966 resultados para Behavioral model


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Objectives: To assess the role of the individual determinants on the inequalities of dental services utilization among low-income children living in the working area of Brazilian`s federal Primary Health Care program, which is called Family Health Program (FHP), in a big city in Southern Brazil. Methods: A cross-sectional population-based study was performed. The sample included 350 children, ages 0 to 14 years, whose parents answered a questionnaire about their socioeconomic conditions, perceived needs, oral hygiene habits, and access to dental services. The data analysis was performed according to a conceptual framework based on Andersen`s behavioral model of health services use. Multivariate models of logistic regression analysis instructed the hypothesis on covariates for never having had a dental visit. Results: Thirty one percent of the surveyed children had never had a dental visit. In the bivariate analysis, higher proportion of children who had never had a dental visit was found among the very young, those with inadequate oral hygiene habits, those without perceived need of dental care, and those whose family homes were under absent ownership. The mechanisms of social support showed to be important enabling factors: children attending schools/kindergartens and being regularly monitored by the FHP teams had higher odds of having gone to the dentist, even after adjusting for socioeconomic, demographic, and need variables. Conclusions: The conceptual framework has confirmed the presence of social and psychosocial inequalities on the utilization pattern of dental services for low-income children. The individual determinants seem to be important predictors of access.

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The hierarchical hidden Markov model (HHMM) is an extension of the hidden Markov model to include a hierarchy of the hidden states. This form of hierarchical modeling has been found useful in applications such as handwritten character recognition, behavior recognition, video indexing, and text retrieval. Nevertheless, the state hierarchy in the original HHMM is restricted to a tree structure. This prohibits two different states from having the same child, and thus does not allow for sharing of common substructures in the model. In this paper, we present a general HHMM in which the state hierarchy can be a lattice allowing arbitrary sharing of substructures. Furthermore, we provide a method for numerical scaling to avoid underflow, an important issue in dealing with long observation sequences. We demonstrate the working of our method in a simulated environment where a hierarchical behavioral model is automatically learned and later used for recognition.

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This study has formulated a behavioral model of individual activity time allocation on weekends, and has extended it to incorporate the latent determinants of time use decisions during weekdays by using a latent variable model. The ultimate goals in developing this model are to improve the individual weekend activity time allocation model by introducing latent variables, and to estimate the value of activity time of different activity types. We conducted a pilot empirical investigation using a small data set regarding time use and expenditure both for weekdays and weekends, and a few indicators of the latent variables collected from individuals in Yokohama, Japan. The empirical findings suggest that the proposed model is valuable not only for modeling activity time allocation, but also in calculating the value of activity time.

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Previous studies on residential energy end use behavior reported significant reduction in energy end use of 7% to 24% when feedback is used to modify behavior in an energy efficient manner. However, most feedback systems investigated in previous studies have not benefited from advanced information systems (IS). IS can shape energy efficiency behavior by providing real-time feedback on energy consumption, cost and environmental impact. Such systems represent a new and less-researched subfield of energy informatics. This paper provides a conceptual framework for showing the potential use of IS to modify residential energy use behavior towards better energy efficiency. The framework builds on research in residential energy end use, in particular energy end use behavioral model. It provides conceptual inputs for a blue-print to develop a residential energy management information system (REMIS) and also highlights the use of new information and communications technologies (ICT) that had not been widely used, setting the grounds for further research in this area.

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Malicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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In order to determine the modulation of anxiolytic and panicolytic-like effects of diazepam by the hormonal cycle of female rats, male and female rats – the latter divided per estrous cycle phase (estrus, diestrus, metaestrus and proestrus) – were tested in the elevated T-maze, a behavioral model of panic and anxiety. Diazepam (0.5, 1.0 and 2.0 mg/kg) or saline solution was injected in individual animals that were submitted to one session in the elevated T-maze 25 min after drug/saline administration. The test consisted of three avoidance trials and one escape trial, separated by a 30 s interval, during which the animals were isolated in individual cages. The avoidance trials began with the animal being placed at the end of the maze's enclosed arm. The time necessary for the animal to leave the central square was considered as the response's latency. The trials that exceeded 300 s were considered as failures. Results demonstrate a decrease in the effects of diazepam in inhibitory avoidance (anxiety) trials in females in diestrus and proestrus, but no relation of gender or estrous cycle on diazepam effects on escape trials (fear). The results support the hypothesis that down-regulation of GABAA receptors by activation of nuclear estrogen receptors and induction of PKC-mediated GABAA receptor phosphorylation by activation of surface estrogen receptors in raphe neurons underlie the modulation of diazepam sensitivity by estrogen.

