The Brief Addiction Science Information Source (BASIS)

STASH, Vol. 5(5) – Substance use and abuse among lesbian, gay, and bisexual youths: The role of rejection to disclosure

Youths who self-identify as lesbian, gay, or bisexual (LGB) are significantly more likely than other young people to report using alcohol, tobacco, and other drugs (Marshal et al., 2008). Recent research has focused on risk or protective factors that influence substance use among this population. One proposed risk factor is rejection from one’s friends and family members following the disclosure of sexual orientation (i.e., “coming out”). Rejection following disclosure might produce feelings of shame and social isolation, which might contribute to increased substance use. This week’s STASH reviews a recent study of the relationship between reactions to disclosure of sexual orientation and substance use among LGB youths (Rosario, Schrimshaw, & Hunter, 2009)

Participants
•    Participants were an ethnically diverse convenience sample of 156 14-21 year-olds (mean age = 18.3, SD = 1.65) recruited from LGB community-based and college student organizations in New York City.

•    Roughly 66% self-identified as lesbian/gay, 31% identified as bisexual, and 3% identified as “other” (e.g., “confused”).

Procedures
•    Participants completed a 2- to 3-hour structured interview at recruitment (Time 1), with follow-up interviews occurring 6 and 12 months later (Times 2 and 3, respectively).

•    The retention rates were 92% for the 6-month assessment and 90% for the 12-month assessment.

•    Attrition analyses revealed that participants lost to one or more follow-up assessments did not differ at baseline from those interviewed at all three assessments on any demographic factors or Time 1 variables.

•    Participants were paid $30 at each interview.

Primary Measures
•    Participants listed the “important people” to whom they first disclosed their sexual orientation and then indicated whether each person reacted in an accepting, neutral, or rejecting manner. Therefore, there were four disclosure measures:  the total number of people, and the number of people who had an accepting, neutral, or rejecting response.

•    Substance use (quantity and frequency of cigarette, alcohol, and marijuana use) was assessed at Times 1-3 using the Alcohol and Drugs Schedule (see Rosario, Schrimshaw, & Hunter, 2009). The Time 1 assessment measured substance use in the past 3 months; the Times 2 and 3 assessments measured substance use in the past 6 months. Investigators assessed substance abuse using 11 items derived from the Diagnostic Interview Schedule for Children (e.g., “Felt you needed or were dependent on alcohol and/or drugs”). The index of substance abuse was the number of endorsed items. 

Results
•    On average, participants first became aware of their sexual orientation at age 10 and first disclosed their sexual orientation at age 15. The majority (57.1%) first disclosed to a friend. Approximately 30% first disclosed to a family member. The typical participant’s first disclosure happened roughly 3 years before Time 1.

•    Correlations and linear regressions controlling for gender, age, and social desirability revealed that, of the four disclosure measures, only the number of rejecting reactions was directly associated with substance use or abuse. More rejecting reactions predicted greater substance use at Times 1 and 2 (beta’s ranged from 0.13-0.28) and more substance abuse symptoms at Time 2 (beta = 0.44) and Time 3 (beta = 0.20). 

•    Researchers used linear regression to assess whether the number of accepting reactions moderated the relationship between the number of rejecting reactions and substance use. The interaction term (number of accepting reactions x number of rejecting reactions) significantly added to the prediction of four measures of alcohol use. Inspection of the regression slopes revealed that when participants had fewer accepting reactions, alcohol frequency and quantity increased as the number of rejecting reactions increased. However, when participants had a high number of accepting reactions, participants reported a relatively low/moderate level of alcohol use, regardless of the number of rejecting reactions they experienced. Figure 1, adapted from Rosario et al., 2009, shows the interaction between accepting and rejecting reactions predicting frequency of alcohol use at Time 1. The pattern was similar for other alcohol measures.

Limitations
•    The sample was composed of individuals living in an urban environment who were members of LGB organizations. Therefore, this sample might differ from the wider population of LGB youths in some important ways.

•    Participants provided descriptions of their disclosure retrospectively.

•    Participants varied in the length of time between disclosure and Time 1; it is unclear whether this variable influenced the relationship between reactions to disclosure and substance use/abuse.

•    Because these data were correlational, it is premature to conclude that reactions to disclosure causally influenced substance use and abuse.

Conclusions
•    Despite the limitations noted above, these data suggest that one risk factor for substance use and abuse among LGB youths is having more friends, family members, and other people react to disclosure in a rejecting manner.
•    Accepting reactions to disclosure are protective and blunt the impact of rejection on substance use and abuse.

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

References
Marshal, M. P., Friedman, M. S., Stall, R., King, K. M., Miles, J., Gold, M. A., et al. (2008). Sexual orientation and adolescent substance use: A meta-analysis and methodological review. Addiction, 103(4), 546-556.

Rosario, M., Schrimshaw, E. W., & Hunter, J. (2009). Disclosure of sexual orientation and subsequent substance use and abuse among lesbian, gay, and bisexual youths: Critical role of disclosure reactions. Psychology of Addictive Behaviors, 23(1), 175-184.

STASH, Vol. 5(4) – Risk factors for substance use among women who were teenage mothers

According to the recent Center for Disease Control’s National Vital Statistics Reports, after years of decline, the rates of teenage pregnancy in the U.S. are rising to 41.9 births per 1000 females (Center for Disease Control and Prevention, 2009). This week the STASH reviews research by De Genna, Cornelius, and Donovan (2009) who conducted a 10-year follow-up examining the risk factors for substance use among women who were teenage mothers.

