is thought to index attentional processing and working memory, is blunted among individuals diagnosed with an alcohol-use disorder. These results are consistent with blunted electrophysiological response activity among alcoholics, more generally (Porjesz & Begleiter, 2003). In addition, adult ch ildren of alcoholics show reduced electrophysiological response activity in research settings. Specifically, indi viduals positive for a family history of alcoholism displayed blunted act ivity in electroencephalographic (EEG) signals and reduced delta and theta activity during cognitive tasks (Kamarajan, Porjesz, 51

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Jones, Chorlian, Padmanabhapillai, Rangaswamy, Stimus & Begleiter, 2005). Deficits in these brain waves indicated a deficit in conscious awareness, recognition memory, episodic retrieval, and attent ional processing. These adult children of alcoholics also displayed reduced P300 during cognitive tasks, indicating a deficit in inhibitory control, or executive functioning, among individuals at risk for future al cohol use disorders. This blunted response phenomenon, obs erved across varying measur es of brain activity, may serve to explain the blunted st artle eyeblink reflexes among the highest risk individuals in the current sample. Another factor that might influence th e blunted startle response pattern among high-risk individuals is the a bundance of alcohol-cues in thei r daily natural surroundings. High-risk individuals may find alcohol-related cues as more pleasing and arousing than neutral cues, as reflected in skin conductan ce and heart rate activity, but the familiarity with alcohol stimuli might render high-risk i ndividuals less likely to devote attentional processing to alcohol cues, re sulting in blunted startle re sponse magnitudes. High risk individuals endorsing more positive, arousing and social alcohol expectancies might in fact be experts in processing alcohol cues and less sensitive to the arousing, appetitive properties of an alcohol-related stimulus. In support of this theor y, research shows that individuals who report lower le vels of response to the physio logical effects of alcohol tend to endorse more positive/arousing alcohol expectancies and are often at higher risk for developing alcohol use disorders la ter in life (Schuckit & Smith, 2006). Furthermore, the context of the laborator y setting and non-availability of alcohol consumption may have influenced startle re sponse patterns. I ndividuals entering the research study were aware that the study involved measures of alcohol use, but 52

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presentation of alcohol-relate d cues may have been unexpected. Although all subjects were current drinkers, possibly the lighter dr inkers were more impr essed and pleasantly surprised by alcohol-related cues Heavier drinkers may have dismissed alcohol cues and processed them as particularly not interesting or pleasing in the laboratory setting, due to the unavailability of consumption. Their blunted response patterns may reflect a competition between the appetitive, pleasi ng nature of the alcohol cues and the frustrative, non-reward state elicited during picture viewing. Results from this study suggest that there may be two distinct response patterns to alcohol-related stimuli, depending on level of risk for future alcohol use disorders, as measured by family history status and alc ohol expectancy levels Startle eyeblink response does indeed index the affective pr ocessing of alcohol-related cues, as further support to the motivational component of expectan cy theory. That is to say that overall, the sample reacted to alcohol -related cues as more appetitive and rated them more pleasing and arousing than neutral cues. In a ddition, social context doe s appear to impact the affective processing of alcohol cues am ong college-aged drinkers and appears to be modulated by level of risk for alcoholism. Findings from this study are limited to a restricted range of risk for alcohol use disorders. For instance, all participants included in this study were either actively enrolled in a four-year undergraduate colleg e or recent graduates. Even though college student do tend to consume more alcohol than non-college students of the same age, preliminary studies suggest th at non-college students may be at increased risk for problematic drinking and future alcohol-use disorders later in life (Fishman, Bekman, Goldman, Darkes & Brandon, 2006; White, Labouvi e & Papadaratsakis, 2005). It would 53

