Digital Commons Network^™

Research Participant Interest In Learning Results Of Biomarker Tests For Alzheimer Disease, Spondita Goswami, Sarah M Hartz, Amy Oliver, Sacha Jackson, Tomi Ogungbenle, Alissa Evans, Erin Linnenbringer, Krista L Moulder, John C Morris, Jessica Mozersky

2020-Current year OA Pubs

IMPORTANCE: While available evidence suggests there are not major psychosocial harms of return of research results, there are limited data on uptake of Alzheimer disease (AD) research results or reasons for declining to learn results among participants in AD research studies.

OBJECTIVES: To quantitatively and qualitatively evaluate who declines to learn individual AD biomarker research results and what factors are associated with the decision.

DESIGN, SETTING, AND PARTICIPANTS: This observational cohort study was conducted between November 1, 2020, and April 15, 2024, among participants aged 65 years or older with unimpaired cognition and available biomarker data (apolipoprotein E genotype and …

Introducing A New Polymerase Chain Reaction Panel–Based Cerebrospinal Fluid Evaluation For Encephalitis And Meningitis: Does It Influence Empiric Treatment Duration, Length Of Hospital Stay, And Pathogen-Specific Diagnoses?, Fabian Sidler, Pascal Bittel, Jonas Marschall, Philipp Jent

2020-Current year OA Pubs

We analyzed the impact of a diagnostic meningitis/encephalitis polymerase chain reaction panel. Introducing the test resulted in no significantly shortened empiric antibiotic streptococcal/meningococcal treatment (-1 day [95% confidence interval {CI}, 0-3 days];

Clinical Validation Of A Vaginal Cervical Cancer Screening Self-Collection Method For At-Home Use: A Nonrandomized Clinical Trial, Megan B Fitzpatrick, Colleen Mcnicholas, Lindsay Kuroki, Et Al.

2020-Current year OA Pubs

IMPORTANCE: One-quarter of US women who are at risk for cervical cancer delay screening. Self-collected (SC) cervical screening was recently US Food and Drug Administration (FDA)-approved in the US for use in a health care setting only; an at-home SC option is crucial to address clinic-related barriers to screening.

OBJECTIVE: To clinically validate the use of an SC device that was designed for optimal at-home performance, safety, ease-of-use, and dry storage and transport.

DESIGN, SETTING, AND PARTICIPANTS: This nonrandomized clinical trial used a prospective method comparison study design. Participants aged 25 to 65 years were recruited from 16 clinical sites …

Combining Exercise Training And Testosterone Therapy In Older Women After Hip Fracture: The Step-Hi Randomized Clinical Trial, Ellen F Binder, Peter M Doré, Camelia Guild, Kelly M Monroe, Dominic Reeds, Kenneth B Schechtman, Et Al.

2020-Current year OA Pubs

IMPORTANCE: Despite receiving postacute rehabilitation services, many older women with a recent hip fracture repair are unable to return to their prefracture level of function. Whether testosterone therapy can enhance recovery after hip fracture in older women with persistent mobility impairments has not been fully examined.

OBJECTIVE: To evaluate the effects of a supervised exercise program combined with topical testosterone therapy on functional outcomes in older women with a recent hip fracture.

DESIGN, SETTING, AND PARTICIPANTS: This phase 3 double-blind, placebo-controlled randomized clinical trial, Starting a Testosterone and Exercise Program After Hip Injury (STEP-HI), was conducted at 8 US sites …

High-Dimensional Mediation Analysis For Longitudinal Mediators And Survival Outcomes, Lili Liu, Haixiang Zhang, Yinan Zheng, Tao Gao, Cheng Zheng, Kai Zhang, Lifang Hou, Lei Liu

2020-Current year OA Pubs

Mediation analysis with high-dimensional mediators is crucial for identifying epigenetic pathways linking environmental exposures to health outcomes. However, high-dimensional mediation analysis methods for longitudinal mediators and a survival outcome remain underdeveloped. This study fills that gap by introducing a method that captures mediation effects over time using multivariate, longitudinally measured time-varying mediators. Our approach uses a longitudinal mixed effects model to examine the relationship between the exposure and the mediating process. We connect the mediating process to the survival outcome using a Cox proportional hazards model with time-varying mediators. To handle high-dimensional data, we first employ a mediation-based sure independence …

Early-Life Factors And Body Mass Index Trajectories Among Children In The Echo Cohort, Chang Liu, Katherine Rivera-Spoljaric, Et Al.

