Experimental and Clinical Psychopharmacology

© 2018 American Psychological Association 2018, Vol. 26, No. 4, 354–365 1064-1297/18/$12.00 http://dx.doi.org/10.1037/pha0000206

Moderation of Craving Reactivity to Drinking-Related Contexts by Individual Differences in Alcohol Sensitivity: An Ecological Investigation

Constantine J. Trela, Alexander W. Hayes, Andrew C. Heath Bruce D. Bartholow, and Kenneth J. Sher Washington University School of Medicine and Midwest University of Missouri and Midwest Research Alcoholism Research Center, St. Louis, Missouri Center, St. Louis, Missouri

Thomas M. Piasecki University of Missouri and Midwest Alcoholism Research Center, St. Louis, Missouri

Laboratory cue exposure investigations have demonstrated that, relative to drinkers who report a high sensitivity to the pharmacologic effects of alcohol, low-sensitivity (LS) drinkers show exaggerated neurocognitive and behavioral reactivity to alcohol-related stimuli. The current study extends this line of work by testing whether LS drinkers report stronger cravings for alcohol in daily life. Data were from an ecological momentary assessment study in which participants (N ϭ 403 frequent drinkers) carried a palmtop computer for 21 days and responded to questions regarding drinking behavior, alcohol craving, mood states, and situational context. Initial analyses identified subjective states (positive and negative mood, cigarette craving) and contextual factors (barϪrestaurant location, weekend, time of day, presence of friend, recent smoking) associated with elevated craving states during nondrinking moments. Effects for nearly all these craving correlates were moderated by individual differences in alcohol sensitivity, such that the associations between situational factors and current alcohol craving were larger among LS individuals (as determined by a questionnaire completed at baseline). Complementary idiographic analyses indicated that self-reported craving increased when the constellation of situational factors more closely resembled individuals’ observed drinking situations. Again, this effect was moderated by alcohol sensitivity, with greater craving response increases among LS drinkers. The findings align with predic- tions generated from theory and laboratory cue exposure investigations and should encourage further study of craving and incentive processes in LS drinkers.

Public Health Significance This study extends prior laboratory-based work demonstrating that an individual’s level of alcohol sensitivity is related to the degree of craving reported when exposed to alcohol cues. Here we provide evidence that the craving reactivity previously observed in highly controlled laboratory environments exists and functions similarly in the “real world.”

Keywords: alcohol, alcohol sensitivity, craving, ecological momentary assessment, incentive

Individual drinkers differ markedly with respect to their sensitivity consume more alcohol to achieve desired psychological effects of to the pharmacologic effects of alcohol (Li, 2000). A great deal of drinking (Schuckit, 1994; Trela, Piasecki, Bartholow, Heath, & Sher, evidence has now indicated that a low-sensitivity (LS) or blunted 2016). This heavy drinking style is thought to promote problematic

This document is copyrighted by the American Psychological Association or one of its alliedresponse publishers. to alcohol is an important risk factor for alcohol use disorder alcohol involvement directly and also indirectly by fostering acquisi-

This article is intended solely for the personal use of(AUD; the individual user and is not to be disseminated broadly. Ray, Bujarski, & Roche, 2016; Schuckit, 1980; Schuckit & tion of coping motives for drinking, biasing alcohol-outcome expec- Smith, 1996; Trim, Schuckit, & Smith, 2009). LS drinkers must tancies to be more positive, and promoting affiliations with heavy-

This article was published Online First July 9, 2018. K05AA017242 (Kenneth J. Sher), and T32AA013526 (Kenneth J. Constantine J. Trela, Alexander W. Hayes, Bruce D. Bartholow, and Kenneth Sher). All authors contributed in a significant way to this article, and all J. Sher, Department of Psychological Science, University of Missouri, and Mid- read and approved the final article. Portions of this work were presented west Alcoholism Research Center, St. Louis, Missouri; Andrew C. Heath, Depart- at the 40th Annual Scientific Meeting of the Research Society on ment of Psychiatry, Washington University School of Medicine, and Midwest Alcoholism, Denver, Colorado. Alcoholism Research Center; Thomas M. Piasecki, Department of Psychological Correspondence concerning this article should be addressed to Con- Science, University of Missouri, and Midwest Alcoholism Research Center. stantine J. Trela, Department of Psychological Sciences, University of This research was supported by National Institutes of Health Grants Missouri, 210 McAlester Hall, Columbia, MO 65211. E-mail: P50AA011998 (Andrew C. Heath), K05AA017688 (Andrew C. Heath), [email protected]

354 ALCOHOL SENSITIVITY AND CRAVING 355

drinking peers (Schuckit, Smith, Anderson, & Brown, 2004; Schuckit tributions of direct pharmacologic effects of alcohol and et al., 2008). However, the mechanisms through which LS risk is to craving experience. A focus on nondrinking experiences may better translated into problematic drinking outcomes remain to be fully isolate craving reactivity effects. Additionally, some theoretical mod- elucidated. els posit that conscious cravings are most likely to be experienced Theorists have long considered craving—an appetitive motiva- when drug-related cue complexes are encountered but automatized tional state associated with an acute to approach and use a self-administration behavioral routines are blocked or resisted (Baker, drug—to be an important feature of problematic substance use (e.g., Piper, McCarthy, Majeskie, & Fiore, 2004; Tiffany, 1990; Tiffany & Baker, Morse, & Sherman, 1987; Drummond, 2001; Sayette, 2016). Conklin, 2000). Notably, the existing laboratory evidence document- A recent influential model, incentive theory (IST; Rob- ing greater incentive reactivity among LS drinkers has been obtained inson & Berridge, 1993), identifies amplification of this drug-wanting from participants in a sober state. Second, whereas our prior work was process as a central mechanism in transition from casual drug use into focused on the subjective effects associated with various eBAC levels, . Specifically, IST posits that neural systems that regulate the current analyses specifically test whether LS moderates the asso- drug wanting can become sensitized through repeated use of drugs ciations between (a) various craving- and alcohol-related contexts and such that cues associated with drug use become imbued with exag- (b) craving for alcohol. This focus on potential LS moderation of gerated incentive salience. Through this process, previously neutral craving reports under differing drinking-related stimulus conditions is drug-related stimuli can be transformed into “motivational magnets” more directly aligned with the designs of cue exposure investigations that command , excite drug wanting, and impel drug use and the central tenets of IST. (Berridge & Robinson, 2003). Because direct assessments of exposure to alcohol cues were not Motivated by IST, an emerging line of research has indicated that incorporated into the electronic diary assessments, we used two LS drinkers show stronger incentive motivational responses to indirect strategies to address the central hypothesis. First, we alcohol-related cues relative to their high-sensitivity (HS) peers. The identified contexts and subjective states that prior research and amplitude of the P3 brain event-related potential (ERP) component is theory have indicated might be considered triggers for craving and modulated by the motivational significance (Nieuwenhuis, Aston- that were empirically associated with elevated momentary craving Jones, & Cohen, 2005; Schupp et al., 2000; Weinberg & Hajcak, during nondrinking moments. We then tested whether any of the 2010) or incentive value (Begleiter, Porjesz, Chou, & Aunon, 1983) significant contextϪcraving associations were moderated by indi- of the eliciting stimulus and therefore can be used to investigate the vidual differences in alcohol sensitivity. In a complementary id- motivational salience of target stimuli. Compared to HS drinkers, LS iographic approach, we used within-subject logistic regression individuals show exaggerated P3 ERPs in response to alcohol images analyses to predict the occurrence of drinking from the same set of (Bartholow, Henry, & Lust, 2007). This sensitivity-related difference contextual factors and subjective states. Predicted values from in neural response is specific to alcohol cues and is not observed in these models yielded, for every diary record, an index of the response to other classes of emotionally arousing stimuli (Bartholow, degree to which the constellation of momentary ratings resembled Lust, & Tragesser, 2010). LS risk has also been linked to attentional that individual’s drinking context. We then conducted analyses, biases toward alcohol cues (Bailey & Bartholow, 2016; Shin, Hop- limited to nondrinking moments, testing whether higher predicted finger, Lust, Henry, & Bartholow, 2010) and a behavioral approach values (indexing a greater match between the current situation and bias to alcohol images (Fleming & Bartholow, 2014). Taken together, that participant’s observed drinking situations) were associated these findings suggest that LS drinkers may be more motivationally with elevated craving and whether this effect was moderated by reactive to environmental alcohol-related cues, perhaps resulting in alcohol sensitivity. Based on the existing laboratory cue exposure greater craving reactivity that promotes alcohol use. studies (e.g., Bartholow et al., 2007, 2010; Fleming & Bartholow, Trela et al. (2016) recently investigated how individual differ- 2014), we expected that drinkers with lower self-reported alcohol ences in self-reported alcohol sensitivity were related to subjective sensitivity would show relatively greater reactivity to empirical responses to alcohol during ecologically assessed drinking epi- antecedents of craving and in situations that more closely resem- sodes. Findings indicated that alcohol sensitivity moderated the bled their recorded drinking occasions. association between momentary estimated blood alcohol concen- tration (eBAC) and intoxication responses (e.g., ratings of buzz, Method dizziness). As anticipated, LS drinkers showed blunted intoxica- This document is copyrighted by the American Psychological Association or one of its allied publishers. tion responses compared to their HS peers. Based on prior labo- This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Participants ratory cue exposure studies, Trela et al. (2016) tentatively hypoth- esized that LS would be associated with greater craving intensity Participants were current drinkers (defined as self-report of four or during drinking episodes, which perforce entail exposure to intero- more drinking occasions in the past 30 days) who were recruited ceptive and exteroceptive alcohol cues. Contrary to predictions, through an e-mail listserv maintained by the University of Missouri alcohol sensitivity was not related to craving intensity and did not that included students, faculty, and staff and also via flyers posted in moderate the relation between eBAC level and craving. the community and print commercial circulars to recruit individuals In the current article, we present additional tests of the working who were unaffiliated with the university. Participants were compen- hypothesis that alcohol sensitivity moderates craving reactivity in the sated up to $150 for their full participation in the study, including natural environment. Data come from the same sample used by Trela attendance at study visits and return of the electronic-diary (ED) used et al. (2016), but the current investigation extends the prior work in in the field. The study intentionally oversampled current cigarette two important ways. First, we focus here on data from moments smokers because a major aim of the larger ecological momentary recorded when participants were not actively drinking. Examining assessment project was to examine alcohol and tobacco co-use (Pi- reports collected during active drinking potentially conflates the con- asecki et al., 2011). Because of this goal of the overarching study, the 356 TRELA ET AL.

