Volume VIII

On behalf of the 2024-2025 Editorial Board, I am proud to present the Eighth Volume of The Capstone Journal of Law and Public Policy. This year, we publish a record eleven articles from ten unique authors representing a wide range of topics and universities. -Michael Regnier, Editor in Chie

Implementation Facilitation Activities Used by an External Facilitator in a Quality Improvement Intervention

Electronic Thesis or DissertationImplementation facilitation is a dynamic, multi-faceted practice that supports both the execution and sustainability of interventions, but there is limited understanding of how implementation facilitation activities are carried out. This knowledge gap may have implications for facilitator training and the long-term success of facilitated interventions. Previous studies have relied mainly on interviews with facilitators. To address this gap, this study examines transcripts of recorded meetings between an implementation facilitator and nursing home leadership teams during a complex, psychosocial quality improvement intervention. This study analyzed transcripts from 24 meetings across two nursing home sites, using Braun and Clarke's reflexive thematic analytical approach (2021). The study identified three themes regarding facilitation activities used by an implementation facilitator: (1) Building Relationships with the Team Through a Compassionate and Strength-Focused Approach; (2) Fostering Critical Thinking of Resident Care Practices; and (3) Co-designing Goals and Action Plans. The theme of fostering critical thinking also highlighted the active involvement of the leadership team in these discussions. This research deepens our understanding of facilitation practices and offers insights for improving the training of facilitators and the design of implementation efforts, ultimately enhancing the effectiveness and sustainability of interventions in healthcare settings

Street Nursing 101: Caring for the Homeless Population

DNP ProjectIntroduction/Purpose: Homelessness presents significant public health challenges, contributing to higher rates of chronic illness, mental health conditions, and over utilization of emergency departments (EDs). This project implemented the Street Nursing 101 educational program to enhance nurses' competence and improve care for homeless patients in the emergency department. Methods: A quantitative approach, guided by the Iowa Model of Evidence-Based Practice, supported the implementation of an online training program centered on homelessness care. Nurse competence was assessed using the PROFFNurse SAS II, modified HCAHPS surveys for patient experience, and hospital data for ED visit trends. Results: Nurse competence mean scores improved from 5 to 8.0, reflecting increased confidence. Perceived training needs dropped from a mean of 8.25 to 4, indicating nurses felt more prepared without requiring immediate additional training. Patient feedback showed a slight decline in reports of "Always" courteous and respectful care but a significant reduction in "Never" listened-to complaints. Ratings for communication, discharge planning, and aftercare education improved, while non-emergent ED visits by homeless patients decreased by 4.6% (from 304 to 290). Discussion: This initiative successfully improved nurse competence, patient feedback experience, and non-emergent visits. By addressing communication gaps, discharge support, and nurse preparedness, Street Nursing 101 provides a replicable model to reduce healthcare disparities and enhance care delivery for homeless populations in ED settings

Prostate Health Empowerment Initiative: Breaking Barriers, Promoting Awareness

DNP ProjectIntroduction: Prostate cancer is the second most frequently diagnosed cancer in the United States, with African American men (AAM) disproportionately affected. Contributing factors include medical mistrust, poor patient-provider communication, fear of diagnosis, and societal stigma. Methods: A culturally tailored educational program on prostate cancer screening guidelines for high-risk AAM was delivered to healthcare providers (HCPs) Surveys conducted before and after the program evaluated the provider’s knowledge while screening and referral rates were compared pre- and post-intervention. Results: Pre-intervention, 38.4% were screened for prostate cancer, while in post-intervention, 33.7% were screened. The proportion of unscreened patients increased from 61.6% to 66.3%. However, clinic visits by AAM increased, suggesting enhanced healthcare engagement. Among those screened, 100% underwent PSA testing, with PSA elevations rising from 3.3% pre-intervention to 4.2% post-intervention. Referral rates for elevated PSA remained at 100% in both periods. Discussion: Although screening rates did not improve as expected, the intervention may have contributed to increased healthcare engagement. Future efforts should focus on addressing screening barriers, enhancing provider engagement, and improving referral tracking to ensure timely prostate cancer detection and treatment for high-risk AAM

Developing and Optimizing a Robust Spray-Capillary Ce-Ms Platform for Ultrasensitive Omics Analysis

