The Brief Addiction Science Information Source (BASIS)

The DRAM, Vol. 8(6) – Brain fitness games and alcohol treatment

Recent studies have provided evidence that cognitive impairments interfere with the treatment processes of individuals with alcohol use disorder (Blume, Schmaling, & Marlatt, 2005; Rinn, Desai, Rosenblatt, & Gastfriend, 2002; Teichner, Horner, & Harvey, 2001). Cognitive remediation therapy (CRT) involves a battery of tasks designed to improve attention, working memory, cognitive flexibility and other neurocognitive abilities. This week’s DRAM reviews a study that attempts to determine whether computer-based cognitive remediation (CR), in addition to a conventional inpatient treatment for alcohol dependence, produces cognitive improvement and improves treatment outcomes (Rupp, Kemmler, Kurz, Hinterhuber, & Fleischhacker, 2012).

Methods

• Forty-one individuals in treatment for alcohol-dependence who exhibited some level of cognitive deficit participated in the study.
  • Half (n=21) received treatment as usual [Controls].
  • Half (n=20) received, in addition to standard treatment, 12 individual training sessions using CR [CR group].
• Both before (T1) and after (T2) the four-week treatment period, researchers administered a battery of cognitive tests, including measures of attention, inhibition, and working memory.
• In addition, both at times T1 and T2, researchers assessed participants' psychological well-being and alcohol craving.
• The authors compared the two groups and their performance before and after treatment using t tests, chi-square test, Fisher's exact test, MANOVA and ANOVA.

Results

• Individuals who participated in the CR treatment sessions showed significant overall improvements from T1 to T2 in measures of attention (F(8,28)=3.23, p=0.01) and memory (F(5,31)=3.09, p<0.05) compared to those who did not. Figure 1 displays group scores on the specific tasks that helped account for these effects, working memory and verbal memory recall.
• The control and CR groups only differed significantly across time on 7 of the 13 specific attention and memory tasks.
• Individuals who participated in the CR treatment sessions also showed significant improvements from T1 to T2 in severity of psychological distress (F(1,35)=6.23, p<0.05) compared to those who did not.

Figure 1: Changes to Working Memory and Verbal Memory Recall from T1 to T2 in Control Group [CONTROL] and Cognitive Remediation Group [CR] (adapted from Rupp et al., 2012).

Limitations

• This study had a sample size under 50 and a duration of only four weeks. A larger or longer study might allow researchers to statistically detect more benefits.
• The control group patients were not exposed to a computer during the length of the study. Improvements in the treatment group might have been due to a placebo effect induced by the additional time and attention given.
• Prospective participants were excluded if they had a history of any other mental disorder, a history of substance dependence other than alcohol or nicotine, or any of a list of other mitigating factors. Thus, the sample may not be representative of the average clinical practice's population.

Conclusions

Worldwide, there have been efforts to study the potential beneficial effects of computer and video games. The report highlighted here can be thought of in that context, as work suggesting that the simple computer games described in the study can assist in the healing process and help people recover. The results suggest that computer-based cognitive remediation therapy may be a worthwhile element to add to an existing alcohol dependence treatment program. In addition, the results support the hypothesis that cognitive enhancement through CR can improve the overall psychological health of individuals undergoing treatment.

- Matthew Tom

References

Blume, A. W., Schmaling, K. B., & Marlatt, G. A. (2005). Memory, executive cognitive function, and readiness to change drinking behavior. Addictive Behaviors, 30(2), 301-314.

Rinn, W., Desai, N., Rosenblatt, H., & Gastfriend, D. R. (2002). Addiction denial and cognitive dysfunction: a preliminary investigation. Journal of Neuropsychiatry and Clinical Neuroscience, 14(1), 52-57.

Rupp, C. I., Kemmler, G., Kurz, M., Hinterhuber, H., & Fleischhacker, W. W. (2012). Cognitive remediation therapy during treatment for alcohol dependence. Journal of Studies on Alcohol and Drugs, 73(4), 625-634.

Teichner, G., Horner, M. D., & Harvey, R. T. (2001). Neuropsychological predictors of the attainment of treatment objectives in substance abuse patients. International Journal of Neuroscience, 106(3-4), 253-263.

The DRAM, Vol. 8(5) - Virtual expectations: The effect of manipulated Facebook profiles on drinking norms and cognitions in adolescents

With over 900 million active users worldwide (Facebook.com, 2012), Facebook is the dominant social networking site in the world. With the growing influence of Facebook, it is important to understand how content on social networking sites affects adolescents’ growth and behavior. This week’s DRAM reviews a study exploring the effects of exposure to Facebook profiles containing alcohol cues on adolescents’ thoughts and beliefs regarding alcohol use (Litt & Stock, 2011).

Methods

• Researchers recruited 189 adolescents between the ages of 13 and 15 from private schools, sports teams, and church youth groups.
• Participants believed they had 40 minutes to view the Facebook profiles of four high school students and rate the users on several personality traits.
• Researchers randomized participants into two experimental groups:
  • Alcohol condition: 3 of the 4 viewed fabricated profiles had textual references to alcohol (e.g., “You were so drunk last night!”).
  • Non-alcohol condition: 3 of the 4 viewed fabricated profiles had no mention of alcohol and had textual references to non-drinking activities (e.g., “I had fun at the movie last night”).
  • After the 40 minutes, participants filled out a questionnaire assessing five outcomes:
    • Willingness to use alcohol ;
    • Affective attitudes about drinking (i.e., the benefits the participant believes drinking would have);
    • Perceived vulnerability (i.e., how vulnerable the participant believes he or she is to the negative aspects of drinking);
    • User prototypes (i.e., how similar the participant believes he or she is to an older adolescent who drinks).
    • Perceived norms (i.e., how often and how much the participant believes older adolescents drink).

