A decade of child pedestrian safety in England: a bayesian spatio-temporal analysis.

BACKGROUND: Child pedestrian injury is a public health and health equality challenge worldwide, including in high-income countries. However, child pedestrian safety is less-understood, especially over long time spans. The intent of this study is to understand factors affecting child pedestrian safety in England over the period 2011-2020. METHODS: We conducted an area-level study using a Bayesian space-time interaction model to understand the association between the number of road crashes involving child pedestrians in English Local Authorities and a host of socio-economic, transport-related and built-environment variables. We investigated spatio-temporal trends in child pedestrian safety in England over the study period and identified high-crash local authorities. RESULTS: We found that child pedestrian crash frequencies increase as child population, unemployment-related claimants, road density, and the number of schools increase. Nevertheless, as the number of licensed vehicles per capita and zonal-level walking/cycling increase, child pedestrian safety increases. Generally, child pedestrian safety has improved in England since 2011. However, the socio-economic inequality gap in child pedestrian safety has not narrowed down. In addition, we found that after adjusting for the effect of covariates, the rate of decline in crashes varies between local authorities. The presence of localised risk factors/mitigation measures contributes to variation in the spatio-temporal patterns of child pedestrian safety. CONCLUSIONS: Overall, southern England has experienced more improvement in child pedestrian safety over the last decade than the northern regions. Our study revealed socio-economic inequality in child pedestrian safety in England. To better inform safety and public health policy, our findings support the importance of a targeted system approach, considering the identification of high-crash areas while keeping track of how child pedestrian safety evolves over time.

FEEDBACK trial - A randomised control trial to investigate the effect of personalised feedback and financial incentives on reducing the incidence of road crashes.

BACKGROUND: Road crashes continue to pose a significant threat to global health. Young drivers aged between 18 and 25 are over-represented in road injury and fatality statistics, especially the first six months after obtaining their license. This study is the first multi-centre two-arm parallel-group individually randomised controlled trial (the FEEDBACK Trial) that will examine whether the delivery of personalised driver feedback plus financial incentives is superior to no feedback and no financial incentives in reducing motor vehicle crashes among young drivers (18 to 20 years) during the first year of provisional licensing. METHODS: A total of 3,610 young drivers on their provisional licence (P1, the first-year provisional licensing) will participate in the trial over 28 weeks, including a 4-week baseline, 20-week intervention and 4-week post-intervention period. The primary outcome of the study will be police-reported crashes over the 20-week intervention period and the 4-week post-intervention period. Secondary outcomes include driving behaviours such as speeding and harsh braking that contribute to road crashes, which will be attained weekly from mobile telematics delivered to a smartphone app. DISCUSSION: Assuming a positive finding associated with personalised driver feedback and financial incentives in reducing road crashes among young drivers, the study will provide important evidence to support policymakers in introducing the intervention(s) as a key strategy to mitigate the risks associated with the burden of road injury among this vulnerable population. TRIAL REGISTRATION: Registered under the Australian New Zealand Clinical Trials Registry (ANZCTR) - ACTRN12623000387628p on April 17, 2023.

Spatial and temporal analysis of road traffic crashes and ambulance responses in Lagos state, Nigeria.

