Behaviour Research and Therapy 41 (2003) 1149–1162www.elsevier.com/locate/brat

Alcohol-related motivational tendencies in hazardousdrinkers: assessing implicit response tendencies using the

modified-IAT

Tibor P. Palfai∗, Brian D. OstafinBoston University, Department of Psychology, 64 Cunningham St, Boston, MA 02215 2407, USA

Received 2 August 2002; received in revised form 22 November 2002; accepted 4 December 2002

Abstract

This study examined the utility of an implicit measure of cognitive associations, the Implicit AssociationTest (IAT; Greenwald, McGhee, & Schwartz, 1998), to assess alcohol-related approach dispositions. Forty-seven hazardous drinkers completed a modified IAT procedure that assessed the relation between alcoholand behavioral categories (i.e., approach and avoid). Participants completed a series of individual differencemeasures before an alcohol cue exposure task in which they anticipated alcohol consumption. Resultsindicate that the modified IAT is associated with binge drinking episodes, perceived difficulty controllingalcohol use, and appetitive responses to alcohol cues. Findings are discussed in terms of the potential valueof this measure to assess alcohol-related memory associations among those whose alcohol use puts themat risk for harm. 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Hazardous drinkers; Alcohol-related cognition; Implicit Association Test; Motivation; Action tendencies

1. Introduction

Common among many learning-based models of substance use is the view that substance-related motivation is driven by automatic, cue-elicited processes (e.g.,Baker et al., 1987; Gold-man & Rather, 1993; Stewart, de Wit & Eikelboom, 1984; Tiffany, 1990). A number of investi-gators have suggested that the presence of substance-related cues may activate an appetitive motiv-ational state that guides the acquisition and consumption of substances (Baker et al., 1987; Stewart,

∗ Corresponding author.+1-617-353-2580; fax:+1-617-353-6933.E-mail address: palfai@bu.edu (T.P. Palfai).

0005-7967/03/$ - see front matter 2003 Elsevier Science Ltd. All rights reserved.doi:10.1016/S0005-7967(03)00018-4

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de Wit & Eikelboom, 1984; Wise, 1988). The incentive motivational model proposed by Stewart,de Wit and Eikelboom (1984), for example, has characterized substance cues as conditioned incen-tive stimuli that, through extensive association with positive outcomes, come to elicit appetitivemotivational processes. Extensive research on cue reactivity has supported the view that alcoholcues may be associated with activation of a central appetitive motivational state (Carter & Tiffany,1999; Niaura et al., 1988). Compared with control cues, alcohol cues produce stronger urges todrink alcohol among both alcohol dependent and non-dependent drinkers (see Carter & Tiffany,1999) and have been shown to result in stronger global positive alcohol-related expectancies(Cooney, Gillespie, Baker & Kaplan, 1987). Similarly, priming doses of alcohol have been asso-ciated with increased desire to drink (Chutuape, Mitchell, & de Wit, 1994) among social drinkers.There is evidence to suggest that alcohol priming doses increase reward sensitivity for alcoholas well as for other incentives among heavier social drinkers (Fillmore & Rush, 2001; Kambouro-poulos & Staiger, 2001) and that those who experience stronger positive affective responses toalcohol (e.g., elation, vigor) may show stronger preferences for alcohol over other incentives(Kirk & de Wit, 2000).

With increasing support for the view that alcohol use behavior may be partly mediated by theactivation of a conditioned appetitive motivational state, there has been interest in delineating thekey elements and processes that may characterize alcohol use motivation. A number of investi-gators have adopted the concept of an information network structure (Bower, 1981; Lang, 1979)to characterize the memory representations that underlie drug motivational states. Although thereare differences among the models, the memory network perspective conceptualizes substance useas mediated by the activation of cognitive-motivational networks that contain information aboutsubstance-related cues, reinforcement expectancies, and response elements (Baker et al., 1987;Goldman & Rather, 1993; Niaura, Goldstein & Abrams, 1991; Stacy, 1997; Tiffany, 1990). Subst-ance-related motivation may be characterized by the activation of these interconnected informationelements which mediate the pursuit of positive incentives (Baker et al., 1987). Thus, a taste of afavorite beer may lead to greater attention to alcohol-related environmental cues, thoughts aboutpositive outcomes related to alcohol use, verbal response elements reflecting the desire to usemore, and the activation of action systems to support alcohol use behavior. Maladaptive substanceuse patterns may be understood as a function of memory networks in which substance-relatedinformation is more extensive, more tightly integrated, more likely to be activated in response tocues, and more likely to dominate over other response systems (Niaura et al., 1991).

