The Division on Addiction is pleased to announce the following people will receive the book Change your Gambling, Change your Life: Jeanne Blake, Nicola Coalter, Don Feeney, Sally Langland, Jamie Large, Judy McCormick, Gavin Miller, Tom Murphy, Megan Petra, Nanciellen Poulin, Glen Rampton, Fred Smith, Naoko Takiguchi, Bob Thomson, Edith Townsend, Marianne Vick, Marlene Warner, Jessica Williams, Andrea Wöhr, and Trish Wright. http://bit.ly/editorial_DOA20th. We’ve selected people from as far away as Australia, Canada, Germany, and Japan. Thank you for celebrating our 20th anniversary with us!
Wednesday, January 25, 2012
STASH, Vol. 8(1) – Who are dual alcohol and marijuana users?
When people drink alcohol, they are more likely also to use marijuana than any other illicit drug (Degenhardt, Hall et al. 2001). However, little is known about this group of dual alcohol/marijuana users, or about how different levels of alcohol and marijuana use affect other risky behaviors. This week’s STASH reviews a study that investigates behavioral and psychosocial characteristics of those who use both alcohol and marijuana (Harrington, Baird et al. 2012). The investigators sought to determine if there are distinct clusters of alcohol/marijuana users and examine the range of potential negative consequences associated with this pattern of substance use.
Method
- Investigators conducted a secondary data analysis of data previously collected for a randomized control trial focusing on brief intervention at an emergency service within a trauma center.
- Participants were 427 individuals who (1) agreed to participate in a study about risk behavior reduction among alcohol and marijuana users and (2) reported using both alcohol and marijuana during the past 30 days.
- Participants reported how frequently they used alcohol and how frequently they used marijuana during the past 30 days.
- The researchers used cluster analysis to identify sub-types of dual users based on frequency of alcohol and marijuana use.In addition, participants completed the following self-report measures of negative consequences:
- Alcohol Use Disorders Inventory Test (AUDIT): A measure of alcohol use frequency, binge drinking episodes, and alcohol-related negative consequences for the past year.
- Marijuana Problem Scale (MPS): A measure of negative psychological, social, occupational, and legal consequences of marijuana use.
- Noteworthy Index of Problems (NIP): A measure of frequency of psychosocial events related to alcohol and/or marijuana use during the past three months (e.g., saying harsh or cruel things to someone, getting in a physical fight, saying embarrassing things). The researchers calculated overall scores as well as separate alcohol-related and marijuana-related scores.
- Injury Behavior Scale (IBC): A measure of injuries during the past year, with separate scores for total injuries, alcohol-related injuries, and marijuana-related injuries. The researchers calculated overall scores as well as separate alcohol-related and marijuana-related scores.
- High Risk Behavior Scale (HRB): A measure of 13 risky behaviors, some related to alcohol and/or marijuana use (e.g., driving after marijuana use) and others not necessarily related to alcohol and/or marijuana use (e.g., speeding, being involved in a physical fight).
- For each of these measures, except the HRB, items were combined to form a single score. For the HRB, items were kept separate.
- The researchers used Analysis of Variance (ANOVA) and Tukey post-hoc tests to compare how participants in different clusters differed in terms of psychosocial and behavioral characteristics.
Results
- The analyses revealed four distinct clusters of drug users based on the frequency of alcohol and marijuana use. The clusters were replicated independently using two sub-samples.
Table 1. Identified clusters
| Frequency of Alcohol Use | |||
|
Frequency of Marijuana Use |
|
Daily |
Weekly |
|
Daily |
Cluster 3 (N = 56) |
Cluster 1 (N = 93) |
|
|
Weekly |
Cluster 4 (N = 55) |
Cluster 2 (N = 223) |
|
- The researchers observed statistically significant differences among the four clusters for the AUDIT (F (3, 420)=39.92, p < .001), the MPS (F (3, 417)= 6.01, p < .001), the overall NIP (F (3, 410)=10.63, p < .001), the overall IBC (F (3, 423)=6.77, p < .001), and several of the HRB items.
- Figure 1a and Figure 1b show AUDIT, MPS, overall IBC, and overall NIP scores as a function of the four clusters of drug users.
Figure 1a. AUDIT scores as a function of clusters of participants.
Figure 1b. MPS, total IBC and total NIP scores as a function of clusters of participants
- Post-hoc Tukey tests revealed the following statistically significant specific group differences:
- For the AUDIT, Cluster 3 scores and Cluster 4 scores were both higher than Cluster 1 and Cluster 2 scores
- For the MPS Cluster 3 scores were higher than Cluster 2 and Cluster 4 scores
- For the NIP, Cluster 3 scores were higher than Cluster 1 and Cluster 2 scores
- For the IBS, Cluster 3 scores were higher than Cluster 1 and Cluster 2 score
Limitations
- This study uses a self-reported data.
- The study measured only frequency of alcohol and marijuana use, but not quantity.