BACKGROUND: Sub-Saharan African countries, Nigeria inclusive, are constrained by grossly limited access to quality pre-hospital trauma care services (PTCS). Findings from pragmatic approaches that explore spatial and temporal trends of past road crashes can inform novel interventions. To improve access to PTCS and reduce burden of road traffic injuries we explored geospatial trends of past emergency responses to road traffic crashes (RTCs) by Lagos State Ambulance Service (LASAMBUS), assessed efficiency of responses, and outcomes of interventions by local government areas (LGAs) of crash. METHODS: Using descriptive cross-sectional design and REDcap we explored pre-hospital care data of 1220 crash victims documented on LASAMBUS intervention forms from December 2017 to May 2018. We analyzed trends in days and times of calls, demographics of victims, locations of crashes and causes of delayed emergency responses. Assisted with STATA 16 and ArcGIS pro we conducted descriptive statistics and mapping of crash metrics including spatial and temporal relationships between times of the day, seasons of year, and crash LGA population density versus RTCs incidence. Descriptive analysis and mapping were used to assess relationships between 'Causes of Delayed response' and respective crash LGAs, and between Response Times and crash LGAs. RESULTS: Incidences of RTCs were highest across peak commuting hours (07:00-12:59 and 13:00-18:59), rainy season and harmattan (foggy) months, and densely populated LGAs. Five urban LGAs accounted for over half of RTCs distributions: Eti-Osa (14.7%), Ikeja (14.4%), Kosofe (9.9%), Ikorodu (9.7%), and Alimosho (6.6%). On intervention forms with a Cause of Delay, Traffic Congestion (60%), and Poor Description (17.8%), had associations with LGA distribution. Two densely populated urban LGAs, Agege and Apapa were significantly associated with Traffic Congestion as a Cause of Delay. LASAMBUS was able to address crash in only 502 (36.8%) of the 1220 interventions. Other notable outcomes include: No Crash (false calls) (26.6%), and Crash Already Addressed (22.17%). CONCLUSIONS: Geospatial analysis of past road crashes in Lagos state offered key insights into spatial and temporal trends of RTCs across LGAs, and identified operational constraints of state-organized PTCS and factors associated with delayed emergency responses. Findings can inform programmatic interventions to improve trauma care outcomes.

Risky motorcycle riding behaviour among young riders in Manipal, India.

BACKGROUND: Motorcycles are one of the most commonly used transportation modes in low and middle-income countries. In India, motorized two-wheelers comprise 70% of the total vehicle population, and motorcycle users are considered the most vulnerable road users. It is essential to understand the risky riding behaviour and associated factors among the motorcyclists to develop evidence-based traffic safety programs targeting motorcycle riders. The purpose of the current study was two-fold. First, it aimed to determine the appropriate structure of a modified version of the MRBQ among young riders in Manipal, India. Second, it assessed to what extent MRBQ factors were associated with self-reported crash involvement and violations. METHODS: The motorcycle rider behaviour questionnaire (MRBQ) is a 43-item scale that assesses five aspects of risky motorcycle rider behaviour, i.e., violations, control errors, traffic errors, stunts, and protective equipment. The MRBQ, along with measures of socio-demographic variables and the number of motorcycle crashes, was filled out by 300 young motorcycle riders who were in the age group of 18-25 years and had been riding for at least the past three years (93% males, 92.3% students). RESULTS: Five factors emerged out of the MRBQ after an exploratory factor analysis: traffic errors, control errors, stunts, protective equipment, and violations. Cronbach's alpha for these factors ranged from .66 to .82. Reports of performing stunts and committing violations were positively associated with self-reported near-crash experiences over the past three months. Riders reporting stunts, violations and using a motorcycle of 125-200 cc reported having received more fines in the last three months. These findings were confirmed in both univariate and multivariate binary logistic regression models. CONCLUSION: The study assessed the factor structure of a modified version MRBQ and the extracted factors associations with self-reported crash involvement. The factor structure revealed in the current study is consistent with MRBQ factor structures found in other countries. However, the support for a relationship between MRBQ factors and self-reported crashes was less significant. The findings suggest that if replicated by future studies, local policymakers are advised to focus on the five MRBQ factors while planning future interventions to achieve a reduction in the number of road crashes among motorcyclists.

Who is to blame for crashes involving autonomous vehicles? Exploring blame attribution across the road transport system.

The introduction of fully autonomous vehicles is approaching. This warrants a re-consideration of road crash liability, given drivers will have diminished control. This study, underpinned by attribution theory, investigated blame attribution to different road transport system actors following crashes involving manually driven, semi-autonomous and fully autonomous vehicles. It also examined whether outcome severity alters blame ratings. 396 participants attributed blame to five actors (vehicle driver/user, pedestrian, vehicle, manufacturer, government) in vehicle-pedestrian crash scenarios. Different and unique patterns of blame were found across actors, according to the three vehicle types. In crashes involving fully autonomous vehicles, vehicle users received low blame, while vehicle manufacturers and government were highly blamed. There was no difference in the level of blame attributed between high and low severity crashes regarding vehicle type. However, the government received more blame in high severity crashes. The findings have implications for policy and legislation surrounding crash liability. Practitioner summary: Public views relating to blame and liability in transport accidents is a vital consideration for the introduction of new technologies such as autonomous vehicles. This study demonstrates how a systems ergonomics framework can assist to identify the implications of changing public opinion on blame for future road transport systems. Abbreviation: ANOVA: analysis of variance; DAT: defensive attribution theory; IV: independent variable.