Results

• Researchers found that the type of profile participants viewed had a significant effect on all outcome measures. Participants in the alcohol condition reported greater willingness to drink, greater similarity to drinkers, higher favorability and fewer negative consequences of drinking, and higher estimates of older adolescent drinking, Fs (1, 189) = 4.22 - 7.89, p < .05.
• As Figure 1 shows, researchers also found that participants’ perceptions and beliefs about alcohol partially mediated the relationship between condition and willingness to drink. In other words, participants who viewed alcohol-related user profiles had more favorable views toward alcohol and found its use more normative, which in turn increased their reported willingness to drink

Figure 1: Schematic of the multiple mediation model (from Litt & Stockman, 2011; reproduced with permission)

Limitations

• Facebook profiles only showed textual references to alcohol; future studies might include photographs etc.
• The study assumes middle school-aged children would be Facebook friends with high school-aged students two years older than themselves.
• While other adolescents previously checked the profiles for authenticity, there was no measure of whether participants accepted the profiles as genuine.

Conclusions

This study shows that experimentally manipulated Facebook profiles can increase young adolescents’ willingness to drink, as well as create a more favorable view of alcohol and drinking behavior. Interestingly, only a short-term exposure to these influences in strangers’ profiles elicited this effect. Future studies might explore whether long-term exposure to peers’ drinking behaviors has a similar, or even greater effect. Studies like this might eventually result in stricter or more comprehensive parental controls over social networking sites like Facebook.

-Daniel Tao

What do you think? Please use the comment link below to provide feedback on this article.  

References

Facebook.com (2012). Key Facts - Facebook Pressroom. Retrieved from http://newsroom.fb.com/content/default.aspx?NewsAreaId=22

Litt, D.M., Stock, M.L. (2011). Adolescent alcohol-related risk cognitions: The roles of social norms and social networking sites. Psychology of Addictive Behaviors, 25(4): 708-713. DOI: 10.1037/a0024226.

The DRAM, Vol. 8(4) - Glass half empty or half full? Internalizing and externalizing pathways to risky alcohol use in DUI offenders

Research continues to investigate the influence of mental health on risky drinking and DUI offense. Evidence suggests that people with “internalizing” disorders tend to drink to cope with negative emotions, whereas those with “externalizing” disorders are more likely to drink in response to positive situations.
This week’s DRAM reviews a study that examined the influence of externalizing and internalizing disorders on first time DUI offenders’ risky drinking and perceived ability to control their drinking in different situations (Schlauch, O’Malley, Rounsaville, & Ball, 2012).

Methods

• 292 first-time DUI offenders completed questionnaires about internalizing and externalizing disorders, as well as coping self-efficacy (i.e., their perceived ability to control their drinking in different high-risk situations).
  • Internalizing disorders included depression, anxiety and other disorders of negative emotionality. Externalizing disorders included conduct disorder, antisocial personality and other disorders of impulse control.
• The coping self-efficacy measured the participant’s perceived ability to cope without drinking in negative and positive situations.
  • Negative situations, i.e.: “If I felt that I had let myself down”
  • Positive situations, i.e.:  “If I were enjoying myself at a party and wanted to feel even better”
• Researchers assessed problematic alcohol use with the Time Line Follow-Back method (TLFB: Sobell & Sobell, 1992), as well as the Addiction Severity Index (ASI: McClellan, Luborsky, O’Brien, & Woody, 1980). For analyses, they calculated the alcohol use score on the ASI, as well as how many days in the past 3 months participants drank heavily (i.e., >3 drinks for women; >4 drinks for men).
• Researchers used structural equation modeling to assess the direct and indirect relationships between variables.

Results

Table 1: Summary of Direct and Indirect Effects of Behavioral Dimensions, Expectations, and Reported  Problematic Alcohol Use

*= p < .01; **= p < .05; Positive Situations= perceived ability to cope without drinking in positive situations; Negative Situations= perceived ability to cope without drinking in negative situations.
Note: Internalizing, externalizing, and problematic alcohol use were all latent variables- composites constructed from multiple measures.

• As Table 1 shows, within the full model, the relationship between internalizing disorders and perceived ability to cope without drinking in negative situations was significant. There was no significant relationship between internalizing disorders and coping efficacy in positive situations or problematic alcohol use.
• In the full model, externalizing disorders were significantly related to coping self-efficacy in both positive and negative situations, but not problematic alcohol use.
• Despite the absence of direct relationships between internalizing and externalizing disorders and problematic alcohol use, both dimensions related indirectly to problematic alcohol use through coping self-efficacy.
• Participants with high scores on internalizing were less able to cope without drinking in negative situations, which, for these participants, predicted problematic alcohol use.
• Participants with high scores on externalizing were less able to cope without drinking in positive situations, which, for these participants, predicted problematic alcohol use.

Limitations

• This was a correlational study, and did not assess causality between the variables of interest. The model did not allow for the effects of risky alcohol use on behavior; for example, problematic alcohol use could potentially lead to or exacerbate anxious or conduct-disordered behavior.
• Although the Time Line Follow-Back method is validated and widely used, retrospective self-report might differ from actual drinking behavior.

