جستجوی مقالات مرتبط با کلیدواژه « driving » در نشریات گروه « پزشکی »

Driving has various harmful factors due to its nature, which affect drivers’ health directly and indirectly. Therefore, it is necessary to know the situation and prevalence of these factors in drivers to implement preventive measures.

This cross-sectional study is a part of a cohort study conducted (2016 to 2018) among the professional drivers of Shahroud, Iran. Data related to background information, blood pressure, height, weight, waist circumference, body mass index, blood factors, hearing loss (dB), respiratory performance indicators, sleep disorders, and accidents were collected from the participants with standard tools and methods.

This study examined 1461 male professional drivers with an average age of 37.30±6.96 years. A total of 426 participants had metabolic syndrome. 797 and 942 people had different degrees of hearing loss, respectively, in the right and left ear. About 129 people had obstructive sleep apnea, and 1330 people had insomnia. Investigations showed that 351 drivers had at least one accident.

This study showed the prevalence of health risk factors in professional drivers at the examined time point. Considering the vital role of drivers in transportation and the country’s economy, it seems necessary to pay more attention to the health of this occupational group. Regular health screening, healthy lifestyle training, improvement of working conditions, and stress management are some interventions that can effectively improve drivers’ health.

Road accidents and related damages and casualties are among the most important concerns of today's societies. Mental workload is one of the main human factors that can cause other factors, such as stress and anger. The present study was conducted to investigate the mental workload and its effect on changing the components of drivers' moods.

A total of 88 tour taxi drivers from Qazvin City participated in this study to examine the desired components. The driving Activity Load Index was used to evaluate mental load and the Profile of Mood States questionnaire to measure drivers' mood components. Based on the designed scenario of driving on high-traffic roads, the desired variables were evaluated. To check the relationship between these variables, paired t-tests and Pearson correlation analysis were used in SPSS version 24 software.

The mean scores of the drivers' work history and age were obtained at 46.60±10.12 and 13.47±9.39 years, respectively. The obtained findings showed that driving on high-traffic roads significantly increased the average mental workload of drivers (P<0.001). Growth in the drivers' mental workload led to a decrease in some mood components that had a positive effect, such as happiness (r=-0.143, P=0.157) and vitality (r=-0.646, P=0.050), while it resulted in a rise in the mood component of depression (r=0.020, P= 0.248).

Based on the findings of the study, it can be concluded that as driving continues, drivers experience a rise in mental workload. However, there was no correlation regarding the effect of this component on the mood components.

Driving is a crucial ability that can impact the quality of life for elderly individuals. Older adults may rely more on driving compared to other age demographics. As individuals age, there are significant changes in physical, cognitive, intellectual, and emotional abilities that are crucial for driving, a skill essential for accessing healthcare, therapy services, work, and social activities, as well as maintaining independence and autonomy in the elderly. Mobility and physical exertion are crucial aspects of health for older individuals, and driving significantly contributes to their ability to move within society. The increase in the elderly population has led to a rise in the number of older drivers. Proficiency in self-efficacy in driving is a crucial ability in this profession that acknowledges the significant aspects of this issue. This study aimed to investigate the correlation between weariness, self-efficacy, and driving behavior among older drivers in an urban setting.

This study was a progressive and descriptive-analysis study conducted among older drivers aged 60 and older who were members of the taxi association. Three hundred and ten eligible participants were chosen using the convenience sampling approach. The data was collected using the demographic data form, the multidimensional fatigue inventory, and Adele's self-efficacy scale. The data was analyzed using descriptive statistics, multiple linear regression, and Pearson correlation tests.

The participants had an average age of 28.3 years with a standard deviation of 9.6 years, and their ages ranged from 60 to 75 years. 42% of the participants had university degrees. They mostly had 30 to 50 years of driving experience. The average self-efficiency in driving among older drivers was 101.87±15.74. The Pearson correlation test indicated a significant and inverse relationship between age factors, the history of the driving license, and the self-efficacy score. In other words, as age and years of driving experience increase, the likelihood of self-efficacy driving reduces substantially. The correlation between the fatigue questionnaire scores and self-driving efficiency was significant(P<0.001). There was an inverse relationship between fatigue and self-efficacy in driving. Higher fatigue levels in older adults led to a decrease in self-activity rates. Multiple linear regression analyses revealed strong associations between educational characteristics, the economic-social status of chronic illness, self-efficiency scores, and fatigue rates. The model indicates that the fatigue score decreases by 0.18 for every one-unit rise in the self-efficiency score. The regression analysis showed that monthly income, vehicle type, and fatigue score were significantly related to driving self-efficacy score(R2=39.5).