A bibliometric analysis of the published road traffic injuries research in India, post-1990.

BACKGROUND: Globally, road traffic injuries are the leading cause of death among those aged 15-29 years. However, road traffic injury research has not received adequate attention from the scientific community in low- and middle-income countries, including India. The present study aims to provide a bibliometric overview of research assessing road traffic injuries in India. METHODS: We used Scopus to extract relevant research in road traffic injuries published from 1991 to 2017. This study presented the key bibliometric indicators such as trends of annual publications and citations, top 10 authors, journals, institutions and highly cited articles, citation analysis of articles, co-occurrence of keywords, etc. Analysis was performed using Scopus, Microsoft Excel, and VOS-viewer. RESULTS: A total of 242 articles were retrieved with an h-index of 18, excluding self-citations. A steadfast growth of publications was documented in last decade, especially after the year 2010. The h-index of the top 10 authors, institutions, journals and highly cited articles did not surpass single digits. A network visualisation map showed that 'traffic accident', 'male', 'adolescent' and 'child' were the most commonly encountered key terms. The prominent authors were Gururaj G, Dandona R, and Hyder AA, whereas the top journals were the Indian Journal of Forensic Medicine and Toxicology, Medico Legal Update, and the International Journal of Applied Engineering Research and top institutions were the All India Institute of Medical Sciences, New Delhi, the Indian Institute of Technology, Delhi, and the Administrative Staff College of India. CONCLUSION: In India, road traffic injuries research is inadequate in quantity and quality, warranting greater attention from researchers and policy planners to address the burden of road traffic injuries.

Injury-severity analysis of crashes involving defective vehicles and accounting for the underlying socioeconomic mediators.

Crashes occur from a combination of factors related to the driver, roadway, and vehicle factors. The impact of vehicles on road crashes is a critical consideration within road safety analysis, even though not much studies have been conducted in this area. This study assessed how various vehicle and other crash factors are significantly associated with crash outcomes. To do this, historical vehicle defect-related crashes were obtained for the state of Alabama from 2016 to 2020. After data cleaning, a crash injury severity model was developed using the random parameters multinomial logit with heterogeneity in means approach to account for possible unobserved heterogeneity in the data. A spatial analysis was further conducted to better understand vehicle defect crashes as a broader societal issue and potentially explore their connection with the socio-demographic characteristics of the drivers of these vehicles. The preliminary data analysis showed that brake and tire defects accounted for about 65% of the vehicle defects associated with the crashes. The model estimation results revealed that improper tread depth and headlight defects were associated with major injury outcomes, while brake defects were more associated with minor injuries. Also, crashes associated with speeding, drunk driving, failure to use seatbelts, and those that occurred on curved roads left with downgrades were likely to result in major injuries. Findings from the spatial analysis showed that postal codes with higher median incomes are more likely to record lower vehicle defect-related crashes, unlike those that have higher proportions of females and African Americans. The study's findings provide data-driven evidence for sustained safety campaigns, workshops, and training on basic vehicle maintenance practices in the low-income communities in the state.

Environmental measures to improve pedestrian safety in low- and middle-income countries: a scoping review.