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not only be interesting, but esse ntial, to include young-adult drinkers both in and out of college settings in future research of this nature. It would also be interesting to dete rmine how the presence of alcohol cues impacts processing of affective cues. A future study might employ a research design where half of the sample is exposed to a ffective cues alone, while the other half are exposed to affective and alcohol-related cues. It is possible that the addition of the alcohol component to the study im pacts the affective state of participants, which might be moderated by risk variable s and alcohol expectancies. Finally, future research should includ e a more exhaustive repertoire of psychophysiological cue reactivity measur es, including skin conductance, cardiac activity, startle eyeblink re sponse and ERP/EEG activity, as indices of alcohol expectancies and risk for future alcohol use disorders. Since most alcohol expectancy research involves explicit measures s upporting the cognitive por tion of expectancy theory, a convergence of re search examining the rela tionship between alcohol expectancies and automatic cue reactivity measures will lend further evidence to the affective component of expectancy theory. Fu rther, this research should extend to other interesting populations, including abstinent individua ls, children in various stages of development, the elderly (among whom alcoholism is on the rise), and adults with varying psychopathologies that often co -occur with alcoho l use disorders. Although this study was one of the first a ttempts of its kind, it was successful in establishing the implicit psychophysiological meas ure, startle eyeblink reflex, as an index of alcohol expectancies among college-aged drin kers. Results were consistent with the posited hypotheses, in that alcohol-related cues were viewed as more pleasing and 54

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appetitive than neutral cues, but only among lower-risk individuals, with less positive/arousing/social alcohol e xpectancies and lacking a fam ily history for alcoholism. It was the startle response patterns am ong high-risk individuals, with more positive/arousing/social alcohol expectanci es and positive for family history of alcoholism, that were surprising. Ultimatel y, this study is a successful look into the relationship between cue reactivity and alc ohol expectancies. The study lends further evidence to support blunted res ponding to affective processing of alcohol-related stimuli among high risk individuals. 55

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References Aas, H.N., Leigh, B.C., Anderssen, N. & Ja kobsen, R. (1998). Two-year longitudinal study of alcohol expectancies and dri nking among Norwegian adolescents. Addiction, 93 373-384. Baron, R.B. & Kenny, D.A. (1986). The mode rator-mediator variab le distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51 1173-1182. Bolles, R.C. (1972). Reinforcement, expectancy, and learning. Psychological Review, 79, Bradley, M.M., Lang, P.J. & Cuthbert, B.N. (1993). Emotion, novelty, and the startle reflex: Ha bituation in humans. Behavioral Neuroscience, 107 970-980. Bradley, M.M., Cuthbert, B.N. & Lang, P.J. (1993). Pictures as prepulse: Attention and emotion in startle modification. Psychophysiology, 30, 541-545. Bradley, M.M., & Lang, P.J. (1994). Measur ing emotion: The self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry, 25 49-59. Bradley, M.M., Moulder, B. & Lang, P.J. (2005) When good things go bad: The reflex physiology defense. Psychological Science, 16, 468-473. Brown, S.A., Goldman, M.S., Inn, A. & Ande rsen, L. (1980). Expectations of reinforcement from alcohol: Their domain and relation to drinking patterns. Journal of Consulting and Clinical Psychology, 48 419-426. Brown, S.A., Christiansen, B.A., & Goldman, M.S. (1987). The Alcohol Expectancy Questionnaire: An instrument for th e assessment of adolescent and adult expectancies. Journal of Studies on Alcohol, 48, 483-491. Cacioppo, J.T., Klein, D.J., Berntson, G.G. & Hatfield, E. (1993). The psychophysiology of emotion. In M. Lewis & J.M. Haviland (Eds.) Handbook of emotions (pp. 119-142). New York: The Guilford Press. Center for Disease Control and Prevention. Na tional Center for Injury Prevention and Control. Web-based Injury Statistics Query and Reporting System (WISQARS). Available on line: http://www.cdc.gov/ncipc/ wisqars/, 2000. 56

