Comprehensive Interventions for Reducing Cannabis Use

Judit Tirado-Muñoz; Juan I. Mestre-Pintó; Magí Farré; Francina Fonseca; Marta Torrens

Disclosures

Curr Opin Psychiatry. 2018;31(4):315-323. 

In This Article

Conclusion and Discussion

Several interventions, including different approaches, have been identified for potentially reducing cannabis use among high-risk and low-risk cannabis users. Regarding preventive interventions, the meta-analysis provide support for the use of interactive school-based programmes to prevent cannabis use, even though recent RCT's have not been identified. This means these types of interventions might be an effective strategy to consider among young students to prevent early initiating of cannabis use, and also considering cannabis use have been found increasing with age. Further research is still needed with quality study designs to discriminate which modality, preventive programmes contents and instructors are the most appropriate to consider.

On the other hand, psychosocial interventions (therapist-assisted) provided moderate evidence for reducing cannabis use: a recent study supported the use of motivational interviewing (PNC)[20] in reducing the probability of abstinence withdrawal and heavy cannabis use, while a brief motivational intervention delivered by GPs only shows efficacy for young and moderate users.[19] An explanation why intervention was more effective among heavy cannabis users could be due to heavier users may be more engaged in the treatment because of the negative consequences derived from consumption, which increases the motivation of adolescents to change their cannabis use. Physicians should ask all patients about their cannabis use during their routine care;[28] approaching cannabis use in primary care is a great opportunity to identify and address cannabis use among nonseeking treatment cannabis users. However, two other studies did not support the use of psychosocial-therapist-assisted interventions. An explanation could be that both interventions focused not only on reducing cannabis use but also alcohol and other drug use, thus efficacy might be confounded by them.

Computerized interventions seem to be the most promising interventions for reducing cannabis use, with meta-analysis and the single study supporting its use. The interest of these types of interventions for cannabis treatment has increased in the past years. It has certain advantages over other types of interventions, such as high cost-effectiveness, easy dissemination, the fact that potential barriers related to intervention training and staff time dedication are diminished,[29] and that could improve accessibility to therapy in cases in which although recognition of cannabis problems, users might not be prepared to attend certain drug treatment settings. Furthermore, one of the meta-analysis[15] has demonstrated the long-term efficacy (maintained at 6-month follow-up) of these types of interventions. A study protocol of a multisession, home-delivered alcohol and CUD intervention (Internet-based attentional bias modification – iABM) to be added to the CBT usual treatment [treatment as usual (TAU)][30] was identified. A total sample of 213 alcohol or cannabis dependent outpatients will be randomized to one of the three study arms (TAU + iABM; TAU + placebo or TAU-only). Primary outcomes will be alcohol and cannabis use, craving and substance use relapse. No results are available at this stage, but this intervention could be a promising opportunity as a supplement to the usual treatment.

Regarding pharmacological treatments for CUD, findings from the review,[17] support taking into consideration certain characteristics of dependent cannabis users (sex, severity of cannabis use, impulsivity) when approaching a pharmacological treatment to improve treatment outcomes. In some cases, the selected outcome measures or the study design is not really accurately connected to the basis behind the selection of candidate medications. In this sense, authors from the pharmacological treatment review, consider the length of use each day or frequency of days of use per week as the most reliable outcomes to be used. Thus, the recent meta-analysis highlights the need to improve pharmacological study designs, outcome measures selected, results interpretation, selecting candidate medications or even consider medication combinations (different mechanisms of action) to generate improvements among severe CUD patients. Moreover, differences identified between treatment-seeking and nontreatment-seeking cannabis users must be taken into account as they may also impact the effects of medication.

In addition to the treatment options in reducing CUD among different groups of patients depending on age, frequency and severity of cannabis use; some recommendations supporting low-risk cannabis use have been highlighted in the current review. As scientific literature has found, there are multiple risk factors for cannabis-related health problems which may be modified by users. Given the changes in laws, it was an acute need for developing public health tools such as the LRCUG[18] for nonseeking treatment users capable to modify their risk behaviours associated with cannabis use. From a public health perspective, harm reduction approaches have proven to be useful in preventing low-risk cannabis users from adopting more risky behaviors and thus becoming problematic users.[31]

To date, a relevant number of reviews and RCT's have been recently published suggesting the increased interest in improving cannabis-treatment options and minimize adverse health effects, even though definitive evidence is still lacking. Considering the four different approaches resulting from the search and reported in this review (whether more preventive, psychological, pharmacological and risk reduction approach), overall promising results has been found in certain interventions and for certain types of users. Thus, the need for making further progress in treatment options for cannabis use has been also reflected in this review.

Finally, cannabis use and the transition to a CUD could be affected by several factors such as socio-demographic predictors, age of onset, other risk factors such as psychiatric comorbidity vulnerability, changes in laws and so on.[32,33] In particular, changes in marijuana legislation seem to be affecting cannabis use prevalence, cannabis potency (which has progressively increased over the past few decades)[34] and related educational, health and economic outcomes. Furthermore, decriminalisation of marijuana for nonmedical purposes encourages harm reduction approaches, providing users with knowledge and strategies to minimize as much as possible adverse health outcomes associated with cannabis use. For these reasons, interventions must address all these aspects, comprehensively, to prevent, reduce or minimize cannabis use and its effects among different population groups (high-risk and low-risk users, seeking treatment or not, men or women, etc.). Further research with adequately powered trials assessing interventions for reducing cannabis use remains a need, before establishing definitive treatment recommendations. Furthermore, more studies evaluating the impact of public health interventions within the emerging cannabis policy paradigm of legalization are also needed.

processing....