OBJECTIVES: This scoping study aims to identify environmental road safety measures implemented in low- and middle-income countries (LMICs) to reduce pedestrian injuries from collisions with motor vehicles. METHODS: This review followed Arksey and O'Malley's approach and reported results using the PRISMA-SCR 2018 checklist. A literature review was conducted in Medline, Google Scholar, and the Transport Research International Documentation database using keyword-derived medical subject heading terms. A total of 14 articles met the pre-established inclusion criteria and were analyzed using a data extraction matrix. The findings were categorized methodically into three prominent themes: (1) methods for reducing pedestrian exposure, (2) traffic calming strategies, and (3) measures for enhancing pedestrian visibility. RESULTS: Traffic calming strategies, including vehicular speed reduction, roadway contraction, and vertical and horizontal diversionary tactics, emerged as the most effective interventions for reducing pedestrian injuries within LMICs. Conversely, interventions geared towards minimizing pedestrian exposure, such as zebra crossings, crosswalks controlled by traffic signals, underpasses, or overpasses, often produced minimal effects, and occasionally exacerbated the risk of pedestrian accidents. Lack of pedestrian visibility due to density of street vendors and parked vehicles was associated with a higher risk of injuries, while billboards impaired drivers' attention and increased the likelihood of collisions with pedestrians. DISCUSSION: In LMICs, the effectiveness of environmental measures in reducing vehicle-pedestrian crashes varies widely. In the face of resource constraints, implementing interventions for pedestrian safety in LMICs necessitates careful prioritization and consideration of the local context.

Developing a national database of police-reported fatal road traffic crashes for road safety research and management in India.

Strengthening crash surveillance is an urgent priority for road safety in low- and middle-income countries. We reviewed the online availability and completeness of First Information Reports (FIRs; police reports) of road traffic crashes in India. We developed a relational database to record information extracted from FIRs, and implemented it for one state (Chhattisgarh, 2017-2019). We found that FIRs can be downloaded in bulk from government websites of 15 states and union territories. Another 14 provide access online but restrict bulk downloading, and 7 do not provide online access. For Chhattisgarh, 87% of registered FIRs could be downloaded. Most FIRs reported the date, time, collision-type, and vehicle-types, but important crash characteristics (e.g. infrastructure attributes) were missing. India needs to invest in building the crash surveillance capacity for research and safety management. However, in the interim, maintaining a national database of a sample of FIRs can provide useful policy guidance.

Risk exposure factors influencing the frequency of road crashes during the COVID-19 pandemic in Ciudad Juarez, Mexico. A negative binomial spatial regression model.

The article aims to investigate the influence of risk exposure factors on the frequency of road crashes from January to August 2020 in Ciudad Juarez, Mexico. It is a longitudinal study with four data sets: road crashes, population and housing census, location of economic activities, and road network information. Specifically, this study investigates the relationship between exposure factors - demographics, main roads and land use - and road crashes. A mixed method analysis was employed, (1) spatial analysis using GIS techniques; and (2) a negative binomial spatial regression model. The results showed a strong spatial dependence (0.274; p-value 0.00) of road crashes in the census tracts, and this effect was statistically significant (0.007) in the spatial regression model. In the model, a high probability (<0.05) of road crashes in the census tracts was found with the population aged 15 to 65 years, the length of main roads and the level of road coverage (Engel index), land uses with economic activities of an industrial and commercial character. The findings of this study successfully capture the social, economic, and urban conditions during the January-August 2020 period in the context of the COVID-19 pandemic. This new knowledge could help create preventive plans and policies to address the frequency of road crashes.

Determinants of self-efficacy of driving behavior among young adults in the UAE: Impact of gender, culture, and varying environmental conditions in a simulated environment.

Research on traffic accidents have acknowledged that human error is the leading cause of road accidents around the world. In the UAE, those aged between 18 and 30 years are involved in the most accidents. As a result, this study examines the perception, attitude and driving behavior of young adults in the UAE. Virtual Reality (VR) was used to examine driving behavior because it offers alternatives to assess driving behavior with a high degree of immersive experience in a safe and replicable environment. Participants drove through a virtual environment that resembled the urban environment of Abu Dhabi in the UAE, which included six traffic events. A sample of 12 females and 27 males also completed a pre and post-simulation questionnaire to report and evaluate their personal driving experience in Abu Dhabi. The volunteer group represented young drivers with limited driving experience and diverse cultural backgrounds. Results indicated that male drivers were less adhering to safe driving behavior compared to females. Even though both males and females exceeded the designated speed limit, males traveled longer distances over the limit. Additionally, it was found that young drivers tend to overestimate their skills with factors like gender, cultural background, and driving experience being key contributors. The results indicate that traffic authorities should take into consideration different approaches in the formulation of policies related to young drivers with periodic reassessment of skills and training to enhance the safety of driving in the UAE and the region.