Researchers recommend implementing a driving rehabilitation program and interventions that provide psychological support in reducing fatigue for older adult drivers based on these findings. The results of the study could assist policymakers in the field of gerontology in planning rehabilitation programs to enhance self-efficacy in driving in older individuals. These programs would consider the factors that contribute to decreased driving efficiency in older drivers and would be implemented in collaboration with welfare organizations and municipalities.

Iran has the highest annual fatality rate in traffic accidents among countries in the world.  This study is designed to predict the protective behaviors of intra-urban traffic accidents based on the constructs of the theory of planned behavior (TPB).

This descriptive-analytic study was conducted in 2022 in Yazd city on 140 people with driver's license using stratified random sampling method. Data were collected through a questionnaire with three parts including demographic variables, evaluation of the TPB constructs, and assessment of socio-cultural factors of driving behaviors.  Data analysis was performed by SPSS version 26 using one-sample t-test, Chi-square, and univariate linear regression tests.

In this study, the mean age of subjects was 39/1 with a standard deviation of 11. Based on the results of the study, 33% of the variance related to protective driving behavior could be predicted with the variables included in the model. The constructs of behavioral intention (β=0/414, p<0/0001) and perceived behavioral control (β= 0/246 p= 0/003) were the determinants of protective behaviors in Yazd city drivers.

In the present study, the perceived behavioral control was the strongest predictor of protective behavioral intention in intra-urban driving. Sometimes, performing a behavior necessitates the acquisition of skills that a person lacks, and increasing perceived behavioral control can lead to improved driving skills. Therefore, TPB offers an effective theoretical framework for increasing the efficacy of traffic accident prevention initiatives.

Escaping from military service occurs first during a process of incompatibility with the situation, then violence, and finally escape. The aim of this study was to investigate the mediating role of distress tolerance in relation to soldiers' violence with desire to escape due to the performance of commanders.

This research was descriptive correlation based on structural equation modeling. The statistical population was all 280 soldiers of Imam Sajjad Educational Center in Urmia, Iran in July 2021. In this study, 210 samples were selected by the simple random sampling. The Buss-Perry Violence Questionnaire, the Simons and Gaher Turbulence Questionnaire, as well as the researcher-made questionnaire of tendency to escape due to the commanders' performance were used to collect data. To analyzing the data, Pearson correlation test and structural equation model were used in the form of SPSS 18 and AMOS 23 software.

Among 210 participants in the study, 139 people had diploma and lower degrees and also 71 people had a bachelor's degree or higher. Confirmatory validity and the measurement model of the three questionnaires were confirmed and the reliability was obtained by Cronbach's alpha method of violence 0.87, distress tolerance was 0.79 and desire to escape was 0.88. The findings showed that the soldiers' violence and distress tolerance due to the performance of the commanders on the desire to escape have a direct and indirect effect of 0.291 and -0.246. The standardized values of the indirect effects of the violence through the mediation of distress tolerance on the tendency to escape were confirmed by the Bootstrap estimation method and violence had an effect on the desire to escape through mediation of distress tolerance (-0.48) (p <0.01). Finally, the research model was approved and 41% of the desire to escape due to the performance of commanders could be explained by the variables of soldiers' violence and distress tolerance in direct and indirect levels.

The present study shows that soldier violence affects the desire to escape through the mediation of distress tolerance and importance of cognitive and emotional factors in explaining the desire to escape due to the performance of commanders.

Traffic accidents are a major problem in the field of transportation in Iran. To address this problem, detailed studies are needed especially over the impact of human risk factors. Therefore, the present study was conducted with the aim of identifying and recognizing the human characteristics associated with the occurrence of traffic accidents resulting in injury or death in the city of Yazd.

In this cross-sectional (descriptive-analytical) study, Yazd traffic accident data were collected using simple sampling method. The data were collected on the basis of COM form 114 by traffic experts present at the accident scenes. After data collection, the data were entered into SPSS software version 20 and analyzed using descriptive statistics, Chi-square, and Mann-Whitney tests.

