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Do genetic and individual risk factors moderate the efficacy of motivational enhancement therapy? Drinking outcomes with an emerging adult sample

Abstract

Research indicates that motivational enhancement therapy (MET) helps catalyze reductions in problem drinking among emerging adults. However, moderators of this intervention remain relatively unknown. Therefore, the objectives of this study were: (1) to test whether a single session of MET increased motivation to reduce drinking and drinking outcomes; and (2) to examine whether genetic dopamine D4 receptor L (DRD4 L) and individual personality risk factors (impulsivity and novelty seeking) moderated the effects of the MET. These hypotheses were evaluated by randomly assigning a sample of emerging adult problem drinkers (n = 67) to receive a single session of MET or alcohol education. Follow-up data indicated that only individuals who were low in impulsivity, novelty seeking and/or who had the short DRD4 variable number of tandem repeats genotype evidenced differentially increased behavior change (taking steps toward reducing drinking) following the MET.

Keywords: Alcohol, emerging adults, genetics, impulsivity, motivation enhancement therapy, novelty seeking

INTRODUCTION

Many emerging adults increase their alcohol use during their college years (O’Malley & Johnston 2002). Specifically, studies throughout the past five decades have consistently found that approximately 40–47% of college students engage in binge drinking (O’Malley & Johnston 2002; Schulenberg & Maggs 2002; Chen, Dufour & Yi 2004-2005). This is concerning, as binge drinking has been significantly associated with an increase in accidents and injuries among this age group (Hingson et al. 2005). Many of these accidents and injuries stem from ‘dumb drinking’, single occasions of excessive consumption that lead to poor choices resulting in sadly irrevocable outcomes, such as those that result from drinking and driving or alcohol-related sexual risk behaviors (Miller & Munoz 2005).

Within the last decade, the cost-effectiveness, transportability and flexibility of motivational enhancement therapy (MET; Miller et al. 1999) has resulted in its surging popularity across adolescent and emerging adult settings (e.g. Stewart et al. 2005; Baer et al. 2007). Although details of this intervention vary between sites and studies (Burke, Arkowitz & Menchola 2003), MET interventions for problem drinking consistently incorporate both the fundamental motivational interviewing (MI) principles (Miller & Rollnick 2002), including rolling with resistance, accurate empathy, developing discrepancy, supporting self-efficacy as well as the provision of personalized feedback about drinking behaviors (Baer et al. 1992, 2001; Marlatt et al. 1998; Monti et al. 1999, 2007; Borsari & Carey 2000, 2005). When examining the efficacy of MET interventions in reducing late adolescent and emerging adult alcohol use, MET has gained support for catalyzing sustained, significant reductions in quantity of drinking (Baer et al. 1992; Borsari & Carey 2000; Monti et al. 2007), frequency of drinking (Borsari & Carey 2000; Monti et al. 2007), frequency of heavy drinking (Borsari & Carey 2000; Monti et al. 2007), alcohol-related problems (Marlatt et al. 1998; Borsari & Carey 2005), negative alcohol-related consequences (Baer et al. 2001), risk behaviors (Monti et al. 1999) and alcohol dependence (Marlatt et al. 1998) in follow-ups spanning from 6 weeks to 4 years.

Despite these robust results, research is needed to investigate the variables that may moderate the effectiveness of MET, particularly with high-risk drinking groups such as emerging adults. Recent research has started to support the clear role of genetic polymorphisms in biological, personality and behavioral phenotypes related to the progression of alcohol dependence. One promising genetic polymorphism is the dopamine D4 receptor (DRD4). Located in exon III, this gene has a 48-base pair (bp) variable number of tandem repeats (DRD4 VNTR). Three common variants (D4.2, D4.4 and D4.7) indicate the length of the VNTR, which has been found to have functional effects on the receptor, with lower response to dopamine corresponding with the longest (D4.7) variant (for a review, see Ray et al. 2009). As some of the key brain regions involved with alcohol dependence include the mesocorticolimbic dopamine pathway (e.g. Kalivas & Volkow 2005), this dopamine receptor is likely to play a critical role in the development and expression of incentive salience, meaning this receptor may modulate the strength and perception of alcohol, subsequently affecting the experience of craving (e.g. Hutchison et al. 2006).

In terms of previous studies, recent research has found that with adults, the DRD4 VNTR polymorphism has been linked to alcohol use disorders, novelty seeking and impulsivity (Benjamin et al. 1996; Ebstein et al. 1996; Noble et al. 1998; Hutchison et al. 2006; Eisenberg et al. 2007; MacKillop et al. 2007; Congdon, Lesch & Canli 2008; Ray et al. 2009). However, the relationship between DRD4 and alcohol use disorders appears to be developmentally sensitive. Specifically, evidence for the role of DRD4 in alcohol abuse symptomology (i.e. frequency of drinking) has been less robust with adolescents and emerging adults, with several studies finding no relationship (Hopfer et al. 2005; Guo, Wilhelmsen & Hamilton 2007; McGeary et al. 2007) and other studies only finding support for this relationship among adolescent males (Skowronek et al. 2006; Laucht et al. 2007).