Through the application of methods from social-cognition research, investigators have beenable to significantly advance their understanding of the cognitive representations and processesthat underly alcohol-related behavior (see Sayette, 1999). Recent evidence suggests that alcoholicsshow stronger attentional biases for alcohol-related words than non-alcoholics as measured by theStroop task (Johnsen, Laberg, Cox, Vaksdal, & Hugdahl, 1994) and dichotic listening tasks(Stetter, Chaluppa, Ackermann, Straube, & Mann, 1994), and show greater interference in taskperformance when secondary tasks include alcohol cues (Sayette et al., 1994). In laboratory stud-ies, the accessibility of alcohol expectancy information (as assessed by latency of response) hasbeen associated with both anticipatory urges to drink and volume of alcohol consumed amonghazardous drinkers (Palfai, Monti, Ostafin, & Hutchison, 2000). Morover, the priming of alcoholexpectancy information in memory has been shown to result in higher levels of alcohol consump-tion (Roehrich & Goldman, 1995; Stein, Goldman, & Del Boca, 2000).

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There have also been a number of studies that have examined the association between elementsof alcohol-related memory networks through priming and free association methods (e.g., Stacy,1995; Weingardt, Stacy & Leigh, 1996). (See Segal [1988] for a discussion on the assessment ofmemory networks). This research has shown that, compared to lighter drinkers, heavier drinkerspossess stronger associations in memory between outcome expectancies and other elements ofalcohol-related memory networks, including alcohol-related cues (Weingardt et al., 1996) andalcohol-related behaviors (Palfai & Wood, 2001; Stacy, 1995, 1997). For example, Stacy (1995)showed that heavy drinkers were more likely than light drinkers to generate alcohol-relatedbehaviors (e.g., drinking) as free associates to positive outcome words. Moreover, the frequencywith which alcohol-related associations are generated to outcome words has been shown to predictsubsequent drinking behavior (Stacy, 1997).

Recently, Wiers and colleagues (Wiers, van Woerden, Smulders & de Jong, 2002) used theImplicit Association Test [IAT] (Greenwald, McGhee & Schwartz, 1998) to examine alcohol-related associations among heavy and light drinkers. The IAT has been utilized extensively inthe attitude literature to provide a method of assessing non-conscious or automatic evaluativeassociations (Devine, 2001; Greenwald & Nosek, 2001). Participants are required to categorize aseries of computer-presented target words by pressing one of two keys on a response box. Thefour categories typically utilized are two target categories (e.g., “fl owers” and “ insects” ) and twoevaluative categories (e.g., “good” and “bad” ). Over a series of trials, the targets are paired withcongruent (e.g., flowers–good, insects–bad) and incongruent (flowers–bad, insects–good) evalu-ative categories which are mapped to a specific response key. The difference between the congru-ent and incongruent trials provides an index of the implicit attitude toward the target. The IAThas recently been applied to study cognitive representations in psychopathology (Gemar, Segal,Sagrati & Kennedy, 2001; Teachman, Gregg, & Woody, 2001). Teachman et al., (2001), forexample, found that implicit evaluative associations to spiders and snakes were specific to phobiatypes and that these responses were associated with self-reported fear to these stimuli.

Using soda as the contrast target category to alcohol, Wiers et al. (2002) found that heavydrinkers showed relatively faster performance on trials in which alcohol and arousal were mappedto the same response key compared to trials that paired alcohol and sedation but did not observethis difference among light drinkers. This implicit difference between heavy and light drinkerswas not, however, demonstrated when the evaluative categories that were used were positive-negative as both groups showed more negative evaluations to alcohol (relative to soda).