Discussion

Despite evidence that psychiatric  disorders are linked to DUI offense (Shaffer et al., 2007), we still do not know much about different pathways that might lead people to offend. This study suggests that DUI offenders with different types of disorder (i.e., internalizing vs. externalizing) might drink and drink to excess for different reasons. Future research is needed to determine how these different drinking pathways might influence DUI recidivism and severity.

-Kat Belkin

What do you think? Please use the comment link below to provide feedback on this article.

References

McClellan, T.A., Luborsky, L., Woody, G.E., & O’Brien, C.P. (1980). An improved diagnostic evaluation instrument for substance abuse patients: The Addiction Severity Index.  The Journal of Nervous and Mental Disease, 168(1), 26-33.

Schlauch, R.C., O’Malley, S.S.,  Rounsaville, B.J., Ball, S.A. (2012). Internalizing and externalizing dimensions and alcohol use in first time DWI offenders: Indirect effects through coping self-efficacy. Psychology of Addictive Behaviors, 26(1), 133-139.

Shaffer, H.J., Nelson, S.E., LaPlante, D.A., LaBrie, R.A., Albanese, M., & Caro, G. (2007). The epidemiology of psychiatric disorders among repeat DUI offenders accepting a treatment-sentencing option. Journal of Consulting and Clinical Psychology, 75(5), 795-804.

Sobell, M.B., Sobell, L.C. (1992). Time line follow-back: A technique for assessing self-reported ethanol consumption. In J. Allen & R. Litten (Eds.), Measuring alcohol consumption: Psychosocial and biochemical methods (41-72). Totowa, NJ: Hummer Press.

The DRAM, Vol. 8(3) - Express lane to drinking problems: Rapid development of alcohol dependence in individuals with anxiety disorders

Past studies consistently have shown that alcohol disorders and anxiety disorders co-occur more frequently than can be explained by chance alone (Boyd et al., 1984; Shaffer et al., 2007). Neurobiological theories of dependence suggest that individuals who have anxiety disorders are especially vulnerable to developing alcohol dependence. This week, the DRAM reviews a study that compared the onset and development of alcohol dependence among individuals with and without anxiety disorders (Kushner et al., 2011).

Methods

• The researchers recruited seventy-eight individuals who had alcohol dependence from an adult inpatient chemical dependency treatment program and assessed them for presence of anxiety disorders. About 54% (n = 42) of the sample met criteria for an anxiety disorder.
• The researchers used the Structured Clinical Interview for DSM-IV (SCID: First et al., 1989), a semi-structured diagnostic interview, to determine the past 4-month presence of the following anxiety disorders:
  • panic disorder (with or without agoraphobia);
  • agoraphobia without panic;
  • social phobia;
  • obsessive–compulsive disorder;
  • generalized anxiety disorder.
• The researchers measured time elapsed between pre-dependence alcohol milestones (i.e., first drink, first regular drinking, first episode of drunkenness, first time regularly getting drunk) and alcohol dependence milestones (i.e., age first met criteria for alcohol dependence, age at most severe symptoms of alcohol dependence).

Results

• The mean age at which participants who had an anxiety disorder reported their alcohol dependence was at its worst (M = 31.4, SD = 10.99) was about 6 years younger than those who never had an anxiety disorder (M = 37.86, SD = 11.91; F(1,74) = 6.05, p < .05).
• As Table 1 shows, individuals who had an anxiety disorder transitioned from regular drinking and from their first episode of drunkenness to alcohol dependence onset significantly faster than did those who did not have an anxiety disorder, (F(1,64) = 7.36, p < .01; F(1,74) =  4.08, p < .05).

Table 1: Time in Years between Pre-Dependence Alcohol Use Milestones and Alcohol Dependence


*F-test indicates means significantly different, p < .05; ** F-test indicates means significantly different, p < .01.

Limitations

• The study did not measure whether total amount of alcohol consumed between the various milestones measured differed between those with and without an anxiety disorder. If drinking quantity varied by anxiety disorder status, it is possible that differences in drinking quantity, not anxiety, affected time to dependence.
• The SCID only measured presence of anxiety in the past 4 months, making it difficult to assess whether participants’ anxiety preceded their alcohol dependence or was a potential consequence of that dependence.
• The SCID used retrospective self-report of disorder onset, which is vulnerable to memory errors and biases.

Conclusions
The researchers found that anxiety-disordered individuals transitioned more quickly from regular drinking and first drunken episode to being dependent on alcohol than individuals who did not have anxiety disorders. Neurobiological theories of alcohol dependence suggest that it results from decreasing release of dopamine over extended periods of alcohol use (Koob & LeMoal, 2008). People who have anxiety disorders might be particularly vulnerable to this cycle, because their dopamine-stress response already is dysregulated, effectively giving them a “head start” in developing symptoms of dependence. This dysregulation might explain why fewer instances of interaction with alcohol are associated with risk for dependence among those who have experienced anxiety disorders.

-Kat Belkin

What do you think?  Please use the comment link below to provide feedback on this article.

References

First, M., Spitzer, R., Gibbon, M., & Williams, J. (1989). Structural Clinical Interview for Axis-I DSM-IV Disorders, Patient Edition (SCID-I/P Version 2.0). New York, NY: New York State Psychiatric Institute.

Koob, G. F., & Le Moal, M. (2008). Addiction and the brain antireward system. Annual Review of Psychology, 59, 29–53.

