853 resultados para health behavior models


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In the exclusion-process literature, mean-field models are often derived by assuming that the occupancy status of lattice sites is independent. Although this assumption is questionable, it is the foundation of many mean-field models. In this work we develop methods to relax the independence assumption for a range of discrete exclusion process-based mechanisms motivated by applications from cell biology. Previous investigations that focussed on relaxing the independence assumption have been limited to studying initially-uniform populations and ignored any spatial variations. By ignoring spatial variations these previous studies were greatly simplified due to translational invariance of the lattice. These previous corrected mean-field models could not be applied to many important problems in cell biology such as invasion waves of cells that are characterised by moving fronts. Here we propose generalised methods that relax the independence assumption for spatially inhomogeneous problems, leading to corrected mean-field descriptions of a range of exclusion process-based models that incorporate (i) unbiased motility, (ii) biased motility, and (iii) unbiased motility with agent birth and death processes. The corrected mean-field models derived here are applicable to spatially variable processes including invasion wave type problems. We show that there can be large deviations between simulation data and traditional mean-field models based on invoking the independence assumption. Furthermore, we show that the corrected mean-field models give an improved match to the simulation data in all cases considered.

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Introduction: Emergency prehospital medical care providers are frontline health workers during emergencies. However, little is known about their attitudes, perceptions, and likely behaviors during emergency conditions. Understanding these attitudes and behaviors is crucial to mitigating the psychological and operational effects of biohazard events such as pandemic influenza, and will support the business continuity of essential prehospital services. ----- ----- Problem: This study was designed to investigate the association between knowledge and attitudes regarding avian influenza on likely behavioral responses of Australian emergency prehospital medical care providers in pandemic conditions. ----- ----- Methods: Using a reply-paid postal questionnaire, the knowledge and attitudes of a national, stratified, random sample of the Australian emergency prehospital medical care workforce in relation to pandemic influenza were investigated. In addition to knowledge and attitudes, there were five measures of anticipated behavior during pandemic conditions: (1) preparedness to wear personal protective equipment (PPE); (2) preparedness to change role; (3) willingness to work; and likely refusal to work with colleagues who were exposed to (4) known and (5) suspected influenza. Multiple logistic regression models were constructed to determine the independent predictors of each of the anticipated behaviors, while controlling for other relevant variables. ----- ----- Results: Almost half (43%) of the 725 emergency prehospital medical care personnel who responded to the survey indicated that they would be unwilling to work during pandemic conditions; one-quarter indicated that they would not be prepared to work in PPE; and one-third would refuse to work with a colleague exposed to a known case of pandemic human influenza. Willingness to work during a pandemic (OR = 1.41; 95% CI = 1.0–1.9), and willingness to change roles (OR = 1.44; 95% CI = 1.04–2.0) significantly increased with adequate knowledge about infectious agents generally. Generally, refusal to work with exposed (OR = 0.48; 95% CI = 0.3–0.7) or potentially exposed (OR = 0.43; 95% CI = 0.3–0.6) colleagues significantly decreased with adequate knowledge about infectious agents. Confidence in the employer’s capacity to respond appropriately to a pandemic significantly increased employee willingness to work (OR = 2.83; 95% CI = 1.9–4.1); willingness to change roles during a pandemic (OR = 1.52; 95% CI = 1.1–2.1); preparedness to wear PPE (OR = 1.68; 95% CI = 1.1–2.5); and significantly decreased the likelihood of refusing to work with colleagues exposed to (suspected) influenza (OR = 0.59; 95% CI = 0.4–0.9). ----- ----- Conclusions:These findings indicate that education and training alone will not adequately prepare the emergency prehospital medical workforce for a pandemic. It is crucial to address the concerns of ambulance personnel and the perceived concerns of their relationship with partners in order to maintain an effective prehospital emergency medical care service during pandemic conditions.

