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School nurses are uniquely situated for this role, as they understand the local environment in a school and can assess and reassess the needs of the faculty and staff.Intimate partner violence (IPV) is a common problem for women in the United States and is associated with symptoms of post-traumatic stress disorder (PTSD) as well as hazardous use of substances like alcohol and drugs. However, not all subtypes of IPV (i.e., physical, sexual, and psychological) are equally predictive of PTSD and hazardous substance use. Although previous research suggests that psychological IPV has the strongest relative effect on PTSD symptoms and substance use, there is less research on IPV subtypes' cumulative effects. In this study, we examined the relative and cumulative effects of physical, sexual, and psychological IPV on PTSD symptoms and hazardous substance use in a sample of women in the United States recruited via Amazon's Mechanical Turk (N = 793) using bootstrapped multiple regression and configural frequency analyses. Results suggest that physical IPV had the most pronounced influence (medium-large effect sizes) on substance use across women, but that the cumulative effects of all three IPV subtypes were most closely associated with diagnostic levels of both PTSD and substance use at the level of groups of women. These findings clarify and extend previous research on the differential effects of IPV subtypes and provide directions for future research and clinical intervention.

the most important way to control diabetes is to follow a preventive lifestyle and if a diabetic individual follows a preventive lifestyle which he or she has accepted. The main objective of the current study is to compare the factors affecting the lifestyle in patients suffering from Type II diabetes and the healthy individuals in Kermanshah City.

this study is based on a case-control design where using simple random sampling, 110 patients suffering from type II diabetes are selected as the case group and 111 healthy subjects among the companions of other patients are selected as the control group from the Center for Diabetics in Kermanshah City. The average age of the participants is





48.8





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11.0



. The questionnaires used for collecting the data included the following the demographic information questionnaire and the lifestyle questionnaire which covers diet, physical activity, coping with stress, and smoking. Software applications including STSTA14 and SPSS23 were used foreasing the tax for harmful foods, considering subsidies for healthy food products, and self-care of individuals can be effective.

healthy lifestyle including proper diet and athletic activity is effective in preventing type II diabetes. Accordingly, implementing policies in the urban transportation system such as providing a special lane for bikers in the cities, increasing the tax for harmful foods, considering subsidies for healthy food products, and self-care of individuals can be effective.

Metamodeling may substantially reduce the computational expense of individual-level state transition simulation models (IL-STM) for calibration, uncertainty quantification, and health policy evaluation. However, because of the lack of guidance and readily available computer code, metamodels are still not widely used in health economics and public health. In this study, we provide guidance on how to choose a metamodel for uncertainty quantification.

We built a simulation study to evaluate the prediction accuracy and computational expense of metamodels for uncertainty quantification using life-years gained (LYG) by treatment as the IL-STM outcome. We analyzed how metamodel accuracy changes with the characteristics of the simulation model using a linear model (LM), Gaussian process regression (GP), generalized additive models (GAMs), and artificial neural networks (ANNs). Finally, we tested these metamodels in a case study consisting of a probabilistic analysis of a lung cancer IL-STM.

In a scenario with low uncertainty in model parameters (i.e., small confidence interval), sufficient numbers of simulated life histories, and simulation model runs, commonly used metamodels (LM, ANNs, GAMs, and GP) have similar, good accuracy, with errors smaller than 1% for predicting LYG. With a higher level of uncertainty in model parameters, the prediction accuracy of GP and ANN is superior to LM. In the case study, we found that in the worst case, the best metamodel had an error of about 2.1%.

To obtain good prediction accuracy, in an efficient way, we recommend starting with LM, and if the resulting accuracy is insufficient, we recommend trying ANNs and eventually also GP regression.

