R. McD. Young

D2 dopamine receptor (DRD2) polymorphism is associated with severity of alcohol dependence

The A(1) allele of the D(2) dopamine receptor (DRD2) gene has been associated with alcohol dependence. However, the expression of this allele risk on the severity of drinking behavior in patients with alcohol dependence has not been systematically explored. The present study examines the association between DRD2 A(1)(+) (A(1)/A(1) and A(1)/A(2) genotypes) and A(1)- (A(2)/A(2) genotype) allele status and key drinking parameters in alcohol-dependent patients. A sample of Caucasian adults was recruited from an alcohol detoxification unit. A clinical interview and the Alcohol Dependence Scale (ADS) questionnaire provided data on consumption, dependence, chronology of drinking and prior detoxification. A(1)(+) allele compared to A(1)- allele patients consumed higher quantities of alcohol, commenced problem drinking at an earlier age, experienced a shorter latency between first introduction to alcohol to the onset of problem drinking and had higher ADS scores. Moreover, A(1)(+) allele patients had more detoxification attempts than their A(1)- allele counterparts. In sum, alcohol-dependent patients with the DRD2 A(1) allele compared to patients without this allele are characterized by greater severity of their disorder across a range of problem drinking indices. The implications of these findings are discussed.

A prospective study of alcohol expectancies and self-efficacy as predictors of young adolescent alcohol misuse.

AIMS To test the relative contribution of two key Social Learning Theory constructs, alcohol expectancies (AEs) and drinking refusal self-efficacy (DRSE), in predicting early adolescent drinking behavior and examine the possible mediational role of DRSE over AE. METHODS High school students (N = 192, mean age 14) were administered measures assessing AE (Drinking Expectancy Questionnaire--Adolescent version; DEQ-A), DRSE (Drinking Refusal Self-Efficacy Questionnaire--Revised Adolescent version; DRSEQ-RA) and indices of alcohol consumption and problem drinking. Age, gender, peer drinking, tobacco use and positive and negative behavioral characteristics were included in the statistical models as known predictors of alcohol misuse. Subjects were followed up at 12 months, with 88.5% retention. RESULTS Initial confirmatory factor analyses verified factor structures of the DEQ-A and DRSEQ-RA. Prospective structural models controlling for Time 1 drinking behavior, age, gender, peer alcohol use, tobacco use and behavior problems identified that DRSE but not AE was associated with problem drinking 12-month post-initial assessment. DRSE mediated AE in predicting problem drinking. CONCLUSION Results suggest that DRSE is a more salient cognitive construct than AE in early adolescence alcohol use. In this age group, prevention and treatment strategies that build refusal self-efficacy may be more effective than strategies that challenge AEs.

Work-place screening of mine employees using the alcohol use disorders identification test (AUDIT) and alcohol breathalyzation

Although public health campaigns focusing on alcohol in the work-place are receiving increasing attention, there is little empirical evidence regarding the use of screening. In this work-place study, 152 mining personnel (67% of the work-force) completed a self report screen using the Alcohol Use Disorders Identification Test (AUDIT). One hundred and thirty-three of these (58.5% of the work-force) also consented to be breathalysed and one (0.75%) recorded a BAC just over threshold for detection. Forty-eight males (37.7% of the male work-force) recorded AUDIT scores of eight or more consistent with hazardous alcohol use and one female registered a cumulative score above the female cut-off level for hazardous alcohol use. Eighty males (67% of the work-force), recorded binge drinking at least monthly and 81 males recorded a cumulative AUDIT score of less than eight; however, on item analysis, 64 (83%) of these recorded binge drinking at least sometimes. There is substantial hazardous alcohol use in this sample work group and younger males had higher alcohol consumption, more adverse consequences and higher total AUDIT scores identifying them as particularly at risk. The Cronbach & AUDIT was 0.72, confirming adequate internal consistency.

The application of machine learning techniques as an adjunct to clinical decision making in alcohol dependence treatment

With few exceptions, research in the addictive sciences has relied on linear statistics and methodologies. Addiction involves a complex array of nonlinear behaviors. This study applies two machine learning techniques, Bayesian and decision tree classifiers, in the assessment of outcome of an alcohol dependence treatment program. These nonlinear approaches are compared to a standard linear analysis. Seventy-three alcohol-dependent subjects undertaking a 12-week cognitive-behavioral therapy (CBT) program and 66 subjects undertaking an identical program but also prescribed the relapse prevention agent Acamprosate were employed in this study. Demographic, alcohol use, dependence severity, craving, health-related quality of life, and psychological measures at baseline were used to predict abstinence at 12 weeks. Decision trees had a 77% predictive accuracy across both data sets, Bayesian networks 73%, and discriminant analysis 42%. Combined with clinical experience, machine learning approaches offer promise in understanding the complex relationships that underlie treatment outcome for abstinence-based alcohol treatment programs.

Psychological and psychosocial functioning in patients with alcohol-related liver disease pre- and post-liver transplantation

35th Annual Scientific Meeting of the Research Society on Alcoholism, June 23-27. San Francisco, California