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The association between Social Support, Health Status, and Health Services Utilization of the elderly, was explored based on the analysis of data from the Supplement on Aging to the National Health Interview Survey, 1984 (N = 11,497) using a modified framework of Aday and Andersen's Expanded Behavioral Model. The results suggested that Social Support as operationalized in this study was an independent determinant of the use of health services. The quantity of social activities and the use of community services were the two most consistent determinants across different types of health services use.^ The effects of social support on the use of health services were broken down into three components to facilitate explanations of the mechanisms through which social support operated. The Predisposing and Enabling component of Social Support had independent, although not uniform, effects on the use of health services. Only slight substitute effects of social support were detected. These included the substitution of the use of senior centers for longer stay in the hospital and the substitution of help with IADL problems for the use of formal home care services.^ The effect of financial support on the use of health services was found to be different for middle and low income populations. This differential effect was also found for the presence of intimate networks, the frequencies of interaction with children and the perceived availability of support among urban/rural, male/female and white/non-white subgroups.^ The study also suggested that the selection of appropriate Health Status measures should be based on the type of Health Services Utilization in which a researcher is interested. The level of physical function limitation and role activity limitation were the two most consistent predictors of the volume of physician visits, number of hospital days, and average length of stay in the hospital during the past year.^ Some alternative hypotheses were also raised and evaluated, when possible. The impacts of the complex sample design, the reliability and validity of the measures and other limitations of this analysis were also discussed. Finally, a revised framework was proposed and discussed based on the analysis. Some policy implications and suggestions for future study were also presented. ^

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The purpose of this study was to apply the Behavioral Model of Health Services Utilization to examine an existing worksite HRA program to identify and examine the roles of determinants of participation in HRA programs. The program consisted of three activities: questionnaire, physical examination, and group interpretation sessions. All of the 1821 employees were eligible for the program; 523 (29%) participated in at least one activity. Results from bivariate analyses suggest that being female, being white, having fewer dependents, and having higher medical claims for the past year were positively associated with participation. Results of logistic regression suggest that Age, Sex, Race, Marital, Number of Dependents, Job Title, Months with the Company, and a log transformed value of Employee's Total Medical Claims were all significant determinants of participation. Applications of the logistic regression models, other factors that should be investigated in future studies, and the limitations of the study were discussed. ^

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Objectives. The purpose of this study was to elucidate behavioral determinants (prevailing attitudes and beliefs) of hand hygiene practices among undergraduate dental students in a dental school. ^ Methods. Statistical modeling using the Integrative Behavioral Model (IBM) prediction was utilized to develop a questionnaire for evaluating behavioral perceptions of hand hygiene practices by dental school students. Self-report questionnaires were given to second, third and fourth year undergraduate dental students. Models representing two distinct hand hygiene practices, termed "elective in-dental school hand hygiene practice" and "inherent in-dental school hand hygiene practice" were tested using linear regression analysis. ^ Results. 58 responses were received (24.5%); the sample mean age was 26.6 years old and females comprised 51%. In our models, elective in-dental school hand hygiene practice and inherent in-dental school hand hygiene practice, explained 40% and 28%, respectively, of the variance in behavioral intention. Translation of community hand hygiene practice to the dental school setting is the predominant driver of elective hand hygiene practice. Intended elective in-school hand hygiene practice is further significantly predicted by students' self-efficacy. Students' attitudes, peer pressure of other dental students and clinic administrators, and role modeling had minimal effects. Inherent hand hygiene intent was strongly predicted by students' beliefs in the benefits of the activity and, to a lesser extent, role modeling. Inherent and elective community behaviors were insignificant. ^ Conclusions. This study provided significant insights into dental student's hand hygiene behavior and can form the basis for an effective behavioral intervention program designed to improve hand hygiene compliance.^

