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Enhancing Transgender Care During the Perioperative Period Through Education for Certified Registered Nurse Anesthetists
No full textUB SON, DNP Research ProjectHealth disparities and discrimination in health care experienced by the transgender population are attributed, in part, to limited knowledge and sensitivity among healthcare providers. This Doctor of Nursing Practice (DNP) project sought to develop and evaluate the impact of an evidence-based online transgender health educational module for CRNAs. Campinha-Bacote’s Process of Cultural Competence in Delivery of Health Care Services model served as the theoretical framework for this DNP project. A non-experimental, quantitative longitudinal research design was applied to deliver a transgender-specific educational module and conduct pre-and post-educational surveys to measure its impact on practicing CRNAs. Members of the New York State Association of Nurse Anesthetists (NYSANA) were recruited for participation, of which a sample of 32 CRNAs was obtained. Data revealed a lack of trans-specific education among CRNAs, with only 10.5% reporting previous exposure to such content. Paired t-tests revealed statistically significant changes in mean scores on several survey items, reflecting more positive attitudes and beliefs, improved clinical and cultural competence, and an overall positive perception of the educational module and its relevance to CRNA practice. While transgender-specific education is not readily included in student or professional development activities, findings implicate that the integration of this material into such programs may be valuable in increasing cultural and clinical competence among Certified Registered Nurse Anesthetists (CRNAs), thus enhancing the perioperative care of the transgender population. Future recommendations align with the current body of evidence, and support integration of transgender specific educational content into professional development activities for CRNAs
Evaluating Nurses’ Self-Efficacy related to In Situ Mock Code Simulation Training
No full textUB SON, DNP Research ProjectBackground and Significance: Hospital nurses need skills and confidence to take action during codes. In situ mock codes (ISMCs) can improve nursing confidence during emergency situations. Purpose, Aims, and Objectives: This study’s purpose was to identify knowledge gaps in ISMC training to enhance future ISMC education and improve nurses’ self-efficacy during code situations. Theoretical Framework: Albert Bandura’s Self-Efficacy Theory emphasizes need for effective learning to promote improved self-efficacy perceptions of task performance. Methods and Design: This study was a secondary data analysis from survey results of 311 nurses using the Mock Code Self-Efficacy Survey (MCSES),a validated measurement tool. Descriptive and inferential statistics were used to describe nurse self-efficacy of 12 code skills. Differences in self-efficacy between medical-surgical (MS) and critical care (CC) nurses were examined and weak clinical areas identified. Results: CC nurses had increased confidence in 11 of 12 clinical skills when compared to MS nurses. The only skill with no difference in confidence was recognizing asystole. Nurses with past mock code experience (PMCE) had more confidence in all 12 clinical skills than those without. In all comparisons, dysrhythmia identification requiring defibrillation and identifying the first code medication administered were the weakest. Conclusion: Overall, CC nurses and nurses with PMCE had higher confidence levels in performing the 12 clinical skills. Future Implications: Lower confidence levels were discovered in MS nurses and nurses with less PMCE. Performing ISMCs routinely on MS units can increase nurses’ experience and confidence in code situations
Continuous Glucose Monitoring Systems and Type 2 Diabetic Control
No full textUB SON, DNP Research ProjectBackground: In the United States, uncontrolled T2D has significant financial expenditure and can lead to multiple health complications for diabetic patients when left unaddressed. Standardizing a method of glucose monitoring for adults with T2D can help reduce overall national healthcare costs, improve patient morbidity, mortality rates, and quality of life, reduce monitoring noncompliance, and improve patient outcomes. Despite numerous evidence-based benefits, limited use of CGMS among adult T2D patients currently exists. Further research is needed to assess CGMS efficacy among adult TD2 patients. Purpose: The purpose of this Doctor of Nursing Practice (DNP) project was to conduct a retrospective chart review to assess the efficacy of continuous glucose monitoring systems (CGMS) in reducing A1C levels in adult patients with type 2 diabetes (T2D) in a Western New York (WNY) endocrinology center. Methods: A retrospective chart review was performed on 57 adult T2D patients from March 5th, 2021 through March 19th, 2021. Inclusion criteria included adults older than 18 years old who are T2D for greater than 12 months and have been prescribed a CGMS for at least 6 months. The Diffusion of Innovation theory was the theoretical framework used to guide the DNP project. Results: Results of this project revealed a mean reduction in A1C levels from 8.2% to 7.7% after application of the CGMS on the T2D. Conclusions and Implications: Findings resulting from this DNP project can contribute to the existing body of research supporting the benefits of utilizing CGMS for adult patients living with T2D and the need to implement CGMS as part of standardized diabetic care