Method

• Pregnant teenagers (n=445, mean age 16.32 ± 1.89, range 12-18 years) were recruited from a Pittsburgh, PA prenatal clinic and interviewed about past year substance use related experiences at three different time points:
  • (1) during pregnancy at recruiting;
  • (2) 6 years after recruitment;
  • (3) 10 years after recruitment.
• 292 participants provided complete data (68% follow-up rate)
• Data collection:
  • Demographic information: race, education, family income.
  • Substance use information (cigarette, alcohol, marijuana, cocaine, and other drug): age at initiation of substance use, peer substance use, frequency, and quantity of substance use.
  • Physical and mental health information: depression, aggression, and hostility.

Results

• Researchers did not observe any difference between the original recruited cohort and the follow-up cohort with respect to demographic information, substance use information, and physical and mental health information.
• As Table 1 shows, teenage mothers in this study cohort remained at higher risk for substance use compared to other young women or adults in the state of Pennsylvania (Pennsylvania Department of Health, 2004)

Table 1. Tobacco use and binge-drinking prevalence among different populations.

• Investigators used logistic regression models to identify factors that influence tobacco use, binge-drinking, and marijuana use, among teenage mothers at follow-up (all p < 0.05).

Figure 1. Factors associated with tobacco and marijuana use at both 6-year and 10-year follow-up.

• As Figure 1 shows, for tobacco use at 6-year follow-up, women who engaged in binge-drinking at 6-year follow-up were more likely to smoke.
• Tobacco use before pregnancy was a significant predictor of tobacco use at 10-year follow-up, while concurrent marijuana use and higher levels of hostility were associated with higher tobacco use at 10-year follow-up.
• For marijuana use at 6-year follow-up, tobacco use pre teen pregnancy and higher levels of adolescent anxiety/depression are significantly predictors of marijuana use, and higher levels of hostility at follow-up were associated with higher marijuana use.
• Race is a significant predictor for marijuana use at 10-year follow-up, indicating that Black mothers were more likely to use marijuana than white mothers; further, use of tobacco and hostility were associated with marijuana use during the 10-year follow-up.

Limitations

• We might not be able to generalize the results of this investigation to teenage mothers from other parts of the country, or to those from other socioeconomic or different racial/ethnic backgrounds.
• This study relied on self-report of substance use, with no biochemical verification.
• This study lacks comparison groups. For example, un-pregnant female teenagers who use substances and were matched for age, socioeconomic, and other demographic features.

Conclusions

• The investigators found that higher levels of hostility were associated with both tobacco and marijuana use at follow-up; this indicates that psychological issues might be associated with substance use.
• The investigators also identified that other substance use was associated with tobacco use, binge-drinking, and marijuana use among teenager mothers.

-Evelyn Chao

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

References
Center for Disease Control and Prevention. (2009). Births: Final Data for 2006. National Vital Statistics Reports, 57(7).

De Genna, N. M., Cornelius, M. D., & Donovan, J. E. (2009). Risk factors for young adult substance use among women who were teenage mothers. Addictive Behaviors, 34(5), 463-470.

Pennsylvania Department of Health. (2004). Behavioral Health Risks of Pennsylvania Adults. http://www.dsf.health.state.pa.us/health/cwp/view.asp?a=175&Q=243554

STASH, Vol. 5(3) - Gender Disparities: What Traumatic Events Place Young Adults at Risk for Substance Use Disorders?

Recent research indicates that a number of risk factors are linked to the development of Substance Use Disorders (SUDs) (Kilpatrick et al., 2000); these risks include traumatic events (Breslau, Davis, & Schultz, 2003; Simpson & Miller, 2002). Most of the research suggests that traumatic event(s) increase the risk for SUDs for young women, but not for young men (Becker & Grilo, 2006; Breslau et al., 2003; Lipschitz, Grilo, Fehon, McGlashan, & Southwick, 2000). However, this week’s STASH reviews a study of  young adults (Danielson et al., 2009) that reports an association between traumatic events and SUDs among both young men and women, but the events differed across gender. 

Methods:

• Participants were 43.5% (N=1753) of those who took part in the 7-8 year follow-up survey to the original National Survey of Adolescents (Kilpatrick et al., 2000).
  • Investigators administered telephone interviews to participants between 18 and 26 years old (mean age = 22.12) who were residing in the United States and selected by using a random digit dialing procedure.  
  • 881 (50.2%) of the sample were male and 872 (49.8%) were female. 
• The interview assessed alcohol and drug abuse, Post-traumatic Stress Disorder (PTSD), and the following traumatic events: sexual assault (SA), physical assault (PA) including severe physical punishment, and witnessed violence (WV).
  • Interview questions that assessed PTSD in the past six months and past year substance abuse used DSM-IV criteria. 
  • Close-ended questions provided measures of SA, PA and WV. Introductory narratives, including a rationale and a behavioral description, illustrated each traumatic event.  

