The Brief Addiction Science Information Source (BASIS)

The DRAM Vol. 6(1) – Drosophila study shows you have to be handsome to stay sober

2010-02-03T12:00:00-05:00

Animal models help scientists to understand human behavior and develop new drugs to treat pathologies. This week’s DRAM reviews a study that examines an animal model of drinking behavior. Devineni and Hebertein (2009) sought to determine if the drinking behavior of drosophila flies resembles human drinking behavior and if genetic mutations modify this behavior.

Method

Investigators gave flies the opportunity to choose between ethanol-containing and nonethanol-containing food. Researchers calculated a preference index (PI) as (ethanol consumption – nonethanol consumption) / total consumption. The index ranged from -1 to 1, with positive numbers indicating preference for ethanol.
Researchers measured the following:
- the basic preference of flies
- the pattern of preference change across time and ethanol concentration shifts
- the preference change after periods of starvation or ethanol deprivation
- ethanol preference of different mutations.

Results

At baseline, the flies consistently showed a statistically significant preference for the ethanol-containing food, even when the caloric ratio between ethanol and nonethanol food was balanced.
The preference for ethanol-containing food increased for the first few days but leveled off after 4 – 5 days.
The level of preference increased with larger ethanol dose concentration.
Starved flies were willing to consume ethanol at levels sufficient to produce behavioral intoxication.
After being deprived of ethanol for several days, flies quickly resumed ethanol consumption when given an opportunity.
Previous testing of 27 different types of mutations by the researchers had found one mutant -- krasavietz – or handsome in Russian – that exhibited a significantly lower preference for alcohol compared to the non-mutated controls. The “handsome” flies were studied in this experiment (see Figure 1).During the first two days the “handsome” flies showed no preference for alcohol, a behavior that was significantly different from controls who took to alcohol immediately.

Figure 1. Five day ethanol preference for control group and mutant fly krasavietz (handsome). N = 25.

Limitations

No animal model provides a perfect analog to human alcohol consumption or alcoholism. For example, social and cultural factors influence human alcoholism, and these influences are difficult to create within animal studies.

Conclusions

This study indicates that drosophila’s drinking behavior resembles human drinking patterns in many facets. Similar to humans, drosophila’s initial preference to ethanol containing food is low and apt to vary,however gradually it increases and becomes consistent. Drosophila gradually are attracted to ethanol despite its aversive taste and intoxicating effect. One characteristic of human alcohol dependence is relapse – a return to previous levels of alcohol consumption after a period of abstinence (Hunt, Barnett, & Branch, 1971). Flies also exhibit a relapse-like behavior after ethanol deprivation. Devineni and Hebertein (2009) showed that a mutation, specific to a single gene, is related to low preference for ethanol. Identifying this and potentially other mutations help scientists to understand the potential molecular mechanisms underlying alcohol preference. No animal model can explain all facets of alcohol dependence among humans. However, a better scientific understanding of ethanol preference in both animals and humans may lead to the discovery of features common to a general reward pathway involved with addiction.

-Julia Braverman

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References

Devineni, A. V., & Hebertein, U. (2009). Preferential Ethanol Consumption in Drosophila Models Features of Addiction. Current Biology, 19, 2126-2132.

Hunt, W. A., Barnett, L. W., & Branch, L. G. (1971). Relapse rates in addictions programs. . Journal of Clinical Psychology 27, 455 - 456.

The WAGER, Vol. 15(1) – Disordered Gambling and Meaningful Correlates among Cambodian Refugees

2010-01-27T14:02:48-05:00

Recent research shows that Cambodian refugees who settled in the United States suffer from disproportionately high rates of trauma (Marshall, Schell, Elliott, Berthold, & Chun, 2005). Other research shows that they also might be more prone to disordered gambling (Petry, Armentano, Kuoch, Norinth, & Smith, 2003). This week the WAGER reviews a study that examines whether socio-demographic variables and trauma are significant correlates of lifetime disordered gambling among a sample of Cambodian refugees (Marshall, Elliott, & Schell, 2009).