The Experience of Second Victim Stress and Perceived Support Needs among Certified Registered Nurse Anesthetists in Upstate New York
No full textUB SON, DNP Research ProjectBackground and Significance: Certified Registered Nurse Anesthetists (CRNAs) are exposed to events that may trigger distress and second victim phenomenon. Literature shows untreated second victim symptoms lead to increased employment turnover, absenteeism, and decreased patient safety. Support systems mitigate these outcomes. Purpose, Aims and Objective: To evaluate the experience of second victim stress and perceived support needs among CRNAs at one nurse anesthesia program’s approved clinical sites. Theoretical Framework: Lazarus and Folkman’s Theory of Stress and Coping. Methods and Design: Across-sectional survey design was submitted to over 300 CRNAs. The Second Victim Experience and Support Tool (SVEST)with supplemental questions was distributed via email link to SurveyMonkey. Quantitative data was analyzed using SVEST guidelines and the Statistical Package for the Social Sciences (SPSS)version 27. Open-ended responses were descriptively reviewed. Protection of Human Rights and Ethical Considerations: Data was collected with consent and stored on a password-protected computer. Participation was voluntary, anonymous, and confidential. Results:19 of 29 completed responses reported at least one domain of distress. Distressed and Non-distressed groups showed significant difference in psychological and physical distress, turnover intention, and desired support options. No distress correlated with the anesthesia care team (ACT) model. Conclusions: CRNA second victim distress is prevalent and increases employment turnover. Debriefing with peers, having a designated location to recompose, and free counseling services are among desired support services. Future Implications and Recommendations: CRNA-specific support preferences are definable and should guide support efforts. Future research should evaluate CRNA-specific stressors
Structure, Function, and Inhibition of Aerobactin Biosynthesis from Hypervirulent Klebsiella pneumoniae
No full textPh.D.Since it was initially described in the mid-1980s in the Asian Pacific Rim, a hypervirulent pathotype of Klebsiella pneumoniae (hvKP) has disseminated throughout the globe. In contrast to classical opportunistic strains of Klebsiella pneumoniae, hvKP is able to cause serious life-threatening infections in previously healthy individuals in the community. Recent reports have confirmed fears within the medical community that the convergence of multi-drug resistant and hypervirulent KP pathotypes has led to the evolution of a highly transmissible, drug resistant, and virulent "super bug." Contemporary investigations toward understanding the enhanced virulence of hvKP strains have highlighted the importance of the biosynthesis of the siderophore aerobactin. Siderophores are small molecule iron-chelators that allow bacteria to assimilate sufficient quantities of this vital nutrient in the often severely iron-limited host environment. With an ever-increasing demand for novel therapeutic approaches for treating Gram-negative infections, we hypothesized aerobactin could be a viable "antivirulence" target for the treatment of infections with hvKP and other pathogens that rely on this siderophore. The research presented herein focused on three general topics: (1) demonstrating the function of the enzymes required to biosynthesize aerobactin, (2) characterizing the structure of the aerobactin synthetase enzymes IucA and IucC, and (3) the developing a high-throughput screening platform for identifying novel small-molecule inhibitors of aerobactin biosynthesis. To lay the foundation, the aerobactin biosynthetic pathway was first functionally demonstrated in vitro using purified enzymes. X-ray crystallography and solution scattering analyses were employed to structurally characterize IucA and IucC, which were combined with a number of biochemical studies to propose a molecular catalytic mechanism for these enzymes. Finally, leveraging our functional and structural knowledge of IucA, a high-throughput biochemical assay was developed and employed to screen over 110,00 compounds for antagonism of IucA catalysis; identifying a number of inhibitors with in vitro activity at low-micromolar concentrations.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Knowing the Uterus: The Role of Obstetrics, Gynecology, and Abortion in the Professionalization of American Medicine, 1880-1920.