Wiers et al. (2002) suggest that heavy and light drinkers may differ with regard to the implicitassociations between alcohol and arousal expectancies (e.g., energetic, lively) but not alcohol andvalence expectancies. Although heavy and light drinkers may have similar evaluative responsesto alcohol, those who use alcohol more frequently may develop an increased activating responseto alcohol cues (Wiers et al., 2002). To explain these findings, the authors suggest that suchdifferences may be related to the distinction between wanting and liking alcohol (Robinson &Berridge, 1993). Robinson & Berridge (1993, 2001) have proposed that liking and wanting mayrepresent two distinct elements of incentive motivation. They suggest that the evaluative processesthat underly substance liking (e.g., pleasure) are distinct from the processes that underly incentivesalience (e.g., wanting) and concomitant approach-related behavior. Wanting and liking processesmay often be highly linked, but may become increasingly separable with persistent substance use.Through repeated use, substance related cues come to automatically activate psychomotor

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response to guide approach behavior even in the absence of pleasure or liking (Robinson &Berridge, 2001).

Others have also characterized substance use motivation in terms of this disposition to act (e.g.,Stewart et al., 1984; Toates, 1985; Wise, 1988). As Stewart et al. (1984) suggest, the substancerelated cue functions to influence substance use behavior, “not by virtue of satisfying some driveor need but rather by acting as a persistent goad to response generation.” The automatic activationof approach tendencies in response to alcohol cues may represent an implicit motivational processthat mediates problematic alcohol use behavior (Robinson & Berridge, 2001). From a memorynetwork perspective, the ability to assess this element of the memory network that is closelyrelated to behavior itself would appear to be critical for understanding automatic processes inalcohol-related motivation.

The current study was designed to extend the use of the IAT to assess alcohol-related motivationin a number of ways. First, the study was designed to examine the predictive value of a modifiedIAT procedure that assessed the strength of alcohol-approach associations in memory. Althoughevidence of strong associations between alcohol and arousal-related expectancies provide sugges-tive evidence for the role of psychomotor activation (Wiers et al., 2002), to our knowledge therehas been no study that has attempted to assess alcohol-approach associations directly. The currentstudy replaces evaluative categories (e.g., good/bad) with action tendency categories (e.g.,approach/avoid), to assess the strength of alcohol-behavioral disposition associations in memory.Second, the current study uses a sample of hazardous drinkers to examine the utility to this task.A number of studies have shown that alcohol-related associations distinguish between heavy andlight drinkers. However, to provide stronger evidence that these measures have clinical utility, itis important to demonstrate that these associations distinguish drinking patterns within a sampleof drinkers who have been assessed to be “at-risk” (i.e., hazardous drinkers). Third, the currentstudy examines the value of the modified IAT for predicting urge responses to alcohol cues. Byeliciting urge responses to the sight and smell of a favorite alcoholic beverage, the study examinedthe potential utility of alcohol-approach associations as an index of alcohol-related motivation.

To accomplish these aims, hazardous drinkers who selected from a community sample com-pleted a modified IAT, a series of individual difference measures, and participated in an alcoholcue exposure procedure in which affect, urges, and expected alcohol-related outcomes wereassessed. It was hypothesized that alcohol-related approach associations as measured by the IATwould be associated with individual differences in drinking behavior, perceived difficulty con-trolling alcohol-related behavior, and a general tendency to pursue reward (i.e., behavioralactivation). Moreover, it was predicted that higher IAT scores would be associated with strongerappetitive responses to alcohol cues, including stronger urges to drink and expected positive out-comes in anticipation of drinking.

2. Methods

2.1. Participants

Forty-eight hazardous drinkers (AUDIT = +8), whose most frequently consumed alcoholic bev-erage was beer, were recruited from local newspaper and university job boards to participate in

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the study. Eligibility requirements included age between 21 and 35, the use of English as a firstlanguage, and Alcohol Dependence Scores (Skinner & Allen, 1982) of less than 9. Those whohad previous treatment for substance abuse or dependence, currently used medications (other thanoral contraceptives), were nursing or pregnant (confirmed by urine test) or had any known impair-ments that may affect the ability to perform speeded cognitive tasks were excluded. One partici-pant failed to complete the measures and was thus eliminated from the analyses. Of the 47 studyparticipants in the final sample, the mean age was 22.96 years old (SD = 2.83) and 19 participantswere female. Participants drank an average of 14.89 days over the previous month (SD = 4.70)and consumed a mean of 4.54 drinks per occasion (SD = 2.05).

2.2. Measures

2.2.1. Implicit Association Test (Greenwald, McGhee & Schwartz, 1998)As discussed above, the IAT has been an extensively utilized measure of implicit attitudes (see

Devine, 2001). Participants are required to categorize a series of computer-presented words bypressing one of two keys. These words belong to one of four categories, two of them are targetcategories and two are evaluative categories. In order to measure behavioral activation related toalcohol, the current study modified the evaluative categories used in previous studies to reflectthe behavioral categories of approach and avoidance.

