首页|Trimbos Institute Reports Findings in Marijuana/Cannabis (Predicting cannabis us e moderation among a sample of digital self-help subscribers: A machine learning study)
Trimbos Institute Reports Findings in Marijuana/Cannabis (Predicting cannabis us e moderation among a sample of digital self-help subscribers: A machine learning study)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Marijuana/Cannabis is the subject of a report. According to news reporting from Utrecht, Netherlands, by NewsRx journalists, research stated, “For individuals who wish to reduce thei r cannabis use without formal help, there are a variety of self-help tools avail able. Although some are proven to be effective in reducing cannabis use, effect sizes are typically small.” The news correspondents obtained a quote from the research from Trimbos Institut e, “More insight into predictors of successful reduction of use among individual s who frequently use cannabis and desire to reduce/quit could help identify fact ors that contribute to successful cannabis use moderation. We analyzed data take n from a randomized controlled trial comparing the effectiveness of the digital cannabis intervention ICan to four online modules of educational information on cannabis. For the current study, we included 253 participants. Success was defin ed as reducing the grams of cannabis used in the past 7 days at baseline by at l east 50 % at 6-month follow-up. To train and evaluate the machine learning models we used a nested k-fold cross-validation procedure. The results show that the two models applied had comparable low AUROC values of .61 (Random Forest) and .57 (Logistic Regression). Not identifying oneself as a cannabis use r, not using tobacco products, high levels of depressive symptoms, high levels o f psychological distress and high initial cannabis use values were the relativel y most important predictors for success, although overall the associations were not strong.”
UtrechtNetherlandsEuropeCyborgsD rugs and TherapiesEmerging TechnologiesMachine LearningMarijuana/Cannabis
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