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Infant Mortality has been made a point of emphasis by the Department of Health and Human Services in the Healthy People 2000, 2010, and 2020 priorities. This study used the Behavioral Model for Vulnerable Populations to consider a number of factors which impact infant mortality in the indigent populations in the State of Texas. The primary focus of this study was the enabling factor of community resources, specifically the program used by each county to provide care to their indigent population. The Legislature of the State of Texas requires that each state have a program set up within a Hospital District, Public Hospital or develop a County Indigent Health Care Program (CIHCP) in order to provide the basic health care needs of their most vulnerable residents. We sought to determine whether the development of a CICHP without an appointed hospital to provide the care would have an adverse effect on residents seeking care and increase infant mortality. A Poisson Regression Analysis was used to analyze incidence rate ratios adjusting for race/ethnicity and wealth/poverty variables. Our study showed that counties using a CIHCP had significantly lower infant mortality rates when compared to counties using a hospital district and were statistically equivalent to counties using a public hospital program or a combination of service programs. This relationship was maintained when adjusted incidence rate ratios were calculated. This may give evidence that counties struggling to fund a public hospital or hospital district may be able to find a more cost-effective alternative in the CIHCP without adversely affecting the health status of their residents. More cost-benefit analysis and controlling analysis must be done to further characterize this relationship. ^

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A Internet está inserida no cotidiano do indivíduo, e torna-se cada vez mais acessível por meio de diferentes tipos de dispositivos. Com isto, diversos estudos foram realizados com o intuito de avaliar os reflexos do seu uso excessivo na vida pessoal, acadêmica e profissional. Esta dissertação buscou identificar se a perda de concentração e o isolamento social são alguns dos reflexos individuais que o uso pessoal e excessivo de aplicativos de comunicação instantânea podem resultar no ambiente de trabalho. Entre as variáveis selecionadas para avaliar os aspectos do uso excessivo de comunicadores instantâneos tem-se a distração digital, o controle reduzido de impulso, o conforto social e a solidão. Através de uma abordagem de investigação quantitativa, utilizaram-se escalas aplicadas a uma amostra de 283 pessoas. Os dados foram analisados por meio de técnicas estatísticas multivariadas como a Análise Fatorial Exploratória e para auferir a relação entre as variáveis, a Regressão Linear Múltipla. Os resultados deste estudo confirmam que o uso excessivo de comunicadores instantâneos está positivamente relacionado com a perda de concentração, e a variável distração digital exerce uma influência maior do que o controle reduzido de impulso. De acordo com os resultados, não se podem afirmar que a solidão e o conforto social exercem relações com aumento do isolamento social, devido à ausência do relacionamento entre os construtos.

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This dissertation introduces an approach to generate tests to test fail-safe behavior for web applications. We apply the approach to a commercial web application. We build models for both behavioral and mitigation requirements. We create mitigation tests from an existing functional black box test suite by determining failure type and points of failure in the test suite and weaving required mitigation based on weaving rules to generate a test suite that tests proper mitigation of failures. A genetic algorithm (GA) is used to determine points of failure and type of failure that needs to be tested. Mitigation test paths are woven into the behavioral test at the point of failure based on failure specific weaving rules. A simulator was developed to evaluate choice of parameters for the genetic algorithm. We showed how to tune the fitness function and performed tuning experiments for GA to determine what values to use for exploration weight and prospecting weight. We found that higher defect densities make prospecting and mining more successful, while lower mitigation defect densities need more exploration. We compare efficiency and effectiveness of the approach. First, the GA approach is compared to random selection. The results show that the GA performance was better than random selection and that the approach was robust when the search space increased. Second, we compare the GA against four coverage criteria. The results of comparison show that test requirements generated by a genetic algorithm (GA) are more efficient than three of the four coverage criteria for large search spaces. They are equally effective. For small search spaces, the genetic algorithm is less effective than three of the four coverage criteria. The fourth coverage criteria is too weak and unable to find all defects in almost all cases. We also present a large case study of a mortgage system at one of our industrial partners and show how we formalize the approach. We evaluate the use of a GA to create test requirements. The evaluation includes choice of initial population, multiplicity of runs and a discussion of the cost of evaluating fitness. Finally, we build a selective regression testing approach based on types of changes (add, delete, or modify) that could occur in the behavioral model, the fault model, the mitigation models, the weaving rules, and the state-event matrix. We provide a systematic method by showing the formalization steps for each type of change to the various models.

