# Individual, contextual, and geospatial influences on decisions to drive under the influence of cannabis

> **NIH NIH R01** · BROWN UNIVERSITY · 2024 · $679,899

## Abstract

PROJECT SUMMARY/ABSTRACT
With expanding cannabis legalization and concurrent significant increases in cannabis-related traffic fatalities,
driving under the influence of cannabis (DUIC) has become a major public health concern. Despite the
impairment in driving skills and increased crash risk associated with cannabis intoxication, little is known about
how individuals make the decision to drive (or not) after using cannabis. The proposed project advances our
team’s work on cannabis and DUIC risk factors to identify person-level (e.g., DUIC cognitions), within-person
processes (e.g., subjective intoxication, affective state, cannabinoid concentration, quantity, route of
administration), and contextual influences (e.g., social context, environmental conditions) that predict DUIC
behaviors in daily life. The proposed multi-method project will provide unique qualitative and quantitative
information about individual-level DUIC behavior using geographically explicit ecological momentary
assessment (EMA), which combines event-level data on cannabis use with spatio-temporal data on vehicle
movement. Our preliminary data has demonstrated the feasibility of these methods by integrating passively
collected continuous location data using a vehicle-based GPS tracking device with EMA data on driving and
cannabis use. Frequent and less frequent cannabis users (N = 260) will complete smartphone measures of
cannabis use, concurrent substance use, affect, momentary impulsivity, perceived DUIC dangerousness,
driving intentions, driving motives and destinations/location, and context during a 4-week EMA period. DUIC
(i.e., driving within a pharmacologically-relevant timeframe) will be identified by integrating geospatial data (i.e.,
latitude/longitude/time and vehicle’s movement) passively and continuously collected in the field with EMA data
on cannabis use. Weekly testing of participant cannabis for Δ⁹-tetrahydrocannabinol (THC) and cannabidiol
(CBD) concentration will be done using a near-infrared spectroscopy device. This will be the first study to
prospectively examine the influence of within-person and contextual predictors on DUIC likelihood and
distance traveled (Aim 1). We will explore driving-related cognitions, indices of working memory capacity, and
user characteristics in relation to cannabis use and driving experience as potential moderators of the effects of
event-level predictors on DUIC (Aim 2). To provide insights on contextual factors and decision-making
processes related to DUIC, participants will complete a narrative qualitative interview focused on annotating
maps of representative DUIC and non-DUIC trips generated by GPS data during one of the four weeks of the
EMA period (Aim 3). Exploratory machine learning analyses will be used to characterize and distinguish DUIC
episodes from non-DUIC driving episodes (Aim 4). The current project will be the first full-scale study to
integrate such real-time individual-level exposure data with DUIC outcome...

## Key facts

- **NIH application ID:** 10833478
- **Project number:** 5R01DA055654-02
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** JANE METRIK
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $679,899
- **Award type:** 5
- **Project period:** 2023-08-01 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10833478

## Citation

> US National Institutes of Health, RePORTER application 10833478, Individual, contextual, and geospatial influences on decisions to drive under the influence of cannabis (5R01DA055654-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10833478. Licensed CC0.

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