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Activating Urban Space for Movement and Joy: a curated journey
Get PDFIn today’s world of sedentary work and study, movement is more important than ever for both our bodies and our minds. These exhibit panel designs explore how public space can be a catalyst for physical wellbeing, creativity, and joy. Featuring a series of photo-based display panels, the exhibit showcases images of dance and movement in public spaces, captured and curated to highlight the often-overlooked role of urban design in supporting health. The exhibit includes reflections on how movement—when thoughtfully integrated into public life—can reduce stress, spark joy, and foster community. Complementing the photography is a set of movement instructions designed to promote wellness through simple, everyday physical activity. “Activating Urban Space for Health and Movement” invites reflection and action, centering movement as a vital part of how we live, learn, and thrive.
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Closing racial and ethnic disparity gaps in pediatric asthma follow up care - A quality improvement initiative
Get PDFABSTRACT
Closing racial and ethnic disparity gaps in pediatric asthma follow up care - A quality improvement initiative
Ayodele Ayeko
Introduction/Background: Inadequate management of asthma significantly contributes to poor asthma control, poor quality of life (QOL), and high hospitalization rates among pediatric patients. The Global Initiative for Asthma (GINA) guidelines offer recommendations designed to enhance asthma control and improve the quality of life for those affected (2015), including recommendations for close follow up care. At WVU Medicine Children’s Hospital (WVUMCH), insufficient asthma control has been associated with lower clinic follow-up rates and an increase in hospitalization. Although educational initiatives aimed at improving asthma management during hospital stays were implemented, the clinic follow-up attendance remained low among children from racial and ethnic minority groups. Staff expressed concerns regarding potential cultural barriers that might hinder access to care.
Purpose: This Doctor of Nursing Practice (DNP) project is a quality improvement initiative, aimed to optimize asthma management and increase the frequency of follow-up visits through a telephone intervention led by a registered nurse for children with asthma who experience racial and ethnic disparities at WVUMCH. The objectives were to 1) Provide a pilot telephone call intervention for patients of African American race/ethnicity and evaluate success for effectiveness and sustainability. 2) Reduce the no-show rate at pulmonary clinic visits by 25% in African American asthma patients’ post hospitalization.
Intervention: The six-month project intervention aimed to follow up with asthma patients from ethnic minority groups, specifically African Americans, through telephone calls after discharge.
Methods: Participant data was extracted from the electronic medical record into the Tableau database by hospital staff. The nursing telephone intervention was executed and measured for time spent to assess feasibility of sustainability. Participants were tracked by the nurse to evaluate follow-up attendance at pulmonary appointments. Deidentified data was used to analyze pulmonology follow-up rates.
Results: Post-intervention (n=8), 37.5% successfully attended and documented follow-up rates in Electronic Medical Record (EMR), while 62.5% followed up elsewhere or delayed entry of asthma information. This represents an improvement compared to the baseline follow-up rate of 28.5% noted in 2023.