threshold to be considered a current smoker was low: self-report of report (CR) following each cigarette smoked in the course of the smoking at least one cigarette per week at screening. Of the 418 day. To prevent excessive assessment burden for heavy smokers, participants who completed informed consent, 403 attended a diary the ED administered questionnaires for only the first cigarette training session and actively recorded data in the field using a study- within a 6-hr block of time. Subsequent CRs within that time issued ED and were included in the current analyses. Participants period returned a note that the cigarette had been logged and ranged in age from 18 to 70 years, but the majority were young adults thanked the participant prior to reverting to the home screen of the (M ϭ 23.3 years, SD ϭ 7.2, Mdn ϭ 21; 75% ages 18–22). The ED. The current analyses include data from 6,605 CRs that were sample was balanced with respect to gender (n ϭ 202 female, 50.1%). followed by a full set of diary items. When participants completed At baseline, participants reported consuming an average of 19.4 the first drink of alcohol in a drinking episode, they were asked to drinks per week in the past 30 days (SD ϭ 15.6, Mdn ϭ 15.1). A total log a drink report (DR; n ϭ 2,108). An automated set of prompted of 258 participants (64.0%) were current smokers, of whom 184 drinking follow-ups (DFUs; n ϭ 8,435) oversampled experiences (71.3%) reported smoking on a daily basis. At baseline, smokers in the aftermath of drinking. reported consuming an average of 57.3 cigarettes per week over the The current analyses chiefly focus on data collected during past 30 days (SD ϭ 72.3, Mdn ϭ 45.2). Other data from this study nondrinking moments (RPs, MRs, and CRs; n ϭ 39,774). Morning have been presented in prior reports (Epler et al., 2014; Piasecki et al., reports were assumed to be nondrinking moments. In RP and CR 2011; Piasecki, Alley, et al., 2012; Piasecki, Wood, Shiffman, Sher, & reports, participants were asked whether they had consumed any Heath, 2012; Piasecki et al., 2014; Robertson et al., 2012; Tarantola, alcohol since making their last report. If they answered this ques- Heath, Sher, & Piasecki, 2017; Trela et al., 2016; Treloar, Piasecki, tion affirmatively, the report was reclassified as a drinking moment McCarthy, Sher, & Heath, 2015), but this article is the first to examine and triggered the drink report follow-ups described above. A total alcohol craving reactivity as a function of individual differences in of 3,296 drink initiation (DI) moments occurred in the study (the alcohol sensitivity during nondrinking moments. Data were collected sum of 2,108 DRs and 1,188 reclassified reports). These DI reports between January 2007 and November 2008. All participants provided were used in the idiographic analyses to identify drinkinglike informed consent, and the protocol was approved by the Institutional situations for each individual. DFUs were used in descriptive Review Boards of the University of Missouri and Washington Uni- analyses. versity School of Medicine. Measures Procedure Alcohol sensitivity. The Self-Rating of the Effects of Alcohol Each participant attended two laboratory visits prior to the record- (SRE; Schuckit, Smith, & Tipp, 1997; Schuckit, Tipp, Smith, Wies- ing phase of the study. At the first session, participants completed a beck, & Kalmijn, 1997) form was administered to evaluate individual battery of questionnaires, including the self-report measure of alcohol differences in sensitivity to alcohol. The SRE queries the number of sensitivity. Participants returned for a second training session during drinks that respondents require before they begin to feel different (i.e., which they were instructed on how to initiate and complete reports on experience any effect of alcohol), to feel dizzy or begin slurring the ED. The recording phase of the study lasted 21 days beginning speech, to begin stumbling or walking in an uncoordinated manner, immediately following the end of the training session. During the and to pass out. These effects are assessed for three distinct time recording phase, participants returned to the lab on four occasions to periods: the first five lifetime drinking episodes, the most recent review compliance and troubleshoot any technical issues. period of drinking on a monthly basis for 3 months, and the heaviest lifetime period of drinking. Responses across all effects and time Diary Device and Protocol periods can be averaged to compute an overall SRE score (Ray, Hart, & Chin, 2011; Schuckit, Tipp, et al., 1997). Higher SRE scores The ED was implemented on Palm m500 palmtop computers indicate lower alcohol sensitivity (i.e., a higher number of drinks (Palm Inc., Sunnyvale, CA) using customized software designed required to experience measured alcohol effects). Previous research for the project by invivodata, Inc. (Pittsburgh, PA). During the has established the validity of the SRE, demonstrating that self- recording phase, participants made five types of reports. Morning reported sensitivity is associated with subjective responses to alcohol reports (MRs; n ϭ 7,424) were completed once daily soon after challenge in controlled laboratory studies (Fleming et al., 2016; This document is copyrighted by the American Psychological Association or one of its allied publishers. awakening. The EDs doubled as alarm clocks, with participants’ Schuckit, Smith, & Tipp, 1997; Schuckit, Tipp, et al., 1997). This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. being able to program their device to deliver a wake-up alarm that For the current analyses, we scored the SRE using a standard- also triggered the MRs. Participants were prevented from program- ized person-mean imputation method (Lee, Bartholow, McCarthy, ming the wake-up alarm to occur after 12 noon and were also Pedersen, & Sher, 2015) to produce a less biased estimate of unable to access MRs regardless of the scheduled wake-up time sensitivity by accounting for the relationship between missing data after noon (i.e., participants who slept through the alarm could not (typically occurring when an individual has never experienced a make up the morning report late in the day). Each participant queried alcohol effect) and overall SRE score. There was a sig- received up to five additional audible prompts on a random sched- nificant difference between male (M ϭ 8.84, SD ϭ 3.02) and ule each day to complete a report. These random prompts (RPs; female (M ϭ 6.57, SD ϭ 2.16) raw SRE scores, t(401) ϭ 8.69, p Ͻ n ϭ 26,933) could occur as soon as the morning report was .001. SRE scores were standardized within sex to avoid conflating completed (or noon in cases where an MR was not completed) and sex differences and alcohol sensitivity. The resulting score indexes were able to trigger until participants indicated they were retiring each participant’s alcohol sensitivity relative to same-sex peers, to sleep for the evening. Participants who were current smokers at with each 1-point change corresponding to a standard deviation the initial laboratory session were instructed to log a cigarette increment. ALCOHOL SENSITIVITY AND CRAVING 357