Results:

• Table 1 shows the results for logistic regression analyses used to predict past year alcohol (N = 442, 25.2%) and drug abuse (N=197, 11.2%).
  • Gender was a significant predictor for developing both alcohol and drug abuse (e.g., OR = 2.02 for men vs. female for alcohol abuse, and OR = 4.23 for men vs. female for drug abuse, both p-values < 0.001).  
• Table 2 shows the gender related results for logistic regression analyses to determine whether traumatic events predicted alcohol and drug abuse for each gender separately. 
  • In contrast to the research currently available, traumatic events significantly increase the risk for alcohol and drug abuse in young men as well as in young women. 
  • The results show that young men and young women differ, however, by which traumatic events increase the risk for alcohol and drug abuse. 
  • For young women: SA increases alcohol and drug abuse, WV and PTSD increase alcohol abuse only.  
  • For young men: PA and PTSD increase both alcohol and drug abuse, WV increases alcohol abuse only, and SA was associated with a decrease for alcohol abuse.  

Table 1- Logistic Regression Analyses, Predictions of Past Year Alcohol and Drug Abuse (Adapted from Danielson et al., 2009).

* Click image to enlarge, or adjust your browser's zoom setting.

Table 2- Logistic Regression Analyses, Predictions of Past Year Alcohol and Drug Use by Gender (Adapted from Danielson et al., 2009).

* Click image to enlarge, or adjust your browser's zoom setting.

Limitations:

• The study uses self report.
• The data was collected from telephone interviews; therefore, participation was limited to young adults who reside in a home with a telephone. The results, therefore, might not generalize to other population segments.
• Significant sample attrition occurred between the original 1995 NSA study and this study. Again, this raises questions about the extent to which we can generalize the results.

Discussion:

The results of this study indicate that specific traumatic events increase the likelihood of developing SUDs among males and females. Perhaps this risk disparity between genders emerges from which traumatic events a male or a female is more likely to experience. Some sources suggest that young women are more likely to report experiencing SA (Rentoul & Appleboom, 1997) and young men are more likely to experience PA and/or WV (Office of Justice Programs, 2006). Prevention programs could benefit by shifting their effort to focus on the different traumatic risk factors associated with the development of SUDs among young men and women (e.g., sexually abused women’s programs should focus more on alcohol and drug abuse risk reduction than other possible risks).

-Tasha Chandler

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

References:

Becker, D. F., & Grilo, C. M. (2006). Prediction of drug and alcohol abuse in hospitalized adolescents: Comparisons by gender and substance type. Behaviour Research and Therapy, 44(10), 1431-1440.

Breslau, N., Davis, G. C., & Schultz, L. R. (2003). Posttraumatic stress disorder and the incidence of nicotine, alcohol, and other drug disorders in persons who have experienced trauma. Archives of General Psychiatry, 60, 289-294.

Danielson, C. K., Amstadter, A. B., Dangelmaier, R. E., Resnick, H. S., Saunders, B. E., & Kilpatrick, D. G. (2009). Trauma-related risk factors for substance abuse among male versus female young adults. Addictive Behaviors, 34(4), 395-399.

Kilpatrick, D. G., Acierno, R., Saunders, B., Resnick, H. S., Best, C. L., & Schnurr, P. P. (2000). Risk factors for adolescent substance abuse and dependence: Data from a national sample. Journal of Consulting and Clinical Psychology, 68(1), 19-30.

Lipschitz, D. S., Grilo, C. M., Fehon, D., McGlashan, T. M., & Southwick, S. M. (2000). Gender differences in the associations between posttraumatic stress symptoms and problematic substance use in psychiatric inpatient adolescents. Journal of Nervous and Mental Disease, 188(6), 349-356.

Office of Justice Programs, B. o. J. S. (2006). Victim characteristics.   Retrieved March 31, 2009, from http://www.ojp.usdoj.gov/bjs/cvict_v.htm#gender

Rentoul, L., & Appleboom, N. (1997). Understanding the psychological impact of rape and serious sexual assault of men: a literature review. Journal of Psychiatric and Mental Health Nursing, 4(4), 267-274.

Simpson, T. L., & Miller, W. R. (2002). Concomitance between childhood sexual and physical abuse and substance use problems. A review. Clinical Psychology Review, 22(1), 27-77.

STASH, Vol. 5(2): What were you thinking?

Researchers have used ecological momentary assessment (EMA) devices to collect data about the real time activities, moods, and environments of research participants. This data allows investigators to gain a better understanding of the events that precede episodes of drug use. Participants respond to random prompts programmed to appear on the EMA screens at specific times and also initiate their own entries. This week, we review a study about the use of EMA devices to monitor the changes in activity and mood immediately preceding craving for, and use of, cocaine and heroin. In this study, researchers were able to monitor changes in mood and setting by requesting that participants enter information into the EMA devices at different pre-set time intervals as well as at other random intervals. Because there were few heroin-only related events, we limit our report to the cocaine findings (Epstein et al., 2009).

