Daily cannabis use motives shift over time — particularly toward sleep and availability reasons — and these transitions predict higher subsequent use, suggesting adaptive interventions could target critical moments.
Digital health intervention designers, cannabis treatment researchers, ecological momentary assessment methodologists
What the researchers found
Four types of weekly motive transitions were identified, with shifts toward sleep-aid and cannabis-availability-dominated motives predicting higher subsequent use frequency. Open-ended data revealed cannabis use for managing sleep disturbances, daily stressor-triggered anxiety, and recovery from medical treatments like chemotherapy.
Why it matters
Static assessments miss the dynamic nature of cannabis use motives. Real-time monitoring of motive shifts could enable just-in-time interventions — sending support when a person transitions toward higher-risk patterns.
The numbers in context
48 participants over 28 days. Four types of weekly motive transitions identified. Sleep aid and availability motives most associated with increased use frequency. Participants aged 22-76, mean 48.8 years.
How the study worked
28-day daily web survey of 48 participants (aged 22-76, 64% female, 22% African American) with baseline and follow-up mental health assessments. Latent transition analysis with random intercepts (RI-LTA) modeled weekly motive class transitions.
What this study cannot tell us
Very small pilot sample (n=48). Convenience sample may not be representative. 28-day period may be too short to capture all motive transition patterns. Daily surveys may themselves influence behavior (reactivity).
How to read the evidence
Innovative methodology demonstrating proof-of-concept, but very small sample limits statistical conclusions.
When this study was published
Published 2026, piloting adaptive intervention methodology for cannabis use.
The bigger picture
This pilot demonstrates the feasibility of a paradigm shift in cannabis intervention: from periodic clinic-based assessment to continuous real-time monitoring that can trigger adaptive support exactly when patterns start shifting toward problematic use.
Questions still open
- What specific interventions should be triggered by motive transitions? Would app-based real-time monitoring be acceptable to cannabis users? Could machine learning predict harmful transitions before they happen?
Common questions
Why do reasons for cannabis use change day to day?
Could an app help people manage cannabis use?
Read the original research
Daily web survey data collection of time-varying cannabis use motives and contexts, with implications for adaptive interventions: A pilot study.
Drug and alcohol dependence, 278, 112974
Citation
Ma, Yongchao; West, Brady T; McCabe, Sean Esteban. (2026). Daily web survey data collection of time-varying cannabis use motives and contexts, with implications for adaptive interventions: A pilot study.. Drug and alcohol dependence, 278, 112974. https://doi.org/10.1016/j.drugalcdep.2025.112974
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