Preventing Substance Use Disorder in Anesthesia Providers

Developing substance use disorder is considered one of the most serious occupational risk factors for anesthesia providers. The purpose of this project was to identify the prevalence and risk factors of substance use disorder within the anesthesia community and to signify the importance of early education and awareness to help prevent the development of substance use disorder through early education, identification, and awareness. The project consisted of an educational PowerPoint that was placed on Southern Illinois University Edwardsville’s (SIUE) wellness website within Black Board. The third-year nurse anesthesia students at SIUE were sent an email on how to access the PowerPoint along with a nine-question online evaluation based on the PowerPoint provided. From the evaluation, nurse anesthesia students demonstrated a need for education regarding substance use disorder within the profession. Anesthesia students also agree that information regarding substance use disorder should be included in the new student orientation. These results correlate closely with the new evidence that early education, early identification, and awareness are key factors in the prevention of developing substance use disorder in the anesthesia provider

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes’ model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes’ equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined

Validation and Calibration of Models for Reaction-Diffusion Systems

Space and time scales are not independent in diffusion. In fact, numerical simulations show that different patterns are obtained when space and time steps ($\Delta x$ and $\Delta t$) are varied independently. On the other hand, anisotropy effects due to the symmetries of the discretization lattice prevent the quantitative calibration of models. We introduce a new class of explicit difference methods for numerical integration of diffusion and reaction-diffusion equations, where the dependence on space and time scales occurs naturally. Numerical solutions approach the exact solution of the continuous diffusion equation for finite $\Delta x$ and $\Delta t$, if the parameter $\gamma_N=D \Delta t/(\Delta x)^2$ assumes a fixed constant value, where $N$ is an odd positive integer parametrizing the alghorithm. The error between the solutions of the discrete and the continuous equations goes to zero as $(\Delta x)^{2(N+2)}$ and the values of $\gamma_N$ are dimension independent. With these new integration methods, anisotropy effects resulting from the finite differences are minimized, defining a standard for validation and calibration of numerical solutions of diffusion and reaction-diffusion equations. Comparison between numerical and analytical solutions of reaction-diffusion equations give global discretization errors of the order of $10^{-6}$ in the sup norm. Circular patterns of travelling waves have a maximum relative random deviation from the spherical symmetry of the order of 0.2%, and the standard deviation of the fluctuations around the mean circular wave front is of the order of $10^{-3}$.Comment: 33 pages, 8 figures, to appear in Int. J. Bifurcation and Chao

Impact of a Novel Adaptive Optimization Algorithm on 30-Day Readmissions Evidence From the Adaptive CRT Trial

AbstractObjectivesThis study investigated the impact of the Medtronic AdaptivCRT (aCRT) (Medtronic, Mounds View, Minnesota) algorithm on 30-day readmissions after heart failure (HF) and all-cause index hospitalizations.BackgroundThe U.S. Hospital Readmission Reduction Program, which includes a focus on HF, reduces Medicare inpatient payments when readmissions within 30 days of discharge exceed a moving threshold based on national averages and hospital-specific risk adjustments. Internationally, readmissions within 30 days of any discharge may attract reduced or no payment. Recently, cardiac resynchronization therapy (CRT) devices equipped with the aCRT algorithm allowing automated ambulatory device programming were introduced. The Adaptive CRT trial demonstrated the algorithm’s safety and comparable outcome against a rigorous echocardiography-based optimization protocol.MethodsWe analyzed data from the Adaptive CRT trial, which randomized patients undergoing CRT defibrillation on a 2:1 basis to aCRT (n = 318) or to CRT with echocardiographic optimization (Echo, n = 160) and followed up these patients for a mean of 20.2 months (range: 0.2 to 31.3 months). Logistic regression with generalized estimating equation methodology was used to compare the proportion of patients hospitalized for HF and for all causes who had a readmission within 30 days.ResultsFor HF hospitalizations, the 30-day readmission rate was 19.1% (17 of 89) in the aCRT group and 35.7% (15 of 42) in the Echo group (odds ratio: 0.41; 95% confidence interval [CI]: 0.19 to 0.86; p = 0.02). For all-cause hospitalization, the 30-day readmission rate was 14.8% (35 of 237) in the aCRT group compared with 24.8% (39 of 157) in the Echo group (odds ratio: 0.54; 95% CI: 0.31 to 0.94; p = 0.03). The risk of readmission after HF or all-cause index hospitalization with aCRT was also significantly reduced beyond 30 days.ConclusionsUse of the aCRT algorithm is associated with a significant reduction in the probability of a 30-day readmission after both HF and all-cause hospitalizations. (Adaptive Cardiac Resynchronization Therapy Study [aCRT]; NCT00980057

The Interagency Process in Support & Stability Operations: Integrating and Aligning the Roles and Missions of Military and Civilian Agencies in Conflict and Post-Conflict Environments

This study addressed the support, stability, and reconstruction missions and tasks for the U.S. government in counterinsurgency warfare and suggests that interagency processes between civilian and military elements are in need of reform as a prerequisite for improving U.S. performance in complex counterinsurgencies. The project examined, assessed, and defined the nature of these problems in the context of historical case studies, policymaking, and current operations, especially in Iraq and Afghanistan, suggesting several ways to improve agency and interagency structures, as well as the education and training of core interagency civilian and military professionals. The findings were presented at a conference on the topic, hosted by the Bush School and the Strategic Studies Institute of the U.S. Army

