Etiological patterns of child abuse and neglect

A review of the various etiological possibilities for child abuse and neglect, designed to offer an additional and different possibility. Consideration is first given to problems, namely the lack of universal definition, heterogeneous effects, and retrospective research. The probability of multifactor models is noted, and sexual abuse is given separate consideration, followed by an exploration of the existing models termed ecological, transactional, transitional, and attachment. An interactive aggression model is then offered as the new possibility. Empirical evidence for cultural and/or ethnic predispositions suggests that society can be a supporting or inhibiting factor in terms of promoting or opposing violence.     

Risk Perception Among Smokers: A Qualitative Study

The aim of this qualitative study is to identify the dimensions people used to assess the risk of smoking and then compare them with those used by health professionals in primary healthcare. Five discussion groups were conducted. The field work was carried out in Barcelona (Spain), from February 2005 to January 2006. Data were analyzed following a semantic‐thematic categorical content analysis (ACC‐ts). Results showed that people tend to employ stereotypical discourses when evaluating the risk of smoking. Similarly, they reassess the risk in the context of their life experience and incorporate new nuances to the arguments sustaining their behavior. Once this reassessment takes place, the decision to continue smoking emerges, and smokers come up with additional arguments justifying their habit (i.e., age, benefits related to costs). Professionals are aware of this process and its multidimensional nature. Nevertheless, their discourse loses this multidimensional feature when discussing the strategies they use at smoking cessation interventions. This qualitative study increases the understanding of various meanings that people attribute to their life experience. These assumptions may be useful for developing health practices that are closer to people. As a practical utility of these results, it would be interesting to apply a preliminary assessment of the different meanings that people attribute to smoking from their life context in risk communication.     

A necessary and sufficient condition for an estimator to be optimal

A necessary condition for an estimator δ₀ to be optimal in a class Δ of estimators is derived. Thic condition becomes also sufficient when the loss function is convex.     

Social innovation indicators

This article provides the results of the Regional Social Innovation Index (RESINDEX), a conceptual and empirical model that explores indicators of social innovation at organizational and regional level. The RESINDEX model links absorptive capacity of knowledge and social innovation in four types of key regional agents: profit and non-profit organizations, universities, and technological centres. The pilot application of the RESINDEX model held in the Basque Country (Spain) during the year 2013. Within the framework of this study 282 regional organizations were surveyed. The article contributes to the conceptual and empirical discussion on indicators in social innovation.     

The statistical impact of inflation on interest rates

Understanding the behavior of interest rates is of central importance in finance. This is due to the fact that interest and forward rates serve as underlyings for many fixed income products. Furthermore, interest rate-based quantities may be used as numeraires when it comes to computing present values of future payoffs. An important macroeconomic factor which is likely to trigger interest rates is inflation. In this paper we extend a well-known continuous time interest rate model by incorporating inflation. Finally, we apply a statistical test to real data to explore the goodness-of-fit of the inflation-based model.     

Hand-Hygiene Mitigation Strategies Against Global Disease Spreading through the Air Transportation Network

The risk for a global transmission of flu-type viruses is strengthened by the physical contact between humans and accelerated through individual mobility patterns. The Air Transportation System plays a critical role in such transmissions because it is responsible for fast and long-range human travel, while its building components—the airports—are crowded, confined areas with usually poor hygiene. Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) consider hand hygiene as the most efficient and cost-effective way to limit disease propagation. Results from clinical studies reveal the effect of hand washing on individual transmissibility of infectious diseases. However, its potential as a mitigation strategy against the global risk for a pandemic has not been fully explored. Here, we use epidemiological modeling and data-driven simulations to elucidate the role of individual engagement with hand hygiene inside airports in conjunction with human travel on the global spread of epidemics. We find that, by increasing travelers engagement with hand hygiene at all airports, a potential pandemic can be inhibited by 24% to 69%. In addition, we identify 10 airports at the core of a cost-optimal deployment of the hand-washing mitigation strategy. Increasing hand-washing rate at only those 10 influential locations, the risk of a pandemic could potentially drop by up to 37%. Our results provide evidence for the effectiveness of hand hygiene in airports on the global spread of infections that could shape the way public-health policy is implemented with respect to the overall objective of mitigating potential population health crises.     

Bayesian Analysis of Multiple Hypothesis Testing with Applications to Microarray Experiments

Recently, the field of multiple hypothesis testing has experienced a great expansion, basically because of the new methods developed in the field of genomics. These new methods allow scientists to simultaneously process thousands of hypothesis tests. The frequentist approach to this problem is made by using different testing error measures that allow to control the Type I error rate at a certain desired level. Alternatively, in this article, a Bayesian hierarchical model based on mixture distributions and an empirical Bayes approach are proposed in order to produce a list of rejected hypotheses that will be declared significant and interesting for a more detailed posterior analysis. In particular, we develop a straightforward implementation of a Gibbs sampling scheme where all the conditional posterior distributions are explicit. The results are compared with the frequentist False Discovery Rate (FDR) methodology. Simulation examples show that our model improves the FDR procedure in the sense that it diminishes the percentage of false negatives keeping an acceptable percentage of false positives.