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Exploring the Experiences of Nursing Faculty Working with Standardized Patients in Simulation: A Mixed Methods Study
No full textNursing faculty in pre-licensure nursing programs are a vital component to simulation education, development, and implementation. With the ongoing challenge of the current healthcare climate, the lack of clinical sites and faculty shortages put high-fidelity simulation in the forefront of nursing education, being relied upon more than ever. To simulate the role of the patient in simulation education, there are two primary modalities that are utilized: manikins and standardized patients (SPs). While not a new approach, SP use in prelicensure nursing education is widely under-researched and the wealth of research surrounding the efficacy of simulation education for student learning does not fully encompass the perspective of the nursing faculty working along SPs in the simulated setting. Due to this significant gap and risk to clarity and standardization of simulation delivery, a mixed methods study was conducted to explore the experiences and perceptions of faculty who utilize standardized patients in simulation. This study aimed to answer the following research questions: What are the experiences of nursing faculty working with Standardized Patients in Undergraduate nursing simulations? What aspects of SP and faculty interaction are most likely to affect student learning outcomes in simulation
Cultivating Nursing Student Competency Through Serious Gaming Simulation-Enhanced Prebriefing
No full textProblem: Simulation is an effective teaching strategy for undergraduate nursing students, providing a safe environment for learning in a low-risk setting. However, students are not fully prepared to take full advantage of high-fidelity simulation activities. The purpose of this study was to examine the impact of serious gaming simulation-enhanced prebriefing on student competency and simulation effectiveness. Methodology: The study employed a quantitative, cross-sectional, quasi-experimental design using secondary data. Participants included undergraduate nursing students in a southern private university. The students were enrolled in the prelicensure nursing program and the obstetric or the transition to practice course. The control group received a traditional prebrief, high-fidelity simulation, and debrief while the intervention group received a serious gaming simulation-enhanced prebrief, high-fidelity simulation and debrief. Student competency was assessed using the valid and reliable Creighton-Competency Evaluation Instrument (C-CEI) while simulation effectiveness was measured by the Simulation Effectiveness Tool-Modified (SET-M). Data Analysis: Independent t-tests were run to compare the means of the SET-M and C-CEI total scale scores between study groups. MANOVAs was completed to examine the mean differences in C-CEI and SET-M subscale scores between the control and intervention groups. Although there were statistically significant outcomes with the clinical judgment and communication C-CEI subscales, the implications of these results are limited due to the small sample size and low reliability of the CCEI in this study. Implications: The results help to focus future research on the best methods to improve student performance during high-fidelity simulation and to demonstrate student competencies
Image Processing Techniques for Water Droplet Penetration Time and Contact Angle Estimation
No full textWater droplet behavior on soil surfaces plays a critical role in numerous environmental processes, including soil erosion, hydrological dynamics, and ecosystem health. Accurate characterization of soil water repellency, quantified by parameters such as water droplet penetration time (WDPT) and contact angles (WDCA), is essential for informed decision-making in agricultural management, forestry practices, and land-use planning. Despite the significance of these parameters, challenges exist in reliably estimating them due to the complex and dynamic nature of soil-water interactions. This thesis address challenges in estimating WDPT and WDCA, by leveraging state-of-the-art image processing techniques and machine learning algorithms. The research focuses on advancing our understanding of water droplet interactions with soil surfaces and developing accurate methods for estimating WDPT and contact angles. Specifically, the thesis explores the utilization of deep machine learning models, such as the Yolov8 instance segmentation model, for water droplet detection, followed by the application of various deep learning methods for WDPT and contact angle estimation. The methodology involves the collection of an extensive dataset comprising over 200 samples of water droplets interacting with different soil textures and types. Through rigorous experimentation and model training, the research achieves a remarkable accuracy of 90% in distinguishing between drowning and fully submerged droplets. Comparative analysis with existing techniques further validates the effectiveness of the proposed methodologies. For Water Droplet Penetration Time (WDPT) and Water Droplet Contact Angle (WDCA), the study demonstrates an error rate below 15% when compared to ground truth data, ensuring the reliability and precision of the approach in analyzing soil-water interactions. The findings of this study have significant implications for environmental science, hydrological modeling, and agricultural sustainability. By providing reliable tools for characterizing soil water repellency, the research contributes to enhancing environmental management practices and informed decision-making in various fields
Interpretable and Evidential Deep Learning for Medical Image Analysis