RNA Viral Community in Human Feces: Prevalence of Plant Pathogenic Viruses

The human gut is known to be a reservoir of a wide variety of microbes, including viruses. Many RNA viruses are known to be associated with gastroenteritis; however, the enteric RNA viral community present in healthy humans has not been described. Here, we present a comparative metagenomic analysis of the RNA viruses found in three fecal samples from two healthy human individuals. For this study, uncultured viruses were concentrated by tangential flow filtration, and viral RNA was extracted and cloned into shotgun viral cDNA libraries for sequencing analysis. The vast majority of the 36,769 viral sequences obtained were similar to plant pathogenic RNA viruses. The most abundant fecal virus in this study was pepper mild mottle virus (PMMV), which was found in high concentrations—up to 10(9) virions per gram of dry weight fecal matter. PMMV was also detected in 12 (66.7%) of 18 fecal samples collected from healthy individuals on two continents, indicating that this plant virus is prevalent in the human population. A number of pepper-based foods tested positive for PMMV, suggesting dietary origins for this virus. Intriguingly, the fecal PMMV was infectious to host plants, suggesting that humans might act as a vehicle for the dissemination of certain plant viruses

Conceptualizing and Treating Social Anxiety in Autism Spectrum Disorder: A Focus Group Study with Multidisciplinary Professionals.

BACKGROUND: Individuals who have autism spectrum disorders (ASD) commonly experience social anxiety (SA). Disentangling SA symptoms from core ASD characteristics is complex, partly due to diagnostic overshadowing and co-occurring alexithymia. Causal and maintaining mechanisms for SA in ASD are underexplored, but it is feasible that there is an ASD specificity to the clinical presentation, with implications for the development of targeted treatments. METHODS: Five focus groups were conducted with multidisciplinary professionals to investigate their perspectives about, and approaches to, working with individuals with ASD and SA. Data were analysed thematically. RESULTS: Data analysis revealed two overarching themes: conceptualizing SA in ASD and service provision. Our results suggest that adaptations to service provision are pertinent, so as to accommodate inherent impairments that can mediate assessment and intervention. CONCLUSIONS: Future studies should establish how aspects of the care pathway can be improved for individuals with ASD and SA

Design and validation of the Health Professionals' Attitudes Toward the Homeless Inventory (HPATHI)

BACKGROUND: Recent literature has called for humanistic care of patients and for medical schools to begin incorporating humanism into medical education. To assess the attitudes of health-care professionals toward homeless patients and to demonstrate how those attitudes might impact optimal care, we developed and validated a new survey instrument, the Health Professional Attitudes Toward the Homeless Inventory (HPATHI). An instrument that measures providers' attitudes toward the homeless could offer meaningful information for the design and implementation of educational activities that foster more compassionate homeless health care. Our intention was to describe the process of designing and validating the new instrument and to discuss the usefulness of the instrument for assessing the impact of educational experiences that involve working directly with the homeless on the attitudes, interest, and confidence of medical students and other health-care professionals. METHODS: The study consisted of three phases: identifying items for the instrument; pilot testing the initial instrument with a group of 72 third-year medical students; and modifying and administering the instrument in its revised form to 160 health-care professionals and third-year medical students. The instrument was analyzed for reliability and validity throughout the process. RESULTS: A 19-item version of the HPATHI had good internal consistency with a Cronbach's alpha of 0.88 and a test-retest reliability coefficient of 0.69. The HPATHI showed good concurrent validity, and respondents with more than one year of experience with homeless patients scored significantly higher than did those with less experience. Factor analysis yielded three subscales: Personal Advocacy, Social Advocacy, and Cynicism. CONCLUSIONS: The HPATHI demonstrated strong reliability for the total scale and satisfactory test-retest reliability. Extreme group comparisons suggested that experience with the homeless rather than medical training itself could affect health-care professionals' attitudes toward the homeless. This could have implications for the evaluation of medical school curricula

Who Sets the Agenda? Analyzing Key Actors and Dynamics of Economic Diversification in Kazakhstan Throughout 2011–2016

This contribution attempts to answer the key question: Who sets the agenda for economic diversification in the context of Kazakhstan? This question remains critical in current scholarly debates. Although Kazakhstan, a young post-Soviet developing nation, has received fair scholarly attention with regard to the agenda setting stage of the policy cycle, the existing literature has yet failed to (1) empirically establish who actually sets the agenda for a certain policy issue and (2) employ the Internet research methods. This paper seeks to fill these gaps. The literature review of Kazakh-specific agenda setting publications suggests that among the major actors, the government tends to exert predominant influence, though other actors may also play a role, for example, media and academia. This research is driven by Internet penetration rate data and focuses on the period from January 2011 until December 2016. The findings lead to two key conclusions. First, think tanks seem to set the government agenda for economic diversification policy in Kazakhstan. Second, the government, while exhibiting the larger agenda setting magnitude vis-à-vis the other actors, shapes the subsequent debates as measured by the number of relevant references in media, think tanks, and academic publications. This research seeks to contribute to existing agenda setting theories in the Internet era by defining the most important actor(s), specifically in the Kazakh context based on longitudinal dynamics in attention