The Brief Addiction Science Information Source (BASIS)

STASH, Vol. 6(7) – I Can’t Focus: Self-Medication Implications behind ADHD Prescription Drug Misuse

As described in a previous BASIS, US college students report taking unprescribed ADHD medications, such as Ritalin, Concerta, and Adderall, to improve their academic performance. An open question is whether some use these prescription medications to manage undiagnosed ADHD. This week the STASH reviews a recent article by Peterkin and colleagues (2010) that explores the potential association between the misuse of ADHD medications and undiagnosed ADHD among college students.

Methods

• A convenience sample of college students (n=190) volunteered to participate in an anonymous survey regarding cognitive performance enhancement.
• The survey asked whether participants had ever been diagnosed with ADHD and whether they had ever used medications used to treat ADHD without a prescription.  
• The survey included the World Health Organization Adult ADHD Self-Report Scale, which has 97.9% classification accuracy for identifying the presence of ADHD symptoms (Kessler et al., 2005). 

Results

• Table 1 shows the distribution of participants by ADHD medication use and results of the ADHD symptom screen.
• Participants who used ADHD medication without a prescription were nearly 7 times more likely than participants who did not use ADHD medication to have ADHD symptoms (χ2 = 62.30, p < 0.0001).  
• Approximately 70% of those who used ADHD medications without a prescription screened positive for ADHD, while only 30% of those who did not use ADHD medications screened positive.  

Table 1 – ADHD Medication Use and ADHD Symptom Results (adapted from Peterkin et al.)

*This analysis was based on 180 respondents – 6 surveys were incomplete and 4 participants who reported misusing ADHD medications had a previous ADHD diagnosis.

Limitations

• Because the recruitment procedures employed flyers seeking people who were interested in cognitive performance enhancement, the study likely oversampled students who used medications to improve academic performance. Consequently, the results might exaggerate the prevalence of ADHD medication use in the absence of an ADHD diagnosis.
• The study relies on self-reported behavior. Some respondents might have been unwilling to admit that they take unprescribed medications.

Discussion

The results indicate that, among college students who take unprescribed ADHD medications, some might be self-medicating undiagnosed ADHD symptoms. These results are not unique to the ADHD population. For example, as a recent STASH discussed (STASH 6(5)), some opioid-dependent individuals use medications (e.g., buprenorphine) without a prescription to self-treat their dependence, anxiety, and pain as well as to prevent withdrawal. Regardless of the underlying condition—ADHD or opioid dependence—individuals should consider using medications under a doctor’s supervision rather than taking on the risks associated with self-medication. Colleges should consider facilitating a doctor-patient relationship by providing treatment outreach for all students.

-Tasha Chandler

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References

DeSantis, A. D., Webb, E. M., & Noar, S. M. (2008). Illicit use of prescription ADHD medications on a college campus: A multimethodological approach. Journal of American College Health, 57(3), 315-324.

Kessler, R. C., Adler, L., Ames, M., Demler, O., Faraone, S., Hiripi, E., et al. (2005). The World Health Organization Adult ADHD Self-Report Scale (ASRS): A short screening scale for use in the general population. Psychological Medicine, 35(2), 245-256.

Peterkin, A. L., Crone, C. C., Sheridan, M. J., & Wise, T. N. Cognitive performance enhancement: Misuse or self-treatment? Journal of Attention Disorders, Published Online First: 21 April 2010. doi: 2010.1177/1087054710365980.

STASH, Vol. 6(6) – The Addictive Potential of Indoor Tanning

The American public increasingly is becoming aware of the health risks of indoor tanning. Just this month, a 10% excise tax on indoor tanning went into effect; this tax is designed both to offset some of the costs of the nation’s health-care reform and to discourage the use of tanning beds. Given the health risks and increasing costs, why do people continue to engage in indoor tanning? For some, indoor tanning might represent an addiction, similar to the process of becoming addicted to substances. This week the STASH reviews an article that explores possible links among indoor tanning addiction, substance use, and mood disorders (Mosher & Danoff-Burg, 2010), implicating excessive indoor tanning as another manifestation of the addiction syndrome (Shaffer et al., 2004).

Methods

• Participants (n = 421) were recruited from students enrolled in psychology classes at a state university in the northeastern US.
• Participants completed a self-report questionnaire assessing several variables.
• Participants reported history of indoor tanning (i.e., ever tanned indoors and frequency of indoor tanning in the past year).  
• To assess participants’ lifetime dependence on indoor tanning, researchers constructed indoor-tanning-related screens based upon the CAGE alcohol screen and the DSM-IV-TR substance-related disorder diagnostic criteria. The investigators classified participants into one of three mutually-exclusive categories: not addicted to indoor tanning, displaying addictive tendencies to indoor tanning (i.e. not addicted to indoor tanning but meeting addiction criteria for at least one of the CAGE or DSM screens), or addicted to indoor tanning (i.e. meeting criteria for both screens).  
• Participants described their past-month substance use by reporting the number of days they had used each of 12 different substances during the past month.  
• Researchers assessed past-week symptoms of anxiety and depression using standard inventories. 

