967 COVID READY Study: Cross-Sectional Survey of Medical Students Volunteering During the Coronavirus Pandemic (COVID-19) In the United Kingdom

Introduction We aimed to identify the willingness, attitudes, and practice of medical students towards volunteering in a clinical capacity during the COVID-19 pandemic. Method We distributed a cross-sectional survey from 2/5/2020 to 14/6/2020 to all medical students at UK medical schools. Results A total of 1145 medical students from 36 medical schools completed the questionnaire. 82.7% of students were willing to volunteer, but only 34.3% had volunteered. The strongest predictors of willingness to volunteer on multiple linear regression were the beliefs that volunteering to work would benefit their medical education (estimate=0.35±0.03, adjusted P < 0.001) and that they would have a positive impact (estimate=0.33±0.03, adjusted P < 0.001). The majority of students were willing to take up a clinical role and were confident in having the necessary skills, but there was a discrepancy between the role’s students were comfortable performing and those they were assigned. Thematic analysis of the issue’s students would face when volunteering identified five themes: safety, professional practice, pressure to volunteer, finances and logistics, and education. Conclusions This study identifies areas for consideration from those responsible for workforce planning, healthcare provision, and student safety. We provide recommendations to facilitate a volunteering process that is safer for students, staff, and patients.

Applying a Delphi-Type Approach to Estimate the Adaptation Cost on Agriculture to Climate Change in Cyprus

Agriculture is highly dependent on climate change, and Cyprus especially is experiencing its impacts on agricultural production to a greater extent, mainly due to its geographical location. The adaptation of farming to the effects of global climate change may lead to the maximization of agricultural production, which is an important and desirable improvement. The main aim of this paper is to rank and quantify the impacts of climate change on the agricultural sector of Cyprus, through a multi-round Delphi survey seeking a consensus agreement in a group of experts. A multidisciplinary group of 20 experts stated their willingness-to-pay for various impacts of climate change. By applying this method, the individual impacts of climate change on crop production and water resources were brought into the modeling effort on equal footing with cost values. The final cost impact estimate represents the total estimated cost of climate change in the agricultural sector. According to the results, this cost reaches EUR 25.08 million annually for the agricultural sector, and EUR 366.48 million for the whole country. Therefore, it is expected that in the seven-year programming period 2014–2020 the total cost of climate change on agriculture ranges from EUR 176 to EUR 2565 million. The most significant impacts are due to the increasing level of CO2 in the atmosphere and the burden of biodiversity and ecosystems.

Drop impact estimate at cutting speed growth, force characteristics upon regenerative character of tool vibration

Revealed in numerous investigations a phenomenon connecting a cutting force drop at cutting speed growth effects considerably cutting dynamics. In the paper there is considered a dynamics of cutting taking into account the regenerative origin of tool vibrations with the estimate of cutting force changes impact upon vibrations. The results obtains may serve as a basis for a cutting mode choice in machine-tools of a lathe group.

Socio-Demographic Variation, Perceived Oral Impairment and Oral Impact on Daily Performance among Children in Saudi Arabia

Background: This study aimed to describe the oral impact (estimate, severity, frequency) on daily performance (e.g., eating, speaking) and identify the potential perceived oral impairment(s) and socio-behavioral factors associated with oral impact, namely presence or absence of oral impact, among children aged 9–12 years old in Al-Madinah Al-Munawwarah, Saudi Arabia. Methods: A cross-sectional convenience sample of 186 children aged 9–12 years old was recruited. Sociodemographic characteristics, oral health-related behaviors, and perceived oral impairments (e.g., caries, toothache) were obtained from participants. The validated Arabic Child Oral Impact on Daily Performance (C-OIDP) inventory was used to assess oral impacts. Sample descriptive statistics and multivariable logistic regressions modeling the association between C-OIDP and explanatory variables were performed. Results: The mean (±SD) age of the children was 10.29 ± 1.24 years, 66.4% were from public schools, and 52% were females. At least one C-OIDP was reported by 78% of the participants. The mean C-OIDP score was 2.27 ± 1.99. Toothache was reported as a perceived impairment for almost all oral impacts and was the strongest predictor of C-OIDP. Low father income was negatively associated with C-OIDP (odds ratio (OR) = 0.24, 95% confidence interval (CI) = 0.10–0.62). Females had significantly higher odds of reporting C-OIDP than males. Conclusions: In this convenience sample, a high percentage of children aged 9–12 years old reported C-OIDP, which was linked to oral impairment and socio-demographic factors. Further studies, however, are required to explore the clinical, behavioral, and sociodemographic factors in relationship to C-OIDP among Saudi children in a representative sample.

