Showing 3 results for Driving
Smb Kamaledini , T Rahimi , M Abedini Ardakani , M Hassanrezaee, Ss Mazloomimahmodabad,
Volume 14, Issue 6 (3-2016)
Abstract
Introduction: Traffic accidents are recognized the main causes of fatalities and injuries, as well as a worldwide public health problem. Among the many factors that contribute to accidents, risky behavior is the most common cause of them. This study aimed to investigate factors related lack of driving discipline among Yazd city drivers in 2014.
Methods: This study is a cross-sectional study has been performed on 373 drivers of Yazd in 2014. The sampling method was convenience. Data were collected by questionnaire and analyzed with SPSS16 software, using Pearson correlation tests, ANOVA, t-test and linear regression analysis.
Results: The data showed that average score of high-risk behavior was 81.41 and risk-taking attitudes and perceived risk were correlated with risky driving behavior significantly (p< 0.001). Among the variables entered into the regression model, risk-taking attitudes and risk perception could predict 35 percent of variance of risky behavior.) F= 27.2, R=0.59, R2= 0.35)
Conclusion: The results show that risky behaviors have influenced by risk-taking attitudes and perceived risk driving. So it is necessary to consider these factors in educational interventions
Azam Tarfiei, Mohammad Hassan Ehrampoush, Mohammad Hassan Lotfi, Alireza Adamezade, ُseyedeh Mahdeh Namayandeh, Mohammad Taghi Gghaneian,
Volume 19, Issue 4 (10-2020)
Abstract
Introduction: 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.
Methods: 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.
Results: 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).
Conclusion: 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.
Seyed Saeed Mazloomy Mahmoodabad, Batool Zeidabadi, Mohammad Reza Rajabalipour,
Volume 22, Issue 4 (11-2023)
Abstract
Introduction: 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).
Methods: 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.
Results: 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.
Conclusion: 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.