The target pair consisted of a set of ten words that were related to alcohol (e.g., brew, liquor)and ten words that were related to electricity (e.g., outlet, lightning). There have been a numberof discussions in the literature about the choice of contrast categories on the IAT (e.g., Brendl,Markman, & Messner, 2001; Greenwald et al., 1998; Nosek & Banaji, 2001). Certain categories,such as addictive substances, do not have clear opposites making the choice of a contrast targetdifficult (see Nosek & Banaji, 2001). One response to this problem is to use a contrast categorythat one would expect relatively similar evaluative responses across individuals. Previous researchon a smoking IAT has used a variety of contrast categories (e.g. sweets, stealing) with the rationalethat both non-smokers and smokers will have relatively similar preferences for the contrast categ-ories but that higher levels of smoking will be associated with a stronger preference for thesmoking category (Swanson, Rudman, & Greenwald, 2001). In the present study, electricity waschosen as a contrast category to alcohol as it was hypothesized to represent a similar responsecategory across participants that would provide a stable contrast (as opposed to other beveragessuch as “coffee” that may include greater variability of response). The behavior category pairconsisted of ten approach (e.g., advance, forward) and ten avoidance (e.g., withdraw, escape)words. Thus, the goal of the task is not to provide information about whether individuals preferalcohol more than electricity but rather to determine whether the strength of alcohol-approachtendency associations is related to individual differences in alcohol-related behavior.

On each trial, participants were instructed to classify a stimulus word into its correspondingcategory. The category titles were presented on the left and right of the stimulus word andremained on the computer screen throughout each block. The categories were mapped onto twokeys on a response box, with the left key representing the categories on the left half of the screenand the right key representing the categories on the right half of the screen. Thus, on a combinedtrial in which “alcohol” and “approach” categories were mapped onto the left half of the screen,participants would press the left key when words such as “ liquor” or “ toward” appeared in the

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center of the screen. Participants were instructed to use the index finger of each hand to makecategorization judgments. They were told to keep their left finger on the left response key andthe right finger on the right response key at all times and respond as quickly and accuratelyas possible.

The IAT was presented in seven blocks, consistent with previous work (Brendl et al., 2001).The seven blocks consisted of: (a) a 40 trial block of the target-concept discrimination (i.e.,alcohol on the left and electricity on the right), (b) a 40 trial block of the behavioral attributediscrimination (i.e. approach on the left and avoid on the right), (c) a 40 trial practice combinationblock (i.e. both alcohol and approach on the left and both electricity and avoid on the right), (d)an 80 trial block of the same combination described in (c), (e) a 40 trial block of the target-concept discrimination in which the target concepts were reversed (i.e., electricity on the left andalcohol on the right), (f) a 40 trial practice combination block (both electricity and approach onthe left and both alcohol and avoid on the right), (g) an 80 trial block of the same combinationas (f).

The stimulus words for the target-concept only and the behavioral-attribute only discriminationtrials were presented randomly. The stimulus words for the combination blocks were presentedrandomly with the only restriction that the trials alternated between target-concept and behavior-concept categories. A 250 ms interval separated each trial after a response was made. The experi-mental task was presented on an IBM-compatible personal computer using Micro-ExperimentalLaboratory (MEL) software (Schneider, 1995). The IAT procedure was similar to Greenwald,McGhee and Schwartz (1998) with modifications based on the work of Karpinski and Hilton(2001). First, no feedback was provided on trials indicating errors. And second, all participantswere presented with the compatible trials (e.g., alcohol-approach) followed by incompatible trials(alcohol-avoid).

2.2.2. Alcohol Use Disorders Identification Test (AUDIT) (Saunders, Aasland, Babor, De LaFuente & Grant, 1993)

The AUDIT is a ten-item screening instrument used to identify persons whose alcohol consump-tion patterns may put them at risk for alcohol-related harm. The self-report instrument, which hasbeen extensively validated in a number of countries, provides information about heavy alcoholuse, symptoms of alcohol dependence, and alcohol-related problems.

