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Adaptation of the Monetary Choice Questionnaire to AccommodateExtreme Monetary Discounting in Cocaine Users

Sheri L. Towe and Andréa L. Hobkirk Duke University School of Medicine

Daniel G. YeDuke University

Christina S. MeadeDuke University School of Medicine

Delay discounting, which refers to the phenomenon that rewards decrease in subjective value as the delayassociated with their receipt increases, is a paradigm that has been used extensively in substance abuseresearch to understand impulsive decision making. One common measure to assess delay discounting isthe Monetary Choice Questionnaire (MCQ) developed by Kirby, Petry, and Bickel (1999) . While theMCQ has great utility because of its simplicity and brief administration time, it is possible that the MCQproduces a ceiling effect in estimating delay discounting parameters in highly impulsive individuals. Inthe present study, we adapted the MCQ to attempt to address this ceiling effect by extending the original

scale with 9 items, and we then compared scores on the original MCQ with the extended MCQ in asample of active cocaine users. The ceiling effect, while observed in the original MCQ scores for overa quarter of the sample, was largely eliminated with the extended scale. Highly impulsive participants,whose scores on the extended scale exceeded the highest possible score on the original scale, had higherlevels of sensation seeking compared to other participants, but not trait impulsivity. The extended MCQmay be useful in populations with high rates of impulsivity, where the original measure may underes-timate discounting rates due to a ceiling effect.

Keywords: impulsivity, delay discounting, cocaine dependence, drug abuse

Delay discounting describes to the phenomenon that rewardsdecrease in subjective value as the delay associated with theirreceipt increases ( Mazur, 1987 ; Rachlin & Green, 1972 ).Highly impulsive individuals exhibit high rates of delay dis-counting in laboratory tasks, meaning that they show preferencefor smaller, immediate rewards over larger, delayed rewards.Research has demonstrated that higher rates of delay discount-ing are associated with various health risk behaviors, includingsubstance use, problematic gambling, and HIV transmissionrisk behaviors ( Bickel & Marsch, 2001 ; Chesson et al., 2006 ;Odum, Madden, Badger, & Bickel, 2000 ; Reynolds, 2006 ).

Delay discounting has been utilized extensively as a para-digm for impulsivity in substance users, because increaseddelay discounting theoretically reflects a fundamental decisionmaking process present in substance using populations ( Reyn-olds, 2006 ). While decision making is a complex process, partof the phenomenology of substance dependence is thatsubstance-dependent persons often make choices that contradicttheir stated goals. For example, a person may commit to quit-ting smoking one day, only to buy a pack of cigarettes thefollowing day. Delay discounting may be a key factor in howthat decision is reached. For those with high rates of delaydiscounting, more distal rewards, like achieving 30 days of sobriety or having funds to pay bills at the end of the month, areunderweighted compared with immediate rewards, such as sub-stance use.

Delay discounting has been shown to correlate with othermeasures of impulsivity, including trait impulsivity and sensa-tion seeking ( Caswell, Bond, Duka, & Morgan, 2015 ; Koff &Lucas, 2011 ). However, other research has shown weak orinconsistent associations ( Mitchell, 1999 ; Vuchinich & Simp-son, 1998 ). Research has demonstrated that higher delay dis-counting rates are associated with addictive behaviors acrossmany different substances, including nicotine, cocaine, opiates,and alcohol compared with nondrug using controls ( MacKillopet al., 2011 ). Cocaine users in particular have demonstratedgreater delay discounting compared with nondrug users(Garcia-Rodriguez, Secades-Villa, Weidberg, & Yoon, 2013 ;Heil, Johnson, Higgins, & Bickel, 2006 ; Kirby & Petry, 2004 ).

This article was published Online First July 20, 2015.Sheri L. Towe and Andréa L. Hobkirk, Department of Psychiatry &

Behavioral Sciences and Duke Global Health Institute, Duke UniversitySchool of Medicine; Daniel G. Ye, Duke Global Health Institute, DukeUniversity; Christina S. Meade, Department of Psychiatry & BehavioralSciences and Duke Global Health Institute, Duke University School of Medicine.

This study was funded by Grants K23-DA028660, F32-DA038519, andT32-AI007392 from the United States National Institutes of Health. We aregrateful to the UNC Center for AIDS Research (P30-AI50410) for itsassistance with patient recruitment. The NIH had no further role in studydesign, data collection, analysis and interpretation of data, writing thereport, or in the decision to submit the article for publication. We thank allthe men and women who participated in this study.