In addition to the important relationship between genetic variables and the development of alcohol dependence, the association between genetic factors and individual personality risk factors is also quite salient, as studies have repeatedly demonstrated that impulsivity and novelty seeking can lead to excessive alcohol consumption levels, alcohol-related problems and consequences (e.g. Lukasiewiez et al. 2008; Verdejo-Garcia, Lawrence & Clark 2008; Vermont et al. 2008). Moreover, Although some adult studies have found that personality factors may not predict who best responds to which type of behavioral treatment (Project MATCH Research Group 1997, 1998), this relationship may also vary by developmental level, as adolescent studies have found preliminary evidence that impulsivity affects the efficacy of MET (e.g. Helstrom, Hutchison & Bryan 2007).

Recent studies have also indicated that genetic factors may influence treatment response. This is an area of rapidly growing interest, with several studies finding that genetic factors may moderate the effectiveness of both pharmacological and behavioral interventions, including MET (Hutchison et al. 2006, 2008; Bauer et al. 2007; Anton et al. 2008). Within the MET/pharmacological studies (Hutchison et al. 2006, 2008), two different genetic variants (e.g. CNR1, DRD4) have predicted who responded to MET combined with either placebo or pharmacotherapy. Notably, as examined in Hutchison et al.’s (2006) study, individuals with the genetic risk factors reduced their drinking only after receiving the active medication. However, individuals ‘without’ the genetic risk factors demonstrated reduction in the MET/placebo condition. Although preliminary, these findings suggest the integral role of genetic risk in predicting who responds to MET or other psychosocial interventions. Understanding the genetic and individual risk factors that may moderate the effectiveness of MET is an important step toward improving the efficacy of alcohol interventions for emerging adults; it may help identify who may respond to psychosocial interventions, and who may need different, perhaps more pharmacologically based, approaches to initiate and sustain reductions in alcohol use.

The objective of the present study was to examine the effects of an empirically validated alcohol intervention, MET, with the high-risk drinking group of emerging adults. The a priori aims were: (1) to determine the effect of a MET on emerging adults motivation to change their drinking behaviors and their drinking outcomes; and (2) to examine potential moderators of the efficacy of the MET, specifically evaluating the role of genetic (DRD4) and individual risk factors (impulsivity and novelty seeking). It was hypothesized that the MET, compared with an alcohol education (AE) control condition, would increase motivation to change drinking behaviors and drinking reductions 30 days post-intervention. It was further hypothesized that the DRD4 VNTR and the individual personality risk factors of impulsivity and novelty seeking would moderate the effectiveness of the MET.

MATERIALS AND METHODS

Participants

This study was conducted with approval from the participating university’s Institutional Review Board. Potential participants were recruited via fliers that invited interested students to participate in an ‘Alcohol Study . Inclusion criteria included self-reported moderate to heavy drinking, as defined by drinking twice per week with a minimum of four to five drinks per drinking occasion (women, men, respectively).

Seventy-five emerging adults (M age = 21 years; 68% male, 87% Caucasian) participated in this study. Each was paid $150 for their participation. Participants were randomly assigned to receive either a single 45-minute session of a MET or an AE control condition. Notably, because of practical constraints (e.g. the need to randomize before genotyping could occur), individuals were randomized to condition prior to genotyping. Eight participants did not complete the study, resulting in a final sample of 67 participants.

Measures

Demographic data are shown in Table 1 for the MET and AE groups, along with personality and drinking data. In addition to demographics, there were three classes of variables assessed: motivation to change, personality and alcohol history, and outcome measures.

Table 1
Pretest differences in motivational enhancement therapy (MET) versus alcohol education (AE) participants.

Motivation

The Contemplation Ladder (Biener & Abrams 1991) was adapted for use with alcohol and was used to assess the level of motivation to change drinking behaviors prior to the intervention and assess the level of motivation 30 days after the intervention. The Ladder is a single-item, continuous measure of motivation to change with good reliability and validity (Biener & Abrams 1991). Baseline motivation to change drinking behavior, as determined by this measure, served as a covariate in analyses of intervention effects to statistically control baseline motivation across treatment groups.

Moderators

Levels of all moderating variables were assessed at baseline.

The Novelty-Seeking (NS) subscale of the Tridimensional Personality Questionnaire (Cloninger 1987) was utilized as a putative moderator of intervention effectiveness. NS is described as the tendency to be excitable, exploratory, enthusiastic and impulsive. Reliability in the sample was adequate (coefficient alpha α = 0.75).

Individuals high in the Impulsivity/Sensation-seeking Scale (IMPSS; Zuckerman & Kuhlman 2000) have been found to have the tendency to take risks for novel, varied and intense experiences (e.g. Zuckerman 1994). Reliability in this sample was adequate (α = 0.80).

The Rutgers Alcohol Problem Index (RAPI; White & Labouvie 1989) was used to assess alcohol-related problems. The RAPI uses 23 items to investigate the impact of alcohol on social and health functioning. This scale has reported high reliability and validity in previous studies (Jessor et al. 1995). Reliability of this measure was high for this sample (α = 0.88).