Methods

Study participants (n=127) were a subsample of Cambodian refugees residing in Long Beach, California. The researchers recruited study participants by using a three stage random procedure:
1) Screening: Census tracks identified areas with the highest concentration of Cambodian residents. The researchers screened 2,001 (97%) of the identified households for eligibility.
2) Eligibility: Participants aged 35 to 75 were eligible if they previously lived in Cambodia during part of the Khmer Rouge regime. This process identified 719 Cambodians as eligible from 586 households (29%).
3) Random Recruitment: One eligible person was selected randomly from each household; 490 participants agreed to participate.

Subsample: The researchers added gambling-related questions to the core study after enrolling approximately 75% of participants. The 127 subsequent participants were used in this study.

Face-to-face interviews assessed the following variables:

Socio-demographic variables: age, gender, marital status, English proficiency (dichotomized as good or fair vs. poor or no ability) and household income (dichotomized as above or below the federal poverty line).
Pre-immigration trauma exposure: assessed 35 events using items from the 17-item Cambodian Harvard Trauma Questionnaire (Mollica et al., 1992) and the 46-item Bosnian version of the Harvard Trauma Questionnaire (Allden et al., 1998).
Disordered gambling classification (i.e., problem or potential pathological gambling) assessed using the South Oaks Gambling Screen (SOGS; Lesieur & Blume, 1987). A score of 3 or more indicated disordered gambling.

The researchers conducted bivariate and multivariate logistic regression analyses to examine the relationships between the socio-demographic and trauma variables and disordered gambling. They reported the results as odds ratios; Table 1 summarizes these findings.

Table 1: Odds Ratios and 95% Confidence Intervals (CI) for Predicting Disordered Gambling (Adapted from Marshall et al, 2009)

Click image to enlarge, or adjust your browser's zoom setting.
¹Analyses are weighted and adjusted for clustering resulting from sample design
²Odds ratios are adjusted for variables with P-values less than 0.05 in bivariate models
³Per Standard Deviation
*P < 0.05
**P < 0.01

Results

Eighteen participants (13.9%) met criteria for disordered gambling.
Table 1 indicates that disordered gambling was significantly correlated with:

Being male (bivariate analysis only)
Being married/cohabitating
Being exposed to high levels of trauma

Limitations

The rate of disordered gambling had large confidence intervals; anywhere from 4% to 24%.
The results might not generalize to other populations, including other populations of Cambodian refugees.

Discussion

The results indicate lower rates (13.9%) of disordered gambling compared to the rates observed among Asian refugees in a similar study (i.e., 70.0%; Petry et al., 2003) that also used the SOGS with the same scoring classification. One difference between the two studies is that the Petry et al. study examined a convenience sample of refugees from three Asian communities (Laos, Cambodia, and Vietnam) at Asian community service organizations in Connecticut. Marshall et al. randomly selected a sample from a large Cambodian refugee community. Regardless, rates of disordered gambling appear to be meaningfully higher among Asian refugees than those observed in the general population (i.e., 1.4-2.9%; Kessler et al., 2008; Petry, Stinson, & Grant, 2005).

The correlation between traumatic events and disordered gambling in this study is consistent with other research (Kausch, Rugle, & Rowland, 2006); however, Marshall et al. found that marriage/cohabitation was significantly associated with disordered gambling. This finding contradicts other research (e.g., Petry et al., 2003; Petry et al., 2005), which reported positive associations between being divorced or single and disordered gambling. As a result, further examinations of disordered gambling and meaningful disordered gambling correlates among Cambodian refugees and other refugee communities are warranted.

-Tasha Chandler

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References

Allden, K., Ceric, I., Kapetanovic, A., Lavelle, J., Loga, S., & Mathias, M. e. a. (1998). Harvard trauma manual: Bosnian-Herzegovina version. Cambridge, MA: Harvard Program for Refugee Trauma, Harvard Medical School.