State and contextual predictors of craving. Because the di- or (b) the report was an RP, DR, or MR and the participants ary protocol did not directly assess participants’ exposure to alcohol answered the recent smoking question affirmatively. cues during nondrinking moments, we selected a number of diary- Additional covariates. To more effectively isolate effects derived measures as possible craving triggers on the basis of existing associated with individual differences in alcohol sensitivity, we research and theory. BarϪrestaurant location was selected because covaried several additional person-level variables assessed in these settings are likely to resemble drinking venues, and some of the baseline questionnaire battery. Impulsivity was assessed these have contained alcohol cues or served alcohol. Time of day and using the total score on the Barratt Impulsiveness Scale (Patton, weekend (vs. weekday) were selected because they tend to be strongly Stanford, & Barratt, 1995). Family history of alcohol use dis- related to alcohol consumption (Piasecki, McCarthy, Fiore, & Baker, order was measured by the Short Michigan Alcoholism Screen- 2008; Reich, Cummings, Greenbaum, Moltisanti, & Goldman, 2015; ing Test (SMAST; Crews & Sher, 1992; Selzer, Vinokur, & van Wood, Sher, & Rutledge, 2007). Positive and negative were Rooijen, 1975), using modified paternal (F-SMAST) and ma- selected based on theories suggesting drug cravings are embedded in ternal (M-SMAST) versions. Participants were considered pos- schematic networks organized around prototypic emotions and can be itive for family history if the F-SMAST or M-SMAST score triggered by schema-congruent emotional states (Baker et al., 1987, was 5 or higher (Crews & Sher, 1992). Typical alcohol con- 2004). Presence of a friend has been associated with alcohol use in sumption patterns were represented using consumption items on ecological studies (aan het Rot, Russell, Moskowitz, & Young, 2008; the Alcohol Use Disorder Identification Test (AUDIT-C; Bush, Piasecki et al., 2008), and socializing is a major motive for drinking Kivlahan, McDonell, Fihn, & Bradley, 1998), a set of three (Cooper, 1994). Finally, recent cigarette use and craving for ciga- items from the AUDIT (Babor, Higgins-Biddle, Saunders, & rettes were selected in light of the frequent couse of alcohol and Monteiro, 2001) assessing frequency of drinking, number of tobacco (Piasecki et al., 2011, 2008; Shiffman & Paty, 2006). drinks per drinking occasion, and frequency of consuming six Diary measures of subjective states. The ED assessed a or more drinks per occasion. variety of subjective states using a common stem (“In the PAST 15 MINUTES, did you feel . . .?”) at each report. These items were Statistical Analysis rated on a 5-point Likert scale ranging from 1 (not at all)to5 (extremely). One item with “crave a drink” completing the item Diary data were analyzed using three-level mixed regression stem assessed alcohol craving. This was used as the primary analyses (Level 1 ϭ moment, Level 2 ϭ day in study, Level 3 ϭ outcome variable. Responses to three items (enthusiasm, happy, participant) with random intercepts at day and participant levels. excited) were averaged to create a positive affect variable (␣ϭ Participant records that did not include reports of all relevant .96), and two items (sad, distressed) were averaged to form a independent and dependent variables were excluded in a casewise negative affect composite (␣ϭ.88). Current smokers also com- fashion. pleted a single item assessing cigarette craving over the past 15 One set of analyses used a nomothetic approach to (a) iden- min in every report. tify contextual and subjective features that were associated with Diary measures of contextual features. In all ED assess- elevated drinking craving across participants and (b) determine ments, participants were asked to report their current location by whether these effects were moderated by individual differences checking all applicable options from a list of possible locations in alcohol sensitivity. These analyses were limited to diary data (school, work, barϪrestaurant, primary residence, outside, vehicle, collected from nondrinking moments. First, a multivariate and other). Responses were recoded to create a binary variable indi- mixed regression analysis predicted current alcohol craving cating endorsement (scored 1) or nonendorsement (0) of the bar– from six selected measures Level 1 variables (positive affect, restaurant location. Similarly, a checklist item asking who the partic- negative affect, weekend, time of day, presence of a friend, and ipant had been with in the past 15 min was recoded to form a binary bar– variable indicating the presence or absence of friend. restaurant location), and covariates at Level 2 (whether any All reports were date- and time-stamped automatically by the drinking occurred on that day) and Level 3 (impulsivity, typical ED. We used this information to create a set of 3-hr blocks (e.g., alcohol consumption, family history status). A series of midnight to 3 am) to represent time of day and to code each follow-up models were then estimated. Each included main report as having occurred on a weekday or weekend. We effects for all of the predictors in the initial model but tested a This document is copyrighted by the American Psychological Association or one of its allied publishers. defined weekend liberally as spanning from 5 p.m. on Thursday single Level 1 Predictor ϫ SRE interaction. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. to 3 p.m. on Sunday because prior literature has suggested that Momentary craving for cigarettes and recent smoking were drinking is heightened in this time frame relative to the rest of assessed in only the subsample of current smokers. Conse- the week for college-age individuals (Del Boca, Darkes, Green- quently, we repeated the nomothetic analyses after limiting the baum, & Goldman, 2004; Wood et al., 2007), an age range data to reports from current smokers, adding cigarette craving containing the bulk of the current sample. and recent smoking as additional predictors of alcohol craving. For current smokers, cigarette use in proximity to each diary Another set of analyses used an idiographic approach (cf. entry was determined using a combination of assessments varying Shiffman, Dunbar, & Ferguson, 2015; Shiffman & Paty, 2006). by record type. CRs were, by definition, assumed to occur after The first step used diary data from both nondrinking and drink smoking. In RPs and DRs, participants were asked a yesϪno initiation (DI) moments. For each participant, we conducted a question as to whether they had smoked a cigarette in the past 15 multivariate logistic regression analysis in which the dependent min. MRs included a similar item but used a different time referent measure was whether the record was a DI record (scored 1) or (“since wakeup”). A binary current smoking variable was created, not (0). All subjective and contextual predictors tested in the with smoking coded as having occurred if (a) the report was a CR nomothetic analyses were included in these logistic models. 358 TRELA ET AL.

Table 1 Fixed Effects From Multilevel Regression Analyses Predicting Momentary Alcohol Craving From Diary-Measured Contextual and Subjective Factors

Full sample (n ϭ 403) Current smokers (n ϭ 258) Level and predictor bSEp bSEp

Level 1 Positive affect .151 .006 Ͻ.001 .116 .007 Ͻ.001 Negative affect .197 .006 Ͻ.001 .159 .007 Ͻ.001 Weekend .169 .011 Ͻ.001 .157 .013 Ͻ.001 Time of daya 09:00–12:00 (Ref) (Ref) 12:00–15:00 .101 .012 Ͻ.001 .097 .014 Ͻ.001 15:00–18:00 .249 .012 Ͻ.001 .252 .015 Ͻ.001 18:00–21:00 .380 .012 Ͻ.001 .387 .015 Ͻ.001 21:00–00:00 .351 .014 Ͻ.001 .366 .017 Ͻ.001 00:00–03:00 .265 .031 Ͻ.001 .248 .033 Ͻ.001 03:00–06:00 Ϫ.016 .047 .732 Ϫ.048 .053 .373 06:00–09:00 Ϫ.041 .015 .006 Ϫ.042 .018 .020 Friend .083 .009 Ͻ.001 .096 .012 Ͻ.001 BarϪrestaurant .144 .012 Ͻ.001 .138 .029 Ͻ.001 Recent smoking Ϫ.048 .010 Ͻ.001 Crave cigarette .167 .005 Ͻ.001 Level 2 Drinking day .173 .014 Ͻ.001 .114 .017 Ͻ.001 Level 3 AUDIT-C .047 .012 Ͻ.001 .056 .014 Ͻ.001 Impulsivity .003 .002 .142 .003 .003 .314 Family history Ϫ.055 .068 .417 Ϫ.057 .076 .450 Note. (Ref) ϭ referent; AUDIT-C ϭ Consumption items on the Alcohol Use Disorder Identification Test. a Omnibus test for time: full analytic sample, F(7, 35,609.06) ϭ 230.47, p Ͻ .001; current smokers, F(7, 25,084.58 ϭ 165.18, p Ͻ .001.

