Development of a Nursing Psychological Safety Assessment Toolkit for Nurse Leaders

DNP ProjectIntroduction/Purpose: Assessing psychological safety within a nursing department is critical information for leaders that gives insight into the culture of teamwork and collaboration. Nursing leaders need the ability to assess their team's psychological safety quickly to help understand safety culture. The purpose of this project was to create a toolkit that nursing leaders can easily access to help assess and improve their team's psychological safety. Methods: Nursing leaders at a single community hospital were administered a pre-test regarding their comfort in assessing psychological safety. The nursing leaders then used the psychological safety toolkit to help assess their department and built an action plan to increase psychological safety. A post-test was performed after the toolkit implementation was complete. The data was analyzed with descriptive and inferential statistics to determine if there was a statistically significant difference in scores from the pre-test and the post-test. Results: The results identified improvement in all mean scores of nurse leaders' comfort in understanding psychological safety, confidence in its importance, ability to assess their team, and ability to build an action plan. Inferential statistics showed a statistically significant improvement in scores for leaders' confidence in creating an action plan. Discussion: Building a toolkit for nursing leaders to administer when they assess for psychological safety will allow leaders to obtain real-time information about their team. By guiding them on how to develop action plans to increase psychological safety, they can create high-functioning teams that invest in a culture of safety

Toward Sensor Fusion Neuromuscular Interface for Continuous Finger Joint Angle Estimation via Deep Transfer Learning

Author Accepted ManuscriptAccurate decoding of motor intent from biosignals is essential for controlling upper-limb prostheses. We proposed a novel high-dimensional multimodal deep learning framework that fuses surface electromyography (sEMG) and B-mode ultrasound (US) images to estimate metacarpophalangeal and proximal interphalangeal joint angles continuously. The framework employs a shared Encoder– Decoder–Regression architecture integrating transposed convolutions, multi-head cross-attention, and long short-term memory layers to jointly capture spatiotemporal features from both modalities. In this model, each modality is processed by its own encoder and decoder, and the resulting feature maps are fused before being passed to the regression head. To improve cross-subject generalization and reduce data requirements for new users, we introduce a transfer learning strategy with parameter freezing. Experiments on data from seven subjects show that, compared with sEMG-only and US-only baselines, the fusion model reduces test RMSE by 1.873◦ (21.02%) and 0.794◦ (10.15%), and increases test local correlation by 0.069 (10.02%) and 0.039 (5.48%) (p < 0.05), demonstrating the potential of multimodal fusion for amputee rehabilitation. Ablation studies further confirm that the full CNN+LSTM+Attention model achieves the best performance, reducing test RMSE by 2.022◦ (22.32%) and increasing test local correlation by 0.053 (7.52%) (p < 0.05). Furthermore, fine-tuning the pretrained model with only 25% of a new subject’s data yields performance comparable to full retraining, highlighting the framework’s data efficiency.This work was supported by Startup funding at The University of Alabama (FOAP #13009-214271-200)

Voices That Mother – the Lived Experiences of Blackmotherscholars in Doctoral Programs

Electronic Thesis or DissertationBlack mothers navigating doctoral programs at Predominantly White Institutions (PWIs) experience a unique and often overlooked intersection of responsibilities, expectations, and systemic barriers. Grounded in womanist theory, this dissertation centers the lived experiences of BlackMotherScholars, a term that reflects the indivisible identities of Black motherhood and scholarship. Through a womanist lens that emphasizes wholeness, transformation, and community care as resistance, this qualitative study explores the ways in which BlackMotherScholars navigate academic spaces highlighting both the challenges and strategies of persistence, resistance, and community-building.BlackMotherScholar Methodology (BMSM) is a framework developed within this study to capture, honor, and validate the experiences of Black mothers in academia. As traditional Western Eurocentric qualitative research methodologies at times fall short of fully accounting for the cultural and communal labor experienced by Black mothers in academic spaces, BMSM builds upon existing qualitative approaches by integrating culturally grounded knowledge traditions and introducing "vibe sessions" as a data collection approach. Vibe sessions are an original methodological contribution, developed through this dissertation, that offers an alternative to traditional interviewing by creating a more relational and affirming space for Black mothers in doctoral programs to share stories. Vibe sessions embody womanist traditions of creating homeplace and collective wisdom-making, drawing from Black cultural traditions of rhythm, energy, and collective storytelling to honor intergenerational knowledge and spiritual grounding, alongside culturally responsive research practices, to create a new method for authentic and embodied engagement. Through these and other methodological choices, BMSM intentionally centers and amplifies the resistance and resilience demonstrated by Black mothers in academia, positioning research itself as an act of reclamation and liberation from traditional academic constraints.This study contributes to ongoing conversations about culturally sustaining qualitative approaches by offering both methodological and practical implications. Through the development and application of BMSM this research reclaims research as a space for liberation, validation, and communal knowledge-building. By centering storytelling, cultural traditions, and embodied ways of knowing, BMSM challenges dominant academic norms and affirms the lived experiences of Black mothers in doctoral programs

