Analysis of working conditions focusing on biological risk: firefighters in Campo Grande, MS, Brazil

Firefighters are exposed to a wide range of risks, among them, biological risk. The objective was to analyze working conditions of firefighters in the city of Campo Grande, MS, Brazil, focusing on risk conditions of exposure to biological material. Three hundred and seven (307) firefighters were interviewed for data collection and observed for ergonomic job analysis (AET). Results: 63.5% of the firefighters suffered some kind of job related accident with blood or body fluids. Statistically significant association was found between having suffered accidents at work and incomplete use of personal protective equipment (PPE). About AET regarding the biological risks, 57.1% of all patients had blood or secretions, which corresponds in average to 16.0% of the total work time, based on a working day of 24 h. Besides biological risks, other stressing factors were identified: emergency and complexity of decision, high responsibility regarding patients and environment, and conflicts. Health promotion and accident prevention actions must be emphasized as measures to minimize these risks.     

A computerized system to monitor resilience indicators in organizations

The concepts developed by resilience engineering allow the understanding and monitoring the functioning of organizations and, particularly, to map the role of human activities, in success or in failure, enabling a better comprehension about how people make decisions in unexpected situations. The capture of information about human activities in the various organization levels gives managers a deeper real-time understanding of what is influencing the people performance, providing awareness of the factors that influence positively or negatively the organizational goals initially projected. The monitoring is important because the correct functioning of complex systems depends on the knowledge that people have to perform their activities and how the system environment provides tools that actually support the human performance. Therefore, organizations should look forward through precursors in operating signals to identify possible problems or solutions in the structure of tasks and activities, safety, quality, schedule, rework, and maintenance. We apply the concepts of resilience engineering to understand the organization by the analysis of cognitive tasks and activities. The aim is the development of a computerized system to monitor human activities to produce indicators to access system resilience. The validation of the approach was made in a real organization and the results show the successful applicability of the system. Based on findings obtained after the experiment of the system in a real organization, and managers and workers opinions, it was possible to show that the use of system provided an anticipated (real-time) perception about how activities are effectively being performed, allowing managers and workers to make decisions more consistent with daily problems, and also to anticipate solutions to cope with unexpected situations.     

Preliminary Findings on Men's Sexual Self-Schema and Sexual Offending: Differences Between Subtypes of Offenders

Available literature suggests that sexual self-schemas (i.e., cognitive generalizations about sexual aspects of oneself) influence sexual behavior. Nonetheless, there is a lack of research regarding their role in sexual offending. The aim of the present study was to investigate the relationship between the men's sexual self-schema dimensions (passionate-loving, powerful-aggressive, and open-minded-liberal) and different types of sexual-offending behavior. A total of 50 rapists, 65 child molesters (21 pedophilic, 44 nonpedophilic), and 51 nonsexual offenders answered the Men's Sexual Self-Schema Scale, the Brief Symptom Inventory (BSI), and the Socially Desirable Response Set Measure (SDRS-5). Data were analyzed using multinomial logistic regression, controlling for age, school education, psychological distress, and social desirability. Results showed that rapists as well as nonsexual offenders were more likely to hold the powerful-aggressive sexual self-view compared to pedophilic and nonpedophilic child molesters. Overall, findings seem to be consistent with both a sociocultural component of aggression and the general cognitive profile of offenders. If further research corroborates these preliminary findings, sexual self-concept may be integrated into a comprehensive multifactorial approach of offending behavior.     

Perceptions of the Neighborhood Environment Associated With Walking at Recommended Intensity and Volume Levels in Recreational Senior Walkers

This study examined the relationship of perceived neighborhood environment factors with recommended volume and intensity of walking in recreational senior walkers. A sample of 85 seniors used an accelerometer and completed the ALPHA questionnaire. Binomial logistic regressions were conducted to detect associations. Perceptions about traffic safety (odds ratio [OR] = 4.395; 95% confidence interval [CI] = 1.024; 18.866) and pleasant environment (OR = 8.718; 95% CI = 1.803; 42.149) were positively related with the achievement of 10,000 steps per day, in older women. The perception of nearby parks was positively associated with the compliance with peak 30-minutes cadence above 100, in older men (OR = 14.353; CI 95% = 1.321; 15.591). No more significant associations were found between perceptions of the neighborhood environment and walking at recommended intensity and volume levels. These results indicated that community initiatives that encourage traffic safety, pleasant environment, and parks may be a promising direction to promote walking at recommended volume and intensity in senior walkers.     