Genotyping

Genomic DNA was isolated from buccal cells using published procedures (Lench, Stanier & Williamson 1988; Freeman et al. 1997), and the average yield of DNA was 40 + 2 µg. The 48 bp VNTR in the third exon of the DRD4 receptor polymorphism was assayed using previously reported methods (Sander et al. 1997). The primer sequences were forward, 5’-AGGACCCTCATGGCCTTG-3’ (fluorescently labeled), and reverse, 5’-GCGACTACGTGG TCTACTCG-3’ (Lichter et al. 1993). Consistent with previous reports (Lerman et al. 1998), participants who carried at least one copy of a seven-repeat or longer allele were classified as DRD4 L, although participants with alleles of fewer than seven-repeats were classified as DRD4 S; similar to frequencies found in other studies (e.g. Hutchison et al. 2006), 42% of sample was classified as DRD4 L and 58% was classified as DRD4 S (see Table 2). The majority of subjects are typically genotyped two times. Any disparities that emerged were resolved with a third genotyping.

Table 2
Evaluation of differences of genetic variables by demographics.

Changes in drinking behavior

Four outcome measures were used to assess changes in drinking behavior at the 30-day follow-up.

The first three were alcohol consumption items derived from the Timeline Follow Back (Sobell & Sobell 1992): the average number of drinks during each drinking occasion (calculated as total drinks/total drinking days), the total number of drinking days and the total number of heavy drinking days.

The fourth measure was the Taking Steps (TS) subscale of the Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES; Miller & Tonigan 1996). Of the three scales of the SOCRATES [i.e. contemplation, readiness for change and taking steps (TS) in changing drinking behavior], TS is the only one that assesses whether or not an individual has engaged in behaviors designed to reduce drinking. The abbreviated version of the TS scale has eight items with response options on a 5-point Likert scale ranging from 1 = ‘Strongly Disagree’ to 5 = ‘Strongly Agree , and has been shown to have good reliability and validity (Isenhart 1994). Reliability of the TS measure in this sample was high (α = 0.93). Items in this scale include the following (Miller & Tonigan 1996, p. 85):

  1. I have already started making some changes in my drinking.
  2. I was drinking too much at one time, but I’ve managed to change my drinking.
  3. I’m not just thinking about changing my drinking, I’m already doing something about it.
  4. I have already changed my drinking, and I am looking for ways to keep from slipping back to my old pattern.
  5. I am actively doing things now to cut down or stop drinking.
  6. I want help to keep from going back to the drinking problems that I had before.
  7. I am working hard to change my drinking.
  8. I have made some changes in my drinking, and I want some help to keep from going back to the way I used to drink.

Procedures

Screening

Participants contacted the study coordinator from advertisements to participate in an ‘Alcohol Study posted on college campus bulletin boards. A comprehensive phone screen provided study procedures, and included general health questions, consumption rates and the alcohol use disorders identification test (AUDIT; Babor et al. 2006) screen, to see if participants appeared to meet inclusion criterion. If participants appeared eligible and interested, they were scheduled for the baseline appointment.

Baseline

All participants completed the informed consent procedures and an assessment battery of paper and pencil measures, as well as DNA collection procedures.

Intervention

Upon completion of baseline measures, participants were randomly assigned to receive either a 45-minute, individually delivered MET or an AE control condition. Interventionists included a clinical psychologist of doctoral level and therapist of master s level. Interviewers were trained using a manual, live-observation and ongoing supervision (provided by the fourth author).

Control: AE

Currently, the standard treatment for college students seeking (or mandated to) alcohol treatment is AE (Barnett & Read 2005). Similar to many other studies of alcohol interventions with college youth (e.g. Barnett et al. 2007; Lau-Barraco & Dunn 2008), we therefore selected a comparison condition which would provide the most accurate comparison between what youth would be most likely to receive in the real-world (AE). During the AE session, the interviewer provided participants with information and handouts on the social, behavioral and biological effects of alcohol abuse. This included information on campus and state drinking policies, physical effects of alcohol (stimulant/depressant), blood alcohol concentration information and long-term risks of alcohol abuse. The interviewer did not elicit individualized information from participants, nor utilized open-ended questioning. However, the interviewer did answer the participants direct questions about alcohol abuse.

MET

The MET condition followed the fundamental principles of MI and the procedures outlined in the MET manual (Miller et al. 1999). The MET session consisted of a 45-minute session, focused on participants ambivalence around their drinking behaviors. Personalized feedback regarding drinking behaviors and related risk factors (i.e. family history of drinking, current drinking rates) was provided in the form of an individualized feedback report based on their responses to baseline measures and as compared with national averages. MET providers were trained to utilize reflections, accurate empathy and open questions to explore ambivalence, to elicit and support change talk, and to assist participants in developing behavioral strategies to reduce their drinking and related negative consequences. At the end of the MET session, all participants in this condition were provided with the same informational handouts as those in the AE session.

Follow-up

Participants completed an immediate post-intervention 11-item manipulation check of the intervention. A follow-up assessment battery was given 30 days after the conditions, to assess changes in motivation to reduce drinking and drinking outcomes.

RESULTS

Pretest differences

Pretest differences were assessed on demographic variables, putative moderators of intervention effectiveness and baseline behavior. There were no pretest differences between the MET and AE participants on demographic variables of gender and culture (Table 1). There was a significant difference in age such that the MET participants were slightly older than the AE participants. However, all analyses reported herein were conducted again with age as a covariate, and all results remained the same. There were no differences between the MET and AE participants on the measure of alcohol problems (RAPI), NS, IMPSS or on the presence of the short or long DRD4 polymorphism. Finally, although there were no differences in the quantity and frequency of alcohol consumption variables, the two groups were significantly different on the TS variable, such that the MET participants reported having taken more steps to reduce their drinking. Given these differences, baseline TS was controlled for in every analysis.