Kausch, O., Rugle, L., & Rowland, D. Y. (2006). Lifetime histories of trauma among pathological gamblers. The American Journal on Addictions, 15(1), 35-43.

Kessler, R. C., Hwang, I., LaBrie, R. A., Petukhova, M., Sampson, N. A., Winters, K. C., et al. (2008). DSM-IV pathological gambling in the National Comorbidity Survey Replication. Psychological Medicine 38(9), 1351-1360.

Lesieur, H. R., & Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers. American Journal of Psychiatry, 144(9), 1184-1188.

Marshall, G. N., Elliott, M. N., & Schell, T. L. (2009). Prevalence and correlates of lifetime disordered gambling in Cambodian refugees residing in Long Beach, CA. Journal of Immigrant Minority Health, 11(1), 35-40.

Marshall, G. N., Schell, T. L., Elliott, M. N., Berthold, S. M., & Chun, C. A. (2005). Mental health of Cambodian refugees 2 decades after resettlement in the United States. Jama, 294(5), 571-579.

Mollica, R. F., Caspi-Yavin, Y., Bollini, P., Truong, T., Tor, S., & Lavelle, J. (1992). The Harvard Trauma Questionnaire. Validating a cross-cultural instrument for measuring torture, trauma, and posttraumatic stress disorder in Indochinese refugees. The Journal of Nervous and Mental Disease, 180(2), 111-116.

Petry, N. M., Armentano, C., Kuoch, T., Norinth, T., & Smith, L. (2003). Gambling participation and problems among South East Asian refugees to the United States. Psychiatric Services, 54(8), 1142-1148.

Petry, N. M., Stinson, F. S., & Grant, B. F. (2005). Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: Results from the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry, 66(5), 564-574.

STASH, Vol. 6(1) – Skunked: Can high-potency cannabis use influence psychosis onset?

2010-01-20T12:00:00-05:00

Research indicates that cannabis use is associated with increased risk of psychosis and that cannabis potency and patterns of use can influence this risk (Henquet, Murray, Linszen, & van Os, 2005; Moore et al., 2007; Murray, Morrison, Henquet, & Di Forti, 2007). During recent decades, the potency of cannabis being sold illicitly in the US has increased dramatically. The average percentage of delta-9 tetrahydrocannabinol (Δ-9 THC) identified within samples seized by law enforcement increased from approximately 2% in 1980 to 8.5% in 2008 (ElSohly, 2009). This week’s STASH reviews a study by Di Forti et al. in which they investigated the correlation between the use of cannabis with higher levels of Δ -9 THC, such as skunk cannabis, and onset of psychosis (Di Forti et al., 2009).

Methods

In this case-control study, researchers enrolled 280 cases (i.e., patients) aged 18-65 from 3 in-patient mental health units in London, UK with first hospital admission for psychosis.
Researchers also enrolled 174 control cases from the general population within the catchments areas of the case-related hospitals via advertisements in newspapers, on the Internet, and recruitment at businesses.

Potential controls completed the Psychosis Screening Questionnaire and were not enrolled in the study if they screened positive for psychosis or had a history of psychosis.

Study participants provided information about sociodemographic variables and drug use history.

Participants reporting cannabis use completed the Cannabis Experience Questionnaire.

Researchers used logistic regression analyses to examine the relationships between case-control status and cannabis use characteristics.

Results

57% (n = 159) of cases and 63% (n = 109) of controls reported having used cannabis at least once (OR = 0.8, 95% CI 0.6-1.5).
Of those study participants reporting cannabis use

77% of cases and 33% of controls reported using cannabis daily (OR adjusted to account for potential confounders (i.e., age, gender, ethnicity, education, employment status) = 6.4, 95% CI 3.2-28.6). See Figure 1.
78% of cases reported preferential use of high-potency (Δ-9 THC levels 12-18%) “skunk” cannabis compared to 37% of controls (Adjusted OR = 6.8, 95% CI 2.6-25.4)
When asked about duration of use, 59% of cases and 38% of controls reported using cannabis for more than 5 years (Adjusted OR = 2.1, 95% CI 0.9-8.4).