Methods

• Investigators recruited 130 cocaine- and heroin-using outpatients from a methadone treatment research clinic.
  • Inclusion criteria: (1) age between 18 and 65 years old; (2) evidence of physical dependence on opiates; (3) evidence of cocaine and opiate use.
  • Exclusion criteria: (1) DSM-IV psychotic disorders; (2) current dependence on alcohol or any sedative hypnotic drug; (3) cognitive impairment precluding informed consent; (4) medical illness compromising study participation
• Participants enrolled in a program that included: 
  • Daily methadone injections (target dose 100mg/day), 7 days/week for up to 20 weeks
  • Urine drug tests 3 times/week
  • Abstinence reinforcement in the form of vouchers for weeks 7-18
• At the end of week 3, participants in the program received EMA configured PDAs 
  • Random prompts were timed to occur during participants’ expected waking hours: 5 random prompts per day for 5 weeks, then 2 random prompts per day for 20 weeks
  • Participants also could initiate their own entry when they craved and/or used heroin and/or cocaine
  • At each random prompt or participant initiated entry, participants reported where they were, what they were doing, with whom, and answered questions about their mood
    • Randomly prompted entries assessed craving and lapse triggers
    • Each question began “Within the past hour I felt …”, ended with triggers statements (listed below), and was answered with yes or no
    • Triggers items: “Saw Drug”, “Was Offered Drug”, “Wanted to See What Would Happen”, “Tempted Out of the Blue”, “Handled $10 in Cash”, “Felt Worried”, “Felt Angry”, “Felt Worried”, “Felt Sad”, “Felt Criticized by Others”, “Was in a Good Mood”, and “Felt Uncomfortable”
• Researchers analyzed the randomly prompted entries of 102 participants (those who provided enough data) at each of the 5 hours preceding each event-contingent entry.  Repeated-measures logistic regressions, with hours before use as the within-subject independent variable, determined whether the patterns of reported triggers changed significantly over time. Investigators analyzed the craving and use events separately.

 

Results

• Overall, participants carried PDAs for a total of 14,918 personal-days (mean: 130.9 days per participant) and answered 78.4% of randomly issued prompts (26,969 out of 34,400) and initiated 2,500 event entries (mean: 21.0 per participant). Participants responded to 1,555 randomly prompted entries during the 5 hours before episodes of craving or/and use.
• All triggers were significantly associated with cocaine use (all p < 0.05), but only “Saw Drug”, “Felt Worried”, and “Felt Criticized by Others” were significantly associated with cocaine craving (all p < 0.05).
• A comparison of positive responses to the following putative triggers showed a significant difference between cocaine use and craving (see Figures 1 and 2). “Wanted to See What Would Happen”, “Tempted Out of the Blue”, “Felt Sad”, and “Was in a Good Mood” produced large linear cocaine use increases (all p < 0.001), but not for cocaine craving.

Figure 1: Percent endorsing triggers before cocaine craving event by hours before CRAVING (adapted from Epstein et al., 2009) (all P < 0.001).

Figure 2: Percent endorsing triggers before cocaine use event by hours before USE (adapted from Epstein et al., 2009) (not significant at α=0.05 level).

Limitations
o Researchers did not examine the effects of environment, acquaintances, and activities.
o It’s possible that random prompts from EMA devices had damaging effects.
o The participants, methadone patients, are not representative of most drug users.

Conclusions
The use of ecological momentary assessment (EMA) technology presents possibilities for both research and clinical work. Epstein et al.’s study shows that drug abusers can be trusted with electronic devices (only one PDA was lost or damaged for every 226 person-days of use) and will use them as instructed. EMA device use allows researchers to use the recorded data to better understand the acute daily triggers that lead to drug use and craving. These EMA devices have the potential to change our understanding of pre-use and pre-craving events and lead to the development of better relapse prevention and treatment methods that can target specific precursors to individual drug use. Furthermore, it is possible to use these devices in clinical settings, so the treatment methods can be tailored to patients’ day-to-day lives by analyzing the data from EMA device use over a shorter period of time.

What do you think? Comments can be addressed to Ingrid R Maurice

References
Epstein, D. H., Willner-Reid, J., Vahabzadeh, M., Mezghanni, M., Lin, J. L., & Preston, K. L. (2009). Real-time electronic diary reports of cue exposure and mood in the hours before cocaine and heroin craving and use. Arch Gen Psychiatry, 66(1), 88-94.

STASH, Vol. 5(1) - Doctor Shopping and Diversion: One Pharmacological Substance Abuse Problem, Two Ways to Support it

Some prescribed medications, such as opioid analgesics, are commonly objects of dependency and abuse (e.g., Martins, Ghandour, & Chilcoat, 2007).  People who abuse controlled pharmaceuticals can obtain extra medication by doctor shopping or by diverting the medication from other sources.  This week’s STASH reports on a study about the demographics, histories of substance abuse, and drug prescription records from people dying of unintentional pharmaceutical overdose in West Virginia in 2006.

Method:
Hall, Logan, Toblin, Kaplan, Kraner et al. (2008) reviewed public and medical records to obtain data.

• The deceased persons’ medical records provided information about their substance abuse behaviors and any past suicide attempts.
• The Controlled Substance Monitoring Program reported the deceased persons’ prescription history, the number of their prescribing doctors, and the number of prescribing pharmacies they used.
• The Office of the Chief Medical Examiner combined this information with toxicology reports, police reports, and interviews with surviving friends and family to determine demographic information about the deceased, the contributing causes of death, death intentionality (e.g., intentional or accidental), and whether markers of substance abuse were associated with the death.
• Because the study could not use self report, the researchers used proxies of substance abuse indicators such as history of substance abuse, presence of other controlled contributory substances, and evidence of non-medical route of medication administration.

Results:

• In West Virginia, 295 unintentional pharmaceutical overdosed deaths were identified during 2006.
• More people diverted than doctor shopped (186 vs 63); only 24 people (8.1%) did both.  The authors did not categorize 46 people from the sample as either doctor shoppers or diverters.
• Table 1 shows more men than women unintentionally overdosed, however, about an equal number of men and women doctor shopped.
• Higher rates of people who diverted were younger and male compared with people who doctor shopped.  Both groups were highly likely to have indicators of substance abuse, although more doctor shoppers had previous overdoses in their medical histories (see Table 1).