No full textPh.D.Historians of women's health have long discussed why, starting in the nineteenth century, women increasingly entrusted physicians, who were mostly male, with caring for their reproductive and sexual health and why, by the first quarter of the twentieth century, physicians had become indispensable to this care. In this dissertation I argue that between the 1880s and 1920s physicians integrated obstetrics and gynecology in every step of their development as a profession. Physicians operating medical schools incorporated obstetrics and gynecology into the education of medical students, making sure students practiced delivering a child before they graduated. Leaders of hospitals supported the establishment of nursing schools, not only to have educated staff taking care of patients but also to train nurses as chaperones for obstetrical and gynecological patients. Physicians also developed gynecological and obstetrical treatments that set them apart from other practitioners. To reduce the number of patients developing puerperal fever, obstetricians developed post-partum treatments aimed at preventing infection, which helped improve physicians' reputation as assistants in childbirth. Gynecologists standardized dilation and curettage, which remained the leading technique to clear the uterus well into the twentieth century. Dilation and curettage allowed physicians to perform abortions as well as treat spontaneous miscarriages and intentional abortions that had not been completed. Taking care of obstetrical and gynecological patients – which included performing abortions – was an integral part of physicians' general practice and led to more patients trusting them in these fields.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Studying FAQs Through a Magnifying Lens: New Results in Theory and Practice
No full textPh.D.Abo Khamis et. al defined and studied the FAQ (Functional Aggregate Query) problem, which encompasses well-studied questions in (seemingly) disparate areas like joins on databases, exact inference on probabilistic graphical models (PGMs) and matrix-chain vector multiplication. They presented an algorithm InsideOut for computing exact inference queries on PGMs that is asymptotically faster than existing algorithms that typically optimize on a well-studied notion called the treewidth. This leads to many open questions...This thesis makes progress on all these three questions, answering them in affirmative and in the process, extends the study of FAQs in three major directions in both theory and implementation—computation over general vector spaces, distributed computation and implementation.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.**The work in this thesis was supported by NSF grants CCF-1319402, 1763481, 171734 and their support is gratefully acknowledged
Optimal Traffic Flow Control Strategies, on a Lane Group- and Vehicle-Based Level, at Freeway Lane-Drops under the Environment of Connected and Automated Vehicles
No full textPh.D.The research of the current dissertation consists of two main parts. The first part of this dissertation's research develops optimal variable, lane group-based, speed limits for traffic control at freeway lane-drop areas (e.g. work zones). The proposed approach uses the microscopic traffic simulation model VISSIM, along with a calibrated and validated macroscopic traffic flow model METANET, to develop the optimal speed limits. A multi-objective optimization framework is adopted whereby the model primarily seeks to improve traffic safety, by reducing the average number of stops, while taking other objectives, such as the average travel time and throughput, into consideration. For optimization, the heuristic, biologically inspired, optimization technique, known as Particle Swarm Optimization (PSO), is utilized, and the ε-constraint method is adopted to allow for considering multiple objectives in the optimization process. The proposed traffic control strategy is then evaluated for a hypothetical freeway lane drop area under a real-world congested traffic scenario. The research findings show that the proposed lane group-based control strategy outperforms other variable, link-based, speed limits, reported in the literature. The reduction in the average number of stops reached up to nearly 50 percent with respect to the base case during the congested traffic situations. This was achievable, while avoiding significant deteriorations in the values of the average travel time and the vehicle throughput (the reductions were constrained in our study to at most 10 percent difference with respect to the base case). The second part of this dissertation’s research develops an optimal, real-time and adaptive control algorithm for helping a Connected and Automated Vehicle (CAV), navigate a freeway lane-drop site (e.g. work zones). The proposed traffic control strategy is based on the Deep Q-Network (DQN) Reinforcement Learning (RL) algorithm, and is designed to determine the driving speed and lane-change maneuvers that would enable the CAV to go through the bottleneck, with the least amount of delay. The DQN RL agent was trained using the microscopic traffic simulator VISSIM, where the learning focused on how the CAV may be able to optimally maneuver the lane drop site while driving as close as possible to the freeway speed limit. VISSIM was also used to compare the performance of the DQN-controlled AV, as opposed to a human-driven vehicle