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Study breakdown

Digital interventions reduced young adults cannabis use by nearly 7 days per month

Meta AnalysisModerate evidence
The takeaway

A meta-analysis of 19 RCTs found digital interventions for young adults reduced cannabis use frequency by about 7 days per month at 3-month follow-up, with feedback on behavior being the most common active ingredient.

People interested in digital health approaches to reducing cannabis use among young adults.

6.79 fewer days of cannabis use per month with digital interventions

What the researchers found

Digital interventions reduced cannabis use frequency by 6.79 days in the previous month at 3-month follow-up (95% CI: -9.59 to -4.00, p<.001) compared to controls. 184 behavior change techniques were identified across interventions (range 5-19 per intervention). Feedback on behavior was the most common technique (89% of interventions). Most interventions were web-based.

Why it matters

Young adults are the heaviest cannabis users but least likely to seek traditional treatment. Digital interventions can reach this population at scale, and this meta-analysis shows they produce meaningful reductions in use frequency.

The numbers in context

19 RCTs, 6,710 participants. Cannabis use reduction: 6.79 fewer days/month at 3 months (p<.001). 184 behavior change techniques identified. Feedback on behavior used in 89% of interventions. 47% of studies showed intervention effect on frequency.

How the study worked

Systematic review and meta-analysis of 19 RCTs (n=6,710) from 7 databases through February 2023. Included web- or mobile-based interventions for cannabis use in community-dwelling young adults (16-35). Random-effects model with standardized mean differences. Behavior change technique coding applied.

What this study cannot tell us

High heterogeneity across studies. Mix of passive and active control conditions. Most interventions were web-based, limiting conclusions about mobile apps specifically. 3-month follow-up may not reflect long-term outcomes. Behavior change technique analysis identifies common ingredients but not which are most effective.

How to read the evidence

Systematic review and meta-analysis of 19 RCTs with large pooled sample. Limited by heterogeneity across studies and short follow-up periods.

When this study was published

Published in 2024 in the Journal of Medical Internet Research, covering literature through February 2023.

The bigger picture

The digital intervention field for cannabis is growing rapidly. This meta-analysis establishes that web and mobile approaches can meaningfully reduce use in young adults, though questions remain about optimal dosing, duration, and which specific techniques drive the effect.

Questions still open

  • What is the optimal duration and frequency for digital cannabis interventions? Which specific behavior change techniques drive the reduction in use? Would digital interventions work for heavier users or those with CUD?

Common questions

Can an app help reduce cannabis use?
This meta-analysis found that web and mobile-based interventions reduced cannabis use by about 7 fewer days per month in young adults. Most effective programs included personalized feedback about the user's cannabis use behavior.
How much did digital interventions reduce cannabis use?
On average, young adults using digital interventions used cannabis about 7 fewer days per month at 3-month follow-up compared to those who received no intervention or minimal information.

Read the original research

Digital Interventions for Recreational Cannabis Use Among Young Adults: Systematic Review, Meta-Analysis, and Behavior Change Technique Analysis of Randomized Controlled Studies.

Journal of medical Internet research, 26, e55031

Citation

Côté, José; Chicoine, Gabrielle; Vinette, Billy; Auger, Patricia; Rouleau, Geneviève; Fontaine, Guillaume; Jutras-Aswad, Didier. (2024). Digital Interventions for Recreational Cannabis Use Among Young Adults: Systematic Review, Meta-Analysis, and Behavior Change Technique Analysis of Randomized Controlled Studies.. Journal of medical Internet research, 26, e55031. https://doi.org/10.2196/55031

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