Figure 1: Patterns of cannabis use among cases and controls (adapted from Di Forti et al., 2009)

* Statistically significant difference, P<0.05

Limitations

Non-random sampling strategies used to recruit controls and a lack of matching between cases and controls might have biased the findings of this study.
Study relies on self-report of drug use history, including the type of cannabis used.
Given the retrospective nature of the study (e.g., asking questions about past cannabis use) it is impossible to establish a temporal, causal relationship between high potency cannabis use and development of psychosis. For example, people who have experienced psychotic episodes might prefer high potency cannabis – perhaps as a self-handicapping strategy.
The authors collected data about patients’ use of other illicit drugs; however, they do not report it in the study. It is possible that the use of other drugs might increase psychosis risk. But, this cannot be determined from the data presented.

Conclusion
Patients with a first psychotic episode onset were significantly more likely than healthy controls to use high-potency cannabis; they also were more likely to use cannabis more frequently than the controls. This finding supports the conclusion of the authors: high concentrations of Δ9-THC is an active contributor to psychosis among cannabis users. Additional research is needed to address the limitations of this study, particularly to establish a temporal relationship between high potency cannabis exposure and onset of psychosis. As high-potency cannabis becomes more widely available to consumers, Di Forti et al. highlight the risks associated with high-potency cannabis for the public health.

-Erica Marshall

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References
Di Forti, M., Morgan, C., Dazzan, P., Pariante, C., Mondelli, V., Marques, T. R., et al. (2009). High-potency cannabis and the risk of psychosis. The British Journal of Psychiatry, 195(6), 488-491.

ElSohly, M. (2009). Quarterly Report Potency Monitoring Project: Report 104: National Institute on Drug Abuse.

Henquet, C., Murray, R., Linszen, D., & van Os, J. (2005). The environment and schizophrenia: the role of cannabis use. Schizophrenia Bulletin, 31(3), 608-612.

Moore, T. H., Zammit, S., Lingford-Hughes, A., Barnes, T. R., Jones, P. B., Burke, M., et al. (2007). Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. Lancet, 370(9584), 319-328.

Murray, R. M., Morrison, P. D., Henquet, C., & Di Forti, M. (2007). Cannabis, the mind and society: the hash realities. Nature Reviews Neuroscience, 8(11), 885-895.

Addiction and the Humanities, Vol. 6 (1) - The evolution of anti-drug ads from Fried Egg to Shoulders

2010-01-13T12:00:00-05:00

This is your brain. This is drugs. This is your brain on drugs. Any questions? These words, part of a 1987 Partnership for a Drug-Free America (PDFA) public-service announcement, are synonymous with the American anti-drug movement of the 1980’s. Although the PDFA credits Fried Egg with helping to persuade Americans that drugs are dangerous and addictive (The Partnership for a Drug-Free America, 2006), many ridicule the ad because of its overly simplistic, fear-based, and unrealistic tone (Alexander, 2000).

How have anti-drug messages changed during the two decades since Fried Egg? The good news is that producers of anti-drug ads have relied more on social science to develop their message content and delivery. For example, research indicates that fear-based messages like Fried Egg are ineffective unless they are accompanied by a viable means for reducing one’s fears (Job, 1988). As a result, when the Office of National Drug Control Policy (ONDCP) produced the What’s your Anti-Drug? campaign, part of a $1.4 billion effort that spanned the years 1998-2005, some of the ads showed teenagers engaged in positive alternatives to drug use. But, the campaign also included several ads that exaggerated the potential consequences of smoking marijuana. For example, in one ad, teenage marijuana smokers run over a small child with their car; in another, a pot smoker accidentally shoots his friend in the head.