Table 1.  Characteristics of people who divert and doctor shop among unintentional pharmaceutical overdose deaths

Adapted from Hall et al (2008); statistical significance testing added
§Includes only clinicians who prescribed controlled medications during the past year to the person who overdosed.
†Marital status among people over age 25.
*p=.05; **p<.05 Indicates a statistical difference between people who diverted and people who doctor shopped according to chi-square test.
Please click on image for a clearer picture, or adjust your browser's zoom settings.

Limitations

• Death intentionality relied on opinions from the Chief Medical Examiner’s office and therefore might not be accurate – death records could reflect a desire to protect the reputation of the deceased, or to help the deceased’s family obtain life insurance payments.  Therefore this sample might include some people who intentionally committed suicide.
• It is difficult to determine the full substance abuse history and the intentionality of the death because of limited data.
• The extent of substance abuse and previous drug overdoses and other measures likely are underestimates because friends and family members might have report inaccurate information and there likely is missing or erroneous information available to them.

Conclusion
Examining these demographic background and substance abuse indicators can help prescribers identify people who obtain extra medication, ultimately preventing overdose.  More information, such as this sample’s health and mental health status, as well their methods for gaining additional medication, also could help prescribers prevent overdose.

What do you think?  Comments can be addressed to Leslie Bosworth

References
Hall, A. J., Logan, J. E., Toblin, R. L., Kaplan, J. A., Kraner, J. C.,
Bixler, D., et al. (2008). Patterns of abuse among unintentional pharmaceutical overdose fatalities. Journal of the American Medical Association, 300(22), 2613-2620.

Martins, S. S., Ghandour, L. A., & Chilcoat, H. D. (2007). Profile of dependence symptoms among extramedical opioid analegesic users. Addictive Behaviors, 32(10), 2003-2019.

STASH Vol. 4 (11): The Need for Speed

The increasing frequency of Attention Deficit Hyperactivity Disorder (ADHD) diagnoses (Center for Disease Control, 2005; Robinson, Sclar, Skaer, & Galin, 1999)) has created an opportunity for an increasing rate of illicit use of the drugs used to treat this disorder. But, compared to other drugs of abuse, the ingestion of ADHD drugs might occur for some atypical reasons. This week’s BASIS reviews DeSantis et al.’s research about undergraduates’ illicit use of ADHD medication. According to researchers, students use the medication illicitly not with the intent of achieving a “high” or “having fun”; instead, they intend to “study longer, stay focused without distractions, and be more productive” at school (DeSantis, Webb, & Noar, 2008).

Participants

• Researchers used a convenience sample of undergraduate students enrolled in a large public university in the southeast US.
• A total of 1, 811 students completed the surveys.

Data Collection

• Researchers used both a quantitative survey instrument and qualitative in-person interviews with a subsample of participants to obtain information about students’ ADHD medication use.

Instrument

• The survey included questions related to demographics, students’ awareness of other students’ stimulant use, the details, perceptions, and reasons for use, and other drug and alcohol use

Results

• 4% (N=78) of the sample had legal prescriptions for ADHD medication.
• Of the 1, 811 undergraduates, 34% (N=585) reported having used ADHD medication illegally during their lifetime.
• Figure 1 shows that among this 34% the top three self-reported reasons for using illicit ADHD medication were related to academic objectives.

Figure 1: Reasons for Illegal Use of ADHD Medication (N=585)

Limitations

• Theses results are limited by the use of self-reported data from only one university.
• The use of this convenience sample means that results might not generalize to a broader population.

Conclusions
According to DeSantis et al., the use of ADHD medication at this particular university was stigma free and students (39%, N=231) found it “very easy” to obtain pills from people on campus. The ease with which students could obtain drugs and the lack of stigma suggest that conventional methods of dealing with substance use and addiction might not be successful in treating students who abuse ADHD medication. The reasons for use (i.e. to do better, to get good grades, perceived increased intelligence and cognitive aptitude) are difficult to argue against in today’s society and seem distinct from stereotypical reasons for drug use (i.e, to escape, to have fun, to get high, peer pressure). To prevent the illicit use of prescription ADHD medication, dosages should be closely monitored to limit the extra pills that students have and pass on to friends. School and prevention programs would also benefit from changing their courses to include information about the physiological dangers of abusing prescription medication.

What do you think? Comments can be addressed to Ingrid R Maurice

References

Center for Disease Control. (2005). Mental health in the United States. Prevalence of diagnosis and medication treatment for attention-deficit/hyperactivity disorder--United States, 2003. Morbidity and Mortality Weekly Report, 54(34), 842-847.

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

Robinson, L., Sclar, D., Skaer, T., & Galin, R. (1999). National trends in the prevalence of attention-deficit/hyperactivity disorder and the prescribing of methylphenidate among school-age children; 1990-1995. Clinical Pediatrics, 38(4), 209-217.

STASH, Vol. 4(10): Let’s Try Something New: Vaccines to Treat Addiction

Conventional treatments for substance abuse can have limited success for some and be ineffective for others. In an attempt to expand the available treatment options, researchers are developing vaccines for addiction. Orson et al. review the current status of vaccines to treat nicotine, cocaine, phenylcyclidine (PCP), methamphetamine, heroin, and morphine for which conventional inpatient and outpatient treatment programs have shown limited success(Orson et al., 2008). In this review, we discuss only the status of vaccines currently undergoing clinical trials with humans.