A total of 2082 cases were studied in traffic accidents (pedestrians=8.8%, passengers=15.4%, and drivers=75.8%). The average age of injured and deceased persons in traffic accidents were 35.08±13.89 and 45.37±17.12 years, respectively. The most common human factors involved in traffic accidents were rush and acceleration (96.8%). Moreover, nonconformity of priority right was 98.9%. A statistically significant relationship was found between human factors and traffic accidents leading to death or injury (p-value=0.04).

  According to the findings, controlling human risk factors can reduce the risk of death and injuries in traffic accidents. Officials, policymakers, and planners can also plan on the most influential factor by carefully analyzing human errors in the event of a traffic accident.

Worldwide statistics declare that 1.2 million people are killed as a result of a road traffic accident (RTA). Besides, 20-50 million are injured every year. Traffic accidents account for leading causes 1.2% of deaths and 23% of injuries. In Iran, 16,000 people are annually cut short in traffic accidents. A great number of people suffer from non-fatal injuries/disabilities, which is estimated not to be less than 335,000. Statistics show that road traffic mortality in Iran has been higher than the global average, which can dramatically increase direct (medical costs, caring disabled people, broken cars, and etc.) and indirect (PTSD, traffic jam, depression in families, losing powers (permanently or temporarily) and etc.) costs. The magnitude of RATs in Iran can be better understood if it is mentioned that accidents are in the position of first place of the ranking of lost years of life. This caveat calls for a focus for urgency in RATs control strategies as a main focal point to improve public health in Iran. Nowadays, a triple-causal approach (vehicle, environment, and human) was accepted in traffic incidents. During recent years, vehicle and environment (as causal factors of traffic incidents) have been greatly improved. In contrast, human behavior has still remained as the most frequent contributing factor (up to 94%). This factor is being the most important and critical factor within any system, including traffic system. In a dangerous traffic situation, which is mostly no room to commit any error, accident prevention remains on drivers' abilities and skills. It seems human factors can play a special role to control human behavior. Therefore, it worth to provide a human factor view on human behavior while driving. During driving, the driver has to collect a large amount of information at any given time and put them in the process of continuous decision making. If any functions of the driver's decision-making process cannot be at the optimum level, human error may lead to catastrophic consequences. Driver errors are usually outcomes of mismatch between driving demands and driver abilities, especially psychologic ones. It is better to say human error is mostly the result of defects or improper function of mental information processing, which is familiar to people as forgetfulness, inattention, carelessness, negligence, recklessness, and etc. A group of methodologies which has been introduced in human factors are able to predict cognitive drivers’ errors. Despite the importance of role of human error in traffic accidents, Human error identification methods (HEIs) have been mostly used in high risk environments such as airline industry. Yet, there is few published studies on identification of driver’s errors and transportation industry. The purpose of this study is to predict driver errors using Human Error Template (HET) method meanwhile a real driving task.

This case study was carried out to identify and predict the drivers' error in a specific real driving scenario. At first, the scenario was designed based on agreement of research team members. To fulfill the scenario, an Iranian car (PARS Peugeot) was used which had successfully passed the technical test (with regard to lights, mirrors, glasses, safety belts, horn, oil, outlet emissions, side slides, shock absorbers, brakes, steering, suspension system lever). The driver was a healthy 42 years old man with 20 years driving experience as his career. A direct route with proper traffic signs was considered on a two-way street with mild traffic flow on a sunny day. The scenario was as: “the driver departs from the park and moves in a pre-determined direction. A few moments later, he speeds up to overtakes the front car. Then, he simply continues driving. By getting the destination, he exits the path and park the car”. Since driving consists of several sub-tasks which should be performed simultaneously, a list of sub-tasks which are required to complete the scenario was provided by interviews, as well as, direct observation. The tasks were analyzed based on Hierarchical Task Analysis (HTA). Then, the tasks list was used as the input for the HET technique. This technique identifies and classifies external errors (EEMs) in the form of human error detection methods (HEIs). The technique considers EEMs in 12 patterns that are described as follows: 1. Fail to execute, e.g. the driver cannot correctly get the clutch 2. Incomplete task execution, e.g. leaving handbrake in middle position 3. Task execution in a wrong direction, e.g. pressing the gear lever in a wrong direction 4. Wrong task execution, e.g. suddenly change direction 5. Task repeated, e.g. placing the lever twice 6. Task execution on the wrong interface element, e.g. pressing a pedal instead of the others. 7. Task execution too early, e.g. turn on the guide much earlier than the redirection. 8. Task execution too late, e.g. delay in coming back to appropriate line and staying in the overtaking line. 9. Too much task execution, e.g. continuous gear changing 10. Too little task execution, e.g. few frequencies of using brakes 11. Misread information, e.g. misreading information on speed gauge 12. Other. Next, errors types and potential consequences were described.

