The Relationship of Urgency to Impulsive Decision-Making During Heightened Affective States in Problem Drinkers a Dissertation P

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The Relationship of Urgency to Impulsive Decision-Making During Heightened

Affective States in Problem Drinkers

A dissertation presented to

the faculty of

the College of Arts and Sciences of Ohio University

In partial fulfillment

of the requirements for the degree

Doctor of Philosophy

Brittni V. Morgan

August 2018

This dissertation titled

The Relationship of Urgency to Impulsive Decision-Making During Heightened

Affective States in Problem Drinkers

BRITTNI V. MORGAN

has been approved for

the Department of Psychology

and the College of Arts and Sciences by

Julie A. Suhr

Professor of Psychology

Joseph Shields

Interim Dean, College of Arts and Sciences 3

Abstract

MORGAN, BRITTNI V., Ph.D., August 2018, Psychology

The Relationship of Urgency to Impulsive Decision-Making During Heightened

Affective States in Problem Drinkers

Director of Dissertation: Julie A. Suhr

Problematic alcohol use remains a significant public health concern among college student populations. Individual differences in the personality traits of neuroticism and impulsivity, particularly its urgency facets, have been found to place some individuals at greater risk for problematic alcohol use. Both positive and negative urgency have been shown to strongly relate to and predict problematic alcohol use outcomes across various populations, including college students. Notably, the vast majority of urgency studies have used only self-report measures, have not controlled for neuroticism, and have not measured actual engagement in impulsive or risky behaviors on behavioral measures of impulsivity such as the Iowa Gambling Task (IGT). Impaired performance on the IGT has been demonstrated in substance users, at-risk groups, and individuals with higher levels of impulsivity and urgency. However, studies that have examined the relationship between urgency and behavioral performance on the IGT have done so in a neutral affective state, without manipulation of mood. The present study examined the relationship between positive and negative urgency and decision-making performance on the IGT after mood induction, controlling for neuroticism. 159 undergraduates who reported high-risk alcohol use on the Alcohol Use Disorders

Identification Test (AUDIT; Saunders et al., 1993) were randomly assigned to a positive, negative, or neutral mood induction group and completed the IGT after mood induction. 4

After controlling for neuroticism, both negative and positive urgency were associated with use of hard drugs, and negative urgency was associated with AUDIT total score; however, contrary to previous findings, the urgency traits were not associated with any other indicators of problematic substance use we examined. Results suggest that the urgency traits relate differentially to indicators of problematic substance use in males and females, which should be taken into consideration by clinicians and in future studies.

Also contrary to hypotheses, the urgency traits were not related to impulsive decision- making on the IGT, and mood condition did not moderate the relationship between urgency traits and IGT performance. It is likely that our visual mood manipulation procedure was not effective at eliciting a sufficient emotion state so as to induce impulsive behaviors in those with elevated urgency. Results suggest that, while both self-report measures of the urgency traits and the IGT are designed to assess impulsivity, they are likely measuring distinct processes. 5

Dedication

In loving memory of Cody.

“Brothers are like streetlights along the road, they don’t make distance any shorter but

they light up the path and make the walk worthwhile.”

-Author Unknown

Acknowledgments

I would like to first thank my advisor, Julie Suhr, for her unwavering patience and encouragement on both this project and throughout my graduate training. I would also like to thank my dissertation committee: Drs. Ryan Shorey, Sarah Racine, Nicholas Allen, and Deborah McAvoy for their flexibility and thoughtful guidance. Additionally, I am appreciative of my research assistants who helped tremendously with data collection:

Sydney Jones, Taylor Gardner, Marissa Kamlowsky, Katherine Russell, Maggie Shaver,

Gabrielle Romeo, and Jasmine Simpkins. I would also like to thank my parents and Mike for their continuous support and love.

Table of Contents

Page

Abstract ...... 3 Dedication ...... 5 Acknowledgments...... 6 List of Tables ...... 9 Chapter 1: Introduction ...... 11 Personality Traits and Alcohol Use ...... 11 Neuroticism and alcohol use...... 11 Impulsivity/urgency and alcohol use...... 12 Urgency and Rash Action ...... 16 Measurement of rash action: Self-report or behavior? ...... 18 Neural mechanisms of impulsivity, urgency, and rash action...... 21 The Role of Mood State in Urgency and Impulsivity ...... 24 Limitations of the Current Literature ...... 25 The Present Study ...... 27 Chapter 2: Methods ...... 29 Participants ...... 29 Measures ...... 30 Alcohol Use Disorders Identification Test-Self Report Version (AUDIT)...... 30 National Institute on Drug Abuse-modified Alcohol, Smoking and Substance Involvement Screening Test, Version 2.0 (NIDA-modified ASSIST V2.0)...... 31 Problematic alcohol use...... 32 NEO Five-Factor Inventory-3 (NEO-FFI-3) neuroticism...... 32 UPPS-P Impulsive Behavior Scale (UPPS-P)...... 33 Positive and Negative Affect Scale (PANAS)...... 33 The Affect Grid...... 34 Alcohol Craving Questionnaire-Short Form-Revised (ACQ-SF-R)...... 34 Iowa Gambling Task (IGT)...... 35 Procedure ...... 35 Analyses ...... 37 Chapter 3: Results ...... 39 Group Differences ...... 39 8

Mood Manipulation Check ...... 39 Hypothesis 1: Urgency and Self-Reported Substance Use ...... 41 Hypothesis 2: Urgency and Risky Decision-Making...... 43 Hypothesis 3: Relationship of Urgency to Decision-Making in Heightened Emotion State...... 43 Relationship of Urgency to Craving in Heightened Emotion State ...... 47 Supplemental Analyses ...... 50 Chapter 4: Discussion ...... 56 Limitations and Future Directions ...... 67 References ...... 70 Appendix A: Measures ...... 99 Appendix B: Tests of Normality ...... 135 Appendix C: The Affect Grid ...... 137 Appendix D: Nonparametric Analyses ...... 138 Appendix E: Supplemental Analyses...... 139

List of Tables

Page

Table 1 Demographic Data by Condition ...... 30 Table 2 Comparisons of Conditions on Pre-Manipulation Measures ...... 40 Table 3 Comparisons of Conditions on Substance Use Variables ...... 42 Table 4 Pearson Product-Moment Correlations of Neuroticism & Urgency Traits with Substance Variables ...... 45 Table 5 Partial Correlations of Urgency Traits & Substance Variables Controlling for Neuroticism ...... 46 Table 6 IGT Performance by Condition ...... 47 Table 7 Pearson Product-Moment Correlations of IGT Risk with Urgency Traits & Neuroticism ...... 48 Table 8 Summary of Hierarchical Regression Analysis Negative Urgency Predicting IGT Performance ...... 49 Table 9 Summary of Hierarchical Regression Analysis Positive Urgency Predicting IGT Performance ...... 50 Table 10 Pearson Product-Moment Correlations of Craving with Urgency Traits & Neuroticism ...... 51 Table 11 Summary of Hierarchical Regression Analysis for Positive Urgency Predicting Craving ...... 52 Table 12 Summary of Hierarchical Regression Analysis for Negative Urgency Predicting Craving ...... 53 Table 13 Tests of Normality ...... 135 Table 14 Spearman’s Rank Order Correlations of Neuroticism, Urgency Traits & Substance Variables ...... 138 Table 15 Summary of Hierarchical Regression Analysis for Neuroticism and Urgency Traits Predicting Number of Hard Drugs Tried ...... 140 Table 16 Summary of Hierarchical Regression Analysis for Negative Urgency Predicting Number of Hard Drugs Tried ...... 141 Table 17 Summary of Hierarchical Regression Analysis for Positive Urgency Predicting Number of Hard Drugs Tried…………………………………………………………...142 Table 18 Summary of Hierarchical Regression Analysis for Negative Urgency Predicting AUDIT Total Score...... 143 Table 19 Pearson Product-Moment Correlations of Additional UPPS-P Traits & Substance Variables ...... 144 10

Table 20 Pearson Product-Moment Correlations of IGT Performance and PANAS Affect ...... 145 Table 21 Pearson Product-Moment Correlations of IGT Performance and Additional UPPS-P Traits ...... 146 Table 22 Pearson Product-Moment Correlations of IGT Performance and Substance Variables ...... 147 Table 23 Pearson Product-Moment Correlations of Post-Manipulation Craving and IGT Performance ...... 148 Table 24 Substance Use Variables Means and Standard Deviations by Gender……… 151 Table 25 Pearson Product-Moment Correlations of Urgency Traits & Substance Variables by Gender ...... 152 Table 26 Summary of Hierarchical Regression Analysis for Negative Urgency Predicting AUDIT Total Score in Males ...... 153 Table 27 Summary of Hierarchical Regression Analysis for Negative Urgency Predicting AUDIT Total Score in Females ...... 154 Table 28 Summary of Hierarchical Regression Analysis for Negative Urgency Predicting Number of Hard Drugs Tried in Males ...... 155 Table 29 Summary of Hierarchical Regression Analysis for Negative Urgency Predicting Number of Hard Drugs Tried in Females ...... 156 Table 30 Summary of Hierarchical Regression Analysis for Positive Urgency Predicting Number of Hard Drugs Tried in Males ...... 157 Table 31 Summary of Hierarchical Regression Analysis for Positive Urgency Predicting Number of Hard Drugs Tried in Females ...... 158

Chapter 1: Introduction

In the United States, harmful levels of alcohol use among college students continue to be a public health concern, with an estimated 20% meeting criteria for an alcohol use disorder, 38% engaging in binge drinking, and 13% engaging in heavy alcohol use (Blanco et al., 2008; SAMHSA, 2014; 2015). About 1 in 4 college students report negative academic consequences as a result of their alcohol use, and approximately

599,000 college students between the ages of 18 and 24 report injuries related to drinking

(Hingson et al., 2002; 2005). That said, not all college students who engage in risky levels of alcohol consumption develop an alcohol use disorder or experience negative consequences as a result. As such, it is important for researchers to identify risk factors associated with more problematic alcohol consumption outcomes.

Personality Traits and Alcohol Use

Individual differences in personality traits have been identified as risk factors for problematic alcohol use. The personality traits most examined in the literature are the Big

Five personality traits, especially neuroticism, and impulsivity, especially the urgency facet.

Neuroticism and alcohol use. Three of the Big Five personality traits

(specifically high neuroticism, low conscientiousness, and low agreeableness) are related to engagement in problematic alcohol and other substance use, including frequency, quantity, craving, relapse, polysubstance use, and severity, in both clinical and nonclinical populations (Flory et al., 2002; Grekin, Sher, & Wood, 2006; Hopwood et al.,

2007; Khan et al., 2005; Kotov et al., 2010; Malouff et al., 2007; Ruiz, Pincus, &

Schinka, 2008; Sher, Bartholow, & Wood, 2000). Among college students specifically, 12

this same pattern of personality traits is related to past year alcohol use disorder; past year alcohol dependence; past year drug use disorder; current levels of alcohol consumption; alcohol-related problems, including arrests while intoxicated, fights while intoxicated, and black outs; and is predictive of alcohol and drug dependency in prospective studies

(Grekin, Sher, & Wood, 2006; Ruiz, Pincus, & Dickinson, 2003; Trull, Waudby, & Sher,

2004; Vollrath & Torgersen, 2002). Neuroticism plays an especially strong role in predicting negative alcohol use outcomes in college students, including alcohol dependency symptoms, number of drinking days, and substance use diagnoses, up to 7 years later (Larkins & Sher, 2006; Sher, Bartholow, & Wood, 2000; Simons, Wills, &

Neal, 2014).

Impulsivity/urgency and alcohol use. Impulsivity is another individual difference trait consistently associated with substance use, including frequency of use, quantity of use, dependence symptoms, and experience of substance-related problems

(Coskupinar, Dir, & Cyders, 2013; Henges & Marczinski, 2012; Lynam & Miller, 2004;

Moreno et al., 2012; Potenza & de Wit, 2010; Ruiz, Pincus, & Schinka, 2008; Sharma,

Markon, & Clark, 2014; Verdejo-Garcia, Lawrence, & Clark, 2008). Trait impulsivity has been broadly defined by the International Society for Research on Impulsivity as a predisposition toward rapid, unplanned reaction to external or internal stimuli without adequate regard to the negative consequences of these actions for themselves or others

(Moeller et al., 2001; Potenza & de Wit, 2010). Even though impulsivity is encompassed in many theories of personality and serves as a clinical criterion for several disorders in the DSM-5, including substance use disorders (American Psychiatric Association; 2013), there is no widely agreed upon consensus as to how it should be defined or measured 13

(Verdejo-Garcia et al., 2007). In an attempt to consolidate broad definitions and self- report measures of impulsivity, Whiteside and Lynam (2001) utilized factor analysis to identify four factors of impulsivity: negative urgency, lack of premeditation, lack of perseverance, and sensation seeking, which became the foundation for the Urgency,

Premeditation (lack of), Perseverance (lack of), Sensation Seeking Impulsive Behavior

Scale (UPPS). More recently, a 5th factor, positive urgency, was added (Cyders & Smith,

2007). Together, negative and positive urgency, the tendency to commit rash actions when experiencing strong negative or positive emotions respectively, form an overall urgency or “emotion-based rash action” disposition domain (Cyders et al., 2007; Cyders

& Smith, 2007). Researchers have demonstrated that negative urgency and positive urgency differentially relate to engagement in risky behaviors in individuals who report experiencing the corresponding mood state, positive or negative (Berg et al., 2015;

Cyders et al., 2007; Cyders & Smith, 2007).

Of the UPPS traits, positive and negative urgency are most strongly associated with substance use. Urgency distinguishes individuals with alcohol use disorders from controls and is consistently elevated in individuals with substance dependence (Berg et al., 2015; Coskupinar, Dir, & Cyders, 2013; Dolan, Bechara, & Nathan, 2008; Fischer et al., 2012; Settles et al., 2012; Verdejo-Garcia et al., 2007; Whiteside & Lynam, 2003;

Whiteside et al., 2005). Further, urgency is associated with and predictive of drinking quantity, drinking frequency, binge drinking, and experience of alcohol-related problems in clinical and non-clinical samples as young as elementary school age (Coskupinar, Dir,

& Cyders, 2013; Fischer et al., 2012; Gunn & Smith, 2010; Riley, Rukavina, & Smith,

2016; Robinson, Ladd, & Anderson, 2014; Settles et al., 2012; Sharma, Markon, & Clark, 14

2014; Verdejo-Garcia et al., 2007; Whiteside et al., 2005). In one large meta-analysis of clinical and nonclinical adult and adolescent populations, both positive and negative urgency were associated with problematic alcohol use, while negative urgency was associated with drinking quantity, drinking frequency, dependence symptoms, and binge drinking, and positive urgency was predictive of overall use (Coskupinar, Dir, & Cyders,

2013).

