863 resultados para Job Demands-Resources model


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This research has as its main reference, the need to detect the development initiatives by public higher education, concepts, methods and teaching and pedagogical tools and to investigate the ability to transfer knowledge and practices of teaching and learning produced for other levels education. The task of providing appropriate training of teachers of basic education to university education is a vital political and administrative demands for a large country, which needs to adequately educate its people, so he can face in the right conditions, the huge and complex demands of regional and national development. The research presented here, aims to gauge the extent and adequacy of current media and information as tools for teaching and pedagogical transfer the knowledge and practices of teaching and learning as a tool for updating and also for training or non-presence blended Primary School Teacher Education. From the established goals will be carried out research, conceptual and field, to analyze and evaluate some educational practices and resulting forms of communication and also to assess the effects brought about by replacing the linear communication model and the model of unilateral to multilateral communication networks on digital models, and practices of schooling. The results obtained from both theoretical and practical will be on the selection of concepts, content production, methodologies and resources run by different "means" integrated with the cultural, economic and social development, both locally, regionally or nationally. The strategic aim will be to expand from the analysis, production and dissemination of concepts, methods and tools made by teachers of Basic Education and Higher Education, teaching and pedagogical possibilities of media and digital devices that are emerging as the derivation of network communication.

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Pós-graduação em Saúde Coletiva - FMB

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Saúde Coletiva - FMB

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Preservation of rivers and water resources is crucial in most environmental policies and many efforts are made to assess water quality. Environmental monitoring of large river networks are based on measurement stations. Compared to the total length of river networks, their number is often limited and there is a need to extend environmental variables that are measured locally to the whole river network. The objective of this paper is to propose several relevant geostatistical models for river modeling. These models use river distance and are based on two contrasting assumptions about dependency along a river network. Inference using maximum likelihood, model selection criterion and prediction by kriging are then developed. We illustrate our approach on two variables that differ by their distributional and spatial characteristics: summer water temperature and nitrate concentration. The data come from 141 to 187 monitoring stations in a network on a large river located in the Northeast of France that is more than 5000 km long and includes Meuse and Moselle basins. We first evaluated different spatial models and then gave prediction maps and error variance maps for the whole stream network.

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Wildlife biologists are often interested in how an animal uses space and the habitat resources within that space. We propose a single model that estimates an animal’s home range and habitat selection parameters within that range while accounting for the inherent autocorrelation in frequently sampled telemetry data. The model is applied to brown bear telemetry data in southeast Alaska.

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Black bears (Ursus americanus) forage selectively in natural environments. To determine if bears also forage selectively for anthropogenic resources we analyzed data on vehicles broken into by bears from Yosemite National Park, California. We classified vehicles into 9 categories based on their make and model and collected data on use (2001–2007) and availability (2004–2005). From 2001 to 2007 bears broke into 908 vehicles at the following rates: minivan (26.0%), sport–utility vehicle (22.5%), small car (17.1%), sedan (13.7%), truck (11.9%), van (4.2%), sports car (1.7%), coupe (1.7%), and station wagon (1.4%). Only use of minivans (29%) during 2004–2005 was significantly higher than expected (7%). We discuss several competing hypotheses about why bears selected minivans.

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Objective: To determine current food handling practices, knowledge and beliefs of primary food handlers with children 10 years old and the relationship between these components. Design: Surveys were developed based on FightBac!™ concepts and the Health Belief Model (HBM) construct. Participants: The majority of participants (n= 503) were females (67%), Caucasians (80%), aged between 30 to 49 years old (83%), had one or two children (83%), prepared meals all or most of the time (76%) and consumed meals away from home three times or less per week (66%). Analysis: Descriptive statistics and inferential statistics using Spearman’s rank correlation coefficient (rho) (p<0.05 and one-tail) and Chi-square were used to examine frequency and correlations. Results: Few participants reached the food safety objectives of Healthy People 2010 for safe food handling practices (79%). Mixed results were reported for perceived susceptibility. Only half of the participants (53-54%) reported high perceived severity for their children if they contracted food borne illness. Most participants were confident of their food handling practices for their children (91%) and would change their food handling practices if they or their family members previously experienced food poisoning (79%). Participants’ reasons for high self-efficacy were learning from their family and independently acquiring knowledge and skills from the media, internet or job. The three main barriers to safe food handling were insufficient time, lots of distractions and lack of control of the food handling practices of other people in the household. Participants preferred to use food safety information that is easy to understand, has scientific facts, causes feelings of health-threat and has lots of pictures or visuals. Participants demonstrate high levels of knowledge in certain areas of the FightBac!TM concepts but lacked knowledge in other areas. Knowledge and cues to action were most supportive of the HBM construct, while perceived susceptibility was least supportive of the HBM construct. Conclusion: Most participants demonstrate many areas to improve in their food handling practices, knowledge and beliefs. Adviser: Julie A. Albrecht

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Pós-graduação em Saúde Coletiva - FMB

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The concept of epidemiological intelligence, as a construction of information societies, goes beyond monitoring a list of diseases and the ability to elicit rapid responses. The concept should consider the complexity of the definition of epidemiology in the identification of this object of study without being limited to a set of actions in a single government sector. The activities of epidemiological intelligence include risk assessment, strategies for prevention and protection, subsystems of information, crisis management rooms, geographical analysis, etc. This concept contributes to the understanding of policies in health, in multisectorial and geopolitical dimensions, as regards the organization of services around public health emergencies, primary healthcare, as well as disasters. The activities of epidemiological intelligence should not be restricted to scientific research, but the researchers must beware of threats to public health. Lalonde's model enabled consideration of epidemiological intelligence as a way to restructure policies and share resources by creating communities of intelligence, whose purpose is primarily to deal with public health emergencies and disasters.

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Objective: This study aims to address difficulties reported by the nursing team during the process of changing the management model in a public hospital in Brazil. Methods: This qualitative study used thematic content analysis as proposed by Bardin, and data were analyzed using the theoretical framework of Bolman and Deal. Results: The vertical implementation of Participatory Management contradicted its underlying philosophy and thereby negatively influenced employee acceptance of the change. The decentralized structure of the Participatory Management Model was implemented but shared decision-making was only partially utilized. Despite facilitation of the communication process within the unit, more significant difficulties arose from lack of communication inter-unit. Values and principals need to be shared by teams, however, that will happens only if managers restructure accountabilities changing job descriptions of all team members. Conclusion: Innovative management models that depart from the premise of decentralized decision-making and increased communication encourage accountability, increased motivation and satisfaction, and contribute to improving the quality of care. The contribution of the study is that it describes the complexity of implementing an innovative management model, examines dissent and intentionally acknowledges the difficulties faced by employees in the organization.

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Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

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Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

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This case-control study aimed to test the association between voice disorders and job stress among public schoolteachers in Sao Paulo, Brazil. The groups consisted of teachers with (n = 165) and without (n = 105) voice-related complaints. Both groups answered the questionnaires Conditions of Vocal Production and Job Stress Scale. Analysis of cases and controls showed comparable samples, differing only by vocal symptoms. There was a statistically significant difference between cases and controls in relation to job stress involving high strain (OR = 2.1;95%CI: 1.1-3.9), which places high demands combined with low job control. High strain in cases in this study represents the highest risk of physical and mental disorders for teachers. Loss of voice prevents teachers from continuing in their professional role, eliminates their professional identity, and jeopardizes their career.

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This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.