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Distracted driving is one of the most significant human factor issues in transport safety. Mobile phone interactions while driving may involve a multitude of cognitive and physical resources that result in inferior driving performance and reduced safety margins. The current study investigates characteristics of usage, risk factors, compensatory strategies in use and characteristics of high-frequency offenders of mobile phone use while driving. A series of questions were administered to drivers in Queensland (Australia) using an on-line questionnaire. A total of 484 drivers (34.9% males and 49.8% aged 17-25) participated anonymously. At least one of every two motorists surveyed reported engaging in distracted driving. Drivers were unable to acknowledge the increased crash risk associated with answering and locating a ringing phone in contrast to other tasks such as texting/browsing. Attitudes towards mobile phone usage were more favourable for talking than texting or browsing. Lowering the driving speed and increasing the distance from the vehicle in front were the most popular task-management strategies for talking and texting/browsing while driving. On the other hand, keeping the mobile phone low (e.g. in the driver's lap or on the passenger seat) was the favourite strategy used by drivers to avoid police fines for both talking and texting/browsing. Logistic regression models were fitted to understand differences in risk factors for engaging in mobile phone conversations and browsing/texting while driving. For both tasks, exposure to driving, driving experience, driving history (offences and crashes), and attitudes were significant predictors. Future mobile phone prevention efforts would benefit from development of safe attitudes and increasing risk literacy. Enforcement of mobile phone distraction should be re-engineered, as the use of task-management strategies to evade police enforcement seems to dilute its effect on the prevention of this behaviour. Some countermeasures and suggestions were proposed in the design of public education campaigns and driver-mobile phone interaction.
This article was published in the following journal.
Name: PloS one
This study examined the frequency of mobile phone dependence in Chinese university students and explored its association with social support and impulsivity. Altogether, 909 university students were c...
This study investigates the effect of passenger and phone conversations on sleep-restricted driving. Six volunteers (50% male, mean age 24.8 ± 4.3 years) had their sleep restricted to 4 h in bed ...
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The purpose of this study is to determine if a mobile sensing platform can passively and objectively detect the presence of clinically significant mood disorder symptomatology and symptom ...
The purpose of this study is to evaluate a mobile phone app designed to help Veterans with PTSD. Participants in this study will be randomized to receive one of 2 possible mobile phone app...
Randomized controlled trial to investigate the impact of a pregnancy-specific mobile phone application on the knowledge of specific pregnancy topics and guidelines.
The purpose of this study is to evaluate a variety of technologies in a driving simulator. Specifically, this research will provide a direct comparison of driver performance measures under...
The effect of environmental or physiological factors on the driver and driving ability. Included are driving fatigue, and the effect of drugs, disease, and physical disabilities on driving.
The relating of causes to the effects they produce. Causes are termed necessary when they must always precede an effect and sufficient when they initiate or produce an effect. Any of several factors may be associated with the potential disease causation or outcome, including predisposing factors, enabling factors, precipitating factors, reinforcing factors, and risk factors.
Telephone surveys are conducted to monitor prevalence of the major behavioral risks among adults associated with premature MORBIDITY and MORTALITY. The data collected is in regard to actual behaviors, rather than on attitudes or knowledge. The Centers for Disease Control and Prevention (CDC) established the Behavioral Risk Factor Surveillance System (BRFSS) in 1984.
Factors that can cause or prevent the outcome of interest, are not intermediate variables, and are not associated with the factor(s) under investigation. They give rise to situations in which the effects of two processes are not separated, or the contribution of causal factors cannot be separated, or the measure of the effect of exposure or risk is distorted because of its association with other factors influencing the outcome of the study.
Loss of vascular ELASTICITY due to factors such as AGING; and ARTERIOSCLEROSIS. Increased arterial stiffness is one of the RISK FACTORS for many CARDIOVASCULAR DISEASES.