One year of COVID-19: Impacts on safe driving behavior and policy recommendations.

INTRODUCTION: In the unprecedented year of 2020, the rapid spread of COVID-19 disrupted everyday activities worldwide, leading the majority of countries to impose lockdowns and confine citizens in order to minimize the exponential increase in cases and casualties. To date, very few studies have been concerned with the effect of the pandemic on driving behavior and road safety, and usually explore data from a limited time span. METHOD: This study presents a descriptive overview of several driving behavior indicators as well as road crash data in correlation with the strictness of response measures in Greece and the Kingdom of Saudi Arabia (KSA). A k-means clustering approach was also employed to detect meaningful patterns. RESULTS: Results indicated that during the lockdown periods, speeds were increased by up to 6%, while harsh events were increased by about 35% in the two countries, compared to the period after the confinement. However, the imposition of another lockdown did not cause radical changes in Greek driving behavior during the late months of 2020. Finally, the clustering algorithm identified a "baseline," a "restrictions," and a "lockdown" driving behavior cluster, and it was shown that harsh braking frequency was the most distinctive factor. POLICY RECOMMENDATIONS: Based on these findings, policymakers should focus on the reduction and enforcement of speed limits, especially within urban areas, as well as the incorporation of active travelers in the current transport infrastructure.

Improvement of road safety management systems of local governments in Korea after evaluating related indicators.

This study analyzes what has changed in the road safety management systems (RSMS) of local governments after evaluating the related indicators continuously from 2015 to 2019. It has evaluated 24 indicators in four areas of RSMS such as institutional management, intervention, intermediate outcome, and the final outcome, according to Han and Lee (2020). It seems that continuous evaluation of indicators of RSMSs in local governments for five years has helped to improve road safety performance in local governments. The result shows that the average overall scores have increased from 77.92 to 83.89, a 7.7% increase. This improvement should have resulted from the competition between local governments, which do not want to be at the bottom in the score comparison. The most remarkable increase has been identified in the areas of institutional management and intervention. They have increased by 13.3% and 16.0%, respectively. In terms of types of local governments, it has been found that the increase in overall scores is higher in provinces which include most rural areas than in metropolitans. However, it has been found that the improvement of institutional management and interventions are not directly associated with the increase of the intermediate and final outcomes, at least during the five years. Further studies examining the relationship between the four areas of RSMS are needed.

Impact of COVID-19 pandemic on road safety in Tamil Nadu, India.

This study uses structured literature mapping to review worldwide trends in traffic safety following the phenomenon of the COVID-19 pandemic. Motivated by dissimilar findings globally and a lack of evidence from emerging nations which have been significantly more affected by road traffic crashes, the study examines the impact of the pandemic-induced lockdown on road traffic deaths and injuries in Tamil Nadu, India. Using a holistic approach, methods such as ARIMA, Holt-Winters, Bayesian Structural Time Series, and Generalized Additive Model are employed for counterfactual prediction, to draw a causal inference of lockdown on traffic safety. In line with global studies, a substantial reduction in traffic crashes, injuries, and fatalities during lockdowns has been found. However, the comparison of relative differences shows that the number of grievous injuries reduced more than minor injuries, crashes, or fatalities. Furthermore, these relative differences were sustained even when metrics returned to normalcy in the post-lockdown phases. Further spatial stratification at two levels (cities and districts) shows that the macroscopic state-level trends are also broadly seen in the sub-units. This validates the consistency of trends across rural-urban differences and shows that, despite variations in the degree of enforcement of the lockdown within Chennai city, contrary to expectation, increased police presence did not have a differential impact on road crashes.

Identification of the Mechanical Failure Factors with Potential Influencing Road Accidents in Ecuador.

