Reducing traffic violations in minority localities: Designing a traffic enforcement program through a public participation process

Effectiveness of road safety interventions: An evidence and gap map

Background

Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low- and middle-income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high-income countries have successfully reduced RTI by using a public health approach and implementing evidence-based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high-income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.

Objectives

The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.

Search Methods

The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.

Selection Criteria

The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post-crash pre-hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non-fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.

Data Collection and Analysis

The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case-control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.

Main Results

The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post-crash pre-hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non-fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety-six percent of the studies were reported from high-income countries (HIC), 4.5% from upper-middle-income countries, and only 1.4% from lower-middle and low-income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.

Authors' Conclusions

The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence-synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.

Validation of a neighborhood sentiment and safety index derived from existing data repositories

BACKGROUND

The communities we live in are central to our health. Neighborhood disadvantage is associated with worse physical and mental health and even early mortality, while resident sense of safety and positive neighborhood sentiment has been repeatedly linked to better physical and mental health outcomes. Therefore, understanding where negative neighborhood sentiment and safety are salient concerns can help inform public health interventions and as a result, improve health outcomes. To date, fear of crime and neighborhood sentiment data or indices have largely been based on the administration of time consuming and costly standardized surveys.

OBJECTIVE

The current study aims to develop a Neighborhood Sentiment and Safety Index (NSSI) at the census tract level, building on publicly available data repositories, including the US Census and ACS surveys, Data Axle, and ESRI repositories.

METHODS

The NSSI was created using Principal Component Analysis. Mineigen and minimum loading values were 1 and 0.3, respectively. Throughout the step-wise PCA process, variables were excluded if their loading value was below 0.3 or if variables loaded into multiple components.

RESULTS

The novel index was validated against standardized survey items from a longitudinal cohort study in the Northeastern United States characterizing experiences of (1) Neighborhood Characteristics with a Pearson correlation of -0.34 (p < 0.001) and, (2) Neighborhood Behavior Impact with a Pearson correlation of -0.33 (p < 0.001). It also accurately predicted the Share Care Community Well Being Index (Spearman correlation = 0.46) and the neighborhood deprivation index (NDI) (Spearman correlation = -0.75).

SIGNIFICANCE

Our NSSI can serve as a predictor of neighborhood experience where data is either unavailable or too resource consuming to practically implement in planned studies.

IMPACT STATEMENT

To date, fear of crime and neighborhood sentiment data or indices have largely been based on the administration of time consuming and costly standardized surveys. The current study aims to develop a Neighborhood Sentiment and Safety Index (NSSI) at the census tract level, building on publicly available data repositories, including the US Census and ACS surveys, Data Axle, and ESRI repositories. The NSSI was validated against four separate measures and can serve as a predictor of neighborhood experience where data is either unavailable or too resource consuming to practically implement in planned studies.

Generalized trust and traffic violations: The moderating role of the individualism dimension

Traffic crashes take well over a million lives every year and are mainly caused by driver behavior and traffic violations. Drivers' attitudes and beliefs are at the root of whether traffic violations will be committed, making it important to explore what contributes to disobedience of traffic law. Generalized trust is one of the most influential factors in interpersonal behavior but has not yet been studied empirically in the context of driving behavior in general, and traffic violations in specific. Using data from about 30,000 participants from 20 European countries, this study examines the relationship between generalized trust and committing traffic violations while paying attention to differences between countries scoring high and low in individualism. A multilevel mixed-effects logistic regression analysis shows that in countries with high individualism scores, the probability to commit traffic violations increases significantly as generalized trust increases, while the association between generalized trust and traffic violations decreases as the country's individualism level decreases. The findings and their implications are discussed with suggestions for future research.

Use of mobile technologies for driving, road accidents, health and psychological variables in Colombian drivers

The aim of this investigation is to show the relationships between the use of Mobile Driving Applications and Devices (mdad) with self-reported road accidents, anger, physical health, and subjective wellbeing, in three types of Colombian drivers. The sample is non-randomized (n = 1149) and 93.2% are male drivers. Results showed that (a) for professional drivers, there is an inverse correlation between the use of mdad with lower driving frequency during weekdays and a higher educational level, (b) for occasional drivers, gps use was directly associated with fatal road accidents and low driving frequency during weekdays, (c) for private drivers, correlations were found between mdad broader usage, higher levels of both aggression and perceived driving difficulty as well as physical health problems mainly hypertension and diabetes. It is necessary to conduct in-depth research on mdad uses, health, and driving styles, by controlling social desirability.  

Ranking policing strategies as a function of criminal complaints: application of the PROMETHEE II method in the Brazilian context

Purpose

The purpose of this study is modelling of a problem of policing strategy order using a multicriteria method.

Design/methodology/approach

For the construction of the impact matrix strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria PROMETHEE II method was used, which with the help of the Visual PROMETHEE software, emulated the systematised data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision makers.

Findings

As a result, this research revealed that radio patrol, when used in a non-randomised manner, is the most effective policing strategy in reducing the 18 criminal demands studied in the perception of decision makers after data emulation with the PROMETHEE II method.

Research limitations/implications

As research implications, it can be inferred that the use of multicriteria methods in the modelling of problems in public security area can contribute to the rationalisation of use of the available means in the fight against crime in large cities. This research showed that it is possible to use customised policing strategies to absolute reality.

Practical implications

The practical impact of this research lies in optimising the resources available to law enforcement agencies in the fight against crime in general.

Social implications

It can be inferred that by choosing appropriate strategies to combat local crime, there is a direct implication in optimising the resources that the government makes available to police agencies. This optimisation allows pressure reduction under the public budget for more features. The model for choosing more effective strategies contributes to local crimes decrease, increasing the sense of the population security.