To obtain good prediction accuracy, in an efficient way, we recommend starting with LM, and if the resulting accuracy is insufficient, we recommend trying ANNs and eventually also GP regression.The arrival of SARS-Co-V-2 (severe acute respiratory syndrome coronavirus 2) has brought not only the COVID-19 (coronavirus disease 2019) pandemic but also the development of a cluster of symptoms known as multisystem inflammatory syndrome in children (MIS-C). Information regarding the long-term implications of COVID-19 infections in children, as well as MIS-C, is scarce and is emerging on an almost daily basis. The purpose of this article is to provide an overview of the recent literature regarding COVID-19 and MIS-C, a Kawasaki-like inflammatory syndrome that developed in children around the same time the COVID-19 pandemic began. Because the school nurse monitors children across a variety of developmental domains, they are in a unique position to identify changes and notice long-term trends related to the health and development of children who contract both COVID-19 and MIS-C.Cost-effectiveness analysis, routinely used in health care to inform funding decisions, can be extended to consider impact on health inequality. Distributional cost-effectiveness analysis (DCEA) incorporates socioeconomic differences in model parameters to capture how an intervention would affect both overall population health and differences in health between population groups. In DCEA, uncertainty analysis can consider the decision uncertainty around on both impacts (i.e., the probability that an intervention will increase overall health and the probability that it will reduce inequality). Using an illustrative example assessing smoking cessation interventions (2 active interventions and a "no-intervention" arm), we demonstrate how the uncertainty analysis could be conducted in DCEA to inform policy recommendations. We perform value of information (VOI) analysis and analysis of covariance (ANCOVA) to identify what additional evidence would add most value to the level of confidence in the DCEA results. The analyses were conducted for both national and local authority-level decisions to explore whether the conclusions about decision uncertainty based on the national-level estimates could inform local policy. For the comparisons between active interventions and "no intervention," there was no uncertainty that providing the smoking cessation intervention would increase overall health but increase inequality. However, there was uncertainty in the direction of both impacts when comparing between the 2 active interventions. VOI and ANCOVA show that uncertainty in socioeconomic differences in intervention effectiveness and uptake contributes most to the uncertainty in the DCEA results. This suggests potential value of collecting additional evidence on intervention-related inequalities for this evaluation. We also found different levels of decision uncertainty between settings, implying that different types and levels of additional evidence are required for decisions in different localities.Major life events often challenge the core beliefs people hold about the world, which is a crucial cognitive process predictive of adjustment outcomes. Elections have been associated with physical and socioemotional responses, but what is unclear is whether core beliefs can be disrupted and what implication this disruption might have for well-being. In two studies, we examined the association between core beliefs disruption and well-being in the context of the 2018 U.S. selleck chemicals llc midterm election. In both studies, participants reported a small degree of disruption of core beliefs due to the election. In Study 1, a 14-day daily diary study spanning the weeks before and after the election, multilevel modeling on 529 daily reports revealed that greater disruption of core beliefs was associated with lower mean levels of life satisfaction and greater changes in positive and negative affect. In Study 2, a cross-sectional study conducted 40 days following the election, linear regression analyses on 767 adults aged 18-77 from all 50 states revealed that the disruption of core beliefs due to the midterm election was positively associated with current life satisfaction. The effect held when controlling for multiple confounding factors. These findings suggest that elections can trigger disruption of core beliefs, and this disruption may spill over to subjective well-being in the short term but may positively contribute to post-election adjustment.

Menopause is one of the natural phenomena in every woman's life. The transition phase gradually brings lots of changes in the life of women, both physically and mentally. In Nepal, these changes are often viewed as the symptoms of old age. This study aims to determine the prevalence of menopausal symptoms and their quality of life (QOL).

A descriptive cross-sectional study was conducted in a rural municipality of Jhapa district, Nepal, with study samples of 215 collected using purposive sampling technique. Semistructured questionnaire and MENQOL questionnaire were used for data collection. Descriptive (mean, standard deviation, frequency and percentage) and inferential statistics (t-test and ANOVA test) were used for data analysis. The confidence interval was taken as 95% and probability of significance at p < 0.05.

The study showed that the mean age of the respondents was 53.51 ± 4.42 years with the mean age at menopause being 47.18 ± 6.16 years. The most prevalent symptoms among postmenopausal womesocial. Presence of these symptoms certainly affects the QOL. Hence, effective awareness and education programme regarding the symptoms and ways to minimize those symptoms should be planned and provided both at individual and community levels.The feeding of animals on bodies after death - so-called post-mortem animal predation - may complicate autopsy interpretations when there has been removal of significant amounts of skin and tissues. An extreme situation which sometimes arises is the complete evisceration and/or consumption of all major cavity organs. Search of autopsy files at Forensic Science South Australia was undertaken for examples of this phenomenon. Although such a finding at autopsy may suggest the actions of larger animals such as dogs or sharks, it may also occur when groups of smaller animals, such as cats, act in concert. Complete loss of organs may also occur if significant insect activity accompanies decomposition. Empty body cavities may therefore result from of a wide variety of animal activities involving a range of species in quite different environments. A significant problem once organs have been removed or consumed is in identifying or excluding natural diseases or injuries that may have played a role in the lethal episode.