Correspondence concerning this article should be addressed to Sheri L.Towe, Duke University, Box 90519, Durham, NC 27708. E-mail:[email protected]

Thisarticleisintendedsolelyforthepersonaluseoftheindividualuserandisnottobedisseminatedbroadly.

Psychology of Addictive Behaviors © 2015 American Psychological Association2015, Vol. 29, No. 4, 1048 –1055 0893-164X/15/$12.00 http://dx.doi.org/10.1037/adb0000101

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One measure that has been successfully used to assess delaydiscounting in the laboratory is the Monetary Choice Question-naire (MCQ; Kirby, Petry, & Bickel, 1999 ). The MCQ asksparticipants to make 27 choices between smaller immediate re-wards versus larger delayed rewards ( Kirby et al., 1999 ). Byexamining the pattern of responses, one can infer a participant’s

rate of delay discounting or “ k value.” Kirby, Petry, and Bickel(1999) found that MCQ scores were correlated with other mea-sures of impulsivity such as the Barratt Impulsiveness Scale, andmean MCQ scores were higher among the substance-users com-pared to nondrug using controls. Additionally, research has shownthat the scores from the MCQ correlate highly with scores fromtraditional measures of delay discounting, such as adjusting-amount procedures ( Epstein et al., 2003 ). Taken together, thisresearch suggests that the MCQ is a valid means of measuringdelay discounting. Given its simplicity and brevity, the MCQ is anideal measure to administer in time-limited research settings whereuse of lengthier behavioral tasks to assess delay discounting is notfeasible.

Highly impulsive persons may exhibit an extreme preference forimmediate rewards. On the MCQ, these individuals select theimmediate reward in all 27 items, resulting in a ceiling effect. Inthese cases, the 27-item MCQ may underestimate the rate of delaydiscounting. This ceiling effect has been observed in prior researchusing the MCQ with substance users. For example, in one sampleof alcohol and cocaine users, participants always selected theimmediate reward in approximately 22% of the MCQs adminis-tered (Black & Rosen, 2011 ). In addition, a ceiling effect has beenobserved in other measures of delay discounting among highlyimpulsive samples and has been cited as a contributing factor tospurious correlations ( Johnson, Bickel, & Baker, 2007 ; Petry &Casarella, 1999 ; Yoon et al., 2007 ). Thus, this ceiling effect is of concern when working with populations who exhibit high impul-

sivity, including stimulant users who engage in high rates of riskybehaviors.

To address this ceiling effect, we adapted the MCQ to accom-modate extreme discounting by adding nine items to extend thescale. The purpose of this article is to describe the adaptationprocess and to compare performance on the original versusadapted versions of the MCQ in a sample of cocaine users.

Method

Participants and Procedures

MCQ data was collected as part of a larger study examining theneurocognitive effects of HIV and cocaine use ( Meade, Towe,Skalski, & Robertson, 2015 ). The community-based sample in-cluded 101 adult cocaine users who met the following inclusioncriteria: (a) 4 days of cocaine use in the past month or a positiveurine drug screen for cocaine, (b) 1 year of regular cocaine use,and (c) lifetime cocaine dependence. Alcohol, marijuana, andnicotine use were permitted, and current alcohol and marijuanadependence were permitted if cocaine dependence was the princi-pal diagnosis. For other drugs, individuals were excluded forlifetime abuse or dependence, history of regular use, any use in thepast year, and/or a positive drug screen. Additional exclusioncriteria were: English nonfluency or illiteracy; ninth gradeeducation; serious neurological disorders (e.g., seizure disorder,

cryptococcal meningitis) or severe head trauma; severe mentalillness; pregnancy; physical disabilities impeding participation(e.g., blindness); and impaired mental status.

Participants were recruited from the Raleigh-Durham, NC areabetween May, 2010 and May, 2015 via advertisements in localnewspapers and websites, flyers, and brochures at community-

based organizations and clinics, and participant referrals. All po-tential participants completed a structured telephone screen toassess preliminary eligibility (e.g., HIV infection, drug use his-tory), and interested individuals were then invited for a compre-hensive in-person screening.

