Tracing the physiological response and behavioral performance of drivers at different levels of mental workload using driving simulators.

INTRODUCTION: The use of mobile phones while driving is known to be a distraction factor and a cause of accidents. The way in which different kinds of conversations affect the behavioral performance of the driver as well as the persistence of the effects are not yet fully understood. METHOD: In this study, in addition to comparing brain function and behavioral function in dual task conditions in three conversations types, the persistent effects of these types of conversations have also been traced. RESULTS: The results show that the content of the mobile phone conversation while driving is the cause of the persistent changes in behavioral and brain functions. Increased time headway and lane departure was observed during and up to 5 min after the emotional conversation was finished. EEG bands also varied in different types of conversations. Cognitive conversations caused an increase in the activity of the alpha and beta bands while emotional conversations enhanced the rate of gamma and beta bands. A meaningful correlation was found between changes in the theta and alpha bands and changes in behavioral performance both during the dual task condition and after the conversation was finished, was also observed. CONCLUSIONS: The content of the conversation is one of the most important factors that increase the risk of road accidents. This can also deteriorate the behavioral performance of the driver and can have persistent effects on behavioral performance and the brain. Practical applications: The findings of this study provide a basis to measure and tracing drivers' cognitive distractions induced by different levels of mental workload through physiological and behavioral performances.

Determining the Levels of Urbanization in Iran Using Hierarchical Clustering.

BACKGROUND: In this study, we used a variety of factors that affect urbanization in Iran to evaluate different provinces in Iran in terms of the level of urbanization. METHODS: Using information from census 2011, we collected data on 33 indicators related to urbanization in 31 provinces in Iran. To rank the provinces we used density-based hierarchical clustering scheme. To determine similarities or differences between the provinces, the square of the Euclidean distance dissimilarity coefficient; Ward's algorithm was used to merge the provinces to minimize intra-cluster variance. One-way analysis of variance (ANOVA) was used to determine the variance between the variables used to rank the provinces in terms of different levels of urbanization. Statistical analysis was performed using SPSS. RESULTS: The provinces in Iran were combined with each other in 30 stages and classified into four levels. Taking into account the variables used to rank the level of urbanization, Tehran, and Alborz provinces were at the highest level of urbanization. On the other hand, the provinces of Sistan and Baluchistan, Kerman, North Khorasan, South Khorasan, Hormozgan, and Bushehr were at the lowest level of urbanization. CONCLUSION: Identification of provinces at the same level of urbanization can help us to discover the strengths and weaknesses in the infrastructures of each of them. Given the differences between various levels of urbanization, the identification of factors that are effective in the process of urbanization can help to access more information required for designing plans for the years to come.

A case-control study on risk factors for unintentional childhood poisoning in Tehran.

BACKGROUND: Poisoning is a major public health problem and is one of the most frequent causes of emergency hospital admissions. The aim of this study was to identify the main risk factors for unintentional childhood poisoning in Tehran, Iran and to suggest possible causes and preventative measures. METHODS: In this case-control study (case, n=140; control, n=280), two controls were selected for every case. Controls were matched by age, sex, and date of hospital attendance. All children and their guardians were then interviewed by the same person using a standard questionnaire that covered the demographic, behavioral, and risk factors associated with accidental poisonings. RESULTS: The most common type of poisoning was related to narcotics (58.6%); and among the narcotics, methadone was the most prevalent poisoning agent (74.7%). Multivariate conditional logistic regression model revealed that addiction in the family (OR=14.6; 95% CI:6.2-34.6), previous poisoning (OR=7; 95% CI:2.4- 20.2), maternal occupation (OR=4; 95% CI:1.3- 12.3), and inaccessibility of poisoning products (OR=0.03; 95% CI:0.01- 0.12) were the main risk factors in unintentional childhood poisoning. CONCLUSION: Addiction in the family as a risk factor and inaccessibility of poisoning products as a protecting factor were recognized to have the highest correlation with the unintentional child poisoning. These two factors were considered as priorities in health education programs.