Professional judgements and decisions on placement in foster care and reunification in Portugal

This study aims to analyse professional judgements and decisions made in the Portuguese child care system in face of a case vignette of child maltreatment. Using the approach proposed by Benbenishty et al. [(2015). Decision making in child protection: An international comparative study on maltreatment substantiation, risk assessment and interventions recommendations, and the role of professionals’ child welfare attitudes. Child Abuse & Neglect, 49, 63–75. doi:10.1016/j.chiabu.2015.03.015], we assessed the decisions of professionals, such as to place the child in foster care or reunify her with her family, on the basis of a series of judgements (e.g. substantiation of alleged abuse and neglect, risk assessments) that are influenced by the characteristics of the case, the decision-making context, and mother's and child's wishes. We conclude that there are different approaches to the case based on different professionals' attitudes that can be classified in two groups: one more pro-removal and the other anti-removal. These groups presented different risk assessments and intervention recommendations, and their decisions where significantly influenced by the mother's and child's wishes. Furthermore, we have done comparisons with studies made in other countries, concluding that the country context can be an important factor that leads to different outcomes. Implications for both practice and research are presented.     

Interval-censored data with misclassification: a Bayesian approach

Survival data involving silent events are often subject to interval censoring (the event is known to occur within a time interval) and classification errors if a test with no perfect sensitivity and specificity is applied. Considering the nature of this data plays an important role in estimating the time distribution until the occurrence of the event. In this context, we incorporate validation subsets into the parametric proportional hazard model, and show that this additional data, combined with Bayesian inference, compensate the lack of knowledge about test sensitivity and specificity improving the parameter estimates. The proposed model is evaluated through simulation studies, and Bayesian analysis is conducted within a Gibbs sampling procedure. The posterior estimates obtained under validation subset models present lower bias and standard deviation compared to the scenario with no validation subset or the model that assumes perfect sensitivity and specificity. Finally, we illustrate the usefulness of the new methodology with an analysis of real data about HIV acquisition in female sex workers that have been discussed in the literature.     

Smoking Risks in Spain: Part I—Perception of Risks to the Smoker

Survey evidence for the Spanish population indicates that perceptions of lung cancer risk and life expectancy loss due to smoking are similar to estimates found in the United States. This paper also presents new evidence on the relative lung cancer risk for smokers, the perceived risk of lung disease for smokers, the heart disease risk for smokers, and the relative heart disease risk for smokers, all of which indicate substantial risk perceptions. Risk beliefs are particularly high for younger respondents, but are lower for better educated respondents.     

Model comparison for a complex ecological system

Summary.  The ecological consequences of climate change and its interaction with other environmental pressures, such as nutrient pollution, are little understood. For freshwater ecosystems, knowledge of these combined effects is required for water resource management and in particular for successful implementation of the European Community Water Framework Directive 2000, which requires that all surface-waters should be at, or above, 'good status' by 2016. Statistical analysis of detailed long-term environmental data sets can be used to explore these combined effects. Loch Leven (Scotland) has been routinely monitored since 1967, providing one of the largest and most extensive of such data sets. Over this period there has been evidence of climate change and a period of eutrophication and recovery at the loch. Transfer functions, additive models and varying-coefficient models are used to explore the complex ecological system at Loch Leven with the aim of obtaining insight into the combined effects of climate change and eutrophication on water quality.     

Factor stochastic volatility with time varying loadings and Markov switching regimes

We generalize the factor stochastic volatility (FSV) model of Pitt and Shephard [1999. Time varying covariances: a factor stochastic volatility approach (with discussion). In: Bernardo, J.M., Berger, J.O., Dawid, A.P., Smith, A.F.M. (Eds.), Bayesian Statistics, vol. 6, Oxford University Press, London, pp. 547–570.] and Aguilar and West [2000. Bayesian dynamic factor models and variance matrix discounting for portfolio allocation. J. Business Econom. Statist. 18, 338–357.] in two important directions. First, we make the FSV model more flexible and able to capture more general time-varying variance–covariance structures by letting the matrix of factor loadings to be time dependent. Secondly, we entertain FSV models with jumps in the common factors volatilities through So, Lam and Li's [1998. A stochastic volatility model with Markov switching. J. Business Econom. Statist. 16, 244–253.] Markov switching stochastic volatility model. Novel Markov Chain Monte Carlo algorithms are derived for both classes of models. We apply our methodology to two illustrative situations: daily exchange rate returns [Aguilar, O., West, M., 2000. Bayesian dynamic factor models and variance matrix discounting for portfolio allocation. J. Business Econom. Statist. 18, 338–357.] and Latin American stock returns [Lopes, H.F., Migon, H.S., 2002. Comovements and contagion in emergent markets: stock indexes volatilities. In: Gatsonis, C., Kass, R.E., Carriquiry, A.L., Gelman, A., Verdinelli, I. Pauler, D., Higdon, D. (Eds.), Case Studies in Bayesian Statistics, vol. 6, pp. 287–302].     

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived "factors" as representing biological "subpathway" structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology.