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1.
Addiction ; 117(7): 1843-1856, 2022 07.
Article in English | MEDLINE | ID: mdl-35083810

ABSTRACT

BACKGROUND AND AIMS: Cannabis and alcohol are frequently detected in fatal and injury motor vehicle crashes. While epidemiological meta-analyses of cannabis and alcohol have found associations with an increase in crash risk, convergent evidence from driving performance measures is insufficiently quantitatively characterized. Our objectives were to quantify the magnitude of the effect of cannabis and alcohol-alone and in combination-on driving performance and behaviour. METHODS: Systematic review and meta-analysis. We systematically searched Academic Search Complete, CINAHL, Embase, Scopus, Google Scholar, MEDLINE, PsycINFO, SPORTDiscus and TRID. Of the 616 studies that underwent full-text review, this meta-analysis represents 57 studies and 1725 participants. We extracted data for hazard response time, lateral position variability, lane deviations or excursions, time out of lane, driving speed, driving speed variability, speed violations, time speeding, headway, headway variability and crashes from experimental driving studies (i.e. driving simulator, closed-course, on-road) involving cannabis and/or alcohol administration. We reported meta-analyses of effect sizes using Hedges' g and r. RESULTS: Cannabis alone was associated with impaired lateral control [e.g. g = 0.331, 95% confidence interval (CI) = 0.212-0.451 for lateral position variability; g = 0.198, 95% CI = 0.001-0.395 for lane excursions) and decreased driving speed (g = -0.176, 95% CI = -0.298 to -0.053]. The combination of cannabis and alcohol was associated with greater driving performance decrements than either drug in isolation [e.g. g = 0.480, 95% CI = 0.096-0.865 for lateral position variability (combination versus alcohol); g = 0.525, 95% CI = 0.049-1.002 for time out of lane (versus alcohol); g = 0.336, 95% CI = 0.036-0.636 for lateral position variability (combination versus cannabis; g = 0.475, 95% CI = 0.002-0.949 for time out of lane (combination versus cannabis)]. Subgroup analyses indicated that the effects of cannabis on driving performance measures were similar to low blood alcohol concentrations. A scarcity of data and study heterogeneity limited the interpretation of some measures. CONCLUSIONS: This meta-analysis indicates that cannabis, like alcohol, impairs driving, and the combination of the two drugs is more detrimental to driving performance than either in isolation.


Subject(s)
Automobile Driving , Cannabis , Driving Under the Influence , Hallucinogens , Accidents, Traffic , Blood Alcohol Content , Cannabinoid Receptor Agonists , Ethanol , Humans , Psychomotor Performance
2.
Infect Control Hosp Epidemiol ; 43(7): 876-885, 2022 07.
Article in English | MEDLINE | ID: mdl-34016200

ABSTRACT

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic has resulted in shortages of personal protective equipment (PPE), underscoring the urgent need for simple, efficient, and inexpensive methods to decontaminate masks and respirators exposed to severe acute respiratory coronavirus virus 2 (SARS-CoV-2). We hypothesized that methylene blue (MB) photochemical treatment, which has various clinical applications, could decontaminate PPE contaminated with coronavirus. DESIGN: The 2 arms of the study included (1) PPE inoculation with coronaviruses followed by MB with light (MBL) decontamination treatment and (2) PPE treatment with MBL for 5 cycles of decontamination to determine maintenance of PPE performance. METHODS: MBL treatment was used to inactivate coronaviruses on 3 N95 filtering facepiece respirator (FFR) and 2 medical mask models. We inoculated FFR and medical mask materials with 3 coronaviruses, including SARS-CoV-2, and we treated them with 10 µM MB and exposed them to 50,000 lux of white light or 12,500 lux of red light for 30 minutes. In parallel, integrity was assessed after 5 cycles of decontamination using multiple US and international test methods, and the process was compared with the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method. RESULTS: Overall, MBL robustly and consistently inactivated all 3 coronaviruses with 99.8% to >99.9% virus inactivation across all FFRs and medical masks tested. FFR and medical mask integrity was maintained after 5 cycles of MBL treatment, whereas 1 FFR model failed after 5 cycles of VHP+O3. CONCLUSIONS: MBL treatment decontaminated respirators and masks by inactivating 3 tested coronaviruses without compromising integrity through 5 cycles of decontamination. MBL decontamination is effective, is low cost, and does not require specialized equipment, making it applicable in low- to high-resource settings.


Subject(s)
COVID-19 , Virus Diseases , COVID-19/prevention & control , Decontamination/methods , Equipment Reuse , Humans , Masks , Methylene Blue/pharmacology , N95 Respirators , Personal Protective Equipment , SARS-CoV-2
4.
Inj Prev ; 26(2): 170-176, 2020 04.
Article in English | MEDLINE | ID: mdl-32015086

ABSTRACT

BACKGROUND: Pedestrians are commonly involved in vehicle collisions that result in injuries and fatalities. Pedestrian distraction has become an emerging safety issue as more pedestrians use their mobile phones while walking and crossing the street. OBJECTIVES: The purpose of this research synthesis and meta-analysis is to determine the extent to which cell phone conversation, text messaging or browsing, and listening to music affect a number of common pedestrian behavioural measures. METHODS: A keyword search was developed with a subject librarian that used MeSH terms from selected databases including PsycINFO, SPORTDiscus, Medline and TRID. Supplemental searches were also conducted with Google Scholar and Mendeley. EFFECT SIZE CODING: Thirty-three studies met inclusion criteria and were subjected to data extraction. Statistical information (ie, M, SD, SE, 95% CI, OR, F, t) was extracted to generate standardised mean difference effect sizes (ie, Cohen's d) and r effect sizes. RESULTS: Fourteen experimental studies were ultimately included in an N-weighted meta-analysis (k=81 effect sizes), and eight observational studies were included in a qualitative overview. Both mobile phone conversation and text messaging increased rates of hits and close calls. Texting decreased rates of looking left and right prior to and/or during street crossing. As might be expected, text messaging was generally found to have the most detrimental effect on multiple behavioural measures. LIMITATIONS: A variety of study quality issues limit the interpretation and generalisation of the results, which are described, as are future study measurement and methods improvements.


