Enhancing Interpretable, Transparent, and Unobtrusive Detection of Acute Marijuana Intoxication in Natural Environments: Harnessing Smart Devices and Explainable AI to Empower Just-In-Time Adaptive Interventions: Longitudinal Observational Study.

Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect acute marijuana intoxication in real time.

Objective: This study aims to explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, like Fitbit, can enhance the detection of acute marijuana intoxication in naturalistic settings.

Mobile phone sensor-based detection of subjective cannabis intoxication in young adults: A feasibility study in real-world settings.

Background: Given possible impairment in psychomotor functioning related to acute cannabis intoxication, we explored whether smartphone-based sensors (e.g., accelerometer) can detect self-reported episodes of acute cannabis intoxication (subjective "high" state) in the natural environment.