The Prevalence of Risky Driving Habits in Riyadh, Saudi Arabia

Prevalence and correlates of depressive symptoms among professional drivers in Saudi Arabia: A cross-sectional study

BACKGROUND

Professional drivers in Saudi Arabia may be at increased risk for mental illness because of their expatriate status, long driving hours, and unhealthy lifestyles.

OBJECTIVE

To assess the prevalence and correlates of depressive symptoms among professional drivers in Saudi Arabia, most of whom are expatriates.

METHODS

Professional drivers (n = 324) were interviewed after convenient sampling of transportation companies. The Depression Anxiety Stress Scale-21 (DASS-21) was used to screen for depressive symptoms. Correlates of depressive symptoms were identified using Cox regression with a fixed follow-up time.

RESULTS

Of the drivers, 20.4% had moderate to severe depressive symptoms. Sleep quality was found to be a significant independent correlate of depressive symptoms. Drivers with poor and fair sleep quality had higher risk of depressive symptoms than drivers with excellent sleep quality (poor: OR = 5.8, CI: 1.95-17.11; fair: OR = 4.5, CI: 1.68-11.96).

CONCLUSION

The frequency of depressive symptoms among professional drivers in Saudi Arabia is high (one out of five). Companies should consider screening for depressive symptoms and sleep disorders among employees and should provide referrals as needed.

Analysis of road traffic injuries presented to the emergency department in the Eastern Province of Saudi Arabia: a hospital-based study

The increasing incidence of road traffic injuries (RTIs) has contributed to the disability and death of millions of people on both a national and global level. This retrospective study was conducted at King Fahad University Hospital (KFUH), Khobar, Saudi Arabia, and included all patients who presented at the emergency department due to road traffic accidents (RTAs) between January 1st, 2022, and December 31st, 2022. Patient data was retrieved from the health information system at KFUH. Descriptive and inferential analysis were performed with several variables analyzed using multivariate logistic regression and factorial ANOVA (MANOVA). During this period, 921 patients were treated at the hospital's emergency department. Of these, 611 (66.3%) were men and 310 (33.7%) were women. The most frequently affected age group was 16-25, representing 427 (46.4%) cases. Most patients were Saudi citizens (837, 90.9%). Among the patients, 19 (2.1%) required surgical treatment within 24 hours of the RTA, and 29 (3.1%) were admitted to the surgical intensive care unit (SICU). There were eight fatalities, representing 0.9% of the cases. January had the highest number of RTAs (12.7%). Moreover, 463 individuals (50.3%) had some form of injury, the most common type being lacerations and abrasions (n=228, 24.8%). Upper limb fractures were the most frequent type of fracture, occurring in 73 cases (7.9%). Being male (P=0.001), non-Saudi (P=0.014), and experiencing accidents during June and July (P=0.002) were associated with an increased prevalence of injury. Mortality had a statistically significant relationship with different patient age groups (P=0.014), patient citizenship (P=0.005), and length of hospital stay (P<0.001).

An exploration of the role of driving experience on self-reported and real-world aberrant driving behaviors

A significant proportion of global road crashes are attributed to unsafe driving behaviors. The current study aimed to explore potential differences in driving behaviors across experienced and novice drivers using two separate approaches; a questionnaire study and an instrumented vehicle study (IVS). The analysis of 260 questionnaires and 1,372 traffic interactions within the IVS revelated that driving experience affects driving performance for different driving tasks. Factor analysis of the questionnaire data revealed the impact of driving errors, lapses, violations, and aggressive violations on the behavior of novice and experienced drivers. Behavioral models of novice and experienced drivers encountering other road users were determined using binary logistic regression. The results showed that novice drivers were more likely to engage in driving violations while experienced drivers were more likely to engage in aggressive violations. Unauthorized speeding, zigzag movements, using a mobile phone while driving, and unauthorized overtaking on roads were the most frequent driving violations by novice drivers. The most frequent aggressive violations by experienced drivers were tempting other drivers to create a race and chasing other drivers. These findings may be used as a framework to facilitate safer driving behaviors by reducing errors, lapses, violations and aggressive violations, and facilitating safety-promoting attitudes.

Car accidents and risky driving behaviors among young drivers from the Eastern Province, Saudi Arabia

Objective: In 2019, road traffic injuries were the second leading cause of death in Saudi Arabia, affecting people of all ages. While multiple factors contribute to crashes, studies highlight the role of risky driving in increasing the chances of car crashes occurring. This study examined the one-year frequency of car crashes and risky driving behaviors among young drivers of both sexes in the Saudi Arabia's Eastern Province, as well as the possible related factors and predictors that contribute toward high car crash rates.Methods: A cross-sectional study was conducted between November 2021 and February 2022 at AlAsala Colleges among young drivers aged 18 years and above. A total of 424 students were selected using stratified random sampling and answered an anonymous, self-administered, structured web-based questionnaire and the Arabic version of the Driver Behavior Questionnaire (DBQ).Results: Car crashes were reported by 26.4% of young male and 19.3% of young female drivers. Male drivers were more aggressive and exhibited more speeding-related behaviors than female drivers, regardless of slight sex differences in unsafe driving behavior. Driving experience, along with other driving characteristics and DBQ items, was found to be significantly associated with road crashes. Furthermore, the type of car, traffic violations, using a phone while driving via headphones, and a distraction-related factor, were all predictive of crash involvement.Conclusions: Young Saudi male drivers were slightly more likely to have car crashes and engage in risky driving practices than young female drivers. Various factors that are related with and predict crashes should be addressed by a collaborative multi-layered strategic plan, with interventions at several levels.