Kushner, M.G., Maurer, E., Menary, K., Thuras, P. (2011).  “Vulnerability to the rapid (“telescoped”) development of alcohol dependence in individuals with anxiety disorder.” Journal of Studies of Alcohol and Drugs, 72(6), 1019-27.

The DRAM, Vol. 8(2) - Happy Birthday to You: Heavy Drinking among College Students

For many people, the college years are a time of increased risk for binge drinking and other risky drinking behavior (The DRAM, Vol. 7(2); The DRAM, Vol. 5(3); The DRAM, Vol. 6(3)). Researchers have determined that some events, like holidays, can dramatically increase such risk (Addiction and the Humanities, Vol. 3(9); The DRAM, Vol. 6(2)) among college students. This week, The DRAM reviews research that examined how the event of turning 21 years old affects risky drinking behavior among college students (Neighbors et al., 2011) compared to other special events and baseline risky drinking behavior (i.e., college student drinking on a typical weekend).

Method

• Between February 2008 and August 2008, the researchers invited, four days after their 21^st birthday, 2,113 undergraduates from a large northwestern university in the United Statesto participate in a survey.
  • Respondents included 1,124 undergraduates (55% female; 62% White; 53% response rate).
• A 45-minute survey assessed past 90-day alcohol use using the Timeline Followback calendar. Researchers calculated daily Blood Alcohol Content (BAC) from information provided about weight, amount consumed, and time spent consuming.

Results

• On average, respondents reported drinking 10 (SD=12.0) days during the past three months, consuming an average of 4.4 (SD=3.4) drinks per drinking day, and reaching an estimated BAC of 0.1 on drinking days.
• Using regression techniques that accommodate large numbers of zeros (i.e., non-drinking days and 0.0 BACs) in the model, the authors investigated the association between special events and drinking participation.
• As Table 1 shows, special events, such as an individual’s 21^st birthday, and certain holidays change students’ risk for engaging in alcohol consumption. For instance, the experience of a 21^st birthday is associated with dramatically larger BAC levels and drinking participation.

Table 1. Means (95% Confidence Intervals) for BAC and Proportions of Respondents Drinking, by Event (adapted from Neighbors et al., 2011)

Predictor	BAC X 100	Drinking
Intercept	8.2 (7.8, 8.7)	0.18 (0.17, 0.19)
Women	8.0 (7.4, 9.2)	0.14 (0.12, 0.16)
Weekday	7.1 (3.7, 7.5)	0.09 (0.08, 0.10)
21st Birthday	18.6 (17.2, 19.8)	0.90 (0.87, 0.93)
New Year’s Eve	12.6 (10.6, 14.9)	0.66 (0.50, 0.74)
New Year’s Day	12.2 (10.2, 14.9)	0.37 (0.28, 0.48)
Super Bowl	8.5 (6.1, 11.1)	0.08 (0.05, 0.12)
Fat Tuesday	9.6 (7.4, 11.4)	0.09 (0.07, 0.14)
Valentine’s Day	7.6 (6.4, 8.5)	0.42 (0.35, 0.52)
President’s Day	6.2 (4.4, 8.5)	0.07 (0.04, 0.10)
St. Patrick’s Day	8.6 (6.9, 9.8)	0.17 (0.12, 0.21)
Spring Break (maximum)	10.7 (9.7, 11.7)	0.75 (0.68, 0.82)
Cinco de Mayo	10.5 (9.2, 12.2)	0.16 (0.13, 0.21)
Memorial Day	6.2 (4.7, 7.7)	0.09 (0.07, 0.13)
Graduation	9.3 (8.5, 10.4)	0.28 (0.23, 0.31)
Fourth of July	10.1 (9.0, 11.4)	0.55 (0.49, 0.67)

Note. Bold values indicate p<.05.

Limitations

• The study has a relatively low response rate.
• The findings are likely to be culturally specific; international researchers might consider other holidays and events that are likely to raise risky drinking behavior among college students.
• Although the Timeline Followback calendar methodology is widely used and well-tested, retrospective self-reported drinking behavior might differ from actual drinking behavior.

Discussion

The results suggest that there are predictable periods of elevated risky drinking among college students, an age cohort that already experiences elevated risk over other cohorts. Interestingly, whereas some periods are consistent with conventional wisdom, others (e.g., St. Patrick’s Day) do not appear to elevate drinking. These findings are useful because they suggest important events that administrators and others might target for enhanced prevention and intervention attempts. This research yields practical suggestions that might improve the health and well-being of at-risk college students.

-Debi LaPlante

What do you think? Please use the comment link below to provide feedback on this article. 

References

Neighbors, C., Atkins, D. C., Lewis, M. A., Lee, C. M., Kaysen, D. Mittmann, A., Fossos, N., & Rodriguez, L. M. (2011). Event-specific drinking among college students. Psychology of Addictive Behaviors, 25(4), 702-707.

The DRAM, Vol. 8(1) – Do U WAN2 DRNK < ?

Research shows that the emergency room (ER) might be an important location for mental health screening and intervention, particularly drug and alcohol screening (Fleming et al., 2007). However, most ERs have limited time and resources to conduct such interventions. This week, the DRAM reviews a study examining the implementation and efficacy of an ER-based screening and brief intervention for young adults delivered through text messaging (Suffoletto, Callaway, Kristan, Kraemer, & Clark, 2011).

