Self-awareness of cognitive efficiency: Differences between healthy elderly and patients with mild cognitive impairment (MCI)

INTRODUCTION

Self-estimation of performance implies the ability to understand one's own performance with relatively objective terms. Up to date, few studies have addressed this topic in mild cognitive impairment (MCI) patients. The aim of the present study was to compare objective measures of performance with subjective perception of specific performance on cognitive tests and investigate differences in assessment between MCI patients and healthy elderly.

METHOD

Thirty-five participants diagnosed with MCI (women = 16, men = 19, mean age = 65.09 years ±SD = 7.81, mean education = 12.83 years ±SD = 4.32) and 35 control subjects similar in terms of age and education (women = 20, men = 15, mean age = 62.46 years ± SD = 9.35, mean education = 14.26 ± SD = 2.84) were examined with an extended battery of neuropsychological tests. After every test they were asked to self-evaluate their performance by comparing it to what they considered as average for people of their age and educational level. This self-evaluation was reported on a scale ranging from -100 to +100.

RESULTS

Significant differences were found in the self-assessment patterns of the two groups in memory measures of verbal and visual delayed recall, visuospatial perception, and tests of attention. MCI patients overestimated their performance on every cognitive domain while control participants underestimated their performance on measures of verbal memory.

CONCLUSIONS

The present results indicate that accuracy of self-report is not uniform across groups and functional areas. The discrepancies in the MCI patients indicate unawareness of their memory deficits, which is contradictory to subjective memory complaints as being an important component for clinical diagnosis.

Relating traffic fatalities to GDP in Europe on the long term

Modeling road safety development can provide important insight into policies for the reduction of traffic fatalities. In order to achieve this goal, both the quantifiable impact of specific parameters, as well as the underlying trends that cannot always be measured or observed, need to be considered. One of the key relationships in road safety links fatalities with risk and exposure, where exposure reflects the amount of travel, which in turn translates to how much travelers are exposed to risk. In general two economic variables: GDP and unemployment rate are selected to analyse the statistical relationships with some indicators of road accident fatality risk. The objective of this research is to provide an overview of relevant literature on the topic and outline some recent developments in macro-panel data analysis that have resulted in ongoing research that has the potential to improve our ability to forecast traffic fatality trends, especially under turbulent financial situations. For this analysis, time series of the number of fatalities and GDP in 30 European countries for a period of 38 years (1975-2012) are used. This process relies on estimating long-term models (as captured by long term time-series models, which model each country separately). Based on these developments, utilizing state-of-the-art modelling and analysis techniques such as the Common Correlated Effects Mean Group estimator (Pesaran), the long-term elasticity mean value equals 0.63, and is significantly different from zero for 10 countries only. When we take away the countries, where the number of fatalities is stationary, the average elasticity takes a higher value of nearly 1. This shows the strong sensitivity of the estimate of the average elasticity over a panel of European countries and underlines the necessity to be aware of the underlying nature of the time series, to get a suitable regression model.

Exploring the association between working memory and driving performance in Parkinson's disease

OBJECTIVE

The aim of this study was to explore whether varying levels of operational and tactical driving task demand differentially affect drivers with Parkinson's disease (PD) and control drivers in their sign recall.

METHODS

Study participants aged between 50 and 70 years included a group of drivers with PD (n = 10) and a group of age- and sex-matched control drivers (n = 10). Their performance in a sign recall task was measured using a driving simulator.

RESULTS

Drivers in the control group performed better than drivers with PD in a sign recall task, but this trend was not statistically significant (P =.43). In addition, regardless of group membership, subjects' performance differed according to varying levels of task demand. Performance in the sign recall task was more likely to drop with increasing task demand (P =.03). This difference was significant when the variation in task demand was associated with a cognitive task; that is, when drivers were required to apply the instructions from working memory.

CONCLUSIONS

Although the conclusions drawn from this study are tentative, the evidence presented here is encouraging with regard to the use of a driving simulator to examine isolated cognitive functions underlying driving performance in PD. With an understanding of its limitations, such driving simulation in combination with functional assessment batteries measuring physical, visual, and cognitive abilities could comprise one component of a multitiered system to evaluate medical fitness to drive.

