Real-Time Tracking Identified What Predicted Cannabis Relapse in Young Adults

Nearly 3 in 4 participants (73.5%) lapsed during attempted abstinence. The combination of negative effect expectancies, perceived family support, confidence to abstain, and situational permissibility during use was highly accurate in predicting who would lapse. Greater percent of days with use, easy accessibility, and situational permissibility were each associated with lapse.

34 young adults aged 18-25 using marijuana 5+ days/week completed ecological momentary assessment (EMA) via smartphone multiple times daily for two weeks of regular use, then two weeks of attempted abstinence.

Most young heavy cannabis users who try to quit relapse on their own. Understanding the real-time factors that predict relapse could enable personalized digital interventions that provide support at the moments when people are most vulnerable.

This study demonstrates that smartphone-based real-time monitoring can capture meaningful predictors of cannabis relapse that traditional surveys miss. As digital health tools become more sophisticated, this approach could enable just-in-time interventions.

Small sample (n=34). Self-selected participants willing to attempt abstinence and use monitoring technology. Two-week abstinence period is short. EMA compliance may vary.