Marijuana use among low-income urban youth: A systematic review

s / Drug and Alcohol Dependence 146 (2015) e118–e201 e149 cocaineand MA-induced reinstatement. Further, PG01037 was effective in reallocating choice behavior from cocaine to food responding in 2 of 4 monkeys. Conclusions: These data support a potential use for buspirone in the drug abuse treatment of relapse and support the continued examination of D3 compounds for novel therapeutic agents. Financial Support: DA012460, NIDA-IRP. http://dx.doi.org/10.1016/j.drugalcdep.2014.09.321 Marijuana use among low-income urban youth: A systematic review Renee M. Johnson1, C. Kaczmarsky2, K.A. Power2 1 Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States 2 Community Health Sciences, Boston University School of Public Health, Boston, MA, United States Aims: To assess whether adolescents in low-income, urban areas are less likely to use marijuana as compared to the general population of adolescents. Methods: We systematically reviewed articles from 1997 to 2012, that focused onUS youth aged 12–18 in urban areas. Samples of youth who were incarcerated, in substance abuse treatment, or homeless were excluded. Results:We identified 39 unique articles that met review criteria. Just 10.3% of the articles focused specifically on marijuana use, whereas 51.3% considered marijuana along with other substances. The final 38.5% reported marijuana use prevalence, though marijuana was not a major focus of the study. More than half (53.8%) of the studies conducted analysis using cross-sectional data, 41% used longitudinal data, and 2% used other methods or a combination of both cross-sectional and longitudinal data. Methods researchers used to assess marijuana use varied greatly. Of the 39 articles identified, 14 studies requested adolescents to report past 30-day marijuana use. Researchers recruited the majority of the participants in the selected studies in school settings (53.8%) andprimarily included racial and ethnic minorities. Clinical based urban samples tended to report higher use of marijuana than school based samples, but this was not consistent or could not be comparatively determined due to variation in data collection methods. Conclusions: Overall, populations of urban adolescents report marijuana use at levels similar to the general population. There is still much to be understood about marijuana prevalence among urban adolescents; contextual geographical and community differences may impact marijuana prevalence more than other indicators. Financial Support: The content is the sole responsibility of the authors and does not necessarily represent the official views of the NIH. Support for this publication was provided by a grant to Dr. Renee M. Johnson from the National Institute on Drug Abuse (K01DA031738). http://dx.doi.org/10.1016/j.drugalcdep.2014.09.322 Effects of training and implementation experience on clinical skills involved in delivering Contingency Management Brinn E. Jones, Bryan Hartzler Alcohol & Drug Abuse Institute, University of Washington, Seattle, WA, United States Aims: Contingency Management (CM) is efficacious in addiction treatment and requires clinicians to perform a variety of skills during client contacts. While there is data to suggest that training improves overall CM delivery skills, little is known about how trainingmaydifferentially impact specific skill areas, andwhat skill areas merit greater emphasis in training. This study reports the effects of training and 90 days of CM implementation experience on the delivery skills of clinicians working at a community based opiate treatment program. Methods: Staff (N=16) participated in a 16-hour trainingworkshop, dispersed as four weekly half-day sessions at their clinic, and completed standardized patient (SP) intervention assessments one week prior, oneweek following training, and at a follow-up assessment after a 90-day period of trial implementation. Two sets of repeated-measures analysis of variance (RM-ANOVA) were conducted. The first, focused on immediate training impacts, assessed temporal change in CM skill areas from preto post-training. The second, focused on eventual impact of training and implementation experience, assessed temporal change from pre-training to follow-up. Given the sample size, corresponding sets of Cohen’s D for dependent measures were also computed. Results: Across individual skill areas, RM-ANOVA were statistically significant (p< .01). All of the immediate training effects were robust (d= .76–2.49), as were eventual effects of training + implementation (d= .89–2.63). Interestingly, eventual effect sizes were greater for 4 of the 6 skill areas, suggesting additive effects of training and implementation experience. Conclusions: Findings indicate robust, durable effects of training on CM delivery that are evident at the 90-day follow-up. Furthermore, it appears that the clinicians had greater improvement of CM delivery at follow-up indicating the potential that experience aided in clinician’s ability to deliver CM. However, this was not uniform over all skill areas. Financial Support: K23 DA025678. http://dx.doi.org/10.1016/j.drugalcdep.2014.09.323 Adolescent attachment and substance use: Concurrent and prospective links Jason D. Jones, Nadia Bounoua, Lauren Pandes-Carter, C.W. Lejuez, Jude Cassidy University of Maryland, College Park, College Park,