In the last decade, several programs for the treatment of cannabis-related disorders were developed. Until now, no information is available on the efficacy of Internet-based counseling approaches for this target group. This article describes the evaluation of "quit the shit," a web-based intervention developed to help young people to quit or reduce their cannabis use significantly. Cannabis users seeking web-based treatment were included in a two-arm controlled trial conducted on a website for drug-related information and prevention. After the baseline assessment, members of the treatment condition were randomized to a 50-day intervention program. Other trial participants were put on a waiting list. A post-test was conducted 3 months after randomization. Of all 1,292 subjects included in the trial, a total of 206 participants took part at the post-test. Per-protocol- and intention-to-treat analyses were conducted. Members of the treatment condition showed a significantly stronger reduction in cannabis use (primary outcome) than the control group. In the per-protocol analyses, moderate-to-strong effects were found for the reduction of the frequency and the reduction of the quantity of consumed cannabis. Small-to-moderate effects were observed on the secondary outcomes (use-related self-efficacy, anxiety, depression, and life satisfaction). Despite limitations concerning the interpretation of the results, the intervention seems to offer an effective treatment option for persons with cannabis-related problems.

In 1998, a total of 3,503 visitors of techno parties in Amsterdam, Berlin, Madrid, Prague, Rome, Vienna and Zurich were interviewed. With this data, a subtly differentiated portrait of the techno party visitor was drawn, especially with a view to his/her involvement in the scene and the use of psychotropic substances. First of all, the results show that the use of illegal substances such as cannabis, ecstasy, amphetamines and cocaine is relatively widespread in the examined techno party scenes. A central characteristic of the drug use could be described as the polydrug occasional user model characterised by the occasional use of diverse substances that are usually taken together. The significance of the findings is discussed with regard to the practice of drug prevention.

BackgroundExcessive alcohol use is a widespread problem in many countries, especially among young people. To reach more people engaging in high-risk drinking behaviors, a number of online programs have been developed in recent years. Change Your Drinking is a German, diary-based, fully automated alcohol intervention. In 2010, a revised version of the program was developed. It is more strongly oriented to concepts of relapse prevention than the previous version, includes more feedback, and offers more possibilities to interact with the program. Moreover, the program duration was extended from 10 to 14 days.ObjectiveThis paper examines whether the revised version of Change Your Drinking is more effective in reducing alcohol consumption than the original version.MethodsThe effectiveness of both program versions was compared in a Web-based, open, randomized controlled trial with follow-up surveys 6 weeks and 3 months after registration. Participants were recruited online and were randomly assigned to either the original or the revised version of Change Your Drinking. The following self-assessed outcomes were used: alcohol use days, alcohol intake in grams, the occurrence of binge drinking and risky drinking (all referring to the past 7 days prior to each survey), and the number of alcohol-related problems.ResultsA total of 595 participants were included in the trial. Follow-up rates were 58.0% after 6 weeks and 49.6% after 3 months. No significant group differences were found in any of the outcomes. However, the revised version was used by more participants (80.7%) than the original version (55.7%). A significant time effect was detected in all outcomes (alcohol use days: P=.002; alcohol intake in grams: P<.001; binge drinking: P<.001; alcohol-related problems: P=.004; risky drinking: P<.001).ConclusionsThe duration and complexity of the program played a minor role in reducing alcohol consumption. However, differences in program usage between the versions suggest the revised version was more attractive to participants.Trial RegistrationInternational Standard Randomized Controlled Trial Number (ISRCTN): 31586428; http://www.controlled-trials.com/ISRCTN31586428/ (Archived by WebCite at http://www.webcitation.org/6BFxApCUT)

BackgroundDigital interventions show promise in reducing problematic cannabis use. However, little is known about the effect of moderators in such interventions. The therapist-guided internet intervention Quit the Shit provides 50 days of chat-based (synchronous) and time-lagged (asynchronous) counseling.ObjectiveIn the study, we examined whether the effectiveness of Quit the Shit is reduced by shortening the program or by removing the chat-based counseling option.MethodsWe conducted a purely Web-based randomized experimental trial using a two-factorial design (factor 1: real-time-counseling via text-chat: yes vs no; factor 2: intervention duration: 50 days vs 28 days). Participants were recruited on the Quit the Shit website. Follow-ups were conducted 3, 6, and 12 months after randomization. Primary outcome was cannabis-use days during the past 30 days using a Timeline Followback procedure. Secondary outcomes were cannabis quantity, cannabis-use events, cannabis dependency (Severity of Dependence Scale), treatment satisfaction (Client Satisfaction Questionnaire), and working alliance (Working Alliance Inventory-short revised).ResultsIn total, 534 participants were included in the trial. Follow-up rates were 47.2% (252/534) after 3 months, 38.2% (204/534) after 6 months, and 25.3% (135/534) after 12 months. Provision of real-time counseling (factor 1) was not significantly associated with any cannabis-related outcome but with higher treatment satisfaction (P=.001, d=0.34) and stronger working alliance (P=.008, d=0.22). In factor 2, no significant differences were found in any outcome. The reduction of cannabis use among all study participants was strong (P<.001, d≥1.13).ConclusionsThe reduction of program length and the waiver of synchronous communication have no meaningful impact on the effectiveness of Quit the Shit. It therefore seems tenable to abbreviate the program and to offer a self-guided start into Quit the Shit. Due to its positive impact on treatment satisfaction and working alliance, chat-based counseling nevertheless should be provided in Quit the Shit.Trial RegistrationInternational Standard Randomized Controlled Trial Number ISRCTN99818059; http://www.isrctn.com/ISRCTN99818059 (Archived by WebCite at http://www.webcitation.org/6uVDeJjfD)

BackgroundTrials demonstrate the effectiveness of web-based interventions for cannabis-related disorders. For further development of these interventions, it is of vital interest to identify user characteristics which predict treatment response.MethodsData from a randomized factorial trial on a web-based intervention for cannabis-users (n = 534) was reanalyzed. As potential predictors for later treatment response, 31 variables from the following categories were tested: socio-demographics, substance use and cognitive processing. The association of predictors and treatment outcome was analyzed using unbiased recursive partitioning and represented as classification tree. Predictive performance of the tree was assessed by comparing its cross-validated results to models derived with all-subsets logistic regression and random forest.ResultsGoal commitment (p < .001), the extent of self-reflection (p < .001), the preferred effect of cannabis (p = .005) and initial cannabis use (p = .015) significantly differentiate between successful and non-successful participants in all three analysis methods. The predictive accuracy of all three models is comparable and modest.ConclusionsParticipants who commit to quit using cannabis, who at least have moderate levels of self-reflection and who prefer mild intoxicating effects were most likely to respond to treatment. To predict treatment response on an individual level, the classification tree should only be used as one of several sources of information.Trial registration: http://www.isrctn.com/ISRCTN99818059