Sometimes, the effect of anti-drug messages is unintended. For example, results from a multi-wave study indicated that the What’s your Anti-Drug? ads might have done more harm than good. Teenage respondents who had more exposure to the ads were less likely to avoid marijuana and more likely to believe that many of their peers used marijuana (Hornik, Jacobsohn, Orwin, Piesse, & Kalton, 2008). Some observers suggest that the ads might inadvertently have communicated the message that “everyone’s doing it” (Hornik et al., 2008). Another study revealed that teenage survey respondents judged six of the ads from the What’s your Anti-Drug? campaign to be less effective than a control program in reducing drug use (Fishbein, Hall-Jamieson, Zimmer, von Haeften, & Nabi, 2002). The particularly ineffective ads tended to be seen as unrealistic, uninformative, and fear-based—much like Fried Egg (Fishbein et al., 2002).

In 2005, the ONDCP shifted its strategy and, together with the PDFA, launched Above the Influence, a multi-media campaign developed using extensive qualitative and quantitative research with teens (Denniston, 2006). This campaign encourages its target audience to rise “above the influence” of drugs and risky sexual activity (The Partnership for a Drug-Free America, 2005). For instance, the Human Puppet ad shows a teenage girl passed out under the influence of an unknown substance while her friends draw on her face and position her arms as if she were a puppet. The tagline is If you’re not in control, who is? Shoulders takes the message of personal autonomy one step further by poking fun at traditional anti-drug messages. Its protagonist is a teenage boy trying to decide whether to accept a marijuana joint offered to him at a party. A series of pro-drug characters, led by the devil, appears on his left shoulder imploring him to accept the joint. Meanwhile, a series of exaggerated anti-drug characters appears on his right shoulder demanding that he refuse to accept it. These include a stern roll-model astronaut, members of the boy’s basketball team, and even Shakespeare. As the protagonist makes his decision, a voice-over declares, The only voice that matters is yours. Eventually the boy makes his decision to reject the joint, and the message to viewers is that they can still maintain their personal autonomy even if they decide to reject drug use. In this way, the campaign is consistent with research indicating that adolescents place a high value on personal autonomy and often react against prevention messages that seem too “preachy” and directive (Kelly, Comello, & Slater, 2006). Interactive features of the campaign’s website also aim to change normative beliefs about how many adolescents use drugs, perhaps in response to earlier findings.

The ONDCP ad Shoulders, available at http://www.mediacampaign.org/

Is Above the Influence working? As evidence of their ads’ effectiveness, the ONDCP frequently points to downward national trends in teenage drug use (e.g. Johnston, O'Malley, Bachman, & Schulenberg, 2004). But, Hornik and colleagues (2008) note the existence of larger declines in tobacco and alcohol use by teens, which suggest that there is a broad influence of widespread cultural shifts that goes beyond the ONDCP/PDFA campaigns. During the coming years, the ONDCP plans to collect new data that will allow them to generate more specific conclusions about the campaign’s effects on drug-related attitudes, beliefs, and intentions; they intend to use this information to refine their future messages. Successfully refining the marketing strategy will be a challenge, because it is very difficult to market health information to teens. However, by empirically evaluating outcomes and generating evidence-based messages, the ONDCP is taking a big step forward from This is your brain on drugs.

--Heather Gray

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

References
Alexander, E. (2000). Famous fried eggs: Students debate effectiveness, accuracy of well-known anti-drug commercial. Retrieved January 4, 2010, from http://www.cnn.com/fyi/interactive/news/brain/brain.on.drugs.html#%27Good%20persuasive%20information%27

Denniston, R. (2006). From "What's Your Anti-Drug?" to "Above the Influence": Rationale and results from branding research for the National Youth Anti-Drug Media Campaign. Paper presented at the The 134th Meeting of the American Public Health Association, Boston, MA.

Fishbein, M., Hall-Jamieson, K., Zimmer, E., von Haeften, I., & Nabi, R. (2002). Avoiding the boomerang: Testing the relative effectiveness of antidrug public service announcements before a national campaign. American Journal of Public Health, 92, 238-245.