2020-Current year OA Pubs

IMPORTANCE: Identifying atypical body mass index (BMI) trajectories in children and understanding associated, modifiable early-life factors may help prevent childhood obesity.

OBJECTIVE: To characterize multiphase BMI trajectories in children and identify associated modifiable early-life factors.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study included longitudinal data obtained from January 1997 to June 2024, from the Environmental influences on Child Health Outcomes (ECHO) cohort, which included children aged 1 to 9 years with 4 or more weight and height assessments. Analyses were conducted from January to June 2024.

EXPOSURES: Prenatal exposure to substances and stress (smoking, alcohol, depression, anxiety), maternal characteristics (prepregnancy …

Simulation-Guided Pan-Cancer Analysis Identifies A Novel Regulator Of Cpg Island Hypermethylation Heterogeneity, Xianglin Zhang, Wei Zhang, Jinyi Zhang, Xiuhong Lyu, Haoran Pan, Tianwei Jia, Ting Wang, Xiaowo Wang, Haiyang Guo

2020-Current year OA Pubs

CpG island hypermethylation, a hallmark of cancer, exhibits substantial heterogeneity across tumors, presenting both opportunities and challenges for cancer diagnostics and therapeutics. While this heterogeneity offers potential for patient stratification to predict clinical outcomes and personalize treatments, it complicates the development of robust biomarkers for early detection. Understanding the mechanisms driving this heterogeneity is essential for advancing biomarker design. Here, simulation-based analyses demonstrate that tumor purity and the high prevalence of low epi-mutation samples significantly obscure the identification of negative, rather than positive, regulators of CpG island hypermethylation, limiting a comprehensive understanding of heterogeneity sources. By addressing these confounders, we …

Three-Year Analysis Of Adult Patients With Relapsed Or Refractory B-Cell Acute Lymphoblastic Leukemia Treated With Brexucabtagene Autoleucel In Zuma-3, Bijal D Shah, Armin Ghobadi, Et Al.

2020-Current year OA Pubs

Brexucabtagene autoleucel (brexu-cel) is an autologous anti-CD19 CAR T-cell therapy approved in the US to treat adults aged ≥18 years (≥26 years in the EU) with relapsed/refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL). Brexu-cel showed an overall complete remission (CR)/CR with incomplete hematologic recovery (CRi) rate of 73% (CR rate 60%) and median overall survival (OS) of 25.4 months in 78 patients with R/R B-ALL after 2 years in ZUMA-3. Here, we report updated outcomes after >3 years median follow-up. As of July 23, 2022, median follow-up in all patients (N = 78) was 41.6 months. Median OS (95% CI) …

Impact Of Chatgpt And Large Language Models On Radiology Education: Association Of Academic Radiology-Radiology Research Alliance Task Force White Paper, David H Ballard, Alexander Antigua-Made, Emily Barre, Elizabeth Edney, Emile B Gordon, Linda Kelahan, Taha Lodhi, Jonathan G Martin, Melis Ozkan, Kevin Serdynski, Bradley Spieler, Daphne Zhu, Scott J Adams

2020-Current year OA Pubs

Generative artificial intelligence, including large language models (LLMs), holds immense potential to enhance healthcare, medical education, and health research. Recognizing the transformative opportunities and potential risks afforded by LLMs, the Association of Academic Radiology-Radiology Research Alliance convened a task force to explore the promise and pitfalls of using LLMs such as ChatGPT in radiology. This white paper explores the impact of LLMs on radiology education, highlighting their potential to enrich curriculum development, teaching and learning, and learner assessment. Despite these advantages, the implementation of LLMs presents challenges, including limits on accuracy and transparency, the risk of misinformation, data privacy issues, …