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Clapp, J.D., Reed, M.B., Holmes, M.R., Lange, J.E. & Voas, R.B. (2006). Drunk in public, drunk in private: The relations hip between college students, drinking environments and alcohol consumption. The American Journal of Drug and Alcohol Abuse, 32, 275-285. Cohen, J. (1992). A Power Primer. Psychological Bulletin, 112 155-159. Cook, E.W. (1999). VPM reference manual. Birmingham, AL: Author. Cook, E.W. (1999). Affective individual differences, psychopa thology, and startle reflex modification. In Dawson, M.E., Schell, A.M. & Bohmelt (Eds.), Startle Modification: Implications for neuros cience, cognitive scie nce and clinical science. (pp.187-208). New York; Cambridge University Press. Cook, E.W., Hawk, L.W., Davis, T.L. & Steven son, V.E. (1991). Affective individual differences and startle reflex modulation. Journal of Abnormal Psychology, 100 5-13. Davis, M. (1997). The neurophysiological basi s of acoustic startle modulation: Research on fear motivation and sensory gating. In Lang, P.J., Simons, R.F. & Balaban, M.T. (Eds.), Attention and orienting: sens ory and motivational processes (pp.6996) New Jersey; Lawrence Erlbaum Associates. Davis, M., Walker, D.L. & Lee, Y. (1999). Neurophysiology and neuropharmacology of startle and its affective modulation. In Dawson, M.E., Schell, A.M. & Bohmelt (Eds.) Startle Modification: Implications fo r neuroscience, cognitive science and clinical science. (pp.95-113). New York; Cambridge University Press. Del Boca, F.K., Darkes, J., Greenbaum, P.E. & Goldman, M.S. (2004). Up close and personal: Temporal variability in the drinking of individua l college students during their first year. Journal of Consulting and Clinical Psychology, 72, 155164. Des Rosiers, S.E., Noll, J.A. & Goldman, M.S. (2002). An exploratory study of alcohol expectancies in semantic sp ace as a function of gender. Alcoholism: Clinical and Experimental Research, 26(S5), 35A. Drobes, D.J., Carter, A.C. & Goldman, M.S. (in preparation). Alc ohol expectancies and cue reactivity to alcohol-related and affective cues. Drobes, D.J., Miller, E.J., Hillman, C.H., Bradley, M.M., Cuthbert, B.N. & Lang, P.J. (2001). Food deprivation and emotional reactions to food cues: implications for eating disorders. Biological Psychology, 57 153-177. 57

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Katz, E.C., Fromme, K., DAmico, E.J. (2000) Effects of outcome expectancies and personality on young adults illicit drug us e, heavy drinking, and risky sexual behavior. Cognitive Therapy & Research, 24, 1-22. Knight, J.R., Wechsler, H., Kuo, M., Seibri ng, M., Weitzman, E.R., & Shuckit, M.A. (2002). Alcohol abuse and depende nce among U.S. college students. Journal of Studies on Alcohol, 63, 263-270. Koch, M. & Schnitzler, H. (1997). The acous tic startle response in ratscircuits mediating evocation, inhibition and potentiation. Behavioral Brain Research, 89 35-49. Kypri, K. & Langley, J.D. (2003). Percei ved social norms and their relation to university student drinking. Journal of Studies on Alcohol, 64, 829-834. Lacey, J.I. & Lacey, B.C. (1970) Some autonomic-central nervous system interrelationships. In P. Black (Ed.), Physiological Correlates of Emotion (pp. 205-227). New York: Academic Press. Lang, P.J. (1980). Behavioral treatment and bio-behavioral assessment: computer applications. In J.B. Sidowski, J.H. Johnson & T.A. Williams (Eds.), Technology in mental health mare delivery systems (pp.119-137). Gainesville, FL: Center for Research in Psychophysiology. Lang, P.J., Bradley, M.M., & Cuthbert, B.N. (1990). Emotion, attention, and the startle reflex. Psychological Review, 97 377-395. Lang, P.J., Greenwald, M.K., Bradley, M.M ., & Hamm, A.O. (1993). Looking at pictures: Affective, facial, vis ceral, and behavioral reactions. Psychophysiology, 30, 261-173. Lang, P.J., Bradley, M.M., & Cuthbert, B.N. (1997). Motivated Attention: Affect, activation, and action. In P.J. Lang, R. F. Simons & M.T. Balaban (Eds.) Attention and orienting: sensory a nd motivational processes. (pp. 97-135). Lee, Y., Lopez, D.E., Meloni, E.G. & Davis, M. (1996). A primary acoustic startle pathway: obligatory role of cochlear root neurons a nd the nucleus reticularis pontis caudalis. The Journal of Neuroscience, 16, 3775-3789. MacCorquodale, K.M & Meehl, P.E. (1953) Preliminary suggestions as to a formalization of expectancy theory. Psychological Review, 60, 55-63. Miranda, R., Meyerson, L.A., Buchanon, T.W. & Lovallo, W.R. (2002a). Altered emotion-modulated startle in young adults wi th a family history of alcoholism. Alcoholism: Clinical and Experimental Research, 26 441-448. 60