Subject(s)
Cell Phone Use/adverse effects , Pedestrians/psychology , Accidents, Traffic/prevention & control , Accidents, Traffic/psychology , Accidents, Traffic/statistics & numerical data , Cell Phone/statistics & numerical data , Cell Phone Use/statistics & numerical data , Humans , Pedestrians/statistics & numerical data , Walking/injuries , Walking/psychology
5.
Hum Factors ; 60(1): 101-133, 2018 02.
Article in English | MEDLINE | ID: mdl-29351023

ABSTRACT

Objective An up-to-date meta-analysis of experimental research on talking and driving is needed to provide a comprehensive, empirical, and credible basis for policy, legislation, countermeasures, and future research. Background The effects of cell, mobile, and smart phone use on driving safety continues to be a contentious societal issue. Method All available studies that measured the effects of cell phone use on driving were identified through a variety of search methods and databases. A total of 93 studies containing 106 experiments met the inclusion criteria. Coded independent variables included conversation target (handheld, hands-free, and passenger), setting (laboratory, simulation, or on road), and conversation type (natural, cognitive task, and dialing). Coded dependent variables included reaction time, stimulus detection, lane positioning, speed, headway, eye movements, and collisions. Results The overall sample had 4,382 participants, with driver ages ranging from 14 to 84 years ( M = 25.5, SD = 5.2). Conversation on a handheld or hands-free phone resulted in performance costs when compared with baseline driving for reaction time, stimulus detection, and collisions. Passenger conversation had a similar pattern of effect sizes. Dialing while driving had large performance costs for many variables. Conclusion This meta-analysis found that cell phone and passenger conversation produced moderate performance costs. Drivers minimally compensated while conversing on a cell phone by increasing headway or reducing speed. A number of additional meta-analytic questions are discussed. Application The results can be used to guide legislation, policy, countermeasures, and future research.


Subject(s)
Accidents, Traffic , Automobile Driving , Cell Phone , Interpersonal Relations , Psychomotor Performance , Humans
6.
Accid Anal Prev ; 106: 31-43, 2017 Sep.
Article in English | MEDLINE | ID: mdl-28554063

ABSTRACT

Driver distraction is a growing and pervasive issue that requires multiple solutions. Voice-recognition (V-R) systems may decrease the visual-manual (V-M) demands of a wide range of in-vehicle system and smartphone interactions. However, the degree that V-R systems integrated into vehicles or available in mobile phone applications affect driver distraction is incompletely understood. A comprehensive meta-analysis of experimental studies was conducted to address this knowledge gap. To meet study inclusion criteria, drivers had to interact with a V-R system while driving and doing everyday V-R tasks such as dialing, initiating a call, texting, emailing, destination entry or music selection. Coded dependent variables included detection, reaction time, lateral position, speed and headway. Comparisons of V-R systems with baseline driving and/or a V-M condition were also coded. Of 817 identified citations, 43 studies involving 2000 drivers and 183 effect sizes (r) were analyzed in the meta-analysis. Compared to baseline, driving while interacting with a V-R system is associated with increases in reaction time and lane positioning, and decreases in detection. When V-M systems were compared to V-R systems, drivers had slightly better performance with the latter system on reaction time, lane positioning and headway. Although V-R systems have some driving performance advantages over V-M systems, they have a distraction cost relative to driving without any system at all. The pattern of results indicates that V-R systems impose moderate distraction costs on driving. In addition, drivers minimally engage in compensatory performance adjustments such as reducing speed and increasing headway while using V-R systems. Implications of the results for theory, design guidelines and future research are discussed.


Subject(s)
Distracted Driving/statistics & numerical data , Reaction Time/physiology , Speech Recognition Software/statistics & numerical data , Accidents, Traffic/prevention & control , Distracted Driving/prevention & control , Female , Humans , Male , Smartphone/statistics & numerical data
7.
Accid Anal Prev ; 87: 161-9, 2016 Feb.
Article in English | MEDLINE | ID: mdl-26724505

ABSTRACT

A systematic review and meta-analysis of naturalistic driving studies involving estimates of safety-critical event risk associated with handheld device use while driving is described. Fifty-seven studies identified from targeted databases, journals and websites were reviewed in depth, and six were ultimately included. These six studies, published between 2006 and 2014, encompass seven sets of naturalistic driver data and describe original research that utilized naturalistic methods to assess the effects of distracting behaviors. Four studies involved non-commercial drivers of light vehicles and two studies involved commercial drivers of trucks and buses. Odds ratios quantifying safety-critical event (SCE) risk associated with talking, dialing, locating or answering, and texting or browsing were extracted. Stratified meta-analysis of pooled odds ratios was used to estimate SCE risk by distraction type; meta-regression was used to test for sources of heterogeneity. The results indicate that tasks that require drivers to take their eyes off the road, such as dialing, locating a phone and texting, increase SCE risk to a greater extent than tasks that do not require eyes off the road such as talking. Although talking on a handheld device did not increase SCE risk, further research is required to determine whether it indirectly influences SCE risk (e.g., by encouraging other cell phone activities). In addition, a number of study biases and quality issues of naturalistic driving studies are discussed.


Subject(s)
Accidents, Traffic/statistics & numerical data , Automobile Driving/psychology , Cell Phone , Risk Assessment/statistics & numerical data , Safety , Humans , Text Messaging
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