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Impaired decision making as a risk factor for college student drinking

Dissertation
Author: Dana Figlock
Abstract:
The primary aim of the present study was to determine whether impairment on neuropsychological measures of decision making predicts increased alcohol use among college students. It was hypothesized that poorer performance on measures of decision making would predict linear increase on indicators of alcohol consumption across the first year of college. An additional aim was to assess whether established risk factors for college student drinking would moderate the association between decision making abilities and increased alcohol consumption, with the expectation that decision making would be more strongly associated with escalation in alcohol use for participants that are male, have a family history of alcohol abuse, report a longer history of pre-college alcohol use, hold more positive alcohol expectancies, and are more impulsive. Aims were pursued in a relatively homogeneous sample of first year college students (N = 136), using a prospective, longitudinal design in which decision making and drinking were assessed at three time-points during the first year of college. Participants additionally provided sociodemographic information and completed self-report impulsivity and alcohol expectancy questionnaires at each assessment. Results showed that drinking and associated negative consequences increased over time during the participants first year in college. However, there was generally little support for the hypotheses that poor decision making abilities are a risk factor for increased alcohol consumption, and that the association is moderated by established risk factors for drinking. Results suggest the need to consider whether drinking is indeed indicative of impaired decision making and underscore the importance of including other factors, especially perceived benefits and influence of social pressure, in models of decision making striving to predict drinking among college students.

vi TABLE OF CONTENTS LIST OF TABLES ........................................................................................................... viii CHAPTER I. INTRODUCTION……………………………………………………….1 Cognitive Correlates of Alcohol Use…………………………………….2 Adults with Alcohol Dependence…………………………………2 Neuropsychological Findings……………………………..2 Neural Findings…………………………………………...4 Social Drinking……………………………………………….......5 College Students……………………………………………..........6 Adolescents…………...….…………………………………….....8 Neural Development………………………………………9 High-Risk Studies………………………………………..11 Consequences of Use…………………………………….13 Summary………………………………………............................14 Decision Making…………………………………………………………14 Decisions Under Uncertainty…….……………………………....14 Decisions Under Risk and Ambiguity…………………...16 The Role of Emotions………………………………........18 Summary.......................................................................................21 Impaired Decision Making………………………………………21 Assessing Decision Making under Ambiguity with IGT………..22 Assessing Decision Making Under Risk with Cups Task……….26 Summary………………………………………………………...28 Substance Use and Decision Making…………………………………….28 Studies Using the IGT…………………………………………...30 Discounting of Delayed Rewards………………………………..33 Summary…………………………………………………………35 College Student Drinking and Decision Making………………………...36 Studies of Decision Making in Adolescents……………………..36 Prevalence of Alcohol Use……………………………………....37 Studies of Decision Making in College Students………………..39 Risk Factors for College Student Drinking……………………...41 Summary and Hypotheses……………………………………….44

II. METHOD………………………………………………………………..46

Participants...…………………………………………………………….46 Procedure………………………………………………………………..46 Self-Report Measures…………………………………………………....47 Measures of Decision Making…………………………………………...49

vii Statistical Procedures…………………………………………………….51

III. RESULTS……………………………………………………………….53

Descriptive Statistics……………………………………………………..53 Correlations………………………………………………………………54 Completers vs. Noncompleters…………………………………………..55 Preliminary Analyses…………………………………………………….55 Aim 1: Decision Making as a Predictor for Alcohol Use………………..59 Aim 2: Moderators of Relationship between Decision Making and Drinking………………………………………………………............62 Aim 3: Covariation between Drinking and Negative Consequences Over the First Year of College……………………………………….64 Aim 4: Ecological Validity of Decision Making Tasks ……...………….65

IV. DISCUSSION…………………………………………………………..66

Decision Making as a Risk Factor for Drinking…………………………67 Interaction between Decision Making and Risk Factors for Drinking…..68 Covariation of Drinking and Negative Consequences…………………...69 Ecological Validity of Measures of Decision Making…………………...71 Accounting for Null Findings……………………………………………72 Strengths and Limitations……………………………………………......76 Implications and Future Directions………………………………………78 Conclusion……………………………………………………………….82