Good practices on cost - effective road infrastructure safety investments

The paper presents the findings of a research project aiming to quantify and subsequently classify several infrastructure-related road safety measures, based on the international experience attained through extensive and selected literature review and additionally on a full consultation process including questionnaire surveys addressed to experts and relevant workshops. Initially, a review of selected research reports was carried out and an exhaustive list of road safety infrastructure investments covering all types of infrastructure was compiled. Individual investments were classified according to the infrastructure investment area and the type of investment and were thereafter analysed on the basis of key safety components. These investments were subsequently ranked in relation to their safety effects and implementation costs and on the basis of this ranking, a set of five most promising investments was selected for an in-depth analysis. The results suggest that the overall cost effectiveness of a road safety infrastructure investment is not always in direct correlation with the safety effect and is recommended that cost-benefit ratios and safety effects are always examined in conjunction with each other in order to identify the optimum solution for a specific road safety problem in specific conditions and with specific objectives.

Attitudes of Greek Drivers with Focus on Mobile Phone Use While Driving

OBJECTIVE

This article investigates the attitudes and behavior of Greek drivers with specific focus on mobile phone use while driving.

METHODS

The research is based on the data of the pan-European SARTRE 4 survey, which was conducted on a representative sample of Greek drivers in 2011. Analysis of the drivers' behavior was carried out by the statistical methods of factor and cluster analysis.

RESULTS

According to the results of factor analysis, Greek drivers' responses in the selected questions were summarized into 4 factors, describing road behavior and accident involvement probability as well as their views on issues concerning other drivers' road behaviors, fatigued driving, enforcement of road safety, and mobile phone use while driving. The results of cluster analysis indicated 5 different groups of Greek drivers--the moderate, the optimistic, the conservative, the risky, and the reasonably cautious--and the characteristics of each group where identified.

CONCLUSIONS

These results may be useful for the appropriate design of targeted road safety campaigns and other countermeasures.

A review of the effect of traffic and weather characteristics on road safety

Taking into consideration the increasing availability of real-time traffic data and stimulated by the importance of proactive safety management, this paper attempts to provide a review of the effect of traffic and weather characteristics on road safety, identify the gaps and discuss the needs for further research. Despite the existence of generally mixed evidence on the effect of traffic parameters, a few patterns can be observed. For instance, traffic flow seems to have a non-linear relationship with accident rates, even though some studies suggest linear relationship with accidents. On the other hand, increased speed limits have found to have a straightforward positive relationship with accident occurrence. Regarding weather effects, the effect of precipitation is quite consistent and leads generally to increased accident frequency but does not seem to have a consistent effect on severity. The impact of other weather parameters on safety, such as visibility, wind speed and temperature is not found straightforward so far. The increasing use of real-time data not only makes easier to identify the safety impact of traffic and weather characteristics, but most importantly makes possible the identification of their combined effect. The more systematic use of these real-time data may address several of the research gaps identified in this research.

Latent risk and trend models for the evolution of annual fatality numbers in 30 European countries

In this paper a unified methodology is presented for the modelling of the evolution of road safety in 30 European countries. For each country, annual data of the best available exposure indicator and of the number of fatalities were simultaneously analysed with the bivariate latent risk time series model. This model is based on the assumption that the amount of exposure and the number of fatalities are intrinsically related. It captures the dynamic evolution in the fatalities as the product of the dynamic evolution in two latent trends: the trend in the fatality risk and the trend in the exposure to that risk. Before applying the latent risk model to the different countries it was first investigated and tested whether the exposure indicator at hand and the fatalities in each country were in fact related at all. If they were, the latent risk model was applied to that country; if not, a univariate local linear trend model was applied to the fatalities series only, unless the latent risk time series model was found to yield better forecasts than the univariate local linear trend model. In either case, the temporal structure of the unobserved components of the optimal model was established, and structural breaks in the trends related to external events were identified and captured by adding intervention variables to the appropriate components of the model. As a final step, for each country the optimally modelled developments were projected into the future, thus yielding forecasts for the number of fatalities up to and including 2020.

Motorcycle riding under the influence of alcohol: results from the SARTRE-4 survey

Riding a motorcycle under the influence of alcohol is a dangerous activity, especially considering the high vulnerability of motorcyclists. The present research investigates the factors that affect the declared frequency of drink-riding among motorcyclists in Europe and explores regional differences. Data were collected from the SARTRE-4 (Social Attitudes to Road Traffic Risk in Europe) survey, which was conducted in 19 countries. A total sample of 4483 motorcyclists was interviewed by using a face-to-face questionnaire. The data were analyzed by means of multilevel ordered logit models. The results revealed significant regional differences (between Northern, Eastern and Southern European countries) in drink-riding frequencies in Europe. In general, declared drinking and riding were positively associated with gender (males), increased exposure, underestimation of risk, friends' behaviour, past accidents and alcohol ticket experience. On the other hand, it was negatively associated with underestimation of the amount of alcohol allowed before driving, and support for more severe penalties.