Predicted values from the logistic models were saved. These monitoring period were not significantly correlated with SRE values indicate the model-predicted probability that a given (rs Յ |.06|, ps Ն .22). moment is a drinking occasion based on the configuration of immediate subjective and contextual features. Note that the use Nomothetic Approach of single-subject logistic regression analyses means that the importance of particular predictors of drinking can vary across Results from the initial multivariate models predicting alcohol individuals. In the next step, we limited data to nondrinking craving from subjective and contextual factors are presented in Table moments and conducted a pooled multilevel regression analysis 1. In the full analytic sample, all Level 1 predictors were simultane- in which ratings of alcohol craving were predicted from se- ously associated with current reports of craving for alcohol. Specifi- lected covariates (drinking day, AUDIT-C, impulsivity, and cally, craving was higher when positive and negative affect were family history), the idiographic model-predicted values (i.e., elevated, on the weekends relative to weekdays, in the presence of a resemblance of the current moment to the participants’ ob- friend, and when in a barϪrestaurant location. Craving also varied served drinking occasions), SRE scores, and the interaction significantly over time of day. Among current smokers, the same between SRE and drinking occasion resemblance. Again, this pattern of results was observed. Additionally, craving for alcohol was positively related to current levels of cigarette craving and lower when This document is copyrighted by the American Psychological Association or one of its alliedidiographic publishers. approach was repeated in the subsample of current recent smoking was reported.1 Craving for alcohol was also stronger This article is intended solely for the personal use ofsmokers, the individual user and is not to be disseminated broadly. including cigarette craving and recent smoking as additional predictors. on days when drinking ultimately occurred. Of the Level 3 covariates, only AUDIT-C was significant, indicating heavier drinkers tended to Results report higher levels of craving. Table 2 summarizes tests of interactions between alcohol sen- Descriptive Analyses sitivity and particular subjective and contextual features. In the full sample, alcohol sensitivity significantly moderated the effects of Standardized SRE scores were strongly correlated with AUDIT-C all state and contextual predictors of craving. In current smokers, (r ϭ .52, p Ͻ .001), indicating that lower sensitivity individuals were heavier drinkers at study baseline. SRE was negatively cor- 1 related with participant age (r ϭϪ.18, p Ͻ .001), indicating that Reports of cigarette craving were significantly higher when recent smoking was reported (b ϭ .482, p Ͻ .001). If momentary cigarette craving older participants tended to be more sensitive to the effects of is omitted from the predictor set in the multivariate nomothetic model, alcohol. Family history of AUD, impulsivity, smoking status, sex, recent smoking is positively associated with alcohol craving (b ϭ .023, p ϭ and proportion of drinking and smoking days during the diary .03). ALCOHOL SENSITIVITY AND CRAVING 359

Table 2 Idiographic Approach StateϪContextual Feature ϫ Alcohol Sensitivity Interaction Fixed Effects From Multilevel Regression Analyses Predicting Inspection of the distribution of predicted probabilities (i.e., Alcohol Craving drinking occasion resemblance) in nondrinking diary records gen- erated from the single-subject logistic regression analyses indi- Sample and State – cated that these values were low overall (M ϭ .037, SD ϭ .101; ϫ Context SRE bSEp98.6% of estimates Ͻ .50) with a modal value of zero (67.6% of Full sample (n ϭ 403) nondrinking moments in the full sample). This was partly attrib- Positive affect .020 .006 .002 utable to the strong association between time of day and drinking Ͻ Negative affect .029 .008 .001 (Piasecki et al., 2011). Panel A of Figure 2 shows the frequency Weekend .047 .014 .001 Time of daya distributions for nondrinking and drinking diary records by time of 09:00–12:00 (Ref) day in the full sample, illustrating the virtual absence of drinking 12:00–15:00 Ϫ.013 .015 .379 records between 3 a.m. and 3 p.m. (the unshaded area). As would 15:00–18:00 .001 .015 .930 18:00–21:00 .036 .015 .019 be expected, the mean model-predicted probabilities hover close to 21:00–00:00 .030 .017 .085 zero in this time window but track higher between 3 p.m. and 3 00:00–03:00 .010 .042 .812 a.m., when both nondrinking and drinking records were observed 03:00–06:00 .061 .081 .450 (shaded area, Panel B). Panel C shows that mean levels of alcohol 06:00–09:00 .002 .020 .923 Friend .039 .012 .001 craving in nondrinking moments were also elevated, primarily at BarϪrestaurant .069 .029 .018 times of day when drinking records were common. In light of these Current smokers (n ϭ 258) patterns, the primary idiographic analyses predicting craving were Recent smoking Ϫ.022 .014 .111 Crave cigarette .014 .006 .017 limited to 20,607 nondrinking diary records logged between 3 p.m. and 3 a.m., a period that is most clinically and practically relevant ϫ Note. Each model included a single State - Context SRE interaction (i.e., drinking is plausible, and craving is more pronounced). term and included main effects for all predictors in Table 1. SRE ϭ Self-Rating of the Effects of Alcohol; (Ref) ϭ referent. Exploratory analyses indicated that temporal patterns of craving a Omnibus test for SRE ϫ Time, F(7, 35,516.22) ϭ 2.12, p ϭ .038. level and drinking resemblance were consistent across weekdays and weekends (profile rs Ն .79). In both the full sample and subsample of current smokers, drinking occasion resemblance was robustly related to contempo- alcohol sensitivity moderated the association between current cig- raneous reports of alcohol craving (see Table 4). As the resem- arette craving and alcohol craving but did not interact with recent blance between the profile of immediate contextual and subjective smoking. Figure 1 illustrates the significant interactions by plotting conditions and those observed in drinking events increased, drink- marginal model-estimated means for alcohol craving for low- and ers reported experiencing higher levels of desire to drink. These high-sensitivity drinkers under varying contextual and subjective conditions. As predicted, the associations between state and con- effects were moderated by individual differences in alcohol sen- textual predictors and current alcohol craving were stronger among sitivity, with lower sensitivity drinkers showing a stronger rela- drinkers with lower alcohol sensitivity. The effects of situational tionship between craving- and drinking-resembling situations. Fig- factors and the moderating effects of alcohol sensitivity tended to ure 3 illustrates these effects. When the analyses were expanded to be modest in magnitude. Elevated craving (i.e., a score greater than include data from all nondrinking moments, similar findings were 1, the value associated with the not at all anchor point) was present obtained (see Table 4). in approximately 25% of all records, and mean levels of current We again conducted supplementary analyses examining craving for alcohol tended to be low overall (approximately 1.5– whether these two-way interactions were further moderated by 2.0 on a 1–5 scale).2 day-level drinking occurrence. Using the records from the pri- As noted above, craving was elevated on days when drinking mary 3 p.m. to 3 a.m. time period, we found the three-way Alcohol ultimately occurred (see Table 1). We conducted supplementary anal- Sensitivity ϫ Drinking Resemblance ϫ Drinking Day interactions This document is copyrighted by the American Psychological Association or one of its alliedyses publishers. incorporating three-way Alcohol Sensitivity ϫ StateϪContext ϫ was not significant in the full sample (b ϭ .052, p ϭ .677). The This article is intended solely for the personal use ofDrinking the individual user and is not to be disseminated broadly. Day interaction terms to explore whether the effects in Table corresponding three-way interaction was significant in the smoker 2 were further moderated by day-level alcohol use outcomes. Find- subsample (b ϭ .492, p ϭ .012). Analyses of the smokers stratified ings revealed significant three-way interactions involving numerous by day-level drinking outcome indicated that alcohol sensitivity states and contexts: positive affect interaction (b ϭ .025, p Ͻ .001); moderated the effect of drinking resemblance on craving on days negative affect interaction (b ϭ .037, p Ͻ .001); friend interaction when drinking occurred (b ϭ .298, p ϭ .001) but not on nondrink- (b ϭ .080, p Ͻ .001); smoked interaction (b ϭ .071, p ϭ .019); crave ing days (b ϭ .030, p ϭ .869). Results were similar when records cigarette interaction (b ϭ .032, p Ͻ .001); time of day omnibus from all nondrinking moments were analyzed. interaction, F(8, 28,635.36) ϭ 3.890, p Ͻ .001. To characterize these effects, we conducted separate analyses stratified by day- level drinking outcome. Findings indicated that the two-way in- 2 teractions between alcohol sensitivity and various craving-related A similar pattern of interaction effects was obtained when gamma regression analyses were performed using generalized linear mixed models states and contexts were observed primarily on days when drinking for skewed outcomes (e.g., Neal & Simons, 2007). The only difference was ultimately occurred (see Table 3). that the SRE ϫ Cigarette Craving interaction was not significant (p ϭ .09). 360 TRELA ET AL.

Figure 1. Model-predicted means and associated 95% confidence intervals illustrating significant interaction effects involving stateϪcontextual features and alcohol sensitivity in nomothetic models. Lines are plotted at the mean of the top (LS) and bottom (HS) quartiles of the distribution of standardized person-mean imputed SRE scores (pooled across sexes) to illustrate sensitivity-related effects and at the mean level of all other covariates. LS ϭ low sensitivity; HS ϭ high sensitivity; Rest. ϭ restaurant; SRE ϭ Self-Rating of the Effects of Alcohol.