Methods

• The authors provide a critical review of current clinical vaccines and animal studies that focus on reactions to vaccinations intended to block the effects of various illicit drugs.

Results

• There are currently three nicotine vaccines undergoing clinical trials (see the first, third, and fourth rows of Table 1 below):

• After 12 weeks, TA-NIC trial participants who were encouraged to quit smoking had a 38% quit rate; this is significantly higher than the 8% placebo group quit rate (LeSage, Keyler, & Pentel, 2006).
• Elevated doses of NicVax resulted in participants’ quitting smoking without being asked to do so (Hatsukami et al., 2005).
• Participants in NicQb trials had quit rates twice those of the placebo group (57% vs 31%) (Maurer et al., 2005).

Table 1: Current Status of Drug Vaccines in Clinical Trials (Orson et al., 2008) 

Vaccine	Drug-Carrier	Human Studies
TA-NIC	Nicotine – cholera toxin b	Phase I, Phase II
Nic-Vax	Nicotine – Pseudomonas exoprotein A.	Phase I, Phase II
NicQb	Nicotine – virus like particle	Phase I, Phase II, Phase IIb
TA-CD	Cocaine – cholera toxin b	Phase I, Phase IIa, Phase IIb

• There is currently one cocaine vaccine in clinical trials: TA-DC (see the second row of Table 1 above).

• Phase I and early Phase II TA-CD vaccine trials demonstrated reduction in cocaine effects in laboratory settings and reduced cocaine use in outpatient settings. (Kosten et al., 2002; Martell, Mitchell, Poling, Gonsai, & Kosten, 2005)
• Higher doses of the TA-DC vaccine led to a periods of reduced cocaine use, as evidenced by researcher monitoring during urine testing (Martell, 2008 submitted).
• Some trial participants overrode the vaccine by increasing their cocaine intake (Orson et al., 2008).

Limitations

• The reviewed trials are in the early research stages (i.e., Phases III and IV are yet to commence); the number of participants is small and the effect sizes are not comparable to large scale studies of conventional treatment options.
• It is difficult to compare the differences in quitting rates across nicotine vaccine studies. Researchers used different methods and different non-medical influences were present in each study. Consequently, placebo quit rates in one study were comparable to vaccine quit rates in another study. These observations suggest the need for additional research with more rigorous research methods.
• The efficacy of the vaccines in human trials has not yet been compared against conventional addiction treatments.

Discussion
The development of substance use vaccines will lead to increased knowledge about drugs, their pharmacokinetics, and the possibility of new treatments for substance addiction. The differences that result from placebo effects could also be further researched as more substance abuse treatments are developed. The complexities of the human body and of addiction science make this research difficult. It takes time to isolate the effects of a drug and the counter-effects of a vaccine, and it is also difficult to resolve the mental and physical aspects of a substance addiction. Despite these hurdles, current advances in addiction and substance use vaccines look promising.

What do you think? Comments can be addressed to Ingrid Maurice

References

Hatsukami, D. K., Rennard, S., Jorenby, D., Fiore, M., Koopmeiners, J., de Vos, A., et al. (2005). Safety and immunogenicity of a nicotine conjugate vaccine in current smokers. Clinical  Pharmacology & Therapeutics, 78(5), 456-467.

Kosten, T. R., Rosen, M., Bond, J., Settles, M., Roberts, J. S., Shields, J., et al. (2002). Human therapeutic cocaine vaccine: safety and immunogenicity. Vaccine, 20(7-8), 1196-1204.

LeSage, M. G., Keyler, D. E., & Pentel, P. R. (2006). Current status of immunologic approaches to treating tobacco dependence: vaccines and nicotine-specific antibodies. The AAPS Journal, 8(1), E65-75.

Martell, B. A., Mitchell, E., Poling, J., Gonsai, K., & Kosten, T. R. (2005). Vaccine pharmacotherapy for the treatment of cocaine dependence. Biological Psychiatry, 58(2), 158-164.

Maurer, P., Jennings, G. T., Willers, J., Rohner, F., Lindman, Y., Roubicek, K., et al. (2005). A therapeutic vaccine for nicotine dependence: preclinical efficacy, and Phase I safety and immunogenicity. European Journal of Immunology, 35(7), 2031-2040.

Orson, F. M., Kinsey, B. M., Singh, R. A., Wu, Y., Gardner, T., & Kosten, T. R. (2008). Substance abuse vaccines. Annals of the New York Academy of Sciences, 1141, 257-269.

STASH Vol. 4(9) - The power of hidden bias: Implicit prejudice toward injecting drug users and nurses' intentions to quit

Implicit prejudice, harboring negative associations toward particular social groups without conscious awareness, predicts a wide range of real-life behaviors, including discriminatory medical decisions (Green et al., 2007) and hiring practices (Ziegert & Hanges, 2005). Drug addicts are often the target of implicit prejudice by the general public. This week’s STASH reports on new research related to implicit prejudice toward injecting drug users (IDUs) among drug and alcohol (D&A) nurses (von Hippel et al., 2008).

Participants
•    Participants were 44 D & A nurses in the Sydney, Australia metropolitan area recruited from D&A treatment facilities, needle and syringe exchange programs, and primary-care facilities that cater to IDUs.