With regard to college student populations, both negative and positive urgency are related to many alcohol use factors, including: total alcohol consumption; average weekly use; frequency of use; quantity of use; binge drinking; problematic alcohol use; and negative drinking consequences, such as driving while intoxicated and blackout drinking

(Adams et al., 2012; Curcio & George, 2011; Cyders et al., 2009; Cyders & Coskunpinar,

2010; Dinc & Cooper, 2015; Dir, Karyadi, & Cyders, 2013; Emery et al., 2014; Fischer

& Smith, 2008; Grimaldi, Napper, & LaBrie, 2014; Kaiser et al., 2012; LaBrie et al.,

2014; Pearson & Henson, 2013; Treloar et al., 2012; Wray et al., 2012). Further, negative urgency is also related to problematic drinking as measured by the Alcohol Use Disorder

Identification Test (AUDIT; Saunders et al., 1993) in college students (r = .39; Karyadi,

2013). Positive urgency has also been shown to relate to substance use correlates independent of the other UPPS impulsivity facets and accounted for unique variance in frequency of drinking/drunkenness and experience of alcohol related problems, over and above frequency and intensity of emotional experiences (Cyders et al., 2007; Cyders &

Coskupinar, 2010).

The predictive role of both negative and positive urgency for substance use facets has also been demonstrated, with both negative and positive urgency measured at the 15

beginning of freshman year predicting drinking quantity at the end of freshman year

(Settles, Cyders, & Smith, 2010); positive urgency at the beginning of freshman year predicting increased illegal drug use, drinking quantity, and negative outcomes of drinking at the end of freshman year (Zapolski, Cyders, & Smith, 2009); and, in female college students, negative urgency was predictive of symptoms of alcohol use disorders 3 months later (Stojek & Fischer, 2013). The urgency traits measured in elementary school children, adolescents, and college students have been shown to relate to and predict future alcohol and drug use (Cyders et al., 2009; Fischer et al., 2012; Gunn & Smith,

2010; Kaiser et al., 2016; Pang et al., 2014; Riley, Rukavina, & Smith, 2016; Settles,

Cyders, & Smith, 2010; Settles, Zapolski, & Smith, 2014; Stojek & Fischer, 2013;

Zapolski, Cyders, & Smith, 2009).

Urgency is also significantly related to self-reported substance craving in response to substance-related cues in college students (Karyadi, 2013; Pavlick, 2007), and negative urgency has been shown to be related to more positive implicit associations about alcohol after exposure to a negative mood condition (Treloar & McCarthy, 2012). In sum, both positive and negative urgency are strongly and consistently related to alcohol use correlates and appear to play a predictive role in the development of alcohol problems.

Although studies reviewed above suggest that impulsivity and urgency predict future substance use, the relationship between substance use and impulsivity appears to be bidirectional in nature. Neurotoxic effects of substance use in frontal, limbic, and insular regions as well as disruptions within the striatal dopamine system have been found to be related to both self-reported and behavioral measures of impulsivity

(Bechara, 2003; Crews & Nixon, 2009; Everitt & Robbins, 2005; Goldstein & Volkow, 16

2002; Heinz et al., 2014). Nevertheless, as reviewed above, there is also considerable evidence to suggest a role of impulsivity, and urgency in particular, as a risk factor for problematic substance use (de Wit, 2009; Everitt & Robbins, 2005; Goldstein & Vokow,

2002; Jentsch & Taylor, 1999; Verdejo-Garcia, Lawrence, & Clark, 2008).

A potential limitation in existing literature is that neuroticism and urgency are both related to alcohol use and misuse and are also related to each other. Both positive and negative urgency load positively on neuroticism and negatively on the conscientiousness and agreeableness domains of the five-factor model, consistent with the pattern of Big Five personality traits associated with substance use (Cyders et al.,

2007; Cyders & Smith, 2008; Settles et al., 2012). Despite the positive loadings of urgency on neuroticism, there is evidence suggesting that urgency is a distinct trait from neuroticism, with the relationship between urgency and substance use remaining even after controlling for negative affect/neuroticism (Cyders & Coskupinar, 2010; Fischer et al., 2007; Kaiser et al., 2012; Spillane & Smith, 2007). That said, few studies examining the relationship between urgency traits and alcohol factors have controlled for neuroticism, which is also consistently related to and predictive of alcohol outcomes.

Urgency and Rash Action

Beyond problematic substance use, positive and negative urgency also relate to self-reported engagement in rash actions more broadly, including compulsive buying behaviors and aggression (Berg et al., 2015; Billieux et al., 2007; 2008a; 2008b; 2010;

Cyders & Smith, 2008; Deckman & DeWall, 2011; Settles et al., 2012; Zapolski, Cyders,

& Smith, 2009). Rash action is the term given to behaviors that an individual engages in when experiencing heightened emotional states and thus should be related to elevated 17

urgency (Cyders & Smith, 2008). Strong emotional experiences may lead some individuals to engage in rash actions without consideration of the negative consequences of their behaviors in order to reduce, regulate, escape, or avoid the experience of negative emotions and to alleviate distress, consistent with the definition of negative urgency

(Berg et al., 2015; Billieux et al., 2010; Cooper, Agocha, & Sheldon, 2000; Cyders &

Smith, 2008; Cyders et al., 2010; Fischer, Anderson, & Smith, 2004; Selby, Anestis, &

Joiner, 2008; Thorberg & Lyvers, 2006). On the other hand, individuals with elevated positive urgency may engage in rash actions in order to enhance positive emotions or to obtain positive reinforcement or reward (Berg et al., 2015; Cyders et al., 2010). As expected, researchers have found that urgency is elevated in clinical disorders highly comorbid with substance abuse and characterized by rash action, including borderline personality, suicidality, self-harm behavior, eating disordered behaviors, Attention-

Deficit Hyperactivity Disorder (ADHD) hyperactivity and impulsivity symptoms, depression, and anxiety symptoms (Anestis, Selby, & Joiner, 2007; Anestis et al., 2011;

Berg et al., 2015; Biederman et al., 2006; Dir, Karyadi, & Cyders, 2013; Fischer &

Smith, 2008; Jacob et al., 2010; Lee et al., 2011; Marmorstein, 2013; Molina et al., 2007;

Whiteside et al., 2005). Importantly, both self-reported urgency and impairments on behavioral measures of impulsivity are associated with these clinical presentations, similar to results in individuals with substance use disorders, suggesting that impulsivity traits may serve as an endophenotype signaling increased vulnerability of at-risk populations to rash action (Cyders & Smith, 2008; Ernst et al., 2006; Marmorstein, 2013).

The urgency traits are also related to self-reported gambling behavior, which is highly comorbid with substance use, in clinical, community, and college student samples 18

(Cyders & Smith, 2008; Cyders et al., 2007; 2010; Fischer & Smith, 2008; Fuentes et al.,

2006; MacLaren et al., 2011; Petry 2001; Petry, Stinson, & Grant, 2005; Smith et al.,

2007; Whiteside et al., 2005). Problematic gambling does not involve the administration of a substance that can lead to changes at the neural level and evidence suggests a shared genetic vulnerability for pathological gambling and problematic substance use; therefore, studying its correlates can provide useful information in understanding the pathways to risky behaviors and how they relate to trait impulsivity and urgency specifically

(Bechara, 2003; Potenza, 2008; Slutske et al., 2000; Verdejo-Garcia, Lawrence, & Clark,

2008).

Measurement of rash action: Self-report or behavior? While there is a clear association between the urgency trait and rash action, including substance use, most of the studies that have examined this relationship have examined self-reported rash actions and self-reported risky behavior engagement, without measuring actual engagement in risky behavior. Self-report measures of impulsivity and engagement in rash action tap into trait-like patterns of behavior, including those that involve emotionally relevant stimuli and/or risk; however, self-report measures may not be an accurate depiction of an individual’s actual behavior in a given situation (Cyders & Coskupinar, 2011). In contrast, behavioral measures are designed to measure tendencies and specific cognitive processes in a specific situation, such as during a particular emotion state (Cyders &

Coskupinar, 2011).

The Iowa Gambling Task (IGT; Bechara et al., 1994) is a widely-used behavioral measure of risky/impulsive decision-making, designed to measure emotion-based decision making involving the ability to consider future consequences of actions, and has 19

been examined extensively in relation to substance use (Bechara et al., 2005; Li et al.,

2010). Research findings suggest that the beginning and the end of the IGT utilize distinct cognitive processes, with the first 40 trials considered decision-making under ambiguity and the last 40 trials considered decision-making under risk, with decisions guided by signals for emotional representations of prior experiences with reward and punishment, or somatic markers (Bechara, 2004; Brand, Labudda, & Markowitsch, 2006;

Noel et al., 2007; Verdejo-Garcia, Perez-Garcia, & Bechara, 2006). In one large meta- analysis of clinical, college, and adolescent populations, researchers found that broad alcohol use, both problematic and nondeviant, was associated with IGT performance

(r=.41) (Sharma, Markon, & Clark, 2014). Individuals who abuse substances, including alcohol, make more disadvantageous choices on the IGT when compared to controls

(Barry & Petry, 2008; Bechara et al., 2001; Bechara & Martin, 2004; Dolan, Bechara, &

Nathan, 2008; Salgado et al., 2009). Researchers have found IGT performance is related to adolescent and college student binge drinking (Goudriaan, Grekin, & Sher, 2007; Xiao et al., 2009; 2013). Furthermore, on behavioral measures of impulsivity, including the

IGT, adolescents demonstrate deficits across measures that predict substance use, with impaired IGT performance well documented (Cauffman et al., 2010; Hooper et al., 2004;

Nigg et al., 2006; Overman et al., 2004).

Notably, within the substance abuse literature, very few studies have examined the relationship between self-reported impulsivity, including urgency, and behavioral measures of impulsivity such as the IGT. Outside of the substance use literature, researchers have generally found low to very low associations between self-report and behavioral impulsivity measures (Sharma, Markon, & Clark, 2014). That said, some 20

studies have found that trait impulsivity is associated with riskier IGT performance, particularly on the final block of trials, in undergraduate populations (Franken et al.,

2008; Suhr & Tsanadis, 2007; Sweitzer, Allen, & Kaut, 2008). The same is found in examination of the relationship between urgency specifically and other behavioral impulsivity tasks in nonclinical populations, with largely small and inconsistent findings

(Bayard, Raffard, & Gely-Nargeot, 2011; Billieux et al., 2010; Cyders & Coskupinar,

2011; Wilbertz et al., 2014). In substance using populations, urgency was related to disadvantageous performance on the IGT and even eliminated the main effect of substance dependency status on IGT performance when entered, suggesting that urgency scores account for impaired IGT performance in this sample (Dolan, Bechara, & Nathan,

2008). However, none of these studies looked at the associations between self-reported impulsivity/urgency and behavioral performance on impulsivity measures while participants were within a heightened emotion state, which is central to the definition of urgency.

Self-reported impulsivity and behavioral impulsivity measures may serve to describe different components of the same broad domain or share important overlap within a common neural system (Sharma, Markon, & Clark, 2014). In a large meta- analysis, Sharma and colleagues (2014) found that behavioral measures and self-report measures of impulsivity each contributed unique variance to the prediction of daily life variables, such as substance use, despite low relationships with each other. Therefore, it is important that researchers utilize both self-report and behavioral measures of impulsivity when considering risk factors for problematic daily life behaviors such as substance use and abuse. 21

Neural mechanisms of impulsivity, urgency, and rash action. Neuroscience models and neuroimaging research provide further evidence for the relationship between trait impulsivity/ urgency, behavioral impulsivity task performance, and substance use variables, given their overlapping neural substrates. In brief, shared neural systems include: impulsive/reward system (ventral striatum and nucleus accumbens), avoidant system (amygdala), prefrontal inhibitory system (vmPFC/orbitofrontal cortex, dorsolateral prefrontal cortex (dlPFC), and anterior cingulate cortex (ACC), and the interoceptive system (insula) (Cardinal et al., 2002; Chambers & Potenza, 2003; Ernst,

Pine, & Hardin, 2006; Luna & Sweeney, 2004; Miller, 2000; Nelson et al., 2005;

Steinberg, 2007; Verdejo-Garcia, Lawrence, & Clark, 2008; Wager et al., 2008).

Impulsive behavior, including substance use, is theorized to be the result of a developed impulsive system coupled with immature avoidant and inhibitory systems. Individual differences determine the degree to which affective states influence impulsive and inhibitory processes; however, generally, strong affective states are found to tax the inhibitory systems, thus impacting rational decision-making and subsequent risky behaviors, including substance use (Baumeister, 2014; Baumeister & Vohs, 2007;

Chester, 2016; Cyders & Smith, 2008; Gray, Braver, & Raichle, 2002). These behaviors are likely to be highly reinforcing by either reducing the distress of strong negative emotions or reinforcing strong positive emotion states (Cyders & Smith, 2008; Kornefel,

2002; Yuen & Lee, 2003).

Trait urgency has been conceptualized as a disparity between increased approach responding to emotion cues along with reduced inhibitory system activation (Albein-

Urios et al., 2013; Cyders et al., 2014; 2015; Joseph et al., 2009; Lewis & Todd, 2007; 22

Smith & Cyders, 2016). These findings suggest that urgency may serve as the crucial link between impulsive behaviors and poor emotion regulation, given that it involves risky behavior in response to strong emotion states. Neuroimaging studies during behavior tasks of impulsivity, including the IGT, have suggested involvement of these same neural regions, with performance on the last half involving more insular activations (Bari &

Robbins, 2013; Li et al., 2010; Mohr, Biele, & Heekeren, 2010; Sharma, Markon, &

Clark, 2014).