Implementation of a Nurse Mentor Program to Increase New Operating Room Nurses' Support, Intent to Stay, and Retention Rates

DNP ProjectIntroduction/Purpose: Retaining nursing staff is essential for nurses' well-being and reducing burnout, positively correlating with patient outcomes. National statistics indicate that, on average, 13% of nurses leave their positions within the first year. Key factors contributing to this attrition include inadequate support during their transition to independent practice. This project aimed to implement a mentoring program for newly hired nurses in the operating room to enhance their feelings of support, increase retention rates, and improve patient outcomes. Methods: A Nurse Mentor program was established based on the American Medical Surgical Nurse Mentoring Program guidelines. Six nurses undergoing orientation in the operating room were paired with mentors. Pairs met biweekly, and Nurse Mentor Agendas were provided to facilitate their discussions. Mentees completed the Intent to Stay, Relationship with Mentor, and Job Satisfaction Scale surveys monthly. Additionally, surgical site infection rates were monitored for assessment purposes. Results: New nurses reported high levels of job satisfaction, strong intent to stay, and positive feedback regarding their relationships with mentors. Remarkably, new nurse retention reached 100% at the six-month mark. Additionally, as vacancies decreased, the surgical site infection ratio improved incrementally from 1.806 to 0.602 over three months. Discussion: The outcomes of the Nurse Mentor Program are highly encouraging. Future longitudinal studies of the program will be critical to evaluating its long-term effects on job satisfaction, intent to remain in their position, and surgical site infection rates

Towards Neurorobotic Interface for Finger Joint Angle Estimation: A Multi-Stage CNN-LSTM Network with Transfer Learning

To maximize the autonomy of individuals with upper limb amputations in daily activities, leveraging forearm muscle information to infer movement intent is a promising research direction. While current prosthetic hand technologies can utilize forearm muscle data to achieve basic movements such as grasping, accurately estimating finger joint angles remains a significant challenge. Therefore, we propose a Multi-Stage Cascade Convolutional Neural Network with Long Short-Term Memory Network, where an upsampling module is introduced before the downsampling module to enhance model generalization. Additionally, we designed a transfer learning (TL) framework based on parameter freezing, where the pre-trained downsampling module is fixed, and only the upsampling module is updated with a small amount of out-ofdistribution data to achieve TL. Furthermore, we compared the performance of unimodal and multimodal models, collecting surface electromyography (sEMG) signals, brightness mode ultrasound images (B-mode US images), and motion capture data simultaneously. The results show that on the validation set, the US image had the lowest error, while on the prediction set, the four-channel sEMG achieved the lowest error. The performance of the multimodal model in both datasets was intermediate between the unimodal models. On the prediction set, the average normalized root mean square error values for the four-channel sEMG, US images, and sensor fusion models across three subjects were 0.170, 0.203, and 0.186, respectively. By utilizing advanced sensor fusion techniques and TL, our approach can reduce the need for extensive data collection and training for new users, making prosthetic control more accessible and adaptable to individual needs

Examining Dietary Acculturation in the Us Southern Food Environment: Determinants of Food Choice and Dietary Patterns Among West African Migrants in the Stroke Belt Region