Method

• Participants were 45 individuals (41% of those initially recruited; 87% of those who screened in) recruited during emergency room visits. Participants were 18-24 years old and screened positive for hazardous drinking according to a past-three month version of the Alcohol Use Disorder Identification Test – Consumption (AUDIT-C: Dawson, Grant, & Stinson, 2005).
• At baseline and 12-week follow-up, all participants completed a computerized timeline follow-back (TLFB) assessment of their past-three month drinking, as well as the Rutgers Alcohol Problems Index to assess past-three month alcohol related problems.
• During the study, all participants received weekly texts for 12 weeks. Researchers randomized participants into one of three groups:
  • Intervention (n = 15):  Participants received weekly texts inquiring about their alcohol consumption. If they drank at hazardous levels during that week, they received additional texts asking them to set a goal to reduce their alcohol consumption during the next week and providing tips for reducing or assessing their drinking levels.
  • Assessment (n = 15): Participants received the same text inquiry about their consumption as the intervention group, but no follow-up texts about reducing or assessing their drinking.
  • Control (n = 15): Participants received weekly text messages reminding them that the researchers would ask them to complete a final survey at the end of the study.

Results

• Almost all (97%) of the young adult ER patients approached for the study willingly completed the AUDIT-C screen, and approximately half screened positive for hazardous drinking. All but one potential participant had access to a phone with text messaging capabilities. Retention was high: 70-80% of the participants in the assessment and intervention conditions responded to all 12 weekly texts, and more than 90% responded to at least one.
• According to weekly responses, participants who received the text-based intervention were less likely to have heavy drinking days (i.e., drinking more than 3 [women] of 4 [men] drinks in a single day) over the 12 weeks compared to participants in the assessment condition. Specifically, participants in the intervention condition had fewer weeks with a heavy drinking day (Median=2, IQR=1-7, compared to Median=7, IQR=3-9), and were less likely to have back-to-back weeks with heavy drinking days (58%, 95% CI=47-68, compared to 69%, 95% CI=58-79) than participants in the assessment condition.
• As Figure 1 shows, according to comparisons between the baseline and follow-up TLFB assessments of prior month drinking, participants in the intervention condition decreased their heavy drinking days and drinks per day, whereas participants in the assessment condition increased their heavy drinking days and drinks per day. 

Figure 1. Change in drinks per day and heavy drinking days from baseline to 12-week follow-up (adapted from Suffoletto et al., 2011).

*p<.05 between conditions for change in number of heavy drinking days; **p<.001 between conditions for change in number of drinks per drinking day
Note. Negative numbers represent decreases.

Limitations

• The small sample size and short follow-up period limit the strength of the study.
• Control participants’ 12-week follow-up data might have been less accurate than other participants’ follow-up data, because researchers did not prompt them to remember their alcohol consumption on a weekly basis.

Conclusions

Suffoletto et. al’s study suggests that text messaging might be a promising brief intervention strategy, particularly for young adults. As communication channels become more advanced and innovative, public health approaches should explore the value of utilizing contemporary channels for promoting positive health behavior.

-Sarah Nelson

What do you think? Please use the comment link below to provide feedback on this article.

References

Dawson, D. A., Grant, B. F., & Stinson, F. S. (2005). The AUDIT-C: screening for alcohol use disorders and risk drinking in the presence of other psychiatric disorders. Compr Psychiatry, 46(6), 405-416.

Fleming, E. A., Gmel, G., Bady, P., Yersin, B., Givel, J. C., Brown, D., et al. (2007). At-risk drinking and drug use among patients seeking care in an emergency department. J Stud Alcohol Drugs, 68(1), 28-35.

Suffoletto, B., Callaway, C., Kristan, J., Kraemer, K., & Clark, D. B. (2011). Text-Message-Based Drinking Assessments and Brief Interventions for Young Adults Discharged from the Emergency Department. Alcohol Clin Exp Res.

The DRAM, Vol. 7(10) – Drinking and Dropping Out - Common Genetic Influences?

Many studies have described an association between academic attainment and alcohol use. For example, Crum et al. (2006) found that drinking among adolescents is associated with more educational problems and Kessler et al. (2005) found that alcohol and substance use disorders are more prevalent among those with lower education levels. It is unclear, however, what role genetic or environmental influences play in this association. This week’s DRAM reviews a study exploring influence of genetic and environmental factors on alcohol use and academic attainment (Latvala, Dick, Tuulio-Henriksson, Suvisaari, Viken, Rose & Kaprio, 2011).

Methods

• 4,858 Finnish twins (1,546 monozygotic [MZ] twins and 3,312 dizygotic [DZ] twins) comprised the sample.
• Participants completed the Rutgers Alcohol Problem Index (RAPI) and reported the maximum number of drinks ever consumed within a 24-hour period, as well as their highest level of education.
• Researchers tested ACE models (GLOSSARY LINK) predicting education, alcohol use problems, and maximum drinks, as well as their correlation, from a combination of three variables derived from twin type (i.e., MZ vs. DZ): genetic influences (A), common environmental influences (C; e.g., family environment), and unique environmental influences (E; e.g., friends).

Figure 1. Schematic of models predicting alcohol use and education attainment (Lavata et al. 2011)

 

Results

• As Figure 1 shows, genetic factors (A) and common environmental factors (C), as well as unique environmental factors (E), predicted educational attainment; however, only genetic factors and unique environmental influences predicted the alcohol use outcomes.
• Genetic factors (A) were significantly related to the negative association between educational attainment and alcohol use problems, which was small but significant in the full sample (r = -.06 to -.09). Put simply, MZ twins had higher correlations between educational attainment and alcohol use outcomes than DZ twins. This pattern was not found for common (C) or unique environmental (E) influences.