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Appendices 64

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Appendix A: Figures 0 2 4 6 8 10 12 14 16 ValenceArousalDominanceCraving Neutral Alcohol-Nonsocial Alcohol-Social * Figure 1: Subjective Affective and Craving Ratings. Note. Repeated measures ANOVA results: Valence ratings: F l inear(1,56) = 16.20, p < .01, = .72; Arousal ratings: F linear(1,56) = 56.87, p < .01, = .71, Dominance ratings: n.s.; Craving ratings F linear(1,56) = 56.21, p < .01, = .67. 65

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 10.00 7.50 5.00 Rating Means Male Female Gender Figure 2: Arousal Rating Means by Gender. Note. Interaction eff ect: F(1,56) = 3.66, p < .05, = .72. 66

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 9.00 8.00 7.00 6.00 5.00 4.00 3.00 2.00 Rating Means Male Female Gender Figure 3: Craving Rating Means by Gender. Note. Interaction eff ect: F(1,56) = 4.17, p < .01, = .68. 67

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Appendix A: Figures (Continued) 70 72 74 76 78 80 BaselineD1A1D2 Neutral Alc-NS Alc-S Figure 4: Mean Cardiac Activity across Cue Type. Note. D1 = initial deceleration; A1 = in itial acceleration; D2 = secondary deceleration; Alc-NS = alcohol-nonsocia l cues; Alc-S = alcohol-social cues 68

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Appendix A: Figures (Continued) 46.5 47 47.5 48 48.5 49 49.5 50 50.5 51 51.5 Early Late Neutral Alcohol-Nonsocial Alcohol-Social Figure 5: Mean Startle Magnitudes during Early and Late Trials. 69

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 49.50 49.00 48.50 48.00 47.50 47.00 46.50 Early Startle Magnitude High Low AEQ Aggression/Arousal Figure 6: Interaction of Cue Type by AEQ Aggression/Arousal Subscale. Note. Interaction eff ect: F(2,102) = 3.13, p < .05, = .96. 70

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 49.50 49.00 48.50 48.00 47.50 47.00 46.50 Early Startle Magnitude High Low AEMax Positive/Arousing Figure 7. Interaction of Cue Type by AEMax Positive/Arousing Subscale. Note. Interaction e ffect: F(2,102) = 3.96, p < .05, = .96. 71

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 49.50 49.00 48.50 48.00 47.50 47.00 46.50 Early Startle Magnitude High Low AEMax Negative Figure 8: Interaction of Cue Type by AEMax Negative Subscale. Note. Interaction e ffect: F(2,102) = 4.43, p < .05, = .96. 72

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 49.50 49.00 48.50 48.00 47.50 47.00 Early Startle Magnitudes High Low AEMax Egotistical Figure 9. Interaction of Cue T ype by AEMax Egotistical Subscale. Note. Interaction e ffect: F(2,102) = 3.84, p < .05, = .96. 73

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 50.00 49.00 48.00 47.00 46.00 Early Startle Magnitude High Low AEMax Horny Figure 10. Interaction of Cue Type by AEQ Horny Subscale. Note. Interaction e ffect: F(2,102) = 10.22, p < .001, = .99. 74

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 52.00 51.50 51.00 50.50 50.00 49.50 49.00 Late Startle Magnitude High Low AEQ Global Positive Figure 11. Interaction of Cue Type by AEQ Global Positive Subscale. Note. Interaction e ffect: F(2,102) = 3.40, p < .05, = .97. 75

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 52.00 51.50 51.00 50.50 50.00 49.50 49.00 Late Startle Magnitude High Low AEQ Tension Reduction Figure 12. Interaction of Cue Type by AEQ Tension Reduction Subscale. Note. Interaction e ffect: F(2,102) = 2.86, p = .06, = .97. 76

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Appendix A: Figures (Continued) Alcohol-Social AlcoholNonsocial Neutral Cue Type 50.00 49.50 49.00 48.50 48.00 47.50 47.00 Early Startle Magnitude Positive Negative Family History Status Figure 13. Interaction of Cue Type by Family History Status. Note. Interaction effect: F = 3.35, p < .05, = .89. 77