Electronic Thesis or DissertationSingle-cell multi-omics provides a vast amount of information, giving us an advantage in discovering mechanisms of gene regulation, protein expression dynamics, and epigenetic differences. This bolsters our understanding of cell heterogeneity in disease, which has implications for advancing diagnostics and treatments. Developing such methods may require the development of single-omics methods that could be paired. This thesis focuses on developing and optimizing an ultrasensitive, robust, and high-throughput spray-capillary CE-MS platform for multi-omics analysis of single cells.The spray-capillary CE-MS technology demonstrates high potential for emerging in single-cell and mass-limited sample analysis due to its enhanced detection limit and ultralow sample volume requirements. However, we had to address some challenges before proceeding with optimizing the system for mass-limited or single-cell analysis. These challenges included the rapid evaporation of such a small sample volume, in addition to the high fragility of the capillary’s tip. To mitigate these challenges, a humidity chamber was developed to maintain the small sample volume of a single cell, ensuring successful sample handling. Additionally, the tip structure of the capillary was modified to enhance the physical robustness of the tip and decrease the ESI voltage applied, which is expected to contribute to less oxidative interferences and a longer capillary life. The work also included optimizing the spray-capillary CE-MS system. First, we worked on improving reproducibility and robustness. Thus, a conditioning protocol was designed and further optimized for the top-down proteomics workflow. Second, to enhance separation and sensitivity, we optimized the CE separation voltage using the bottom-up proteomics workflow. These developments and optimizations were dedicated to enabling the analysis of mass-limited or single-cell samples by spray-capillary CE-MS. As a proof-of-principle experiment, HeLa protein digest single-cell samples were tested where peptides were detected from tiny fractions of single cells. Overall, this work has demonstrated that the optimized spray-capillary CE-MS platform implies a high potential for multi-omics analysis from single cells

A Tale of Two Precincts: an Exploratory Institutional Ethnography of Missing Persons Cases in Two Alabama Sheriff's Departments

Electronic Thesis or DissertationIn my thesis, I explore the institutional processes and disparities in missing persons casework across two sheriff’s departments in Alabama. This research has the potential to significantly impact law enforcement practices and the lives of those affected by cases of missing persons. Using a combination of institutional ethnography and structural violence theory, my study compares a well-resourced urban county (County A) with an under-resourced rural county (County B). Data were collected through interviews with field investigators, analysis of missing persons reports, and public case data, including social media posts made by each department. At first glance, the findings reveal significant disparities in case outcomes based on institutional resources, community engagement, and race, as well as the urgency of addressing these issues. Instead of a purely quantitative approach, the ethnographies of the two departments in these counties give context to the publicly available data, providing a more comprehensive understanding of cases of missing persons. County A demonstrated a systemic approach to cases of missing persons, utilizing advanced technologies, public outreach, and social media, leading to higher success rates in case resolutions, particularly after 2011. In contrast, County B, constrained by limited resources and external reliance on media outreach, may seem to exhibit a community-based approach, with fewer publicly reported cases and a lower resolution rate due to the invisibility of their caseloads.My research draws attention to the need for increased funding and structural reforms to address these disparities, particularly in rural and marginalized communities. It also emphasizes the importance of community engagement and modern investigative tools, such as social media, in resolving cases of missing persons. My thesis concludes by offering recommendations for policy changes and future research to address the systemic inequalities that continue to impact missing persons investigations in Alabama and beyond. My study highlights context within data disparities, combining structural violence frameworks and institutional ethnography to understand the “how’s” and “why’s” of missing person investigations

Branding English, Shaping Perceptions: Language Ideologies and Professional Positioning Among Brazilian ELT Influencers on Instagram

Electronic Thesis or DissertationThe rise of social media has enabled English language teachers (ELT) to adopt entrepreneurial roles as social media influencer teachers (SMITs). This exploratory study investigates how Brazilian mega SMITs (those with more than one million followers) construct their professional identities and disseminate language ideologies on Instagram. Using a qualitative netnographic approach, this research examines the multimodal discourse of seven prominent Brazilian ELT influencers, focusing on their profile information, pinned posts (n=12), and the ten most-viewed Reels (n=70).Findings reveal that SMITs strategically position themselves as authorities by blending pedagogical content with self-branding techniques. Their discourse frames English as a marketable product within linguistic entrepreneurship ideology, emphasizing its role in providing financial success and social mobility. English is associated with prestige, often linked to native speakers from developed countries, reinforcing native-speakerism and raciolinguistic ideologies while diminishing local linguistic practices. SMITs portray their teaching methods as superior through student testimonials and comparisons to traditional approaches, legitimizing their expertise. Additionally, they encourage engagement with Instagram as a learning tool by creating entertaining and interactive content, which increases audience retention and enhances their visibility within the platform’s algorithm. While these influencers challenge traditional ELT structures by circumventing institutional gatekeeping, they also contribute to the commodification of language learning. This study contributes to discussions on the evolving role of ELT within platformized digital environments by highlighting the intersection of digital labor, influencer culture, and language ideologies. It also raises critical questions about the role of social media in shaping perceptions of English language learning in Brazil