Effects on 30-day follow-up motivation

An analysis of covariance (ANCOVA) was conducted to test for differences in the 30-day follow-up motivation as measured by the Contemplation Ladder. Intervention condition was the independent variable, and baseline Ladder scores and TS served as covariates. There were significant intervention effects, F(1,60) = 5.62, P < 0.05. The pattern of the adjusted means (i.e. controlling for baseline motivation) showed that the MET participants had higher motivation, Madj = 5.97 [standard error of the mean (SE) = 0.50] than AE participants, Madj = 4.18 (SE = 0.55) at follow-up. There was no moderation of these effects by NS, RAPI or the DRD4 VNTR polymorphism. However, there was a significant intervention × IMPSS interaction, F(1,58) = 4.18, P = 0.05. Controlling for pretest motivation, the pattern suggests that the highest motivation to change was exhibited by low IMPSS participants in the MET condition, Madj = 6.06, and the lowest motivation to change was exhibited by low IMPSS participants in the AE condition, Madj = 3.01, as anticipated. Levels of motivation among those high on IMPSS did not differ between condition however: MET − Madj = 5.89, AE − Madj = 5.80. Post hoc pair-wise comparisons on the adjusted means confirmed that low IMPSS participants in the AE intervention had significantly lower motivation to change than all three other groups (P-values for comparisons ranged from 0.001 to 0.009), but those three other groups did not significantly differ from one another.

Effects on 30-day follow-up drinking behavior

The ANCOVAs on the drinking measures (average drinks per drinking day, total number of drinking days and total number of heavy drinking days), controlling for baseline values and baseline TS, showed changes in the expected direction, though none were statistically significant. Those in the MET condition decreased their average number of drinks per drinking day from 5.38 to 5.04, as compared with AE participants who went from 5.45 to 5.15 average drinks per session, F(1,60) < 1, not significant (ns). Similarly, the MET participants decreased their drinking days slightly from 11.71 to 11.50 over a 1-month follow-up, although AE participants also decreased slightly from 11.07 to 10.99 days, F(1,60) < 1, ns. Participants in the MET condition decreased their largest number of heavy drinking days from 8.36 drinks to 7.43 drinks, as compared with 7.80 drinks to 6.99 drinks in the AE condition, F(1,60) < 1, ns.

An ANCOVA on the Taking Steps to Reduce Drinking measure (TS), controlling for baseline TS and for baseline motivation, showed a marginal main effect of the intervention [F(1,59) = 3.70, P = 0.06], such that controlling for baseline TS, those in the MET condition were more likely to rate themselves as having taken action to reduce their drinking and had a desire not to ‘go back’ to previous drinking patterns. As this measure seemed to show the largest response to the intervention, we chose to examine moderation of drinking reductions in the context of the TS measure.

Moderation of effects on drinking reductions

The next step in our analysis was to test our putative moderators of intervention effects on behavior change (taking steps to reduce drinking; TS). In each of the following analyses, the main effect of the moderator (median split for continuous moderators) and the intervention × moderator interaction were included in the ANCOVA on the TS measure, controlling for baseline TS and for baseline motivation.

DRD4 genotype

The intervention × DRD4 interaction was significant, F(1,5 7) = 6.44, P = 0.01. As can be seen in Fig. 1, DRD4 S individuals responded more favorably to the MET condition, although DRD4 L individuals actually responded slightly more favorably to the AE condition. Post hoc pair-wise comparisons between conditions at posttest (controlling for baseline TS) confirmed that DRD4 S participants in the MET condition had taken more steps toward changing their drinking than DRD4 L individuals in the MET condition (P = 0.001). None of the other comparisons were significant.

Figure 1
Intervention effects by DRD4 VNTR genotype in the alcohol education (AE) control and motivational enhancement therapy (MET) conditions. (a) DRD4 S individuals. (b) DRD4 L individuals

Impulsivity (IMPSS)

The intervention × IMPSS interaction was significant, F(1,5 7) = 8.22, P < 0.01. As can be seen in Fig. 2a, in the AE condition there was no change from pretest to posttest among low IMPSS participants, although those in the MET condition increased behavior change. In contrast (see Fig. 2b), high IMPSS participants actually increased behavior change in the direction of reductions in drinking in the AE condition, but did not show any noticeable change in the MET condition. Post hoc pair-wise comparisons between conditions at posttest (controlling for base-line TS) confirmed that low IMPSS participants in the MET condition had taken more steps toward changing their drinking than any other group (P-values for comparisons ranged from 0.04 to 0.001), but that the three other groups did not significantly differ from one another. In other words, high impulsivity participants—regardless of intervention—and low impulsivity participants in the AE control had all taken fewer steps to change their drinking.

Figure 2
Intervention effects by level of impulsivity/sensation-seeking in the alcohol education (AE) control and motivational enhancement therapy (MET) conditions. (a) Low impulsivity/ sensation seeking. (b) High impulsivity/sensation seeking

Novelty seeking (NS)

The intervention × NS interaction was significant, F(1,57) = 4.01, P = 0.05. The pattern of means was identical to the effects for IMPSS, such that high NS participants responded positively to the AE condition and not to the MET, although low NS participants responded to the MET but not the AE condition [1].