Conclusion: While the project cannot ensure the long-term sustainability of the piloted post discharge phone calls, outcomes were notably improved for African American asthma patients. Updating the asthma dashboard after discharge is crucial to avoid missing post-discharge calls before the first follow-up appointment. Additionally, this intervention could be expanded to benefit other minority groups, such as Hispanics. Using the data from this initiative, stakeholders may determine whether the intervention is not only desirable but also sustainable in the long run
Simulated Slot Machine Gambling in Relation to Sign-Tracking
Get PDFThe propensity to attribute incentive salience to reward-related cues, or sign-tracking (ST) has been linked to addiction in animal models and some initial human data. The current study explores the role of sign-tracking (ST), as a potential risk factor for problematic slot machine gambling, which abundantly features audiovisual reward-related cues, henceforth sensory features. A sample of healthy participants without gambling problems (n = 30) completed a Pavlovian-to-Instrumental Transfer (PIT) paradigm to assess ST propensity and played on a realistic slot machine simulator consisting of two versions: with sensory features (SF+) and without (SF-). Each game version had fixed bet sizes, included segments of relatively high- and low-volatility outcomes, and was followed by an optional bonus round participants could elect to play, in which they could vary their bet sizes. Self-report, behavioral, EEG, and eye-tracking data were collected to assess: 1) perceived game immersion, 2) post-reinforcement pauses and loss chasing; 3) ERPs related to reward anticipation and outcome feedback: contingent negative variation (CNV), win-related P300, and feedback-related negativity (FRN) in response to losses; 4) attentional bias towards the visual reward-related cues. Results showed that individuals with higher ST propensity did not exhibit greater immersion, amplified P300, CNV, FRN, or increased attentional bias to the visual game features during the SF+ version of the game. Greater immersion was self-reported in the SF+ version of the game and by individuals with a lower ST propensity. Post-reinforcement pauses and loss-chasing behavior were only evident in the SF- and not the SF+ version of the game, and greater volatility of outcomes promoted greater attentional bias towards the visual game cues in the SF- of the game only. Surprisingly, amplified (more negative) CNV amplitudes were observed in the SF- game. Overall, audiovisual game features (SF+) rendered the game more immersive and decreased behavioral sensitivity to outcome values. Associations of ST propensity with game experience and behavior were mostly absent, and when present, were in the opposite direction from that hypothesized
Effects of Physical Activity and Purpose in Life in Cognitive Aging
Get PDFCognitive decline has become a growing public health concern with the increase in aging populations throughout the world. As Physical Activity has shown to be one of the key factors in maintaining and enhancing cognitive health in older adults, this study explores the psychological mechanisms that might underlie this relationship. Using data from the Midlife in the United States (MIDUS) study, the analyses examine whether Purpose in Life mediates the relationship between Physical Activity and both cognitive abilities—Episodic Memory and Executive Functioning, whether age strengthens this effect, and whether Physical Activity itself could act as a mediator. The results showed that Purpose in Life significantly mediated the relationship between Physical Activity and both cognitive outcomes, with age moderating this relationship only for Episodic Memory. Furthermore, results showed that Physical Activity does not act as a mediator in these relationships. Findings from this study suggest that among physical activities with similar cardiovascular benefits, the one that also nurtures individuals’ purpose in life and boosts psychological well-being should be prioritized
Effects of High-Frequency repetitive Transcranial Magnetic Stimulation on Impulse Control Disorders in Patients with Parkinson’s Disease on Dopamine Replacement Therapy
Get PDFParkinson’s Disease (PD) is a debilitating neurodegenerative disorder that causes motor deficits, cognitive impairment, and depression. The mainstay treatment for motor symptoms is dopamine replacement therapy (DRT). DRT takes the form of levodopa or dopamine receptor agonists (DAs) and can be associated with impulse control disorders (ICDs). Currently, the approach to mitigating these side effects is to decrease or stop DRT, which may cause motor symptoms to return, making the management of the disorder more difficult. Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation treatment for multiple disorders, including its approved use for smoking cessation. It has also shown promise as a potential treatment for other addictive disorders. Because ICDs typically present as behavioral addictions they may also be helped by rTMS without the need to change DRT. This study aimed to evaluate acute effects of high-frequency rTMS over the dorsolateral prefrontal cortex (dlPFC) on cognitive behaviors related to ICDs. In a within-subject sham-controlled crossover design, patients with ICD with ICDs underwent 20-Hz rTMS over the left dlPFC followed by a reinforcement learning task assessing learning from positive versus negative feedback and a delay-discounting task assessing decisional impulsivity. rTMS effects on ICD-related urges and preoccupations were also assessed. Although there were not enough participants for the TMS-related findings to be interpretable, the present study provides insights regarding the feasibility of this protocol and information regarding the prevalence and characteristics of ICDs in the participating clinic. This new knowledge is instrumental for the future planning of clinical trials examining rTMS as a possible treatment for ICDs in PD in the current setting
Improving Neuromuscular Blockade Surveillance in Anesthesia Care with Quantitative Train of Four Monitoring
No full textProblem Statement: Despite the availability of quantitative train of four (TOF) monitoring, anesthesia providers more frequently rely on tactile (qualitative) TOF monitoring, which is associated with underestimation of recovery from muscle relaxation. Inadequate recovery from muscle relaxants results in residual weakness and its associated complications in the postoperative period, including compromised respiratory function (Thilen et al., 2023).
