Effectiveness of Digitally Delivered Interventions for Cannabis Use Reduction in Adults: An Individual Participant Data Meta-Analysis

Cannabis use disorder is one of the most common substance use disorders worldwide, and the associated public health issues are growing as cannabis becomes more widely legalized and accepted across different countries. Digitally delivered interventions, including web-based interventions, mobile applications and, blended formats combining digital components with human contact, have emerged as a scalable and accessible treatment option. While the overall body of evidence from randomized controlled trials (RCTs) shows that such interventions reduce cannabis use, conventional meta-analyses cannot reveal which individuals benefit most from which type of intervention and under what conditions. They also cannot account for the substantial heterogeneity in treatment response likely to exist among a diverse population of cannabis users. Individual participant data meta-analysis (IPDMA) overcomes these limitations by harmonizing raw participant-level data across primary studies and reanalyzing them using a common statistical framework. This approach provides substantially greater power for moderation analyses than any single trial or aggregate-level synthesis, enables proper adjustment for baseline covariates, and allows for the examination of individual-level predictors and effect modifiers of treatment outcome, dropout, and deterioration. The present study aims to conduct the first comprehensive IPDMA of digitally delivered interventions for cannabis use reduction in adults. By pooling and harmonizing participant-level data from eligible RCTs, we will estimate the overall effectiveness of digital cannabis interventions and systematically examine individual- and study-level moderators of treatment response. The findings are intended to advance evidence-based, personalized decision-making in digital cannabis treatment and to inform future clinical practice guidelines.