Driver Behavior and Intention Recognition Based on Wavelet Denoising and Bayesian Theory

Driver behavior and intention recognition affects traffic safety. Many scholars use the steering wheel angle, distance of the brake pedal, distance of the accelerator pedal, and turn signal as input data to identify driver behaviors and intentions. However, in terms of time, the acquisition of these parameters has a relative delay, which lengthens the identification time. Therefore, this study uses drivers’ EEG (electroencephalograph) data as input parameters to identify driver behaviors and intentions. The key to the driving intention recognition of EEG signals is to reduce their noise. Noise interference has a significant influence on EEG driving intention recognition. To substantially denoise EEG signals, this study selects wavelet transform theory and wavelet packet transform technology, collects the EEG signals during driving, uses the threshold noise reduction method on EEG signals to reduce noise, and achieves noise reduction through wavelet packet reconstruction. After the wavelet packet coefficients of EEG signals are obtained, the energy characteristics of the wavelet packet coefficients are extracted as input to the Bayesian theoretical model for driver behavior and intention recognition. Results show that the maximum recognition rate of the Bayesian theoretical model reaches 82.6%. Early driver behavior and intention recognition has important research significance for traffic safety and sustainable traffic development.

Towards Sustainable Road Safety in Saudi Arabia: Exploring Traffic Accident Causes Associated with Driving Behavior Using a Bayesian Belief Network

Understanding the causes and effects of road accidents is critical for developing road and action plans in a country. The causation hypothesis elucidates how accidents occur and may be applied to accident analysis to more precisely anticipate, prevent, and manage road safety programs. Driving behavior is a critical factor to consider when determining the causes of traffic accidents. Inappropriate driving behaviors are a set of acts taken on the roadway that can result in aberrant conditions that may result in road accidents. In this study, using Al-Ahsa city in Saudi Arabia’s Eastern Province as a case study, a Bayesian belief network (BBN) model was established by incorporating an expectation–maximization algorithm. The model examines the relationships between indicator variables with a special focus on driving behavior to measure the uncertainty associated with accident outcomes. The BBN was devised to analyze intentional and unintentional driving behaviors that cause different types of accidents and accident severities. The results showed when considering speeding alone, there is a 26% likelihood that collision will occur; this is a 63% increase over the initial estimate. When brake failure was considered in addition to speeding, the likelihood of a collision jumps from 26% to 33%, more than doubling the chance of a collision when compared to the initial value. These findings demonstrated that the BBN model was capable of efficiently investigating the complex linkages between driver behavior and the accident causes that are inherent in road accidents.

"Motorcycle Ambulance" Policy to Promote Health and Sustainable Development in Large Cities

INTRODUCTION

Motorcycles can be considered a new form of smart vehicle when taking into account their small and modern structure and due to the fact that nowadays, they are used in the new role of ambulance to rapidly reach emergency patients in large cities with traffic congestion. However, there is no study regarding the measuring of access time for motorcycle ambulances (motorlances) in large cities of Thailand.

STUDY OBJECTIVE

This study aims to compare access times to patients between motorlances and conventional ambulances, including analysis of the use of automated external defibrillators (AEDs) installed on motorlances to contribute to the sustainable development of public health policies.

METHODS

A cross-sectional study was conducted on all motorlance operations in Emergency Medical Services (EMS) at Srinagarind Hospital, Thailand from January 2019 through December 2020. Data were recorded using a national standard operation record form for Thailand.

RESULTS

Two hundred seventy-one motorlance operations were examined over a two-year period. A total of 52.4% (N = 142) of the patients were male. The average times from dispatch to vehicle (motorlance and traditional ambulance) being en route (activation time) for motorlance and ambulance in afternoon shift were 0.59 minutes and 1.45 minutes, respectively (P = .004). The average motorlance response time in the afternoon shift was 6.12 minutes, and ambulance response time was 9.10 minutes at the same shift. Almost all of the motorlance operations (97.8%) were found to have no access to AED equipment installed in public areas. The average time from dispatch to AED arrival on scene (AED access time) was 5.02 minutes.

CONCLUSION

The response time of motorlances was shorter than a conventional ambulance, and the use of AEDs on a motorlance can increase the chances of survival for patients with cardiac arrest outside the hospital in public places where AEDs are not available.