Results

• Among the 229 participants who reported ever tanning indoors, the mean number of past year indoor tanning visits was 23 (SD=24), 70 (30.6%) met the CAGE-based criteria for tanning addiction, 90 (39.3%) met the DSM-IV-TR-based criteria for tanning addiction, and 50 (21.8%) met the criteria for both.
• Table 1 shows the odds of the study measures predicting indoor tanning status.
• Compared with participants who were classified as not addicted (n = 119) to indoor tanning, participants who were classified as being addicted to indoor tanning (n = 50) reported (a) more frequent past-year indoor tanning use; (b) more symptoms of anxiety; (c) more days of alcohol use during the past-month; and (d) more days of marijuana use during the past-month.  
• Compared with participants who were classified as not addicted to indoor tanning, participants who were classified as having addictive tendencies (n = 60) reported (a) greater past-month alcohol use, and (b) greater past-month marijuana use.  
• Depression rates were not significantly different across all groups. 

Table 1 – Odds Ratios (95% Confidence Interval) of Indoor Tanning Addiction Status for Study Measures (adapted from Mosher & Danoff-Burg, 2010).

 
* p < 0.05  ** p < 0.001 CI = Confidence interval
¹Stimulants include cocaine, amphetamines, and the nicotine in tobacco

Limitations

• The researchers did not measure these associations prospectively. Therefore, it is not possible, on the basis of these data, to make claims about the sequence of events (e.g., whether anxiety is a risk factor for future addiction to indoor tanning or vice versa).
• The results from a survey of college students in psychology classes might not be representative of students or the general population; consequently, these findings also might not generalize to other population segments.
• The CAGE and DSM based indoor-tanning-addiction screens used in this study have relatively low internal consistency (i.e., .58 for the CAGE and .56 for DSM) and some of the items evidence questionable face validity (e.g., “Do you try to cut down on the time you spend in tanning beds or booths, but find yourself still tanning?”). Future research will need to examine the validity and reliability of these criteria.

Discussion

This study investigated whether indoor tanning, a novel target behavior for addiction research, could be an object of addiction; the results suggest that it is, but how is tanning an addiction? The syndrome model of addiction offers an explanation (Shaffer et al., 2004). The syndrome model suggests that, when people with psychological risk factors repeatedly interact with a potential object of addiction and find the result desirable, they become vulnerable to addiction. Perhaps underlying anxiety and unhealthy group norms increase young people’s vulnerability to both indoor tanning addiction and the misuse of alcohol and marijuana. Engaging in these behaviors might temporarily reduce anxious feelings and or produce feelings of well-being (Feldman et al., 2004). If so, tanning can set the stage for the potential emergence of addiction. Further prospective research is needed to explore the sequelae and components of these events.

-Tasha Chandler
 
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References

Feldman, S. R., Liguori, A., Kucenic, M., Rapp, S. R., Fleischer, A. B., Jr., Lang, W., et al. (2004). Ultraviolet exposure is a reinforcing stimulus in frequent indoor tanners. Journal of the American Academy of Dermatology, 51(1), 45-51.

Mosher, C. E., & Danoff-Burg, S. (2010). Addiction to indoor tanning: Relation to anxiety, depression, and substance use. Archives of Dermatology, 146(4), 412-417.

Shaffer, H. J., LaPlante, D. A., LaBrie, R. A., Kidman, R. C., Donato, A. N., & Stanton, M. V. (2004). Toward a syndrome model of addiction: Multiple expressions, common etiology. Harvard Review of Psychiatry, 12, 367-374. 

STASH, Vol. 6(5) – To intoxicate or to ameliorate? Reasons for illicit use of buprenorphine among opioid-dependent treatment seekers

The previous edition of STASH highlighted the complex relationship between subjective distress and substance abuse. We continue to explore this theme in this week’s STASH by reviewing a new study about the illicit use of buprenorphine, an opioid analgesic, among opioid-dependent treatment seekers. Schuman-Olivier and colleagues (2010) explored whether treatment seekers typically use buprenorphine as an attempt to attain euphoria or as self-treatment for pain and symptoms of opioid dependence. Additional research goals were to describe the prevalence of illicit buprenorphine use and to explore and how illicit buprenorphine use decreases as people become engaged in comprehensive substance abuse treatment. 

