“I neither sleep well nor drive cautiously”: How does sleep quality relate to crash involvement directly and indirectly?

Shams, Zhaleh; Mehdizadeh, Milad; Sanij, Hamed Khani

doi:10.1016/j.jth.2020.100907

Cited by 15 publications

(5 citation statements)

References 47 publications

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“…This is consistent with several published studies linking sleep loss/circadian desynchrony with risk-taking behavior (Alvaro et al, 2018;Fritz et al, 2020;Goel et al, 2009;Killgore, 2015;Womack et al, 2013). In addition, road safety literature identifies risk-taking behavior as a mediating (Shams et al, 2020), and several studies have documented correlations between sleepiness/fatigue and traffic violations (Mahajan et al, 2019;Naderi et al, 2018;Useche et al, 2017).…”

Section: Overtaking Violation During a Car-following Tasksupporting

confidence: 90%

Driving simulator performance worsens after the Spring transition to Daylight Saving Time

et al. 2022

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Section: Overtaking Violation During a Car-following Tasksupporting

confidence: 90%

Driving simulator performance worsens after the Spring transition to Daylight Saving Time

et al. 2022

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“…Errors refer to failures of planned actions to achieve intended consequences, whereas violations are deliberate deviations from what is considered safe practice. Both these underlying constructs have been associated with accident involvement in previous studies (de Winter & Dodou, 2010;de Winter et al, 2015;Shams et al, 2020;Rezapur-Shahkolai et al, 2020;Mehdizadeh et al, 2018Mehdizadeh et al, , 2019. However, speeding, inattentive, and fatigued/tired driving seem to be of particular importance in accident causation.…”

Section: Introductionmentioning

confidence: 79%

Aberrant Driving Behaviour Among Home Health Care Workers

Nordgård¹,

Nordfjærn

2022

SSRN Journal

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“…When considering physical conditions, insufficient sleep can impact driving and decision-making capability, where drowsy driving increases road traffic accidents, and mindlessness leads a driver to select a sub-optimal choice. Furthermore, sleep deprivation increases blind spots on roads [8], leading to collisions with objects on the road.…”

Section: Introductionmentioning

confidence: 99%

Development of a Safety Heavy-Duty Vehicle Model Considering Unsafe Acts, Unsafe Conditions and Near-Miss Events Using Structural Equation Model

Pumpugsri,

Rattanawong,

Vongmanee

2023

Sustainability

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The World Health Organization has revealed that Thailand ranks first in Asia with regard to the region’s road traffic death rate. Due to the growth in the domestic economy and demands in logistics, traffic congestion regularly occurs and brings higher risks to transportation, resulting in a constant increase in the accident rate involving heavy-duty vehicles (HDVs), with a tendency to escalate in the future. To prevent its occurrence and solve the problem, this research aims to present a “Safety HDV Model” based on four dimensions, namely, driver behaviors, unsafe roadway environment, types of vehicles and near-miss events, which are all considered as causes of accidents. In this study, the researchers use the Delphi method to obtain a consensus from experts in logistics and safety from both public and private organizations, and then they define indicators and assess the complex dimensions. Based on the consensus, the researchers find 4 dimensions, 15 factors and 55 indicators with a high level of consensus at the Kendall’s coefficient of concordance (W) of 0.402 and P less than 0.001 to be relevant to safety in logistics. To estimate the influences among dimensions, the researchers apply a structural equation model and find that both absolute fit indices and incremental fit indices demonstrate good fit, with a CMIN/DF of 1.90, RMSEA of 0.048, GFI of 0.95, AGFI of 0.92 and RMR of 0.032 for the absolute fit indices and NFI of 0.97, CFI of 0.98, TLI of 0.98 and IFI of 0.98 for the incremental fit indices. As the model is consistent with data and variables, it is considered to be valid to be adopted by responsible authorities to improve unsafe roadway environments and behaviors of HDV drivers. As the data in the model can be altered by location, the model can be utilized as a tool in strategic planning and management to prevent accidents in each area of the country in the future.

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“I neither sleep well nor drive cautiously”: How does sleep quality relate to crash involvement directly and indirectly?

Cited by 15 publications

References 47 publications

Driving simulator performance worsens after the Spring transition to Daylight Saving Time

Driving simulator performance worsens after the Spring transition to Daylight Saving Time

Aberrant Driving Behaviour Among Home Health Care Workers

Development of a Safety Heavy-Duty Vehicle Model Considering Unsafe Acts, Unsafe Conditions and Near-Miss Events Using Structural Equation Model

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