NOTES………………………………………………………………………………….84

REFERENCES…………………………………………………………………………86

APPENDIX TABLES…….………………………………………………………...…103

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LIST OF TABLES Table A1. Descriptive Statistics at Time 1 (N = 136)……………………………………..…104 A2. Descriptive Statistics at Time 2 (N = 134)………………………………….........105 A3. Descriptive Statistics at Time 3 (N = 102)…………………………………….…106 A4. Descriptive Statistics for Alcohol Use at Times 1 - 3………………………….....107 A5. Descriptive Statistics for Negative Consequences of Alcohol Use………...….....108 A6. Means and Standard Deviations for Measures of Decision Making Times 1-3.....109 A7. Correlations between Indicators of Alcohol Use and Measures of Decision Making……………………………………………………………………………110 A8. Associations between Harmful Drinking (AUDIT Scores) and Decision Making Tasks Over the First Year of College………………………………………….…111 A9. Associations between Drinking Quantity and Decision Making Tasks Over the First Year of College……………………………………………………………...113 A10. Associations between Binge Drinking Frequency and Decision Making Tasks Over the First Year of College……………………………………………………115 A11. Correlations between Indicators of Alcohol Use and Composite of Negative Consequences of Drinking…………………………………………………….…117 A12. Covariation between Indicators of Alcohol Use and Alcohol-Related Negative Consequences…………………………………………………………………….118 A13. Correlations between Measures of Decision Making at Time 1 and Composite of Negative Consequences of Drinking at Times 1-3……………………………119

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CHAPTER I INTRODUCTION It is now well established that persons with long histories of heavy drinking sometimes experience structural and functional changes in the brain, especially in the frontal lobes, that are associated with impaired cognition. Investigations of the causal relationship between alcohol use and cognitive functioning have yielded mixed results because of the evidence for an association between long-term alcohol use and cognitive risk factors that increase the likelihood of alcohol abuse. Recent theories of decision making have been invoked to explain compulsive drinking; they predict that deficits in cognitive ability precede alcohol dependence. Although studies reliably demonstrate that persons with alcohol dependence perform poorly on validated laboratory measures of decision making, temporal precedence has not been established. Given the prevalence and consequences of heavy drinking among college students, decision making abilities, considered a potential risk factor for drinking in this population, merit assessment. Although a number of empirical studies have sought to identify risk factors for drinking by college students, no studies to date have examined decision making as one such risk factor. The present study seeks to determine whether impairment on neuropsychological measures of decision making predicts alcohol use in college students. This goal was accomplished by utilizing a longitudinal design in which decision making and drinking were assessed at three time-points over the first year of college. The following review of the literature provides a theoretical basis for the study. It begins with a review of general cognitive impairments associated with substance use,

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with a focus on whether such deficits presage alcohol use or, instead, are consequences of heavy alcohol use. The cognitive abilities that permit decision making were of particular interest to the present study, so theories of decision making are reviewed. Evidence is presented attesting to the utility of laboratory measures of decision making in persons with substance dependence. Finally, the literature on decision making abilities among binge drinking college students is reviewed; it highlights the need to consider decision making as a risk factor for drinking in this population. Cognitive Correlates of Alcohol Use Adults with Alcohol Dependence Neuropsychological findings. One of the earliest reviews of cognitive functioning in alcoholics concluded that alcoholics perform more poorly than healthy controls on a variety of neuropsychological measures (Kleinknecht & Goldstein, 1972). Studies over the past 30 years have corroborated these findings, consistently demonstrating that chronic, heavy alcohol consumption is associated with concomitant changes in general cognitive functioning (e.g., Bates, Bowden & Barry, 2002; Giancola & Moss, 1998), as evidenced by poorer performance on measures of visuospatial abilities and memory (e.g., Sullivan, Fama, Rosenbloom & Pfefferbaum, 2002; Ratti et al., 1999; Parsons, 1998). The extent to which alcohol dependence is associated with deficits in the “higher order” cognitive operations known as executive functions, which guide complex behavior through self-direction, delayed gratification, planning, decision-making, and response control, has also been examined (Zinn, Stein, Swartzwelder, 2004; Barkley, 1997). Specific abilities related to executive functioning assessed by neuropsychological measures include attentional control, abstract reasoning, cognitive flexibility, working