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This study identifies and describes HIV Voluntary Counseling and Testing (VCT) of middle aged and older Latinas. The rate of new cases of HIV in people age 45 and older is rapidly increasing, with a 40.6% increase in the numbers of older Latinas infected with HIV between 1998 and 2002. Despite this increase, there is paucity of research on this population. This research seeks to address the gap through a secondary data analysis of Latina women. The aim of this study is twofold: (1) Develop and empirically test a multivariate model of VCT utilization for middle aged and older Latinas; (2) To test how the three individual components of the Andersen Behavioral Model impact VCT for middle aged and older Latinas. The study is organized around the three major domains of the Andersen Behavioral Model of service use that include: (a) predisposing factors; (b) enabling characteristics and (c) need. Logistic regression using structural equation modeling techniques were used to test multivariate relationships of variables on VCT for a sample of 135 middle age and older Latinas residing in Miami-Dade County, Florida. Over 60% of participants had been tested for HIV. Provider endorsement was found to he the strongest predictor of VCT (odds ration [OR] 6.38), followed by having a clinic as a regular source of healthcare (OR=3.88). Significant negative associations with VCT included self rated health status (OR=.592); Age (OR=.927); Spanish proficiency (OR=.927); number of sexual partners (OR=.613) and consumption of alcohol during sexual activity (.549). As this line of inquiry provides a critical glimpse into the VCT of older Latinas, recommendations for enhanced service provision and research will he offered.

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The first essay developed a respondent model of Bayesian updating for a double-bound dichotomous choice (DB-DC) contingent valuation methodology. I demonstrated by way of data simulations that current DB-DC identifications of true willingness-to-pay (WTP) may often fail given this respondent Bayesian updating context. Further simulations demonstrated that a simple extension of current DB-DC identifications derived explicitly from the Bayesian updating behavioral model can correct for much of the WTP bias. Additional results provided caution to viewing respondents as acting strategically toward the second bid. Finally, an empirical application confirmed the simulation outcomes. The second essay applied a hedonic property value model to a unique water quality (WQ) dataset for a year-round, urban, and coastal housing market in South Florida, and found evidence that various WQ measures affect waterfront housing prices in this setting. However, the results indicated that this relationship is not consistent across any of the six particular WQ variables used, and is furthermore dependent upon the specific descriptive statistic employed to represent the WQ measure in the empirical analysis. These results continue to underscore the need to better understand both the WQ measure and its statistical form homebuyers use in making their purchase decision. The third essay addressed a limitation to existing hurricane evacuation modeling aspects by developing a dynamic model of hurricane evacuation behavior. A household's evacuation decision was framed as an optimal stopping problem where every potential evacuation time period prior to the actual hurricane landfall, the household's optimal choice is to either evacuate, or to wait one more time period for a revised hurricane forecast. A hypothetical two-period model of evacuation and a realistic multi-period model of evacuation that incorporates actual forecast and evacuation cost data for my designated Gulf of Mexico region were developed for the dynamic analysis. Results from the multi-period model were calibrated with existing evacuation timing data from a number of hurricanes. Given the calibrated dynamic framework, a number of policy questions that plausibly affect the timing of household evacuations were analyzed, and a deeper understanding of existing empirical outcomes in regard to the timing of the evacuation decision was achieved.