[1] Please note that no significant correlation emerged between the DRD4 VNTR and impulsivity (r = 0.10, P = 0.42) and between the DRD4 VNTR and novelty-seeking (r = 0.01, P = 0.96). However, unsurprisingly, there was a substantial correlation between impulsivity and novelty-seeking (r = 0.54, P < 0.001). Because of multi-collinearity, both variables could not be included in one model. We therefore ran two models, one with impulsivity as a covariate in addition to gender and race, and one with novelty-seeking as a covariate in addition to gender and race. As 86% of our sample was Caucasian, to include race as a covariate, we had to re-categorize race as Caucasian versus non-Caucasian. In the analysis including impulsivity, race, and gender as covariates, the gene × treatment interaction was still significant, F(1,54) = 7.09, P = 0.01. In the analysis including novelty-seeking, race, and gender as covariates, the gene × treatment interaction was also still significant, F(1,54) = 7.66, P < 0.01. Notably, inclusion of these covariates did not alter the presented findings.

Manipulation checks

Immediately following the intervention, participants were asked for their feedback on the intervention. There were two classes of manipulation checks in this feedback section. As accurate empathy is one of the main tenets of MET, one set of four questions measured the participant’s evaluation of the interventionist’s empathy (e.g. ‘The person I spoke with today was easy to talk to’), rated on five-point scales ranging from 1 ‘Strongly Disagree’ to 5 ‘Strongly Agree’. The evaluation score was the mean of the four items comprising this measure. Participants in the MET condition perceived the interventionist to be significantly more empathic [M = 4.50, standard deviation (SD) = 0.81] than participants did in the AE condition [M = 3.69, SD = 0.88, t (62) = −3.82, P < 0.001]. The second class of manipulation checks involved assessing whether participants perceived the presence of the MET components. Participants were given seven components of the MET (e.g. receiving a personal feedback report, developing goals to make some changes), and were asked to answer the question ‘How useful was each of the following topics’ on a 0–5 scale, where 0 = ‘topic was not introduced’, 1 = topic was ‘not useful’ and 5 = topic was ‘very useful’, for each of the seven components. Because we were interested in whether the components had been introduced and noticed during the MET compared with the AE condition, answers were re-coded such that 0 = ‘not introduced’ and answers ranging from 1 to 5 = ‘introduced’. The dependent variable was thus the number of the MET components noticed by the participants. As expected, the MET participants reported that a significantly higher number of the MET components were introduced (M = 6.51, SD = 0.80) than AE participants (M = 2.33, SD = 2.04), t (62) = −11.35, P < 0.001.

DISCUSSION

This study is one of the first investigations of genetic and individual risk moderators of MET with an emerging adult sample. Notably, although the MET sample had slightly larger decreases in the number of heavy drinking days, drinking outcomes were not significantly different between the MET and the AE control condition. Despite similar drinking outcomes, the MET group reported themselves as being significantly more likely than the AE group to have taken action to reduce their drinking (TS). This differential movement on the TS variable is notable, as a strong clinical predictor of sustained abstinence is the endorsement of actions to reduce drinking (e.g. Carbonari & DiClemente 2000).

With respect to the investigated moderators, the proposed genetic and individual risk factors indicated that, although the MET increased behavior change during the first 30 days after the intervention, these effects were stronger among individuals who were low in impulsivity/sensation seeking, low in novelty seeking, or had the S genotype of the DRD4 VNTR polymorphism. The MET was not effective in influencing behavior change to reduce drinking among individuals who were high on impulsivity/sensation seeking, high on novelty seeking or for DRD4 L individuals.

In order to maximize the effectiveness of MET, it is critical to understand who is most likely to benefit from this intervention. In the present study, the MET only resulted in drinking reductions among emerging adults who demonstrated lower impulsivity, lower novelty seeking or had the DRD4 S genotype. High impulsivity and novelty seeking have previously been related to more severe, chronic levels of alcohol problems and it is therefore not surprising that these traits were associated with a poor response to the MET in the current study. In addition, the DRD4 L genotype has been associated with higher craving for alcohol after exposure to alcohol cues and appears to predict the effectiveness of medications that target mesocorticolimbic circuits (Hutchison et al. 2002, 2003, 2006). The present findings are also consistent with data suggesting that MET combined with placebo effectively reduces alcohol consumption in treatment-seeking adults with the S genotype (Hutchison et al. 2006). Thus, together, these factors may represent a neurobiological vulnerability that predicts a poor response to a psychosocial intervention like MET. The clinical implication of these findings is that emerging adults, who demonstrate a personality or genetic profile associated with a more chronic, potentially biologically-driven drinking pattern, may require a more pharmacologically focused intervention in order to effectively initiate and sustain drinking reductions. Although many challenges are likely to come along with using genetic factors in tailoring substance abuse treatment (Shields & Lerman 2008), this study provides important data indicating that emerging adults with specific genetic and individual personality risk factors respond better to one type of intervention over another.