Discussion that LS status moderated the P3 amplitude to alcohol cue exposure when controlling for other AUD risk factors such as impulsivity Findings from this study complement evidence from prior lab- and familial alcoholism. In a cue exposure study involving young oratory cue exposure investigations indicating that LS drinkers adult smokers, individual differences in the severity of tobacco show enhanced neurophysiological and behavioral reactivity to dependence did not moderate P3 responses to smoking images alcohol-related cues (Bartholow et al., 2007, 2010; Fleming & (Piasecki, Fleming, Trela, & Bartholow, 2017). However, in this Bartholow, 2014; Shin et al., 2010) and extend those findings by same study, smokers who reported lower alcohol sensitivity demonstrating that LS drinkers show greater alcohol craving re- showed larger neural responses to smoking images compared to activity to drinking- and craving-related settings in the natural their higher sensitivity peers. Taken together, such findings sug- environment. This line of inquiry has drawn from incentive sen- gest exaggerated incentive salience is not an essential or inevitable sitization theory, which posits that drugs of abuse like alcohol can sensitize neural circuitry responsible for imbuing reward- concomitant of addiction or addiction risk and indicate that a low predicting cues with motivational salience (Robinson & Berridge, subjective response to alcohol may be a trait marker that identifies 1993, 2003, 2008). With repeated use, previously neutral cues “cue reactors.” It is interesting that mesolimbic dopaminergic This document is copyrighted by the American Psychological Association or one of its allied publishers. associated with drug self-administration become attractive targets systems have been implicated in both incentive (Saunders This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. that may elicit behavioral approach accompanied by the subjective & Robinson, 2012) and subjective response to alcohol (Setiawan et experience of wanting or craving (Berridge & Robinson, 2003). al., 2014). The possibility that LS risk and pathological drug From this theoretical perspective, the current findings suggest that wanting have overlapping neural underpinnings merits focused the development of a pathologically amplified, alcohol-focused investigation in future research. wanting process may be an important mechanism through which A prior analysis of data collected during active drinking epi- LS confers risk for problematic drinking outcomes. sodes from the same sample focused on prediction of craving and Preclinical studies have revealed that there are substantial indi- other subjective states as a function of momentary eBAC level vidual differences in the susceptibility to sensitization of incentive (Trela et al., 2016). Findings indicated that momentary eBAC was for reward-paired cues (Flagel, Akil, & Robinson, not related to craving intensity. Furthermore, individual differ- 2009). These findings suggest that there may be multiple pathways ences in alcohol sensitivity did not moderate the association be- to addiction, with perhaps only a subset of cases attributable to tween craving and eBAC (Trela et al., 2016). The current analyses sensitized drug wanting and exaggerated cue reactivity (Robinson, focused more squarely on how craving responses were related to Yager, Cogan, & Saunders, 2014). Bartholow et al. (2010) found environmental and subjective setting conditions associated with ALCOHOL SENSITIVITY AND CRAVING 361

Table 3 StateϪContext ϫ Alcohol Sensitivity Interactions From Analyses Predicting Alcohol Craving, Stratified by Day-Level Drinking Outcomes

Drinking days Nondrinking days Sample and SRE ϫ StateϪContext bSEp bSEp

Full sample (n ϭ 403) Positive affect .031 .009 Ͻ.001 .005 .009 .563 Negative affect .037 .011 Ͻ.001 .020 .011 .066 Weekend .037 .019 .053 .038 .021 .067 Time of daya 09:00–12:00 (Ref) (Ref) 12:00–15:00 Ϫ.008 .021 .685 Ϫ.014 .021 .520 15:00–18:00 .019 .022 .383 Ϫ.020 .021 .331 18:00–21:00 .068 .021 .001 Ϫ.003 .021 .905 21:00–00:00 .023 .026 .380 .035 .022 .107 00:00–03:00 Ϫ.022 .050 .656 .154 .082 .058 03:00–06:00 .011 .107 .917 .01 .125 .939 06:00–09:00 .001 .027 .985 Ϫ.017 .028 .552 Friend .074 .017 Ͻ.001 .001 .015 .933 BarϪrestaurant .078 .038 .040 .05 .045 .264 Current smokers (n ϭ 258) Recent smoking Ϫ.016 .015 .283 Ϫ.079 .029 .006 Crave cigarette .01 .007 .119 .003 .01 .757 Note. Each model included a single State - Context ϫ SRE interaction term and included main effects for all Predictors in Table 1. SRE ϭ Self-Rating of the Effects of Alcohol; (Ref) ϭ referent. a Omnibus test for SRE ϫ Time on drinking days, F(7, 21,100.47) ϭ 2.57, p ϭ .012. Omnibus test for SRE ϫ Time on nondrinking days, F(7, 14,368.72 ϭ 1.67, p ϭ .112.

craving and drinking. This focus on situational factors that may itively state that increases in craving were caused by exposure to serve as learned triggers for craving (vs. alcohol dose) more clearly the putative situational triggers. It is theoretically possible that the aligns with the tenets of IST upon that motivated prior cue expo- increases in craving observed in the study were caused by a sure studies examining moderating effects of LS risk (e.g., Bar- variable(s) that we did not measure via the ED or at the partici- tholow et al., 2007, 2010). This may account for the greater pants’ baseline laboratory visit. In addition, average levels of correspondence of the current findings with predictions extrapo- self-reported craving for alcohol were low during nondrinking lated from the laboratory investigations (e.g., Fleming & Bar- moments. Furthermore, the effects of drinking- and craving-related tholow, 2014; Trela et al., 2016). It is also possible that the craving settings and their moderation by LS on craving tended to be reactivity and effects of trait moderators of such reactivity are modest in magnitude. These observations appear incongruent with more evident when alcohol has not been consumed (e.g., Baker et the theoretical expectation that drug-related cues become powerful al., 2004; Tiffany, 1990). However, analyses focused on reactivity “motivational magnets” that are pathologically wanted and poten- to discrete situational features during active alcohol use might tially question the clinical relevance of the findings. On the other show effects similar to those found here. hand, incentive sensitization theory recognizes that under differing The strength of the moderating effect that alcohol sensitivity had conditions, mesolimbic drug-wanting responses may be evident at on the relationship between the state and contextual predictors of various levels of awareness, ranging from subtle unconscious craving depended in part on whether drinking ultimately occurred biasing of attention and motivation to more intense desire with on a given day. The meaning of these effects is uncertain on explicit awareness of craving experience (Berridge & Robinson, present evidence. One possibility is that cravings triggered by 2016). From this perspective, even low levels of self-reported This document is copyrighted by the American Psychological Association or one of its allied publishers. environmental contexts or internal states sometimes impel individ- craving may be theoretically interesting, tapping a comparatively This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. uals to initiate drinking, and this process may be more prominent high threshold on the continuum of possible incentive salience in LS drinkers. If so, limiting analyses to days on which drinking “wanting” outcomes. However, such distinctions also suggest that occurred would tend to reveal an excess of stateϪ/context craving self-reported craving ratings may represent rather blunt instru- reactivity in LS drinkers compared to their higher sensitivity peers, ments for investigating incentive salience effects in ecological for whom other factors may be more influential in drink initiation. studies. In future work, it would be valuable to incorporate addi- A second possibility is that planned drinking later in the day (e.g., tional ambulatory measures that may be more sensitive to subtler happy hour following work) might elicit anticipatory craving that effects, such as mobile visual dot-probe or Stroop tasks (Kerst & operates differentially based on one’s alcohol sensitivity. Unfor- Waters, 2014; Marhe, Waters, van de Wetering, & Franken, 2013). tunately, the present data do not allow us to fully evaluate these A second important caveat is that the diary protocol did not alternative explanations. incorporate direct assessments of exposure to alcohol cues per se. Although these “real world” observations generally accord with We used both a theory-based nomothetic approach and an empir- our prior laboratory findings, several caveats must be noted. Chief ically derived idiographic method to identify states and settings among these is that due to observational design, we cannot defin- that were associated with craving and alcohol use occasions. 362 TRELA ET AL.