No full textAutomatic histopathological Whole Slide Image (WSI) analysis has been highlighted along with the advancements in microscopic imaging techniques, but manual examination and diagnosis of WSIs are time-consuming and tiresome. Recently, deep convolutional neural networks have succeeded in histopathological image analysis. Especially, Convolutional Neural Networks CNN models such as Inception and DenseNet have achieved effective performance. However, automatic histopathological WSI analysis still has significant drawbacks such as considering deep learning as black-box models, predicting disease independently on a small part of images (patch images) extracted from WSIs, limitations in predicting a single slide-based score for a patient, and capturing disease-specific morphology patterns (e.g., protein rearrangements and subtype morphology) from primary screening WSI images’ protein rearrangements. To address these gaps, I have developed three interpretable and evidential deep learning models: Deep-Hipo, HipoMap, and Deep-PATHO. My proposed model explains disease specific morphology patterns which were aligned with domain experts. In Deep-Hipo, I designed multi-scale receptive fields to simultaneously capture local information (20x patch) and global information (5x). Deep-Hipo achieved significant performance over state-of-the-art models by considering patch dependencies. The Histopathology representation Map (HipoMap) is a novel and generalized slide-score prediction framework for any CNN-based patch-wise pretraining models. HipoMap generates a slide-based prediction framework by generating one representation map for a WSI. My research shows that HipoMap can be extended to many applications such as cancer classification, survival prediction, survival analysis, and sub-type classification. Deep-PATHO is a novel deep-learning architecture that synchronizes morphology between local (High magnification) and global (Low magnification). Deep-PATHO has achieved significant performance in identifying complex morphological patterns of ALK rearrangements in WSI images
The Role of Cognitive Dysfunction in Late-Life Depression
No full textDepression is one of the most common psychiatric concerns in older adults. Because of the intersection of biological, emotional, social, and cognitive factors that are at play in depression, symptoms are often heterogeneous in presence and severity. In combination with the expected changes in cognitive abilities as one ages, late-life depression can be additive to these changes. The higher risks of neurodegenerative processes and vascular events in later life can cause, magnify, or accelerate cognitive decline. As such, individuals with late-life depression often present with a complex array of problems that can impact cognition and functioning, and thus complicate the implementation of traditional psychotherapies. Although treatment methods have been adapted to target late-life depression, they are often modifications of treatment approaches for depression in other age groups, rather than developments to directly address unique late-life depression presentations. This dissertation will investigate and discuss aspects of our understanding of the role of cognitive functioning in late-life depression, with the overarching goal of narrowing the focus of research and clinical practice to targeting shortcomings and improve late-life depression treatment. The three main aims of the dissertation are broadly, (1) identify how the scientific literature accounts for cognitive functioning in late-life depression psychotherapy research, (2) determine whether cognitive functioning predicts late-life depression psychotherapy treatment response, and (3) understand the barriers and facilitators to practical implementation of an adapted psychotherapy for late-life depression
Southern Nevada Regional Industrial Study
No full textRecognizing the ongoing need to diversify the Southern Nevada economy, in 2023 GOED commissioned Brookings Mountain West, the UNLV Center for Business and Economic Research, and the UNLV Transportation Research Center to evaluate how Southern Nevada can leverage its geography and connectivity to neighboring states and metros at the megapolitan level to pursue industrial opportunities in the face of shifting global supply chains, diminishing developable land, the need for efficient management of the regional water supply, and the availability of unprecedented federal resources to support clean energy development, manufacturing, electrification of transportation systems, and supply-chain resiliency.
The study builds on previous economic development reports, analyzes a wide range of economic data from Las Vegas and adjacent metros, and incorporates insights gleaned from background interviews with representatives from state and local governments, utilities, transportation agencies, and economic development organizations to identify industrial opportunities the region should pursue, infrastructure investments that are needed to support these opportunities, and policy and governance interventions to facilitate and fund regional industrial-based economic diversification
Using ChatGPT with Novice Arduino Programmers: Effects on Performance, Interest, Self-Efficacy, and Programming Ability
No full textA posttest-only control group experimental design compared novice Arduino programmers who developed their own programs (self-programming group, n =17) with novice Arduino programmers who used ChatGPT 3.5 to write their programs (ChatGPT-programming group, n = 16) on the dependent variables of programming scores, interest in Arduino programming, Arduino programming self-efficacy, Arduino programming posttest scores, and types of programming errors. Students were undergraduates in an introductory agricultural systems technology course in Fall 2023. The results indicated no significant (p \u3c .10) differences between groups for programming rubric scores (p = .50) or interest in Arduino programming (p = .50). There were significant differences for Arduino programming self-efficacy, (p = .03, Cohen’s d = 0.75) and Arduino posttest scores, (p = .03, Cohen’s d = 0.76); students in the self-programming group scored significantly higher on both measures. Analysis of students’ errors indicated the ChatGPT group made significantly (p \u3c .01) more program punctuation errors. These results indicated novice students writing their own programs developed greater Arduino programming self-efficacy and programming ability than novice students using ChatGPT. Nevertheless, ChatGPT may still play an important role in assisting novices to write microcontroller programs
The Cardiorespiratory Response while Nordic Walking vs. Regular Walking Among Middle-Aged to Older Adults