Despite the fact that correlational, longitudinal, and neuroscience evidence supports the relationship between substance use and urgency, the underlying mechanisms remain largely unclear. The few neuroimaging studies that have examined trait impulsivity, including urgency, in substance users have generally implicated these same neural regions; however, most did not include assessment of how an individual behaves during a heightened emotion state (Albein-Urios et al., 2013; Asensio et al., 2015;

Moreno-Lopez et al., 2012). Urgency may serve as a mechanism underlying impaired behavioral task performance in substance abusers and those at-risk for substance abuse; however, few studies have looked at trait impulsivity alongside behavioral task performance. In one study of healthy adults, urgency was negatively related to reduced frontal activation during behavioral task performance, but only in participants with low urgency (Wilbertz et al., 2014). In another study, greater urgency was associated with increased insula and decreased OFC/vmPFC activation during the IGT in both adolescent binge drinkers and never drinkers (Xiao et al., 2013). These studies indicate that urgency is related to neural activations in these same regions during behavioral task performance; 23

however, as urgency involves the tendency to act rashly in the face of strong emotions, it is important to take into consideration the role of cue exposure and/or affective states.

Few studies have examined the neuroimaging correlates of urgency as it relates to affective states or salient cues, with largely inconsistent results. For example, among social drinkers, negative urgency related to increased right lateral OFC and left amygdala activations during exposure to negative images versus neutral images and mediated the relationship between neural activations and self-reported risky behaviors, including substance use (Cyders et al., 2015). For substance cues specifically, Cyders and colleagues (2014) found that, using an olfactory alcohol cue with social drinkers, negative urgency related to bilateral increases in vmPFC activations and mediated the relationship between these neural activations and alcohol craving and problematic alcohol use. In an undergraduate sample, Chester and colleagues (2016) found that, when presented with alcohol images, negative urgency related to activations in the caudate nucleus but not lateral prefrontal cortex. Others have found that negative urgency is positively related to greater left-frontal EEG activity in response to alcohol cues in unselected undergraduate students (Gable, Mechin, and Neal, 2015; Mechin, Gable, &

Hicks, 2016). Despite these inconsistencies, it remains clear that frontal regions are strongly implicated in urgency, substance use, and response to salient cues. Further, given these results, it is likely that urgency serves as a mediator between neural activations and cue-induced mood as well as self-reported behavioral correlates, including substance use.

However, given the limitations of relying only on self-report, studies should experimentally manipulate mood state in order to examine the effects of manipulation on observable behavioral task performance (Cyders et al., 2010). 24

The Role of Mood State in Urgency and Impulsivity

Studies that have examined the effect of cues or mood manipulation on behavioral task performance among substance users have found that, generally, negative affect is associated with more risky and impulsive behavior. For example, negative affect was associated with riskier IGT performance in a nonclinical sample and self-reported negative mood was positively related to risky deck (Deck B) selections and negatively related with non-risky deck (Deck D) selections (Buelow & Suhr, 2013; Suhr &

Tsanadis, 2007). This is consistent with other research indicating that the experience of intense emotions and emotionally arousing stimuli negatively affects behavioral task performance, specifically decision-making (Bechara, 2004; 2005; Dolan, 2007; Shiv,

Loewenstein & Bechara, 2005; Verbruggen & De Houwer, 2007).

As mentioned above, the subjective emotional experience of craving is associated with neural regions responsible for effective executive functioning. Studies have consistently demonstrated that alcohol cue exposure elicits craving in both clinical, social, and high-risk alcohol users and that this reactivity to substance cues negatively impacts executive functioning (Fox et al., 2007; Kareken et al., 2004; Mason et al., 2008;

Noel et al., 2007; Stormark et al., 1995). Others found that individuals with higher negative urgency experienced greater mood change and craving following a negative mood induction and alcohol prime (VanderVeen et al., 2016). In another study, polysubstance users (including alcohol) performed significantly worse than controls on the IGT in the face of drug-related or positive IAPS images (Fernandez-Serrano et al.,

2011). Hollett (2015) compared low-risk and high-risk young adult drinkers’ performance on the Balloon Analogue Risk Task (BART; Lejuez et al., 2002) and the 25

IGT in the face of alcohol cues and found that, although there were no overall performance in the groups, performance was related to baseline craving. Research clearly suggests an impact of affect and/or salient-cue exposure on behavioral decision-making measures, including the IGT. Thus, the inconsistent relationship between urgency and behavioral task performance generally may be due to the lack of an emotional context during task performance.

Limitations of the Current Literature

Urgency is clearly associated with substance use, craving, and with rash action broadly, and evidence exists to substantiate its role as a predisposing risk factor for impulsive behaviors such as substance use. That said, research that has examined the relationship of urgency to rash action has largely relied on self-reported tendencies rather than observable behavioral performance, such as on risky decision-making tasks, on which clinical and non-clinical alcohol users demonstrate impaired or diminished performance. Even though trait and behavioral measures of impulsivity share neural substrates and both strongly and consistently relate to substance use, the link between the two remains unclear and inconsistent, which may be explained by the lack of an affective context when investigating their relation (Sharma, Markon, & Clark, 2014).

Given the definition of urgency, it is expected that substance users with elevated urgency would be more likely to demonstrate decision-making impairments in the face of strong negative or positive emotions. While no studies have examined the relationship between urgency and behavioral outcomes with manipulated affect in a clinical sample, researchers have found that, in community alcohol users, those with greater negative urgency in a negative mood condition reached greater peak breath alcohol concentration 26

on a self-administration task than those with lower urgency (2=0.48), showed increased intoxication over time (2=0.62), and demonstrated more alcohol seeking (2=0.54), effects not present in the neutral mood condition (VanderVeen et al., 2016). Similar findings were demonstrated in a study by Cyders and colleagues (2010) in a sample of unselected college students. In their sample, positive urgency predicted beer consumption following a positive mood induction when compared to a neutral mood induction. In a sample of undergraduates who endorsed previous alcohol consumption, Chester and colleagues (2016) found that, during a Go/No-Go task with either positive, negative, or neutral IAPS images in the background, groups performed similarly, despite neuroimaging findings. However, on a different behavioral task, Cyders and colleagues

(2010) found that college students with elevated urgency demonstrated increased impulsive decision-making on the BART compared to those low on urgency when in a positive mood condition (story mood induction plus imagination mood induction). In a different sample of healthy volunteers, Billieux and colleagues (2010) found that poor response inhibition on the Emotion Stop-Signal Task (Logan, 1994), which used human faces with either joy, neutral, or sadness emotional expressions, was predictive of impulsive decision-making on the IGT (total score and last 40 trials), which related significantly to both negative urgency and self-reported problematic behavioral outcomes

(excessive phone use, internet use, and compulsive buying). Additionally, impulsive decision-making on the second part of the IGT predicted negative urgency and indirectly predicted problematic behaviors through its effect on negative urgency, providing further support for the link between negative urgency and impulsive behaviors whether on behavioral tasks or in real-life (Billieux et al., 2010). 27

The Present Study

In the few studies that have utilized cue exposure or mood exposure/induction, researchers have found that individuals high in urgency tend to engage in more risky or impulsive behaviors following the manipulation, and that this is likely associated with alterations in networks within the prefrontal regions. In the present study, we sought to expand upon this literature by investigating the relationship between both positive and negative urgency, after controlling for neuroticism, and performance on an impulsive decision-making task (IGT) during both positive and negative mood conditions in a sample of undergraduates who indicated high-risk drinking behavior. Further, we sought to clarify the role of craving on behavioral task performance in those with elevated trait urgency.

The first aim was to replicate existing literature demonstrating the relationship of urgency traits to substance use generally. We hypothesized that greater urgency, whether negative and positive, would relate to problematic substance use variables (AUDIT total score, greater monthly and weekly frequency of alcohol use, average number of drinks consumed on drinking occasion, greater drug use, and younger age of first use) after controlling for neuroticism.

The second aim was to further examine the relationship of urgency to a behavioral measure of impulsivity, given the inconsistent findings in existing literature. We hypothesized that individuals with greater urgency, after controlling for neuroticism, would demonstrate greater impulsivity on the IGT, particularly the last 50-100 trials.

The final aim was to examine whether the positive and negative urgency traits would be differentially related to behavioral impulsivity and craving in manipulated 28

mood contexts. We hypothesized that negative urgency would relate more strongly to impulsive decision-making on the IGT in the negative manipulated mood context and positive urgency would relate more strongly to impulsive decision-making on the IGT in the positive manipulated mood context. We also explored the relationship between the urgency traits and self-reported craving in the corresponding manipulated mood context.

Chapter 2: Methods

Participants

Participants were 159 undergraduates (mean age = 19.44; range = 18-47), enrolled in introductory psychology courses in which they could earn course credit. Of the 159 participants, 84 identified as female; 150 identified as Caucasian; 100 identified as freshman and 34 identified as sophomores. Participants were pre-screened for age and

English proficiency and individuals who endorsed binge drinking on a measure of high- risk drinking were invited to participate; 191 individuals signed up to participate in the study. Individuals who reported any history of neurological illness/injury (e.g. seizures, moderate to severe traumatic brain injury, brain tumors) (N= 4) and who did not meet study criteria for high risk drinking at the time of study participation (N= 28) were not included in final analyses, resulting in the final sample of 159. Individuals were also assessed for Attention-Deficit Hyperactivity Disorder symptoms via the Adult ADHD

Self-Report Scale-v1.1 (ASRS-v1.1); however, they were not excluded based on symptom report. A total of 29 participants (18.2%) reported symptoms highly consistent with ADHD according to the ASRS-v1.1 scoring instructions (Adler, Kessler, & Spencer,

2003). See Table 1 for detailed demographics.

With respect to substance use variables, average AUDIT total score was 8.84

(SD=4.56); average age of first alcohol use was 15.56 years (SD= 1.73); on average individuals reported consuming alcohol 1.45 days per week (SD= 0.95) and 6.67 days per month (SD= 7.03); the average number of drinks consumed per drinking occasion was

5.77 (SD= 5.37); and the average number of hard drugs tried was 1.27 (SD=1.87). 30

Table 1

Demographic Data by Condition Demographic Full Sample Positive Neutral Negative Mean Age (SD) 19.44 (2.91) 19.20 (1.15) 19.52 (4.10) 19.64 (2.83) Gender Male 47.2% 49.1% 44.2% 48% Female 52.8% 50.9% 55.8% 52% Ethnicity Caucasian 94.3% 93% 100% 90% African 2.5% 3.5% 0% 4% American Asian .6% 1.8% 0% 0% American Other 2.5% 1.8% 0% 6% Level of Education First year 62.9% 64.9% 65.4% 58% Second year 21.4% 21.1% 21.2% 22% Third year 10.1% 10.5% 7.7% 12% Fourth year 5.7% 3.5% 5.8% 8%

Study inclusion required a positive response to binge drinking (six or more drinks on one occasion) on item #3 of the AUDIT: 54.7% reported binging “less than monthly,” 25.2% reported binging “monthly,” and 20.1% reported binging “weekly.”

Measures

Copies of non-copyrighted tests for all tests administered in the study are included in Appendix A; only measures relevant to study hypotheses are described here.

Alcohol Use Disorders Identification Test-Self Report Version (AUDIT). The

AUDIT (Saunders et al., 1993) is a 10-item screening instrument for past year excessive, hazardous, and/or harmful alcohol use, as well as alcohol dependence. The AUDIT provides an accurate measure of alcohol risk across genders, age, and cultures, with 31

sensitivities and specificities superior to those found in other self-report alcohol use measures (Reinert & Allen, 2002; Saunders et al., 1993; Allen et al., 1997). In college student populations, the AUDIT has demonstrated good discriminability and accurate detection of alcohol use diagnoses based on DSM criteria, with high sensitivity (0.94) and moderate specificity (0.66) (Fleming, Barry, & MacDonald, 1991). The instrument demonstrates internal consistency across samples and settings in the .80s as well as good two-week test-retest reliability (.92) among university students (Kokotailo et al., 2004;

Lennings, 1999; Reinert & Allen, 2002). For the present study, the AUDIT was used at prescreen to recruit at-risk individuals who endorsed “less than monthly,” “monthly,”

“weekly,” or “daily or almost daily” binge drinking on item 3, “how often do you have six or more drinks on one occasion?” The AUDIT was repeated at time of study participation to ensure that participants still endorsed high-risk binge drinking following the same criteria at prescreen; those who did not endorse binge drinking on AUDIT item

3 at time of study participation (N= 28) were excluded from analyses. AUDIT total score was used as one measure of problematic substance use as it related to positive and negative urgency (α= 0.751 in the current sample).

National Institute on Drug Abuse-modified Alcohol, Smoking and Substance

Involvement Screening Test, Version 2.0 (NIDA-modified ASSIST V2.0). The NIDA- modified ASSIST (National Institute on Drug Abuse, 2012) consists of 8 items regarding frequency, cravings, and consequences of substance use. The NIDA-modified ASSIST was adapted from the World Health Organization (WHO) Alcohol, Smoking and

Substance Involvement Screening Test (ASSIST), Version 3.0 (WHO, 2010). For the present study, questions from the NIDA-modified ASSIST V2.0 were included in the 32

demographic questionnaire used as one measure of problematic substance use.

Specifically, endorsement of use of cannabis, cocaine, prescription stimulants, methamphetamine, inhalants, sedatives or sleeping pills, hallucinogens, street opioids, or other specified drugs was totaled to examine number of hard drugs tried as it related to positive and negative urgency.

Problematic alcohol use. For the present study, the following questions were included in the demographic questionnaire as measures of problematic substance use: “At what age did you have your first alcoholic beverage beyond a sip or taste?” “On average, how many days did you consume alcohol in the past 30 days?” “On average, how many days of the week do you consume alcohol?” and “On average, how many alcoholic drinks do you consume per drinking occasion?”

NEO Five-Factor Inventory-3 (NEO-FFI-3) neuroticism. The NEO-FFI-3

(Costa & McCrae, 2010) is a widely-used personality inventory designed to measure the five major factors of personality: extraversion, agreeableness, conscientiousness, openness to experience, and neuroticism (Digman, 1990; McCrae & John, 1992).