2.2.3. Time Line Follow Back -30 days (Sobell, Sobell, Leo, & Cancilla, 1988)This calendar-based self-report instrument was used to assess alcohol consumption patterns

over the previous month. It has been utilized extensively with a wide range of drinking populationsand has been shown to be a highly reliable and valid instrument of drinking quantity, frequency,and heavy drinking episodes. For males, heavy drinking episodes were calculated as consumptionof five or more drinks on a given occasion whereas for women heavy drinking episodes wereidentified as consumption of four or more drinks per occasion (Wechsler, Davenport, Dowdall,Moeykens, & Castillo, 1994).

2.2.4. Young Adult Alcohol Problems Screening Test (YAAPST) (Hurlbut & Sher, 1992)This is a measure of negative consequences related to alcohol use that includes problems rel-

evant to the general population and to young adults in particular. Respondents rate the frequency

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of a series of alcohol-related negative consequences that they may have experienced over the pastyear. The measure provides an extensive range of alcohol-related problems and has been shownto have good reliability and validity in previous studies (Wood, Read, Palfai, & Stevenson, 2001).

2.2.5. Temptation and Restraint Inventory (Collins & Lapp, 1992)The TRI was developed as a measure of drinking restraint. It contains two higher order factors,

Temptation to drink and Restriction of alcohol intake. The Temptation factor consists of threesubscales that assess: (1) persistent thoughts about drinking (Cognitive Preoccupation), drinkingto relieve negative affect (Emotional Drinking) and perceived difficulty controlling drinking(Govern). Previous research has established the validity and reliability of the Temptation factorand has shown that the Govern subscale shows a particularly strong association with quantity ofconsumption per occasion (Collins, George, & Lapp, 1989) and symptoms of alcohol dependence(Connor, Young, Williams, & Ricciardelli, 2000).

2.2.6. Behavioral Activation and Inhibition Scales (BIS/BAS; Carver & White, 1994)The BIS/BAS was designed to assess individual differences in activity related to Gray’s (1987)

two motivational systems; BIS which mediates responses to punishment, and the BAS subscalesmediate responses to reward. The BIS/BAS consists of 20, four-point Likert type items anchoredwith the responses of “strongly agree” and “strongly disagree” . There is support for both a twofactor structure corresponding to the behavioral inhibition and behavioral activation systems aswell as for more highly differentiated BAS subscales (Jorm et al., 1999). Reliability and validityof the BAS subscale as a measure of appetitive motivation has been established with both college(Carver & White, 1994) and community (Jorm et al., 1999) subsamples.

2.2.7. Urge to drink alcoholUrge to drink ratings were taken at several points during the procedure using an 11-point Likert

scale. These ratings have been utilized in several previous studies and have shown to be wellvalidated self-report measures of urges to consume alcohol (Monti et al., 1993; Palfai et al., 2000).

2.2.8. Affect grid (Russell, Weiss, & Mendelsohn, 1989)This measure assesses two central dimensions of affect, pleasure-displeasure and arousal-sleepi-

ness (Russell, 1979). Participants rate their affect by placing an X within a 9 × 9 Grid that isanchored with affect descriptors. Scores for arousal and valence are computed on single ninepoint scales based on the placement of the X. Research has demonstrated its convergent anddiscriminant validity with more extensive measures of affect (Russell et al., 1989).

2.2.9. Global positive expectancies (Cooney et al., 1987)To assess global expectations of pleasant alcohol effects, a brief measure was constructed using

five-point Likert-items. In addition to the two items regarding the anticipated ‘ taste’ and ‘effects’of alcohol used by Cooney et al., (1987), participants were asked about the degree to which theyexpected the consumption of alcohol to be satisfying. As the internal reliability of these threeitems was high (Coefficient alpha = 0.92), a composite score of global alcohol effects was calcu-lated based on these items.

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2.2.10. ProcedureAfter completing the pre-experimental procedures (e.g., breathanalyzer to confirm absence of

alcohol, pregnancy test for women, consent form), participants began the IAT as described above.Following completion of this task, participants completed a series of measures related to theiralcohol use (e.g. Time Line Follow-Back). Following a brief rest period, participants began aseries of individual difference measures. At the end of the questionnaire phase, participants com-pleted baseline measures of affect and urge to drink. They then began the cue exposure phase.All participants were presented with a glass of beer that they were told that they would consume.They were then asked to rate their urge to drink, affect, and their global positive expectancieswhile the beverage was in front of them (Anticipation Phase).

