Identifying Subgroups of Cannabis Users Based on Help-Seeking Preferences: A Latent Class Analysis.

BACKGROUND: The majority of people with cannabis use disorder do not seek treatment. If we were able to gain more insight into different subgroups of cannabis users based on help-seeking preferences, we could use this information to inform the development and promotion of interventions targeted at specific subgroups of cannabis users, to ultimately narrow the treatment gap. METHODS: An online survey was conducted among 1,015 Dutch frequent cannabis users (18-72 years) to assess their cannabis use, help-seeking preferences, psychopathology, and psychological distress. Latent class analysis was used to identify classes of cannabis users based on their help-seeking preferences. Differences between the identified classes in terms of sociodemographics, cannabis use, and psychopathology were examined. RESULTS: We identified four classes with distinct preferences for support. Class 1 ("no support/only social," n = 548) had a low probability of finding any form of support appealing other than social support. Class 2 ("online help," n = 170) had relatively high probabilities of finding online help appealing. Class 3 ("GP/outpatient," n = 208) had a relatively high probability of finding support from the general practitioner and outpatient substance use disorder treatment appealing. Class 4 ("all sources," n = 89) had moderate to high probabilities for all sources of support. In terms of sociodemographics, differences between the classes were found with regard to gender and level of education. The classes were fairly similar with regard to cannabis use, only the "online help" class scored significantly lower on both cannabis use frequency and quantity compared to most of the other classes. In terms of psychopathology, the "GP/outpatient" class and the "all sources" class experienced more cannabis use-related problems and were more likely to report multiple past quit attempts than the "online help" class and the "no support/only social" class. CONCLUSIONS: Our study shows that there is a lot of inter-individual variation in how appealing various forms of help are to cannabis users. Our findings emphasize the importance of promoting a variety of treatment modalities for cannabis users, including real-life and digital options, and indicate what might appeal to whom.

Predicting cannabis use moderation among a sample of digital self-help subscribers: A machine learning study.

BACKGROUND: For individuals who wish to reduce their cannabis use without formal help, there are a variety of self-help tools available. Although some are proven to be effective in reducing cannabis use, effect sizes are typically small. More insight into predictors of successful reduction of use among individuals who frequently use cannabis and desire to reduce/quit could help identify factors that contribute to successful cannabis use moderation. METHODS: We analyzed data taken 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 defined as reducing the grams of cannabis used in the past 7 days at baseline by at least 50 % at 6-month follow-up. To train and evaluate the machine learning models we used a nested k-fold cross-validation procedure. RESULTS: 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 user, not using tobacco products, high levels of depressive symptoms, high levels of psychological distress and high initial cannabis use values were the relatively most important predictors for success, although overall the associations were not strong. CONCLUSIONS: Our study found only modest prediction accuracy when using machine learning models to predict success among individuals who use cannabis and desire to reduce/quit and show interest in digital self-help tools.

A guided digital intervention to reduce cannabis use: The ICan randomized controlled trial.

AIMS: To test the effectiveness of a digital intervention to reduce cannabis use (ICan) with adherence-focused guidance compared with educational cannabis information. DESIGN: This was a single-blind randomized controlled trial. Follow-up clinical outcome measurements took place 3 and 6 months after randomization. SETTING: The trial was conducted in the Netherlands. The intervention and guidance took place on-line, with recruitment via Facebook/Instagram advertisement campaigns. PARTICIPANTS: Inclusion criteria were ≥ 18 years, cannabis use on ≥ 3 days/week, the desire to reduce/quit cannabis and using a smartphone. Participants were allocated to either ICan (n = 188) or control (n = 190) (69% male, mean age = 27.5 years). INTERVENTION AND COMPARATOR: ICan is a mobile (web-)application based on motivational interviewing and cognitive behavioural therapy and includes three main components: screening, brief intervention (six modules) and referral to treatment. The control condition consisted of non-interactive educational cannabis information. MEASUREMENTS: Primary outcome was the number of cannabis use days in the 7 days prior to the 6-month follow-up measurement. Secondary outcome measures at 3- and 6-month follow-up were the number of grams of cannabis used and attitudes towards seeking professional help for cannabis use related problems. FINDINGS: Intention-to-treat analysis showed that 6 months after randomization the mean number of cannabis use days in the past 7 days was reduced in both conditions (time P < 0.001), with no significant group × time interaction effect [ICan = 4.17 days, control = 4.31 days, Cohen's dbetween = 0.06, 95% confidence interval (CI) = -0.15, 0.26, P = 0.93]. Three months after randomization the mean number of grams used in the past 7 days was reduced in both conditions, with a significantly larger reduction in the ICan condition (P = 0.009, Cohen's dbetween = 0.15). At 6-month follow-up the significant group × time interaction effect was no longer present (P = 0.30). In both conditions, attitudes towards seeking professional help remained virtually unchanged over time. CONCLUSIONS: A digital intervention to reduce cannabis use (ICan) was more effective than non-interactive educational cannabis information in reducing grams of cannabis used over 3 months, but not more effective at reducing cannabis use days at 6-month follow-up. Cannabis use reductions were maintained in both conditions between 3 and 6 months' follow-up.

ICan, an Internet-based intervention to reduce cannabis use: study protocol for a randomized controlled trial.

BACKGROUND: Heavy cannabis use is associated with adverse physical and mental health effects. Despite available effective treatments, the majority of heavy cannabis users does not seek professional help. Web-based interventions can provide an alternative for cannabis users who are reluctant to seek professional help. Several web-based cannabis interventions are effective in reducing cannabis use; however, the effect sizes are typically small and attrition rates are typically high. This suggests that web-based programs can be an effective cannabis use intervention for some, while others may need additional substance use treatment after completing a web-based intervention. Therefore, it is important that web-based interventions do not solely focus on reducing cannabis use, but also on improving attitudes towards substance use treatment. The Screening Brief Intervention and Referral to Treatment (SBIRT) approach appears to be well suited for the purpose of reducing cannabis use and improving substance use treatment utilization. Based on the SBIRT approach-and based on cognitive behavioral therapy (CBT) and motivational interviewing (MI)-we developed the Internet-based cannabis reduction intervention ICan. METHODS/DESIGN: This protocol paper presents the design of a randomized controlled trial (RCT) in which we evaluate the effectiveness of the ICan intervention compared to four online modules of educational information on cannabis in a sample of Dutch frequent cannabis users. The primary outcome measure is frequency of cannabis use. Secondary outcome measures include the quantity of cannabis used (grams), the attitudes towards seeking help and the number of participants who enter specialized treatment services for cannabis use-related problems. DISCUSSION: To the best of our knowledge, ICan is the first Internet-based intervention for cannabis users that combines screening, a brief intervention-based on CBT and MI-and referral to treatment options. TRIAL REGISTRATION: The study is registered in the Netherlands Trial Register; identifier NL7668 . Registered on 17 April 2019.