Although the entire NEO-FFI-3 was administered, only the 12-item neuroticism scale was used in the present study. The neuroticism scale has been shown to have adequate internal consistency (ranging from .79 in middle school aged children to .86 in adults) and two-week test reliability (.89 in college students) (Robins et al., 2001). For the present study the NEO-FFI-3 neuroticism scale score, excluding the impulsivity facet, was used to control for neuroticism in analyses examining the relationship of the urgency traits to both substance use variables and decision-making performance on the IGT (α=

0.852 in the current sample). 33

UPPS-P Impulsive Behavior Scale (UPPS-P). The UPPS-P (Lynam et al.,

2007; Whiteside & Lynam, 2001) is a 59-item self-report scale designed to measure five impulsivity dimensions of rash action including: lack of planning, lack of perseverance, negative urgency, positive urgency, and sensation seeking. The five scales have demonstrated good convergent validity across assessment methods, good discriminant validity, and strong relationships to external correlates (Cyders & Smith, 2007; Smith et al., 2007). Estimates of internal consistency reliability for each scale are greater than

0.80, with some studies finding internal consistencies as high as 0.90 for negative urgency and 0.94 for positive urgency in undergraduate samples (Dir, Karyadi, & Cyders,

2013). The UPPS-P negative and positive urgency scale scores were used in the present study (α= 0.940 positive, α = 0.906 negative, in the current sample).

Positive and Negative Affect Scale (PANAS). The PANAS (Watson, Clark, &

Tellegen, 1988) is a 20-item self-report measure consisting of two 10-item mood scales, positive and negative. Total scores for the 10 positive and 10 negative mood items were calculated separately, with higher scores indicating greater positive or negative mood state. High internal consistency has been found for both scales (Buelow & Suhr, 2013;

Crawford & Henry, 2004; Watson, Clark, & Tellegen, 1988). Watson, Clark, and

Tellegen (1988) reported good test-retest reliability two different occasions approximately 8 weeks apart in a college student population and approximately one week apart in a clinical sample. For the present study, the PANAS was administered prior to and following visual mood manipulation to ensure the manipulation procedure elicited the desired affective state (α= 0.887; 0.902; 0.902; 0.912 across the 4 time points for 34

positive affect, α = 0.796; 0.882; 0.832; 0.835 across the 4 time points for negative affect, in the current sample).

The Affect Grid. The Affect Grid (Russel, Weiss, & Mendelsohn, 1989) is a single-item scale in the form of a 9x9 grid designed to measure affect along two dimensions: valence (pleasure vs. displeasure) and arousal (high arousal vs. low arousal).

Participants were asked to place a single mark in one box within the grid, indicating their current mood. The Affect Grid has good inter-rater reliability (0.98 for valence; 0.97 for arousal) and good convergent validity with the PANAS (Russel, Weiss, & Mendelsohn,

1989). For the present study, the affect grid was administered alongside the PANAS prior to and following the visual mood manipulation, as another test of whether the manipulation elicited the desired affective state.

Alcohol Craving Questionnaire-Short Form-Revised (ACQ-SF-R). The

ACQ-SF-R (Singleton, Tiffany, & Henningfield, 2000; 2004) is a 12-item self-report measure designed to measure craving for alcohol. A general craving index is derived by summing all items (total ACQ-SF-R score) and dividing by 12. The ACQ-SF-R correlates strongly with the 47-item Alcohol Craving Questionnaire (ACQ-NOW;

Singleton, Tiffany, & Hennington, 2004) from which it was derived. The ACQ-SF-R has demonstrated moderate to strong reliability (over 0.90) and validity (Drobes & Thomas,

1999; Frahm, 2017). For the present study, the ACQ-SF-R total score was used as a measure of self-reported craving and examined in relationship to positive and negative urgency in the corresponding manipulated mood context (α= 0.850; 0.866 over 2 time points in the current sample). The ACQ-SF-R was administered at baseline and immediately following mood manipulation procedure. 35

Iowa Gambling Task (IGT). The IGT (Bechara, 2005; 2007; Bechara et al.,

1994; 2000) is a computerized behavioral task designed to measure real-world emotion- based decision making. Individuals are given $2000 at the beginning of the task and are given 100 trials to maximize their profit by choosing cards from one of four decks (A, B,

C, & D). Decks A and B are considered “disadvantageous” and decks C and D are

“advantageous” (Bechara et al., 2000; Bowman, Evans, & Turnbull, 2005) based on net loss and gain. The task is designed to measure decision-making under risk and under ambiguity. Participants are unaware of the relative advantages/disadvantages of each deck upon task initiation. In the present study, the computerized IGT was administered during visual mood induction to assess decision-making performance during a heightened affective state. Since research suggests a split in performance between the first half

(decision-making under ambiguity) and the last half (decision-making under risk) trials, the present study analyzed performance on the last half of IGT trials as it related to positive and negative urgency in the corresponding manipulated mood context.

Procedure

Individuals were recruited through the university online psychology subject pool.

Once individuals were pre-screened for age (18 and older), English proficiency, and high- risk drinking (Item #3 AUDIT), those meeting criteria viewed a brief description of the study and were invited to participate to earn course credit. Participants signed up online for available time slots and attended one individual session.

Upon arrival, participants completed informed consent procedures, followed by computerized demographic information, medical/psychological history, substance use history, and self-report questionnaires (ASRS-v1.1; AUDIT; NEO-FFI-3; UPPS-P). 36

Participants then completed the mood and craving questionnaires (ACQ-SF-R, PANAS, and the Affect Grid) on paper. Participants were randomly assigned to either positive, negative, or neutral visual mood induction condition. Visual mood induction was via images from the International Affective Picture System (IAPS; Lang, Bradley, &

Cuthbert, 2008), the most widely used stimulus set of images based on models of emotion that has been demonstrated as an effective elicitor of emotions in meta-analytic studies

(Lench, Flores, & Bench, 2011) as well as substance use studies (Chester et al., 2016;

Cyders et al., 2014; 2015; Treloar & McCarthy, 2009; 2012). For the present study, participants viewed 30 images in each mood condition on a computer screen, with each image displayed for 2 second intervals. Images were derived from a prior study by

Cyders and colleagues (2015), who found a main effect of mood and an interaction between mood condition and ratings on the Affect Grid. The technical manual for the

IAPS images indicates that there are significant gender differences in valence and arousal ratings for many of the images (Lang, Bradley, Cuthbert, 2008). As such, some images from the study by Cyders and colleagues (2015) were replaced and matched for valence and arousal by gender. See Appendix A for a list of specific images used in the present study. Once participants had viewed all 30 images, mood and craving questionnaires were re-administered. Following initial exposure to the assigned mood condition images and completion of the mood and craving questionnaires, the images continued to be displayed in 2-second intervals throughout the remaining session. Participants were given instructions for the computerized IGT decision-making task, which was administered on an adjacent computer screen while mood condition images continued to be displayed.

Prior to trial 50 of the IGT, mood questionnaires (PANAS and the Affect Grid) were re- 37

administered, and then the remaining 50 trials were administered. Upon completion of the

IGT task, participants completed mood ratings (PANAS and the Affect Grid) a final time.

Participants also completed one 5-point Likert rating of their awareness of the IAPS images during cognitive task performance. Upon completion of the entire study, each participant was debriefed and awarded credit for participation.

Analyses

To assess the effectiveness of the IAPS visual mood manipulation, a repeated measures ANOVA was conducted to analyze positive and negative affect as measured by the PANAS over the four time points in the three assigned mood conditions. Post-hoc analyses were conducted to determine level of group differences when repeated measures

ANOVA was significant.

Prior to hypothesis testing, examination of histograms, Q-Q plots, and Shapiro-

Wilk tests were conducted for all study variables, and outliers were removed from analyses. A critical value of 3.29 as suggested by Kim (2013) was used as a cut-off for non-normality given our medium sample size. See Appendix B, Table 13 for detailed tests of normality and outliers. Assumptions of normality were violated for multiple substance use variables. Specifically, AUDIT total score, average days a month alcohol consumption, number of hard drugs tried, average number of consumed alcoholic beverages per drinking occasion, and pre- and post-manipulation craving were positively skewed. Additionally, AUDIT total score, average number of consumed alcoholic beverages per drinking occasion, number of hard drugs tried, and pre-manipulation craving were leptokurtic. As such, correlational analyses to address hypothesis #1 were conducted with both parametric and non-parametric procedures, which were similar 38

regarding significance of relationship effects; as a result, only the parametric results are reported below. Results of non-parametric correlational analyses are provided in

Appendix D, Table 14. For hypothesis #2, parametric correlational analyses were also conducted to assess the strength of the relationship between negative and positive urgency and decision-making performance, while controlling for trait neuroticism.

For hypothesis #3, two hierarchical multiple regression analyses were conducted to investigate whether an association between urgency traits and decision-making depended upon assigned mood condition (positive, neutral, negative). Prior to hypothesis testing, examination of assumptions was completed, including linearity of relationship, normal distribution of variables, no multicollinearity, and homoscedasticity. No assumptions were violated.

Finally, for exploratory hypothesis #4, two hierarchical multiple regression analyses were conducted to investigate whether an association between urgency traits and post-manipulation self-reported craving depended upon assigned mood condition

(positive, neutral, negative). Prior to hypothesis testing, examination of assumptions was completed, including linearity of relationship, normal distribution of variables, no multicollinearity, and homoscedasticity.

Chapter 3: Results

Group Differences

The three randomly assigned mood condition groups were not significantly different in age, F(2, 155) = .33, p = .72, gender F(2, 156) = .14, p = .87, ethnicity F(2,

154) = .42, p = .66, or level of education, F(2, 156) = .61, p = .54. See Table 1. With respect to substance use variables, groups did not differ on average AUDIT total score

F(2, 155) = 1.23, p = .30, average age of first alcohol use F(2, 151) = .20, p = .82, average days consumed alcohol a week F(2, 156) = .54, p = .58, average days consumed alcohol a month F(2, 153) = 2.31, p = .10, average number of drinks consumed per drinking occasion F(2, 151) = 1.90, p = .15, or average number of hard drugs tried F(2,

155) = 1.40, p = .25. Groups did not differ on negative urgency F(2,154) = 1.86, p = .16, positive urgency F(2, 154) = 2.05, p = .13, NEO-FFI-3 neuroticism F(2, 154) = 2.74, p =

.07, baseline PANAS negative affect F(2, 154) = .56, p = .57 or baseline PANAS positive affect F(2, 154) = .31, p = .74. See Tables 2 and 3.

Mood Manipulation Check

The visual mood induction was, in the short term, an effective mood manipulation, as suggested by a statistically significant interaction between time and condition for PANAS positive affect, F(3.82, 284.44) = 2.12, p = .05, and for PANAS negative affect, F(4.14, 328.86) = 5.54, p<.001. Upon further exploration, groups did not differ on positive, F(2, 149) = 0.98, p = 0.38, or negative, F(2, 149) = 0.19, p = 0.83, affect at time 1, as expected. There were significant group differences on positive affect,

F(2, 149) = 4.97, p = .01, and negative affect, F(2, 149) = 16.09, p < .001 at Time 2. 40

Table 2

Comparison of Conditions on Pre-Manipulation Measures Full Sample Positive Neutral Negative ANOVA Measure M SD M SD M SD M SD F p UPPS-P NU 28.38 7.38 27.59 7.77 27.73 7.06 30.16 7.16 1.68 .19

UPPS-P PU 27.40 8.26 26.43 7.72 26.60 7.88 28.94 8.84 1.95 .15 Neuroticism 23.03 7.98 23.84 8.46 20.94 7.37 24.78 7.39 1.68 .19 ACQ-SF-r 33.58 7.52 32.39 6.08 33.31 8.55 35.22 7.71 1.93 .15 PANAS PA 27.63 7.83 27.63 6.81 28.33 8.92 27.06 7.86 .42 .66 PANAS NA 14.06 4.46 13.96 4.32 13.73 4.70 14.59 4.49 .48 .62 ASRS-v1.1 1.75 1.68 1.63 1.52 1.63 1.74 2.01 1.79 .84 .43

Note: UPPS-P = Urgency, Perseverance (lack of), Premeditation (lack of), Sensation Seeking, Positive Urgency Impulsive Behavior Scale; NU = UPPS-P Negative Urgency; PU = UPPS-P Positive Urgency; Neuroticism = NEO Five Factor Inventory-3, Neuroticism Scale; ACQ-SF-r = Alcohol Craving Questionnaire Short-Form Revised; PANAS = Positive and Negative Affect Scale; PA = Positive Affect; NA = Negative Affect; ASRS-v1.1 = Adult ADHD Self-Report Scale, Version 1.1

Post-hoc tests showed that there was greater positive affect in the positive manipulated mood condition compared to the negative manipulated mood condition, p = .01, and that there was greater negative affect reported in the negative manipulated mood condition relative to the positive manipulated mood condition, p<.001, and the neutral mood condition, p<.001. Groups did not differ on positive, F(2, 149) = 1.09, p = 0.34, or negative, F(2,149) = 0.98, p = 0.38, affect at Time 3, at the start of IGT trial 50. Groups did not differ on positive, F(2,149) = 0.88, p = 0.42, or negative, F(2, 149) = 0.53, p =

0.59, affect at time 4. Results suggest the mood induction procedure was initially effective, as evidenced by significant group differences in positive and negative affect at time 2; however, this effect was not sustained beyond time 2. This suggests that the mood 41

induction was not successful at significantly impacting mood state for the duration of study participation.

Participants were also administered the Affect Grid at all four time points.

Consistent with the PANAS results, groups only differed on Affect Grid pleasure and arousal at time 2. See Appendix C for supplemental Affect Grid results. One reason for the short-term effectiveness of our mood induction was participants’ low awareness of the IAPS images during IGT task performance. Of our sample, only 1.3% reported being

“extremely aware,” 20.1% reported they were “moderately aware,” 21.4% reported they were “somewhat aware,” 22% reported being “not at all aware,” and 35.2% reported they were slightly aware of the IAPS images during the IGT task.

Hypothesis 1: Urgency and Self-Reported Substance Use

Negative and positive urgency were significantly positively related to one another, r(157) = .66, p < .001. Greater neuroticism was significantly related to higher scores on negative urgency, r(157) = .62, p <.001, and positive urgency, r(157) = .42, p

<.001. Greater neuroticism was associated with higher AUDIT total score, r(156) = .23, p

= .004, and endorsement of more hard drugs tried, r(156) = .23, p = .004.

Neuroticism was not significantly related to average number of days consumed alcohol a week, r(157) = .02, p = .80, age of first alcohol use, r(152) = -.04, p = .59, average days consume alcohol a month, r(154) = -.02, p = .86, or average number of drinks consumed on drinking occasion, r(152) = -.05, p = .56.

