Naturalistic conversation improves daytime motorway driving performance under a benzodiazepine: a randomised, crossover, double-blind, placebo-controlled study

Nonbenzodiazepine hypnotics and police-reported motor vehicle crash risk among older adults: a sequential target trial emulation

Nonbenzodiazepine hypnotics ("Z-drugs") are prescribed for insomnia but might increase the risk of motor vehicle crash (MVC) among older adults through prolonged drowsiness and delayed reaction times. We estimated the effect of initiating Z-drug treatment on the 12-week risk of MVC in a sequential target trial emulation. After linking New Jersey driver licensing and police-reported MVC data to Medicare claims, we emulated a new target trial each week (July 1, 2007, to October 7, 2017) in which Medicare fee-for-service beneficiaries were classified as Z-drug-treated or untreated at baseline and followed for an MVC. We used inverse probability of treatment and censoring-weighted pooled logistic regression models to estimate risk ratios (RRs) and risk differences with 95% bootstrap confidence limits (CLs). There were 257 554 person-trials, of which 103 371 were Z-drug-treated and 154 183 untreated, giving rise to 976 and 1249 MVCs, respectively. The intention-to-treat RR was 1.06 (95% CL, 0.95-1.16). For the per-protocol estimand, there were 800 MVCs and 1241 MVCs among treated and untreated person-trials, respectively, suggesting a reduced MVC risk (RR, 0.83; 95% CL, 0.74-0.92) with sustained Z-drug treatment. Z-drugs should be prescribed to older patients judiciously but not withheld entirely over concerns about MVC risk. This article is part of a Special Collection on Pharmacoepidemiology.

A scoping review of motor vehicle operator performance assessments for benzodiazepine receptor agonists

Background

Benzodiazepines and Z-drugs (e.g., zopiclone, zolpidem) (benzodiazepine receptor agonists or BZRAs), are prescribed for anxiety and insomnia disorders. However, they are not indicated as first line therapies for long-term management due to harms and efficacy limitations. BZRAs have also been associated with traffic accident risks. Patients taking BZRAs are told to consult with health care providers regarding motor vehicle operation safety. However, advice on driving is variable. The objective of this scoping review is to identify, map, and characterize the evidence for assessments that measure driving performance in people taking BZRAs.

Methods

Embase (Elsevier), MEDLINE (Ovid), and PsycINFO (EBSCO) were searched. Covidence was used for screening. Each stage of screening included two independent reviewers. A REDCap database was used for data extraction by two independent reviewers. Results were tabulated and summarised as a narrative.

Results

Driving performance was assessed with 20 unique BZRAs across 183 studies (n = 92 experimental; n = 91 observational) in 178 publications. Zopiclone was the most studied. In experimental studies, the Standard Deviation of Lateral Position (SDLP) was used most often (n = 54, 62 %) and many studies (n = 35, 38 %) were conducted in the Netherlands. For observational studies, biological detection (e.g., urine, blood) (n = 73, 80 %) followed by prescription drug/dispensing records (n = 17, 19 %) were the most common impairment measures and Norway (n = 20) is where most studies took place. In experimental studies, most (n = 89, 97 %) were conducted using only one driving setting. Simulated driving in a car (n = 36) and road driving in traffic (n = 36) were common as compared to nontraffic driving course (n = 8) and simulated driving (n = 9). In experimental studies, seventy-eight of the 92 studies (85 %) had at least one measure that identified impairment.

Conclusions

BZRA effects on motor vehicle driving performance have been studied using heterogenous protocols with multiple measures and settings, ranging from simulation to authentic traffic situations in experimental studies to biological detection and dispensing records in observational studies. Many BZRAs have been studied but study representation does not match prescribing pattern prevalence. The interpretation and contextualization of results for clinical practice is challenging due to the complexity (i.e., protocols, measures, settings). Future work in this area should work to improve knowledge translation of results so information is more readily accessible and applicable to health care providers and patients.

Evaluation method regarding the effect of psychotropic drugs on driving performance: A literature review

Although automobile driving is necessary for many people, including patients with mental disorders, the influence of psychotropic drugs on driving performance remains unclear and requires scientific verification. Therefore, the objective of this study was to conduct a review of the literature in order to aid the development of a valid evaluation method regarding the influence of medication on driving performance. We conducted a literature search using two sets of terms on PubMed. One set was related to psychotropic drugs, and the other to driving tests. We excluded reviews and case studies and added literature found on other sites. A total of 121 relevant reports were found. The experiments were roughly divided into on-the-road tests (ORT) and driving simulators (DS). Although highway driving tests in ORT are most often used to evaluate driving performance, DS are becoming increasingly common because of their safety and low cost. The validity of evaluation methods for alcohol should be verified; however, we found that there were few validated tests, especially for DS. The scenarios and measurement indices of each DS were different, which makes it difficult to compare the results of DS studies directly. No evaluation indices, except for SD of lateral position, were sufficiently validated. Although highway ORT are the gold standard, DS were shown to have an increasing role in evaluating driving performance. The reliability of DS needs to be established, as does their validation with alcohol in order to accumulate more high-quality evidence.