3. Results

3.1. Data reduction

Consistent with previous research using the IAT, (Greenwald et al., 1998), response time distri-butions demonstrated evidence of positive skewness. Responses longer than 3000 ms and shorterthan 300 ms likely reflect distractions and anticipations that represent processes distinct from thedomain of interest and were therefore eliminated from analyses along with incorrect responses(Brendl et al., 2001). The remaining data (exclusions represented less than 5% of the data) werelog-transformed in order to normalize the distribution and trials were averaged within each block.Mean response times for untransformed data were 850.65 ms (SD = 200.18) for congruent trialsand 941.80 ms (SD = 179.9) for incongruent trials. To measure the automatic activation ofapproach tendencies, mean response times to the congruent blocks were subtracted from the meanlatencies of the incongruent block. This difference reflected the primary measure of alcoholapproach associations. We refer to this difference throughout the manuscript as the IATapproach score.

3.2. IAT and individual difference measures

In order to examine the validity of the IAT as an implicit measure of alcohol-related responseassociations, a series of correlation coefficients were computed between IAT approach scores (i.e.,response times for incongruent trials—response times for congruent trials) and alcohol-relatedindividual difference measures. These analyses suggested that stronger alcohol-approach associ-ations were correlated with more intense drinking behavior. Those who had higher IAT approachscores reported more frequent binge drinking in the past month (r (47) = 0.34, p � 0.05). Simi-larly, partial correlations showed that IAT approach scores were associated with quantity of drink-ing per occasion (pr = 0.29, p = 0.05), controlling for gender. Although IAT approach scoreswere associated with heavier amounts consumed per single occasion drinking, they did not appearto be significantly associated with frequency of drinking (pr = �11, p = ns) or frequency ofalcohol-related problems in the past year as measured by the YAAPST (r (47) = 0.17, p = ns).

Examination of the association between the IAT and the Temptation subscales of the TRIshowed that the IAT scores were specifically associated with the Govern subscale (r (47) =

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0.33, p � 0.05) which assesses difficulty controlling alcohol use, but not the other Temptationsubscales (Emotional Drinking = 0.09; Cognitive Preoccupation = 0.09). As previous work hassuggested that individual differences in behavioral activation may be associated with appetitiveresponses to alcohol cues (Kambouropoulos & Staiger, 2001), we also examined the associationbetween the IAT and the BIS/BAS subscales. As expected, the IAT was positively correlatedwith sensitivity to positive incentives measured by the BAS composite (r (47) = 0.33, p �0.05) but not behavioral inhibition as measured by the BIS (r (47) = �0.09). Taken together, theIAT appears to be associated with approach tendencies toward alcohol within drinking contextsas suggested by higher frequency of binge drinking, more difficulty controlling alcohol use, andstronger sensitivity to reward.

3.3. IAT and reactivity to alcohol cues

Central to many information processing models is the view that cognitive representationsbecome automatically activated in the presence of eliciting cues (Baker et al., 1987). If the IATassesses individual differences in alcohol-specific action tendencies, they should be predictive ofappetitive responses when individuals are presented with a drinking context. In order to assessthis prediction, participants underwent a beverage administration procedure in which they antici-pated the consumption of their preferred alcoholic beverage (beer). Analyses of the associationbetween the IAT and reactivity to alcohol cues provided further support for this implicit measureof alcohol-specific approach tendencies.

3.4. Anticipatory responses to alcohol cues

In order to examine the influence of cues on indices of incentive motivation, a series of plannedcontrasts were conducted to examine subjective responses to the anticipation of consumption andfollowing consumption by comparing them to baseline ratings. In addition to the urge to drink,arousal and pleasantness ratings were taken at baseline and immediately before participants antici-pated consumption of beer placed before them. Contrasts indicted that urge ratings significantlyincreased from baseline (M = 3.57, SD = 2.22) to anticipation of consumption (M = 5.11, SD =2.45), F (1.46) = 29.21, p � 0.01. Similarly, affect also changed from baseline (Arousal M =3.55, SD = 1.50; Valence M = 5.11, SD = 1.37) to anticipation (Arousal M = 5.10, SD = 1.56;Valence M = 5.98, SD = 1.20). There were significant increases in ratings of arousal F (1.45)= 37.28, p � 0.01 and pleasantness, F (1.45) = 23.04, p � 0.01 in anticipation of drinking.

