Ranking Spatial and Temporal Hotspots for Road Safety Interventions Using a Nonlinear Aggregation Approach

In recent years, the concept of a composite performance index, brought from economic and business statistics, has gained popularity in the field of road safety. The construction of the Composite Safety Performance Index (CSPI) involves the following key steps: the selection of the most appropriate indicators to be aggregated and the method used to aggregate them.

Over the last decade, various aggregation methods for estimating the CSPI have been suggested in the literature. However, recent studies indicates that most of these methods suffer from many deficiencies at both the theoretical and operational level; these include the correlation and compensability between indicators, as well as their high “degree of freedom” which enables one to readily manipulate them to produce desired outcomes.

The purpose of this study is to introduce an alternative aggregation method for the estimation of the CSPI, which is free from the aforementioned deficiencies. In contrast with the current aggregation methods, which generally use linear combinations of road safety indicators to estimate a CSPI, the approach advocated in this study is based on non-linear combinations of indicators and can be summarized into the following two main steps: the pairwise comparison of road safety indicators and the development of marginal and composite road safety performance functions. The introduced method has been successfully applied to identify and rank temporal and spatial hotspots for Northern Ireland, using road traffic collision data recorded in the UK STATs19 database. The obtained results highlight the promising features of the proposed approach including its stability and consistency, which enables significantly reduced deficiencies associated with the current aggregation methods. Progressively, the introduced method could evolve into an intelligent support system for road safety assessment.

Work-related training and the probability of transitioning from non-permanent to permanent employment

It is widely believed that work-related training increases a worker’s probability of moving up the job-quality ladder. This is usually couched in terms of effects on wages, but it has also been argued that training increases the probability of moving from non-permanent forms of employment to more permanent employment. This hypothesis is tested using nationally representative panel data for Australia, a country where the incidence of non-permanent employment, and especially casual employment, is high by international standards. While a positive association between participation in work-related training and the subsequent probability of moving from either casual or fixed-term contract employment to permanent employment is observed among men, this is shown to be driven not by a causal impact of training on transitions but by differences between those who do and do not receive training; i.e., selection bias.

A Framework for Spatial Road Safety Assessment: Case Study of Northern Ireland

Road traffic injuries are a major health issue worldwide. There are many factors that can
affect the levels of road traffic collisions which in turn increase the levels of people killed or
seriously injured. When road traffic collisions occur, observed facts are recorded in relation
to the incident. These facts are recorded as variable observations, and for this study,
variables and indicators are defined almost equivalently. There can be hundreds of different
indicators for the various collisions, as different countries face different road situations. This
makes it difficult to perform a road safety assessment, which can be applied globally. The
goal of this study is to select the most appropriate indicators and create a composite
indicator as a function of these indicators, which can be used as summary values, allowing
ease of comparisons between the countries/regions that have undergone a road safety
assessment. The composite indicator will then be used to assess the current situation in
Northern Ireland and provide scores for ranking policing in terms of overall road safety on
their road networks.

Pattern Recognition Approach for Road Collision Hotspots Analysis: Case Study of Northern Ireland

In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.

Ownership type and team climate in elderly care facilities: the moderating effect of stress factors

Aims. This paper is a report of a study examining the association between ownership type and perceived team climate among older people care staff. In addition, we examined whether work stress factors (time pressure, resident-related stress, role conflicts and role ambiguity) mediated or moderated the above mentioned association. Background. There has been a trend towards contracting out in older people care facilities in Finland and the number of private for-profit firms has increased. Studies suggest that there may be differences in employee well-being and quality of care according to the ownership type of older people care. Methods. Cross-sectional survey data was collected during the autumn of 2007 from 1084 Finnish female older people care staff aged 1869 years were used. Team Climate Inventory was used to measure team climate. Ownership type was divided into four categories: for-profit sheltered homes, not-for-profit sheltered homes, public sheltered homes and not-for-profit nursing homes. Analyses of covariance were used to examine the associations. Results. Team climate dimensions participative safety, vision and support for innovation were higher in not-for-profit organizations (both sheltered homes and nursing homes) compared to for-profit sheltered homes and public sheltered homes. Stress factors did not account for these associations but acted as moderators in a way that in terms of task orientation and participative safety employees working in for-profit organizations seemed to be slightly more sensitive to work-related stress than others. Conclusion. Our results suggest that for-profit organizations and public organizations may have difficulties in maintaining their team climate. In consequence, these organizations should focus more effort on improving their team climate.

Psychosocial factors in GP work:the effects of taking a GP position or leaving GP work

BACKGROUND: We examined the effects of leaving public sector general practitioner (GP) work and of taking a GP position on changes in work-related psychosocial factors, such as time pressure, patient-related stress, distress and work interference with family. In addition, we examined whether changes in time pressure and patient-related stress mediated the association of employment change with changes of distress and work interference with family. METHODS: Participants were 1705 Finnish physicians (60% women) who responded to surveys in 2006 and 2010. Analyses of covariance were conducted to examine the effect of employment change to outcome changes adjusted for gender, age and response format. Mediational effects were tested following the procedures outlined by Baron and Kenny. RESULTS: Employment change was significantly associated with all the outcomes. Leaving public sector GP work was associated with substantially decreased time pressure, patient-related stress, distress and work interference with family. In contrast, taking a position as a public sector GP was associated with an increase in these factors. Mediation tests suggested that the associations of employment change with distress change and work interference with family change were partially explained by the changes in time pressure and patient-related stress. CONCLUSIONS: Our results showed that leaving public sector GP work is associated with favourable outcomes, whereas taking a GP position in the public sector is associated with adverse effects. Primary health-care organizations should pay more attention to the working conditions of their GPs, in particular, to time pressure and patient-related stress.

Work stress and risk of cancer:meta-analysis of 5700 incident cancer events in 116 000 European men and women

To investigate whether work related stress, measured and defined as job strain, is associated with the overall risk of cancer and the risk of colorectal, lung, breast, or prostate cancers.