Originality/value

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices and in their associated use in ordering strategies through a multicriteria method. This study contributed to applied police intelligence.

Motorcycle-related head and neck injuries: increased risk among ethnic minorities

Background

Ethnic disparities have been associated with injury and mortality. The impact of ethnicity on head and neck injury (HNI), traumatic brain injury (TBI), in-hospital mortality and resource utilization following a motorcycle crash (MCC) is undetermined. This study explored the influence of ethnicity in these aspects and the effect of helmet use on HNI and TBI following a MCC.

Methods

The National Trauma Registry provided hospitalization data on motorcycle riders and passengers between 2008 and 2017. Ethnicity was classified as Jews or Arabs, the two major ethnic groups in Israel. Univariate followed by multivariable logistic models were applied to examine ethnic disparities. Mediation effect was tested by structural equation modeling.

Results

Among 6073 MCC casualties, Arabs had increased odds of HNI (OR = 1.37,95% CI = 1.12–1.65) and TBI (OR = 1.51,95%CI = 1.12–1.99), and a six-fold decreased odds of helmet use (OR = 0.16,95%CI = 0.12–0.22). The HNI and TBI associations with ethnicity were mediated by helmet use. Arabs had significantly higher odds for admission to intensive care unit (OR = 1.36,95%CI = 1.00–1.83), and lower odds for ambulance evacuation (OR = 0.73,95%CI = 0.61–0.89) and discharge to rehabilitation (OR = 0.55,95%CI = 0.39–0.7). In-hospital mortality was not associated with ethnicity.

Conclusions

Helmet non-use is an important etiologic factor associated with motorcycle-related HNI and TBI among Arabs. While in Israel, ethnic equality exists in in-hospital health care, disparities in ambulance and rehabilitation utilization was found. Intervention programs should target the Arab population and focus on helmet compliance.

Operational research applied in the field of public security

Purpose

Because that the crime in a wide way impacts the life of the people in the big metropolis, researchers have treated the question from several angles. The purpose of the paper, under the umbrella of operational research, is to develop a model of the ordering of police strategies, in the fight against crime in general, according to a certain criminal demand.

Design/methodology/approach

For the construction of the impact matrix of the strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria ELECTRE IV method was used, which with the help of the J-Electre software emulated the systematized data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision-makers.

Findings

As a result, the research revealed that policing strategies directed at solving specific crimes are the most effective in the perception of decision-makers after the emulation of data with the ELECTRE IV method.

Research limitations/implications

As research implications, it can be inferred that the use of multicriteria methods in the modeling of problems in the area of public security can contribute to rationalization of the use of the means available in the fight against crime in large cities. The research showed that it is possible to use customized policing strategies to a certain reality.

Practical implications

The method presented in this research is directly related to the major strategies: problem-oriented policing and hot spot policing. This method allows public safety managers to consider the possibility of combining different law enforcement strategies in each context. In this sense, the use of the multiple-criteria decision analysis (MCDA) (ELECTRE IV) method allows the evaluation of a large set of alternatives according to a set of established criteria, speeding up the process and reducing subjectivity, allowing the manager to analyze several scenarios with greater clarity and impartiality and choosing an alternative that best solves the proposed problem. The expected result is the rationalization of the available means applied in the search for the reduction of crime rates.

Social implications

The customization of policing strategies, according to criminal demands, implies the efficient way to reduce criminal charges. Reducing criminal rates enables the development of the local economy, tourism and the quality of life of people by exercising their freedom to the full.

Originality/value

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices, and in their associated use in ordering strategies through a multicriteria method.

A model of policing strategy choice

Purpose

The purpose of this paper is to develop a method for the discovery of knowledge in emergency response databases based on police incident reports, generating information that identifies local criminal demands that allow the selection of the appropriate policing strategies portfolio to solve the problem.

Design/methodology/approach

The developed model uses a methodology for the discovery of knowledge involving text mining techniques using Latent Dirichlet Allocation (LDA) integrated with the ELECTRE I multicriteria method.

Findings

The developed method allowed the identification of the most common criminal demands that occurred from January 1 to December 31, 2016, in the policing areas studied. One of the crimes does not occur homogeneously in a particular locality. In this study, it was initially observed that 40 per cent of the crimes identified in the Integrated Public Safety Area 5, or AISP-5, (historical city center of RJ) had no correlation with AISP-19 (Copacabana - RJ), and 33 per cent of crimes crimes in AISP-19 were not identified in AISP-5. This finding guided the second part of the method that sought to identify which portfolio of policing strategies would be most appropriate for the identified demands. In this sense, using the ELECTRE I method, eight different scenarios were constructed where it can be identified that for each specific criminal demand set there is a set of policing strategies to be applied.

Research limitations/implications

The collected data represent the social dynamics of neighbourhoods in the central and southern zones of the city of Rio de Janeiro during the specific period from January 2013 to December 2016. This limitation implies that the results cannot be generalised to areas with different characteristics.

Practical implications

The developed methodology contributes in a complementary way to the identification of criminal practices and their characteristics based on reports of police occurrences stored in emergency response databases. The knowledge generated through the identification of criminal demands allows law enforcement decision makers to evaluate and choose among the available policing strategies, which best suit the reality they study, and produce the reduction of criminal indices.

Social implications

It is possible to infer that by choosing appropriate strategies to combat local crime, the proposed model will increase the population’s sense of safety through an effective reduction in crime.

Originality/value

The originality of the study lies in the integration of text mining techniques, LDA and the ELECTRE I method for detecting crime in a given location based on crime reports stored in emergency response databases, enabling identification and choice, from customized policing strategies to particular criminal demands.