their having acted as conditioned alcohol cues. A lower subjective response to alcohol is hypothesized to foster acquisition of coping motives for drinking (Schuckit et al., 2004), which might explain why negative affect is accompanied by an elevated desire to drink in LS individuals. Similarly, the presence of a friend could be associated with higher craving through mechanisms that have little to do with associative learning. LS individuals are expected to selectively affiliate with heavy-drinking peers (Schuckit et al., 2004). If so, their friends may be more likely to directly invite or pressure them to drink compared to the company kept by higher sensitivity drinkers. Future ecological studies are needed to more strictly probe incentive sensitization mechanisms in LS drinkers. It will be important to determine whether similar findings are ob- served when participants explicitly report noticing alcohol cues (e.g., Begh et al., 2016) or when cue presentations are manipulated directly via the mobile device (e.g., Wray, Godleski, & Tiffany, 2011). The current study did not formally investigate whether individ- ual differences in craving reactivity were associated with problem- atic drinking outcomes. Prior reports from this sample indicated that individual differences in alcohol sensitivity were not associ- ated with drinking frequency (Piasecki, Alley, et al., 2012). How- ever, relative to their high-sensitivity peers, LS drinkers had steeper rising slopes of estimated blood alcohol concentration when drinking (Trela et al., 2016) and were more likely to report hangovers the morning after drinking (Piasecki, Alley, et al., 2012). Indirectly, such findings suggest craving reactivity in non- drinking moments might be more related to the speed, quantity, or consequences of consumption than to the likelihood of alcohol use initiation. This remains to be tested formally in future studies. Although these downstream consequences require additional in- vestigation, documenting a relation between LS risk and real- world craving responses is itself significant given the inclusion of Figure 2. Panel A: Frequency distributions of nondrinking and drinking craving as an AUD diagnostic criterion in the fifth edition of the (both drink initiation records and drinking follow-ups) diary records as a Diagnostic and Statistical Manual of Mental Disorders (Hasin et function of time of day. Panel B: Mean predicted values (i.e., drinking al., 2013). occasion resemblance) from participant-stratified logistic regression anal- The models included a number of covariates at the day and yses in the full sample by time of day. Panel C: Mean ratings of alcohol person levels in an attempt to isolate effects uniquely associated craving in the full sample by time of day. The shaded area (3 p.m. to 3 a.m.) with alcohol sensitivity. It is possible that these covariate controls was selected as the focus of primary idiographic analyses. were overly stringent (Meehl, 1971). For example, a pattern of heavy alcohol consumption, such as captured by the AUDIT-C, might be considered to represent a fundamental expression of LS Findings from both approaches provide evidence linking LS risk risk, potentially playing an important causal role in translating a with a general craving reactivity in the natural environment, but latent vulnerability into an active craving reactivity phenotype. If they cannot directly establish that these effects arise as a result of so, the current findings might understate the true relation between This document is copyrighted by the American Psychological Association or one of its allied publishers. incentive sensitization or associative learning. Of the contexts alcohol sensitivity and craving response in daily life. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. examined here, the barϪrestaurant location is likely the best indi- A final caveat is that the participants in the current study were rect proxy for exposure to discrete environmental alcohol-related not administered the neurocognitive and behavioral tasks used to cues. However, our brief assessment of physical locations did not identify incentive salience effects in our prior laboratory studies allow us to determine which of these situations actually contained (Bartholow et al., 2007, 2010; Fleming & Bartholow, 2014; Shin such cues. It is possible that alcohol cues were absent in a large et al., 2010). Thus, it remains to be empirically established that subset of occasions for which barϪrestaurant was endorsed (e.g., responses on such tasks are associated with self-reported cravings fast food outlets). The theoretical relevance of other of the corre- for alcohol in the natural environment. Comprehensive, multim- lates of craving to IST can be questioned. For example, positive ethod studies are needed to confirm that various putative indicators and negative affect were tested on the assumption that they pro- of incentive salience that have been associated with LS risk indeed duce interoceptive cues that may become associated with drinking tap a common psychological process. through associative learning (Baker et al., 1987, 2004). The inten- In summary, drinkers who report a lower level of sensitivity to sities of these affective states were empirically associated with alcohol report larger changes in craving when encountering elevated craving, but it is possible that this is not attributable to craving- and drinking-related states and contexts. The findings ALCOHOL SENSITIVITY AND CRAVING 363

Table 4 Fixed Effects From Idiographic Models Predicting Alcohol Craving

Full sample (n ϭ 403) Current smokers (n ϭ 258) Model and predictor bSEpbSEp

Limited to 3 p.m. to 3 a.m. Intercept .512 .229 .026 .431 .303 .156 Drinking day .307 .021 Ͻ.001 .242 .027 Ͻ.001 AUDIT-C .073 .018 Ͻ.001 .086 .023 Ͻ.001 Impulsivity .007 .003 .031 .007 .004 .078 Family history Ϫ.097 .089 .280 Ϫ.065 .111 .556 SRE Ϫ.070 .051 .173 Ϫ.099 .068 .147 Drink occasion resemblance 1.106 .049 Ͻ.001 1.116 .062 Ͻ.001 SRE ϫ Predicted Value .298 .064 Ͻ.001 .272 .082 .001 All records Intercept .611 .192 .002 .519 .245 .035 Drinking day .172 .014 Ͻ.001 .139 .018 Ͻ.001 AUDIT-C .055 .015 Ͻ.001 .067 .019 Ͻ.001 Impulsivity .005 .003 .030 .006 .003 .063 Family history Ϫ.065 .075 .388 Ϫ.044 .090 .627 SRE Ϫ.035 .043 .410 Ϫ.068 .055 .215 Drink occasion resemblance 1.765 .040 Ͻ.001 1.842 .051 Ͻ.001 SRE ϫ Drink Occasion Resemblance .192 .052 Ͻ.001 .164 .068 .015 Note. AUDIT-C ϭ Consumption items of the Alcohol Use Disorder Identification Test; SRE ϭ Self-Rating of the Effects of Alcohol.

align with predictions generated from theory and laboratory cue studies of incentive salience wanting and low subjective response exposure investigations and should encourage further study of to alcohol. craving processes in LS drinkers. Theoretical inferences are con- strained by several important caveats arising from limitations in the assessment protocol. Future investigations with specialized References assessments are needed to more sensitively probe whether the aan het Rot, M., Russell, J. J., Moskowitz, D. S., & Young, S. N. (2008). kinds of craving effects seen here are largely attributable to height- Alcohol in a social context: Findings from event-contingent recording ened reactivity to alcohol-related cues in the manner anticipated by studies of everyday social interactions. Alcoholism: Clinical and Exper- IST. It is important to note that the current study had the potential imental Research, 32, 459–471. http://dx.doi.org/10.1111/j.1530-0277 to produce evidence disconfirming the basic assertion that LS .2007.00590.x drinkers show greater craving reactivity, which could have cast Babor, T. R., Higgins-Biddle, J. C., Saunders, J. B., & Monteiro, M. G. doubt on the tenability of our hypothesis. This initial evidence (2001). The Alcohol Use Disorders Identification Test: Guidelines for provides a foundation for more rigorous and probative follow-on use in primary care (2e). Geneva, Switzerland: World Health Organi- zation. Bailey, K., & Bartholow, B. D. (2016). Alcohol words elicit reactive cognitive control in low-sensitivity drinkers. Psychophysiology, 53, 1751–1759. http://dx.doi.org/10.1111/psyp.12741 Baker, T. B., Morse, E., & Sherman, J. E. (1987). The motivation to use drugs: A psychobiological analysis of urges. In C. Rivers (Ed.), The Nebraska Symposium on motivation: Vol. 34. Alcohol use and abuse (pp. 257–323). Lincoln, Nebraska: University of Nebraska Press. This document is copyrighted by the American Psychological Association or one of its allied publishers. Baker, T. B., Piper, M. E., McCarthy, D. E., Majeskie, M. R., & Fiore, This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. M. C. (2004). Addiction motivation reformulated: An affective process- ing model of negative . Psychological Review, 111, 33–51. http://dx.doi.org/10.1037/0033-295X.111.1.33 Bartholow, B. D., Henry, E. A., & Lust, S. A. (2007). Effects of alcohol sensitivity on P3 event-related potential reactivity to alcohol cues. Psy- Figure 3. Model-predicted mean ratings of momentary alcohol craving chology of Addictive Behaviors, 21, 555–563. http://dx.doi.org/10.1037/ and associated 95% confidence intervals illustrating Alcohol Sensitivity ϫ 0893-164X.21.4.555 Contextual Resemblance to Drinking Situations interactions from idio- Bartholow, B. D., Lust, S. A., & Tragesser, S. L. (2010). Specificity of P3 graphic models, using records occurring between 3 p.m. and 3 a.m. Lines event-related potential reactivity to alcohol cues in individuals low in are plotted at the mean of the top (LS) and bottom (HS) quartiles of the alcohol sensitivity. Psychology of Addictive Behaviors, 24, 220–228. distribution of standardized person-mean imputed SRE scores (pooled http://dx.doi.org/10.1037/a0017705 across sexes) to illustrate sensitivity-related effects and at the mean level of Begh, R., Smith, M., Ferguson, S. G., Shiffman, S., Munafò, M. R., & all other covariates. LS ϭ low sensitivity; HS ϭ high sensitivity; SRE ϭ Aveyard, P. (2016). Association between smoking-related attentional Self-Rating of the Effects of Alcohol. bias and craving measured in the clinic and in the natural environment. 364 TRELA ET AL.