Table 3

Comparison of Conditions on Substance Use Variables Measure N All Positive Neutral Negative ANOVA Conditions M SD M SD M SD M SD F p AUDIT 158 8.72 4.31 9.33 4.78 8.04 4.06 8.73 3.94 1.23 .30 Total Days/Week 159 1.45 .95 1.49 .95 1.34 .99 1.53 .90 .54 .58 Days/Month 156 5.99 3.94 5.09 3.32 6.65 4.60 6.28 3.70 2.31 .10 Drug Use 158 1.22 1.77 .98 1.53 1.17 1.81 1.55 1.96 1.40 .25 Age First 154 15.55 1.48 15.51 1.58 15.66 1.44 15.48 1.43 .20 .82 Use Drinks/ 154 4.99 2.77 4.87 2.83 4.53 2.35 5.59 3.05 1.90 .15 Occasion Note: AUDIT = Alcohol Use Disorder Identification Test; Days/Week = average number of days a week consume alcohol; Days/Month = average number of days a month consume alcohol; Drug Use = number of hard drugs tried; Age First Use = age at which consumed more than a sip of alcohol; Drinks/Occasion = average number of drinks consumed on drinking occasion.

Pearson correlation coefficients were computed for the relationship between negative and positive urgency traits with substance use variables for which neuroticism was not significantly related. Partial correlation coefficients controlling for neuroticism were calculated to analyze the relationship between positive and negative urgency and substance use variables that were significantly related to neuroticism (AUDIT total score, number of hard drugs tried).

Higher negative urgency was associated with endorsement of consuming alcohol more days a week, r(157) = .18, p = .03; however, positive urgency was not, r(157) = .11, p = .17. Age of first use of alcohol was not significantly related to either negative urgency, r(152) = -.12, p = .15, or positive urgency, r(152) = -.15, p = .07. Additionally, 43

average days consumed alcohol in the past month was not significantly related to negative urgency, r(154) = .03, p = .74, or positive urgency, r(154) = .12, p = .15.

Further, average number of drinks consumed on drinking occasion was not significantly related to negative urgency, r(152) = .05, p = .55, or positive urgency, r(152) = .13, p =

.10. Higher scores on negative urgency were associated with more hard drugs tried, pr(155) = .28, p < .001, and were associated with greater AUDIT total score, pr(155) =

.16, p = .05, after controlling for neuroticism. Greater positive urgency was associated with more hard drugs tried after controlling for neuroticism, pr(155) = .28, p < .001, but not associated with AUDIT total score, pr(155) = .13, p = .10. See Tables 4 and 5.

Hypothesis 2: Urgency and Risky Decision-Making

IGT performance did not vary by manipulated mood condition, see Table 6.

Neuroticism was not associated with IGT risk, r(156) = -.03, p = .72. As such, Pearson correlations were computed to assess the relationship between negative and positive urgency and risky decision-making on the last half of the IGT, without controlling for neuroticism. Contrary to hypotheses, negative urgency was not significantly related to risky decision-making on the IGT, r(156) = .07, p = .42. Also contrary to hypotheses, positive urgency was not significantly related to risky decision-making on the IGT, r(146) = .11, p = .18. See Table 7.

Hypothesis 3: Relationship of Urgency to Decision-Making in Heightened Emotion

State

Simple correlations of negative and positive urgency and IGT performance within each of the mood conditions are reported in Table 7. A three-stage hierarchical multiple regression analysis was conducted to test the hypothesis that the relationship of negative 44

urgency and risky decision-making on the IGT was moderated by mood condition. In the first step, negative urgency was included and did not account for a significant amount of variance in IGT risk, R2 = .00, F(1, 156) = .66, p = .42. In the second step, mood conditions (positive and negative) were added to the model, with the neutral group serving as the reference group; mood condition did not account for significantly more variance than negative urgency alone, R2= .00, p = .93. Neither positive mood condition,  = .01; p = .95, nor negative mood condition,  = .03; p = .72 were significant predictors of IGT risk. Next, two interaction terms were computed for negative urgency by assigned mood condition, positive and negative. The interaction terms for negative urgency and assigned mood condition (positive, negative) were added to the regression model and did not account for significantly more variance than negative urgency and the two mood conditions, R2= .01, p = .59. Neither the interaction of negative urgency and negative mood condition,  = .04; p = .75, nor the interaction of negative urgency and positive mood condition,  = .12; p = .32, were significant predictors of IGT risk. See Table 8.

A three-stage hierarchical multiple regression analysis was also conducted to test the hypothesis that the relationship of positive urgency and risky decision-making on the

IGT was moderated by mood condition. In the first step, positive urgency was included and did not account for a significant amount of variance in IGT risk, R2 = .01, F(1, 156) =

1.84, p = .18.

Table 4

Pearson Product-Moment Correlations of Neuroticism & Urgency Traits with Substance Variables Scale AUDIT Days/ Days/ Drinks # Hard Drugs Age Totala Monthb Weekc Occasiond Triede First Usef Neuroticism .23** -.02 .02 -.05 .23** -.04 Negative .26*** .03 .18* .05 .36*** -.12 Urgency Positive .22* .12 .11 .13 .35*** -.15 Urgency Note: AUDIT = Alcohol Use Disorder Identification Test; Days/Week = average number of days a week consume alcohol; Days/Month = average number of days a month consume alcohol; Drug Use = number of hard drugs tried; Age First Use = age at which consumed more than a sip of alcohol; Drinks/Occasion = average number of drinks consumed on drinking occasion. Neuroticism = NEO Five Factor Inventory-3, Neuroticism Scale; UPPS-P = Urgency, Perseverance (lack of), Premeditation (lack of), Sensation Seeking, Positive Urgency Impulsive Behavior Scale; Negative Urgency = UPPS-P Negative Urgency; Positive Urgency = UPPS-P Positive Urgency an=156. bn=156. cn=159. dn=154. en=158. fn=154. *p < .05. ** p < .01 ***p < .001.

In the second step, mood conditions (positive and negative) were added to the model, with the neutral group serving as the reference group; mood condition did not account for significantly more variance than positive urgency alone, R2= .00, p = .96. Neither positive mood condition,  = .01; p = .95, nor negative mood condition,  = .03; p = .78, were significant predictors of IGT risk. Next, two interaction terms were computed for positive urgency by assigned mood condition, positive and negative. The interaction terms for positive urgency and assigned mood condition (positive, negative) were added to the regression model and did not account for significantly more variance than positive urgency and the two mood conditions, R2= .03, p = .10. 46

Table 5

Partial Correlations of UPPS-P Urgency Traits and Substance Variables Controlling for Neuroticism Control Variable Negative Positive Urgency Variable Urgency Neuroticism AUDIT Total .16* .10

Days/Month .05 .13

Days/Week .21* .11

Drinks Occasion .10 .17*

# Hard Drugs .28** .28** Tried Age First Use -.12 -.14

Note: AUDIT = Alcohol Use Disorder Identification Test; Days/Week = average number of days a week consume alcohol; Days/Month = average number of days a month consume alcohol; Drug Use = number of hard drugs tried; Age First Use = age at which consumed more than a sip of alcohol; Drinks/Occasion = average number of drinks consumed on drinking occasion. Neuroticism = NEO Five Factor Inventory-3, Neuroticism Scale; UPPS-P = Urgency, Perseverance (lack of), Premeditation (lack of), Sensation Seeking, Positive Urgency Impulsive Behavior Scale; Negative Urgency = UPPS-P Negative Urgency; Positive Urgency = UPPS-P Positive Urgency an=156. bn=156. cn=159. dn=154. en=158. fn=154. *p < .05. **p < .001.

The interaction of positive urgency and negative mood condition,  = -.10; p = .41, nor the interaction of positive urgency and positive mood condition,  = .14; p = .21 were significant predictors of IGT risk. See Table 9.

Table 6

IGT Performance by Condition Measure Full Sample Positive Neutral Negative N = 158 N= 57 N= 51 N= 50 M SD M SD M SD M SD IGT Risk 23.85 8.93 23.66 9.05 23.55 8.98 24.38 8.88 Note: IGT = Iowa Gambling Task. Groups did not differ on IGT Risk F(2, 155) = .13, p = .88.

Relationship of Urgency to Craving in Heightened Emotion State

A three-stage hierarchical multiple regression analysis was conducted to explore whether the relationship of positive urgency and post-mood manipulation craving would be moderated by mood condition. In the first step, positive urgency was included and accounted for a significant amount of variance in craving, R2 = .13, F(1, 155) = 23.18, p

< .001. In the second step, mood conditions (positive and negative) were added to the model, with the neutral group serving as the reference group; mood condition did not account for significantly more variance than positive urgency alone, R2= .03, p = .09.

Neither positive mood condition,  = -.02; p = .84, nor negative mood condition,  = .16; p = .07, were significant predictors of post-manipulation craving. Next, two interaction terms were computed for positive urgency by assigned mood condition, positive and negative. The interaction terms for positive urgency and assigned mood condition

(positive, negative) were added to the regression model and did not account for significantly more variance than positive urgency and the two mood conditions, R2=

.01, p = .62. 48

Table 7

Pearson Product-Moment Correlations of IGT Risk with Urgency Traits and Neuroticism Measure IGT Risk Full Sample NEO-FFI-3 -.03 NU .07 PU .11 Positive NEO-FFI-3 -.01 NU .16 PU .31* Neutral NEO-FFI-3 -.05 NU -.04 PU .08 Negative NEO-FFI-3 -.05 NU .03

PU -.08 Note: IGT = Iowa Gambling Task; NEO-FFI-3 = NEO Five Factor Inventory 3 Neuroticism Scale; UPPS-P = Urgency, Perseverance (lack of), Premeditation (lack of), Sensation Seeking, Positive Urgency Impulsive Behavior Scale; NU = UPPS-P Negative Urgency Scale; PU = UPPS-P Positive Urgency Scale *p < .05

Neither the interaction of positive urgency and negative mood condition,  = -.09; p =

.45, nor the interaction of positive urgency and positive mood condition,  = .01; p = .90, were significant predictors of post-manipulation craving. See Table 10 for simple correlations between post-manipulation craving and urgency/neuroticism variables. See

Table 11 for regression results. 49

Table 8

Summary of Hierarchical Regression Analysis Negative Urgency Predicting IGT Performance IGT Performance Variable R2 F B SE B  Step 1 .00 .66 Negative Urgency .08 .10 .07 Step 2 .01 .27 Negative Condition .65 1.81 .03 Positive Condition .10 1.73 .01 Step 3 .01 .37 Negative Urgency x .24 .24 .12 Positive Condition Negative Urgency x .08 .26 .04 Negative Condition Note: Assigned mood condition was represented as two dummy variables with neutral condition serving as the reference group. IGT = Iowa Gambling Task; Negative Urgency = UPPS-P Negative Urgency Scale

A three-stage hierarchical multiple regression analysis was also conducted to explore whether the relationship of negative urgency and post-mood manipulation craving was moderated by mood condition. In the first step, negative urgency was included and accounted for a significant amount of variance in craving, R2 = .14, F(1,

155) = 24.98, p < .001. In the second step, mood conditions (positive and negative) were added to the model, with the neutral group serving as the reference group; mood condition did not account for significantly more variance than negative urgency alone,

R2= .03, p = .09. Neither positive mood condition,  = -.02; p = .82, nor negative mood condition,  = .16; p = .07, were significant predictors of post-manipulation craving.

Next, two interaction terms were computed for negative urgency by assigned mood condition, positive and negative. 50

Table 9

Summary of Hierarchical Regression Analysis for Positive Urgency Predicting IGT Performance Variable IGT Performance R2 F B SE B  Step 1 .01 1.84 Positive Urgency .12 .09 .11 Step 2 .01 .63 Negative Condition .51 1.80 .03 Positive Condition .11 1.73 .01 Step 3 .04 1.34 Positive Urgency x .28 .22 .14 Positive Condition Positive Urgency x -.17 .21 -.10 Negative Condition Note: Assigned mood condition was represented as two dummy variables with neutral condition serving as the reference group. IGT = Iowa Gambling Task; Positive Urgency = UPPS-P Positive Urgency Scale

The interaction terms for negative urgency and assigned mood condition (positive, negative) were added to the regression model and did not account for significantly more variance than negative urgency and the two mood conditions, R2= .01, p = .50. Neither the interaction of negative urgency and negative mood condition,  = .05; p = .66, nor the interaction of negative urgency and positive mood condition,  = -.08; p = .51, were significant predictors of post-manipulation craving. See Table 12.

Supplemental Analyses

As an additional follow-up to study aim #1, we examined the amount of variance neuroticism and the urgency traits together accounted for in number of hard drugs tried, see Appendix E, Tables 15, 16 and 17.

Table 10

Pearson Product-Moment Correlations of Craving with Urgency Traits and Neuroticism Measure ACQ-SF-r Full Sample NEO-FFI-3 .18* NU .35** PU .35** Positive Mood NEO-FFI-3 .09 NU .29* PU .43** Neutral Mood NEO-FFI-3 .20 NU .30* PU .34* Negative Mood NEO-FFI-3 .21 NU .42**

PU .25 Note: ACQ-SF-r = Alcohol Craving Questionnaire, Short-Form revised; NEO-FFI-3 = NEO Five Factor Inventory 3 Neuroticism Scale; NU = UPPS-P Negative Urgency Scale; PU = UPPS-P Positive Urgency Scale *p < .05 **p < .01

Neuroticism and negative urgency together accounted for 12% of the variance in number of hard drugs tried, p < .01. A similar model that included neuroticism and positive urgency accounted for 13% of the variance in number of hard drugs tried, p < .01. We also examined the amount of variance neuroticism and negative urgency accounted for in

AUDIT total score, see Appendix E, Table 18. Together they accounted for 8% of the variance in AUDIT total score, p = .01.

Table 11

Summary of Hierarchical Regression Analysis for Positive Urgency Predicting Craving Variable Craving R2 F B SE B  Step 1 .13 23.18 Positive Urgency .40 .08 .36* Step 2 .16 2.44 Negative Condition 3.09 1.72 .16 Positive Condition -.33 1.65 -.02 Step 3 .16 .49 Positive Urgency x .03 .22 .01 Positive Condition Positive Urgency x -.16 .20 -.09 Negative Condition Note: Assigned mood condition was represented as two dummy variables with neutral condition serving as the reference group. Craving = Alcohol Craving Questionnaire, Short Form, revised (ACQ-SF-R), Positive Urgency = UPPS-P Positive Urgency Scale *p < .001

Results of previous meta-analytic studies have found that UPPS-P dimensions other than the urgency traits were related to problematic substance use variables (Berg et al., 2015; Coskupinar, Dir, & Cyders, 2013). As such, we conducted supplemental analyses to examine the relationship of lack of perseverance, lack of premeditation, and sensation seeking with our substance use variables. See Table 19 in Appendix E. Several variables were related with substance use measures, with similar effect sizes to the urgency variables.