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Appendix B: Measures Participant Demographics 1. Age _____ Date of Birth __ __ / __ __ / __ __ __ __ 2. What is your gender? Female Male 3. What is your ethnicity? __Hispanic or Latino (Spanish origin) __Not Hispanic or Latino 4. What is your race? __American Indian or Alaska Native __Asian __Black or African American __Native Hawaiian/ other Pacific Islander __White 5. What is your current marital status __Single, never married __Divorced __Married __Widowed __Cohabitating __Separated 6. What is your usual pattern of employment over the past year? __Full time (40 hours/ week) __Military Service __Part time (regular hours ) __Retired/disability __Part time (irregular hours) __Homemaker __Student __Unemployed 7. What is the highest level of education you have completed? __No formal education __Some grade school __Completed grade school __Some high school __Completed high school __Some college __Completed college __Some gradate work __A graduate degree 78

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Appendix B: Measures (Continued) 8. Are you currently taking any medications? ______ Yes ______ No Medication Dosage/Frequency When Started Purpose 1) 2) 3) 4) 5) 9. Surgery, hospitalizat ions or injuries: Date Diagnosis Treatment Hospital/ Doctors Name 10. Habits: Do you drink coffee? Yes No How often?_______ Amount_________ Do you smoke cigarettes? Yes No How often?_______ Amount_________ Do you smoke cigars? Yes No How often?_______ Do you use snuff? Yes No How often?_______ Do you smoke a pipe? Yes No How often?_______ 11. Past medical history (give age you had any of the following): ____heart disease ____asthma ____hypertension ____kidney disease ____head inju ry ____loss of consciousness ____stroke ____glaucoma ____neurological disorder ____thyroid trouble ____heart trouble ____diabetes ____bronchitis ____seizure 12. Do you have any problems with your hearing? If so, please describe: ______________________________________________________________________ ______________________________________________________________________ 13. Do you have any problems with your vision? If so, please describe: ______________________________________________________________________ ______________________________________________________________________ 79

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Appendix B: Measures (Continued) Alcohol Expectancy Questionnaire This is a questionnaire about the effects of alcohol. Read each statement carefully and respond according to your own personal feel ings, thoughts, and beliefs about alcohol now We are interested in what you think about alcohol, regard less of what other people might think. If you think that the statement is true, or mostly true, or true some of the time, then circle the number 1, for "AGREE. If you think the statement is false, or mostly false, then circle the number 0, for "DISAGREE. When the statements refer to drinking alcohol, you may think in terms of drinking a ny alcoholic beverage, such as beer, wine, whiskey, liquor, rum, scotch, vodka, gin, or vari ous alcoholic mixed drinks. Whether or not you have had actual dri nking experiences yourself, you are to answer in terms of your beliefs about alcohol It is important that you respond to every question PLEASE BE HONEST. REMEMBER, YOUR ANSWERS ARE CONFIDENTIAL. RESPOND TO THESE ITEMS ACCORDING TO WHAT YOU PERSONALLY BELIEVE TO BE TRUE ABOUT ALCOHOL 0=DISAGREE 1=AGREE 0 1 1. Some alcohol has a pleas ant, cleansing, tingly taste. 0 1 2. Drinking adds a certain warmth to social occasions. 0 1 3. When I'm drinking, it is easier to open up and express my feelings. 0 1 4. Time passes quickly when I'm drinking. 0 1 5. Drinking makes me feel flushed. 0 1 6. I feel powerful when I drink, as if I can really influence others to do what I want. 0 1 7. Drinking gives me more confidence in myself. 0 1 8. Drinking makes me feel good. 0 1 9. I feel more creative after I've been drinking. 0 1 10. Having a few drinks is a nice way to celebrate special occasions. 0 1 11. When I'm drinking I feel freer to be myself and do whatever I want. 0 1 12. Drinking makes it easier to concen trate on the good feelings I have at the time. 0 1 13. Alcohol allows me to be more assertive. 0 1 14. When I feel "high" from drinking everything seems to feel better. 0 1 15. I find that conversing with member s of the opposite sex is easier for me after I've had a few drinks. 0 1 16. Drinking is pleasurable because it' s enjoyable to join in with people who are enjoying themselves. 0 1 17. I like the taste of some alcoholic beverages. 0 1 18. If I'm feeling restricted in any wa y, a few drinks make me feel better. 0 1 19. Men are friendlier when they drink. Please continue on to next page 80