No full textTopics in Exercise Science and Kinesiology Volume 5: Issue 1, Article 6, 2024. Roughly five million deaths worldwide are accounted for by physical inactivity. Furthermore, there is a strong dose-response relationship between physical inactivity and all-cause mortality, cardiovascular health, and metabolic health. Recently, Nordic walking (NW) has been introduced as a mode of exercise where one can increase energy expenditure compared to regular walking (RW) due to increased engagement of upper body musculature using poles while walking. According to established findings, most work has been done in a laboratory which can interrupt natural NW mechanics. Therefore, this study\u27s purpose was to measure the cardiorespiratory and energy expenditure differences in NW and RW in a field setting. Twenty middle-aged and older adults participated in this study. The initial session included Nordic walking familiarization, 10-m gait speed test, and a peak oxygen uptake (VO2peak) test. The two exercise sessions consisted of either NW or RW on an indoor track for 30-min. All metabolic variables were measured via COSMED K5. A paired-sample t-test revealed a significant difference between NW and RW for %VO2peak values (p = .008), kcal· min-1 (p = .005), and total kcal expenditure (p = .001). No significant difference was found for preferred gait speed (p =.485) between NW and RW. NW elicited a higher %VO2peak, kcal· min-1, and total kcal expenditure compared to walking. In turn, this study agrees with previous research and supports the use of NW to increase energy expenditure to potentially improve one’s metabolic and cardiovascular health
Exploring the Mechanistic Trail Connecting Cellular Function, Health, and Athletic Performance With Phase Angle: A Review on the Physiology of Phase Angle and Exercise-Based Interventions
No full textTopics in Exercise Science and Kinesiology Volume 5: Issue 1, Article 7, 2024. Bioelectrical impedance analysis-derived phase angle (PhA) has been widely used in clinical and sports settings, as it is positively associated with health and fitness. However, what PhA is measuring at the cellular level has not been addressed, which limits our interpretation of PhA. The purpose of this review is to provide a roadmap, starting with the mechanistic link between the dielectric properties of mammalian cells and their physiological function. In simplistic terms, PhA measures cellular permittivity and electrical conductivity. These characteristics determine cellular health and function. This theory is the crux of how PhA relates to physiological function. One of the foundational assumptions is that PhA is affected by cellular membrane integrity. Intact cell membranes are essential for proper cellular function, namely cell-to-cell communication and intracellular signaling. This also relates to the quality of neuromuscular communication, or the ability of the neural system to control motor output, which accounts for the increased PhA values after exercise training. This paper summarizes the most recent reports of PhA in relation to exercise training and status, disease, age, and sex. Also, we offer future avenues of research that will help to understand how to best utilize and interpret PhA. By matching the relevant background information about cellular changes that occur with health or disease to PhA values, researchers and clinicians will better understand the assumptions when using bioelectrical impedance-derived PhA. Overall, this review provides practitioners with insight into what changes in PhA could mean in terms of cellular health and function
Introduction of the Anatomy Academy Program To Children in a Rural Elementary School
No full textChildren in rural communities experience health and education disparities. Early exposure to health promoting habits can positively impact future health habits. Healthcare providers who grew up in rural areas are more likely to practice in rural areas. Doctor of physical therapy students and physical therapists implemented Anatomy Academy, a service-learning program aimed at promoting healthy living and introducing healthcare occupations, to elementary students in a rural area as this program had previously only been implemented in urban areas. The Biomedical Institutional Review Board at the University of Nevada, Las Vegas approved this study. A 40-minute lesson was delivered weekly for seven weeks by four doctor of physical therapy students and two physical therapists to fourth grade children at a rural Nevada elementary school. A cohort study design was used to collect data from the children using a twenty-question survey. Incomplete or unmatched pre/post surveys were not included in the final analysis. Statistical analyses were performed using SPSS Version 27. Wilcoxon Signed Rank Tests were used to compare pre- and post-survey data among all participants. Where significant differences were found, descriptive statistics to determine the actual changes in survey responses were analyzed. The data analysis included 43 completed surveys and excluded 32 incomplete or unmatched surveys. Significant differences were noted in the subjective responses to “How much do you like to learn about anatomy?” (pre-score 60.5% favorable response, post-score 90% favorable response, p=.001), “Do you have an interest in becoming a healthcare worker?” (pre- 11.6% yes, 41.9% no, post-51.2% yes, 16.3% no, p=.003), and “How much screen time do you get per day?” (pre-48.8% \u3c 2 hours, post-62.8% \u3c 2 hours, p=.013). For objective responses, we noted significant increase in correct responses to the following questions: “Where is the first place digestion starts to occur?” (pre-32.6%, post-74.4%, p=.003), and “How many minutes per day should you and other children do physical activities?” (pre-23.3%, post-55.8%, p=.0004). Study participants reported increased interest in health care and increased knowledge of some anatomy and health habits content following Anatomy Academy. The study was limited to fourth grade students at a rural elementary school in Nevada, so results may not be generalizable to other areas or populations. Student reflections on their Anatomy Academy experiences were collected through a Qualtrics questionnaire after weeks one and seven to allow doctor of physical therapy students to expand on the professional and interpersonal growth obtained throughout their opportunity, while also tying their experiences to the American Physical Therapy Association core values. A Qualtrics questionnaire was administered to stakeholders of the elementary school to assist with examining intervention outcomes and Anatomy Academy program perceptions. Physical therapists and doctor of physical therapy students can provide children in rural communities with knowledge about health promotion and fitness through programs such as Anatomy Academy, possibly creating opportunities for future healthcare leaders in rural areas where healthcare providers are limited. Future research in other rural areas is warranted