Table 12

Summary of Hierarchical Regression Analysis for Negative Urgency Predicting Craving Craving Variable R2 F B SE B  Step 1 .14 22.98 Negative Urgency .47 .09 .37 Step 2 .17 2.50 Negative Condition 3.08 1.71 .16 Positive Condition -.38 1.64 -.02 Step 3 .17 .69 Negative Urgency x -.15 .23 -.08 Positive Condition Negative Urgency x .11 .24 .05 Negative Condition Note: Assigned mood condition was represented as two dummy variables with neutral condition serving as the reference group. Craving = Alcohol Craving Questionnaire, Short Form, revised (ACQ-SF-R), Negative Urgency = UPPS-P Negative Urgency Scale

In the present study, the urgency traits were not associated with IGT risky decision-making; however, affect has been shown to relate to performance on behavioral measures of impulsivity, including the IGT (Buelow & Suhr, 2013; Dolan, 2007; Suhr &

Tsanadis, 2007). As such, we conducted a supplemental analysis for study aim 2 to examine the relationship of affect to IGT performance. Positive affect on the PANAS was not associated with IGT performance at any time point. Negative affect on the PANAS was not associated with IGT performance at time points 1-3; however, it was significantly associated with IGT performance at time 4 (r = .16, p = .04), see Appendix

E, Table 20. 54

Prior research has found that other dimensions of UPPS-P trait impulsivity may be more strongly associated with decision-making impairments on the IGT task in undergraduate samples, particularly the lack of premeditation trait (Zermatten et al.,

2005). As such, we conducted supplemental analyses for study aim 2 to examine the relationship of IGT performance to the lack of perseverance, lack of premeditation, and sensation seeking traits. IGT performance was not significantly associated with any of the

UPPS-P traits. See Table 21 Appendix E.

Prior research has found significant associations exist between self-reported craving and performance on behavioral measures of impulsivity, including the IGT

(Wang et al., 2012). As such, we conducted supplemental analyses to examine the relationship between IGT performance on the last half of the task and self-reported craving. Correlational analyses did not indicate a significant relationship between the IGT and craving in the full sample or within any of the mood conditions, see Appendix E,

Table 23.

Previous research has largely found mixed results regarding gender differences in urgency traits. That said, some studies have found greater positive urgency in males and greater negative urgency in females (Billieux et al., 2010; Cyders, 2013; Cyders & Smith,

2007; D’Acremont & Van der Linden, 2005). As such, we explored gender differences in the urgency traits and whether there were differential relationships with problematic substance use variables and IGT performance between gender groups. Males (M = 28.08,

SD = 6.93) and females (M = 28.65, SD = 7.80) did not differ in negative urgency, t(157)

= -.49, p = .63, but males (M = 29, SD = 7.52) were higher in positive urgency than females (M = 25.98, SD = 8.67), t(157) = 2.34, p = .02, consistent with prior research 55

(Cyders, 2013). Interestingly, positive urgency was significantly associated with number of hard drugs tried, more days a month consumed alcohol, and younger age of first use of alcohol in females, but not males. See Appendix E, Table 24. However, there were no significant relationships of the urgency traits to IGT performance in either gender (see

Appendix E, Table 25). 56

Chapter 4: Discussion

Our study was the first, to our knowledge, to examine the relationship between the urgency traits and IGT performance in the context of a manipulated mood state, which is central to the definition of urgency. Overall, although the first study aim was partially supported, study hypotheses regarding the relationship of urgency to IGT performance were not supported.

The first goal of the study was to replicate and extend previous research demonstrating a relationship between urgency and indicators of problematic substance use, controlling for neuroticism. Consistent with previous findings, negative and positive urgency were strongly related to one another, accounting for 44% of variance in one another. Additionally, the urgency traits were strongly related to neuroticism, which accounted for 38% of the variance in negative urgency and 18% of the variance in positive urgency. Consistent with prior research, our results suggest that, while the urgency traits and trait neuroticism have strong overlap, they are not the same construct.

Even accounting for neuroticism, both negative urgency (pr = .28) and positive urgency (pr = .28) were associated with endorsement of more hard drugs tried.

Furthermore, consistent with expectations, elevated AUDIT total score was significantly associated with negative urgency after controlling for neuroticism (pr = .16, p = .05), but contrary to expectations, it was not significantly related to positive urgency (pr =.13, p =

.10). In the present study, the relationship between negative urgency and AUDIT score was weaker than Karyadi (2013) reported (r = .39); however, they did not control for neuroticism/negative affect in their study. In one study that did control for neuroticism,

Papachristou, Nederkoorn, & Jansen (2016) found a stronger relationship between 57

negative urgency and AUDIT total score (pr = .48); however, they assessed neuroticism via the Eysenck Personality Questionnaire Revised Short Form (Eysenck, Barrett, &

Eysenck, 1984). Generally, however, our findings using the AUDIT and number of hard drugs tried were consistent with previous research demonstrating that the relationship between urgency and substance use remains after controlling for neuroticism (Anestis et al., 2009; Cyders & Coskupinar, 2010; Fischer et al., 2007; Kaiser et al., 2012). The

AUDIT questionnaire includes items that, in addition to frequency and quantity of alcohol use, assess problematic outcomes from drinking behaviors such as blackouts, drinking related injuries, having others express concern about alcohol use, etc. It is possible that negative affect/neuroticism and the tendency to act rashly in the face of strong negative emotions are more consistently related to problematic drinking outcomes than rash action in the face of positive emotions.

Inconsistent with previous meta-analytic research (Coskupinar, Dir, & Cyders,

2013), the urgency traits were not significantly related to many of the other substance use variables we examined. Our results are in contrast to the meta-analysis by Coskupinar,

Dir, and Cyders (2013), which found that positive and negative urgency were related to many substance use variables, including quantity of alcohol use, frequency of alcohol use, alcohol dependency symptoms, problems associated with alcohol use, and binge drinking. Our supplemental analyses suggested that lack of perseverance was the UPPS-P trait most strongly associated with younger age of first use of alcohol and related more strongly to AUDIT total score and number of hard drugs tried than the urgency traits.

Consistent with meta-analytic findings, our results suggest that the specific UPPS-P traits likely show differential patterns of relationships to specific alcohol use outcomes. 58

Few studies that have examined the relationship between the urgency traits and indicators of problematic substance use have accounted for neuroticism, despite the strong relationship between neuroticism and the urgency traits and the relationship between neuroticism and substance use. It is possible that the combination of the urgency traits and neuroticism accounts for more variance in problematic substance use than neuroticism alone. Our supplemental analyses suggested that neuroticism and negative urgency together explained more variance in number of drugs tried as well as AUDIT total score than neuroticism alone, although the amount of variance accounted for remained small. We also found that neuroticism and positive urgency together explained more variance in number of hard drugs tried than neuroticism alone, although again the amount of variance accounted for remained small.

Broadly, the lack of relationships for other problematic substance use variables was possibly due to the restricted ranges on those variables, which may have contributed to fewer and weaker correlations with both urgency traits and neuroticism than what previous researchers have found. For example, in the present sample, 53.2% of our sample reported drinking between 2 and 6 drinks per occasion. Additionally, for the substance variable of age of first use of alcohol, 47% of our sample reported age 16. In regard to average number of days individuals reported consuming alcohol a month,

55.8% of our sample reported drinking between 2 and 6 days a month.

In addition, we may have found weaker relationships between the urgency traits and substance use variables due to characteristics of our sample. We recruited individuals who specifically reported binge drinking on AUDIT item #3, defined as consuming 6 or more drinks on drinking occasion. That said, despite reporting binge use on the AUDIT, 59

the majority (61.2%) of our sample endorsed consuming an average of 5.77 drinks per drinking occasion. When compared to Cyders and colleagues (2014), in which 51.9% of their sample reported an average of 14 drinks consumed per drinking occasion, our sample appears to be less risky in their alcohol use. Further, in the present sample, average weekly alcohol use was 1.45 days; however, previous studies that also recruited high-risk participants reported average weekly alcohol use as 5.41 days a week (Kaiser et al., 2012). Regarding the AUDIT, the accepted cut-off score for hazardous alcohol use is

8 (Babor et al., 2001). Although our sample of problematic drinkers had elevated average

AUDIT total scores, 9.32 for males and 8.19 for females, our sample mode was 5 and only 85 participants had AUDIT total scores of 8 or greater, suggesting our sample may not have as clinically significant of substance use problems as has been seen in prior literature.

It is also possible that differences between males and females obscured potentially meaningful findings, particularly for positive urgency. Specifically, after controlling for neuroticism, positive urgency was associated with more hard drugs tried in females (pr =

.37, p = .001), but not in males (pr = .08, p = .49). We also found that positive urgency was associated with younger age of first use of alcohol (r = -.23, p = .04) and average number of days a month individuals consumed alcohol (r = .21, p = .05), but only in females. Cyders (2013) reported that males and females did not show differential relationships of urgency with risky behavior. However, our results suggest that positive urgency is differentially related to risky substance use, with relationships seen only in women. As few studies have taken into account gender differences in examinations of the 60

urgency traits in relation to problematic outcomes, future studies should test for gender differences, as they may have implications for assessment and treatment.

Overall, relationships between the urgency traits, neuroticism, and problematic substance use variables have potential clinical implications. For one, it is important for clinicians to assess for the presence of strong negative emotion states (neuroticism), and the tendency to act rashly in the face of strong negative emotions, in individuals who may be at risk for substance use problems. Specifically, individuals who tend to experience more frequent negative emotions and engage in rash action in response to strong negative emotions are likely to be at risk for trying more hard drugs. Those who have elevated negative urgency, but not necessarily greater neuroticism, may be more likely to consume alcohol more days a week. Further, on a measure of problematic alcohol use, the AUDIT, greater neuroticism is likely to be associated with more problems, but only in females (r

= .37, p = .001).

It is likely more common for individuals who present with impulsive behaviors in the face of distressing negative emotions to receive clinical attention. However, results of the present study suggest clinicians should be mindful to assess for engagement in rash actions when individuals are experiencing strong positive emotions as well, especially in female populations. This is especially relevant in college student populations who report risky substance use behaviors during times of celebration, as part of positive social interactions, or to enhance positive mood states (Cyders et al., 2007). Our findings suggest it is important to assess for positive urgency in females, given the implications it has for consuming alcohol more days a month and consuming alcohol for the first time at a younger age. 61

Our findings also lend support for the importance of assessing multiple factors of impulsivity via the UPPS-P measure in individuals who are at risk for problematic substance use. For example, we found that individuals who experience difficulty remaining focused on a task, the lack of perseverance UPPS-P trait, may be more likely to experience substance use problems, including greater AUDIT total scores, use of more hard drugs tried, and consuming alcohol at a younger age. At the same time, those who tend to act without thinking (lack of premeditation) and those who seek out novel and thrilling experiences (sensation seeking) may also be more likely to engage in greater use of hard drugs. Further, individuals with elevations on sensation seeking are likely to consume more drinks on drinking occasion, consistent with prior literature suggesting that sensation seeking is the trait most strongly associated with binge alcohol use

(Coskupinar, Dir, & Cyders, 2013). Additionally, our findings suggest clinicians should assess multiple dimensions of problematic substance use, given our findings of differential relationships with the UPPS-P impulsivity traits. Assessing problematic substance use with only one measure may limit the ability of researchers to explore relationships between substance use and impulsivity traits that may have important clinical and research implications.

The relationships we found between the urgency traits and problematic behavioral outcomes have potential treatment implications. Specifically, individuals who engage in impulsive behaviors with potentially problematic outcomes in response to strong emotion states may benefit from treatments that aim to address emotion regulation skills, such as

Dialectical Behavioral Therapy (DBT; Linehan, 2014) as opposed to treatments designed to find alternative outlets for risky behavior, which may be helpful in an individual with 62

elevated sensation seeking, for example. Within the DBT skills training framework, individuals are taught Distress Tolerance skills, or the ability to adaptively respond to emotions and reduce negative outcomes and tolerate emotion states in the moment. A strong base of evidence suggest that distress tolerance skills training is effective with individuals with clinical levels of problematic alcohol use (Bornovalova et al., 2012;

Linehan, 1993). Individuals who experience more frequent negative emotional experiences, or neuroticism, as well as greater levels of urgency (positive or negative) would likely benefit from utilization of emotion regulation strategies to assist in guiding behaviors to prevent problematic outcomes.

Our results indicating gender differences in positive urgency also have important clinical implications. First, clinicians should use caution when interpreting the UPPS-P self-report questionnaire, given that traits appear to have differential relationships to problematic outcomes depending upon gender. This appears to be especially true for positive urgency traits. Even though we found that males report greater levels of positive urgency, our results suggest that females may have more problematic outcomes related to positive urgency than males do. It may be that females experience negative substance use outcomes of behaviors driven by positive emotions to a greater degree than their male counterparts. This is especially important to consider in college student populations where substances of potential abuse are readily available and often incorporated into social functions and extracurricular activities.

Our second aim was to examine the relationship of the urgency traits to a behavioral measure of impulsivity, namely the IGT. Inconsistent with hypotheses, neither positive or negative urgency was significantly related to impulsive decision- 63

making on the last half of the IGT task. These findings stand in contrast to those of other researchers (Billieux et al., 2010; Xiao et al., 2009), who found a relationship between impulsivity/urgency and IGT performance; however, the present results are consistent with prior studies examining the relationship of urgency to IGT in healthy individuals

(Bayard, Raffard, Gely-Nargeot, 2011) and in undergraduate samples (Zermatten et al.,

2005). One potential reason for inconsistent findings might be differences in how IGT performance was assessed across the studies. However, Billieux and colleagues (2010) examined IGT risk similarly, on trials 61-100 rather than 50-100. Another potential reason for our lack of findings is that our sample may have been less risky on the IGT than prior samples. For example, Billieux and colleagues (2010) found an average IGT risk of 24.50 (8.23) in a sample of healthy volunteers while in the present study average

IGT risk was 18.55 (7.89), suggesting our sample did not demonstrate as risky of decision-making as those that have found a relationship between IGT performance and the urgency traits.