Materials and Procedure
•    Implicit prejudice toward IDUs was measured with the Implicit Associations Test, a computerized procedure that uses reaction times to measure how strongly people associate certain categories. Here, researchers measured how strongly participants associated the concept “injection drug user” with positive or negative personality attributes (e.g., “wonderful” versus “awful”). Each participant received a d score based on responses to this task. Positive d scores indicate stronger associations between IDUs and negative attributes; negative d scores indicate stronger associations between IDUs and positive attributes.

•    Participants also completed a self-report measure of prejudice toward IDUs that directly asked 9 questions, such as “I avoid injecting drug users whenever possible” and “Injecting drug use is immoral” on a 5-point scale anchored by strongly disagree and strongly agree. The possible range was therefore 1 (indicating a low level of reported prejudice) to 45 (indicating a high level of reported prejudice). The mean score for this sample was 2.16 (SD = 0.60).

•    Job stress was measured with 2 items (e.g., “Working with injecting drug users is really a strain for me”). Answers were provided on a 6-point scale ranging from never to every day.

•    Intentions to change jobs was measured with one item (“During the next year, I will probably look for a new job in another area of nursing”). Responses were provided on a 5-point scale ranging from strongly disagree to strongly agree (mean score = 2.45; SD = 1.23).

•    Participants also completed a 12-item measure of the extent to which their IDU clients exhibited a variety of challenging behaviors (e.g., verbal abuse, stealing) during treatment. Answers were provided on a 4-point scale, from never to often. 

Results
•    The average implicit prejudice score across all participants was d = 0.26 (SD = 0.26), which is significantly greater than zero (t(42) = 4.16, p < 0.001).

•    As Figure 1 shows, nurses who reported that their IDU clients engaged in more challenging behaviors reported experiencing more job stress (β = 0.43, p < 0.01). More job stress, in turn, was associated with a stronger intention to quit D & A nursing (β = 0.56, p < 0.001). However, the relation between job stress and intention to quit D & A nursing was mediated by implicit prejudice toward IDUs (indirect effect = 0.175, 95% CI = 0.53-0.49). Greater implicit prejudice against IDUs appears to be the process through which job stress influences the intention to quit D & A nursing. 

Figure 1: The mediated effect of stress on intention to change jobs among D & A nurses. 

Fig. 1. Path coefficients represent standardized regression weights. The coefficient below the path between job stress and intention to quit D & A nursing represents the direct effect with no mediators in the model; the coefficient above the path represents the direct effect when the mediators are included in the model. Please note that for ease of presentation we have not represented two additional variables included in the original model. Analyses revealed that removing these variables from the model does not substantially change the results. * p < 0.05, ** p < 0.01, *** p < 0.001. 

Limitations
•    Some have questioned the interpretation of implicit prejudice d scores, suggesting that there is no true zero point reflecting a cut-off between prejudiced and non-prejudiced responding (Blanton & Jaccard, 2006).

•    The authors did not measure actual job turnover, but rather the stated intention to leave D & A nursing. Consequently, this research does not inform us about actual job changes.

•    It is possible that the pattern of results varied as a function of study site (i.e., needle exchange programs versus primary-care facilities); this analysis was not included in the report. 

Conclusions
The size of the average d score in this study indicates that, on average, the sample of nurses held a slightly strong association between IDUs and negative personality attributes.  The authors speculate that D & A staff might believe (and report) on a conscious level that IDUs are worthy of care and sympathy, and yet still harbor negative associations about this group on an unconscious, or implicit, level. Challenging behaviors on the part of IDU clients and resulting job stress appears to increase implicit prejudice toward IDUs, which then increases the intention to quit D & A nursing. Identifying a process through which nurses decide to quit D & A nursing might be helpful to prevent staff burnout and turnover, which are prevalent problems in this subfield of nursing care.

What do you think?  Comments can be addressed to Heather Gray.

References

Blanton, H. & Jaccard, J. (2006). Arbitrary metrics in psychology. American Psychologist, 61, 27-41.

Green, A. R., Carney, D. R., Pallin, D. J., Ngo, L. H., Raymond, K. L., Iezzoni, L. I., & Banaji, M. R. (2007). The presence of implicit bias in physicians and its prediction of thrombolysis decisions for black and white patients. Journal of General Internal Medicine, 22, 1231-1238.

von Hippel, W., Brener, L., & von Hippel, C. (2008). Implicit prejudice toward injecting drug users predicts intentions to change jobs among drug and alcohol nurses. Psychological Science, 19, 7-11.

Ziegert, J. C. & Hanges, P. J. (2005). Employment discrimination: The role of implicit attitudes, motivation, and a climate for racial bias. Journal of Applied Psychology, 90, 553-562.

STASH, Vol 4(8) - Safe Housing for Homeless, Drug Injecting Adolescents

Rates of substance use among homeless adolescents are high (e.g., Greene, Ennett, & Ringwalt, 1997). Some factors might exacerbate the likelihood that a homeless adolescent uses illicit substances.  This week’s STASH explores the relationship between injection drug use and the quality of housing that homeless adolescents are able to find (Rhule-Louie, Bowen, Baer, & Perterson, 2008).

Participants

• Participants were 285 homeless adolescents (average age 17.4) from Seattle, recruited from homeless agencies or from the street.  The sample was 72.8% Caucasian and 54.6% male.
• Homelessness: The participants had an unstable living arrangement (i.e., did not live with a family member or in a group home) for the past month and had no plan for a stable living environment for the next month. 
  
