Abstract
BACKGROUND: With the rising prevalence of daily cannabis use in the U.S., more individuals may seek treatment for adverse outcomes (e.g., cannabis use disorder) arising from frequent cannabis use. Adaptive interventions leverage self-reported motives for cannabis use to develop personalized support. Research has demonstrated that these motives can be collected on a yearly, monthly, or daily basis, and strongly predict both the frequency of cannabis use and associated adverse outcomes. METHODS: We employed a daily web survey over a 28-day period to assess daily motives and open-ended self-reported contexts of nonmedical cannabis use. Participants, aged 22-76 (n = 48, Mean = 48.8, SD = 17.1; 64 % female; 22 % African American), completed a baseline web survey on demographics and mental health and a follow-up web survey on mental health at present and cannabis use behaviors during the study. We applied latent transition analysis with random intercepts (RI-LTA) to analyze the data. RESULTS: In our descriptive analyses, we identified four types of transitions in weekly latent motive classes, particularly transitions toward motives dominated by sleep aid and cannabis availability. Participants experiencing these transitions reported higher subsequent cannabis use frequency. Open-ended contextual information revealed behaviors such as cannabis use related to managing sleep disturbances, anxiety triggered by daily stressors, and recovery from medical treatments (e.g., chemotherapy). CONCLUSIONS: Our findings underscore the value of monitoring short-term transitions in cannabis use motives and contexts. This approach can inform the timing and content of adaptive interventions, proactively addressing the contexts and motives to prevent adverse cannabis use outcomes. Additional replications of this approach using larger samples are needed.