Psychology of Addictive Behaviors, 30, 868–875. http://dx.doi.org/10 tary assessment study. Journal of Consulting and Clinical Psychology, .1037/adb0000231 81, 1–12. http://dx.doi.org/10.1037/a0030754 Begleiter, H., Porjesz, B., Chou, C. L., & Aunon, J. I. (1983). P3 and Meehl, P. E. (1971). High school yearbooks: A reply to Schwarz. Journal stimulus incentive value. Psychophysiology, 20, 95–101. http://dx.doi of Abnormal Psychology, 77, 143–148. http://dx.doi.org/10.1037/ .org/10.1111/j.1469-8986.1983.tb00909.x h0030750 Berridge, K. C., & Robinson, T. E. (2003). Parsing reward. Trends in Neal, D. J., & Simons, J. S. (2007). Inference in regression models of Neurosciences, 26, 507–513. http://dx.doi.org/10.1016/S0166-2236 heavily skewed alcohol use data: A comparison of ordinary least (03)00233-9 squares, generalized linear models, and bootstrap resampling. Psychol- Berridge, K. C., & Robinson, T. E. (2016). Liking, wanting, and the ogy of Addictive Behaviors, 21, 441–452. http://dx.doi.org/10.1037/ incentive-sensitization theory of addiction. American Psychologist, 71, 0893-164X.21.4.441 670–679. http://dx.doi.org/10.1037/amp0000059 Nieuwenhuis, S., Aston-Jones, G., & Cohen, J. D. (2005). Decision mak- Bush, K., Kivlahan, D. R., McDonell, M. B., Fihn, S. D., & Bradley, K. A. ing, the P3, and the locus coeruleus-norepinephrine system. Psycholog- (1998). The AUDIT alcohol consumption questions (AUDIT-C): An effec- ical Bulletin, 131, 510–532. http://dx.doi.org/10.1037/0033-2909.131.4 tive brief screening test for problem drinking. Archives of Internal Medicine, .510 158, 1789–1795. http://dx.doi.org/10.1001/archinte.158.16.1789 Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of Cooper, M. L. (1994). for alcohol use among adolescents: the Barratt Impulsiveness Scale. Journal of Clinical Psychology, 51, Development and validation of a four-factor model. Psychological As- 768–774. http://dx.doi.org/10.1002/1097-4679(199511)51:6Ͻ768:: sessment, 6, 117–128. http://dx.doi.org/10.1037/1040-3590.6.2.117 AID-JCLP2270510607Ͼ3.0.CO;2-1 Crews, T. M., & Sher, K. J. (1992). Using adapted short MASTs for Piasecki, T. M., Alley, K. J., Slutske, W. S., Wood, P. K., Sher, K. J., assessing parental alcoholism: Reliability and validity. Alcoholism: Clinical and Experimental Research, 16, 576–584. http://dx.doi.org/10 Shiffman, S., & Heath, A. C. (2012). Low sensitivity to alcohol: Rela- .1111/j.1530-0277.1992.tb01420.x tions with hangover occurrence and susceptibility in an ecological mo- Del Boca, F. K., Darkes, J., Greenbaum, P. E., & Goldman, M. S. (2004). mentary assessment investigation. Journal of Studies on Alcohol and Up close and personal: Temporal variability in the drinking of individual Drugs, 73, 925–932. http://dx.doi.org/10.15288/jsad.2012.73.925 college students during their first year. Journal of Consulting and Piasecki, T. M., Cooper, M. L., Wood, P. K., Sher, K. J., Shiffman, S., & Clinical Psychology, 72, 155–164. http://dx.doi.org/10.1037/0022-006X Heath, A. C. (2014). Dispositional drinking motives: Associations with .72.2.155 appraised alcohol effects and alcohol consumption in an ecological Drummond, D. C. (2001). Theories of drug craving, ancient and modern. momentary assessment investigation. Psychological Assessment, 26, Addiction, 96, 33–46. http://dx.doi.org/10.1046/j.1360-0443.2001.961333.x 363–369. http://dx.doi.org/10.1037/a0035153 Epler, A. J., Tomko, R. L., Piasecki, T. M., Wood, P. K., Sher, K. J., Piasecki, T. M., Fleming, K. A., Trela, C. J., & Bartholow, B. D. (2017). Shiffman, S., & Heath, A. C. (2014). Does hangover influence the time P3 event-related potential reactivity to smoking cues: Relations with to next drink? An investigation using ecological momentary assessment. craving, tobacco dependence, and alcohol sensitivity in young adult Alcoholism: Clinical and Experimental Research, 38, 1461–1469. http:// smokers. Psychology of Addictive Behaviors, 31, 61–72. http://dx.doi dx.doi.org/10.1111/acer.12386 .org/10.1037/adb0000233 Flagel, S. B., Akil, H., & Robinson, T. E. (2009). Individual differences in Piasecki, T. M., Jahng, S., Wood, P. K., Robertson, B. M., Epler, A. J., the attribution of incentive salience to reward-related cues: Implications Cronk, N. J.,...Sher, K. J. (2011). The subjective effects of alcohol- for addiction. Neuropharmacology, 56(Suppl. 1), 139–148. http://dx.doi tobacco co-use: An ecological momentary assessment investigation. .org/10.1016/j.neuropharm.2008.06.027 Journal of Abnormal Psychology, 120, 557–571. http://dx.doi.org/10 Fleming, K. A., & Bartholow, B. D. (2014). Alcohol cues, approach bias, .1037/a0023033 and : Applying a dual process model of addiction to Piasecki, T. M., McCarthy, D. E., Fiore, M. C., & Baker, T. B. (2008). alcohol sensitivity. Psychology of Addictive Behaviors, 28, 85–96. http:// Alcohol consumption, smoking urge, and the reinforcing effects of dx.doi.org/10.1037/a0031565 cigarettes: An ecological study. Psychology of Addictive Behaviors, 22, Fleming, K. A., Bartholow, B. D., Hilgard, J., McCarthy, D. M., O’Neill, S. E., 230–239. http://dx.doi.org/10.1037/0893-164X.22.2.230 Steinley, D., & Sher, K. J. (2016). The Alcohol Sensitivity Questionnaire: Piasecki, T. M., Wood, P. K., Shiffman, S., Sher, K. J., & Heath, A. C. Evidence for construct validity. Alcoholism: Clinical and Experimental (2012). Responses to alcohol and cigarette use during ecologically Research, 40, 880–888. http://dx.doi.org/10.1111/acer.13015 assessed drinking episodes. Psychopharmacology, 223, 331–344. http:// Hasin, D. S., O’Brien, C. P., Auriacombe, M., Borges, G., Bucholz, K., dx.doi.org/10.1007/s00213-012-2721-1 Budney, A.,...Grant, B. F. (2013). DSM–5 criteria for substance use Ray, L. A., Bujarski, S., & Roche, D. J. (2016). Subjective response to disorders: Recommendations and rationale. American Journal of Psychia- This document is copyrighted by the American Psychological Association or one of its allied publishers. alcohol as a research domain criterion. Alcoholism: Clinical and Exper- try, 170, 834–851. http://dx.doi.org/10.1176/appi.ajp.2013.12060782 This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. imental Research, 40, 6–17. http://dx.doi.org/10.1111/acer.12927 Kerst, W. F., & Waters, A. J. (2014). Attentional retraining administered in Ray, L. A., Hart, E. J., & Chin, P. F. (2011). Self-Rating of the Effects of the field reduces smokers’ attentional bias and craving. Health Psychol- ogy, 33, 1232–1240. http://dx.doi.org/10.1037/a0035708 Alcohol (SRE): Predictive utility and reliability across interview and Lee, M. R., Bartholow, B. D., McCarthy, D. M., Pedersen, S. L., & Sher, self-report administrations. Addictive Behaviors, 36, 241–243. http://dx K. J. (2015). Two alternative approaches to conventional person-mean .doi.org/10.1016/j.addbeh.2010.10.009 imputation scoring of the Self-Rating of the Effects of Alcohol Scale Reich, R. R., Cummings, J. R., Greenbaum, P. E., Moltisanti, A. J., & (SRE). Psychology of Addictive Behaviors, 29, 231–236. http://dx.doi Goldman, M. S. (2015). The temporal “pulse” of drinking: Tracking 5 .org/10.1037/adb0000015 years of binge drinking in emerging adults. Journal of Abnormal Psy- Li, T. K. (2000). Pharmacogenetics of responses to alcohol and genes that chology, 124, 635–647. http://dx.doi.org/10.1037/abn0000061 influence alcohol drinking. Journal of Studies on Alcohol, 61, 5–12. Robertson, B. M., Piasecki, T. M., Slutske, W. S., Wood, P. K., Sher, K. J., http://dx.doi.org/10.15288/jsa.2000.61.5 Shiffman, S., & Heath, A. C. (2012). Validity of the Hangover Symp- Marhe, R., Waters, A. J., van de Wetering, B. J. M., & Franken, I. H. A. toms Scale: Evidence from an electronic diary study. Alcoholism: Clin- (2013). Implicit and explicit drug-related cognitions during detoxifica- ical and Experimental Research, 36, 171–177. http://dx.doi.org/10.1111/ tion treatment are associated with drug relapse: An ecological momen- j.1530-0277.2011.01592.x ALCOHOL SENSITIVITY AND CRAVING 365