Can variations in visual behavior measures be good predictors of driver sleepiness? A real driving test study

OBJECTIVE

The primary purpose of this study was to examine the association between variations in visual behavior measures and subjective sleepiness levels across age groups over time to determine a quantitative method of measuring drivers' sleepiness levels.

METHOD

A total of 128 volunteer drivers in 4 age groups were asked to finish 2-, 3-, and 4-h continuous driving tasks on expressways, during which the driver's fixation, saccade, and blink measures were recorded by an eye-tracking system and the subjective sleepiness level was measured through the Stanford Sleepiness Scale. Two-way repeated measures analysis of variance was then used to examine the change in visual behavior measures across age groups over time and compare the interactive effects of these 2 factors on the dependent visual measures.

RESULTS

Drivers' visual behavior measures and subjective sleepiness levels vary significantly over time but not across age groups. A statistically significant interaction between age group and driving duration was found in drivers' pupil diameter, deviation of search angle, saccade amplitude, blink frequency, blink duration, and closure duration. Additionally, change in a driver's subjective sleepiness level is positively or negatively associated with variation in visual behavior measures, and such relationships can be expressed in regression models for different period of driving duration.

CONCLUSIONS

Driving duration affects drivers' sleepiness significantly, so the amount of continuous driving time should be strictly controlled. Moreover, driving sleepiness can be quantified through the change rate of drivers' visual behavior measures to alert drivers of sleepiness risk and to encourage rest periods. These results provide insight into potential strategies for reducing and preventing traffic accidents and injuries.

Medication use and the risk of motor vehicle collisions among licensed drivers: A systematic review

OBJECTIVES

Driving under the influence of prescription and over-the-counter medication is a growing public health concern. A systematic review of the literature was performed to investigate which specific medications were associated with increased risk of motor vehicle collision (MVC).

METHODS

The a priori inclusion criteria were: (1) studies published from English-language sources on or after January 1, 1960, (2) licensed drivers 15 years of age and older, (3) peer-reviewed publications, master's theses, doctoral dissertations, and conference papers, (4) studies limited to randomized control trials, cohort studies, case-control studies, or case-control type studies (5) outcome measure reported for at least one specific medication, (6) outcome measure reported as the odds or risk of a motor vehicle collision. Fourteen databases were examined along with hand-searching. Independent, dual selection of studies and data abstraction was performed.

RESULTS

Fifty-three medications were investigated by 27 studies included in the review. Fifteen (28.3%) were associated with an increased risk of MVC. These included Buprenorphine, Codeine, Dihydrocodeine, Methadone, Tramadol, Levocitirizine, Diazepam, Flunitrazepam, Flurazepam, Lorazepam, Temazepam, Triazolam, Carisoprodol, Zolpidem, and Zopiclone.

CONCLUSIONS

Several medications were associated with an increased risk of MVC and decreased driving ability. The associations between specific medication use and the increased risk of MVC and/or affected driving ability are complex. Future research opportunities are plentiful and worthy of such investigation.

Complaints of Poor Sleep and Risk of Traffic Accidents: A Population-Based Case-Control Study

INTRODUCTION

This study aimed to determine the sleepiness-related factors associated with road traffic accidents.

METHODS

A population based case-control study was conducted in 2 French agglomerations. 272 road accident cases hospitalized in emergency units and 272 control drivers matched by time of day and randomly stopped by police forces were included in the study. Odds ratios were calculated for the risk of road traffic accidents.

RESULTS

As expected, the main predictive factor for road traffic accidents was having a sleep episode at the wheel just before the accident (OR 9.97, CI 95%: 1.57-63.50, p<0.05). The increased risk of traffic accidents was 3.35 times higher in subjects who reported very poor quality sleep during the last 3 months (CI 95%: 1.30-8.63, p<0.05), 1.69 times higher in subjects reporting sleeping 6 hours or fewer per night during the last 3 months (CI 95%: 1.00-2.85, p<0.05), 2.02 times higher in subjects reporting symptoms of anxiety or nervousness in the previous day (CI 95%: 1.03-3.97, p<0.05), and 3.29 times higher in subjects reporting taking more than 2 medications in the last 24 h (CI 95%: 1.14-9.44, p<0.05). Chronic daytime sleepiness measured by the Epworth Sleepiness Scale, expressed heavy snoring and nocturnal leg movements did not explain traffic accidents.

CONCLUSION

Physicians should be attentive to complaints of poor sleep quality and quantity, symptoms of anxiety-nervousness and/or drug consumption in regular car drivers.