Limitations

• The education system in Finland is very different from that in the United States: schooling is free and mandatory through 9^th grade (middle school). Schools are of relatively uniform quality (Latvala et al., 2011). This may limit generalizability to countries such as the US, where income and social status can greatly influence education accessibility and quality Twin studies are limited in their generalizability, given the unique context within which twins develop.
•  This study cannot determine causality; we cannot know whether genetic or environmental factors directly influence educational attainment or alcohol use, only their level of association.

Conclusions

The current study suggests that genetic factors (A) influence both educational attainment and alcohol use, as well as their relationship, suggesting that there may be a common genetic underpinning for both these phenotypes. Common environmental influences (C), however, only influenced educational achievement. These results suggest a genetic influence on both educational attainment and alcohol use. Environmental influences play a greater role in educational attainment than alcohol use. 

-Daniel Tao

What do you think? Please use the comment link below to provide feedback on this article.

References

Crum, R.M., Juon, H.S., Green, K.M., Robertson, J., Fothergill, K., Ensminger, M. (2006). Educational achievement and early school behavior as predictors of alcohol-use disorders. Journal of Studies on Alcohol, 67, 75-85.

Kessler, R.C., Berglund, P., Demler, O., Jin, R., Merikangas, K.R., Waters, E.E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disoders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 593-602.

Lavata, A., Dick, D.M., Tuulio-Henriksson, A., Suvisaari, J., Viken, R.J., Rose, R.J., Kaprio, J. (2011). Genetic correlation and gene-environment interaction between alcohol problems and educational level in young adulthood. Journal of Studies on Alcohol and Drugs, 72, 210-220. 

The DRAM, Vol. 7(9) - Slipping through the cracks: Underdiagnosis of comorbid mental illness among repeat DUI offenders

This week, the DRAM continues its series focusing on driving under the influence (DUI). This is the last of five issues concentrating on the body of recent DUI research. In the first four issues, DRAM Vol. 7(5), DRAM Vol. 7(6), DRAM Vol. 7(7) , and DRAM Vol. 7(8), we addressed DUI-related trends, methods to detect heavy alcohol consumption and recidivism, the use of ignition interlock devices to reduce DUI behavior, and different psychiatric profiles among DUI offenders.

Repeat DUI offenders represent a population of individuals who are at high risk for co-occurring psychiatric disorders (Lapham, C'De Baca, McMillan, & Lapidus, 2006). However, in a variety of clinical settings, such as addiction treatment facilities and DUI offender programs, offenders often do not undergo comprehensive screening for psychiatric disorders (Nelson et al., 2007; Shaffer et al., 2007). This week, the DRAM reviews a study that evaluated the extent to which repeat DUI offenders are diagnosed with comorbid psychiatric disorders during mandatory treatment (McMillan et al., 2008).

Method

• The sample consisted of 233 repeat DUI offenders (86% male, Mage= 38.5, 72% White) scheduled to undergo mandatory alcohol treatment at seven licensed facilities.
• The investigators assessed their sample with a battery of surveys, using the following measures:
  • The Composite International Diagnostic Interview (CIDI; Robins, Helzer, Ratcliff, & Seyfried, 1982)—assesses whether respondents meet diagnostic criteria for a range of mental health disorders. The investigators used the CIDI to assess disorders occurring within the past 12 months.
  • The Treatment Abstraction Form (Timken, 2001)—gathers data from treatment charts of persons convicted of DUI and sentenced to mandatory treatment, including mentions of alcohol or drug use disorders in an offenders’ medical records as well as any psychiatric comorbidity identified during the treatment process.

Results

• 92.9% of participants with bipolar disorder, 68.4% of those with depression, and 100.0% of those with OCD went undiagnosed for these disorders during treatment.
• The CIDI identified just over 10% of the sample as qualifying for a drug use disorder. Participants were overdiagnosed as having drug use disorders during treatment. Treatment records identified more than 25% as having drug use disorders; approximately 24.6% (adjusted) of defendants who were not identified as having a   drug use disorder on the CIDI were diagnosed with such during treatment.
  • The CIDI is a valid and reliable instrument for assessing mental health disorders in general populations; however, its validity has not been assessed in repeat DUI populations. There is no gold standard for diagnosis, and the CIDI “diagnosis” is a proxy just as are real-time clinician impressions for a patient’s “actual” mental health status. Absent a gold standard, we cannot determine whether the clinician or the CIDI are correct.
  • The CIDI was administered prior to treatment admission, and the records analyzed to determine disorders recognized during treatment included observations made later (i.e., during treatment), as well as records that potentially pre-dated CIDI administration. Therefore, mental health status might have been different at the time of each assessment. 
  • It is possible that the treatment programs’ patient records were not consistently maintained or accurately reflected clinicians’ diagnoses. Clinicians might have diagnosed patients consistently with the CIDI, but the diagnosis not properly recorded. Programs might not have had an alternative diagnosis record keeping system, but nevertheless made some diagnoses that were in line with the CIDI

Figure 1: A Comparison of Comorbid Psychiatric Disorders Identified by the CIDI and Treatment Records among Repeat DUI Offenders

Note. Cases identified through treatment as qualifying for a given disorder are not necessarily the same cases as those identified by the CIDI.

