Effects of mobile phone-related distraction on driving performance at roundabouts: Eye movements tracking perspective.

Modern road infrastructures are complex networks featuring various elements such as roads, bridges, intersections, and roundabouts, with advanced control systems. Roundabouts have gained prominence as a safer alternative to traditional intersections promoting smoother traffic flow and fewer collisions by guiding traffic in one direction, encouraging reduced speed, and minimizing conflict points.This study investigated driver behavior within roundabouts, focusing on gaze behavior, particularly the left-side mirror and window, under mobile phone distraction conditions. In addition, the effects of roundabout specifications (i.e., number of lanes and size of the central island) and the drivers' characteristics (i.e., driving experience) were examined.In total, 43 participants, aged 19-56 years including 30 males and 13 females, held a valid driving license, drove through a virtual simulated urban road containing four roundabouts, implemented in a static driving simulator, under baseline condition (no distraction) as well as mobile-induced distraction. Driving simulator data were collected and drivers' gaze direction and fixation on nine areas of interest were captured with an eye tracker. Results: showed that experienced drivers exhibit a more fixation on the left-side mirror and window and were less distracted. Moreover, the road environment, i.e., the number of cars and the roundabout size, significantly influenced the drivers' attention. As regards the driving performance, the number of infractions increased when the drivers diverted focus from the left side of the car. The outcomes of the present study might help to improve traffic safety at roundabouts.

Influence of noise level and seniority in the workplace on the SAL, ELI and percentage of hearing loss indices in the diagnosis and prevention of hearing loss in the working population.

INTRODUCTION: This research relates the most important work-related factors affecting the development of hearing loss to the main methods used as medical assessment criteria in the diagnosis of occupational deafness. These criteria are the Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss, and are applied to data obtained from audiograms performed on workers in occupational medical examinations. METHOD: Depending on the assessment method selected, these often return different results in grading an individual's hearing status and predicting how it will evolve. To address this problem, medical examinations (including audiograms) were carried out on a heterogeneous sample of 1,418 workers in Spain, from which demographic or personal data (gender, age, etc.), occupational data (noise level to which each individual is exposed, etc.) and other non-work-related factors (exposure to noise outside work, family history, etc.) were also gathered. Using Bayesian Networks, the conditional probability of an individual developing hearing loss was obtained taking into account all these factors and, specifically, noise level and length of service in the workplace. Sensitivity analyses were also carried out using the three scales (SAL, ELI and Percentage Hearing Loss Index), proving their suitability as tools the diagnosis and prediction of deafness. These networks were validated under the Receiver Operating Characteristic curve (ROC) criterion and in particular by the Area Under the Curve (AUC). RESULTS: The results show that all three methods are deficient in so far as detecting preventive hearing problems related to noise in most workplaces. CONCLUSIONS: The most restrictive methods for detecting possible cases of deafness are the SAL index and the Percentage Loss Index. The ELI index is the least restrictive of the three methods, but it is not able to discriminate the causes of hearing problems in an individual caused by exposure to noise, either by its intensity level or by the time of exposure to noise. Practical Applications: The use of the three methods in the field of occupational risk prevention is extremely limited and it seems reasonable to think that there is a need for the construction of new scales to correct or improve the existing ones.

Effects of Mobile Phone Use on Driving Performance: An Experimental Study of Workload and Traffic Violations.

The use of communication technologies, e.g., mobile phones, has increased dramatically in recent years, and their use among drivers has become a great risk to traffic safety. The present study assessed the workload and road ordinary violations, utilizing driving data collected from 39 young participants who underwent a dual-task while driving a simulator, i.e., respond to a call, text on WhatsApp, and check Instagram. Findings confirmed that there are significant differences in the driving performance of young drivers in terms of vehicle control (i.e., lateral distance and hard shoulder line violations) between distracted and non-distracted drivers. Furthermore, the overall workload score of young drivers increases with the use of their mobile phones while driving. The obtained results contribute to a better understanding of the driving performance of distracted young drivers and thus they could be useful for further improvements to traffic safety strategies.

Assessment of the Influence of Technology-Based Distracted Driving on Drivers' Infractions and Their Subsequent Impact on Traffic Accidents Severity.