Trajectories Of Attention Problems In Preschoolers Born Very Preterm., Marie Camerota, Francisco Xavier Castellanos, Brian S. Carter, Jennifer Check, Jennifer Helderman, Julie A. Hofheimer, Elisabeth C. Mcgowan, Charles R. Neal, Steven L. Pastyrnak, Lynne M. Smith, Thomas Michael O'Shea, Carmen J. Marsit, Barry M. Lester

Manuscripts, Articles, Book Chapters and Other Papers

BACKGROUND: Children born preterm are at heightened risk for neurodevelopmental impairment, including specific deficits in attention. Few studies have investigated change over time in attention problems prior to school entry. The current study aims to describe trajectories of attention problems from age 2 through 5 years in a cohort of children born(GA), identify sociodemographic, medical, and neurobehavioral characteristics associated with attention trajectories, and test whether attention problem trajectories predict the risk of a reported attention-deficit/hyperactivity disorder (ADHD) diagnosis.

METHODS: We studied 608 infants from the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study, a prospective, multisite study of …

Maternal Cardiometabolic Risk Factors In Pregnancy And Offspring Blood Pressure At Age 2 To 18 Years., Zhongzheng Niu, Ako Adams Ako, Sarah Dee Geiger, Caitlin G. Howe, Wei Perng, Rachana Singh, Margaret R. Karagas, Amy J. Elliott, Andrea Cassidy-Bushrow, Carlos A. Camargo, Keia Sanderson, Cynthia T. Mcevoy, Emily Oken, Dana Dabelea, Tina V. Hartert, Brian S. Carter, Annemarie Stroustrup, Andrea Lampland, Thomas G. O'Connor, Semsa Gogcu, Mark L. Hudak, Lyndsey E. Shorey-Kendrick, Qi Zhao, Yu Ni, Jeffrey Vanwormer, Assiamira Ferrara, Monique Hedderson, Yeyi Zhu, Akram Alshawabkeh, Jose Cordero, Daphne Koinis-Mitchell, Susan Carnell, Carrie V. Breton, Theresa M. Bastain, Shohreh F. Farzan, Echo Cohort Consortium

Manuscripts, Articles, Book Chapters and Other Papers

IMPORTANCE: Higher blood pressure in early life may signal cardiovascular disease over the life course, but determinants of blood pressure in early life are poorly understood.

OBJECTIVE: To examine the association of maternal cardiometabolic risk factors during pregnancy with offspring blood pressure from age 2 to 18 years and explore whether the association is modified by offspring sex and race and ethnicity.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study analyzed data from the Environmental Influences on Child Health Outcomes program between January 1, 1994, and March 31, 2023. Three common maternal cardiometabolic risk factors during pregnancy were examined: prepregnancy obesity, …

A Scoping Review Of Sexual And Reproductive Health Interventions With Youth In U.S. Juvenile Facilities., April Mcneill-Johnson, Jason Glenn, Nekia Ivory Daniel, Mira Menon, Basil H. Aboul-Enein, Patricia J. Kelly, Megha Ramaswamy

Manuscripts, Articles, Book Chapters and Other Papers

Youth placed in U.S. juvenile detention facilities face multilevel barriers that contribute to disparate sexual and reproductive health (SRH) outcomes when compared to their peers in the general adolescent population. Minimal information is available about evidence-based interventions that have been effective in changing these outcomes. The aim of this scoping review was to focus on the current state of SRH and identify recommendations for SRH care. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for scoping reviews guidelines, we searched electronic databases for publications published through March 2024. The search terms were designed to find intervention studies focusing …

Funding For Public Transportation: Results From A Midwest Exit Poll, Joseph S. Lightner, Greg Vonnahme, Steven Chesnut, Nancy Ziegler, Nathan Nguyen, Christiana Sylvaine, Rian Snead, Jordan A. Carlson, Jannette Berkley-Patton, Amanda Grimes