Background: Neuromuscular blockade (NMB) drugs are required to facilitate endotracheal intubation and allow for surgical manipulation. When these drugs are used, train of four (TOF) stimulations are used to monitor and assess the depth and recovery from NMB. TwitchView monitors (quantitative monitoring) is an electronic method that gives a more accurate ratio of the first and fourth twitches which correlates with better recovery from muscle relaxation. Though readily available to all staff, TwitchView monitoring is not used as frequently as tactile TOF monitoring in clinical practice.
Literature Review to Support Planned Intervention: The American Society of Anesthesiologist (ASA) guidelines support quantitative TOF monitoring as the standard for care (Thilen et al., 2023). The use of quantitative TOF monitors decreases the incidence of residual NMB and respiratory complications in postoperative patients when compared to tactile TOF monitoring (Naguib et al., 2007).
Project Aims: The purpose of this project was to improve compliance with clinical practice guidelines (CPG) of NMB and improve utilization of quantitative NMB monitoring at the project’s clinical site. An analysis of cost-effectiveness of TwitchView monitoring vs. cost of the residual effects of NMB will be performed.
Methods: IHI model for improvement was used along with the Plan-Do-Study-Act (PDSA) (AHRQ, 2020) as a framework to implement education and monitor for changes in utilization and compliance with CPG documentation of adequate muscle recovery over three months.
Implementation: Three cycles of the PDSA model were completed monthly using patient chart review for data collection to monitor for changes and areas for improvement.
Evaluation: Data regarding utilization was collected monthly to evaluate by a regression analysis using multinomial logistic models
Reactive Model-Free Control for Underactuated Vehicles Operating in Resource-Constrained Environments
Get PDFBuoyancy-driven, underactuated vehicles offer a compelling solution for long-duration autonomous operations in constrained environments. By leveraging buoyancy to generate lift, these vehicles can remain aloft for extended periods with minimal power requirements, making them well-suited for applications in atmospheric monitoring, planetary exploration, and communications. However, their limited actuation authority, strong coupling with environmental forces, and operating domains introduce significant control challenges, including nonlinearity, sensitivity to external disturbances, and limited observability.
This work investigates the design and implementation of lightweight, reactive model-free control strategies that enable robust autonomy in such constrained settings. A digital Extremum Seeking Controller (ESC) is first implemented as a reference behavior, offering an adaptive, model-free framework that guides the system toward a visual target using only local measurements. Building on this foundation, a fully analog control system is developed that leverages the ESC framework and classical PID control strategies using phototransistor-based optical tracking, bandpass filtering, and hardware-integrated motor drive circuits. By eliminating computation and software, the analog controller enables real-time reactive behavior in environments where localization and digital processing are difficult. Both strategies are benchmarked against a nonlinear Model Predictive Controller (MPC) using a validated 6DOF dynamic model of a custom-designed airship platform.