with no intelligent control, in terms of the driving speed or travel time needed to traverse the lane drop site, under a congested, real life-like traffic scenario. The research findings demonstrate the promise of DQN RL in allowing the CAV to intelligently and optimally navigate through the lane drop site. On the scenario for which the agent was trained, the reduction in the CAV travel time was around 96 percent with respect to the base case. For validation and stability purposes, several experiments with different random seeds were carried out. The reductions in the mean and standard deviation of the DQN-controlled CAV travel times were 30.91 and 61.43 percent respectively compared to the base case. Further experiments with higher input demands and different configuration were implemented and again on average the DQN RL agent showed a better and more stable performance in terms of the travel time compared to the base case.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
The Investigation of the Binding Affinity of Enterobactin Toward Metal Ions via Density Functional Theory (DFT) Calculations
No full textM.S.Enterobactin (Ent) is a natural product siderophore that can transport iron in bacteria with a very large stability constant of ferric-enterobactin of ~ 1049. In order to understand the ability of Ent to form metal-Ent complexes, we investigated formation equilibria between M-Ent and hexa-aquo M(H2O)6 complexes, with di-valent and tri-valent metal ions such as Fe3+, Fe2+, Cu2+, Co2+ using density function theory (DFT) computation. Equilibria energetics were obtained from the DFT energies of optimized M-Ent complexes in the gas phase and their solvation energies determined with a polarizable continuum model (CPCM) of the aqueous phase gas. We also investigated equilibria between Ent and ethylenediaminetetraacetic acid (EDTA) as the complexing agent. We found good agreement with the well-accepted Irving-Williams scale for metal ion complexation. We also investigated the effect of pH on the protonation states of Ent during complexation. Molecular modeling is a powerful approach to study trends in metal ion complexation.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*
Modeling Daily Ambient Air Pollution Using Community Multiscale Air Quality (CMAQ) System
No full textPh.D.Fine particulate matter (PM2.5) is a complex mixture of particles originating from anthropogenic aerosols and natural emission sources that can cause serious adverse health effects. Most health studies have estimated human exposures to PM2.5 using ground observations despite their limited spatial and temporal coverage. Satellite aerosol optical depth (AOD) has been increasingly used as a proxy variable to sparse ground observations, but the availability of satellite AOD is restricted by physical conditions. More importantly, neither ground PM2.5 observations nor satellite AOD-based model predictions can distinguish PM2.5 emanating from different emission sources. The Community Multiscale Air Quality (CMAQ) model has the potential to fill these gaps by providing spatially wall-to-wall, temporally continuous, and deterministic estimations of source-specific PM2.5 concentrations. However, CMAQ model outputs may be subject to systematic biases and uncertainties arising from error-prone inputs and imperfect parameter settings, such as horizontal grid resolution and domain size. This dissertation aims to determine the optimal parameter settings of CMAQ models for PM2.5 predictions and to improve the accuracy of CMAQ-modeled source-specific PM2.5 predictions for health impact assessments. The objectives were achieved through the following three studies: (1) investigation of the effect of the CMAQ grid resolution on PM2.5-related health impact assessments; (2) assessment of the influence of the CMAQ domain size on regional PM2.5 predictions; (3) calibration of CMAQ-based source-specific PM2.5 predictions for uncertainty-aware health impact assessments. More specifically, the first study was designed to investigate the uncertainty of CMAQ prediction accuracy associated with two horizontal grid resolutions of 4 km and 12 km and to assess their impacts on human health studies. The findings showed that CMAQ model simulation at 12 km resolution with further calibration and/or downscaling is a viable option for capturing small-scale within-city variations of PM2.5 concentrations. The second study presented an approach for CMAQ model uncertainty assessment with respect to domain size and reported the spatio-temporal variations of CMAQ model performance over two study domains: a relatively small domain and a large domain. The results suggested that the overall model performance was better for CMAQ simulations with a large domain relative to the smaller domain. In the third study, I proposed a two-stage calibration approach as a means of adjusting biases in CMAQ-based source-specific PM2.5 predictions and demonstrated its application to wildland fire-specific PM2.5 estimations over the eastern United States in 2014. Based on the findings, I concluded that the proposed calibration strategy could provide reliable wildland fire-specific PM2.5 predictions and health burden estimates to support policy development for reducing fire-related risks.**To request an accessible version of the file(s) associated with this item, contact [email protected]. Please include the item's persistent URL [http://hdl.handle.net/. . .] in your request.*