Overall, the inconsistent findings regarding the relationship of urgency to the IGT task across prior studies and the present study raise concern about the nature of the IGT task as a measure of impulsive behavior. In fact, researchers have found that impaired performance on the IGT is not consistently associated with impaired performance on other measures of risky decision-making, suggesting they may be measuring different constructs (Lejuez et al., 2010). Damasio (1996) proposed that decision-making on the

IGT is guided by “emotion based biasing signals generated from the body,” also known as somatic markers (Dunn, Dalgleish, & Lawrence, 2006). Further, it was originally hypothesized that these emotion-based signals impacted decision-making prior to 64

conscious comprehension of the reward/punishment schedule of deck selection on the

IGT (Turnbull et al., 2003). Given the definition of urgency, it seems likely that those with elevated urgency would struggle to be able to utilize conscious knowledge about the reward/punishment contingencies of each deck due to the impact of heightened emotion states on behavior, in this case, deck selection. However, other researchers have demonstrated that knowledge regarding the reward/punishment schedule on the IGT task occurs much earlier than originally believed, with some research suggesting learning after trial 20 (Bowman et al., 2005; Maia & McClelland, 2004). These findings suggest that, despite elevated urgency, participants may have still effectively utilized “explicit” learning of reward patterns in order to maximize gains on the IGT task. Furthermore, IGT performance may be related to other emotion regulation constructs that are related to, but not the same as, impulsivity. For example, Sharma and colleagues’ (2014) meta-analysis reported that IGT performance loaded more strongly on an inhibition dimension than it did on an impulsive decision-making dimension. Additionally, other researchers have suggested that IGT performance may be guided by a preference (or lack thereof) for risk rather than impulsivity (Dunn, Dalgleish, & Lawrence, 2006). Others have suggested that it is lack of premeditation that is most strongly associated with efficient decision-making on the IGT (Rochat et al., 2018; Zermatten et al., 2005). This suggests that the diminished ability to think and reflect through consequences before acting is the dimension of trait impulsivity most strongly related to risky decision-making on the IGT; however, our supplemental analyses did not reveal significant associations between IGT performance and any of the other UPPS-P traits. 65

Coskupinar and colleagues (2014) also hypothesized that a potential reason for the lack of associations between trait and behavioral measures of impulsivity in the literature is due to research designs that only utilize a single behavioral task. They proposed that a clearer picture of the relationships between impulsivity traits, such as urgency, and behavioral impulsivity will emerge by incorporating several measures of behavioral impulsivity in study designs. As such, a potential explanation for our lack of findings between the urgency traits and behavioral impulsivity may have been due to our use of only one measure of behavioral impulsivity. That said, utilization of more than one measure of behavioral impulsivity was not feasible in the present study due to our visual mood manipulation procedure.

Past meta-analytic research has suggested that significant relationships between behavioral and self-report measures of impulsivity are the exception rather than the rule

(Sharma et al., 2014). The authors proposed that both trait and state measures of impulsivity tap into higher-order constructs that impact daily life behaviors such as substance use and abuse. Specifically, they found that negative urgency was related to alcohol and drug use dimensions, as was IGT performance; however, the two were not related to one another (Sharma et al., 2014). Inconsistent with their findings, results of correlational analyses in the present study indicated that IGT performance was not significantly associated with any of our indicators of problematic substance use. As previously noted, our lack of findings may be related to our less risky sample, who also did not appear to have clinical levels of substance use.

Tests for study aim 3 did not suggest that the relationships between the urgency traits and IGT performance varied by mood state. In addition to the study limitations 66

already mentioned, another potential reason for the lack of findings may have been the nature of the mood induction. Analyses suggested that the mood induction we utilized was only temporarily effective and did not extend through IGT task performance.

Previous research on the urgency traits has found the IAPS images to be an effective mood induction procedure (Cyders et al., 2014; Treloar & McCarthy, 2012). One reason for the lack of effectiveness in the current study might be that the participants did not remain aware of the IAPS images during the IGT task, even though they were playing on a screen next to the IGT. The majority of participants reported being only “slightly aware” or “not at all aware” that the images continued to play. Other urgency researchers have suggested that use of the IAPS images may not be effective as means of eliciting a sufficient emotion state so as to “induce impulsive behaviors” (Cyders, Coskupinar, &

Lehman, 2012).

Although we did not find associations between the urgency traits and IGT performance, other researchers have found that the subjective experience of craving is associated with urgency and is associated with IGT performance (VanderVeen et al.,

2016; Wang et al., 2012). Our exploratory analyses showed that greater positive and negative urgency were associated with increased post-manipulation craving after controlling for neuroticism, consistent with previous research indicating a relationship between urgency and craving in response to substance cues (Karyadi, 2013; Pavlick,

2007). However, linear regression models did not suggest that mood state moderated the relationship between urgency constructs and craving. It has been proposed that problematic drinking in individuals with elevated urgency is due to difficulty resisting cravings in order to reduce negative affect or enhance positive affect (Cyders et al., 2007; 67

Smith et al., 2007). As noted above, our manipulation procedure likely did not induce elevations in positive or negative affect to a level that would moderate the relationship between the urgency constructs and craving. Despite past research that suggests craving is associated with IGT performance (Wang et al., 2012), we found nonsignificant results after controlling for trait neuroticism. That said, our study utilized a nonclinical sample and did not present individuals with substance cues during task administration or as part of our mood manipulation procedure. It is likely that, in the face of substance cues, craving signifies increased emotional reactions, either positive or negative, which may impact performance on behavioral measures of impulsivity to a greater extent than IAPS negative or positive images alone could elicit.

Limitations and Future Directions

In addition to the limitations already mentioned, our study had some additional limitations to note. First, our sample was one of convenience and was composed of undergraduate college students who identified as mostly Caucasian and who were in their first year of college. As a result, our findings may not generalize to other populations with different demographic characteristics. Further, despite our attempts to oversample for high-risk individuals in regard to substance use, our sample largely reported levels of use that are below what is typically considered hazardous use. As such, our findings may not generalize to those who are experiencing more problematic outcomes from substance use or those who are presenting for clinical treatment of problematic behaviors.

Additionally, given that most of our study participants were in their first year of college, it is possible that we did not detect increases in problematic substance use that have been found to occur over the first year of college. Future studies should study the relationship 68

between urgency traits and problematic substance use outcomes over time in undergraduate samples, to examine whether they are predictive of the development of problematic substance use during the college years.

As noted above, our chosen mood manipulation procedure was found to be ineffective for the duration of behavioral impulsivity task completion. As such, we were unable to assess whether mood condition, and the experience of elevated positive or negative affect, truly had a meaningful impact on the relationship between urgency traits and performance on a behavioral measure of impulsivity or on the relationship between urgency traits and craving. Future research should continue to examine the relationship of the urgency traits to problematic outcomes, including substance use, in the context of a manipulated mood condition, particularly negative affect/neuroticism and should utilize more effective emotion-induction procedures. For example, Chester and colleagues

(2016) overlaid letters in a go/no-go task on IAPS images that were either positive, negative, or neutral, depending on assigned mood condition. Having the images presented on the same screen as the task, as opposed to on an adjacent screen from the task, may serve to increase awareness in participants. Other researchers, such as Cyders and colleagues (2010), utilized a combined story mood and imaginal/writing mood induction procedure, which resulted in increases in positive mood.

Additionally, we did not utilize alcohol or substance related cues as a part of our study design, which have been found to impact executive function and performance on behavioral measures of impulsivity, including the IGT (Wang et al., 2012). It seems likely that individuals with elevated urgency may exhibit more impaired performance on behavioral measures of impulsivity in the face of cues that elicit craving, a strong 69

subjective emotional experience. As such, future research should examine the relationship of the urgency traits with measurable outcomes in the face of substance cue reactivity.

An additional study limitation was the use of only one behavioral measure of impulsivity, the IGT, and we analyzed performance on the last half of the task, considered decision-making under risk. Others have proposed that, by looking at IGT performance differently, including percentages of risky deck selection across all trials, may provide a more accurate picture of risk. Future research should continue to examine the relationship of the urgency traits with other domains of behavioral impulsivity in order to assess the potential underlying mechanisms that place some individuals at greater risk of problematic substance use outcomes.

Finally, supplemental analyses indicated that other UPPS-P dimensions were also associated with aspects of problematic substance use, consistent with previous research

(Adams et al., 2012; Berg et al., 2015; Coskupinar, Dir, & Cyders, 2013). As such, future studies should examine all of the UPPS-P impulsivity facets in order to explore the differential relationships of impulsivity traits to alcohol use outcomes.

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Appendix A: Measures

Ohio University Consent Form

Title of Research: Impulsivity and Affective Decision-Making

Researchers: Brittni Morgan, M.A. Julie Suhr, Ph.D.

You are being asked to participate in research. For you to be able to decide whether you want to participate in this project, you should understand what the project is about, as well as the possible risks and benefits in order to make an informed decision. This process is known as informed consent. This form describes the purpose, procedures, possible benefits, and risks. It also explains how your personal information will be used and protected. Once you have read this form and your questions about the study are answered, you will be asked to sign it. This will allow your participation in this study. You should receive a copy of this document to take with you.

Explanation of Study This study is being conducted to examine the relationship between personality traits and performance on psychological tests during heightened emotion states. Participants will be randomly assigned to one of three emotion conditions prior to completing psychological tests.

If you agree to participate, you will be asked some questions about your medical and mental health history and any current medications you might use. You will also complete self-report measures about your personality traits. You will also be asked about your alcohol and drug use history. Then you will look at thirty pictures on the computer, followed by a computerized task.

Your participation in the study will last one hour.

Risks and Discomforts You will be asked about potentially illegal activity, specifically alcohol and drug use, you may have engaged in in the past. You will not be asked about your intent to engage in substance use in the future. Your study information is confidential and will not be examined while your identifying information is still known to any examiner, nor will any identifying information be attached to your study information, to minimize accidental disclosure of any reported history.

While the computer pictures you view have been used in many research projects, you may feel discomfort in viewing disturbing images that may elicit emotional reactions during your participation in this study. If you experience discomfort that leads you to wish to discontinue your participation, please inform the investigator.

100

Benefits This study is important to science/society because learning about how personality traits, cognitive functioning, and emotion states are related may help psychologists to determine which individuals are at a greater risk for problematic outcomes from their behaviors when experiencing strong emotions.

You may not benefit personally by participating in this study.

Confidentiality and Records Your study information will be kept confidential by use of a research number that will be in no way tied to any unique identifying information about you.

Consent forms will be stored in locked file cabinets in the Clinical Neuropsychology Research Laboratory. The consent form, which has your name on it, will be kept separately from your data.

Additionally, while every effort will be made to keep your study-related information confidential, there may be circumstances where this information must be shared with: * Federal agencies, for example the Office of Human Research Protections, whose responsibility is to protect human subjects in research; * Representatives of Ohio University (OU), including the Institutional Review Board, a committee that oversees the research at OU;

Compensation As compensation for your time/effort, you will receive one experimental credit for your participation in this study. If you discontinue your participation early, you will receive experimental credit for your participation commensurate with the amount of time you completed. For example, if you discontinue your participation within the first ½ hour of the experiment, you will receive ½ credit.

Contact Information If you have any questions regarding this study, please contact Brittni Morgan at [email protected] or Dr. Julie Suhr at [email protected].

If you have any questions regarding your rights as a research participant, please contact Dr. Chris Hayhow, Director of Research Compliance, Ohio University, (740)593-0664, email [email protected].

By signing below, you are agreeing that:  you have read this consent form (or it has been read to you) and have been given the opportunity to ask questions and have them answered  you have been informed of potential risks and they have been explained to your satisfaction. 101

 you understand Ohio University has no funds set aside for any injuries you might receive as a result of participating in this study  you are 18 years of age or older  your participation in this research is completely voluntary  you may leave the study at any time. If you decide to stop participating in the study, there will be no penalty to you and you will not lose any benefits to which you are otherwise entitled.

Signature Date

Printed Name

102

Demographic Questionnaire

Age: ______(must be at least 18 to participate in this study) Sex:  Male  Female Gender:  Male  Female  Transgender Race: (check all of which apply)  African American or Black  American Indian or Alaska Native  Asian American  European American or White or Caucasian  Native Hawaiian or Other Pacific Islander  Other ______. Ethnicity: (check one)  Hispanic/Latino(a)  Nonhispanic Level of Education:  Freshman  Sophomore  Junior  Senior History of Prior Head Injury?  Yes  No If yes, at what age did you experience your head injury or concussion? ______If yes, what was the mechanism of injury (i.e. head to ground, head to windshield)? ______If yes, did you lose consciousness?  Yes  No If yes, for how long? ______If yes, did you experience disorientation, confusion, and/or memory loss immediately following the injury?  Yes  No If yes, for approximately how long? ______If yes, did your injury result in hospitalization?  Yes  No If yes, how long were you hospitalized? ______If yes, was any imaging conducted (i.e. MRI, CT)?  Yes  No If yes, what imaging was conducted and what were the findings? Did you have more than one head injury or concussion?  Yes  No If yes, at what age did you experience your head injury or concussion? ______If yes, what was the mechanism of injury (i.e. head to ground, head to windshield)? ______If yes, did you lose consciousness?  Yes  No If yes, for how long? ______If yes, did you experience disorientation, confusion, and/or memory loss immediately following the injury?  Yes  No If yes, for approximately how long? ______If yes, did your injury result in hospitalization?  Yes  No If yes, how long were you hospitalized? ______If yes, was any imaging conducted (i.e. MRI, CT)?  Yes  No If yes, what imaging was conducted and what were the findings?______History of Psychological Diagnoses:  Yes  No If Yes, what was your diagnosis? ______If Yes, at what age were you diagnosed? ______103