Strengthening the Research Base That Informs STEM Instructional Improvement Efforts: A Meta-Analysis

We present results from a meta-analysis of 95 experimental and quasi-experimental pre-K–12 science, technology, engineering, and mathematics (STEM) professional development and curriculum programs, seeking to understand what content, activities, and formats relate to stronger student outcomes. Across rigorously conducted studies, we found an average weighted impact estimate of +0.21 standard deviations. Programs saw stronger outcomes when they helped teachers learn to use curriculum materials; focused on improving teachers’ content knowledge, pedagogical content knowledge, and/or understanding of how students learn; incorporated summer workshops; and included teacher meetings to troubleshoot and discuss classroom implementation. We discuss implications for policy and practice.

Adaptive Localization for the Ensemble-Based Observation Impact Estimate Using Regression Confidence Factors

The goal of this study is to improve an ensemble-based estimation for forecast sensitivity to observations that is straightforward to apply using existing products of any ensemble data assimilation system. Because of limited ensemble sizes compared to the large degrees of freedom in typical models, it is necessary to apply localization techniques to obtain accurate estimates. Fixed localization techniques do not guarantee accurate impact estimates, because as forecast time increases the error correlation structures evolve with the flow. Here a dynamical localization method is applied to improve the observation impact estimate. The authors employ a Monte Carlo “group filter” technique to limit the effects of sampling error via regression confidence factor (RCF). Experiments make use of the local ensemble transform Kalman filter (LETKF) with a simple two-layer primitive equation model and simulated observations. Results show that the shape, location, time dependency, and variable dependency of RCF localization functions are consistent with underlying dynamical processes of the model. Application of RCF localization to ensemble-estimated impact showed marked improvement especially for longer forecasts and at midlatitudes, when systematically verified against actual impact in RMSE and skill scores. The impact estimates near the equator were not as effective because of large discrepancies between the RCF function and the localization used at assimilation time. These latter results indicate that there exists an inherent relationship between the localization applied during the assimilation time and the proper localization choice for observation impact estimates. Application of RCF for automatically tuned localization is introduced and tested for a single observation experiment.

Finding legitimacy for the role of budget impact in drug reimbursement decisions

Objectives:Research has shown that effectiveness, cost-effectiveness, and severity of illness each play a role in drug reimbursement decisions. However, the role of budget impact in such decisions is less obvious. Policy makers almost always demand a budget impact estimate yet seem reluctant to formally include budget impact as a rationing criterion. Health economists even reject budget impact as a legitimate criterion. For these reasons, it is important to examine its use in rationing decisions, and rationales underlying its use.Methods:We trace several rationales supporting the use of budget impact through a literature review, supplemented by semistructured interviews with eleven key stakeholders involved in drug reimbursement decisions in the Netherlands.Results:Budget impact arguments are used in certain instances, although policy makers appear uncomfortable with its use because well described rationales still are lacking. In addition, we identify the following rationales to support budget impact as a rationing criterion: opportunity costs, loss aversion, uncertainty and equal opportunity.Conclusions:Budget impact plays a role in drug reimbursement decisions and has rationales to support its use. However, policy makers do not easily admit that they consider budget impact and are even reluctant to explicitly use budget impact as a formal criterion. A debate would strengthen the theoretical foundation of budget impact as a legitimate criterion in the context of drug reimbursement decisions. Such discussion of budget impact's role will also enhance policy-makers' accountability.