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memory, decision making, and planning (Stuss & Benson, 1984). To the extent that compulsive, pathological drinking is influenced by poor behavioral control and decision making, there should be an association between alcohol dependence and measures of executive functioning such as the Wisconsin Card Sorting Task (Heaton, 1981), Tower of Hanoi (Lezak, 1995), Stroop Test (Stroop, 1935), Trail Making Test (Reitan & Wolfson, 1993), and word-fluency tests (Benton & Hamsher, 1978). Consistent with expectations, studies have reliably demonstrated that executive functions are often the most severely impaired of all cognitive deficits in alcohol- dependent adults (Giancola & Moss, 1998). Alcoholics have slower processing speed and impaired cognitive flexibility and attentional control as compared to non-alcoholics (Zinn et al. 2004; Ratti, Bo, Giardini & Soragna, 2002; Paraherakis, Charney, & Gill, 2001). They also have difficulty manipulating information in working memory, planning, and inhibiting impulsive behavioral responses (Noel, Bechara, Dan, Hanak & Verbanck, 2007). Deficits in executive functioning persist after cessation of drinking and have been observed in alcoholics who have been abstinent for several weeks (Bates, Voelbel, Buckman, Labouvie & Barry, 2005; Zinn et al., 2004). These deficits do, however, improve with longer periods of abstinence (Mann, Gunther, Stetter, Ackermann, 1999); Rourke and Grant, 1999), indicating that impairment in executive functioning is partially reversible. Although speculations are tentative, the finding that impairment can improve with abstinence suggests that cognitive dysfunction may partly be a consequence of alcohol use rather than a premorbid vulnerability.

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Neural findings. Given the pervasiveness of executive functioning deficits in alcoholics, a number of studies have sought to identify neural correlates of the observed impairment. Numerous studies have shown that executive functions are largely mediated by the frontal lobes (e.g., Casey, Giedd & Thomas, 2000; Shallice, 1988), specifically, the region of the prefrontal cortex (PFC; Lezak, 1995; Stuss & Benson, 1984). However, most neuroimaging and neurophysiological studies of the brains of alcohol-dependent individuals have focused on frontal lobe functioning more generally. Studies using positron emission tomography have identified decreased cerebral metabolic rates in the medial-frontal region of the frontal cortex in alcoholics (e.g., Adams et al., 1993; Gilman et al., 1990). Single photon emission computed tomography (Gansler et al., 2000; Nicolas et al., 1993), computerized tomography (Rosse, Riggs, Dietrich, Schwartz & Deutsch, 1997; Ron, Acker & Lishman, 1980), and magnetic resonance imaging (Pfefferbaum, Sullivan, Mathalon & Lim, 1997; Sullivan, Marsh, Mathalon, Lim & Pfefferbaum, 1996) studies have similarly provided evidence for diminished frontal lobe functioning. These results converge to document the presence of dysfunction and morphological abnormalities in the frontal lobes of chronic alcoholics (Moselhy, Georgiou & Kahn, 2001). Taken together, the results of these studies suggest that alcoholism is associated with structural and functional changes in the brain, especially in the frontal lobes, that are associated with cognitive changes. However, most of these studies used clinically referred patients with long histories of alcohol dependence, leaving several important questions unanswered: 1) Does the observed cognitive impairment represent a change from pre-morbid functioning? 2) Is cognitive impairment a cause or a consequence of

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alcoholism? 3) If the observed deficits are in fact changes in functioning, at what point in the drinking history does this occur? Examining the neural and cognitive characteristics of younger, heavy drinkers without alcohol dependence, adolescents with a genetic risk for alcoholism, or both might provide at least partial answers to these questions. Social Drinking In light of the apparent cognitive consequences of alcoholic drinking, researchers have questioned whether similar impairments are observed among heavy “social” drinkers. Social drinkers are an important population to study because they use alcohol regularly but have not progressed to problematic alcohol use and, presumably, have had less exposure to its neurotoxic effects. Thus, careful study of social drinkers may reveal how much alcohol consumption is necessary to produce the cognitive deficits that are identified in persons with alcohol dependence. Early studies conducted by Parker and Noble (1977, 1980) provided support for the continuity hypothesis (Ryback, 1971), which predicts a linear relationship between amount of alcohol consumed and cognitive deficits. However, a review of the literature on social drinking found that these results were not entirely replicable and questioned whether other causal hypotheses (i.e., alcohol-threshold) or non-alcohol-causal hypotheses (i.e., cognitive-causal, stress-emotional-causal, genetic-causal) may better account for the relationship (Parsons & Nixon, 1998; Parsons, 1986). A substantial problem with the literature on social drinking is that studies have not consistently defined social drinking, with definitions varying from three U.S. standard drinks (USSD) per week (Carey & Maisto, 1987) to 105 USSD drinks per week (Williams & Skinner, 1990), making it especially difficult to make cross-study