Limitations

• The CIDI is a valid and reliable instrument for assessing mental health disorders in general populations; however, its validity has not been assessed in repeat DUI populations. There is no gold standard for diagnosis, and the CIDI diagnosis is just as much of a proxy as real-time clinician impressions for a patient’s “actual” mental health status.
• The CIDI was administered prior to treatment admission, and the records analyzed to determine disorders recognized during treatment included observations made later (i.e., during treatment), as well as records that potentially pre-dated CIDI administration. Therefore, mental health status might have been different at the time of each assessment. 
• It is possible that the treatment programs’ patient records were not consistently maintained or accurately in line with clinicians’ diagnoses. Patients may have been diagnosed correctly by program therapists, but the diagnosis not properly recorded. Programs may not have had an alternative diagnosis record keeping system, but may have nevertheless made diagnoses that aligned with the CIDI.

Discussion
This study demonstrated that mental health disorders other than drug use disorders likely are underdiagnosed within DUI-related treatment. Underdiagnosis of comorbid psychiatric conditions during mandatory treatment likely stands in the way of improving outcomes for this patient population. Ignorance of complicating diagnoses might result in increased rates of relapse and recidivism in an already vulnerable population.  Future research efforts should focus on improving pathways to identifying and treating DUI offenders with comorbid conditions.
The Division on Addictions is in the process of developing and testing CARS, a computerized assessment and referral system that guides DUI program staff through a standardized mental health assessment with their clients. For more information about our efforts in this area, please visit www.divisiononaddictions.org.

-Katerina Belkin

What do you think?  Please use the comment link below to provide feedback on this article.

References

Lapham, S. C., Kapitula, L. R., C’de Baca, J., & McMillan, G. P. (2006). Impaired-driving recidivism among repeat offenders following an intensive court-based intervention. Acc Analys Prevent, 38, 162–169.

Lapham, S. C., C'De Baca, J., McMillan, G. P., & Lapidus, J. (2006). Psychiatric disorders in a sample of repeat impaired-driving offenders. J Stud Alcohol, 67(5), 707-713.

McMillan, G. P., Timken, D. S., Lapidus, J., C'De Baca, J., Lapham, S. C., & McNeal, M. (2008). Underdiagnosis of comorbid mental illness in repeat DUI offenders mandated to treatment. J Subst Abuse Treat, 34(3), 320-325.

Nelson, S. E., LaPlante, D. A., Peller, A. J., LaBrie, R. A., Caro, G., & Shaffer, H. J. (2007). Implementation of a computerized psychiatric assessment tool at a DUI treatment facility: a case example. Adm Policy Ment Health, 34(5), 489-493.

Robins, L. N., Helzer, J. E., Ratcliff, K. S., & Seyfried, W. (1982). Validity of the Diagnostic Interview Schedule, Version II: DSM-III diagnoses. Psychological Medicine, 12, 855– 870.

Shaffer, H. J., Nelson, S. E., LaPlante, D. A., LaBrie, R. A., Albanese, M., & Caro, G. (2007). The epidemiology of psychiatric disorders among repeat DUI offenders accepting a treatment-sentencing option. J Consult Clin Psychol, 75(5), 795-804.

Timken, D. S. (2001). TAB (Treatment Abstraction Form). Albuquerque, NM7 Behavioral Health Research Center of the Southwest.

The DRAM, Vol. 7(8) - Severe DUI Offenders: One Size Doesn’t Fit All

This week, the DRAM continues its series focusing on driving under the influence (DUI). This is the fourth of five issues concentrating on the body of recent DUI research. In the first three issues, DRAM Vol. 7(5), DRAM Vol. 7(6), and DRAM Vol. 7(7)  we addressed DUI-related trends, methods to detect heavy alcohol consumption and recidivism, and the use of ignition interlock devices to reduce DUI behavior.

DUI research suggests that DUI offenders exhibit an array of characteristics that distinguish them from the general population – mental health issues, personality characteristics, and criminal behavior, among others. It is tempting to conclude from this research that DUI offenders are a homogenous group characterized by these traits. However, this week the DRAM reviews recent research by Hubicka and colleagues (2010) suggesting that even among severe (i.e., defined in this study as having a BAC >=0.1 at time of arrest) DUI offenders, multiple profiles exist.

Methods

• Hubicka and colleagues (2010) recruited 163 (12% female) Swedish DUI offenders whose BAC was >=0.1 at time of arrest.
• The researchers assessed their sample using the following measures, all of which have general population norms available:
  • The Alcohol Use Disorders Identification Test (AUDIT):  A screen for alcohol-related problems.
  • The Revised Neuroticism-Extraversion-Openness Personality Inventory (NEO-PI-R): Assesses five major personality traits – extraversion, agreeableness, neuroticism, conscientiousness, and openness to experience.
  • The Symptom Checklist (SCL-90): A self-report measure of psychiatric symptoms across all major domains of mental illness.
  • Researchers also collected DUI arrest records for the two years following the study.
  • Researchers used cluster analysis to identify subtypes of DUI offenders grouped by personality, mental health, and alcohol use characteristics. They compared the rate of DUI relapse across these groups.

Results

• Severe DUI offenders exhibited significantly lower conscientiousness, higher agreeableness, and lower openness to experience than the general population, and scored significantly higher (i.e., higher = more problematic) than the general population on 8 of 9 mental health domains.
• Cluster analyses identified three DUI subtypes, presented in Table 1.