Simulation and experimental results show that while MPC achieves superior tracking accuracy when full-state feedback and modeling are available, the analog and ESC controllers offer viable alternatives for low-power, real-time control in resource-limited environments. This work contributes to the advancement of deployable autonomous systems by demonstrating that simple, reactive controllers can effectively operate in nonlinear, uncertain, and underactuated domains without reliance on global state estimation or high-performance computation
Does Education on Aseptic Non-Touch Technique Affect Nurse Knowledge On Aseptic Technique When Placing Ultrasound Guided Peripheral Intravenous Lines? A Quality Improvement Initiative
Get PDFThis Doctor of Nursing Practice (DNP) project attempted to increase nurse’s knowledge of aseptic technique when placing USG-PIVs in hospitalized adult patients after educational training on the Aseptic Non-Touch Technique Clinical Practice Framework (ANTT CPF). Implementation of the ANTT CPF in the cardiovascular intensive care unit (CVICU) at Ruby Memorial Hospital, as a didactic educational session for nurses already trained to place ultrasound-guided peripheral intravenous lines, was utilized for this DNP project. Pre- and post-surveys were employed to determine changes in knowledge scores as well as feelings of comfort and knowledge related to the CPF. Results remained stable for survey scores, feelings of comfort, and feelings of knowledge on the post-survey and follow-up survey. This project is easily transferable to other units and areas of practice within the hospital that also use ultrasounds to place peripheral intravenous access catheters (PIVs) because the placement of PIVs is a routine procedure for hospitalized patients
Dataset Evaluation of a Hybrid Additive Manufacturing System for Continuous Carbon Fiber-Reinforced Polymer Printing Using a Robust Feature Selection Machine Learning Pipeline
No full textManufacturing is undergoing a digital transformation of systems and processes – commonly known as Industry 4.0. This transformation is fueled by data which enables many of the smart manufacturing technologies like artificial intelligence (AI), digital twins, and augmented reality applications. However, manufacturing data, especially machine tools and other shopfloor applications, is infamously difficult to acquire and work with for a variety of reasons, including limited resources, data scarcity, privacy and cybersecurity concerns, high dimensionality, imbalanced target classes, and frequent missing values to name a few. These issues not only persist but are abundant in advanced manufacturing processes like additive manufacturing (AM). This makes working with AM process data difficult for practitioners who wish to utilize data-driven solutions like AI and machine learning (ML) for process improvement.
This thesis explores the deployment of data-driven approaches to evaluate a representative challenging dataset obtained from a unique, state-of-the-art hybrid additive manufacturing (HAM) machine. This unique manufacturing system employs two advanced manufacturing processes to construct additive structures using carbon fiber-reinforced polymer (CFRP) materials. The machine tool has a dual orifice head with a material extrusion nozzle and a tape laying fiber guide with a rotational axis. These orifices utilize existing technologies such as material extrusion AM (MEX-AM) and automated fiber placement (AFP) respectively, to create a novel HAM process. The relationship between the input process parameters, material microstructure changes during object construction, and final part properties is an established framework in AM. Through leveraging multi-scalar process-structure-property (PSP) relationships, predictions about physical and mechanical characteristics of constructed objects can be generated. These predictions can be utilized to provide an in-situ closed-loop solution to quality issues in a myriad of AM technologies. Before constructing this closed-loop quality system, it is important that the process parameters which impact the desired results are monitored and their data is intentionally collected. In this analysis, a feature selection approach is evaluated using a ML pipeline to robustly evaluate preprocessing techniques and their impact on the analysis of raw manufacturing data with imbalanced classes and data leakage. This study quantifies the stability and reliability of selected features using binary classification model accuracy, precision, recall, F1-scores, and the area under the receiver operator characteristic (AUC-ROC) curve. The results of this study illustrate the importance of intentionally applying the appropriate preprocessing techniques depending on the practitioner’s dataset characteristics
Ecosocialism, Degrowth, and Global South Thought: Critical Legal Transformations
No full textThis Article explores how Critical Legal Research (CLR) can help drive transformations of our ecological political economy towards true system change. CLR entails a critical legal theory–informed approach to legal and broader socio-legal research. After articulating the CLR framework, this Article explores its potential in the context of leading and intertwined bodies of theory for transformative change: ecosocialism, degrowth, and Global South and Indigenous thought. Next, this Article offers concrete avenues to help pursue such emancipatory change—i.e., specifically focusing on the popular conception of an “ecosocialist transition.” Ecosocialist transition strategies include non-reformist reforms, dual power, a radical just transition, and joining ecosocialism with a broader global movement of movements. As this Article contends, such ecosocialist transition strategies can be powerfully informed by CLR via embedding CLR within bottom-up forms of socio-legal praxis, such as radical movement lawyering. Ultimately, such CLR praxis constitutes an emerging and vital, yet still largely underutilized, dimension in the struggles to combat white patriarchal capitalism and to pursue ecologically viable and socially emancipatory futures