Conclusion
These analyses identified four distinct groups of alcohol and marijuana users according to the frequency of using both substances. The results showed that individuals who used alcohol daily experienced more alcohol-related problems than individuals who used it weekly, independent of marijuana use. The pattern of marijuana use was less clear. For instance, people who used marijuana daily reported more instances of driving under the influence of marijuana than did weekly marijuana users, regardless of how frequently they used alcohol. However, for the number of marijuana related problems, daily marijuana users were not significantly different from weekly marijuana users, if the marijuana user also used alcohol weekly. The daily users of both substances reported more marijuana-related problems than weekly marijuana users. The authors speculate that individuals who use both substances daily might need targeted intervention and treatment efforts because of the highest number of associated problems.
-Julia Braverman
What do you think? Please use the comment link below to provide feedback on this article.
References
Degenhardt, L., W. Hall, et al. (2001). "The relationship between cannabis use and other substance use in the general population." Drug and Alcohol Dependence 64(3): 319-327.
Harrington, M., J. Baird, et al. (2012). "Identifying subtypes of dual alcohol and marijuana users: A methodological approach using cluster analysis." Addictive Behaviors 37(1): 119-123.
Thursday, January 19, 2012
Addiction & the Humanities, Vol. 8(1): DARE to be Ineffective? A look at Drug Education Programs in Schools
During 1983, Police Chief Daryl Gates created the Drug Abuse Resistance Education, or DARE program, which more than 80% of school districts in the United States use for educating students about resisting drug use. Every year, more than 26 million students participate in a DARE course (DARE, 2009). The DARE program utilizes uniformed police officers to teach students to make decisions to resist drug use (DARE, 2009). In addition to classes, DARE incorporates interactive education and activities like dances and socials and culminates in a graduation ceremony (DARE, 2009). DARE is very popular among students and parents. A Canadian study showed that 95% of students responded that they enjoyed the knowledge and presentation of the DARE program (RCMP, 2007). DARE is ubiquitous and popular, but is it effective?
Image 1: A graduating DARE class
Effectiveness of DARE
Ringwalt et al. (1991) showed that, although DARE increased students’ awareness and understanding of drugs, it only had a small, not statistically significant, effect on alcohol, tobacco and marijuana use. Similarly, Clayton, et al. (1996) found no differences in the rates of alcohol, tobacco, or marijuana use among DARE graduates one year after the program, or for alcohol, tobacco or marijuana trajectories between students who took DARE and controls at the five-year follow-up. Finally, a ten-year follow-up with the Clayton et al. (1996) sample found no relationship between DARE status and cigarette, alcohol, marijuana, or illicit substance use (Lynam, Zimmerman, Novak, Logan, Martin, Leukefeld & Clayton, 1999). Although proponents of DARE argue that DARE also helps to promote self-esteem and good decision making skills among graduates, Clayton et al. (1996), found only a modest effect on self-esteem and no effect on decision making immediately after course administration. At ten-year follow-up, Lynam et al. (1999) found no effect on self-esteem and a decrease in self-esteem among students who completed DARE.
Why is DARE still being taught?
DARE continues to be widely administered, despite the preponderance of evidence against the program. Why do school officials continue to offer DARE? Birkeland, Murphy-Graham and Weiss (2005) conducted more than 100 interviews with teachers, administrators, and police officers determining why DARE continues to be administered in the face of overwhelming negative evidence. Birkeland et al. (2005) found three main arguments for the continuation of DARE programs: popularity, unrealistic expectations, and secondary benefits.
- DARE is a popular program among students and parents alike. Administrators cite this as a potential barrier to elimination.
- Administrators point to unrealistic expectations on the part of researchers and the public when evaluating DARE programs. The idea that a one-semester class can reduce or eliminate drug use by itself is unrealistic. Many school administrators signed off on the program with this fact in mind, and therefore the preponderance of negative evidence is not particularly troublesome to them. Many view DARE as merely a fraction of the effort necessary to curb youth substance use.
- Police officers and administrators cite the beneficial secondary effects of DARE as a reason DARE programs persist. Police officers and administrators feel that the presence of and interaction with uniformed police officers is important for children. Research studies and critics focusing on drug use as the primary outcome do not factor in this benefit when evaluating DARE programs.
The Future of DARE?
DARE has sought to change its curriculum and created new programs to address criticisms about its lack of efficacy. During 1999, for example, DARE received private funding to create a new program, Take Charge of Your Life. Sloboda et al. (2009) evaluated the effectiveness of this new program. The study found that students who participated in Take Charge reported higher 30-day alcohol and cigarette consumption, and binge drinking rates compared to those who did not.
Other authors have suggested replacing one-size-fits-all programs such as DARE with more targeted interventions. Midford (2009) noted that focusing limited resources on harm prevention for troubled students is more beneficial than focusing on prevention for all students.
DARE has survived for more than 30 years and remains popular, despite overwhelming evidence against its efficacy as a drug prevention program. Many teachers and administrators see merit in the program, citing unseen benefits. Whereas DARE might never be the solution to youth substance use, DARE will likely continue to be offered to students as a piece of the overall effort to reduce youth drug use. Should DARE continue in its present form? Please let us know your opinion.