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comparisons. To address this issue, in a review of 17 studies conducted between 1986 and 1996, Parsons and Nixon (1998) classified studies into two groups: those that found evidence of cognitive impairment and those that did not. Results showed that mean number of weekly drinks per week was significantly higher in the group with cognitive impairment, suggesting that impairment was only detectable in samples that drank most heavily and frequently. This review, which failed to provide support for non-alcohol causal hypotheses, instead suggested that cognitive impairment is related to the amount of alcohol consumed per occasion, but only after an individual’s threshold for alcohol intake (MacVane, Butters, Montgomery & Farber, 1982) has been reached. Parsons and Nixon (1998) concluded that consuming 5-6 USSD drinks daily over time increases risk for cognitive impairment, a risk that increases with daily consumption of 7-9 USSD drinks, and becomes most likely in persons with a daily consumption of 10 or more USSD drinks. These findings have implications for the current categorical classification of college student binge drinking (discussed below) and may make it difficult to detect cognitive impairment among heavy drinking college students. College Students Studies of college student drinking typically classify students according to whether or not they engage in binge drinking (Wechsler, Davenport, Dowdall, Moeykens & Castillo, 1994) which was defined by Wechsler and his colleagues as four or more drinks on a single occasion by women and five or more drinks by men (Wechsler, Dowdall, Davenport & Rimm, 1995; Wechsler & Nelson, 2001); students are further categorized by frequent binge drinking status, defined as binge drinking three or more times during a two-week period (Wechsler et al., 1994). Such categorization, which

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greatly reduces the variability in quantity and frequency of individual drinkers, may not be the best method for studying the effects of drinking. Consequently, several studies have instead classified college students based on the presence of an alcohol use disorder, as determined by the Diagnostic and Statistical Manual of Mental Disorders, 4 th Ed. (DSM-IV; APA, 1994). Studies that have elected to examine the heaviest and most problematic college- aged drinkers identify impairment on several neuropsychological measures. However, in many cases, there are few differences between drinkers and non-drinkers. For example, a cross-sectional study of first-year undergraduates revealed that students with alcohol use disorders (AUDs: alcohol abuse and alcohol dependence) performed more poorly on measures of visuospatial ability and motor speed, but did not differ from non-AUD students on measures of verbal ability, memory, or attention (Sher, Martin, Wood & Rutledge, 1997). These findings were especially pronounced for students who met criteria for alcohol dependence (versus abuse) and are generally compatible with those obtained in adults with alcohol dependence. However, at seven-year follow-up, there were relatively few differences in cognitive functioning between these groups, even though the students who had AUDs in the first year of college reported greater alcohol consumption at follow-up than those without AUDs (Wood, Sher & Bartholow, 2002). Based on the apparent lack of differences between groups, the authors concluded that heavy drinking during the college years does not seem to be associated with lasting impairments in cognition. Studies that have specifically examined executive functioning as it relates to college student drinking generally have not reported a significant association between

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these variables (e.g., Wood et al., 2002; Blume, Marlatt & Schmaling, 2000; Sher et al., 1997). For example, the authors of a recent study aimed to determine whether the negative consequences of alcohol use could be explained by deficits in executive control (Whitney, Hinson & Jameson, 2006). The authors did not find a relationship between a general deficit in executive functioning and negative consequences of drinking, suggesting poor external validity of broad-spectrum measures of executive functioning. However, these findings contrast with those of an earlier study (Giancola, Zeichner, Yarnell & Dickson, 1996), which found a significant association between executive functioning and the severity of consequences of alcohol use. These conflicting results may be an artifact of methodological differences such as the inclusion of only male participants in a study (Giancola et al., 1996). In contrast to the robust findings of executive functioning in alcohol dependent adults, studies of college student drinkers have largely failed to document similar impairment. Even when such deficits are noted, heavy drinking college students do not show impairment at the level observed in alcohol-dependent adults (Giancola & Tarter, 1999). Although causal conclusions cannot be drawn from cross-sectional studies, these results appear to suggest that a) cognitive impairments, including executive dysfunction, are only associated with heavy alcohol use that escalates beyond that which characterizes college student drinking, or b) it is necessary to look for moderating variables to detect cognitive impairment in college students. Adolescents Studies of alcohol-dependent adults and heavy social drinkers have provided evidence for the cognitive and neural changes that accompany protracted alcohol use.