If Yes, what treatment have you undergone for diagnosis (i.e. medication, counseling)?______Do you have a history of neurological disorders (e.g. epilepsy, brain tumor)?  Yes  No If yes, what was/is your diagnosis? ______If yes, at what age did you first receive your neurological disorder diagnosis? __ If yes, what treatment(s) have you undergone for your diagnosis (i.e. medication, surgery)?______Current Prescription & Over-the-Counter Medications + Purpose + Dosage: ______History of Alcohol Use Disorder Diagnoses:  Yes  No If Yes, what was your diagnosis? ______If Yes, have you participated in treatment for your alcohol use, and, if so, what was the treatment?  Yes  No ______What is the date of your last alcoholic beverage? ____/____/_____ At what age did you have your first alcoholic beverage beyond a sip or taste? (If you are unsure, give your best estimate.) ______On average, how many days did you consume alcohol in the past 30 days? ______On average, how many days of the week do you consume alcohol? ______On average, how many alcoholic drinks do you consume per drinking occasion? ______Have you ever consumed any other substances of abuse other than alcohol?  Yes  No If yes, please indicate which of the following you have ever consumed:  Nicotine  Cannabis (Marijuana, Pot, Grass, Hash, Hash Oil)  Cocaine (Crack, Coke, Coca leaves, Freebase)  Prescription Stimulants (Ritalin, Concerta, Dexedrine, Adderall, diet pills, etc.)  Sedatives or sleeping pills (Valium, Serepax, Ativan, Xanax, Librium, Rohypnol, GHB, etc.)  Methamphetamine (speed, crystal meth, ice, etc.)  Street Opioids (Heroin, Opium, etc.)  Prescription Opioids (fentanyl, oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.  Hallucinogens (Ecstasy, LSD, acid, mushrooms, Special K, Mescaline, Peyote, PCP, Angel Dust, DMT)  Solvents/Inhalants (paint thinner, Trichlorethylene, Gasoline, nitrous oxide, Petrol Gas, Glue)  Others (Anabolic steroids, Amyl Nitrate, Anticholinergic compounds) Specify: ______If yes, how often have you used the substance you mentioned in the past three months? 104

Substance Never Once Monthly Weekly Daily or or Almost Twice Daily Cannabis (marijuana, pot, grass, 0 2 3 4 6 hash, etc.) Cocaine (coke, crack, etc.) 0 2 3 4 6 Prescription stimulants (Ritalin, 0 2 3 4 6 Concerta, Dexedrine, Adderall, diet pills, etc.) Inhalants (nitrous oxide, glue, gas, 0 2 3 4 6 paint thinner, etc.) Sedatives or sleeping pills (Valium, 0 2 3 4 6 Serepax, Ativan, Librium, Xanax, Rohypnol, GHB, etc.) Hallucinogens (LSD, acid, 0 2 3 4 6 mushrooms, PCP, Special K, ecstasy, etc.) Street opioids (heroin, opium, etc.) 0 2 3 4 6 Prescription opioids (fentanyl, 0 2 3 4 6 oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.) Other—Specify: 0 2 3 4 6

In the past 3 months, how often have you had a strong desire or urge to use (first drug, second drug, etc.)? Substance Never Once Monthly Weekly Daily or or Almost Twice Daily Cannabis (marijuana, pot, grass, 0 3 4 5 6 hash, etc.) Cocaine (coke, crack, etc.) 0 3 4 5 6 Prescription stimulants (Ritalin, 0 3 4 5 6 Concerta, Dexedrine, Adderall, diet pills, etc.) Inhalants (nitrous oxide, glue, gas, 0 3 4 5 6 paint thinner, etc.) Sedatives or sleeping pills (Valium, 0 3 4 5 6 Serepax, Ativan, Librium, Xanax, Rohypnol, GHB, etc.) Hallucinogens (LSD, acid, 0 3 4 5 6 mushrooms, PCP, Special K, ecstasy, etc.) 105

Street opioids (heroin, opium, etc.) 0 3 4 5 6 Prescription opioids (fentanyl, 0 3 4 5 6 oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.) Other—Specify: 0 3 4 5 6

During the past 3 months, how often has your use of (first drug, second drug, etc.) led to health, social, legal, or financial problems? Substance Never Once Monthly Weekly Daily or or Almost Twice Daily Cannabis (marijuana, pot, grass, 0 4 5 6 7 hash, etc.) Cocaine (coke, crack, etc.) 0 4 5 6 7 Prescription stimulants (Ritalin, 0 4 5 6 7 Concerta, Dexedrine, Adderall, diet pills, etc.) Inhalants (nitrous oxide, glue, gas, 0 4 5 6 7 paint thinner, etc.) Sedatives or sleeping pills (Valium, 0 4 5 6 7 Serepax, Ativan, Librium, Xanax, Rohypnol, GHB, etc.) Hallucinogens (LSD, acid, 0 4 5 6 7 mushrooms, PCP, Special K, ecstasy, etc.) Street opioids (heroin, opium, etc.) 0 4 5 6 7 Prescription opioids (fentanyl, 0 4 5 6 7 oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.) Other—Specify: 0 4 5 6 7

During the past 3 months, how often have you failed to do what was normally expected of you because of your use of (first drug, second drug, etc.)? Substance Never Once Monthly Weekly Daily or or Almost Twice Daily Cannabis (marijuana, pot, grass, 0 5 6 7 8 hash, etc.) Cocaine (coke, crack, etc.) 0 5 6 7 8 106

Prescription stimulants (Ritalin, 0 5 6 7 8 Concerta, Dexedrine, Adderall, diet pills, etc.) Inhalants (nitrous oxide, glue, gas, 0 5 6 7 8 paint thinner, etc.) Sedatives or sleeping pills (Valium, 0 5 6 7 8 Serepax, Ativan, Librium, Xanax, Rohypnol, GHB, etc.) Hallucinogens (LSD, acid, 0 5 6 7 8 mushrooms, PCP, Special K, ecstasy, etc.) Street opioids (heroin, opium, etc.) 0 5 6 7 8 Prescription opioids (fentanyl, 0 5 6 7 8 oxycodone [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.) Other—Specify: 0 5 6 7 8

Has a friend or relative or anyone else ever expressed concern about your use of (first drug, second drug, etc.)? Substance No, Yes, but not in Yes, in the never the past 3 past 3 months months Cannabis (marijuana, pot, grass, hash, etc.) 0 3 6 Cocaine (coke, crack, etc.) 0 3 6 Prescription stimulants (Ritalin, Concerta, 0 3 6 Dexedrine, Adderall, diet pills, etc.) Inhalants (nitrous oxide, glue, gas, paint 0 3 6 thinner, etc.) Sedatives or sleeping pills (Valium, Serepax, 0 3 6 Ativan, Librium, Xanax, Rohypnol, GHB, etc.) Hallucinogens (LSD, acid, mushrooms, PCP, 0 3 6 Special K, ecstasy, etc.) Street opioids (heroin, opium, etc.) 0 3 6 Prescription opioids (fentanyl, oxycodone 0 3 6 [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.) Other—Specify: 0 3 6

Have you ever tried and failed to control, cut down, or stop using (first drug, second drug, etc.)? 107

Substance No, Yes, but not in Yes, in the never the past 3 past 3 months months Cannabis (marijuana, pot, grass, hash, etc.) 0 3 6 Cocaine (coke, crack, etc.) 0 3 6 Prescription stimulants (Ritalin, Concerta, 0 3 6 Dexedrine, Adderall, diet pills, etc.) Inhalants (nitrous oxide, glue, gas, paint 0 3 6 thinner, etc.) Sedatives or sleeping pills (Valium, Serepax, 0 3 6 Ativan, Librium, Xanax, Rohypnol, GHB, etc.) Hallucinogens (LSD, acid, mushrooms, PCP, 0 3 6 Special K, ecstasy, etc.) Street opioids (heroin, opium, etc.) 0 3 6 Prescription opioids (fentanyl, oxycodone 0 3 6 [OxyContin, Percocet], hydrocodone [Vicodin], methadone, buprenorphine, etc.) Other—Specify: 0 3 6

Have you ever used No, Never Yes, but not in the Yes, in the past 3 any drug by injection past 3 months months (NONMEDICAL USE ONLY)?

If yes, approximately how much do you use per occasion (first drug, second drug, etc.)?

If yes, at what approximate age did you start using (first drug, second drug, etc.)

If yes, have you ever received any kind of treatment for your substance use (first drug, second drug, etc.)?  Yes

 No

If yes, what type(s) of treatment have you received?

108

Alcohol Use Disorders Identification Test: Self-Report Version (AUDIT; Saunders et al., 1993)

PARTICIPANT: Because alcohol use can affect your heath and can interfere with certain medications and treatments, it is important that we ask some questions about your use of alcohol. Your answers will remain confidential so please be honest.

Place an X in one box that beset describes your answer to each question.

Questions 0 1 2 3 4 How often do you have a drink Never 2-4 2-3 4 or more Monthly containing alcohol? times a times a times a or Less month week week How many drinks containing alcohol do you have on a typical day when you are 1 or 2 3 or 4 5 or 6 7 to 9 10 or more drinking? How often do you have six or Less Daily or more drinks on one occasion? Never than Monthly Weekly almost daily monthly How often during the last year Less have you found that you were Daily or Never than Monthly Weekly not able to stop drinking once almost daily monthly you had started? How often during the last year Less have you failed to do what was Daily or Never than Monthly Weekly normally expected of you almost daily monthly because of drinking? How often during the last year have you needed a drink first Less Daily or thing in the morning to get Never than Monthly Weekly almost daily yourself going after a heavy monthly drinking session? How often during the last year Less Daily or have you had a feeling of guilt Never than Monthly Weekly almost daily or remorse after drinking? monthly How often during the last year have you been unable to Less Daily or remember what happened the Never than Monthly Weekly almost daily night before because of your monthly drinking? 109

Have you or someone else Yes, but been injured because of your not in Yes, during No drinking? the last the last year year Has a relative, friend, doctor, Yes, but or other health care worker not in Yes, during been concerned about your No the last the last year drinking or suggested you cut year down?

110

Adult Self-Report Scale-V1.1 (ASRS-V1.1) Screener

from WHO Composite International Diagnostic Interview

Check the box that best describes Never Rarely Sometimes Often Very how you have felt and conducted Often yourself over the past 6 months. Please give the completed questionnaire to your healthcare professional during your next appointment to discuss the results.

How often do you have trouble wrapping up the final details of a project, once the challenging parts have been done?

How often do you have difficulty getting things in order when you have to do a task that requires organization?

How often do you have problems remembering appointments or obligations?

When you have a task that requires a lot of thought, how often do you avoid or delay getting started?

How often do you fidget or squirm with your hands or feet when you have to sit down for a long time?

How often do you feel overly active and compelled to do things, like you were driven by a motor?

Adult ADHD Self-Report Scale-V1.1 (ASRS-V1.1) The ASRS-v1.1 (Adler,

Kessler, & Spencer, 2003) is a 6-item screening instrument of ADHD symptoms in adults developed in conjunction with the World Health Organization (WHO). The items on the 111

ASRS-v1.1 are consistent with DSM-IV criteria for ADHD. The ASRS-v1.1 has demonstrated high internal consistency (.88; Adler et al., 2006) and good two-week test- retest reliability (.86; Matza et al., 2011). For the present study, the ASRS-v1.1 was used to assess for adult ADHD symptoms for descriptive purposes (α = .69 in the current sample).

112

The Positive and Negative Affect Schedule

(PANAS; Watson, Clark, & Tellegen, 1988)

This scale consists of a number of words that describe different feelings and emotions.

Read each item and then list the number from the scale below next to each word.

Indicative to what extent you feel this way right now, that is, at the present moment

OR indicate the extent you have felt this way over the past week (circle the instructions you followed when taking this measure).

1 2 3 4 5

Very Slightly A Little Moderately Quite A Bit Extremely or Not At All

____1. Interested ____11. Irritable

____2. Distressed ____12. Alert

____3. Excited ____13. Ashamed

____4. Upset ____14. Inspired

____5. Strong ____15. Nervous

____6. Guilty ____16. Determined

____7. Scared ____17. Attentive

____8. Hostile ____18. Jittery

____9. Enthusiastic ____19. Active

____10. Proud ____ 20. Afraid

The Affect Grid (Russell, Weiss, & Mendelsohn, 1989)

You use the “affect grid” to describe feelings. It is in the form of a square—a kind of map for feelings. The center of the square (marked by X in the grid below) represents a neutral, average, everyday feeling. It is neither positive nor negative.

The vertical dimension of the map represents degree of arousal. Arousal has to do with how wide awake, alert, or activated a person feels—independent of whether the feeling is positive or negative. The top half is for feelings that are above average in arousal. The lower half for feelings below average. The bottom represents sleep, and the higher you go, the more awake a person feels. So, the next step up from the bottom would be half awake/half asleep. At the top of the square is maximum arousal. If you imagine a state we might call frantic excitement (remembering that it could be either positive or negative), then this feeling would define the top of the grid.

The right half of the grid represents pleasant feelings. The farther to the right the more pleasant. The left half represents unpleasant feelings. The farther to the left, the more unpleasant.

If the “frantic excitement” was positive, it would, of course, fall on the right half of the grid. The more positive, the farther to the right. If the “frantic excitement” was negative, it would fall on the left half of the grid. The more negative, the farther to the left. If the “frantic excitement” was neither positive nor negative, then it would fall in the middle square of the top row.

Other areas of the grid can be labeled as well. Up and to the right are feelings of ecstasy, excitement, joy. Opposite these, down and to the left, are feelings of depression, melancholy, sadness, and gloom. 114

Up and to the left are feelings of stress and tension. Opposite these, down and to the right,

are feelings of calm, relaxation, serenity.

Feelings are complex. They come in all shades and degrees. The labels we have

given are merely landmarks to help you understand the affect grid. When actually using

the grid, put an X anywhere in the grid to indicate the exact shade and intensity of

feeling. Please look over the entire gird to get a feel for the meaning of the various areas.

Please rate your mood as it is right now.

Stress High Arousal Excitement

Unpleasant Feelings Pleasant

Feelings

Depression Sleepiness Relaxation

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ALCOHOL CRAVING QUESTIONNAIRE-SHORT FORM-REVISED

(ACQ-SF-R; Singleton, Tiffany & Henningfield, 2004)

INSTRUCTIONS: Please indicate how much you agree or disagree with each of the following statements by placing a single checkmark (like this: _X__) along each line between STRONGLY DISAGREE and STRONGLY AGREE. The closer you place your checkmark to one end or the other indicates the strength of your disagreement or agreement. We are interested in how you are thinking or feeling right now as you are filling out this questionnaire. Please complete every item.

RIGHT NOW

1. If I had some alcohol, I would probably drink it.