Road traffic accidents result in injury or even death of passengers. One potential cause of these accidents is mechanical failures due to a lack of vehicle maintenance. In the quest to identify these mechanical failures, this paper aims to set up the procedure to identify the mechanical failures that contribute to traffic accidents in cities located in developing countries, including the city of Cuenca-Ecuador. For present research, a database provided by the entity responsible for the Vehicle Technical Inspection, the Empresa Pública Municipal de Movilidad, Tránsito y Transporte and for the ones responsible of managing traffic accident data, Oficina de Investigación de Accidentes de Tránsito and Sección de Investigación de Accidentes de Tránsito was used. The vehicle subcategories M1 and M3 (bus type) and N1, so named according to Ecuadorian technical standards, were considered the most relevant regarding accident rates. The database was analysed with descriptive statistics, a Pareto chart and time series with the quadratic trend. From this analysis, the most significant failures found in the VTI in all three subcategories were the alignment of the driver headlight, both horizontal and vertical, braking imbalance on the 2nd axle, insufficient tire tread and parking brake effectiveness. All these failures showed a decreasing trend over time and in the forecast at a maximum of two to three years. The most relevant causes of road accidents recorded during the period 2009-2018 related to mechanical failures were the braking system (65.5%) and the steering system (17.2%) for subcategory M1.

Multidimensional prediction of work traffic crashes among Spanish professional drivers in cargo and passenger transportation.

The aim of this study was to examine the effect of different environmental, mechanical and individual factors associated with fatalities and serious injuries caused by work traffic accidents among cargo and passenger transport drivers (CPTD) in Spain. For this cross-sectional study, national data on work traffic accidents collected in Spain during the last 3 years were analyzed through a regression modeling approach, in order to predict the severity of traffic crashes involving CPTD. Using binary logistic regression analyses, it was found that the type of road and accident, the meteorological, light and vehicle conditions, individual characteristics and risky driving behaviors significantly predict the risk of fatal work traffic accidents and serious injuries. These findings highlight the importance of combining organizational efforts with national road safety policies in order to generate a traffic safety culture among CPTD.

Quantitative Analysis of the Social Costs of Road Traffic Crashes Literature.

Despite recent improvements in tackling road safety challenges, particularly in developed countries, road traffic crashes account for 1.35 million deaths annually and cost over 65 us$ billion. This paper reviews the existing socio-economic costs literature, highlights research gaps, and draws attention to the lack of analysis in developing countries, which account for 90% of the fatalities. We rely on both simple descriptive analyses and formal econometric analyses. Our descriptive results show an upward trend over the recent years, mostly in high and middle-income countries. The paper focuses on the differences in estimating the socio-economic costs of road traffic crashes using two popular methodologies, the willingness-to-pay (wtp) and the human capital (hc). Our econometric analysis shows that papers that use wtp tend to compute the impact as a percentage of gdp that is on average ̃1% higher than those that use the hc approach. Likewise, studies using the human capital method tend to underestimate the total socio-economic costs by a factor of two compared to the cost derived from the wtp approach; this gap then reduces substantially when accounting for population density, countries' income levels, and road safety outcomes. Further, the paper stresses the underreporting problem and the inexistence of a mechanism to reasonably account for it in socio-economic costs calculations. The paper concludes by advocating for more studies focusing on low and middle-income countries using a combination of common approaches with other valuation methods.

Can Professional Motorcyclists Be an Asset in the Immediate Post-Crash Care System in Benin? Baseline of Knowledge and Practices in the City of Cotonou (Benin).