Methods
•    An outpatient addiction service in New England served as the study site. All participants met DSM-IV criteria for opioid dependence.
•    Stage 1 participants included 44 individuals seeking outpatient treatment with buprenorphine (i.e. “new intakes”) and 34 patients already receiving outpatient treatment with buprenorphine (i.e. “existing patients”).  Participants reported, on average, 12.7 years of opioid use.¹
•    Among other measures not described here, participants completed: the Buprenorphine Beliefs and Behaviors Questionnaire, to measure reasons for buprenorphine use (e.g., to get high, to save money, to reduce pain); and the Illicit Buprenorphine Use Questionnaire, to measure whether participants used buprenorphine illicitly (e.g., by buying illicit “street” buprenorphine).
•    For Stage 2, researchers administered the same surveys to 42 of the Stage 1 participants three months later.²

Results
•    The Stage 1 past 90-day prevalence of illicit buprenorphine use was 49%. Most patients who used buprenorphine illicitly (61%) were new intakes – those who did not yet have access to a doctor’s prescription.
•    Patients reported that they used buprenorphine to reduce distress, not to get high. As Figure 1 indicates, the most common reasons for buprenorphine use among all Stage 1 participants were to self-treat opioid dependence, anxiety, and pain. Illicit users were more likely than non-illicit users to use buprenorphine to prevent withdrawal, reduce pain, treat depression, and save money (all χ² > 3.50, all p ≤ .05).
•    At Stage 1, only 32% of existing patients, compared with 61% of new intakes, reported illicit buprenorphine use during the past 90 days (χ² = 6.46, p  < .05). Among completers of Stage 2, illicit buprenorphine use dropped by 70% from Stage 1 to Stage 2 (repeated measures χ² = 4.89, p < .05).


Figure 1: Percent of participants in each group (illicit users, non-illicit users, and all users) who endorsed each potential reason for buprenorphine use. Asterisks indicate significant differences between illicit users and non-illicit users, as revealed by chi-square analysis.
Based on data reported by Schuman-Olivier et al. (2010).


 Limitations
•    This study had a small sample size, which limits the power to detect significant differences; it also employed a homogenous sample obtained from one clinic, which limits conclusions about the generalizability of the findings.
•    The follow-up time frame was only 3 months, which precludes understanding whether and how people use buprenorphine to prevent long-term relapse.
•    These data, collected at intervals separated by 3 months, do not speak to the effectiveness of buprenorphine in self-treatment for short-term states such as cravings and depressed moods.

Discussion
About half of patients in this sample used buprenorphine illicitly at baseline. The fact that these individuals were most likely to use buprenorphine to self-treat their opioid dependence, pain, and depression counters the notion that most people use this drug illicitly to mimic the euphoric effects of opiates. Further, these data reveal that once engaged in an outpatient addiction treatment setting, and given a legal prescription for buprenorphine, most patients tend to reduce their illicit use of this drug. Overall this study suggests that people turn to buprenorphine to deal with recurrent feelings of distress and symptoms of opioid dependence, and that they are less likely to do so illicitly when given an affordable prescription. Future studies using more frequent assessments (e.g., ecological momentary assessment) might shed light on the effectiveness of buprenorphine for alleviating short-term distress. We suggest that policy makers take these data and the results from larger future studies into consideration when making decisions about the prescription use of buprenorphine as part of comprehensive substance abuse and mental health treatment programs.

--Heather Gray

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References
Schuman-Olivier, Z., Albanese, M., Nelson, S. E., Roland, L., Puopolo, F., Klinker, L., & Shaffer, H. J. (2010). Self-treatment: Illicit buprenorphine use by opioid-dependent treatment seekers. Journal of Substance Abuse Treatment, 39, 41-50.

Notes.
1.    New intakes did not differ from existing patients on any demographic variables measured (e.g., gender composition, salary, age). However, new intakes reported greater depression severity and more frequent lifetime benzodiazepine use at Stage 1.
2.    Researchers chose to track the first three-quarters of participants who were eligible for Stage 1.

STASH, Vol. 6(4) – Taking the Good with the Bad: The Role of Psychiatric Distress in Substance Abuse Treatment Seeking

Needle-exchange programs (NEPs) hold the potential to reduce drug-related harms by promoting safer drug-injection practices and by serving as a bridge to treatment for substance abuse. Yet, few NEP participants (5-11%) take advantage of available treatment referral services (Kidorf et al., 2005; Riley et al., 2002). This week’s STASH reviews a recent study that investigated a potential moderator of substance abuse treatment enrollment among NEP participants (Kidorf et al., 2010). Based on data from national epidemiological studies (e.g., Cohen, Feinn, Arias, & Kranzler, 2007), Kidorf and colleagues (2010) hypothesized that NEP participants who have concurrent psychiatric distress are more likely to enroll in treatment for substance abuse than their counterparts who have relatively little concurrent psychiatric distress.

Methods

• This study was conducted in collaboration with the Baltimore Needle Exchange Program.
• Data for this study came from a larger randomized evaluation of strategies designed to promote substance abuse treatment enrollment (Kidorf et al., 2009). The evaluation study compared the effectiveness of two experimental conditions against standard enrollment practices (i.e. treatment as usual).
• Study participants were 281 opioid-dependent individuals with an average age of 41 years. The study population was largely male (71.2%), unmarried (89.7%), and African-American (72%).
• Researchers used the Symptom Checklist 90-Revised to generate a measure of participants’ overall psychiatric distress. On this scale participants indicate the extent to which they feel a variety of forms of distress (e.g., depression, anxiety, hostility).
• The central outcome was whether participants enrolled in substance abuse treatment (inpatient or outpatient) during the 4-month study period. 
• The authors used a frequency distribution to classify participants into three groups of roughly the same size (i.e. low, medium, or high baseline psychiatric distress).  Then, they used logistic regression to evaluate the relationship between baseline psychiatric distress and substance abuse treatment enrollment (with the low baseline psychiatric distress group serving as the reference group), after controlling for demographic variables, randomized treatment enrollment condition, baseline drug use severity, and syringe exchange sites.