Electronic Thesis or DissertationBackground: Each year, over 500,000 international students, including many from Sub-Saharan Africa, enroll in universities within the United States (US). Up to 90% of these students remain in the country after graduation, often gradually adopting American lifestyles. As they acculturate to US lifestyle and dietary practices, these students risk losing the health advantage they initially had upon arrival, a decline commonly referred to as the "healthy immigrant effect". Unfortunately, the Southeastern US is commonly referred to as the Stroke Belt and is associated with a 10% higher risk of cardiometabolic diseases (CMDs) compared to other regions of the US. As CMDs disproportionately affects Black populations, West African (WA) international graduate students who acculturate in the Stroke Belt food environment region may also face increased CMD risk. Purpose: This study examined dietary acculturation and diet quality of WA international graduate students in three adjacent US Stroke Belt states—Alabama (AL), Georgia (GA), and Mississippi (MS). It investigated potential factors influencing their level of dietary acculturation and diet quality including nutrition knowledge, perception of the food environment, and food security status. Methods: This study employed a quantitative, cross-sectional study design, utilizing the Contento Determinants of Food Choice Model. This involved a comprehensive literature review to identify appropriate data collection tools for measuring the constructs of interest. Expert panel reviews, pilot testing, and iterative modifications were performed to ensure both construct and face validity of the final survey instrument. Reliability was assessed using a test-retest method. Quantitative survey data were analyzed with descriptive analysis, ANOVA, and regression analyses whereas qualitative responses to open-ended questions were thematically analyzed. Results: A total of 156 eligible WA international students from AL, GA, and MS completed the survey. The mean dietary acculturation score was 2.5 on a scale of 0–5 (SD = 0.4; Range =1.7–3.7), indicating a balanced intake of both traditional and non–WA foods. Regression analysis identified self-rated health (β = –0.356, p < .001), remittance behavior (β = –0.259, p < .001), income (β = 0.224, p = .002), and length of residence in the US (β = 0.184, p = .011) as the strongest predictors of dietary acculturation in this population, explaining 33% of the adjusted variance. Diet quality overall was generally poor, with a mean score of 40.6 on a scale of 0-100 (SD = 8.1; Range = 22.1–61.9). Gender was a significant predictor of diet quality (β = 0.17, p < .001), with females reporting higher overall diet quality scores (p = .001). Knowledge about how to prepare WA foods was also a strong predictor of better diet quality (β = 0.29, p < .001). Participants rated their perception of a healthy food environment at 3.0 (SD = 0.8) and the unhealthy food environment at 3.7 (SD = 1.1) on a 1–5 scale. Key barriers reported to maintaining traditional diets included limited availability of traditional foods, high cost, transportation constraints, and compromised authenticity of traditional food ingredients. Facilitators included access to ethnic stores, social and community support, personal food preferences, and use of digital media for recipe adaptation and ingredient sourcing. Discussion and Conclusion: In this population of WA students residing in the Stroke Belt region, participants demonstrated bicultural dietary acculturation shaped by personal, cultural, and environmental factors. Remittance behavior emerged as a novel predictor of dietary acculturation by encouraging continuity of traditional dietary practices. The overall poor diet quality reported in this population also highlights the need for culturally tailored nutrition education that builds on existing culinary knowledge of traditional food. Perceptions of the food environment were complex as participants reported their food environment as being both healthy and unhealthy. These findings call for further research to better understand the intersecting roles of culture, economics, and environment in shaping dietary behaviors among WA international students

Open Access Publication Trends at an R1 University: Using Data-Driven Strategies for Institutional Repository Promotion and Outreach

Introduction: This exploratory study examines five years of institutional publishing output of an R1 University, examining to what extent authors have utilized open access (OA) publishing opportunities. Literature Review: The literature review explores the concurrent benefits of (OA) publishing and institutional repositories, citing similar studies on bibliometrics and publishing trends and data-informed strategies for promoting library services relative to scholarly communications topics. Methods: Data was collected from Web of Science combined with the OA data from the UnPaywall Rest API and cleaned and analyzed in OpenRefine and Microsoft Excel. Results: The findings suggest that many university authors pursue OA publishing opportunities, with nearly half (45%) of the articles in the sample utilizing various OA publishing models and nearly one-third appearing in at least one OA repository. Discussion: The results of this study were used to better understand OA publication trends at the university and inform educational and outreach strategies. Conclusion: The authors conclude with recommendations for further study and ideas for promotion of The University of Alabama’s institutional repository utilizing the data from this research

The Implementation of Lifestyle Modifications in Patients Diagnosed with Polycystic Ovary Syndrome (PCOS)

