Work stress increasingly affects many workers from different countries. Conditions such as high demand, low social support and low job control are considered predictors of increased stress. With data obtained from the V European Working Conditions Survey (EWCS) a Bayesian network model was made. It provides information on the levels of stress in relation to model demand-control-social support (DCS), differentiating into work situations as they are, self-employed, private and public. To deepen understanding of the interrelationships between these variables sensitivity analysis of individual and overall were performed to check the DCS model assumptions. This model applied in the V EWCS identified the variations and similarities between different work situations, proving that having low levels of demand, together with control and high social support, the likelihood of stress decreases.
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.
Obtaining data on worker accident rates is necessary in order to analyze the causes and variables involved in the occurrence of said accidents. The majority of these data, collected after the accident occurs, do not consider the employee׳s working conditions. Here are presented the data on workplace accidents and the conditions of the workers by analyzing the generic data supplied as part of the 7th National Survey of Workplace Conditions (EWCS) in Spain, conducted in 2011. These data will yield the variables needed to determine if the information on workplace risks provided by the survey respondents has an appreciable effect on the occurrence of occupational accidents in the working population, and will also be used to explore other variables.
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