# Feasibility/Acceptability of a Brief Motivational Intervention Integrating Online Personalized Feedback & Tailored Text Messages for Frequent/High-Intensity Cannabis Use in Post-Legalization Landscape

> **NIH NIH R34** · UNIVERSITY OF WASHINGTON · 2024 · $311,000

## Abstract

ABSTRACT
Cannabis is a widely used psychoactive substance among young adults (YAs), with ~44% using in the past
year. Daily use by YAs not attending college (14.5%) is 3x the prevalence of daily use by college attending
peers (4.7%). Cannabis is associated with acute and longer-term consequences. A growing concern among
researchers and clinicians is of frequent and/or high-intensity use (i.e., daily/near daily use, use multiple times
a day, and use of higher potency THC products). Although published research has grown exponentially in the
last decade regarding correlates and consequences of cannabis, development and evaluation of efficacious
brief interventions to reduce cannabis use is still needed. Mobile health (mHealth) technology may help
address gaps between clinical need and formal clinical services, particularly for non-treatment seeking YAs
and those typically underserved and underrepresented in research such as non-college YAs. The proposed
R34 application uses a multi-method user-informed approach to develop a novel brief motivational mHealth
intervention that incorporates cutting-edge cannabis intervention research. The proposed intervention is an
integrated mobile-enhanced web-based program with subsequent text messages for 5 weeks that provides
reflection on YAs’ cannabis use in 5 domains: (1) patterns/potency of use, (2) motivations for use, (3) social
connections and use, (4) personal use goals and use and (5) protective behavioral strategies. The intervention
prioritizes autonomy and will allow YAs to direct their journey through the program and allowing for self-
identification of personal reduction goals. YAs are at different places with respect to readiness to change, thus
by allowing the YA to direct their journey, the program will present appropriate content based on their interests
and tailored to their self-efficacy and readiness to change. YAs will have opportunity to reflect on motivations
for using cannabis, and when appropriate, cognitive behavioral skills-training for substance-free strategies for
coping with negative mood and emotions, potential for engaging in substance-free activities, social skill
building, exploration of the relationships among values, future goals, and cannabis use, and opportunities to
explore lower-risk use. Aim 1: Develop a YA cannabis intervention (Take 5) to reduce cannabis use and
negative consequences among non-collegiate YAs engaging in frequent/high-intensity cannabis use. Focus
groups and user experience interviews will inform the development of the intervention. Aim 2: Conduct a 6-
month pilot study with non-collegiate YAs in WA (who use cannabis 15+ days/month, use 2+ times per day
when use, or use high-potency THC products [60%+]) to determine feasibility and acceptability. 120 YAs will
be randomized to Take 5 (n=60) or attention control condition (n=60). The present application addresses
several priorities in NIDA’s Strategic Plan, including using technology (e.g., smartphones) to ...

## Key facts

- **NIH application ID:** 10948385
- **Project number:** 1R34DA061049-01
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** CHRISTINE M Lee
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $311,000
- **Award type:** 1
- **Project period:** 2024-08-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10948385

## Citation

> US National Institutes of Health, RePORTER application 10948385, Feasibility/Acceptability of a Brief Motivational Intervention Integrating Online Personalized Feedback & Tailored Text Messages for Frequent/High-Intensity Cannabis Use in Post-Legalization Landscape (1R34DA061049-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10948385. Licensed CC0.

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