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However, it remains unclear when in a person’s “drinking career” structural, functional, and/or cognitive changes occur (Tapert, Caldwell & Burke, 2004). The period of adolescence, commonly defined as the second decade of life (Monti et al., 2005), provides a unique window of opportunity to study the effects of alcohol on the brain, given that adolescents, developmentally, are old enough for risk factors to be detected but young enough that differences in potential risk markers cannot be attributed to the consequences of alcohol use (Nigg et al. 2004). Although many advances have been made in this arena, it remains unclear whether adolescent alcohol use definitively causes brain damage (Moss, 2008). This issue has proven sufficiently important that NIAAA released a Request for (Grant) Applications in January, 2007, specifically to address the consequences of alcohol use on the developing brain and whether potential deficits persist or recover. A review of the extant literature provides evidence for both pre- existing cognitive vulnerabilities toward alcohol use and cognitive consequences of alcohol use. Neural development. Before considering neural and cognitive functioning in high risk or alcohol abusing adolescents, it is first necessary to consider the changes that occur in healthy adolescents during this period of development. Two main maturational events occur in the brain during this time: axonal myelination tissue and synaptic pruning (Blakemore & Choudhury, 2006). Myelination of axons serves to increase the speed of neural transmission and is completed in most brain regions during early childhood; however, myelination in the frontal cortex increases in the prefrontal area during adolescence (Clark, Thatcher & Tapert, 2008; Ashtari et al. 2007; Barnea-Goraly et al., 2005; Lenroot & Giedd, 2006) and continues into early adulthood (Moss, 2008;

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Schneider et al, 2004). In contrast, the proliferation of synapse formation during the postnatal period results in an overabundance of connections that reaches peak volume around 12 years of age; these are then eliminated, or “pruned”. Pruning begins relatively late in the prefrontal cortex (Gotgay et al., 2004; Lenroot & Giedd, 2006; Sowell, Thompson, Leonard, Welcome, Kan & Toga, 2004) and continues through young adulthood (Moss, 2008; Sowell, et al., 1999; Giedd, et al., 1999). To summarize, the teen years and early-mid twenties are characterized by linear increases in myelination in the prefrontal cortex and decreases in prefrontal gray matter. Because the prefrontal cortex is one of the last brain regions to mature (Nigg et al., 2004; Casey, Giedd & Thomas, 2000; Giedd et al., 1999), it may be more sensitive to the effects of alcohol. An imaging study of adolescents with alcohol use disorders showed that adolescents with alcohol use disorders have less prefrontal white matter volume than healthy controls (De Bellis, Narasimhan, Thatcher, Keshavan, Soloff & Clark, 2005). This is a potentially important finding, given that increasing white matter organization is associated with development of executive functioning in adolescents (Clark et al., 2008). Although this study did not determine whether delayed white matter organization was a result of alcohol use or predated it (Clark et al., 2008), evidence from experimental studies using animal models suggests that several areas of the juvenile brain, including the ventral prefrontal cortex, are more sensitive to alcohol-induced brain damage than are adult brains (Crews et al., 2000). Thus, it is possible that the adolescent brain is preferentially susceptible to alcohol induced neural changes. Unfortunately, all of the current evidence supporting the view that AUDs in human adolescents are associated

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with differences in brain structure and function come from small, cross-sectional studies that preclude causal conclusions. High-risk studies. To address the question of causality, several lines of research have employed the high risk paradigm, which questions whether children of alcoholic parents exhibit cognitive impairments prior to the onset of problem drinking (Nigg et al., 2004). Having a biological parent with alcoholism is the strongest predictor of alcoholism in children (Schuckit, 1986). Therefore, if cognitive deficits exist in children with a family history of alcoholism, they may represent potential risk factors for the development of subsequent substance use disorders (Giancola & Tarter, 1999). Studies reliably identify a relationship between family history of alcoholism and poorer cognitive functioning. Adolescent boys with a family history of alcoholism have poorer language skills (Tapert & Brown, 2000), lower full scale IQ, and weaker capacity for delay of gratification (Nigg et al., 2004). Children from high-density alcoholism families, defined by the presence of an alcoholic father and at least two other first or second degree alcoholic relatives, showed additional impairments on measures of visuocontructional abilities, working memory, and executive functioning at baseline assessment. When they were assessed three years later, between the ages of 11 and 17 years old, there were no group differences on visuoconstructional abilities or working memory; however, adolescents from high density alcoholism families remained impaired on measures of executive functioning (Corral, Rodriguez, Holguin & Cadaveira, 2003). These findings suggest that the development of executive functioning is affected by family history of alcoholism and that executive functioning does not “catch up” as readily as other cognitive abilities.

