Designing a conceptual model for the formation of unsafe antisocial behaviors in motor vehicle drivers: a grounded theory study.

BACKGROUND: Many accidents caused by vehicles are the result of improper driving behavior. Use the vehicle in an antisocial form has led to a phenomenon called driving violence. Antisocial behavior while driving has a potential risk to other road users. This study aims to explain the conceptual framework of the formation of unsafe antisocial behaviors in the road traffic field. METHODS: This qualitative grounded theory study was conducted with exploratory methods. 31 participants were included in this study. Purposeful and theoretical sampling was used in this study. The data collection process was semi-structured interviews. Codes, subcategories, and categories were extracted by the inductive process and analyzed by Corbin and Strauss approach. Trustworthiness criteria were used to assure the quality of the results. The data analysis process continued until there were no new concepts. RESULTS: A conceptual model was developed to explain the different relationships between the main categories extracted from the study. 10 main categories with 44 subcategories were extracted. Categories include cultural factors, educational factors, rules, economic factors, psychological factors, infrastructure weakness, poor socialization of individuals, violent driving, reduced social welfare and reduced traffic safety. CONCLUSIONS: The people's socialization weakness in society was considered as the core concept in the process of formation of these behaviors. The conceptual model obtained from this study can be used in developing prevention programs and identifying the required interventions Considering the negative consequences caused by this type of behavior, its prevention should be the focus of road traffic policy makers.

Exploring the Factors Affecting Unsafe Antisocial Behaviors of Drivers in Iran: A Qualitative Study.

OBJECTIVE: To explore the factors affecting unsafe antisocial behaviors of drivers in the context of Iran. METHODS: The interviews were conducted from June to November 2019. A number of 19 participants were selected using purposive sampling method. The data were collected using face to face in-depth semi-structured interviews. Content analysis using Granheim's approach was applied for data analysis. RESULTS: Seven categories and 14 sub-categories were extracted from the data. The categories included cultural factors, educational and training factors, laws, imitating, substance abuse, awareness and attitude, and psychological problems. CONCLUSION: Based on the findings, various cultural, legal, educational, individual and psychological factors affect the unsafe antisocial behavior in driving. Seemingly, such behaviors could increase the chance of death or injury caused by road traffic crashes among the road users and affect social welfare of the citizens and road user's safety.

The Relationship between Nurse's Job Stress and Patient Safety.

BACKGROUND: Patient safety is a key element of the quality of health services. Nurses are the largest group that care for patients, observing safe in nursing care would reduce injuries, disability, morbidity and mortality. However, high stress can lead to a decline in the quality of nursing care. AIM: This study aimed to investigate the relationship between job stress of the nurses and patient safety in a teaching hospital of Hamadan in 2017. MATERIAL AND METHODS: This is a cross-sectional study. The data was gathered by a questionnaire of Nurse's job stress prepared by the researcher that after confirming the validity and reliability was completed by 198 nurses of three teaching hospitals of Hamadan city that were selected by simple random sampling and the checklist of patient safety that was collected by the researcher. Data analysis was done in the two levels of descriptive and analysis statistics. RESULTS: The results showed that the job stress of the nurses and patient safety (mean = 1.75 and SD = 0.114) have been at an average level. There was no statistically significant relationship between Nurse's job stress and patient safety because the Spearman correlation coefficient showed that r = 0.007 and p = 0.919. Among the demographic factors, there was only a significant relationship between marital status and Nurse's job stress (p < 0.05). CONCLUSION: Because of nursing job stress is affected by different working conditions, further studies in the many hospitals are needed. Moderate levels of patient safety are not acceptable; Therefore, heath's policymakers should focus on providing the safety of all patients at the optimal level, with more effort to reduce the stress of their nurses at the lowest level.

Analysis of developmental level of counties of Fars in terms of health infrastructure indicators using standardized scores pattern approach and factor analysis.

INTRODUCTION: It is necessary for planning in order to achieve optimal development, to have knowledge and understanding of the current situation. This identification requires separate areas of study into planning and assessing regions of each area with development indicators and analysis and ranking each area in terms of having gifts of development. The study also aims to analyze the development level of counties of Fars in terms of health infrastructure indicators using standardized scores pattern and factor analysis. METHODS: This is a descriptive and applied study, which has discussed the levels of 29 counties of Fars based on 10 health selected indicators using a standardized scoring model. Data were collected using a data collection form developed by the researchers through the Center of Statistics and Shiraz University of Medical Sciences. Results were analyzed using Excel and SPSS 19. RESULTS: Based on calculations according to standardized score and factor analysis methods, Shiraz and Rostam had the most and the least level between the other cities, respectively. Also development coefficient and operating score of the studied counties ranged from a maximum of 0.894 to a minimum of -0.941, and a maximum of 3.861 to a minimum of 2.001, respectively. DISCUSSION: There are relatively large differences between different counties in healthcare sector, and most studied counties in terms of healthcare sector indicators are not satisfactory. So planning how to allocate healthcare resources from policy makers to improve the studied counties is essential.