Results

• Overall, 40% of participants enrolled in substance abuse treatment during the course of the study.
• As Figure 1 shows, participants with high baseline psychiatric distress were more likely to enroll in substance abuse treatment (M = 52% enrollment) than participants with low levels of baseline psychiatric distress (M = 33% enrollment) (adjusted OR = 2.15, CI = 1.10-4.23, p < .05). Participants with low levels of baseline psychiatric distress did not differ from participants with medium levels of baseline psychiatric distress (M = 36% enrollment).

Figure 1: Proportion of participants who did and did not enroll in substance abuse treatment as a function of baseline psychiatric distress. Based on data reported in Kidorf et al. (2010).

Limitations

• The levels of substance abuse treatment enrollment were higher than what typically is reported (Kidorf et al., 2005; Riley et al., 2002). This was likely the result of at least two aspects of the study. First, only participants who were not already receiving substance abuse treatment at baseline were included in the study. Second, about two-thirds of participants were exposed to an intervention designed to promote treatment enrollment. These aspects of the study might limit the generalizability of the study’s findings.
• Different forms of concurrent psychiatric illness might differentially be related to the decision to seek treatment for substance abuse. However, the authors did not explore this possibility.
• It appears the authors did not also measure enrollment in psychiatric services.

Discussion

People who use needle-exchange programs are more likely than the general population to suffer from psychiatric disorders in addition to their substance abuse. Most commonly, these disorders include major depression, post-traumatic stress disorder, and antisocial personality disorder (Kidorf et al., 2004). These disorders create distress, impair functioning, and exacerbate substance abuse problems. However, the current study suggests that higher levels of psychiatric distress might be beneficial to the extent that they motivate people to seek treatment for substance abuse. The authors speculate that psychiatric distress might motivate treatment-seeking because it increases self-perceived functional impairment, reduces the reinforcement value of substance use, or reflects a combination of these processes. Knowledge about this potential moderator of treatment seeking might be used to better match NEP participants to appropriate referral services.

--Heather Gray

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

References

Cohen, E., Feinn, R., Arias, A., & Kranzler, H. R. (2007). Alcohol treatment utilization: Findings from the National Epidemiologic Survey on Alcohol and Related Conditions. Drug and Alcohol Dependence, 86, 214-221.

Kidorf, M., Disney, E., King, V., Kolodner, K., Beilenson, P., & Brooner, R. K. (2005). Challenges in motivating treatment enrollment in community syringe exchange participants. Journal of Urban Health, 82, 456-467.

Kidorf, M., Disney, E. R., King, V. L., Neufeld, K., Beilenson, P. L., & Brooner, R. K. (2004). Prevalence of psychiatric and substance use disorders in opioid abusers in a community syringe exchange program. Drug and Alcohol Dependence, 74, 115-122.

Kidorf, M., King, V. L., Neufeld, K., Peirce, J., Kolodner, K., & Brooner, R. K. (2009). Improving substance abuse treatment enrollment in community syringe exchangers. Addiction, 104, 786-795.

Kidorf, M., King, V. L., Peirce, J., Burke, C., Kolodner, K., & Brooner, R. K. (2010). Psychiatric distress, risk behavior, and treatment enrollment among syringe exchange participants. Addictive Behaviors, 35, 499-503.

Riley, E. D., Safaeian, M., Strathdee, S. A., Brooner, R. K., Beilenson, P., & Vlahov, D. (2002). Drug user treatment referrals and entry among participants of a needle exchange program. Substance Use & Misuse, 37, 1869-1884.

STASH, Vol. 6(3) - Skittish rats: Anxiety behavior during early withdrawal from cocaine exposure

Recovery from addictive behavior is difficult to maintain and susceptible to many factors. For instance, the symptoms of physical and psychological withdrawal that people experience when they eliminate or just reduce some pattern of addictive behavior can create a significant risk for relapse. This week, STASH examines such consequences of withdrawal in a review of a recent animal model study of the development of anxiety-like symptoms during early withdrawal from cocaine exposure (Santucci & Rosario, 2010).

Methods

• Researchers randomly assigned 26 adolescent (30-38 days old) male Long-Evans hooded rats to one of three experimental conditions: (1) daily injections of saline; (2) daily injections of 10mg/kg cocaine hydrochloride; or (3) daily injections of 20mg/kg cocaine hydrochloride.
• Researchers administered these injections for 7-8 consecutive days, allowed the rats a 10-11 day recovery period, and then tested the rats’ propensity for anxiety-related behavior in an elevated zero maze.
• • The researchers measured the rats’ time spent in open areas of the maze on two occasions, separated by a 24-hour period. 
  • Time spent in open areas (i.e., those without walls) is a measure of animals’ habituation; researchers operationally defined the failure to spend time in open areas as an index of anxiety-related behavior. 