DNP ProjectIntroduction: PCOS is a syndrome that impacts a female’s hormones, causing weight gain, acne, increased hair growth, and irregular periods. Implementing interventions focused on diet and exercise can reduce the risk of increased PCOS symptoms such as hirsutism and weight gain. Methods: The practice intervention project provided participants with a 10-minute educational presentation from The American College of Obstetricians and Gynecology (ACOG) and World Health Organization (WHO). Following consent, four participants began a six-week intervention including a low-carbohydrate, high protein diet and 30 minutes of moderate to high intensity walking for 5 days per week. The Ferrimen-Gallwey Scoring system was utilized to assess for severity of hirsutism. Height and weight were obtained, and body mass index (BMI) was calculated pre and post intervention. A diet recall and exercise log were utilized during project intervention. Results: The results of the dependent t-test showed a statistical difference in the participants BMI between pre-intervention (M = 40.43, SD = 9.085) and post- intervention (M = 38.575, SD = 9.7967). Ferrimen-Gallwey scores also showed a statistical difference between pre=intervention (M + 21.25, SD = 7.500) and post-intervention (M = 15.50, SD = 6.455). Overall, all four participants showed a decrease in BMI and decrease in Ferrimen-Gallwey score between pre and post intervention Discussion: Achieving symptom control of PCOS can be challenging. Compliance is a large factor in controlling and managing symptoms of PCOS. Interventions aimed at lifestyle interventions using evidence-based guidelines must be initiated at time of diagnosis to reduce the symptoms and prevent complications of PCOS

Integrated Analysis of Electric Aircraft Performance and Battery Design Through Coupled Modeling of Flight, Battery, and Thermal Dynamics

Electronic Thesis or DissertationElectric aviation has emerged as a focus of research in recent years with significant progress in electric aircraft development. One of the greatest hinderances to the wider adoption of electric aircraft is the inability of current battery technology to simultaneously provide high gravimetric energy density and power density over a wide range of operating conditions while ensuring safety and reliability. In this work, a coupled framework consisting of longitudinal flight dynamics for a fixed-wing aircraft, high-fidelity electrochemical battery physics, and battery heat generation is developed to analyze battery performance characteristics and understand performance limitations under dynamic loads representative of an aircraft propulsion system. Using this framework, simulations are conducted to analyze and understand the interplay between electrode design parameters and material properties, flight control variables, and operating temperature of the battery system. The results show that cruise velocity has the largest impact on the aircraft range with the range 30% higher at the optimal velocity compared to the lowest range at highest cruise velocity considered. The range and cell-level limiting current are found to drop by as much as 15% and 50% at 0°C compared to their respective values at 30°C. For the range of values considered, electrode design parameters have been found to increase the aircraft range and the limiting current by approximately 15% and 150%, respectively, compared to the reference design parameters values representative of actual cell considered in this study. After taking into account all the key energy loses occurring at the cell level, we found each kWh of pack energy to translate to about 6.5km of air travel distance. Additionally, battery heat generation modeling was incorporated and compared to experimental data. Peak battery temperature during the climb phase vary between 7 and 20°C depending on ambient temperature, the amount of cooling, power requirement, and battery electrode design. Finally, atmospheric variations' effect on air density and battery performance are analyzed leading to aircraft range differences of up to 21% between locations at the same time of year and up to 11% at the same location at different times of year

Analysis of Timing Behavior for Wireless Synchronization of Bioimpedance Analog Front End Sensors

Electronic Thesis or DissertationBioimpedance spectroscopy is a noninvasive and cost-efficient technique used in imaging, body composition analysis, tissue health assessment, and more. Compact, low-cost impedance analyzers such as the MAX30009 have permitted development of wearable bioimpedance sensors for health monitoring applications. Multi-site bioimpedance measurement can offer insight in biological processes throughout the body, but the accuracy of multi-site analysis depends on the timing synchronization of distributed nodes. This thesis aims to analyze the effects of timing errors in multi-site bioimpedance measurement and develop a wirelessly synchronized bioimpedance sensor network to address the needs of modern bioimpedance applications. Bluetooth-enabled microcontrollers are used with MAX30009 devices and real-time clocks to achieve initial synchronization and low clock drift