Hide and See: Exploring the Role of Protective Regions and Clear Sightlines in Shaping Customer Behaviors

Electronic Thesis or DissertationVarious attributes in the retail environment, such as clear sightlines and regions of shelter and protection, can make a consumer feel safe and ultimately impact consumer outcomes such as shopping intentions, satisfaction, and repatronage intentions. The hypotheses presented in this dissertation are rooted in Prospect and Refuge Theory, a subset of evolutionary psychology focused on the positive effect of the presence of clear sightlines and the protective regions on consumer behavior outcomes. Theorized to be driven by an evolutionary desire to inhabit regions that offer safety from possible threats while still permitting faculty of sight, Prospect and Refuge Theory theorizes humans possess a biological preference for environments with unobstructed views, such as transparent window or clear lines of sight to the door, and areas of protection such as alcoves, booths, covered areas, and perimeters. This research explores how environments that offer clear sightlines and regions of protection generate greater feelings of psychological safety which increase satisfaction and purchase intentions for consumers. We find that clear sightlines into a store and the presence of regions of protection increase sense of safety which drives higher shopping intentions and other key customer outcomes. In addition, we also explore potential boundary conditions for these effects such as store type and information about products and services. Findings from this research support the goal of retailers and service providers to enhance in-store experiences and are applicable in a vast array of contexts including restaurant, retail, hospitality, and entertainment settings

Model-Based Knowledge-Driven Machine Learning for Automotive Radar Imaging and Perception

Electronic Thesis or DissertationThis thesis enhances automotive radar object detection by integrating deep learningnetworks with radar signal processing expertise. Automotive radar sensors are essential inadvanced driver assistance systems and autonomous vehicles due to their low cost,robustness, and effective operation in all weather conditions. Cameras and LiDAR systems,while offering advanced environmental perception, suffer performance degradation inadverse weather and poor visibility and often have higher costs. Millimeter-waveautomotive radars, operating between 76–81 GHz with bandwidths up to 4 GHz, providehigh range resolution and strong penetration capabilities through fog, rain, snow, smoke,and dust. Despite these advantages, radar’s potential for object detection and classificationremains underutilized due to limitations in angular resolution, reliance on sparse pointclouds in commercial systems, and the scarcity of publicly available high-resolutionautomotive radar datasets.To address these challenges, this thesis focuses on three key enhancements. First, wepropose novel deep learning frameworks for Direction of Arrival (DOA) estimation, aimedat improving angular resolution and object localization accuracy while simultaneouslyreducing system complexity. Second, by integrating deep learning into the radar signalprocessing pipeline, we enhance feature extraction from raw radar data. This integrationnot only improves radar image quality but also increases the reliability of subsequentobject detection and classification tasks. Third, we develop the BAMA Radar Dataset, acomprehensive collection of radar data with corresponding LiDAR and camera data,specifically tailored for autonomous driving scenarios and diverse environmental conditions.This dataset fills a critical gap, as existing autonomous vehicle perception datasets oftenprioritize camera and LiDAR recordings, with limited radar data. Using this dataset, wedesign and implement an object detection network optimized for high-resolution radarimagery, addressing the unique characteristics of radar data to enhance detectionperformance. The network is trained and evaluated on our dataset and other public radardatasets, ensuring robust validation of its capabilities.Through these advancements, this thesis enhances the capability of automotive radarsystems for object detection and classification in autonomous vehicles. Integrating deeplearning with radar signal processing boosts radar performance and complements existingperception systems, contributing to safer and more reliable autonomous drivingtechnologies

It Takes Two: a Study of Meaning Negotiation and Multimodal Communication in Collaborative Gaming

Electronic Thesis or DissertationThis study examines how multimodal interaction resources such as speech, movement, and gesture mediate negotiation for meaning during collaborative gaming among second language learners. It also investigates the production of language-related episodes by second-language learners. This qualitative study examines participant interactions during collaborative gaming. It draws on applied linguistics (Smith, 2003; Varoni & Gass, 1985) and gesture studies (Norris, 2004). Data collection includes screen recordings, audio recordings, and video recordings of participants engaged in cooperative gameplay. The findings reveal that negotiation episodes occur spontaneously during collaborative gaming, and second-language learners employ interactional strategies like clarification requests, confirmation checks, elaboration, and comprehension checks to repair communication breakdown. The results also highlight the use of gestures during negotiation episodes and describe how second language learners dynamically co-construct meaning using multimodal resources like gestures, gaze, and head movement