Abstract
BACKGROUND: Emerging adult (EA) cannabis use is associated with increased risk for health consequences. Just-in-time adaptive interventions (JITAIs) provide potential for preventing the escalation and consequences of cannabis use. Powered by mobile devices, JITAIs use decision rules that take the person's state and context as input, and output a recommended intervention (e.g., alternative activities, coping strategies). The mHealth literature on JITAIs is nascent, with additional research needed to identify what intervention content to deliver when and to whom. METHODS: Herein we describe the protocol for a pilot study testing the feasibility and acceptability of a micro-randomized trial for optimizing MiWaves mobile intervention app for EAs (ages 18-25; target N = 120) with regular cannabis use (≥3 times per week). Micro-randomizations will be determined by a reinforcement learning algorithm that continually learns and improves the decision rules as participants experience the intervention. MiWaves will prompt participants to complete an in-app twice-daily survey over 30 days and participants will be micro-randomized twice daily to either: no message or a message [1 of 6 types varying in length (short, long) and interaction type (acknowledge message, acknowledge message + click additional resources, acknowledge message + fill in the blank/select an option)]. Participants recruited via social media will download the MiWaves app, and complete screening, baseline, weekly, post-intervention, and 2-month follow-up assessments. Primary outcomes include feasibility and acceptability, with additional exploratory behavioral outcomes. CONCLUSION: This study represents a critical first step in developing an effective mHealth intervention for reducing cannabis use and associated harms in EAs.