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Appendix B: Measures (Continued) Alcohol Expectancy Questionnaire (Page 2) 0=DISAGREE 1=AGREE 0 1 20. After a few drinks, it is easier to pick a fight. 0 1 21. If I have a couple of drinks, it is easier to express my feelings. 0 1 22. Alcohol makes me need less atten tion from others than I usually do. 0 1 23. After a few drinks, I feel mo re self-reliant than usual. 0 1 24. After a few drinks, I don't worry as much about what other people think of me. 0 1 25. When drinking, I do not consider myself totally accountable or responsible for my behavior. 0 1 26. Alcohol enables me to have a better time at parties. 0 1 27. Drinking makes the future seem brighter. 0 1 28. I often feel sexier after I've had a couple of drinks. 0 1 29. I drink when I'm feeling mad. 0 1 30. Drinking alone or with one other person makes me feel calm and serene. 0 1 31. After a few drinks, I feel br ave and more capable of fighting. 0 1 32. Drinking can make me more satisfied with myself. 0 1 33. My feelings of isolation and alienation decrease when I drink. 0 1 34. Alcohol helps me sleep better. 0 1 35. I'm a better lover after a few drinks. 0 1 36. Alcohol decrease s muscular tension. 0 1 37. Alcohol makes me worry less. 0 1 38. A few drinks makes it easier to talk to people. 0 1 39. After a few drinks I am usually in a better mood. 0 1 40. Alcohol seems like magic. 0 1 41. Women can have orgasms more easily if they've been drinking. 0 1 42. Drinking helps get me out of a depressed mood. 0 1 43. After I've had a couple of drinks, I feel I'm more of a caring, sharing person. 0 1 44. Alcohol decreases my feeli ngs of guilt about not working. 0 1 45. I feel more coordinated after I drink. 0 1 46. Alcohol makes me more interesting. 0 1 47. A few drinks makes me feel less shy. 0 1 48. Alcohol enables me to fall asleep more easily. 0 1 49. If I'm feeling afraid, alcohol decreases my fears. 0 1 50. Alcohol can act as an anesthe tic, that is, it can deaden pain. 0 1 51. I enjoy having sex more if I've had some alcohol. 0 1 52. I am more romantic when I drink. 0 1 53. I feel more masculine/feminine after a few drinks. Please continue on to next page 81

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Appendix B: Measures (Continued) Alcohol Expectancy Questionnaire (Page 3) 0=DISAGREE 1=AGREE 0 1 54. Alcohol makes me fe el better physically. 0 1 55. Sometimes when I drink alone or with one other person it is easy to feel cozy and romantic. 0 1 56. I feel like more of a happy-go-lucky person when I drink. 0 1 57. Drinking makes get togethers more fun. 0 1 58. Alcohol makes it easier to forget bad feelings. 0 1 59. After a few drinks, I am more sexually responsive. 0 1 60. If I'm cold, having a few drinks will give me a sense of warmth. 0 1 61. It is easier to act on my fee lings after I've had a few drinks. 0 1 62. I can discuss or argue a point more forcefully after I've had a drink or two. 0 1 63. A drink or two makes the humorous side of me come out. 0 1 64. Alcohol makes me more outspoken or opinionated. 0 1 65. Drinking increases female aggressiveness. 0 1 66. A couple of drinks makes me more aroused or physiologically excited. 0 1 67. At times, drinking is like permission to forget problems. 0 1 68. If I am tense or anxious, having a few drinks makes me feel better. 82