Limitations

The objective of this investigation was to determine the effects of a MET on the motivation to reduce drinking and drinking outcomes in an emerging adult sample. Notably, this was a relatively homogenous, college-attending sample, and additional research is necessary to support these findings across a more diverse demographic. Moreover, the current sample size may have underpowered our genetic analyses; replication with a larger sample size would provide greater support for our findings. In addition, although reductions in quantity and frequency of drinking were in the expected direction at the 1-month follow-up, these changes were not significantly different from those of the AE control sample. Obviously, future research utilizing larger samples and longer follow-ups is necessary to replicate and extend our preliminary results.

Summary and future directions

The current work provides support for the notion that MET increases the motivation to change risky drinking behavior in an emerging adult sample. Further, we have shown that, for at least a subset of individuals, these changes in motivation appear to be translated into drinking reductions. From a larger perspective, the current work demonstrates the importance of tailoring treatment to genetic and individual personality risk factors. Although these findings arguably make designing broadly successful interventions more difficult, the more sophisticated our knowledge of individual differences in response to treatment becomes, the more likely our chances of success at developing effective treatments for the widest range of at-risk individuals.

Acknowledgements

This study was supported by grants from the Alcohol Beverage Medical Research Foundation and by the National Institute of Alcoholism and Alcohol Abuse (RO1 11473-01A1; PI: K. E. Hutchison). The authors would like to thank Angela Wooden for her assistance with participant recruitment, study management and data collection, and Lindsay Chandler for her review of the manuscript.