After providing written informed consent, participants weregiven a breathalyzer test to ensure sobriety, and they provided aurine sample for drug and pregnancy screening. Self-reportedHIV-positive status was verified by medical record review, andHIV-negative status was confirmed by an OraQuick © rapid HIVtest. Participants then completed clinical interviews and question-naires. Eligible participants returned on another day to complete aneurocognitive assessment that included the MCQ, additional clin-ical interviews and questionnaires, and another urine drug test. Allquestionnaires were computerized using audio computer-assistedself-interview (ACASI).

Participants were paid $35 for the screening visit, regardless of eligibility, and $65 for the neurocognitive assessment. All proce-dures were approved by the institutional review boards at DukeUniversity Health System and University of North Carolina atChapel Hill.

Measures

Original Monetary Choice Questionnaire (MCQ-27).Participants are presented with choices between smaller, immedi-ate rewards and larger, delayed rewards (e.g., “Would you prefer

$54 today or $80 in 30 days?;” Kirby et al., 1999 ). The MCQ-27includes a fixed set of 27 items with immediate rewards rangingfrom $11–$78 and delayed rewards ranging from $25–$85 with adelay of 7–186 days. Delayed rewards are grouped into threecategories based on size, with nine items per category: small($25–$35), medium ($50–$60), and large ($75–$85).

As described by Kirby et al. (1999) , participants’ hyperbolicdiscount parameter ( k value) is determined by fitting data to thefollowing discount function equation: V immediate V delayed /(1 k D), in which V is the reward value in dollars and D is delay indays (Mazur, 1984 ). Values of k range from 0.00016 to 0.25 for theMCQ-27, with higher values indicating a greater preference forsmaller, immediate rewards over larger, delayed rewards. Eachpossible k value increases by an order of approximately 2.5,resulting in a logarithmic scale. K values are estimated by takingthe geometric midpoint between the discount rates associated witheach item and then examining the participant’s pattern of re-sponses across trials to determine which k value is most consistentwith the response pattern. By examining the pattern of responses inthis way, one can infer a participant’s point of indifference be-tween delayed and immediate rewards. To determine the mostconsistent value, the proportion of a participant’s choices that areconsistent with each k value is calculated. The k value that yieldsthe highest proportion is the value assigned to the participant. If two or more values have the same proportion, the participant’sassigned k value is the geometric mean of those values. Because


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raw k values tend to be highly skewed, k values are normalizedusing the natural logarithm transformation. K values are alsoranked from 1 to 10. Rank 1 and Rank 10 represent the lowest andhighest possible k values, respectively (e.g., when a participantselects all delayed rewards or all immediate rewards across trials),and Ranks 2 through 9 are assigned to the ranges of discount rates

between items (e.g., values between 0.00016 to 0.00040 wereRank 2).Extended Monetary Choice Questionnaire (MCQ-36). To

expand the MCQ-27, nine items with higher associated k values wereadded. Three new items were added to each category (small, medium,large), resulting in 12 items per category and a total of 36 items for theMCQ-36. Additional k values for the extended scale were computedby continuing the logarithmic scale of the original MCQ-27, resultingin new k values of 0.625, 1.5625, and 3.90625. The new itemsincluded delay periods lasting 1–7 days and utilized the same threedelayed rewards as the other items in the category. The immediatereward for each additional item was calculated based on the standarddiscount function equation, resulting in immediate rewards for thesenew items ranging from $5–$17. Dollar amounts were rounded to the

nearest whole dollar, and then the exact k for that dollar amount wascalculated with the formula. This resulted in k values for the MCQ-36ranging from 0.00016 to 4.00. K values were also natural log trans-formed and ranked for the MCQ-36, with ranks ranging from 1 to 13.Table 1 shows the items included in the MCQ-36 and their calculatedk values.

The MCQ-36 was computerized using ePrime (PsychologySoftware Tools, Inc., http://www.pstnet.com ). Choices were pre-sented in random order, and participants indicated their responseusing a computer mouse. Participants completed the full MCQ-36,and then scores were generated for the original MCQ-27 and theextended MCQ-36. Participants were told that all rewards werehypothetical, and participants did not receive any money based ontheir performance on the task.

Barratt Impulsiveness Scale—version 11 (BIS-11). At theneurocognitive assessment, participants completed the BIS-11(Patton, Stanford, & Barratt, 1995 ), which is one of the oldest andmost widely used self-report measures of trait impulsivity ( Stan-ford et al., 2009 ). The BIS-11 includes 30 items that describecommon impulsive or nonimpulsive behaviors and preferences.