A review of powered-two-wheeler behaviour and safety

Powered-two-wheelers (PTWs) constitute a very vulnerable type of road users. The notable increase in their share in traffic and the high risk of severe accident occurrence raise the need for further research. However, current research on PTW safety is not as extensive as for other road users (passenger cars, etc.). Consequently, the objective of this research is to provide a critical review of research on Power-Two-Wheeler behaviour and safety with regard to data collection, methods of analysis and contributory factors, and discuss the needs for further research. Both macroscopic analyses (accident frequency, accident rates and severity) and microscopic analyses (PTW rider behaviour, interaction with other motorised traffic) are examined and discussed in this paper. The research gaps and the needs for future research are identified, discussed and put in a broad framework. When the interactions between behaviour, accident frequency/rates and severity are co-considered and co-investigated with the various contributory factors (riders, other users, road and traffic environment, vehicles), the accident and injury causes as well as the related solutions are better identified.

Impact of texting on young drivers' behavior and safety on urban and rural roads through a simulation experiment

PROBLEM

This research aims to investigate the impact of texting on the behavior and safety of young drivers on urban and rural roads.

METHOD

A driving simulator experiment was carried out in which 34 young participants drove in different driving scenarios; specifically, driving in good weather, in raining conditions, in daylight and in night were examined. Lognormal regression methods were used to investigate the influence of texting as well as various other parameters on the mean speed and mean reaction time. Binary logistic methods were used to investigate the influence of texting use as well as various other parameters in the probability of an accident.

RESULTS

It appears that texting leads to statistically significant decrease of the mean speed and increase of the mean reaction time in urban and rural road environment. Simultaneously, it leads to an increased accident probability due to driver distraction and delayed reaction at the moment of the incident. It appeared that drivers using mobile phones with a touch screen present different driving behavior with respect to their speed, however, they had an even higher probability of being involved in an accident.

DISCUSSION

The analysis of the distracted driving performance of drivers who are texting while driving may allow for the identification of measures for the improvement of driving performance (e.g., restrictive measures, training and licensing, information campaigns).

PRACTICAL APPLICATIONS

The identification of some of the parameters that have an impact on the behavior and safety of young drivers concerning texting and the consequent results can be exploited by policy decision makers in future efforts for the improvement of road safety.

Road safety forecasts in five European countries using structural time series models

OBJECTIVE

Modeling road safety development is a complex task and needs to consider both the quantifiable impact of specific parameters as well as the underlying trends that cannot always be measured or observed. The objective of this research is to apply structural time series models for obtaining reliable medium- to long-term forecasts of road traffic fatality risk using data from 5 countries with different characteristics from all over Europe (Cyprus, Greece, Hungary, Norway, and Switzerland).

METHODS

Two structural time series models are considered: (1) the local linear trend model and the (2) latent risk time series model. Furthermore, a structured decision tree for the selection of the applicable model for each situation (developed within the Road Safety Data, Collection, Transfer and Analysis [DaCoTA] research project, cofunded by the European Commission) is outlined. First, the fatality and exposure data that are used for the development of the models are presented and explored. Then, the modeling process is presented, including the model selection process, introduction of intervention variables, and development of mobility scenarios.

RESULTS

The forecasts using the developed models appear to be realistic and within acceptable confidence intervals. The proposed methodology is proved to be very efficient for handling different cases of data availability and quality, providing an appropriate alternative from the family of structural time series models in each country.

CONCLUSIONS

A concluding section providing perspectives and directions for future research is presented.

Relationship between motorcyclists' attitudes, behavior, and other attributes with declared accident involvement in Europe

OBJECTIVE

The objective of this study is to investigate patterns of road safety attitudes and behaviors of motorcyclists in Europe on the basis of the results of the pan-European questionnaire-based survey SARTRE-4, carried out in late 2010 in 18 European countries and Israel. In addition, we attempt to explore the link between attitudes, behaviors, and other motorcyclist attributes with motorcyclist involvement in accidents in the past 3 years, in which someone, including the rider, was injured and received medical attention as stated in the motorcyclists' responses.