References

  • Anton RF, Oroszi G, O’Malley S, Couper D, Swift R, Pettinati H, Goldman D. An evaluation of mu-opioid receptor (oprm1) as a predictor of naltrexone response in the treatment of Alcohol Dependence: results from the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) study. Arch Gen Psychiatry. 2008;65:135–144. [PMC free article] [PubMed]
  • Babor TF, Higgins-Biddle JC, Sanders JB, Montero MG. Audit: The alcohol use disorders identification test: Guidelines for use in primary care (The World Health Organization) 2006.
  • Baer JS, Garrett SB, Beadnell B, Wells EA, Peterson P. Brief motivational intervention with homeless adolescents: evaluating effects on substance use and service utilization. Psychol Addict Behav. 2007;21:582–586. [PubMed]
  • Baer JS, Kivlahan DR, Blume AW, McKnight P, Marlatt GA. Brief intervention for heavy drinking college students: 4-year follow up and natural history. Am J Public Health. 2001;91:1310–1316. [PMC free article] [PubMed]
  • Baer JS, Marlatt GA, Kivlahan DR, Fromme K, Larimer ME, Williams E. An experimental test of three methods of alcohol risk reduction with young adults. J Consult Clin Psychol. 1992;60:974–979. [PubMed]
  • Barnett BP, Read JP. Mandatory alcohol intervention for alcohol-abusing college students: a systematic review. J Subst Abuse Treat. 2005;29:147–158. [PubMed]
  • Barnett NP, Murphy JG, Colby SM, Monti PM. Efficacy of a counselor vs. computer-delivered intervention with mandated college students. Addict Behav. 2007;32:2529–2548. [PMC free article] [PubMed]
  • Bauer LO, Covault J, Harel O, Das S, Gelernter J, Anton R, Kranzler HR. Variation in GABRA2 predicts drinking behavior in project MATCH subjects. Alcoholism: Clinical and Experimental Research. 2007;31:1780–1787. [PMC free article] [PubMed]
  • Benjamin J, Benjamin J, Li L, Patterson C, Greenberg BD, Murphy DL, Hamer DH. Population and familial association between the D4 dopamine receptor gene and measures of Novelty Seeking. Nat Genet. 1996;12:81–84. [PubMed]
  • Biener L, Abrams DB. The Contemplation Ladder: validation of a measure of readiness to consider smoking cessation. Health Psychol. 1991;10:360–365. [PubMed]
  • Borsari B, Carey KB. Effects of a brief motivational intervention with college student drinkers. J Consult Clin Psychol. 2000;68:728–733. [PubMed]
  • Borsari B, Carey KB. Two brief alcohol interventions for mandated college students. Psychol Addict Behav. 2005;19:296–302. [PMC free article] [PubMed]
  • Burke BL, Arkowitz H, Menchola M. The efficacy of motivational interviewing: a meta-analysis of controlled clinical trials. J Consult Clin Psychol. 2003;71:843–861. [PubMed]
  • Carbonari JP, DiClemente CC. Using transtheoretical model profiles to differentiate levels of alcohol abstinent success. J Consult Clin Psychol. 2000;68:810–817. [PubMed]
  • Chen CM, Dufour MC, Yi H-Y. Alcohol consumption among young adults ages 18–24 in the United States: results from the 2001–2002 NESARC survey. Alcohol Res Health. 2004–2005;28:269–280.
  • Cloninger CR. Neurogenetic adaptive mechanisms in alcoholism. Science. 1987;236:410–416. [PubMed]
  • Congdon E, Lesch KP, Canli T. Analysis of DRD4 and DAT polymorphisms and behavioral inhibition in healthy adults: implications for impulsivity. Am J Med Genet B Neuropsychiatr Genet. 2008;147:27–32. [PubMed]
  • Ebstein RP, Novick O, Umansky R, Priel B, Osher Y, Blaine D, Bennett ER, Nemanov L, Katz M, Belmaker RH. Dopamine D4 receptor (D4DR) exon III polymorphism associated with the human personality trait of Novelty Seeking. Nat Genet. 1996;12:78–80. [PubMed]
  • Eisenberg DT, Mackillop J, Modi M, Beauchemin J, Dang D, Lisman SA, Lum JK, Wilson DS. Examining impulsivity as an endophenotype using a behavioral approach: a DRD2 TaqI A and DRD4 48-bp VNTR association study. Behav Brain Funct. 2007;3:2. [PMC free article] [PubMed]
  • Freeman B, Powell J, Ball D, Hill L, Craig I, Plomin R. DNA by mail: An inexpensive and noninvasive method for collecting DNA samples from widely dispersed populations. Behavioural Genetics. 1997;27:251–257. [PubMed]
  • Guo G, Wilhelmsen K, Hamilton N. Gene-lifecourse interaction for alcohol consumption in adolescence and young adulthood: five monoamine genes. Am J Med Genet. 2007;144:417–423. [PubMed]
  • Helstrom A, Hutchison KE, Bryan A. Motivational enhancement therapy of high risk adolescent smokers. Addict Behav. 2007;32:2404–2410. [PMC free article] [PubMed]
  • Hingson R, Heeren T, Winter M, Wechsler H. Magnitude of alcohol-related mortality and morbidity among U.S. college students ages 18–24: changes from 1998 to 2001. Annu Rev Public Health. 2005;26:259–279. [PubMed]
  • Hopfer CJ, Timberlake D, Haberstick B, Lessem JM, Ehringer MA, Smolen A, Hewitt JK. Genetic influences on quantity of alcohol consumed by adolescents and young adults. Drug Alcohol Depend. 2005;78:187–193. [PubMed]
  • Hutchison KE, Haughey HM, Niculescu M, Schact J, Kaiser A, Stitzel J, Horton WJ, Filbey FM. The incentive salience of alcohol: translating the effects of genetic variant in CNR1. Arch Gen Psychiatry. 2008;65:841–850. [PMC free article] [PubMed]
  • Hutchison KE, McGeary J, Smolen A, Bryan A, Swift RM. The DRD4 VNTR polymorphism moderates craving after alcohol consumption. Health Psychol. 2002;21:139–146. [PubMed]
  • Hutchison KE, Ray L, Sandman E, Rutter MC, Peters A, Davidson D, Swift R. The effect of olanzapine on craving and alcohol consumption. Neuropsychopharmacology. 2006;31:1310–1317. [PubMed]
  • Hutchison KE, Wooden A, Swift RM, Smolen A, McGeary J, Adler L, Paris L. Olanzapine reduces craving for alcohol: a DRD4 VNTR polymorphism by pharmacotherapy interaction. Neuropsychopharmacology. 2003;28:1882–1888. [PubMed]
  • Isenhart CE. Motivational subtypes in an inpatient sample of substance abusers. Addict Behav. 1994;19:463–475. [PubMed]
  • Jessor R, Van D, en Bos J, Vanderryn J, Costa FM, Turbin MS. Protective factors in adolescent problem behavior: moderator effects and developmental change. Dev Psychol. 1995;31:923–933.
  • Kalivas PW, Volkow ND. The neural basis of addiction: a pathology of motivation and choice. Am J Psychiatry. 2005;162:1403–1413. [PubMed]