Multitasking while driving negatively affects driving performance and threatens people's lives every day. Moreover, technology-based distractions are among the top driving distractions that are proven to divert the driver's attention away from the road and compromise their safety. This study employs recent data on road traffic accidents that occurred in Spain and uses a machine-learning algorithm to analyze, in the first place, the influence of technology-based distracted driving on drivers' infractions considering the gender and age of the drivers and the zone and the type of vehicle. It assesses, in the second place, the impact of drivers' infractions on the severity of traffic accidents. Findings show that (i) technology-based distractions are likely to increase the probability of committing aberrant infractions and speed infractions; (ii) technology-based distracted young drivers are more likely to speed and commit aberrant infractions; (iii) distracted motorcycles and squad riders are found more likely to speed; (iv) the probability of committing infractions by distracted drivers increases on streets and highways; and, finally, (v) drivers' infractions lead to serious injuries.

On the contribution to the alignment during an organizational change: Measurement of job satisfaction with working conditions.

INTRODUCTION: Modern approaches to Occupational Health and Safety have acknowledged the important contribution that continuous improvements to working conditions can make to the motivation of employees, their subsequent performance, and therefore to the competitiveness of the company. Despite this fact, organizational change initiatives represent a path less traveled by employees. Specialized literature has drawn on the fact that employees' satisfaction presents both the foundation and catalyst for effective implementation of improvements to working conditions. METHOD: This paper conceptualizes the alignment of employees through measurement of job satisfaction and uses the Bayesian Network to assess the influence of human factors, particularly the cognitive, emotional, and behavioral aspects. Toward this aim, the Bayesian Network is evaluated through a cross-validation process, and a sensitivity analysis is then conducted for each influential dimension: emotional, cognitive, and behavioral. RESULTS: The results reveal that these three dimensions are interrelated and have a direct influence on job satisfaction and employees' alignment during the organization change. Further, they suggest that the best strategy for enhanced alignment and smooth conduct of organizational changes is simultaneous enhancement of the three dimensions. Practical applications: This study shows the influence of emotional, cognitive, and behavioral dimensions on job satisfaction and employees' alignment during the organizational change. Furthermore, it elaborates the way to develop efficient and effective strategies for a successful change implementation and sustained alignment.

Assessment and Modeling of the Influence of Age, Gender, and Family History of Hearing Problems on the Probability of Suffering Hearing Loss in the Working Population.

Hearing loss affects hundreds of millions of people all over the world, leading to several types of disabilities, ranging from purely physical to psychological and/or social aspects. A proper analysis to ascertain the main risk factors is essential in order to diagnose early and treat adequately. An exploratory analysis based on a heterogeneous sample of 1418 workers is presented in order to identify the main trigger factors for hearing loss. On the one hand, we recorded several medical and environmental parameters, and on the other, we created a model based on Bayesian networks in order to be able to infer the probability of hearing loss considering different scenarios. This paper focuses on three parameters: gender, age, and a family history of hearing problems. The results obtained allow us to infer or predict the best or worst auditory level for an individual under several different scenarios. The least relevant factor is the existence of a family history of deafness, followed by the gender factor, which slopes considerably toward better hearing for females, and most prominent of all, the age factor, given the large differences identified between the various age groups when the gender and family history of deafness variables remain constant.

An Investigation into Unsafe Behaviors and Traffic Accidents Involving Unlicensed Drivers: A Perspective for Alignment Measurement.

Road traffic plays a vital role in countries' economic growth and future development. However, traffic accidents are considered a major public health issue affecting humankind. Despite efforts by governments to improve traffic safety, the misalignment between the policy efforts and on-ground infringements, distractions and breaches reflect the regulatory failure. This paper uses the Bayesian network method to investigate unsafe behaviors and traffic accidents involving unlicensed drivers as a perspective for the regulatory alignment assessment. The findings suggest that: (1) unlicensed drivers are more likely to have unsafe driving behaviors; (2) the probability of being involved in a severe traffic accident increases when the drivers are unlicensed and decreases in the case of licensed drivers; (3) young drivers are noticeably more likely to engage in unsafe behaviors, usually leading to serious injuries and deaths, when their driving licenses are invalid; (4) women are more likely to engage in right-of-way violations and to have collisions with no serious injuries, contrary to unlicensed men drivers, who are involved in other types of traffic accidents resulting in serious injuries.