Table 1 Items in the Extended Monetary Choice Questionnaire (MCQ-36)

Reward size Amount today Amount later Delay in days Calculated k valuea

Small 34 35 186 0.00016Small 28 30 179 0.00040Small 22 25 136 0.00100Small 25 30 80 0.00250Small 19 25 53 0.00596Small 24 35 29 0.01580Small 14 25 19 0.04135Small 15 35 13 0.10256

Small 11 30 7 0.24675Small b 6 25 5 0.63333Small b 5 30 3 1.66667Small b 7 35 1 4.00000Medium 54 55 117 0.00016Medium 47 50 160 0.00040Medium 54 60 111 0.00100Medium 49 60 89 0.00252Medium 40 55 62 0.00605Medium 34 50 30 0.01569Medium 27 50 21 0.04056Medium 25 60 14 0.10000Medium 20 55 7 0.25000Medium b 12 50 5 0.63333Medium b 13 55 2 1.61538Medium b 12 60 1 4.00000Large 78 80 162 0.00016Large 80 85 157 0.00040Large 67 75 119 0.00100Large 69 85 91 0.00255Large 55 75 61 0.00596Large 54 80 30 0.01605Large 41 75 20 0.04146Large 33 80 14 0.10173Large 31 85 7 0.24885Large b 17 80 6 0.61765Large b 13 75 3 1.58974Large b 17 85 1 4.00000

a Exact values calculated using the standard discount function equation, V immediate Vdelayed /(1 k D), in whichk represents the k value, V is the reward value in dollars and D is delay in days. b Item added to the MCQ-36that was not included in the MCQ-27.


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Participants rate each items using a 4-point scale ( rarely/never ,occasionally , often , almost always/always ), and higher scores in-dicate greater impulsiveness. All 30 items are summed to yield atotal score, ranging from 30 to 120, and there are six subscalesbased on first-order factors determined by a principal componentanalysis ( Patton et al., 1995). The six subscales are attention,

motor impulsiveness, self-control, cognitive complexity, persever-ance, and cognitive instability.Sensation Seeking Scale—version V (SSS-V). Participants

also completed the SSS-V ( Zuckerman, 1994 ; Zuckerman, Eysenck,& Eysenck, 1978 ). In this 40-item, forced-choice questionnaire, par-ticipants choose which of two statements best applies to them. Thisinventory was developed to measure individual differences in stimu-lation and arousal needs and is thought to correlate with impulsivity.Reliability and construct validity for this instrument has been well-established ( Zuckerman, 1994 ; Zuckerman et al., 1978 ). Each state-ment is scored as either 0 or 1, and then items are summed to createa total score, ranging from 0 to 40. In addition to a total score, theSSS-V produces four subscales that represent different dimensions of sensation seeking: thrill and adventure seeking, experience seeking,disinhibition, and boredom susceptibility.

Other measures. Demographic characteristics and detailed as-sessments of substance use were completed at the screening visit.Interviews included Module E of the Structured Clinical Interview for DSM–IV–TR to assess for lifetime cocaine dependence and othersubstance use disorders ( First, Spitzer, Gibbon, & Williams, 1996 )and the Addiction Severity Index-Lite to assess lifetime substance useand associated impairments ( McLellan et al., 1992 ). Frequency of substance use in the past 30 days was assessed using timeline follow-back methodology ( Robinson, Sobell, Sobell, & Leo, 2014 ; Sobell &Sobell, 1996 ). A urine toxicology screen for cocaine, cannabis, am-phetamine, methamphetamine, oxycodone, methadone, other opioids(including heroin), benzodiazepines, and barbiturates was used to

corroborate self-report. Premorbid verbal IQ was estimated using theWechsler Test of Adult Reading (WTAR), in which participants read50 words aloud that have atypical grapheme to phoneme translations(Wechsler, 2001 ). Finally, participants completed a computerizedsurvey that assessed demographics.

Participants completed the Brief Symptom Inventory 18 (BSI-18)at the neurocognitive assessment. The BSI-18 is an 18-item question-naire which assesses psychological distress. Participants rate theirlevel of distress associated with 18 symptoms over the past week using a 5-point Likert scale (0 not at all to 4 extremely ;Derogatis, 1993 ). An overall score is created by calculating the meanof all 18 items. The HIV Risk Behavior Scale (HRBS), a brief interview, was also completed at the neurocognitive assessment. TheHRBS, a well-validated measure, assesses frequency of drug risk behaviors (six items) and sex risk behaviors (six items) in the past 30days (Darke, Hall, Heather, Ward, & Wodak, 1991 ). For the HRBS,items are summed to create a total score.