METHODS

The various components of motorcyclist attitudes and behaviors such as reasons for driving a motorcycle, driving while impaired, perceived risk factors, and risk-taking behavior were determined by means of a principal component analysis (PCA) on 38 variables contained in the survey. A binary logistic regression model was then applied in order to link the attitudes and the stated behavior with the declared involvement in past accidents.

RESULTS

The results revealed 8 components. Component 1 (driving while impaired and speeding accident factors), component 2 (motorcycle benefits), component 3 (perceived risk of maneuvers), component 4 (sensation seeking), component 5 (road, vehicle, and environmental risk factors), component 7 (no modal options), and component 8 (attitudes toward drinking and friends' drinking) are associated with stated preferences and attitudes, whereas component 6 (dangerous and angry behaviors) is associated with stated behavior. Moreover, it was found that motorcyclists who tend to have dangerous attitudes and behaviors as well as younger motorcyclists are more likely to have been involved in an accident. It was also showed that driving exposure is positively associated with increased probability of a past accident.

CONCLUSIONS

The findings of the study provide some insight into the association between attitudes, behaviors, and declared past accident involvement. Furthermore, the analysis of such large databases with the inclusion of many different countries constitutes a step for further research in the field of motorcyclists' behaviors and safety. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

Reaction times of young alcohol-impaired drivers

Young individuals who drive under the influence of alcohol have a higher relative risk of crash involvement; as such, the literature has extensively investigated the factors affecting such involvement through both post-accident surveys and simulator experiments. The effects of differentiated breath alcohol concentrations (BrAC) on young driver behavior, however, have been largely unaddressed, mainly as a result of the difficulty in collecting the necessary data. We explore young driver behavior under the influence of alcohol using a driving simulator experiment where 49 participants were subjected to a common pre-defined dose of alcohol consumption. Comparing reaction times before and after consumption allows for interesting insights and suggestions regarding policy interventions. As expected, the results indicate that increased reaction times before consuming alcohol strongly affect post-consumption reaction times, while increased BrAC levels prolong reaction times; a 10% increase in BrAC levels results in a 2% increase in reaction time. Interestingly, individuals with faster alcohol absorption times perform better regardless of absolute BrAC level, while recent meals lead to higher reaction times and regular exercising to lower.

Exposure data and risk indicators for safety performance assessment in Europe

The objective of this paper is the analysis of the state-of-the-art in risk indicators and exposure data for safety performance assessment in Europe, in terms of data availability, collection methodologies and use. More specifically, the concepts of exposure and risk are explored, as well as the theoretical properties of various exposure measures used in road safety research (e.g. vehicle- and person-kilometres of travel, vehicle fleet, road length, driver population, time spent in traffic, etc.). Moreover, the existing methods for collecting disaggregate exposure data for risk estimates at national level are presented and assessed, including survey methods (e.g. travel surveys, traffic counts) and databases (e.g. national registers). A detailed analysis of the availability and quality of existing risk exposure data is also carried out. More specifically, the results of a questionnaire survey in the European countries are presented, with detailed information on exposure measures available, their possible disaggregations (i.e. variables and values), their conformity to standard definitions and the characteristics of their national collection methods. Finally, the potential of international risk comparisons is investigated, mainly through the International Data Files with exposure data (e.g. Eurostat, IRTAD, ECMT, UNECE, IRF, etc.). The results of this review confirm that comparing risk rates at international level may be a complex task, as the availability and quality of exposure estimates in European countries varies significantly. The lack of a common framework for the collection and exploitation of exposure data limits significantly the comparability of the national data. On the other hand, the International Data Files containing exposure data provide useful statistics and estimates in a systematic way and are currently the only sources allowing international comparisons of road safety performance under certain conditions.

Multilevel analysis in road safety research

Hierarchical structures in road safety data are receiving increasing attention in the literature and multilevel (ML) models are proposed for appropriately handling the resulting dependences among the observations. However, so far no empirical synthesis exists of the actual added value of ML modelling techniques as compared to other modelling approaches. This paper summarizes the statistical and conceptual background and motivations for multilevel analyses in road safety research. It then provides a review of several ML analyses applied to aggregate and disaggregate (accident) data. In each case, the relevance of ML modelling techniques is assessed by examining whether ML model formulations (i) allow improving the fit of the model to the data, (ii) allow identifying and explaining random variation at specific levels of the hierarchy considered, and (iii) yield different (more correct) conclusions than single-level model formulations with respect to the significance of the parameter estimates. The evidence reviewed offers different conclusions depending on whether the analysis concerns aggregate data or disaggregate data. In the first case, the application of ML analysis techniques appears straightforward and relevant. The studies based on disaggregate accident data, on the other hand, offer mixed findings: computational problems can be encountered, and ML applications are not systematically necessary. The general recommendation concerning disaggregate accident data is to proceed to a preliminary investigation of the necessity of ML analyses and of the additional information to be expected from their application.

