The use of contingency management and motivational/skills-building therapy to treat young adults with marijuana dependence. J Consult Clin Psychol

Division of Substance Abuse, Yale University School of Medicine, West Haven, CT 06516, USA.
Journal of Consulting and Clinical Psychology (Impact Factor: 4.85). 11/2006; 74(5):955-66. DOI: 10.1037/0022-006X.74.5.955
Source: PubMed


Marijuana-dependent young adults (N = 136), all referred by the criminal justice system, were randomized to 1 of 4 treatment conditions: a motivational/skills-building intervention (motivational enhancement therapy/cognitive-behavioral therapy; MET/CBT) plus incentives contingent on session attendance or submission of marijuana-free urine specimens (contingency management; CM), MET/CBT without CM, individual drug counseling (DC) plus CM, and DC without CM. There was a significant main effect of CM on treatment retention and marijuana-free urine specimens. Moreover, the combination of MET/CBT plus CM was significantly more effective than MET/CBT without CM or DC plus CM, which were in turn more effective than DC without CM for treatment attendance and percentage of marijuana-free urine specimens. Participants assigned to MET/CBT continued to reduce the frequency of their marijuana use through a 6-month follow-up.

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Available from: Kathleen Carroll,
    • "Arguably, the most effective outpatient treatments for CUD combine Motivational Enhancement Therapy (MET), CBT, and Contingency Management (CM; Budney et al., 2006; Carroll et al., 2006, 2012; Kadden et al., 2007; Litt et al., 2013). Although limitations have been raised with real-world implementation of such interventions due to availability and cost (Carroll, 2014), recent studies suggest that computer-assisted versions of these treatments may enhance access and reduce cost without sacrificing efficacy (Budney et al., 2011, 2015; Kay-Lambkin et al., 2009, 2011). "
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    ABSTRACT: Cannabis users frequently report concurrent tobacco use, and tobacco use is associated with poorer outcomes during treatment for cannabis use disorders (CUD). Interventions that simultaneously target both tobacco and cannabis use disorders may enhance cessation outcomes for either or both substances. This study evaluated an intervention integrating highly effective treatments for cannabis and tobacco use disorders. Thirty-two participants meeting diagnostic criteria for CUD and reporting daily tobacco use were enrolled in a 12-week computer-assisted behavioral treatment for CUD. Participants were encouraged to participate in a tobacco intervention that included a computer-assisted behavioral treatment tailored for tobacco and cannabis co-users, and nicotine-replacement therapy (NRT). Cannabis and tobacco outcomes were evaluated using descriptive statistics and were compared to a historical control group that received treatment for CUD but not tobacco. Participants achieved 3.6±4.3 consecutive weeks of cannabis abstinence, which was comparable to the historical control group (3.1±4.4). A majority of the sample (78%) completed at least one tobacco module and 44% initiated NRT. Over half (56%) initiated tobacco quit attempts, and 28% were tobacco abstinent for at least two consecutive weeks. Participants showed greater reduction in tobacco use (cigarettes per day) than the historical control group, but differences in tobacco abstinence rates during the final month of treatment were not statistically significant (12.5% vs. 4%). Findings suggest that providing a tobacco intervention during treatment for CUD is feasible and may positively impact tobacco use without negatively affecting cannabis use outcomes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    Drug and alcohol dependence 08/2015; DOI:10.1016/j.drugalcdep.2015.08.001 · 3.42 Impact Factor
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    • "Third, rate of relapse, that is, change in abstinence over the posttreatment period, did not differ among the three conditions, which supports the hypothesis that treatment effects on cannabis abstinence over time would not differ between THERAPIST and COMPUTER delivered MET/CBT/CM conditions. This observation , if replicated, provides a particularly important contribution to the effectiveness literature because some, but not all, prior studies of therapist-delivered MET/CBT/CM have demonstrated that the MET/CBT component enhanced maintenance of posttreatment abstinence outcomes engendered with CM (Budney et al., 2006; Carroll et al., 2006, 2012; Kadden et al., 2007; Rawson et al., 2006). "
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    ABSTRACT: Computer-assisted behavioral treatments hold promise for enhancing access to and reducing costs of treatments for substance use disorders. This study assessed the efficacy of a computer-assisted version of an efficacious, multicomponent treatment for cannabis use disorders (CUD), that is, motivational enhancement therapy, cognitive-behavioral therapy, and abstinence-based contingency-management (MET/CBT/CM). An initial cost comparison was also performed. Seventy-five adult participants, 59% Black, seeking treatment for CUD received either, MET only (BRIEF), therapist-delivered MET/CBT/CM (THERAPIST), or computer-delivered MET/CBT/CM (COMPUTER). During treatment, the THERAPIST and COMPUTER conditions engendered longer durations of continuous cannabis abstinence than BRIEF (p < .05), but did not differ from each other. Abstinence rates and reduction in days of use over time were maintained in COMPUTER at least as well as in THERAPIST. COMPUTER averaged approximately $130 (p < .05) less per case than THERAPIST in therapist costs, which offset most of the costs of CM. Results add to promising findings that illustrate potential for computer-assisted delivery methods to enhance access to evidence-based care, reduce costs, and possibly improve outcomes. The observed maintenance effects and the cost findings require replication in larger clinical trials. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
    Psychology of Addictive Behaviors 05/2015; 29(3). DOI:10.1037/adb0000078 · 2.09 Impact Factor
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    • "Improvements were largely maintained over the follow-up period. Carroll et al. (2006) randomized 136 cannabis dependent adults (aged 18–25) to 8 weeks of (a) CBT þ ME þ CM, (b) CBT þ ME, or (c) TAU (Carroll et al., 2006). There was a main effect for more negative urine specimens . "
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    ABSTRACT: Narrative reviews conclude that behavioral therapies (BTs) produce better outcomes than control conditions for cannabis use disorders (CUDs). However, the strength and consistency of this effect has not been directly empirically examined. The present meta-analysis combined multiple well-controlled studies to help clarify the overall impact of behavioral interventions in the treatment of CUDs. A comprehensive literature search produced 10 randomized controlled trials (RCTs; n = 2,027) that were included in the final analyses. Analyses indicated an effect of BTs (including contingency management, relapse prevention, and motivational interviewing, and combinations of these strategies with cognitive behavioral therapy) over control conditions (including waitlist [WL], psychological placebo, and treatment as usual) across pooled outcomes and time points (Hedges' g = 0.44). These results suggest that the average patient receiving a behavioral intervention fared better than 66% of those in the control conditions. BT also outperformed control conditions when examining primary outcomes alone (frequency and severity of use) and secondary outcomes alone (psychosocial functioning). Effect sizes were not moderated by inclusion of a diagnosis (RCTs including treatment-seeking cannabis users who were not assessed for abuse or dependence vs. RCTs including individuals diagnosed as dependent), dose (number of treatment sessions), treatment format (either group vs. individual treatment or in-person vs. non-in-person treatment), sample size, or publication year. Effect sizes were significantly larger for studies that included a WL control comparison versus those including active control comparisons, such that BT significantly outperformed WL controls but not active control comparisons.
    Evaluation &amp the Health Professions 04/2014; 38(1). DOI:10.1177/0163278714529970 · 1.91 Impact Factor
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