Quality Assurance Procedures

All MCQ data were evaluated to ensure that participants respondedin a consistent manner and appeared to understand the task. Withineach category of delayed rewards (small, medium, large), consistencywas evaluated by examining the highest proportion of consistentchoices. Cases where ties resulted (e.g., two or more k values haveequally high proportions) were considered indicative of potentially

inconsistent responding because a tie indicates that multiple k valuesare equally likely to represent a participant’s true point of indifference.While ties are generally handled by taking the geometric mean of thek values, this method has potential for bias when the pattern of responding is inconsistent. Therefore, we established more rigorousstandardized criteria to evaluate when ties result in k value estimates

that are potentially not valid. The k value within a category wasexcluded if either of the following criteria were met: (a) there was atie for the highest proportion between two k values and those k valueswere separated by more than one other k value, or (b) there was a tiebetween three or more k values for the highest proportion. This firstcriterion was selected because the geometric mean of two tied k values which are separated by only one other k value likely doesclosely approximate a participant’s actual point of indifference, butthe geometric mean of two highly discrepant k values (i.e., separatedby more than one other k value) may not provide as accurate anapproximation. For example, responses in the large category for oneparticipant resulted in a two-way tie between k values of Rank 6 andRank 10, and a geometric mean between these two values wouldresult in a k value of Rank 8. If one of these responses was an erroror mistake by the participant (due to lack of comprehension orresponse imputation error), a Rank of 8 would not be as closelyrepresentative of the participant’s actual point of indifference. Thesecond criterion was selected because three- and four-way ties gen-erally result in very low proportions. For example, responses in thesmall reward category for one case resulted in a four-way tie, witheach k value having a proportion of 0.58. When no exclusion rule wasmet, the k values within each category were considered valid.

Cases were also evaluated for overall consistency. Cases weremarked as overall inconsistent when either: (a) k value proportionswere less than or equal to 0.80 in at least two categories, (b) propor-tions in all three categories resulted in ties, or (c) k values across twoor more categories were excluded during scoring. These criteria were

selected because they each indicate that inconsistent responding oc-curred across two or more reward categories. When a case wasmarked as overall inconsistent, all k values for that case were ex-cluded.

Using these procedures, two cases (2%) were marked as highlyinconsistent overall and excluded from analysis, resulting in 99 caseswith valid MCQ data. In the individual reward categories for theremaining 99 cases, no cases were marked as invalid in small, onecase was marked as invalid in medium, and two cases were marked asinvalid in large. For those cases, that category value was consideredinvalid, but the other two categories were marked as valid andtherefore the case was retained for analysis.

Data Analysis PlanQuantitative analysis was conducted using SPSS 21.0.0

(SPSS Inc., Chicago, IL). Descriptive statistics were used tocharacterize the sample and determine the geometric mean forthe raw k value, mean ln k value, mean rank value, and the totalnumber of cases with the maximum score for both the MCQ-27and MCQ-36. Participants whose k value on the MCQ-36exceeded the maximum possible k value of 0.25 on the MCQ-27were classified as extreme responders. Independent sample t tests and chi-squared tests were conducted to identify differ-ences in demographic and other relevant variables across ex-treme responders and nonextreme responders. Variables iden-



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tified as significantly different between groups and relevantdemographic characteristics (age, race, gender, and years of education) were included as covariates in the remaining anal-yses. Univariate analyses of covariance (ANCOVAs) were per-formed to examine differences between extreme versus nonex-treme responders on the BIS, SSS, and other relevant variables.

Results

Participant Characteristics

The majority of participants were male (66%) and AfricanAmerican (92%). Participants were 46.29 years old on average(SD 8.46) and 49% of the sample was HIV-positive. Approx-imately 24% of the sample identified as gay, lesbian, or bisex-ual. Participants reported 12.24 years of education on average(SD 2.40) and 84% reported being unemployed. Participantshad used cocaine on average 10.50 of the past 30 days ( SD 7.64) and reported a mean of 17.80 years of regular cocaine use(SD 7.48). The vast majority (88%) reported smoking as theirusual route of cocaine administration, and 85% of the sampletested positive for cocaine in a urine drug screen completed onthe day the MCQ was administered.