3.5. Predicting anticipatory responses to alcohol cues

To examine the predictive value of the modified IAT measure, separate analyses were conductedfor baseline and anticipation measures of alcohol-related motivation. Baseline measures of urgeto drink and affect were taken at the end of the second questionnaire period, prior to instructionson the beverage administration task. IAT scores were not significantly correlated with baselinemeasures of urge [r (47) = 0.11], arousal [r (47) = �0.12], or valence [r (47) = 0.10]. In contrast,IAT scores were significantly associated with subjective responses to the anticipation of alcoholconsumption. These scores indicate that IAT scores were significantly associated with alcohol

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specific responses including the composite measure of global positive expectancies from drinking(e.g., pleasant effects, pleasant taste, satisfying) [r (47) = 0.41, p � 0.01] and urges to drink [r(46) = 0.30, p � 0.05], but not general affect as measured by the Arousal scale[r (47) = 0.23,p = n.s.] or the Pleasantness scale [r (47) = 0.16, p = n.s] of the Affect Grid. To measure reactivityto the anticipation of alcohol consumption, a series of partial correlations was computed thatcontrolled for baseline responses. These analyses showed that those who scored higher on themodified IAT exhibited significantly stronger urge (pr = 0.30, p � 0.05) and arousal reactivity (pr = 0.30, p � 0.05) to the anticipation of drinking, although valence was not significant (pr =0.12, p = ns). Thus, IAT scores were associated with a number of indices of appetitive motivationincluding higher urge and arousal reactivity, and more positive expected effects of drinking beer.

4. Discussion

The present study was designed to examine alcohol-action tendency associations among hazard-ous drinkers. A modified IAT procedure was constructed to assess implicit alcohol-approach tend-encies. The pattern of associations between IAT scores and subjective responses to alcohol cuessupported the view that this measure may be a useful index of alcohol use motivation. IATapproach scores were associated with a number of appetitive responses to alcohol. Analyses ofsubjective responses suggest that those with higher alcohol-approach scores experienced strongerurges to drink, stronger positive expected outcomes, and stronger affective arousal responses inanticipation of alcohol consumption. These findings are consistent with the view that the presenceof cues that signal upcoming reward may increase the activation of an alcohol-related appetitivenetwork (e.g., Baker, Morse & Sherman, 1987).

This tendency to be more responsive to the incentive value of alcohol was further supportedanalyses of the individual differences data. IAT approach scores were associated with frequentheavy drinking episodes within the past month and higher levels of drinking per occasion. More-over, analyses of the specific subscales of the Temptation and Restraint Inventory suggested thatIAT was strongly associated with the Govern subscale but not the other subscales of Emotionaldrinking or Cognitive Preoccupation of the Temptation factor. These findings indicate that thosewith stronger implicit approach tendencies appear to have specific difficulties controlling theirdrinking behavior, but are not necessarily more likely to drink in response to emotional cues orthink more about drinking. These results parallel findings from previous research on the Temp-tation and urge reactivity with hazardous drinkers in which those with high Govern subscalescores reported stronger urges to drink both before and after alcohol consumption (Palfai, 2001).Additional support for the modified alcohol-specific IAT as an index of appetitive motivationaltendencies comes from correlational analyses with the BIS/BAS measure (Carver & White, 1994).Consistent with previous research on behavioral activation and alcohol cue reactivity(Kambouropoulos & Staiger, 2001) the IAT approach score were associated with the BAS scale,but not the BIS, suggesting that the performance on the modified IAT is associated with individualdifferences in reward responsiveness.

Results of the present study are consistent with the view that alcohol-related motivation maybe cognitively represented as stronger relative associations between alcohol and approach tend-encies. The pattern of correlations between the IAT and other measures suggests that this modified

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IAT may be specifically associated with cue-activated drinking behavior. IAT response times werecorrelated with heavy drinking episodes, quantity per occasion, difficulty controlling consumptionand urges in anticipation of drinking. They were not, however, significantly associated with fre-quency of consumption, thoughts about drinking, or urges in non-cued contexts (i.e., baseline).Thus, it appears that this IAT may assess memory representations that are particularly importantfor determining responses to alcohol cues (e.g., desire to drink on exposure to alcohol-relatedstimuli, decisions about how much to consume) and less informative regarding the processes thatinfluence decisions about whether to place oneself in alcohol-related environments.