Table 1. Severe DUI Offender Subtypes (adapted from Hubicka, et al., 2010)

Group	AUDIT	NEO-PI-R	SCL-90	Relapse
Group 1 (N = 104; 64%)	High level of alcohol problems	Similar to general population	Similar to general population	9.3%
Group 2 (N = 50; 31%)	Very high level of alcohol problems	High neuroticism, low conscientiousness	Elevated mental health problems	12.6%
Group 3 (N = 8; 5%)	Very high level of alcohol problems	Very high neuroticism, low conscientiousness	Severe mental health problems	0.0%

• Group 3, arguably the group with the highest levels of psychopathology, was significantly less likely to relapse than the other two groups.

Limitations

• This study was conducted with severe DUI offenders in Sweden. These offenders and the Swedish general population might differ from United States’ DUI offenders and general population.
• Study involvement was voluntary and required the offenders to contact the researchers proactively to participate, leading to a potential selection bias that might bias the results.
• All measures other than DUI relapse were self-report; consequently, these data are vulnerable to self-report biases.

Discussion

Though repeat or severe DUI offenders reliably exhibit elevated mental health, personality, and substance use problems, the current research suggests that these risks are not evenly distributed. Indeed, the largest group (i.e., Group 1) differed from the general population only on the extent of alcohol use problems. The two more severe subtypes also had elevated alcohol use problems; one of these was characterized primarily by high neuroticism and low conscientiousness, and the other also had multiple mental health issues. Level of problems itself was not a predictor of relapse – the group with the most problems had the lowest relapse rate. Future research needs to investigate these subtypes longitudinally to determine how DUI develops in relation to these other problems; for example, whether the Group 3 type is using alcohol to self-medicate pre-existing mental health issues, or whether the Group 2 type is exhibiting DUI as part of a more general impulsive pattern.

-Sarah Nelson

What do you think? Please use the comment link below to provide feedback on this article.

References

Hubicka, B., Kallmen, H., Hiltunen, A., & Bergman, H. (2010). Personality traits and mental health of severe drunk drivers in Sweden. Social Psychiatry and Psychiatric Epidemiology, 45(7), 723-731.

The DRAM, Vol. 7(7) – Ignition interlock devices: The silver bullet for DUI?

This week, the DRAM continues its series focusing on driving under the influence (DUI). This is the third of five issues concentrating on the body of recent DUI research. In the first two issues, DRAM Vol. 7(5) and DRAM Vol. 7(6), we addressed DUI-related trends and methods to detect heavy alcohol consumption and recidivism.

Ignition Interlock Devices (IIDs) are gaining rapid popularity among State governments as tools to reduce DUI recidivism. Figure 1 shows the rapid increase in the number of IIDs installed in recent years. An IID is a dashboard-mounted device that requires an operator to provide a breath sample periodically. If the device detects more than a predetermined amount of alcohol, the car’s engine will not start. Today’s DRAM reviews a meta-analysis of 15 studies assessing the effectiveness of IIDs (Elder, Voas, Bierness, Shults, Sleet, Nichols & Compton, 2011).

Figure 1. The rapid increase in the number of IIDs installed (from Elder et al., 2011)

Methods

• Researchers identified 15 studies examining various IID programs around the US.
• Although programs differed in their exact protocols, all targeted high-risk offenders, were offered in conjunction with a reduced sentence, and required IID installation for a minimum period of time.

Results

• The studies that examined the effects of IID installation on recidivism all found that IID installation was associated with lowered rates of recidivism.

• Across studies, recidivism was 60%-75% lower for offenders with IIDs than for those without.
• The only randomized control trial of IIDs found a 63% decrease in alcohol-related re-arrest among the IID group compared to a conventional treatment group (Beck, Rauch, Baker, & Williams, 1999). It is important to note that only a small percentage of either group were re-arrested.

• No studies found evidence of long-term behavioral change after IID removal. In all studies that measured recidivism after IID removal, recidivism rates among those who had IIDs installed rebounded to pre-IID levels post-removal.

Limitations

• No studies monitored participants to ensure compliance with IID guidelines. Research suggests people can circumvent IIDs by providing a third-party breath sample or illegally driving a car without an IID (Marques & Voas, 2010).
• Only one of the 15 studies was a true randomized control trial. Additional randomized controlled trials will help further clarify the effects of IIDs on recidivism.

Discussion

These results suggest that IIDs are an effective tool against future DUI reoffense among recidivist DUI offenders while installed. However, the fact that IIDs are effective only while installed suggests that IIDs do not influence driving habits and behavior in the long-term, but rather reduce offenders’ access to vehicles after drinking. As a result, IIDs should be viewed not as a silver bullet, but as one tool to be used in conjunction with other tools, as part of a comprehensive strategy against DUI.

-Daniel Tao

What do you think? Please use the comment link below to provide feedback on this article.

References

Beck, K. H., Rauch, W. J., Baker, E. A., & Williams, A. F. (1999). Effects of Ignition Interlock License Restrictions on drivers with multiple alcohol offenses: A randomized trial in Maryland. American Journal of Public Health, 89(1), 1696-1700.

Elder, R. W., Voas, R., Beirness, D., Shults, R. A., Sleet, D. A., Nichols, J. L., & Compton, R. (2011). Effectiveness of Ignition Interlocks for preventing alcohol-impaired driving and alcohol-related crashes: A community guide systematic review. American Journal of Preventive Medicine, 40(3), 362-376.

Marques, P. R., & Voas, R. B. (2010). Key features for ignition interlock programs (No. DOT HS 811 262). Washington, DC: NHTSA.