Cyclist Injury Severity in Spain: A Bayesian Analysis of Police Road Injury Data Focusing on Involved Vehicles and Route Environment.

This study analyses factors associated with cyclist injury severity, focusing on vehicle type, route environment, and interactions between them. Data analysed was collected by Spanish police during 2016 and includes records relating to 12,318 drivers and cyclist involving in collisions with at least one injured cyclist, of whom 7230 were injured cyclists. Bayesian methods were used to model relationships between cyclist injury severity and circumstances related to the crash, with the outcome variable being whether a cyclist was killed or seriously injured (KSI) rather than slightly injured. Factors in the model included those relating to the injured cyclist, the route environment, and involved motorists. Injury severity among cyclists was likely to be higher where an Heavy Goods Vehicle (HGV) was involved, and certain route conditions (bicycle infrastructure, 30 kph zones, and urban zones) were associated with lower injury severity. Interactions exist between the two: collisions involving large vehicles in lower-risk environments are less likely to lead to KSIs than collisions involving large vehicles in higher-risk environments. Finally, motorists involved in a collision were more likely than the injured cyclists to have committed an error or infraction. The study supports the creation of infrastructure that separates cyclists from motor traffic. Also, action needs to be taken to address motorist behaviour, given the imbalance between responsibility and risk.

The Influence of Recognition and Social Support on European Health Professionals' Occupational Stress: A Demands-Control-Social Support-Recognition Bayesian Network Model.

Healthcare professionals undergo high levels of occupational stress as a result of their working conditions. Thus, the aim of this study is to develop a model that focuses on healthcare professionals so as to analyze the influence that job demands, control, social support, and recognition have on the likelihood that a worker will experience stress. The data collected correspond to 2,211 healthcare workers from 35 countries, as reported in the sixth European Working Condition Survey (EWCS). The results obtained from this study allow us to infer stress under several working condition scenarios and to identify the more relevant variables in order to reduce this stress in healthcare professionals, which is of paramount importance to managing the stress of workers in this sector. The Bayesian network proposed indicates that emotional demands have a greater influence on raising the likelihood of stress due to workload than do family demands. The results show that the support of colleagues, in general, has less effect on reducing stress than social support from superiors. Furthermore, the sensitivity analysis shows that, in high-demand and low-control situations, recognition clearly impacts stress, drastically reducing it.

Using Bayesian networks to analyze occupational stress caused by work demands: preventing stress through social support.

Occupational stress is a major health hazard and a serious challenge to the effective operation of any company and represents a major problem for both individuals and organizations. Previous researches have shown that high demands (e.g. workload, emotional) combined with low resources (e.g. support, control, rewards) are associated with adverse health (e.g. psychological, physical) and organizational impacts (e.g. reduced job satisfaction, sickness absence). The objective of the present work is to create a model to analyze how social support reduces the occupational stress caused by work demands. This study used existing Spanish national data on working conditions collected by the Spanish Ministry of Labour and Immigration in 2007, where 11,054 workers were interviewed by questionnaire. A probabilistic model was built using Bayesian networks to explain the relationships between work demands and occupational stress. The model also explains how social support contributes positively to reducing stress levels. The variables studied were intellectually demanding work, overwork, workday, stress, and social support. The results show the importance of social support and of receiving help from supervisors and co-workers in preventing occupational stress. The study provides a new methodology that explains and quantifies the effects of intellectually demanding work, overwork, and workday in occupational stress. Also, the study quantifies the importance of social support to reduce occupational stress.

From the traditional concept of safety management to safety integrated with quality.

This editorial reviews the evolution of the concepts of safety and quality that have been used in the traditional workplace. The traditional programs of safety are explored showing strengths and weaknesses. The concept of quality management is also viewed. Safety management and quality management principles, stages, and measurement are highlighted. The concepts of quality and safety guarantee are assessed. Total Quality Management concepts are reviewed and applied to safety quality. Total safety management principles are discussed. Finally, an analysis of the relationship between quality and safety from data collected from a company in Spain is presented.