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Other studies that specifically examined executive functioning have generally shown that at-risk adolescents are impaired in this domain (Nigg et al., 2004; Shoal & Giancola, 2001; Giancola & Tarter, 1999; Harden & Pihl, 1995). Such deficits are significantly related to the negative consequences associated with substance use (Shoal & Giancola, 2001) and age of first drink (McGue et al., 2001). Although some studies failed to demonstrate clear impairment (e.g., Nixon & Tivis, 1997), that may have been due to the variability of the measures used to examine executive functioning in cross-study comparisons. Executive functioning is a multi-faceted construct (Miyake, Friedman, Emerson, Witzki & Howerter., 2000) that cannot be readily captured by one common factor (Nigg et al., 2004); failure to provide a comprehensive battery of tests (e.g., Wisconsin Card Sorting Task, Trail Making Test) could result in conflicting findings. Evidence from imaging studies corroborates the results of neuropsychological testing. Youth with a family history of alcoholism were shown to have less neural activation in prefrontal, occipital, and parietal regions during a behavioral inhibition task of executive functioning (Schweinsburg et al. 2004). In a recent study, high risk adolescents demonstrated less frontal activation during an anti-saccade measure of executive functioning (McNamee et al., 2008), confirming the presence of neural deficits in brain regions associated with inhibition among high-risk youth. High-risk studies of adolescents sometimes include teens that currently use substances and/or have a substance use disorder. Inclusion of this group makes it more difficult to detect cognitive risk factors but does allow for the study of the synergistic effects of vulnerability and protracted use of alcohol and drugs. Substance-using adolescents with a family history of alcohol abuse show impaired attention (Tapert &

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Brown, 2000) and executive functioning (Tarter et al., 2003). Executive dysfunction in this group is associated with more negative consequences of substance use (Shoal & Giancola, 2001) and appears to mediate the relationship between parental substance use disorder and the child’s substance use disorder (Tarter et al., 2003). Consequences of use. Attention has recently turned toward investigating the neuropsychological correlates of adolescent alcohol dependence, irrespective of whether or not there is familial risk for alcoholism. These studies have shown that alcohol dependence in adolescents is associated with impaired performance on measures of verbal abilities, processing speed (Brown, Tapert, Granholm & Delis, 2000), general executive functioning (Giancola & Tarter, 1999), and attention (Tapert, Granolm, Leedy & Brown, 2002; Tapert & Brown, 1999). Of note, attentional difficulties were most pronounced in adolescents who continued to abuse substances between baseline assessment and reassessment four (Tapert & Brown, 1999) and eight years later (Tapert et al., 2002). This finding suggests that a longer duration of alcohol use is associated with greater cognitive impairment in this domain. In a recent review, Tapert, Caldwell and Burke (2004) concluded that several factors moderate the relationship between adolescent alcohol dependence and cognitive impairment in attention and visuospatial abilities. These include the severity of alcohol dependence as approximated by the number of withdrawal symptoms (Tapert et al., 2002; Brown et al., 2000; Tapert & Brown, 1999), family history of alcoholism (e.g., Tapert & Brown, 2000), and being female (Medina et al., 2008; Tapert et al., 2001; Moss et al., 1994). Further research is needed to explore the effect of these moderating variables on other domains of cognitive functioning.

Full document contains 134 pages
Abstract: The primary aim of the present study was to determine whether impairment on neuropsychological measures of decision making predicts increased alcohol use among college students. It was hypothesized that poorer performance on measures of decision making would predict linear increase on indicators of alcohol consumption across the first year of college. An additional aim was to assess whether established risk factors for college student drinking would moderate the association between decision making abilities and increased alcohol consumption, with the expectation that decision making would be more strongly associated with escalation in alcohol use for participants that are male, have a family history of alcohol abuse, report a longer history of pre-college alcohol use, hold more positive alcohol expectancies, and are more impulsive. Aims were pursued in a relatively homogeneous sample of first year college students (N = 136), using a prospective, longitudinal design in which decision making and drinking were assessed at three time-points during the first year of college. Participants additionally provided sociodemographic information and completed self-report impulsivity and alcohol expectancy questionnaires at each assessment. Results showed that drinking and associated negative consequences increased over time during the participants first year in college. However, there was generally little support for the hypotheses that poor decision making abilities are a risk factor for increased alcohol consumption, and that the association is moderated by established risk factors for drinking. Results suggest the need to consider whether drinking is indeed indicative of impaired decision making and underscore the importance of including other factors, especially perceived benefits and influence of social pressure, in models of decision making striving to predict drinking among college students.