MCQ-27 and MCQ-36 Descriptive Characteristics

Table 2 presents geometric means of raw k values, mean ln k values, and mean rank values for the MCQ-27 and the MCQ-36overall and within each reward category. With the extendedscale, the MCQ-36 produced higher k values than the MCQ-27overall and across each category. Figure 1 shows the number of participants with each rank value in the MCQ-36. A total of 26participants (26%) were assigned a k value of 0.25 in either

their overall mean or within at least one individual reward sizecategory on the MCQ-36. Seventeen participants (17%) wereassigned a k value of 0.25 for their overall mean k value.Eighteen participants (18%) received a k value of 0.25 in thesmall category, 15 (15%) in medium, and 16 (16%) in large. Atotal of four participants (4%) were assigned the maximumpossible k value of 4.00 in either their overall mean or within atleast one individual reward size category. Two participants(2%) were assigned the maximum k value of 4.00 for theiroverall mean, with two participants (2%) receiving the maxi-mum value in the small category, two (2%) in the mediumcategory, and four (4%) in the large category.

Comparison of Extreme Responders to NonextremeResponders

We compared the 26 extreme responders to the 73 nonex-treme responders on other participant and substance use char-acteristics (e.g., occupational status, days of cocaine use) to

identify other potential control variables. A significantly higherproportion of nonextreme responders (89%) were unemployedcompared to extreme responders (69%) for occupational status,

2 (1, N 99) 5.55, p .018. There was also a significantdifference between groups on sexual orientation, 2 (1, N 99) 3.88, p .049, such that a larger proportion (39%) of extreme responders identified as gay, lesbian, or bisexual com-pared to nonextreme responders (19%). There were no othersignificant differences between groups. Therefore, in additionto age, race, gender, and years of education, occupational statusand sexual orientation were included as covariates in the sub-sequent ANCOVAs.

Table 3 presents the adjusted means and F values for eachANCOVA. Several group differences were apparent on theSSS-V, with extreme responders having higher scores overalland on the experience seeking and disinhibition subscales. Onthe BIS-11, groups did not significantly differ across the total orsubscale scores. Groups also did not differ on premorbid verbalIQ, HRBS score, or BSI total score. To reduce the risk of a TypeI error due to multiple comparisons, we applied a familywiseBonferroni adjustment to the significance level for theseANCOVAs so that significance levels were set at p .003. Noresults were significant using this adjusted significance level.Traditional p values (i.e., p .05, 0.01) are noted in Table 3 .

Discussion

In this sample of active cocaine users, the modified MCQ-36appeared to be successful in reducing a ceiling effect on k scores compared with the MCQ-27. There was a clear ceilingeffect using the original MCQ-27 items, with over a quarter of participants producing k values that exceeded the maximumpossible k value. This ceiling effect was reduced substantiallywith the MCQ-36 to only four participants receiving the max-imum possible k value. Based on these results, use of theextended MCQ-36 may be warranted in populations with highrates of impulsivity, such as out-of-treatment cocaine users, inorder to get a more accurate estimate of discounting parameters.

Table 2 Average K Values, ln K Values, and Ranks for the Original Monetary Choice Questionnaire (MCQ-27) and Extended MonetaryChoice Questionnaire (MCQ-36)

Reward size

K value geo. mean (95% CI) a ln k value M (SD) Ranked k value M (SD)

MCQ-27 MCQ-36 MCQ-27 MCQ-36 MCQ-27 MCQ-36

Small N 99 0.06 [0.05, 0.08] 0.08 [0.05, 0.10] 2.76 (1.34) 2.57 (1.62) 8.08 (1.58) 8.21 (1.81)Medium N 98 0.05 [0.04, 0.06] 0.06 [0.04, 0.08] 3.00 (1.35) 2.84 (1.61) 7.82 (1.58) 7.93 (1.80)Large N 97 0.04 [0.03, 0.05] 0.05 [0.03, 0.07] 3.20 (1.38) 2.97 (1.80) 7.59 (1.63) 7.78 (2.02)Overall mean N 99 0.05 [0.04, 0.06] 0.06 [0.04, 0.08] 2.98 (1.20) 2.78 (1.51) 7.84 (1.43) 7.99 (1.69)a geo. mean geometric mean of raw k values, 95% CI 95% confidence intervals for each geometric mean.



