Road safety data collection systems in Iran: A comparison based on relevant organizations

A qualitative study on apparent and latent contributing factors to driving errors in Iran

Road traffic crashes (RTCs) disproportionately impact low and middle-income countries (LMICs). Current interventions in LMICs primarily target road user behavior, neglecting systemic issues and casting drivers as mere contributors. Given Iran's unique cultural, financial, and social intricacies, this study aims to explore the latent causes of RTCs, prioritizing drivers' experiences and encompassing insights from various traffic system components. Applying a qualitative approach, data were collected through 46 semi-structured interviews with 38 participants, including drivers and experts from traffic-related organizations. Content analysis identified ten themes as contributing to driving errors. Direct factors included fatigue influenced by economic and occupational conditions, distraction from internal and external sources, reckless behaviors influenced by traffic culture and environment, and Inadequate driving skills due to training. Macro-scale challenges in road infrastructure, vehicle quality, education, and accident investigations were highlighted. The lack of a centralized traffic safety authority and a predominant focus on penalizing drivers overshadowed systemic issues. The study offers valuable insights into the complex interplay of factors contributing to driving errors in LMICs, advocating for a paradigm shift towards holistic, systemic interventions beyond individual driver behavior and challenging the conventional blame-centric view associated with driving errors.

Evaluation of cost-effectiveness of single-credit traffic safety course based on Kirkpatrick model: a case study of Iran

BACKGROUND

Training plays a role in reducing traffic accidents, and evaluating the effectiveness of training programs in managers' decision-making for training continuation is important. Thus, the present study aimed to evaluate the cost-effectiveness of a single-credit traffic safety course based on the four levels of the Kirkpatrick model in all Iranian universities.

METHODS

This interventional study aimed to evaluate the cost-effectiveness of a single-credit traffic safety course based on the Kirkpatrick model from 2016 to 2020 in Iran. The data were collected in three stages: (1) calculating the costs of offering traffic safety courses, (2) determining the effectiveness of providing such courses based on the levels of the Kirkpatrick model, and (3) evaluating the cost-effectiveness of administering traffic safety courses. Data were collected through researcher-made and standardized questionnaires. The research population included traffic safety course instructors and university students who could take this course. Finally, the data were analyzed with SPSS v. 23 and also calculations related to ICER, which shows the cost effectiveness of providing single credit course.

RESULTS

Scores of the students' reaction level to the traffic safety course was 41.8% before the course; this score was estimated at 67% after the course. At the level of learning, students' knowledge was 43.6% before the training course, which reached 73% after the course. At the level of behavior, the state of students' desirable traffic behaviors was 54% before the course, which reached 66.1% after the course. The educational effectiveness of the course presentation at the level of results was 58.2% before and 74.8% after the course. While assuming that the weights of all model levels were constant, the cost of a 1% increase in the overall educational effectiveness by using the Kirkpatrick model, compared to not providing the course (not administering the intervention) was 486.46 USD.

CONCLUSION

The results showcased the effectiveness of the traffic safety course in all four levels of The Kirkpatrick model. Therefore, policy-makers and officials in charge of delivering this program should strengthen it and resolve its deficiencies to realize all its educational goals at the highest level.

Assessing the design of road traffic death information systems in Iran: A participatory systems approach

AIM

To describe and analyze the information architecture and information pathways of the road traffic death recording, registration and reporting system in Guilan Province, northernIran.

METHODS

We used Business Process Mapping, a qualitative approach. This participatory and iterative approach consists of a document review, key informant interviews, development of a process map and a participatory workshop with key stakeholders to illuminate and validate the findings. We classified the tasks performed in the system into three phases: (1) Identification and recording; (2) Notification and registration, and (3) Production of statistics.

RESULTS

We identified 13 stakeholders, with operating and influencing roles in the process of identification, registration and production of statistics about road traffic deaths in Guilan province. The three main sources of road traffic death statistics are the Ministry of Health and Medical Education, the National Organization for Civil Registration and the Forensic Medicine Organization. Our results reveal a highly fragmented system with minimal cross-sectoral data exchange. Each stakeholder operates in a silo resulting in delays and redundancies in the operating system. In the absence of an effective communication among stakeholders, the information exchange was dependent on the family of the deceased. These fragmented information silos alter the compilation of cause of death statistics and result in under-reporting and discrepancies in road traffic deaths figures.

CONCLUSIONS

Designing a comprehensive road traffic information system that provides accurate and timely information requires an understanding of the information flow and the entangled web of different stakeholders operating in the system. Participatory systems approaches such as process mapping can assist in capturing the complexity of the system and the integration process by facilitating stakeholders' engagement and ownership in improving the design of the system.

The effectiveness of fixed speed cameras on Iranian taxi drivers: An evaluation of the influential factors

Background

The adherence to speed limits can reduce deaths associated with road traffic injuries (RTIs) by more than a quarter. This study aimed to evaluate the effective factors on the speeding behavior of Iranian taxi drivers around fixed speed cameras.

Method

Telematics devices used in this study collected the location and speed of the vehicles. The units of analysis in this study were trips per camera, including 2.5 km before and after each camera. Linear regression analysis was used to identify kangaroo driving (KD), defined as trips with a significant V-shape in speed distribution around the camera. In the clustered camera zones, cameras were placed at regular intervals of approximately 3.5 km.