Robinson, T. E., & Berridge, K. C. (1993). The neural basis of drug Setiawan, E., Pihl, R. O., Dagher, A., Schlagintweit, H., Casey, K. F., craving: An incentive-sensitization theory of addiction. Brain Research Benkelfat, C., & Leyton, M. (2014). Differential striatal Reviews, 18, 247–291. http://dx.doi.org/10.1016/0165-0173(93)90013-P responses following oral alcohol in individuals at varying risk for Robinson, T. E., & Berridge, K. C. (2003). Addiction. Annual Review of dependence. Alcoholism: Clinical and Experimental Research, 38, 126– Psychology, 54, 25–53. http://dx.doi.org/10.1146/annurev.psych.54 134. http://dx.doi.org/10.1111/acer.12218 .101601.145237 Shiffman, S., Dunbar, M. S., & Ferguson, S. G. (2015). Stimulus control in Robinson, T. E., & Berridge, K. C. (2008). The incentive sensitization intermittent and daily smokers. Psychology of Addictive Behaviors, 29, theory of addiction: Some current issues. Philosophical Transactions of 847–855. http://dx.doi.org/10.1037/adb0000052 the Royal Society of London: Series B, Biological Sciences, 363, 3137– Shiffman, S., & Paty, J. (2006). Smoking patterns and dependence: Con- 3146. http://dx.doi.org/10.1098/rstb.2008.0093 trasting chippers and heavy smokers. Journal of Abnormal Psychology, Robinson, T. E., Yager, L. M., Cogan, E. S., & Saunders, B. T. (2014). On 115, 509–523. http://dx.doi.org/10.1037/0021-843X.115.3.509 the motivational properties of reward cues: Individual differences. Neu- Shin, E., Hopfinger, J. B., Lust, S. A., Henry, E. A., & Bartholow, B. D. ropharmacology, 76, 450–459. http://dx.doi.org/10.1016/j.neuropharm (2010). Electrophysiological evidence of alcohol-related attentional bias .2013.05.040 in social drinkers low in alcohol sensitivity. Psychology of Addictive Saunders, B. T., & Robinson, T. E. (2012). The role of dopamine in the Behaviors, 24, 508–515. http://dx.doi.org/10.1037/a0019663 accumbens core in the expression of Pavlovian-conditioned responses. Tarantola, M. E., Heath, A. C., Sher, K. J., & Piasecki, T. M. (2017). WISDM European Journal of Neuroscience, 36, 2521–2532. http://dx.doi.org/10 primary and secondary dependence motives: Associations with smoking .1111/j.1460-9568.2012.08217.x rate, craving, and cigarette effects in the natural environment. & Sayette, M. A. (2016). The role of craving in substance use disorders: Theo- Tobacco Research, 19, 1073–1079. http://dx.doi.org/10.1093/ntr/ntx027 retical and methodological issues. Annual Review of Clinical Psychology, Tiffany, S. T. (1990). A cognitive model of drug urges and drug-use 12, 407–433. http://dx.doi.org/10.1146/annurev-clinpsy-021815-093351 behavior: Role of automatic and nonautomatic processes. Psychological Schuckit, M. A. (1980). Self-rating of alcohol intoxication by young men Review, 97, 147–168. http://dx.doi.org/10.1037/0033-295X.97.2.147 with and without family histories of alcoholism. Journal of Studies on Tiffany, S. T., & Conklin, C. A. (2000). A cognitive processing model of Alcohol, 41, 242–249. http://dx.doi.org/10.15288/jsa.1980.41.242 alcohol craving and compulsive alcohol use. Addiction, 95(Suppl. 2), Schuckit, M. A. (1994). Low level of response to alcohol as a predictor of 145–153. http://dx.doi.org/10.1046/j.1360-0443.95.8s2.3.x future alcoholism. American Journal of Psychiatry, 151, 184–189. Trela, C. J., Piasecki, T. M., Bartholow, B. D., Heath, A. C., & Sher, K. J. http://dx.doi.org/10.1176/ajp.151.2.184 (2016). The natural expression of individual differences in self-reported Schuckit, M. A., & Smith, T. L. (1996). An 8-year follow-up of 450 sons level of response to alcohol during ecologically assessed drinking epi- of alcoholic and control subjects. Archives of General Psychiatry, 53, sodes. Psychopharmacology, 233, 2185–2195. http://dx.doi.org/10 202–210. http://dx.doi.org/10.1001/archpsyc.1996.01830030020005 .1007/s00213-016-4270-5 Schuckit, M. A., Smith, T. L., Anderson, K. G., & Brown, S. A. (2004). Treloar, H., Piasecki, T. M., McCarthy, D. M., Sher, K. J., & Heath, A. C. Testing the level of response to alcohol: Social information processing (2015). Ecological evidence that affect and perceptions of drink effects model of alcoholism risk—A 20-year prospective study. Alcoholism: depend on alcohol expectancies. Addiction, 110, 1432–1442. http://dx Clinical and Experimental Research, 28, 1881–1889. http://dx.doi.org/ 10.1097/01.ALC.0000148111.43332.A5 .doi.org/10.1111/add.12982 Schuckit, M. A., Smith, T. L., & Tipp, J. E. (1997). The Self-Rating of the Trim, R. S., Schuckit, M. A., & Smith, T. L. (2009). The relationships of Effects of Alcohol (SRE) form as a retrospective measure of the risk for the level of response to alcohol and additional characteristics to alcohol alcoholism. Addiction, 92, 979–988. http://dx.doi.org/10.1111/j.1360- use disorders across adulthood: A discrete-time survival analysis. Alco- 0443.1997.tb02977.x holism: Clinical and Experimental Research, 33, 1562–1570. http://dx Schuckit, M. A., Smith, T. L., Trim, R., Kreikebaum, S., Hinga, B., & .doi.org/10.1111/j.1530-0277.2009.00984.x Allen, R. (2008). Testing the level of response to alcohol-based model of Weinberg, A., & Hajcak, G. (2010). Beyond good and evil: The time- heavy drinking and alcohol problems in offspring from the San Diego course of neural activity elicited by specific picture content. Emotion, Prospective Study. Journal of Studies on Alcohol and Drugs, 69, 571– 10, 767–782. http://dx.doi.org/10.1037/a0020242 579. http://dx.doi.org/10.15288/jsad.2008.69.571 Wood, P. K., Sher, K. J., & Rutledge, P. C. (2007). College student alcohol Schuckit, M. A., Tipp, J. E., Smith, T. L., Wiesbeck, G. A., & Kalmijn, J. consumption, day of the week, and class schedule. Alcoholism: Clinical (1997). The relationship between Self-Rating of the Effects of alcohol and Experimental Research, 31, 1195–1207. http://dx.doi.org/10.1111/j and alcohol challenge results in ninety-eight young men. Journal of .1530-0277.2007.00402.x Studies on Alcohol, 58, 397–404. http://dx.doi.org/10.15288/jsa.1997.58 Wray, J. M., Godleski, S. A., & Tiffany, S. T. (2011). Cue-reactivity in the .397 natural environment of cigarette smokers: The impact of photographic

This document is copyrighted by the American Psychological Association or one of its alliedSchupp, publishers. H. T., Cuthbert, B. N., Bradley, M. M., Cacioppo, J. T., Ito, T., & and in vivo smoking stimuli. Psychology of Addictive Behaviors, 25,

This article is intended solely for the personal use of the individual userLang, and is not to be disseminated broadly. P. J. (2000). Affective picture processing: The late positive 733–737. http://dx.doi.org/10.1037/a0023687 potential is modulated by motivational relevance. Psychophysiology, 37, 257–261. http://dx.doi.org/10.1111/1469-8986.3720257 Selzer, M. L., Vinokur, A., & van Rooijen, L. (1975). A self-administered Received October 18, 2017 Short Michigan Alcoholism Screening Test (SMAST). Journal of Stud- Revision received April 8, 2018 ies on Alcohol, 36, 117–126. http://dx.doi.org/10.15288/jsa.1975.36.117 Accepted April 9, 2018 Ⅲ