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There were some notable differences between extreme re-sponders and nonextreme responders on the SSS, though thesewere not statistically significant after correcting for multiplecomparisons using the Bonferroni adjustment. Overall, extremeresponders had higher levels of sensation seeking comparedwith nonextreme responders, and showed particularly high lev-els of sensation seeking in disinhibition and experience seeking.Disinhibition reflects both social and sexual disinhibition that isexpressed in substance-use behaviors and variety in sexualpartners ( Zuckerman et al., 1978 ). Experience seeking repre-sents the pursuit of new sensations and experiences through themind and senses, and activities such as travel and a noncon-forming lifestyle ( Zuckerman et al., 1978 ).

There were few differences between extreme responders andnonextreme responders on cocaine use, trait impulsivity, andmany other participant characteristics. The lack of differenceson cocaine use variables is very likely the result of stricteligibility criteria for the sample related to frequency andseverity of cocaine use. Use of these strict criteria resulted in a

relatively homogeneous sample in terms of substance use char-acteristics.

The findings from this study have important implications formeasuring delay discounting in highly impulsive populations.In our results, scores based on the MCQ-27 yielded k values thatunderestimated delay discounting due to a ceiling effect for alarge proportion of our participants. Other studies using the27-item MCQ with substance users reported mean k valuessimilar to those in the current study sample ( Gonzalez et al.,2012 ; Kirby & Petry, 2004 ). Therefore, it is possible that othershave found a similar ceiling effect, although it has not beenreported. The MCQ-36 represents a way to assess a wider rangeof delay discounting in highly impulsive individuals that cap-tures variability that would otherwise be missed by the shorterMCQ-27. Furthermore, while yielding a potentially more accu-rate estimate of delay discounting, the addition of nine items inthe MCQ-36 did not substantially increase the length of time of administration. Future research might compare this extendedMCQ against other validated measures of delay discounting.

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Figure 1. Histograms of ranked k -values across reward categories and by overall mean for the MCQ-36.Shaded bars represent ranks from the original MCQ-27 items. Additional ranks from the extended k value scaleincluded in the MCQ-36 are unshaded. MCQ-27 Original Monetary Choice Questionnaire; MCQ-36 Extended Monetary Choice Questionnaire.



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Additionally, future research could examine whether scores onthe MCQ-36 are more predictive of risk behaviors.

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Table 3Comparison of Extreme Responders to Nonextreme Responders Using ANCOVA

Adjusted means

Nonextreme responders Extreme respondersMeasure ( N 73) ( N 26) F value

Barratt Impulsiveness ScaleBIS-11 total score 65.18 65.52 F (1, 91) .02Self-control 14.69 15.60 F (1, 91) 1.40Motor impulsiveness 14.51 13.71 F (1, 91) 1.40Attention 9.93 10.28 F (1, 91) .29Cognitive instability 4.66 5.04 F (1, 91) 1.04Cognitive complexity 13.16 13.12 F (1, 91) .01Perseverance 8.23 7.78 F (1, 91) .87

Sensation Seeking ScaleSSS-V total score 14.22 17.04 F (1, 91) 5.14Thrill and adventure seeking 3.23 3.52 F (1, 91) .24Experience seeking 4.62 5.56 F (1, 91) 4.21Disinhibition 4.14 5.48 F (1, 91) 8.27Boredom susceptibility 2.23 2.47 F (1, 91) .37

Estimated premorbid verbal IQ 86.83 82.71 F (1, 90) 2.04HRBS sex composite 3.37 4.34 F (1, 91) 1.19

BSI total score 0.49 0.53 F (1, 91) .11 Note. The covariates included were age, race, gender, years of education, sexual orientation, and occupationalstatus. Means presented represent the adjusted means after controlling for all covariates in the ANCOVA. BIS-11point scales: total, 30 –120; self-control, 6–24; motor impulsiveness, 7–28; attention, 5–20; cognitive instability,3–12; cognitive complexity, 5–20; perseverance, 4–16. SSS-V point scales: total, 0–40; all subscales, 0–10.ANCOVA analysis of covariance; SSS-V Sensation Seeking Scale - version V; HRBS HIV Risk Behavior Scale; BSI Brief Symptom Inventory. p .05. p .01.



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Received April 8, 2015Revision received May 8, 2015

Accepted May 9, 2015



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