Results

• Results indicated a significant main effect for testing occasion, F(1,23)=4.60, p<.05. Compared to the first testing, the rats spent more time in the open areas during the second testing occasion.
• The results also indicated a significant main effect for the experimental condition, F(2,23) = 4.44, p < .05. As Figure 1 shows, compared to those injected with cocaine, rats injected with saline spent more time in open areas during the second section.
• The was no interaction of occasion and experimental condition, F(2,23) < 1.00, p > .05.

Figure 1. Mean time spent in open areas by testing occasion and experimental group.

 
Limitations

• This study used animals to examine withdrawal-related anxiety behavior. Additional research should determine the applicability of these findings to human withdrawal experiences.
• The rats experienced limited cocaine exposure. It is unclear whether the amount of exposure approximates the experiences and intake of individuals who suffer from cocaine-related addiction.

Discussion

This study suggests that early withdrawal from cocaine creates anxiety-related behavior in adolescent rats. It is unclear whether this behavior represents a failure to habituate, or an inability to maintain habituation over time. Regardless, should this animal model of anxiety-related withdrawal experiences prove applicable to human early withdrawal experiences, treatment and relapse prevention efforts should anticipate and adjust for anxiety experiences that might place individuals at-risk for early relapse.

References

Santucci, A. C. & Rosario, A. (2010). Anxiety-like responses in adolescent rats following a 10–11-day withdrawal period from repeated cocaine administration. Brain Research Bulletin, 81, 441-444.

ⁱ An elevated zero maze consists of an elevated circular runway that contains areas with and without walls.

STASH, Vol. 6(2) - Incentives for abstinence: The beneficial effects of contingency management for individuals recovering from substance use disorders

High dropout rates plague traditional outpatient treatment programs for substance use disorders (Substance Abuse and Mental Health Services Administration, 2008). This week’s STASH reviews a new study that evaluated the effectiveness of two adjunctive services aimed at improving outcomes among individuals who have begun treatment for cocaine dependence (McKay et al., 2010). The adjunctive services were contingency management (CM), which provides incentives for abstinence; and relapse prevention (RP), which teaches skills for avoiding and coping with “high-risk” situations.

Methods

• Participants were 100 adults with current diagnoses of cocaine dependence who had been engaged in an intensive outpatient program (IOP) for at least two weeks.
• Participants averaged 41 years of age, 14 years of regular cocaine use, and four prior drug abuse treatments. On average, participants reported being abstinent for 44 consecutive days at baseline (two weeks after the start of IOP).
• All participants received standard IOP treatment, which used a 12-step approach, for up to four months.
• In addition, participants were assigned randomly to one of four conditions: 
• • Treatment as usual (TAU; n = 25): No adjunctive treatment beyond IOP.
  • CM (n = 26): Three times per week for 12 weeks starting at baseline, participants received a gift certificate for each cocaine-free urine sample they provided. Participants could earn a maximum of $1,150 if all samples were cocaine-negative. Gift certificates could be redeemed at retail businesses that did not permit exchange for cash, or for payment of household bills.
  • RP (n = 24): During a 20-week period starting at baseline, participants were offered one individual session per week to learn how to identify, anticipate, and cope with “risky” situations (i.e. situations that might trigger relapse).
  • CM + RP (n = 25): Participants received the 12-week CM protocol plus the 20-week RP protocol. In order to be eligible for CM gift certificates, participants had to attend RP sessions.
• The primary outcome was repeated binary indicators of cocaine use, measured via urine toxicology and self-report
• Participants provided data every three months for an 18-month post-baseline period. Retention rates were acceptable; at the 18-month assessment, 76% of the sample provided urine samples and self-reports.
• The researchers used generalized estimating equations with intent to treat analysis to compare outcomes among the four groups.

Results

• Participants in the four conditions did not differ at baseline on any of the diagnostic, treatment, or problem severity variables.
• On average participants stayed in IOP for about 3 months.
• There was a significant main effect of CM provision: across all time points, participants in the two CM conditions (CM and CM + RP) were less likely to provide cocaine-positive urines than were participants in the two non-CM conditions (RP and TAU), χ2 (1) = 3.77, p = 0.05. There was no main effect for the provision of RP, no significant interaction between CM and RP, and no significant interaction between condition and time.
• As indicated in Figure 1, the beneficial effect of CM was due primarily to low rates of cocaine-positive urines in the CM + RP condition, especially at the 6- and 9-month post-baseline assessments.

Figure 1: Percentage of urine samples obtained at each follow-up that were positive for cocaine. as a function of condition. Adapted from McKay et al. (2010).

Limitations

• The power to detect significant group differences was limited by the study’s small sample size.
• The authors only enrolled participants who completed at least 2 weeks of IOP before the baseline assessment. It is unclear whether these results would generalize to individuals who show less commitment to recovery
• Participants in the RP-alone condition did not attend many RP sessions. This might help explain why there was no main effect of RP on abstinence.