  • Lau-Barraco C, Dunn ME. Evaluation of a single-session expectancy challenge intervention to reduce alcohol use among college students. Psychol Addict Behav. 2008;22:168–175. [PubMed]
  • Laucht M, Becker K, Blomeyer D, Schmidt MH. Novelty seeking involved in mediating the association between the dopamine D4 receptor gene exon III polymorphism and heavy drinking in male adolescents: results from a high-risk communitysample. Biol Psychiatry. 2007;61:87–92. [PubMed]
  • Lench N, Stanier P, Williamson R. Simple non invasive method to obtain DNA for gene analysis. Lancet. 1988;1(8599):1356–1358. [PubMed]
  • Lerman C, Caporaso N, Main D, Audrain J, Boyd NR, Bowman ED, Shields PG. Depression and self-medication with nicotine: the modifying influence of the dopamine D4 receptor gene. Health Psychol. 1998;17:56–62. [PubMed]
  • Lichter JB, Barr CL, Kennedy JL, Vantol HH, Kidd KK, Livak KJ. A hypervariable segment in the human dopamine receptor D4(DRD4) gene. Human Molecular Genetics. 1993;2:767–773. [PubMed]
  • Lukasiewiez M, Neveu X, Blecha L, Falissard B, Reynaud M, Gasquet I. Pathways to substance-related disorder: a structural model approach exploring the influence of temperament, character, and childhood adversity in a national cohort of prisoners. Alcohol Alcohol. 2008;43:287–295. [PubMed]
  • McGeary JE, Esposito-Smythers C, Spirito A, Monti PM. Associations of the dopamine D4 receptor gene VNTR polymorphism with drug use in adolescent psychiatric patients. Pharmacol Biochem Be. 2007;86:401–406. [PMC free article] [PubMed]
  • MacKillop J, Mattson RE, Anderson MacKillop EJ, Castelda BA, Donovick PJ. Multidimensional assessment of impulsivity in undergraduate hazardous drinkers and controls. J Stud Alcohol Drugs. 2007;68:785–788. [PubMed]
  • Marlatt GA, Baer JS, Kivlahan DR, Dimeff LA, Larimer ME, Quigley LA. Screening and brief intervention for high-risk college student drinkers: results from a 2-year follow-up assessment. J Consult Clin Psychol. 1998;66:604–615. [PubMed]
  • Miller WR, Munoz RF. Controlling Your Drinking. New York: Guilford Press; 2005.
  • Miller WR, Rollnick S. Motivational Interviewing: Preparing People for Change. 2nd edn. New New York: Guilford Press; 2002.
  • Miller WR, Tonigan JS. Assessing drinkers’ motivations for change: the Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES) Psychol Addict Behav. 1996;10:81–89.
  • Miller WR, Zweben A, DiClemente CC, Rychtarik RG. Motivational Enhancement Therapy Manual: A Clinical Research Guide for Therapists Treating Individuals with Alcohol Abuse and Dependence. New Rockville, MD: NIAAA/NIH; 1999.
  • Monti PM, Barnett NP, Colby SM, Gwaltney CJ, Spirito A, Rohsenow DJ, Woolard R. Motivational interviewing versus feedback only in emergency care for young adult problem drinking. Addiction. 2007;102:1234–1243. [PubMed]
  • Monti PM, Colby SM, Barnett NP, Spirito A, Rohsenow DJ, Myers MG, Woolard R, Lewander W. Brief intervention for harm reduction with alcohol-positive older adolescents in a hospital emergency department. J Consult Clin Psychol. 1999;67:989–994. [PubMed]
  • Noble EP, Ozkaragoz TZ, Ritchie TL, Zhang X, Belin TR, Sparkes RS. D2 and D4 dopamine receptor polymorphisms and personality. Am J Med Genet. 1998;81:257–267. [PubMed]
  • O’Malley PM, Johnston LD. Epidemiology of alcohol and other drug use among American college students. J Stud Alcohol Suppl. 2002;14:23–29. [PubMed]
  • Project MATCH Research Group. Matching patients with alcohol disorders to treatments: clinical implications from project MATCH. J Ment Health. 1998;7:589–602.
  • Project MATCH Research Group. Matching alcoholism treatments to client heterogeneity: project MATCH Posttreatment drinking outcomes. J Stud Alcohol. 1997;58:7–29. [PubMed]
  • Ray LA, Bryan A, MacKillop J, McGeary J, Hesterberg K, Hutchison KE. The dopamine D(4) Receptor (DRD4) gene exon III polymorphism, problematic alcohol use and novelty seeking: direct and mediated genetic effects. Addict Biol. 2009;14:238–244. [PMC free article] [PubMed]
  • Sander T, Harms H, Dufeu P, Kuhn S, Rommelspacher H, Schmidt LG. Dopamine D4 receptor exon III alleles and variation of novelty seeking in alcoholics. American Journal of Medical Genetics. 1997;74:483–487. [PubMed]
  • Schulenberg JE, Maggs JL. A developmental perspective on alcohol use and heavy drinking during adolescence and the transition to young adulthood. J Stud Alcohol Suppl. 2002;14:54–70. [PubMed]
  • Shields AE, Lerman CV. Anticipating clinical integration of pharmacogenetic treatment strategies for addiction: are primary care physicians ready? Clin Pharmacol Ther. 2008;83:635–639. [PubMed]
  • Skowronek MH, Laucht M, Hohm E, Becker K, Schmidt MH. Interaction between the dopamine D4 receptor and the serotonin transporter promoter polymorphisms in alcohol and tobacco use among 15-year-olds. Neurogenetics. 2006;7:239–246. [PubMed]
  • Sobell LC, Sobell MB. Time-line follow-back: a technique for assessing self-reported alcohol consumption. In: Litten RZ, Allen JP, editors. New Measuring Alcohol Consumption. Totowa, NJ: Humana Press; 1992. pp. 73–98.
  • Stewart SH, Conrod PJ, Marlatt GA, Comeau MN, Thush C, Krank M. New developments in prevention and early intervention for alcohol abuse in youths. Alcoholism: Clinical and Experimental Research. 2005;29:278–286. [PubMed]
  • Verdejo-Garcia A, Lawrence AJ, Clark L. Impulsivity as a vulnerability marker for substance-use disorder: review of findings from high-risk research, problem gamblers and genetic association studies. Neurosci Biobehav Rev. 2008;32:777–810. [PubMed]
  • Vermont LV, Feldstein Ewing SW, Claus E, Taborsky-Barba S, Hutchison KE. Impulsivity as a risk factor for the initiation and escalation of alcohol abuse in late adolescents. Alcoholism: Clinical and Experimental Research. 2008;S32:113A.
  • White HR, Labouvie EW. Towards the assessment of adolescent problem drinking. J Stud Alcohol. 1989;50:30–37. [PubMed]
  • Zuckerman M. Behavioral Expressions and Biosocial Biases of Sensation Seeking. New New York, NY: Cambridge University Press; 1994.
  • Zuckerman M, Kuhlman DM. Personality and risk-taking: common biosocial factors. J Pers. 2000;68:999–1029. [PubMed]
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