PURPOSE: The situation of road crashes-related deaths remains problematic in low-income countries. The present study aims at analyzing the first-aid knowledge and practices of professional motorcyclists (PMs) in the city of Cotonou in Benin. MATERIALS AND METHODS: This is a cross-sectional analytical study conducted from 25 March to 19 April 2019 in Cotonou and concerned PMs registered in a fleet who gave their consent to participate in the study. The World Health Organization's two-stage adaptive cluster sampling technique was applied to select the eligible PMs while respecting the proportionality rate per fleet. A logistic regression analysis was done and the odds ratios were estimated with 95% confidence interval. RESULTS: The 430 PMs surveyed were all middle-aged men with an average age of 38.38 (±8.70). Among them, 62.56% knew at least one of the emergency phone numbers for the ambulance, police or fire services and 49.53% of the PMs knew at least one of the 3 techniques evaluated. In addition, 33.23% of PMs who had witnessed at least an RC stated that they had alerted the emergency services, and 32.27% said they had helped the victims. The main reason given for the lack of initiative in RCs was lack of knowledge of the course of action to take (19.64%). The level of knowledge was associated with the level of education (AOR: 3.11; CI 95%: 1.79-5.43) and with the length of experience (AOR: 2.56; CI 95%: 1.58-4.18). CONCLUSION: This study reveals that the level of knowledge and practice of PMs in the field of first aid in Cotonou is low and demonstrates the relevance and the need to include this target group in the first-aid chain for road crashes in Benin.

Mobile phone use while driving: Development and validation of knowledge, attitude, and practice survey instruments.

INTRODUCTION: Instruments that assess the knowledge, attitude, and practice (KAP) of mobile phone use serve as a primary assessment tool on which mobile phone distracted driving interventions can be designed. The objective of this study is to develop and validate KAP-modeled survey instruments that measure the knowledge of mobile phone hazards while driving (KMPHD), the attitude of drivers towards mobile phone use while driving (AMPUD), and the practice of mobile phone use while driving (PMPUD). METHOD: This study was a cross-sectional analytical survey conducted in Ibadan, Nigeria. Three instruments were designed to measure KMPHD, AMPUD, and PMPUD. Content validity, item analysis, exploratory factor analysis were conducted, and items were excluded based on the collective results of the analysis. The domains of the constructs and the reliability of the instruments are reported. A confirmatory factor analysis was used to assess the regression weights of each item and the model fit. RESULTS: From an original list of 13, 12, and 10 items in the KMPHD, AMPUD, and PMPUD instruments, a final list of 7, 5, and 7 items were generated in each survey instrument, respectively. Two domains of the knowledge of hazards and practice of mobile phone use were obtained, and attitude to phone use while driving was a single domain. The reliabilities (Cronbach alpha) of the KMPHD (0.881), AMPUD (0.954), and PMPUD (0.920) were sufficiently high. Also, all items in the three instruments had moderate-to-high regression coefficients, and the model fits of the instruments were good. CONCLUSIONS: This study provides KAP-modeled survey instruments that can be used to assess a population-based knowledge, attitude, and practice of mobile phone use while driving. Practical Applications: This survey instrument can be used in assessing baseline knowledge, attitude, and practice of phone use while driving and determine the focus and effectiveness of mobile phone-induced distracted driving interventions.

Traffic crashes in Dhaka, Bangladesh: analysing crashes involving unconventional modes, pedestrians and public transit.

Road safety is a global concern; particularly, in developing countries due to the significantly high collision occurrences and subsequent deaths. This study presents a spatial and temporal analysis of collision frequency and injury severity of crashes in Dhaka, Bangladesh. The focus is to understand the spatio-temporal trend of collisions involving pedestrians, public transit and unconventional modes, which are the key collision factors in Dhaka. This research utilizes the police-reported collision record for Dhaka for the years 2011-2015. In temporal analysis, temporal trends (monthly, daily and hourly) of injury severity of different vehicle occupants (pedestrians, public transit and unconventional modes) have been explored using descriptive analytics. Daily distribution suggests that a higher share of severe injuries involving pedestrians (16.6%) and unconventional modes (20.5%) occur on Fridays and Thursdays, respectively. The hourly distribution suggests that pedestrians are more vulnerable from 11:00am to 12:00pm on weekends. Unconventional mode users are vulnerable from 7:00am to 8:00am on weekdays. Spatial analysis is performed adopting a Kernel density estimation (KDE) technique. The results suggest that the major activity locations of Dhaka such as central business district (CBD), airport and ferry terminals are collision prone areas. Interestingly, the density of public transit collisions is skewed around the major transit hubs of the city.