Conclusions

This study suggests that cocaine-dependent individuals who have begun outpatient therapy might benefit from the provision of contingency management. Providing monetary rewards for abstinence from illegal drugs is in line with other practical approaches to persistent societal problems. For instance, conditional cash transfer programs such as Opportunity NYC (NYC Center for Economic Opportunity, 2010) attempt to reduce poverty by providing cash incentives for academic performance and responsible parenting behaviors. Though Opportunity NYC has yet to be thoroughly evaluated, data from McKay and colleagues (2010)  suggest that cash incentives for healthier behavior can in some cases produce beneficial effects.

-Heather Gray

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References

McKay, J. R., Lynch, K. G., Coviello, D., Morrison, R., Cary, M. S., Skalina, L., et al. (2010). Randomized trial of continuing care enhancements for cocaine-dependent patients following initial engagement. Journal of Consulting and Clinical Psychology, 78, 111-120.

NYC Center for Economic Opportunity. (2010). Opportunity NYC: Conditional cash transfers.   Retrieved February 19, 2010, from http://www.nyc.gov/html/ceo/downloads/pdf/report_opportunity_nyc.pdf

Substance Abuse and Mental Health Services Administration. (2008). Treatment episode data set (TEDS): 2005. Discharges from substance abuse treatment services. (DHHS Publication No. SMA 08-4314.). Rockville, MD: Author.

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

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.

 

STASH, Vol. 5(10) – Can family interventions in early adolescence reduce teen illicit drug contact years later?

Exposure to, and use of, substances during early adolescence is associated with increased risk of escalating use, abuse, and dependence later in life (Agrawal et al., 2006; Grant & Dawson, 1997; Van Etten, Neumark, & Anthony, 1997).  Researchers have identified factors associated with reductions in opportunities to engage in substance use, such as parenting practices that emphasize adolescent monitoring and non-coercive discipline (Chen, Storr, & Anthony, 2005).  This week’s STASH reviews the findings of a family level intervention program focusing on adolescent contact with illicit drugs (Spoth, Guyll, & Shin, 2009).

Methods

• Researchers randomly assigned 22 rural Iowa schools to receive either the Iowa Strengthening Families Program (ISFP, N=11) or no intervention, with minimal researcher contact with participants (Control, N=11).
• •  Of the families eligible for participation in the study (i.e., they had children in the 6th grade), fifty three percent completed pre-testing (ISFP N = 238, Control N = 208).
  • Of those completing pre-testing in the ISFP group, 49% of families (N = 117) attended the ISFP intervention for an overall intervention response rate of 26%.
• The ISFP program provided families of sixth graders with seven evening prevention sessions including content presented to parents alone, adolescents alone, and both groups simultaneously.
• • Parents received information about parenting practices that have been shown to reduce adolescent risk of initiating drug use.
  •  Adolescents received information about peer interactions and social skill development.
• Students who completed the baseline test provided follow-up information about illicit drug exposure and drug use experience at the end of 6th, 7th, 8th, 10th, and 12th grade. As Table 1 shows, the ISFP group (N=238) included both students who attended the ISFP sessions (N=117) and those who only completed the pre-test (N=121).

Table 1: Assessment participation (adapted from Iowa State University Partnerships in Prevention Science Institute Participation figure)

 


Results

• ISFP participating adolescents were less likely to be exposed to illicit substance use than the control group adolescents, with statistically significant differences observed at the grade 8 (p=0.014) and grade 10 (p<0.001) interviews.
•  ISFP participating adolescents were about 2 times less likely than control group adolescents to have engaged in illicit substance use by grade 12 (15.5% of ISFP participants vs. 30.1% of Controls, OR=2.34; 95% CI = 1.34, 4.12; p = 0.002).

Figure 1: Illicit Substance Use Exposure (adapted from Spoth, Guyll, & Shin, 2009)

Limitations

• Researchers included all 238 pre-tested students in the ISFP group but provided no justification for expecting an intervention effect among the 121 students who did not receive the intervention.
• The recruitment (53%) and participation rates (49%) for the study are low and rate of participation at follow-up varies across study waves (Table 1).  It is possible that factors related to non-participation also might be related to substance exposure and use, which could confound the study results.
• The study population was predominantly white and from rural areas.  Consequently, these results might not generalize to urban/suburban or ethnically diverse populations.
• This study relies on self-report of illicit drug exposure and use.
• The illicit drug use assessment did not ask specifically about misuse of prescription drugs, but included the category of “other.”  The study results might underestimate the actual rates of prescription drug misuse.