Hierarchical task analysis (HTA) showed that for implementation of the scenario, three main tasks and nine sub-tasks were needed. Among 101 errors detected by HET, 16% were considered as unacceptable errors. Also, the most common types of errors included: “Task execution incomplete” (25.74%), “Task executed too late” (21.78%) and “Fail to execute” (13.86%), respectively. The results from the distribution of human errors in the main tasks and sub-tasks indicate that the main task “scrolling the route” accounts for 48% of all errors. Distribution of this ratio for “acceleration changing”, “line changing” and “distance adjusting” was 49%, 33% and 18%, respectively. Rate of errors were 33% in task of “moving” of which 79% were related to the “starting point of the movement” sub-task, 18% to the “alarms control” sub-task, and 3% to the “fasten seat belt” sub-task. Also, 19% of errors were found in the “parking” task, which 79% were related to “stopping” sub-task, 16% related to “shut downing”, and 5% related to “unlocking seat belt”. The distribution of catastrophic errors for the “scrolling the route”, “moving” and “parking” were found 4, 11, and 1 error, respectively. These were considered as "unacceptable" errors due to the high rate of incident occurrence (for example, suddenly line changing, lack of control of one of the front or rear line, etc.).

The majority of identified type of errors in this study were “Fail to execute”. Therefore, to reduce this type of error, it is necessary to use corrective actions, such as periodic retraining drivers, equipping vehicles with visual and audible markers and alarms in relation to incomplete tasks. These actions can have a beneficial effect on reducing the severity and chances of occurrence of errors. Human Error Template (HET) is a comprehensive method that has been used widely in the aviation industry. As previous studies, the results of this study showed HET is capable to identify and classify driving errors. Using the technique in traffic domain can provide a great opportunity to predict drivers’ error. Consequently, there will be a great hope to control them before-the-fact. In spite of the importance of identifying drivers’ error, a few studies have been published. It seems the multi-sub-tasks nature of driving has caused the researchers to avoid involving in HTA for driving. To have a better understand of control strategy in traffic domain, however, it is strongly recommended to apply human error techniques for driving situation. Human factors

Unsafe behaviors of motorcyclists are one of the main causes of their mortality. Measuring the unsafe behaviors of motorcyclists and planning for control them in the first step, requires a tool that matches the cultural, social and religious characteristics of the society. The purpose of this study was to design and psychometric of measurement tool of unsafe behaviors in motorcycle driving based on information, motivation and behavioral skills model.

In this cross-sectional descriptive-analytical study to determine the tool items, after reviewing the scientific resources, and the need assessment of beliefs in the community under study, a 32-item questionnaire consisting of information, motivation and behavioral skills domains was designed. Its validity was done by content validity (quantitative and qualitative), formal validity and construct validity (confirmatory factor analysis) and its reliability was done by internal consistency (Cronbach's alpha) and test-retest (ICC) using LISREL 8.8 software.

After the validity and reliability, 21 items remained in the final version of the questionnaire. The content validity index was 0.97-1. Also, the results of construct validity showed RMSEA=0.071 and X2/df=1.97 (p<0.001). Tool reliability was confirmed using internal consistency (α=0.70-0.87) and its stability by test-retest (ICC=0.992).

Designed questionnaire to assess the unsafe behaviors of motorcyclists based on the information, motivation and behavioral skills model has appropriate validity and reliability and is approved.

Driver distraction increases the risk of traffic accidents and it is important. Present study was performed to aim study of most important factors of voluntary engagement in distraction and susceptibility to involuntary distraction related to road traffic injuries.Methods and Materials: We analyzed survey responses of 370 bus drivers about six of voluntary engagement in distraction and seven of suceptibility to involuntary distraction using the questionnaire (37 questions). Differences between different groups of independent variables examined using ANOVA model. Was identified most important factors of voluntary engagement in distraction and susceptibility to involuntary distraction related to road traffic injuries based on the average score of drivers. A regression wad applied to estimate of the impact of factors driver distraction on the road traffic injuries using the Odds ratio. Our study was carried out in 2018 and its statistical analysis in using STATA version 14.