Hornik, R., Jacobsohn, L., Orwin, R., Piesse, A., & Kalton, G. (2008). Effects of the National Youth Anti-Drug Media Campaign on Youths. American Journal of Public Health, 98, 2229-2236.

Job, R. F. S. (1988). Effective and Ineffective Use of Fear in Health Promotion Campaigns. American Journal of Public Health, 78, 163.

Johnston, L. D., O'Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2004). Monitoring the Future National Survey Results on Drug Use, 1975-2003: Volume 1: Secondary School Students. Bethesda, MD: National Institute on Drug Abuse.

Kelly, K. J., Comello, M. L. G., & Slater, M. D. (2006). Development of an aspirational campaign to prevent youth substance use: 'Be under your own influence.' Social Marketing Quarterly, 12, 14-27.

The Partnership for a Drug-Free America. (2005). ONDCP Launches New Teen Brand. Retrieved January 7, 2010, from http://www.drugfree.org/Portal/About/NewsReleases/ONDCP_Launch

The Partnership for a Drug-Free America. (2006). The Partnership's "Fried Egg" TV message. Retrieved January 4, 2010, from http://www.drugfree.org/Portal/About/NewsReleases/Fried_Egg_Message

ASHES, Vol. 6 (1) –Modest lifetime cigarette use affects women’s breast cancer risk.

2010-01-06T13:00:00-05:00

There are numerous factors that can lead to breast cancer. These influences include age, family history, exposure to hormones and lifestyle habits such as smoking and drinking alcohol. In this week’s ASHES, we review a study by Croghan et al. (2009). The study compared the prevalence of non-milk duct or lobule related breast cancer among women who reported smoking more than 100 cigarettes during their lifetime and women who smoked less than 100 cigarettes or never smoked.

Methods

Croghan et al. collected data from 8,927 female patients seen at the Mayo Clinic Breast Clinic between August 1, 1993 and November 31, 2003
The final sample of 8,097 women included:

831 current smokers;
714 former smokers; and
6,552 women who never smoked.

Researchers excluded women who:

were diagnosed with non-breast-related cancers;
were diagnosed with breast cancers originating in the milk-producing ducts or lobules of the breast; or
could not be linked with the Mayo Clinic Diagnostic Index.

Patients completed a self-administered questionnaire. If patients made return visits to the clinic, researchers included only their first completed survey in the analyses.
To test the effect tobacco smoke has on the probability of a breast cancer diagnosis, researchers compared patients with no cancer to patients with breast cancer using Pearson chi-squared tests and multivariate logistic regression with stepwise elimination. In each case, researchers used a two-sided test with a 0.05 significance level.

Table 1: Predictive Model of Breast Cancer using Logistic Regression (Adapted from Croghan et al, 2009)

Results

Croghan et al., using logistic regression found, after controlling for other factors, that having a personal history of ever smoking more than 100 cigarettes increased the odds of a breast cancer diagnosis by 25% (CI = 1.07, 1.46).

Limitations

Self-report of previous smoking behavior provides a limited amount of data.
Self-report might be affected by recall bias.
The use of a multivariate model includes shared variance; researchers did not specifically analyze the unique variance* due to cigarette smoking.

Conclusion

The researchers admit that it is difficult to assess the effects of lifestyle habits such as smoking and drinking. More research is needed to clarify the influence of lifestyle on the development of breast cancer. Nevertheless, Croghan et al. observed that smoking at least 100 cigarettes at any point during life increases a woman’s risk for developing breast cancer. This study supports a cautionary note: it is possible that modest levels of substance use can lead to adverse health issues.

-Ingrid Maurice

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References

Croghan, I. T., Pruthi, S., Hays, J. T., Cha, S., Johnson, R. E., Kosel, M., et al. (2009). The role of smoking in breast cancer development: an analysis of a Mayo Clinic cohort. The Breast Journal, 15(5), 489-495.

*Note: Researchers did not test the effect of cigarette smoking on the development of breast cancer independently from other variables listed in Table 1.