Conclusion
The authors concluded that the results of this study indicate that an intervention targeting young adolescents and their parents provided a protective shield against illicit substance use initiation via reductions in exposure to illicit drugs. They attribute the protective effect to alterations in parental behaviors that limit adolescent exposure to illicit drugs. Further research will be needed to address the limitations of this study, particularly to elucidate the effects of combining ISFP participants and non-participants in the intervention group for analysis and to explore the potential impact of low rates of participation at baseline and varying follow-up rates. Until these limitations are addressed, it is difficult to judge from this study the potential of intervention techniques in early adolescence to reduce harm by effecting behavior long after program participation.
-Erica Marshall

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References

Agrawal, A., Grant, J. D., Waldron, M., Duncan, A. E., Scherrer, J. F., Lynskey, M. T., et al. (2006). Risk for initiation of substance use as a function of age of onset of cigarette, alcohol and cannabis use: findings in a Midwestern female twin cohort. Preventive Medicine, 43(2), 125-128.

Chen, C. Y., Storr, C. L., & Anthony, J. C. (2005). Influences of parenting practices on the risk of having a chance to try cannabis. Pediatrics, 115(6), 1631-1639.

Grant, B. F., & Dawson, D. A. (1997). Age at onset of alcohol use and its association with DSM-IV alcohol abuse and dependence: results from the National Longitudinal Alcohol Epidemiologic Survey. Journal of Substance Abuse, 9, 103-110.

Spoth, R., Guyll, M., & Shin, C. (2009). Universal intervention as a protective shield against exposure to substance use: long-term outcomes and public health significance. American Journal of Public Health, 99(11), 2026-2033.

Van Etten, M. L., Neumark, Y. D., & Anthony, J. C. (1997). Initial opportunity to use marijuana and the transition to first use: United States, 1979-1994. Drug and Alcohol Dependence, 49(1), 1-7.

 

STASH, Vol. 5(9) – Can marijuana use protect adolescents from brain damage associated with binge drinking?

Studies link abnormalities in the white matter of the brain among alcohol-dependent adults with impairment of executive functioning, working memory, and attention (Chanraud et al., 2007; Pfefferbaum et al., 2000).  However, few studies have investigated white matter abnormalities in sub-clinical alcohol users, particularly adolescents.  The effect of binge drinking, which is common among adolescents, coupled with marijuana use also has been largely ignored.  This week’s STASH reviews an imaging study by Jacobus et al., which examined white matter abnormalities in adolescents with histories of sub-clinical binge drinking and binge drinking + marijuana use (Jacobus et al., 2009).

Methods

• Forty-two youths aged 16-19 years recruited from high schools and colleges were classified as controls (n=14), binge drinkers (n=14) or binge drinkers + marijuana users (n=14) using the Customary Drinking & Drug Use Record.
• • Researchers classified participants as binge drinkers if they reported at least 1 episode of at least 4 drinks for females and at least 5 drinks for males.
  • Researchers classified participants as binge drinkers + marijuana users if they met the criteria for binge drinkers and reported 180-1800 episodes of lifetime marijuana use.
• Using demographic variables, the study groups were well-matched, although binge drinkers + marijuana users had significantly more occasions of drinking than binge drinkers alone (p<0.05).
• Researchers performed diffusion tensor imaging (DTI) scans on study participants to assess the integrity of their white matter fiber clusters as measured by fractional anisotropy (FA) and mean diffusivity (MD).
• Lower FA values and higher MD values correlate positively with the abnormality of white matter structure.

Results

• Binge drinkers and binge drinkers + marijuana users had significantly lower FAs than controls.
• • Binge drinkers had significantly lower FAs than controls in all 8 fiber clusters under investigation (ps<0.016). 
  • Binge drinkers + marijuana users had significantly lower FAs than controls in 3 of 8 clusters (ps<0.01).
• Binge drinkers had significantly lower FAs than binge drinkers + marijuana users in 4 of 8 examined clusters (ps 0.014 to 0.043).
• There were no significant differences in MD between the study groups.

Figure 1: Between-group FA differences (from Jacobus et al.)
   
  

CON = Control BG = Binge drinking BG+MJ = Binge drinking + marijuana use
a = CON>BG; b = CON>BG+MJ; c = BG<BG+MJ; d = BG>BG+MJ, all p<0.05

Limitations

• Drug use history relies on self-reported data.
• Small samples, which can lead to selection bias.
• The study was not longitudinal in nature so causal relationships between drug and alcohol use and white matter abnormalities cannot be determined.
• Researchers did not investigate effect of heavy marijuana use without binge drinking on white matter fiber bundles.  It is possible that binge drinking + marijuana use is protective while either alone is more damaging.

Conclusion
The results indicate that binge drinking and binge drinking + marijuana are associated with white matter damage in adolescents.  From this result, the study authors conclude that marijuana use might have a protective effect against the damage caused by binge drinking.  Additional research that addresses the limitations of this study is needed to fully elucidate the relationship between binge drinking, marijuana use, and white matter abnormalities and to examine the potential effects of this damage on the cognitive functioning of adolescents.  Research about the broader impacts of white matter damage on adolescent health and development, such as the potential effects of white matter damage on behavior, is needed.

-- Erica Marshall

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

References
Chanraud, S., Martelli, C., Delain, F., Kostogianni, N., Douaud, G., Aubin, H. J., et al. (2007). Brain morphometry and cognitive performance in detoxified alcohol-dependents with preserved psychosocial functioning. Neuropsychopharmacology, 32(2), 429-438.

