Highlights Cannabis was found to increase standard deviation of lateral position and decrease speed. Participants had some capacity to predict changes in driving performance after cannabis use. Self-reported readiness to drive and changes in speed were influenced by participant use history.

    Abstract Objective It is unclear to what extent individuals who use cannabis can accurately assess their ability to drive safely following cannabis use, and lack of understanding as to what factors influence changes in driving performance following cannabis use. This research explores whether self-reported readiness to drive (RTD) and previous experience (PE) using cannabis within 2 h of driving can predict observed changes in driving performance following acute cannabis use. Methods Individuals who used cannabis at least monthly completed a baseline simulated drive, were dosed with cannabis of approximately 6.18% THC, then drove at approximately 30-minutes, 90-minutes, and 180-minutes post-dose. Before each drive, participants were asked if they felt safe to drive (on real roadways, not the simulator), a yes/no question (RTD-yes/RTD-no). Venous blood was drawn at baseline and approximately 15-minutes post-dose. Cannabis use history was obtained and included whether the participant had ever driven within 2 h of use (PE-yes/PE-no) and how many days out of the past 30 they had done so (NPD). Drives were segmented into events delineated by changes in the driving environment. Within events, standard deviation of lateral position (SDLP), average speed, and number of lane departures were calculated, and differences from baseline were modeled using mixed-effects regression. Models considered covariates of time, event, and speed, and used RTD-yes/RTD-no, PE-yes/PE-no, NPD, and their interactions as potential predictors. Conditional R 2 was used to compare the predictive ability of RTD versus change in Delta-9-THC. Data Sources Data were collected from 30 individuals who use cannabis and included cannabis use patterns, driving behaviors after use, self-reported RTD, measures of driving performance, and cannabinoid blood levels. Results RTD-no predicted a 2.60 cm increase in SDLP relative to baseline (95 % CI: 0.43, 4.73, p = 0.018). Average speeds generally decreased relative to baseline, except for RTD-yes with PE-yes (+1.08 mph, 95 % CI: 0.05, 2.11). NPD predicted increased speed among RTD-yes (+0.11 mph per additional day, 95 % CI: 0.01, 0.22) and decreased speed among RTD-no (-0.06 mph per additional day, 95 % CI: −0.18, 0.32). The difference in these effects was statistically significant (p = 0.038). RTD, PE, and NPD were not significant predictors of changes in number of lane departures. For all outcomes, models using RTD achieved higher conditional R 2 than models that replaced this variable with change in Delta-9-THC. Differences were most prominent when modeling change in speed with NPD ( R 2 = 0.544 with RTD vs. R 2 = 0.481 with change in Delta-9-THC). Significance of Results These results suggest individuals who use cannabis can somewhat self-identify when they are likely to exhibit greater degraded lateral control, although RTD does not fully explain observed degradation in performance. Past research suggests drivers may reduce speed to compensate for recognized impairment following acute cannabis use. Our findings suggest this to be true for those who reported never having previously driven within 2 h of cannabis use or reported RTD-no, but not for those who had previously driven within 2 h of cannabis use and reported RTD-yes. This indicates compensatory behavior is not uniform and helps focus public health outreach efforts.


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    Titel :

    Predicting changes in driving performance in individuals who use cannabis following acute use based on self-reported readiness to drive


    Beteiligte:
    Miller, Ryan (Autor:in) / Brown, Timothy (Autor:in) / Schmitt, Rose (Autor:in) / Gaffney, Gary (Autor:in) / Milavetz, Gary (Autor:in)


    Erscheinungsdatum :

    2023-11-06




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch