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Predicting High Urinary Tract Infection Rates in Skilled Nursing Facilities: A Machine Learning Approach
No full textObjectives: Urinary tract infections (UTIs) are the most common healthcare-associated infections in Skilled Nursing Facilities (SNFs); they are associated with longer lengths of stay, higher levels of care, increased treatment costs, and higher mortality rates. This study aimed to develop a machine learning classification model to predict the risk of high catheter-associated urinary tract infection rates based on SNF characteristics. Methods: We analyzed 94,877 total SNF-year observations from 2019 to 2024, not unique facilities; thus, individual SNFs may appear in multiple years. The factor variables were average length of stay in days, number of staffed beds, total nurse and total physical therapy staffing hours per resident per day, facility ownership, geographic classification, facility accreditation, Accountable Care Organization affiliations, Centers for Medicare and Medicaid Services SNF Overall Star Rating, and the SNF-year of the observations. We utilized three machine learning models for this analysis: Random Forest, XGBoost, and LightGBM. We used Shapley Additive exPlanations to interpret the best-performing machine learning model by visualizing feature importance and examining the relationship between key predictors and the outcome. Results: We found that machine learning models outperformed traditional logistic regression in predicting UTIs in skilled nursing facilities. Using the best-performing model, Random Forest, we identified rural SNFs, and the number of staffed beds as the most influential predictors of high UTI rates, followed by average length of stay, and geographic location. Conclusions: This study demonstrates the value of using facility-level characteristics to predict the risk of UTIs in SNFs with machine learning models. Results from this study can inform infection prevention efforts in post-acute care settings.Health Informatics and Information ManagementPhysical Therap
Oral History Interview: Pat Ray Thompson
No full textUnedited transcript file (.pdf) and edited video files available with closed captioning.Oral history interview with Sylvia Thompson, widow, and Vic Willoughby, service buddy, remembering Veteran Pat Ray Thompson
Oral history interview: Jason Poindexter
No full textEdited and unedited transcript files (.pdf) and edited and unedited video files available with closed captioning.Interview with Travis Westbrook. He describes his life growing up with his brother as children and teenagers, his brother's choice to join the Marine Corps, and his impact on the people around him
Universal Depression Screening in School-Aged Children/Adolescents in Public Schools: A Systematic Review [paper]
No full textYouth suicide has risen substantially over the past decade. However, many children and adolescents with depressive symptoms remain undetected in public schools due to reliance on behavior-based referral systems. Universal depression screening has been proposed as a proactive approach in supporting earlier identification and timely referral to mental health services. This systematic review examined whether school-based universal depression screening improves recognition of depressive symptoms and facilitates referral and treatment initiation among students in grades K-12. A systematic search of three databases was conducted using predefined criteria to identify peer-reviewed studies published in the United States between 2020 and 2025. Seven studies met eligibility and quality appraisal thresholds. Data was extracted into an evidence synthesis table and analyzed for patterns in design, implementation, outcomes, stakeholder perceptions, and contextual factors. Across these studies, universal screening substantially increased identification of depressive symptoms and improved pathways to early intervention when compared with traditional referral approaches. Stakeholder groups, including teachers, parents, and clinicians, reported strong support for school-based screening when adequate workflow, confidentiality protections, and follow-up systems were in place. Several perceived barriers were identified, including time constraints, limited mental health staffing, stigma, and inconsistent follow-up. Universal depression screening in public schools appears to be both effective and feasible when supported by appropriate infrastructures and clear referral pathways. Findings highlight the need for ongoing development of screening practices and further research to strengthen long-term outcomes and implementation strategies.Nursin
Oral history interview: Albert Lee Nicholson
No full textEdited and unedited transcript files (.pdf) and edited and unedited video files available with closed captioning.Oral history interview with Tommy Houston, III about his uncle, Albert Lee Nicholson. Tommy discusses his uncle's life, service, and legacy
A Review of Artificial Intelligence and Its Use in Accounting
No full textArtificial Intelligence is a crucial new tool for the future. No industry can seem to get away from its use and accounting is no exception. This paper is an overview of AI and a review of AI use in Accounting. When I refer to “AI” I specifically mean Generative AI or Large Language Models, which are AI models specifically made to create new content based on patterns. Examples include ChatGPT, Gemini, Copilot, etc. I will mainly focus on questions that relate to the how and why aspects of AI. I will answer questions like how AI will be used in accounting, how it should be implemented, why accountants should use it, and general questions about AI. I find answers to these questions with various methods. This includes sources like the book Co-Intelligence Living and Working with AI, an AI course designed by the accounting firm EY, and frameworks designed by COSO, along with general secondary research. Additionally, I used AI to show examples of prompting and responses as part of my paper. ChatGPT is the AI Chatbot I chose to use. This project will also include a description of a chat bot I have made using Perplexity to help demonstrate AI capabilities.Finance and Economic
Comparison of GLP-1 Receptor Agonists’ Effect on Weight in those with Schizophrenia: A Systematic Review [poster]
No full textIntroduction: Individuals with schizophrenia experience a shortened life expectancy primarily due to cardiovascular and metabolic complications associated with antipsychotic induced weight gain. Current interventions, such as lifestyle modifications and initiating metformin, have demonstrated limited efficacy. This paper aims to compare the effects of different glucagon-like 1 receptor agonists on weight in patients with schizophrenia who are taking antipsychotics. Methods: This systematic review conducted searches on six different databases using the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. Eligible studies included randomized controlled trials, cohort studies, case series, and a quasi-experimental design. Seven articles across five different countries met the inclusion criteria, consisting of a total sample size of 36,776 participants. Results: All studies demonstrated meaningful reductions in body weight, body mass index, and hemoglobin A1c in participants taking glucagon-like 1 receptor agonists. Semaglutide showed the most consistent and substantial evidence for weight loss, followed by liraglutide, then dulaglutide. Discussion: Findings in this review indicate that glucagon-like 1 receptor agonists are effective at mitigating antipsychotic induced weight gain. Semaglutide demonstrated the greatest efficacy in reducing weight. Further large-scale trials are needed to evaluate the long-term outcomes of these medications in this population.Nursin
Animal Assisted Therapy and Healthcare Workers: A Systematic Review [poster]
No full textIntroduction: Healthcare workers (HCW) in modern society are plagued with emotional exhaustion, declining rates of job satisfaction, and increasing levels of anxiety. The crisis HCWs face, driven by increasing stressors, shapes the prevalence of burnout. This systematic review evaluates current research on Animal-Assisted Therapy (AAT) as an intervention for HCW. Methods: Guided by Jean Watson’s Theory of Human Caring, the review synthesizes research from seven peer-reviewed studies conducted between 2020 and 2025 throughout the United States. Research employs numerous techniques, including qualitative, quasi-experimental, and observational designs, and incorporates opinions and descriptors from 785 participants across all seven studies. Results: Studies showcase positive correlations between reduced anxiety, improved mood, and preferred method of treatment for HCWs. Research limitations throughout this research discuss the small sample sizes, geographic concentration, and reliance on self-reported data. Discussion: The overall message of the findings of this research for HCWs describes AAT as an initiative to promote well-being and retention of HCWs. AAT as an intervention is already changing the landscape of patient care, and when HCWs are afforded this therapeutic technique, a cultural transformation will occur.Nursin
Everything Hurts
No full textWith the swift evolution of artificial intelligence, a sudden and terrifying shift has emerged in the arts, entertainment, and human relationships. This capstone explores this topic through my own short film with a greater emphasis on the psychological impact of these technological advances and how far someone could go for a connection through a digital and inhuman medium. The short film is titled Everything Hurts, and it follows Marty, an aimless college student who finds solace in an AI recreation of his deceased girlfriend, Angela. With Marty immersed in this artificial intelligence, his friends attempt to redirect him to a real-life relationship with Lexi, only to find themselves sent down a rabbit hole of conspiracy and murder as the AI degrades over time. This project aims to dissect the negative impact of artificial intelligence both in the entertainment industry and in human relationships, and furthermore, demonstrate how filmmaking has continuously been able to depict human emotion in an organic way without the assistance of generative artificial intelligence.Englis
Criminal investigative failures: A network analysis
No full textThe police investigative function is a key component of the criminal justice system. Wrongful convictions and investigative failures can cause significant and long-lasting damage at all levels of society. These failures are typically the product of multiple interconnected factors, which can be generally grouped into structural, organizational, and personal categories. Using network analysis, we explore the relationships between the causal factors associated with investigative failures in 50 murder and rape cases, most of them wrongful convictions. We identified 40 different causal factor types. Some of these functioned as catalysts (initiators that cascaded into other causal factors), some as brokers (bridges between factors), and others as products (the end result of the causal factor chain). Understanding the architecture of the network – its components and relationships – provides a means for mitigating the risk of criminal investigative failures.This research was funded with a grant (2014-IJ-CX-0037) awarded by the National Institute of
Justice (NIJ) through their Sentinel Events initiative. The findings and conclusions of this article
are those of the authors and do not necessarily reflect those of NIJ