Findings

A total of 93,160 trips were recorded from 13,857,443 data points. There was an inverse association between drivers' age and KD with an odds ratio (OR) of 0.98 (95% confidence interval: 0.98-0.98). The intercity trips had a substantially higher probability of KD than urban trips (OR: 4.94 [4.73-5.16]). The tendency of drivers toward KD during the daylight hours vs. nighttime was significant for both urban (OR: 1.15 [1.06-1.25]) and intercity (OR: 1.18 [1.14-1.22]) trips. The 4 -8 a.m. period had the highest chance of KD in both urban (10.71% [7.41-14.53]) and intercity (44.13% [41.18-47.09]) trips. There was a significant decrease in the odds of KD inside the clustered camera zones (OR: 0.22 [0.20-0.25]).

Conclusion

The heterogeneous occurrence of KD in different locations and times indicates the necessity of evidence-based decision-making in urban planning to improve safe driving behaviors. The lower occurrence of KD in clustered camera zones could be a practical key to the effective control of speeding behaviors by helping in the efficient placement of cameras through sustainable development of cities and roads.

Bayesian spatial analysis of crash severity data with the INLA approach: Assessment of different identification constraints

Multinomial logit models have been widely used in the analysis of categorical crash data. When the regional information of the data is available, the dependence structure needs to be incorporated into the model to accommodate for spatial heterogeneity. We consider a Bayesian multinomial structured additive regression model to analyze categorical spatial crash data and compare its performance with a fractional split multinomial model. We use the multinomial-Poisson transformation to apply the integrated nested Laplace approximation method for fitting the proposed model efficiently and fast. Moreover, we consider two different types of identifiability constraints to deal with the inherent identifiability problem of the multinomial models. The proposed models are studied through simulated examples and applied to a road traffic crash dataset from Mazandaran province, Iran.

The level and trend of road traffic injuries attributable mortality rate in Iran, 1990-2015: a story of successful regulations and a roadmap to design future policies

BACKGROUND

Road-Traffic-Injuries (RTIs) are predicted to rise up to the fifth leading cause of worldwide death by 2030 and Iran has the third highest RTIs mortality among higher-middle income countries. Although the high mortality of RTI in Iran is a warning, it provides the opportunity to indirectly assess the implemented RTI-related regulations' effectiveness via high-resolution relevant statistics and, hence, Iran could serve as a guide for countries with similar context. In order to do so, we utilized this study to report the time and spatial trends of RTIs-related mortality in different age and sex groups and road user classes in Iran.

METHODS

Based on the national death-registration-system (DRS), cemeteries data, and the demographic characteristics, and after addressing incompleteness, we estimated mortality rates using spatiotemporal and Gaussian process regression models. We assessed Pearson seatbelt and helmet use and RTIs-attributable Age-Standardized-Morality-Rate (ASMR) associations. We also predicted RTIs-death-numbers, 2012-2020, by fitting a Generalized Additive Model to assess the status of achieving relevant sustainable development goal (SDG), namely reducing the number of RTIs-related deaths by half.

RESULTS

Overall RTIs-attributable death and ASMR at the national level increased from 12.64 [95% UI, 9.52-16.86] to 29.1 [22.76-37.14] per 100,000 people in the time period of 1990-2015. The trend consisted of an increasing segment in 1990-2003 followed by a decreasing part till 2015. The highest percentage of death belonged to the three-or-more-wheels motorized vehicles. Pedestrian injuries percentage increased significantly and the highest mortality rate occurred in 85 years and older individuals. Low prevalence of seatbelt and helmet use were observed in provinces with higher than the median ASMR due to the relevant cause of each. RTIs-attributable death number is expected to reduce by 15.99% till 2020 which is lower than the established SDG goal.

CONCLUSIONS

Despite the observed substantial moderation in the RTI-ASMR, Iran is till among the leading countries in terms of the highest mortality rates in the world. The enforced regulations including speed limitations (particularly for elder pedestrians) and mandatory use of seatbelt and helmet (for young adult and male drivers) had a considerable effect on ASMR, nevertheless, the RTI burden reduction needs to be sustained and enhanced.

Developing a National Integrated Road Traffic Injury Registry System: A Conceptual Model for a Multidisciplinary Setting

Introduction

Despite a high burden of traffic injuries, effective integrated or linked injury surveillance systems are rarely available in many low- and middle-income countries (LMICs). The aim of the current study was to define a conceptual model for developing a national integrated traffic injury registry in Iran.

Methods

A mult-method study financially and technically supported by the World Health Organization, Iranian Ministry of Health, Iranian Traffic Police, and the Iranian Legal Medicine Organization was conducted. A theoretical framework, forming the core conceptual components, was developed based on expert reviews. The preliminary conceptual model was developed by a panel of experts and tailored through a national workshop of 50 scientists, authorities and experts from nearly all sectors related to road safety promotion and injury management. It was then sent out to external reviewers in order to assess and improve the content validity of the model.

Results

The conceptual model was developed to have six components. These included 1) aims and core definitions; 2) content and core measurements; 3) data flow; 4) data collection routines; 5) organizational matrix; 6) implementation organization. The Haddon's matrix was adapted to be used as the theoretical framework in defining the content and data flow components of IRTIR. Five subcomponents were defined in the content and core measurements component with each having several subcategories. Each subcomponent/subcategory was finally divided into several item groups to guide defining the final data measurement variables. The data flow component was defined with six data sequence stations. Through the organizational matrix component, five major organizations relevant to road traffic safety were defined as core data production contributors. Some organizations also owned several sub-organizations which contributed in this regard.

Conclusion

It is concluded that the IRTIR conceptual model includes the required six components for developing a national integrated registry for Iran. Its main component called, content and core measurements, leads the researchers in developing final data collection tools in developing the national registry of road traffic injuries in Iran.