  • The average length of time they lived away from home was 2.49 years.
• Substance use: During the past month, all participants used an illicit substance 4+ times or had 1+ binge drinking episode(s).
  • 36.1% of the sample used injection drug(s) during the past month

Measures
An in-person interview determined:

• Past month frequency and type of substance use, and
• Places they lived during the past month.

Method

• Authors rated the safety of the living arrangements (e.g., squatting or living on the street were both considered riskier than staying with a friend).
• The authors used chi square analyses to explore the relationship between their housing-related safety and their substance use.

Results

• A path analysis showed that teens who injected drugs lived in fewer places during the past month (standardized beta weight = -.146, p<.05).
• However, Table 1 shows that teens who injected drugs were more likely to live in riskier places and less likely to live in safer places than the rest of the sample.

Table 1. Chi Square analysis of injection drug users’ living situations, as compared to the rest of the sample

Adapted from Rhule-Louie et al. (2008).

Limitations

• Interview data was derived from participants’ self report.
• There was no independent confirmation of substance use habits.
• The sample is not nationally representative; results might not generalize to all homeless youth.
• Authors did not report basic proportions, so judging whether the results are clinically significant is difficult.

Conclusion
Injection drug users had more consistent living situations, but these situations were more risky, leaving them consistently unsafe.  There is an assumption that stability for teens, particularly homeless teens, is optimal, but the context of this stability is important. For example, obtaining and injecting drugs might be easier to do when consistently living in a car than a halfway house, with a friend, and/or some adult relative’s house.  Therefore, interventions should focus on maximizing safety, as well as stability.  Placing a teen in a safe, stable home could ultimately reduce drug use; similarly, drug treatment could provide a foundation for seeking safer housing.

What do you think?  Comments can be addressed to Leslie Bosworth.

References

Greene, J. M., Ennett, S. T., & Ringwalt, C. L. (1997). Substance use among runaway and homeless youth in three national samples. American Journal of Public Health, 87, 229-235.

Rhule-Louie, D. M., Bowen, S., Baer, J. S., & Perterson, P. L. (2008). Substance use and health and safety among homeless youth. Journal of Child and Family Studies, 17, 306-319.

STASH Vol. 4(7) - Do You Feel What I Feel? Amphetamine Exposure and Personality

Some scientists have speculated that substance misuse affects people differently depending on their personality (Nurnberger Jr et al., 1982; Reif & Lesch, 2003). This week we report on a study that examined the influence of personality-traits on individuals’ reactions to amphetamine exposure (White, Lott, & de Wit, 2006).

Participants: 128 healthy individuals recruited from the community
Experiment: In random order, researchers administered a placebo(1), 10mgs, and 20mgs of amphetamine to all participants, under double-blind conditions, over the course of three sessions separated by a minimum of 48 hours
Research Objective: To measure how personality traits (i.e., reward sensitivity, physical fear, and impulsivity) might moderate subjective responses to exposure to amphetamine
Measures: Multidimensional Personality Questionnaire-Brief Form (MPQ-BF) (Depue & Collins, 1999; Patrick, Curtin, & Tellegen, 2002; Tellegen, 1982)

Figure 1*: Association between Physical Fear & D-Amphetamine

*Adapted from: Figure 1: Trait physical fearlessness and positive activational responses to d-amphetamine. Higher-order positive drug effect (factor score) responses in participants with low [low physical fear] and high [high physical fear] scores on MPQ-BF Harm Avoidance.

Results, Figure 1:

• Individuals who scored low on physical fear had higher positive responses2 to low dose amphetamine compared to individuals who scored high on physical fear (p?0.005)
  • Physical fear did not significantly effect responses to medium dose amphetamine
• Amphetamine response was not related to having high or low reward sensitivity or impulsivity

Main limitations:

• Self-reports of sensitive information might have introduced recall bias
• Participant similarities (e.g., educated, physically/psychiatrically healthy, relatively young) limit our ability to generalize the results

Discussion:
White et al.’s findings show that personality-related factors moderate the activational effects of one dose of amphetamine in healthy volunteers.  The findings suggest that further research could help clinicians develop methods and materials to recognize whether and how personality-related factors influence addiction risk and recovery.

Notes

1. A substance containing no medication and prescribed or given to reinforce a patient's expectation to get well.

2. Positive Activational Responses were defined as: greater activation, euphoria, vigor, arousal, elation, friendliness, and positive mood, and less sedation and fatigue.

References

Depue, R., & Collins, P. (1999). Neurobiology of the structure of personality: dopamine, facilitaion of incentive motivation, and extraversion. Behavioral and Brain Science(22), 491+569.

Nurnberger Jr, J., Gershon, E., Simmons, S., Ebert, M., Kessler, L., Dibble, E., et al. (1982). Behavioral, biochemical and neuroendocrine responses to amphetamine in normal twins and ‘well-state’ bipolar patients. Psychoneuroendocrinology, 7, 163-176.

Patrick, C., Curtin, J., & Tellegen, A. (2002). Development and validation of a brief form of the Multidimentional Personality Questionnaire. Psychological Assessment(14), 150-163.

Reif, A., & Lesch, K.-P. (2003). Toward a molecular architecture of personality. Behavioral Brain Research, 139, 1–20.

Tellegen, A. (1982). Brief Manual for the Multidimensional Personality Questionnaire. . University of Minnesoata.

White, T. L., Lott, D. C., & de Wit, H. (2006). Personality and the Subjective Effects of Acute Amphetamine in Healthy Volunteers. Neuropsychopharmacology, 31, 1064-1074.