Manuscripts, Articles, Book Chapters and Other Papers

Public transportation can lead to increases in physical activity, access to jobs, healthcare, and healthy food, and may improve overall health. Funding for public transit is essential for a sustainable transportation system. However, most health studies have not focused on voting behavior as a mechanism for sustaining public transportation. This study employs a cross-sectional, in-person, exit poll of voters at 10 randomly selected polling locations during a local election in 2023 in Kansas City, Missouri. The voter ballot included a question to extend an existing 3/8 cent sales tax for public transportation. Participants (N = 649) overwhelmingly supported (90.6 %) …

Making Tabby, Making Place: Examining A Gullah Geechee Wattle And Tabby Daub Dwelling Through Thin Section Analysis, Jacob E. Hamill

Graduate Masters Theses

Tabby is a building material made from lime, sand, oyster shell, and water that is geographically associated with the Sea Islands of South Carolina, Georgia, and Florida. This material was used from the early 18^th century to end of the American Civil War to construct all-manner of buildings in the Sea Islands region. Enslaved African descendant communities constructed wattle and tabby daub dwellings within plantation landscapes, and these settlements are interpreted as spaces where enslaved people exercised greater spatial autonomy.

This thesis analyzes the remains of a wattle and tabby daub structure located on what was once Old Fort …

Data-Driven Audits: Audit Analytic Platforms And General Ledger Analytic Tools, Daniel E. O'Leary, Vernon J. Richardson, Marcia Weidenmier Watson

Accounting Faculty Publications and Presentations

The future of auditing is a data-driven audit, which extracts and analyzes digital data stored in client accounting systems. To help conduct data-driven audits, audit firms are developing audit analytic platforms (AAPs). This paper focuses on one key application tool of AAPs that analyzes the entire population of general ledger transactions. These general ledger analytics tools (GLATs) use assessment routines to assign a risk score to each transaction, helping guide the auditor’s planning, risk assessment, and selection of high-risk transactions for substantive procedures. GLATs help support audit quality and provide valuable new insights about client operations. We discuss the analytics …

Factors Influencing Community Assembly Of The Amphibian Microbiome In Rochester, Ny, Thomas R. Minahan

Theses

Amphibians are crucial in wetlands and, by extension, our planet. As predator and prey, amphibians serve as keystone species, vital for the continued equilibrium in their wetland ecosystems. However, the global amphibian population is currently threatened by the spread of a pathogenic fungus known as Batrachochytrium dendrobatidis (Bd). Over the past thirty years, Bd has spread worldwide, threatening hundreds of amphibian species. The environmental factors that influence microbial community assembly in amphibians are key to developing interventions that can protect amphibians from disease. This research examines the abiotic and biotic factors influencing microbial community composition in amphibians of Rochester, New …

Ai Emotional Companion App, Ruyi Liu

Theses

"Lumi" is an AI emotional companion app designed to provide personalized, immersive, and emotionally supportive experiences. The project explores how customizable virtual characters can fulfill the growing emotional and social needs of users through multimodal interaction, intimacy-building systems, and gamified engagement. By combining user interviews, competitive analysis, and iterative prototyping, this thesis investigates how design strategies can strengthen the user’s emotional bond with an AI character. The final product presents a flexible platform where users can create unique AI companions, interact in diverse ways, and develop lasting emotional connections. This work contributes to the field of emotional UX and digital …

A Remote Sensing-Based Evaluation Of Road And Electricity Infrastructure Expansion Effects On Development In Sub-Saharan Africa, Tunmise Ibukun Raji

Theses

Sub-Saharan African countries consistently rank low on human development indicators despite decades of international aid and domestic investment. To address these challenges, governments across the region are allocating substantial portions of their national budgets to infrastructure expansion, viewing it as a catalyst for accelerated socio-economic development. However, given severely constrained budgets, these nations often face trade-offs between infrastructure development and investment in other important sectors such as healthcare and education. This highlights the need for infrastructure investments to deliver their anticipated benefits. This dissertation examines the relationship between infrastructure development and socio-economic development in Sub-Saharan Africa, with a particular focus …