Clearly there are a number of issues that need to be addressed to better understand this modifiedIAT as a measure of alcohol-specific action tendencies. First, this IAT creates a summary scorethat involves the difference between approach and avoidance tendencies. As a difference score,the measure obscures the fact that individuals who are more alcohol-involved may experienceboth strong approach and avoidance associations to alcohol (Breiner, Stritzke, & Lang, 1999).This would suggest the need for an independent assessment of alcohol-specific approach andavoidant tendencies. However, even if these dimensions are not bipolar, the relative strength ofthese tendencies may still be an important predictor of alcohol use behavior as final outputdecisions (e.g., whether to drink more or to stop drinking) require the dominance of one motiv-ational system over another (Miller, 1944; Toates, 1985). From this perspective, a given stimulusmay activate both approach and avoidance motivational systems, however, those with relativelystronger approach tendencies will exhibit evidence of stronger alcohol motivation in the form ofgreater levels of alcohol consumption. Whether the difference score is the best method of assessingthe dominance of one motivational system is an open question. Regardless of this possibility, theindependent implicit assessment of alcohol-specific approach and avoidant tendencies would bean important next step in efforts to understand self-regulatory processes in alcohol use and todevelop assessment instruments for those who are in treatment. Second, the IAT task employeda specific order of category presentation. Other research has indicated that using a single presen-tation order may influence the magnitude but not the direction of IAT effects (Karpinski & Hilton,2001). However, future studies should be conducted which examine the use of compatible andincompatible blocks first in order to control for individual differences in the ability to switchresponse sets (Mierke & Klauer, 2001). Third, more extensive research must be conducted onestablishing the reliability of this measure. Although these findings suggest the potential utilityof this modified IAT for assessing alcohol-related motivation, determination of the validity of thismeasure is bounded by estimates of its reliability. Recent work (Cunningham, Preacher, & Banaji,2001) has suggested a number of ways to examine the reliability of these response time measureswhich need to be incorporated in future work, especially if these measures are to be incorporatedinto clinical assessment. Finally, it must be noted that participants in this study completed theself-report measures in a fixed order which may have influenced the specific pattern of associationswith the IAT measure. Future efforts to validate this modified IAT should examine alternativemeasures of this alcohol-approach construct, conduct more extensive assessments to establish itsdiscriminant and convergent validity, and counterbalance questionnaire administration to increaseconfidence about results.

Despite the need for more extensive work to address these issues, the current research contrib-utes to the growing body of evidence for implicit cognitive-motivational processes in alcohol useby demonstrating the utility of a motivational IAT. First, this modified IAT was associated with

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a variety of responses to alcohol cues in anticipation of consumption. These findings provideconverging evidence that the modified IAT may assess critical elements of the alcohol-relatedmotivational networks. This may hold value for developing implicit measures of drug use motiv-ation which may be important for understanding the distinct contributions of implicit and explicitprocesses in drug use behavior (Tiffany, 1990). Second, the modified IAT was associated withheavy episodic drinking and perceived difficulty controlling alcohol use among a sample of youngadult hazardous drinkers. As such, this measure may be useful for identifying those at risk ofdeveloping harmful drinking patterns. Additionally, implicit measures such as the IAT may beparticularly useful to assess these vulnerabilities as they are less susceptible to social desirabilitybiases or defensiveness (Greenwald et al., 1998). The development of implicit indices of alcoholuse motivation may have particular value in cue reactivity assessment procedures as many ofthose who are in treatment or have strong pressures not to drink may not report urges in responseto high risk cues (Monti et al., 1993). Finally, the current findings may also have general impli-cations for the assessment of motivational processes in other forms of psychopathology. The mostimportant contribution in this regard is the extension of the IAT task from assessment of evaluativedimensions to one that assesses action tendencies. Because action tendencies represent such a keyelement of motivational states (Baker et al., 1987; Lang, 1995; Stewart et al., 1984; Toates, 1985),it may be beneficial to assess these dimensions of memory networks in efforts to better understanddepression (Gemar, Segal, Sagrati & Kennedy, 2001), anxiety (Teachman et al., 2001), and otherforms of psychopathology.

Acknowledgements

This work was supported in part by grant #R01 AA11534-05 from NIAAA to the first author.Correspondence regarding this manuscript should be sent to Tibor Palfai, Department of Psy-chology, 648 Beacon St. Boston, MA, 02215, USA or by e-mail at palfai@bu.edu.

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