Jacobus, J., McQueeny, T., Bava, S., Schweinsburg, B. C., Frank, L. R., Yang, T. T., et al. (2009). White matter integrity in adolescents with histories of marijuana use and binge drinking. Neurotoxicology Teratology, 31(6), 349-355.

Pfefferbaum, A., Sullivan, E. V., Hedehus, M., Adalsteinsson, E., Lim, K. O., & Moseley, M. (2000). In vivo detection and functional correlates of white matter microstructural disruption in chronic alcoholism. Alcoholism, Clinical and Experimental Research, 24(8), 1214-1221.

 

STASH, Vol. 5(8) – Straight dope: A randomized controlled trial of diacetylmorphine (heroin) treatment for opioid addiction

Opioid abuse affects more than 1 million North Americans and is a serious public health concern contributing to ill health and fatal overdose (United Nations Office on Drugs and Crime, 2008).  Although maintenance treatment with oral methadone is standard for opioid dependence, some opioid-dependent individuals do not respond well, have difficulty maintaining treatment, and/or continue to use illicit opioids while receiving methadone. This week’s STASH reviews the first North American randomized controlled trial of diacetylmorphine, the active component in heroin, versus methadone treatment for opioid dependence in individuals for whom standard treatments have been unsuccessful (Oviedo-Joekes et al., 2009).

Methods

• Researchers enrolled 251 opioid users in Montreal, Quebec and Vancouver, British Columbia, into an open-label, randomized controlled trial. Participants all had injected opioids daily for the past year and had at least two previous treatment attempts including one attempt with methadone treatment.
• Participants were randomized into three* groups for the 12-month study period.
• methadone (N=111): taken orally and dispensed once daily at clinic sites.
• diacetylmorphine (N=115): self-administered by injection up to three times daily by participants under medical supervision at study clinic sites.
• The primary outcomes of interest, assessed at 3, 6, 9, and 12 months were:
• Retention in treatment or drug-free status outside of the study context.
• Reduction in illicit drug use and/or other illegal activity assessed by the European Addiction Severity Index.

Results

• Figure 1 shows that treatment retention for participants receiving injectable diacetylmorphine was 87.8% compared to 51.4% of participants receiving oral methadone at 12-month follow-up, a significant difference (p < .0001).
• Figure 1 also shows that rates of illicit drug use and/or other illegal activities were reduced by 67.0% in the diacetylmorphine treatment group compared to 47.7% in the methadone treatment group (p < .01).
• The mean number of days of illicit heroin use per month was reduced from 26.6 to 5.3 in the diacetylmorphine group compared to a reduction from 27.4 to 12.0 days per month in the methadone treatment group (p < 0.001).

Figure 1 Primary Outcomes at 12 Months (adapted from Oviedo-Joekes et al., 2009).
  

Limitations

• The study relies on self-report data of illicit opioid use.
• Given the nature of the treatments under investigation, it is not possible to perform a double-blind study.
• Authors fail to acknowledge or control for the possible confounding of treatment outcome due to route of administration (i.e., injection use versus oral ingestion), social setting within which people use these drugs, with psychoactive effects of the drug.

Conclusion
This study shows that individuals treated for opioid dependence with injectable diacetylmorphine were more likely to remain in treatment and were less likely to engage in illicit drug use or other criminal behaviors compared to those treated with oral methadone.  The study authors conclude that for the subgroup of opioid-dependent individuals for which traditional (i.e., methadone) treatment options are not successful, clinically supervised treatment with diacetylmorphine appears to be a safe and effective treatment option. This interpretation must be tempered, however, because the researchers failed to account for the potential confounding effect of route of administration (i.e., oral vs. injected) on the study outcomes. It is likely that injection heroin users would prefer injection to another treatment (i.e., oral methadone) that requires significant behavioral change and places them on a different physiological and therefore psychosocial schedule. Perhaps diacetylmorphine administration is more appropriately understood as a harm-reduction strategy similar to needle exchange programs.  Further research is needed to assess the impact of diacetylmorphine administration on the lives of opioid dependent individuals. 

-Erica Marshall

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

References

Haasen, C., Verthein, U., Degkwitz, P., Berger, J., Krausz, M., & Naber, D. (2007). Heroin-assisted treatment for opioid dependence: randomised controlled trial. Br J Psychiatry, 191, 55-62.

Oviedo-Joekes, E., Brissette, S., Marsh, D. C., Lauzon, P., Guh, D., Anis, A., et al. (2009). Diacetylmorphine versus methadone for the treatment of opioid addiction. N Engl J Med, 361(8), 777-786.

United Nations Office on Drugs and Crime. (2008). World drug report. Vienna.

van den Brink, W., Hendriks, V. M., Blanken, P., Koeter, M. W., van Zwieten, B. J., & van Ree, J. M. (2003). Medical prescription of heroin to treatment resistant heroin addicts: two randomised controlled trials. Bmj, 327(7410), 310.

* Twenty-five study participants were assigned to receive a treatment option not addressed in this review.