Predicting The Probability Of Crime Related Danger In Los Angeles, Joshua Oghenetega Okpako

Theses

This thesis examines the use of advanced machine learning to predict crime danger in Los Angeles, where 2023 violent crime rates (503 per 100,000) surpass the national average (363.8 per 100,000). Rooted in theories like social disorganization and victim vulnerability, it addresses the lack of combined victim-centric modeling by focusing on three questions: (1) Do blended ensemble models outperform individual models in predicting crime danger? (2) Can unsupervised learning techniques enhance supervised models’ accuracy through label generation or augmentation? (3) How can we interpret accurate machine learning models' decision-making processes? Using historical crime data from Los Angeles (2020–2025) and various …

Innovating Criminal Justice: Predictive Analytics For Effective Recidivism Management, Dina Ali Haidar

Theses

Recidivism—the tendency of previously convicted individuals to reoffend—poses significant challenges to criminal justice systems worldwide. In the United States, a study by the Bureau of Justice Statistics revealed that approximately 68% of released prisoners were rearrested within three years, and 83% within nine years (Bureau of Justice Statistics, 2018). These high rates underscore systemic deficiencies in rehabilitation processes and resource allocation. Traditional risk assessment tools often rely on static factors, failing to account for the dynamic and individualized nature of reoffending risks. This limitation highlights the need for innovative, data-driven methodologies to enhance offender management strategies. This study proposes a …

Predicting And Forecasting University Rankings In The Uae Using Machine Learning, Fatma Ibrahim Ahmad

Theses

Higher Education Institutions (HEIs) play a vital role in advancing knowledge economies, and institutional rankings are increasingly used as global benchmarks of academic performance and reputation. In the context of the United Arab Emirates (UAE), enhancing institutional competitiveness in global rankings aligns with national strategies such as UAE Vision 2030 and the Centennial Plan 2071. This research applies machine learning (ML) techniques to develop predictive models that forecast institutional ranking outcomes, enabling data-driven planning and continuous academic improvement. The study utilizes a dataset compiled from the QS World University Rankings (2020–2024), cross- referenced against the institutional listings maintained by the …

Ai-Driven Prediction Of Flight Cancellations: A Machine Learning Approach In Minimizing Airline Disruption, Hind Nasser

Theses

This thesis investigates the use of machine learning to predict flight cancellations, aiming to reduce operational disruption and improve airline decision-making. The research is motivated by the need for more proactive strategies in aviation, where flight cancellations often result in financial losses and customer dissatisfaction. The study is framed within the CRISP-DM methodology and demonstrates how historical flight data can be transformed into actionable insights using structured analytics. The research addresses three core questions: how effectively machine learning can predict cancellations, which evaluation metrics are most suitable in an imbalanced context, and how model outputs can support airline operations. A …

Personalized Nutrition Recommendations For Arab Communities: Transforming Diet And Health Through Machine Learning, Khalfan Aldoobi

Theses

A lack of cultural understanding in traditional nutrition approaches prevents proper adherence to healthy dietary patterns among individuals. The Arab population faces unique challenges due to cultural dietary customs and lifestyle changes that have made obesity and diet illnesses major global public health challenges. The rapid shift to high-calorie but undernourished foods and less physical activity has resulted in alarming rate increases of obesity, cardiovascular diseases, and type 2 diabetes. The lack of cultural understanding in traditional nutrition approaches prevents proper adherence to healthy dietary patterns among individuals. This study focuses to fills the existing gap by applying Artificial Intelligence …