-Daniel Tao
What do you think? Please use the comment link below to provide feedback on this article.
References
Birkeland, S., Murphy-Graham, E., Weiss, C. (2005). Good reasons for ignoring good evaluation: The case of drug abuse resistance education (D.A.R.E.) program. Evaluation and Program Planning, 28, 247-256.
Clayton, R.R, Cattarello, A.M., Johnstone, B.M. (1996). The effectiveness of Drug Abuse Resistance Education (Project DARE): 5-year follow up results. Preventative Medicine, 25(3), 307-318.
DARE (2009). 2009 Annual Report. Retrieved Jan. 18, 2012 from http://dare.org/home/documents/0310DARE_AnnualReport_11WEB_000.pdf.
Ennett, S.T., Rosenbaum, D.P., Flewelling, R.L., Bieler, G.S., Ringwalt, C.L., Bailey, S.L. (1994). Long-term evaluation of Drug Abuse Resistance Education. Addictive Behaviors, 19(2), 113-125.
Lynam, D.R., Milich, R., Zimmerman, R., Novak, S.P., Logan, T.K., Martin, C., Leukefeld, C., Clayton, R. (1999). Project DARE: No effects at 10-year follow-up. Journal of Consulting and Clinical Psychology, 67(4),590-593.
Midford, R. (2009) Drug prevention programmes for young people: Where have we been and where should we be going? Addiction, 105(10), 1688-1695.
Ringwalt, C., Ennett, S.T., Holt, K.D. (1991). An outcome evaluation of Project DARE (Drug Abuse Resistance Education). Health Education Research, 6(3), 327-337.
RCMP. (2007). D.A.R.E. Drug Abuse Resistance Education, National Client Survey 2007. Retrieved Jan. 18, 2012 from http://dare.procon.org/sourcefiles/2007RCMP.pdf.
Sloboda, Z., Stephens, R.C., Stephens, P.C., Grey, S.F., Teasdale, B., Hawthorne, R.D., Williams, J., Marquette, J.F. (2009). The Adolescent Substance Abuse Prevention Study: A randomized field trial of a universal substance abuse prevention program. Drug and Alcohol Dependence, 102, 1-10.
Friday, January 13, 2012
Wednesday, January 11, 2012
ASHES, Vol. 8(1): Who’s winning at quitting? A state-by-state look at smoking cessation quitlines
States and the federal government have enacted public policies that assist with smoking cessation. A popular line of treatment is over-the-phone counseling via quitline. Quitlines can and often do serve as the first and sometimes the only line of help for smokers who want to quit. Since 2004, every state in the U.S., the District of Columbia, and Puerto Rico has operated a tobacco cessation quitline (American Lung Association, 2011). This week’s ASHES focuses on these state quitlines by examining data presented in the American Lung Association’s State of Tobacco Control Report (2011).
Methods
- The American Lung Association’s State of Tobacco Control Report (2011) provides information at the state level about the following quitline statistics:
1. Dollars spent, per smoker, on quitlines;
2. percentage of all smokers who receive treatment via the quitlines
- We calculated an additional variable, quitline cost effectiveness, operationalized as % of smokers who received treatment / money spent per smoker
- If states spend large amounts of money but serve few of their smokers, their score on this variable will be low; if, conversely, they spend less money but serve more of their smokers, their score will be high.
Results
Table 1. State Spending on Quitlines and Smokers Served
- There was a highly significant correlation (r = .667, p < .001), between the money spent per smoker, and the percentage of smokers who received treatment via quitline counseling.
- The five states that spent the most money per smoker were South Dakota, Wyoming, Maine, North Dakota, and Delaware.
- The five states that served the greatest number of smokers were South Dakota, New York, Oklahoma, Montana, and Iowa.
- The five most “cost effective” states (% served / spending) were Connecticut, New York, Wisconsin, Iowa, and Missouri. There was little overlap between the highest-spending states and the most cost-efficient states.
Limitations
- This is a correlational study; therefore it cannot inform us about the causal connection between spending and treatment.
- The fact that more smokers are receiving treatment in a given state does not tell us about the quality of that treatment. Greater dollars spent might equate to better care, not just more care.
Discussion
Though dollars spent was positively associated with treatment engagement, states that were most cost effective in their quitline treatment programs were not the same states that reported the most spending. The CDC and the North American Quitline Consortium report that quitline services are not receiving the optimal rate of funding ($10.53 per tobacco user) to provide best practice-level services. However, appeals for increased funding must be considered carefully. Throwing more money into state-funded quitlines might not necessarily be predictive of better overall treatment efficiency.
- Kat Belkin and Sarah Nelson
What do you think? Please use the comment link below to provide feedback on this article.
References
American Lung Association (2011). Helping smokers quit: Tobacco cessation coverage 2011. Accessible at http://www.lungusa.org/assets/documents/publications/smoking-cessation/helping-smokers-quit-2011.pdf
