Abstract Background Marijuana initiation among adults aged 50 years and older has increased substantially. Although acute tetrahydrocannabinol exposure can impair psychomotor function, less is known about how real-world medical marijuana initiation relates to functional tasks such as driving in mid-to-late life. Objective The objective of our study was to evaluate the feasibility of recruiting and retaining adults aged 50 years and older, who are newly registered for medical marijuana, and matched non–marijuana-using controls, into a longitudinal high-fidelity driving simulator protocol, and to explore preliminary associations between medical marijuana initiation and simulated driving performance. Methods This prospective, nonrandomized feasibility cohort study enrolled adults aged 50 years and older who are newly registered in the Florida Medical Marijuana Use Registry, along with age-, race-, and sex-matched controls. Assessments occurred at baseline (T1; preinitiation) and at 1 month (T2). Primary feasibility outcomes included recruitment, retention, simulator completion and tolerance, and exposure verification. Exploratory outcomes included reaction time and divided attention (DA) performance, which are measured using an immersive, high-fidelity driving simulator. Results Recruitment and exposure verification procedures were feasible, but simulator sickness contributed to substantial missing data. Exploratory analyses suggested group differences in select DA outcomes at T2. At T2, reaction time to DA situation 3 (DA3) was significantly shorter in the medical marijuana group (n=14, mean 2.57, SD 1.63) than in the control group (n=7, mean 5.79, SD 4.32; t 19 =−2.50, P =.02, g =−1.11, 95% CI −2.04 to −0.16). These findings should be interpreted cautiously, given the small sample size, missing data, and multiple comparisons. Conclusions A prospective protocol examining medical marijuana initiation and simulated driving among mid-to-late-life adults is feasible, but future studies should incorporate design and analytic refinements to address simulator sickness and missing data and to better characterize exposure timing and patterns.
Ennis et al. (Fri,) studied this question.