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Appendix B: Measures (Continued) Alcohol Expectancy Multi-Axial Assessment (AEMax) This page contains words describing possi ble effects of alcohol. For each word, imagine it completing the sentence: DRINKING ALCOHOL MAKES ONE ." Then, for each word mark the number that indicates how often you think that this effect happens or would happen after drinking several drinks of alcohol "Drinking alcohol" refers to drinking any alcoholic beverage such as beer, wine, wine coolers, whiskey, scotch, vodka, gin, or mixed drinks. There are no right or wrong answers. Answer each item quickly according to your first impression and according to your ow n personal beliefs about the effects of alcohol. The available responses/numbers and their meaning are indicated below: 0 Never 1 Very Rarely 2 Rarely 3 Occasionally 4 Frequently 5 Very Frequently 6 Always "DRINKING ALCOHOL MAKES ONE ." 1. Dizzy _______ 13. Attractive _______ 2. Arrogant _______ 14. Ill _______ 3. Horny _______ 15. Sleepy _______ 4. Light-headed _______ 16. Lustful _______ 5. Erotic _______ 17. Social _______ 6. Appealing _______ 18. Cocky _______ 7. Deadly _______ 19. Sick _______ 8. Beautiful _______ 20. Dangerous _______ 9. Sociable _______ 21. Outgoing _______ 10. Egotistical _______ 22. Hazardous _______ 11. Tired _______ 23. Drowsy _______ 12. Woozy _______ 24. Nauseous _______ 83

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Appendix B: Measures (Continued) ZKPQ DIRECTIONS : On the front and back page you will find a series of statements that persons might use to describe themselves. Read each statement and decide whether or not it describes you. Then indicate your answer by circling the appropriate number. If you agree with a statement or decide th at it describes you, answ er TRUE by circling the (1). If you disagree with a statement, or feel that it is not de scriptive of you, answer FALSE by circling the (0). 0 = FALSE 1 = TRUE Answer every statement either False (0) or True (1), even if you are not enti rely sure of your answer. FALSE TRUE 1. I tend to begin a new job without much advance planning on how I will do it. 0 1 2. I usually think about what I am going to do before doing it. 0 1 3. I often do things on impulse. 0 1 4. I very seldom spend much time on the detail s of planning ahead. 0 1 5. I like to have new and exciting experiences and sensations even if they are a little frightening 0 1 6. Before I begin a complicated job, I make careful plans. 0 1 7. I would like to take off on a tr ip with no preplanned or defined routes or timetables. 0 1 8. I enjoy getting into new situations where you cant predict how things will turn out. 0 1 9. I like doing things just for the th rill of it. 0 1 10. I tend to change interests freque ntly. 0 1 11. I sometimes like to do things that are a lit tle frightening. 0 1 12. Ill try anything once. 0 1 13. I would like the kind of life where one is on the move and traveling a lot, with lots of change and excitement. 0 1 14. I sometimes do crazy things just for fun. 0 1 15. I like to explore a strange city or section of town by myself, even if it means getting lost. 0 1 16. I prefer friends who are excitingl y unpredictable. 0 1 17. I often get so carried away by new and exciting things and ideas that I never think of the possible complications. 0 1 18. I am an impulsive person. 0 1 19. I like wild uninhibited parties. 0 1 84

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Appendix B: Measures (Continued) Family Grid This instrument is to be admini stered as a personal interview This questionnaire concerns your family a nd experiences that family members have had with alcohol. Please begin by describing your family by indicating in Column A the total number of biological (i.e., related by blood) relatives (both living and dead) that you have in each category on each side of your family. For example, a lthough you have only one biological grandmother on your mothers side (as shown in Column A), you may have several aunts (your mothers biological sisters) or none at all. If you have no relatives in a particular category, put the letter N (for None) in Column A in the space next to the category. If you dont know how many relatives you have in a category, put DK (for Dont Know) in the space. Next, please indicate in Column B the number of biological relatives (both living and dead) in each category that had in the past, or currently have, what you would call a significant drinking problem, one that did, or should have, led to treatme nt. Some signs that drinking may be a problem include legal problems (e.g., drunk driving violations), health problems (e.g., cirrhosis of the liver, alcohol withdrawal symptoms), relationship probl ems (e.g., arguments about alcohol with family members), or work/school problems (e.g., poor performance, absenteeism resulting from alcohol use), or actual treatment (e.g., detox or rehab, AA meeting attendance). If you have no relatives with alcohol problems in a particular category, put the letter N (for None) in Column A in the space next to the category. If you dont know how many relatives you have in a category, put DK (for Dont Know) in the space. Biological Relative A B Mothers Side Number of biological relatives Number of relatives with alcohol problems Grandmother 1 Grandfather 1 Mother 1 Aunt(s) Uncle(s) Fathers Side Grandmother 1 Grandfather 1 Father 1 Aunt(s) Uncle(s) Siblings Brother(s) Sister(s) 85