Mean (SE) of mean score of voluntary engagement in distraction was estimated 11/53 (0.23), attitudes and beliefs about distraction 63.16 (0.75), susceptibility to involuntary distraction 14 (0.37) and overall score of distraction  88/7 (0.99). 63.78% of drivers of intercity buses were classified in low distraction. Continually checking roadside accident scenese and reading roadside advertisements were identified as most important factors of voluntary engagement in distraction (mean of 2.6 and 2.5, respectively). Rosdside accident scenes and  speaking of passenger with driver were identified as most important factors of suceptibility to Involuntary distraction ( each of mean=2.5). A significant relationship was found between severity of distraction while driving and each of variables age, marital status, driving history, number of driving services per month and negative score status in driving license. The odds of accidents related to traffic accidents for drivers that involving hold phone conversations during driving was increase by 1.46 times.

Event roadside accident scenese and continually checking, reading roadside advertisements and speaking of passenger with driver were identified as most important factors of driver distraction among bus drivers. Individual factors such as age and driving experience, driving habits including number of driving services per month and negative score status (on the license) can be influenced by driver distraction severity. Previous studies results showed that driver distraction status and identifying the most important factors of  driver distraction were not sufficiently considered. Present studies results indicate the importance of a number of driver distraction factors compared to other factors.

Traffic accidents outcomes not only involve death and injury in the community, but also lead to a collapse in social relationships, disturbing mental health, and lowering the quality of life of people in these communities. Violent behaviors in driving in addition to physical harm and death also affect the social and mental health of citizens. This research was conducted to identify violent behavior of motor vehicle drivers and to measure and distribute these behaviors in Tehran.
Methods and Materiales: This research was carried out using a researcher-made questionnaire with high validity and reliability in the period of September-December 2018. The questionnaire consisted of two sections of demographic information of drivers and 20 specific questions about violent behaviors. Exclusive questions on the 5-point Likert scale were completely disagreeable = 1 to totally agree = 5. Content validity coefficient was used to calculate content validity, which was 0.7 for any questions and 0.72 for all questions. Using the 10 experts, content validity index was also 0.8. Cronbach's alpha coefficient was used for reliability. Cronbach's coefficient was 0.7. Data were analyzed using SPSS software version 22 and descriptive statistics and non-parametric statistical analysis (Mann-Whitney and Kruskal).

Being nervous from getting stuck in traffic or getting stuck behind a slow-driving driver has the highest distribution among drivers (11.2). The lowest mean was the passing of red lights and tongues or smears for other drivers. Investigating the relationship between demographic variables and the degree of violence in drivers also showed a significant relationship between vehicle type and mean of violence (p = 0.001) and between mean of violence in two groups of drivers who had a history of conflict and the group which did not have (p = 0.018).

Considering that violent behavior in driving can have many negative consequences in the society, educations should be applied for people who have a history of conflict and engagement with other people and have less patience in traffic; in order to improve driving behavior, aggression control and respecting the law.

Between in-vehicle tools, cell phone use while driving is known as distraction sources in the world. This issue is even more important because of the increased accidents and losses caused by driving it. The purpose of this study was to investigate driver behavior and determine the factors affecting the use of cell phone while driving.

To achieve the goal, the theory of planned behavior was used. A questionnaire was designed based on this theory and collected in Gorgan city. The “factor analysis’ method was used to evaluate the factors affecting the use of cell phone while driving.

Results showed that among the five important factors of driving behavior, perceived behavioral control, explained 25.32, had highest impact on cell phone use while driving. also, other factors like addicted to mobile phone and demographic characteristics were the second and third cause of mobile phone use while driving.

The results indicate that the driver is convinced that he is controlling his behavior and is able to react quickly and responsibly against unexpected events (such as the sudden braking of a car while using a cell phone), among all of variable, this variable is the most important that cause use of cell phone. Therefore, So, authorities should pay attention to the mentioned shortcomings and attempt to take a helpful strike for reforming them.