Predicting Student Dropout Risk Using Machine Learning, Fatma Alameri

Theses

Student dropout remains a persistent challenge in higher education, undermining institutional performance, reducing workforce preparedness, and limiting students’ academic and economic opportunities. Accurately identifying students at risk of attrition is complex, due to the interplay of academic, financial, and behavioral factors. This thesis addresses this challenge by applying a combined machine learning framework—integrating both unsupervised and supervised techniques—to predict student dropout using structured, first-year academic and financial data. The study utilizes a comprehensive dataset of 4,424 undergraduate student records from a European higher education institution, covering ten academic years and comprising 35 variables related to academic performance, enrollment behavior, and …

Fake News Detection: Leveraging Natural Language Processing And Machine Learning For Reliable Information Verification, Roshni Rajendra Salve

Theses

This dissertation details the creation and assessment of a machine learning algorithm designed to identify fake news utilizing Natural Language Processing (NLP) methods. The research employs several machines learning models, including Long Short-Term Memory (LSTM) and other deep learning techniques, to detect and classify misleading information. Data is sourced from a variety of platforms, such as social media and online news outlets, to compile a thorough dataset. The data is pre-processed to eliminate noise, address missing values, and extract essential features through techniques like tokenization, stop-word removal, and lemmatization. The performance of the models is evaluated using key metrics such …

Future Unleashed: Reimagining Marketing Strategies With Future Foresight, Afra Sultan Al Suwaidi

Theses

In today’s fast-paced and dynamic business landscape, marketing plays a crucial role in influencing business strategy and decision-making in an organisation. Marketing not only helps organisations identify and anticipate trends, threats, and opportunities, but also enables them to formulate and implement effective strategies to capitalise on these insights and achieve the organisation’s vision and goals. Future Foresight in marketing empowers organisations to stay ahead of the curve and gain a deeper understanding of the target audience and industry landscape. The evolving nature of marketing driven by advancements in technology, particularly artificial intelligence, machine learning, and digital marketing channels, makes it …

Driving Innovations To Secure The Future Of Cell Culture Bioprocessing, Weichang Zhou

Cell Culture Engineering XIX

Please click Additional Files below to see the full abstract

Here Be Dragons: The Barriers Of Korean American Female Leaders In Secondary Schools, Joyce A. Kim

Dissertations

In K-12 public schools, there is a shortage of Korean American women in school leadership roles at the secondary level. This phenomenological study explores the contributing factors to this lack of representation, how institutions can recruit and retain Korean American female leaders, and how school systems can better support them. This study examines the leadership experiences of eight Korean American women. It utilizes the socio-political contexts of Korean patriarchy, the Model Minority Myth, and mentorship to help frame the problem of existing barriers. This study explores the following questions: What factors hinder Korean American women in school leadership? What structural …

Shades Of Families: Exploring Intersectionalities Of Cross-Cultural Parenting Experiences In The U.S., Shu-Han Huang

Dissertations

As multiracial and multicultural families continue to grow across the United States, parents must navigate evolving cultural identities, systemic inequities, and increasing social and emotional pressures. These realities underscore the need for parenting resources that are both culturally responsive and emotionally supportive. This transcendental phenomenological study explored the lived experiences of 11 cross-cultural parents raising children in the U.S., with a focus on how intersecting identities and systemic forces shape parenting practices.

Guided by Critical Multiracial Theory and Intersectionality Theory, this study investigated parenting at the personal, familial, societal, and structural levels. Data were collected through semi-structured interviews and analyzed …

Analyzing The Impact Of Motivational Interviewing In A School Counseling Setting With Academically At-Risk High School Students, Brian Linhart

Dissertations

This study investigates the impact of motivational interviewing (MI) on the academic performance and motivation of academically at-risk high school students over an eight-week period. The primary research questions examine whether there is a statistically significant impact of using MI in a school counseling setting on academic performance and internal motivations. Data collection methods included academic performance, the Self-Reported Academic Beliefs, Behavior, and Self-Efficacy questionnaire, and the MI Pre and Post Meeting Questionnaire to assess students’ motivation and engagement. The study employs a quantitative approach using Friedman’s rank sum test and a paired t-test with a Wilcoxon Signed-Rank test, to …