Road safety performance indicators for the interurban road network

Various road safety performance indicators (SPIs) have been proposed for different road safety research areas, mainly as regards driver behaviour (e.g. seat belt use, alcohol, drugs, etc.) and vehicles (e.g. passive safety); however, no SPIs for the road network and design have been developed. The objective of this research is the development of an SPI for the road network, to be used as a benchmark for cross-region comparisons. The developed SPI essentially makes a comparison of the existing road network to the theoretically required one, defined as one which meets some minimum requirements with respect to road safety. This paper presents a theoretical concept for the determination of this SPI as well as a translation of this theory into a practical method. Also, the method is applied in a number of pilot countries namely the Netherlands, Portugal, Greece and Israel. The results show that the SPI could be efficiently calculated in all countries, despite some differences in the data sources. In general, the calculated overall SPI scores were realistic and ranged from 81 to 94%, with the exception of Greece where the SPI was relatively lower (67%). However, the SPI should be considered as a first attempt to determine the safety level of the road network. The proposed method has some limitations and could be further improved. The paper presents directions for further research to further develop the SPI.

State-space based analysis and forecasting of macroscopic road safety trends in Greece

In this paper, macroscopic road safety trends in Greece are analyzed using state-space models and data for 52 years (1960-2011). Seemingly unrelated time series equations (SUTSE) models are developed first, followed by richer latent risk time-series (LRT) models. As reliable estimates of vehicle-kilometers are not available for Greece, the number of vehicles in circulation is used as a proxy to the exposure. Alternative considered models are presented and discussed, including diagnostics for the assessment of their model quality and recommendations for further enrichment of this model. Important interventions were incorporated in the models developed (1986 financial crisis, 1991 old-car exchange scheme, 1996 new road fatality definition) and found statistically significant. Furthermore, the forecasting results using data up to 2008 were compared with final actual data (2009-2011) indicating that the models perform properly, even in unusual situations, like the current strong financial crisis in Greece. Forecasting results up to 2020 are also presented and compared with the forecasts of a model that explicitly considers the currently on-going recession. Modeling the recession, and assuming that it will end by 2013, results in more reasonable estimates of risk and vehicle-kilometers for the 2020 horizon. This research demonstrates the benefits of using advanced state-space modeling techniques for modeling macroscopic road safety trends, such as allowing the explicit modeling of interventions. The challenges associated with the application of such state-of-the-art models for macroscopic phenomena, such as traffic fatalities in a region or country, are also highlighted. Furthermore, it is demonstrated that it is possible to apply such complex models using the relatively short time-series that are available in macroscopic road safety analysis.

Explaining the road accident risk: weather effects

This research aims to highlight the link between weather conditions and road accident risk at an aggregate level and on a monthly basis, in order to improve road safety monitoring at a national level. It is based on some case studies carried out in Work Package 7 on "Data analysis and synthesis" of the EU-FP6 project "SafetyNet-Building the European Road Safety Observatory", which illustrate the use of weather variables for analysing changes in the number of road injury accidents. Time series analysis models with explanatory variables that measure the weather quantitatively were used and applied to aggregate datasets of injury accidents for France, the Netherlands and the Athens region, over periods of more than 20 years. The main results reveal significant correlations on a monthly basis between weather variables and the aggregate number of injury accidents, but the magnitude and even the sign of these correlations vary according to the type of road (motorways, rural roads or urban roads). Moreover, in the case of the interurban network in France, it appears that the rainfall effect is mainly direct on motorways--exposure being unchanged, and partly indirect on main roads--as a result of changes in exposure. Additional results obtained on a daily basis for the Athens region indicate that capturing the within-the-month variability of the weather variables and including it in a monthly model highlights the effects of extreme weather. Such findings are consistent with previous results obtained for France using a similar approach, with the exception of the negative correlation between precipitation and the number of injury accidents found for the Athens region, which is further investigated. The outlook for the approach and its added value are discussed in the conclusion.