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BACKGROUND: Grafting of autologous hyaline cartilage and bone for articular cartilage repair is a well-accepted technique. Although encouraging midterm clinical results have been reported, no information on the mechanical competence of the transplanted joint surface is available. HYPOTHESIS: The mechanical competence of osteochondral autografts is maintained after transplantation. STUDY DESIGN: Controlled laboratory study. METHODS: Osteochondral defects were filled with autografts (7.45 mm in diameter) in one femoral condyle in 12 mature sheep. The ipsilateral femoral condyle served as the donor site, and the resulting defect (8.3 mm in diameter) was left empty. The repair response was examined after 3 and 6 months with mechanical and histologic assessment and histomorphometric techniques. RESULTS: Good surface congruity and plug placement was achieved. The Young modulus of the grafted cartilage significantly dropped to 57.5% of healthy tissue after 3 months (P < .05) but then recovered to 82.2% after 6 months. The aggregate and dynamic moduli behaved similarly. The graft edges showed fibrillation and, in some cases (4 of 6), hypercellularity and chondrocyte clustering. Subchondral bone sclerosis was observed in 8 of 12 cases, and the amount of mineralized bone in the graft area increased from 40% to 61%. CONCLUSIONS: The mechanical quality of transplanted cartilage varies considerably over a short period of time, potentially reflecting both degenerative and regenerative processes, while histologically signs of both cartilage and bone degeneration occur. CLINICAL RELEVANCE: Both the mechanically degenerative and restorative processes illustrate the complex progression of regeneration after osteochondral transplantation. The histologic evidence raises doubts as to the long-term durability of the osteochondral repair.

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Currently, well-established clinical therapeutic approaches for bone reconstruction are restricted to the transplantation of autografts and allografts, and the implantation of metal devices or ceramic-based implants to assist bone regeneration. Bone grafts possess osteoconductive and osteoinductive properties, however they are limited in access and availability and associated with donor site morbidity, haemorrhage, risk of infection, insufficient transplant integration, graft devitalisation, and subsequent resorption resulting in decreased mechanical stability. As a result, recent research focuses on the development of alternative therapeutic concepts. Analysing the tissue engineering literature it can be concluded that bone regeneration has become a focus area in the field. Hence, a considerable number of research groups and commercial entities work on the development of tissue engineered constructs for bone regeneration. However, bench to bedside translations are still infrequent as the process towards approval by regulatory bodies is protracted and costly, requiring both comprehensive in vitro and in vivo studies. In translational orthopaedic research, the utilisation of large preclinical animal models is a conditio sine qua non. Consequently, to allow comparison between different studies and their outcomes, it is essential that animal models, fixation devices, surgical procedures and methods of taking measurements are well standardized to produce reliable data pools as a base for further research directions. The following chapter reviews animal models of the weight-bearing lower extremity utilized in the field which include representations of fracture-healing, segmental bone defects, and fracture non-unions.

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Adolescents engage in many risk-taking behaviors that have the potential to lead to injury. The school environment has a significant role in shaping adolescent behavior, and this study aimed to provide additional information about the benefits associated with connectedness to school. Early adolescents aged 13 to 15 years (N = 509, 49% boys) were surveyed about school connectedness, engagement in transport and violence risk-taking, and injury experiences. Significant relations were found between school connectedness and reduced engagement in both transport and violence risk-taking, as well as fewer associated injuries. This study has implications for the area of risk-taking and injury prevention, as it suggests the potential for reducing adolescents' injury through school based interventions targeting school connectedness.

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We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

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This research paper aims to develop a method to explore the travel behaviour differences between disadvantaged and non-disadvantaged populations. It also aims to develop a modelling approach or a framework to integrate disadvantage analysis into transportation planning models (TPMs). The methodology employed identifies significantly disadvantaged groups through a cluster analysis and the paper presents a disadvantage-integrated TPM. This model could be useful in determining areas with concentrated disadvantaged population and also developing and formulating relevant disadvantage sensitive policies. (a) For the covering entry of this conference, please see ITRD abstract no. E214666.

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Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.

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Despite considerable success in treatment of early stage localized prostate cancer (PC), acute inadequacy of late stage PC treatment and its inherent heterogeneity poses a formidable challenge. Clearly, an improved understanding of PC genesis and progression along with the development of new targeted therapies are warranted. Animal models, especially, transgenic immunocompetent mouse models, have proven to be the best ally in this respect. A series of models have been developed by modulation of expression of genes implicated in cancer-genesis and progression; mainly, modulation of expression of oncogenes, steroid hormone receptors, growth factors and their receptors, cell cycle and apoptosis regulators, and tumor suppressor genes have been used. Such models have contributed significantly to our understanding of the molecular and pathological aspects of PC initiation and progression. In particular, the transgenic mouse models based on multiple genetic alterations can more accurately address the inherent complexity of PC, not only in revealing the mechanisms of tumorigenesis and progression but also for clinically relevant evaluation of new therapies. Further, with advances in conditional knockout technologies, otherwise embryonically lethal gene changes can be incorporated leading to the development of new generation transgenics, thus adding significantly to our existing knowledge base. Different models and their relevance to PC research are discussed.