The relationship between presenteeism and job satisfaction: A mediated moderation model using work engagement and perceived organizational support

Research on presenteeism has largely focused on its prevalence, determinants and consequences on the health of both employees and organizations. To date, few studies have examined the influence of presenteeism on workers’ attitudinal and motivational responses. Based on the Effort–Recovery Theory, this study evaluates the mediating effect of work engagement in the relationship between presenteeism and job satisfaction. Building on previous work, this study also proposes to consider perceived organizational support as a moderator of the work engagement–job satisfaction relationship. Presented in the form of a mediated moderation model, the results of bootstrapped regression analyses show three main results. First, presenteeism is negatively associated with work engagement and job satisfaction. Secondly, work engagement is one of the factors through which presenteeism influences job satisfaction. Thirdly, perceived organizational support moderates the association between work engagement and job satisfaction so that, at a low level of work engagement, feeling supported by the organization makes a difference on job satisfaction. Overall, this research is part of the limited number of studies that have focused on the interplay existing between presenteeism and its consequences in terms of job attitudes.     

An Ecological Model for Quantitative Risk Assessment for Schistosomiasis: The Case of a Patchy Environment in the Coastal Tropical Area of Northeastern Brazil

We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case‐specific features: stage‐structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site‐specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics. We parameterize the model through a real‐world application in the district of Porto de Galinhas (PG), one of the main touristic destinations in Brazil, where previous studies identified four parasite populations within the metapopulation. The results provide a good approximation of the dynamics of the system and are in agreement with our field observations, i.e., the lack of basic infrastructure (sanitation level and health programs) makes PG a suitable habitat for the persistence and growth of a parasite metapopulation. We quantify the risk of SM metapopulation explosion and quasi‐extinction and the time to metapopulation explosion and quasi‐extinction. We evaluate the sensitivity of the results under varying scenarios of future periodic PZQ treatment (based on the Brazilian Ministry of Health's plan) and sanitation quality. We conclude that the plan might be useful to slow SM metapopulation growth but not to control it. Additional investments in better sanitation are necessary.     

Model averaging inconcentration–QT analyses

This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Four criteria to evaluate providers' service-delivery response to new contraceptive introduction

This article presents an evaluation framework developed to assess the first-level effects of introducing the Standard Days Method (SDM) in Peru Ministry of Health clinics. Four questions are asked: 1) To what extent do providers routinely achieve SDM service delivery standards? 2) Is the time invested in SDM delivery consistent with program norms? 3) How does SDM delivery compare with delivery of established methods? and 4) How does SDM introduction affect delivery of established methods? A study at 62 clinics demonstrated the framework's usefulness. The Standard Days Method introduction had positive overall effects on the quality of care but provider training needed adjustments.     

A new regression model for bimodal data and applications in agriculture

We define the odd log-logistic exponential Gaussian regression with two systematic components, which extends the heteroscedastic Gaussian regression and it is suitable for bimodal data quite common in the agriculture area. We estimate the parameters by the method of maximum likelihood. Some simulations indicate that the maximum-likelihood estimators are accurate. The model assumptions are checked through case deletion and quantile residuals. The usefulness of the new regression model is illustrated by means of three real data sets in different areas of agriculture, where the data present bimodality.     

The Global Compact for Safe,Orderly and Regular Migration: What's Next

The Director General of IOM reflects on the next steps to implement the Global Compact for Migration, IOM's new responsibility as Coordinator of the UN Migration Network, and the role that research can play in realizing the Compact's potential.     

Sexual Health Services for Homeless Youth: A Qualitative Analysis of their Experiences

The sexual health problems experienced by homeless youth bring into question their use of available sexual health services. Using a qualitative typological analysis, this study aims to identify sexual health services utilization profiles for homeless youth, and to understand the role of the homeless experience on the utilization of sexual health services. Individual interviews were conducted with 33 homeless youth (17 men, 16 women) between 18 and 25?years of age. Typological analysis identified four profiles: (1) a targeted use of sexual health services to determine one’s serological status following a relational change during the homeless experience; (2) a limited use of sexual health services to manage sexual emergencies that arise during the homeless experience; (3) a regular use of sexual health services to avoid the risks associated with the homeless experience; (4) a frequent use of sexual health services to obtain support when engaging in prostitution during the homeless experience. This study shows that the precarious and unstable conditions within the homeless experience incite youth to utilize sexual health services in different ways. These findings point to the importance of rethinking sexual health services to better adapt them to the different utilization profiles of homeless youth.     

Subset sum problems with digraph constraints

We introduce and study optimization problems which are related to the well-known Subset Sum problem. In each new problem, a node-weighted digraph is given and one has to select a subset of vertices whose total weight does not exceed a given budget. Some additional constraints called digraph constraints and maximality need to be satisfied. The digraph constraint imposes that a node must belong to the solution if at least one of its predecessors is in the solution. An alternative of this constraint says that a node must belong to the solution if all its predecessors are in the solution. The maximality constraint ensures that no superset of a feasible solution is also feasible. The combination of these constraints provides four problems. We study their complexity and present some approximation results according to the type of input digraph, such as directed acyclic graphs and oriented trees.     

Rainfall interception capacity of tree species used in urban afforestation

Afforestation is inserted in the urban environment and interferes directly in the surface runoff. In order to quantify the rainfall interception by tree species, an experiment was carried out in the city of Uruaçu, Goiás, Brazil, with the four most common tree species in the urban afforestation of the region. The species chosen were the Mangifera indica (mango tree), the Caesalpinia peltophoroides (sibipiruna tree), the Pachira aquatica (munguba tree) and the Licania tomentosa (oiti). In order to register precipitation, ten pluviographs were used. They are capable of measuring precipitation over time in terms of duration, volume, and intensity. For events with a mean cumulative precipitation of 16.7 mm, the mean values of interception found in each species were: Mangifera indica - 8.0 mm; Pachira aquatica - 7.4 mm; Licania tomentosa - 7.2 mm; and Caesalpinia peltophoroides - 4.8 mm. The research confirms the importance of studies related to the identification of the species’ individual characteristics that interfere in the rainfall interception capacity and that can consequently contribute to urban drainage actions. In addition, it proves the existence of variations of rainfall interception in relation to rainfall events and during their occurrences and emphasizes the need for a careful definition of the species that will compose the urban afforestation.     

<Emphasis Type="BoldItalic">MAD-STEC</Emphasis>: a method for multiple automatic detection of space-time emerging clusters

Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev–Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.