Digital Commons Network^™

09.08.2025 Ored Connect, Liz Williamson

ORED Newsletter

• Researcher training opportunities
• Project to increase PhD student success
• ORED online training opportunities

Advancing Ckd Diagnosis: Race-Free Egfr, Cystatin C, And Genetic Insights, Halah Tariq Albar

Saudi Toxicology Journal

Globally, the rates of chronic kidney disease (CKD) are increasing due to the increasing incidence of hypertension, obesity, and diabetes mellitus. Early detection and treatment of kidney disease are essential in improving health outcomes. Estimate glomerular filtration rate (eGFR) is used to diagnose, stage, and manage CKD. CKD biomarkers are broadly categorized into traditional (serum creatinine), emerging (cystatin C), and disease specific (Interleukin-6). The purpose of this narrative review is to synthesize the current evidence regarding the use of eGFR in diverse populations. The initial eGFR equations included race variables, which created a controversial debate about their relevancy and has …

Dynamical Regulation Of Blood Pressure And Cognitive Function, Joshua Sweigert, Tara Gruenewald, Margie Lachman, Teresa Seeman, Maxine Weinstein, Tse-Hwei Choo, Martina Pavlicova, Ramakrishna Mukkamala, Richard P. Sloan

Psychology Faculty Articles and Research

BACKGROUND

Blood pressure (BP) is not steady. It varies over intervals from months to consecutive cardiac cycles, and this variation contains meaningful information beyond mean BP. Variability over multiple clinic visits (VVV-BP) and during 24-h ambulatory monitoring (ABPV) is positively related to risk of stroke and coronary artery disease and negatively associated with cognitive performance. Beat-to-beat BP variation, often quantified as low frequency variability (0.04–0.15 Hz, LF-BPV), is less well-studied. Here, we examine the relationship between LF-BPV and cognitive outcomes in 1953 participants from the Midlife in the US study.

METHODS

Participants completed the Brief Test of Adult Cognition by …

Air Pollution And Diseases: Signaling, G Protein-Coupled And Toll Like Receptors, Isabella Cattani-Cavalieri, Katrina F. Ostrom, Jordyn Margolis, Rennolds S. Ostrom, Martina Schmidt

Pharmacy Faculty Articles and Research

Air pollution is a significant public health issue that impacts lung health, particularly in vulnerable populations such as children, the elderly, and individuals with pre-existing respiratory conditions. Both natural and anthropogenic sources of air pollution give rise to a variety of toxic compounds, including particulate matter (PM), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and polycyclic aromatic hydrocarbons (PAHs). Exposure to these pollutants is strongly associated with the development and exacerbation of respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), lung cancer, and idiopathic pulmonary fibrosis (IPF). Notably, early life exposure to pollutants such as …

Lewy Body Dementia Promotion By Air Pollutants, Xiaodi Zhang, Haiqing Liu, Xiao Wu, Longgang Jia, Kundlik Gadhave, Lena Wang, Kevin Zhang, Hanyu Li, Rong Chen, Ramhari Kumbhar, Ning Wang, Chantelle E Terrillion, Bong Gu Kang, Bin Bai, Minhan Park, Ma Cristine Faye Denna, Shu Zhang, Wenqiang Zheng, Denghui Ye, Xiaoli Rong, Liu Yang, Lili Niu, Han Seok Ko, Weiyi Peng, Lingtao Jin, Mingyao Ying, Liana S Rosenthal, David W Nauen, Alex Pantelyat, Mahima Kaur, Kezia Irene, Liuhua Shi, Rahel Feleke, Sonia García-Ruiz, Mina Ryten, Valina L Dawson, Francesca Dominici, Rodney J Weber, Xuan Zhang, Pengfei Liu, Ted M Dawson, Shizhong Han, Xiaobo Mao

Faculty, Staff and Student Publications

Evidence links air pollution to dementia, yet its role in Lewy body dementia (LBD) remains unclear. Here we showed in a cohort of 56.5 million individuals across the U.S. that PM2.5 exposure raises LBD risk. Mechanistically, we found PM2.5 exposure led to brain atrophy in wild-type mice, an effect not seen in α-synuclein (αSyn)-deficient mice. PM2.5 exposure generated a highly pathogenic αSyn strain, PM-PFF, with enhanced proteinase K-resistance and neurotoxicity, resembling αSyn LBD strains. PM2.5 samples from China, the U.S., and Europe consistently induced proteinase-resistant αSyn strains and in vivo pathology. Transcriptomic analyses revealed shared responses between PM2.5-exposed mice and …

The Causal Pivot: A Structural Approach To Genetic Heterogeneity And Variant Discovery In Complex Diseases, Chad A Shaw, C J Williams, Taotao Tan, Daniel Illera, Nicholas Di, Joshua M Shulman, John W Belmont

Center on Aging Staff Publications

We present the Causal Pivot (CP) as a structural causal model (SCM) for analyzing genetic heterogeneity in complex diseases. The CP leverages an established causal factor or factors to detect the contribution of additional suspected causes. Specifically, polygenic risk scores (PRSs) serve as known causes, while rare variants (RVs) or RV ensembles are evaluated as candidate causes. The CP incorporates outcome-induced association by conditioning on disease status. We derive a conditional maximum-likelihood procedure for binary and quantitative traits and develop the Causal Pivot likelihood ratio test (CP-LRT) to detect causal signals. Through simulations, we demonstrate the CP-LRT’s robust power and …

How Life-Cycle Real-World Evidence Can Bridge Evidentiary Gaps In Precision Oncology, Emanuel Krebs, Deirdre Weymann, Tania M. Bubela, Dean A. Regier

Office of the Provost

Precision oncology uses omics-based diagnostic technologies to inform histology-agnostic cancer treatment. To date, health system implementation remains limited owing to high uncertainty in regulatory and reimbursement evidence submissions. In this perspective, we describe a life-cycle approach to the evaluation of precision oncology technologies that addresses evidentiary uncertainty and is grounded in real-world evidence (RWE) derived using data routinely collected by healthcare systems. We consider the role for RWE in international regulatory and reimbursement decision-making, review common biases for observational precision oncology evaluations, make specific recommendations for RWE study design and analysis, and specify healthcare system requirements for data collection. We …

Emerging Clinical Role Of Tavapadon, A Novel Dopamine Partial Agonist, In The Treatment Of Parkinson’S Disease, Alan D. Kaye, Bennett M. Ford, Brennan M. Abbott, Kalob M. Broocks, Sofia Novacic, Sahar Shekoohi

School of Medicine Faculty Publications

Tavapadon, a novel oral dopamine-D1R/D5R partial agonist, has been studied in recent years for the treatment of late-stage development Parkinson’s disease (PD). Levodopa, a dopamine precursor that currently remains the gold-standard first-line therapy for PD motor symptoms, serves as a benchmark against emerging dopaminergic agents. By selectively activating D1-family receptors on direct-pathway medium neurons, Tavapadon differs in that it delivers levodopa-level motor benefit while avoiding its many D2R/D3R-mediated adverse effects. In placebo-controlled trials, Tavapadon produced clear, clinically meaningful gains in motor function and day-to-day activities, as captured by the Unified Parkinson’s Disease Rating Scale (UPDRS). Recent late-stage results have revealed …

09.02.2025 Ored Connect, Liz Williamson

ORED Newsletter

• NIH Specific Aims Statement RED Talk
• NSF Research Security Training 

Deep Learning-Driven Proteomics Analysis For Gene Annotation In The Renin-Angiotensin System, Mortaza Eivazi, Kamran Hosseini, Shahin Alipanahi, Huijing Xia, Luke Restivo, Ayushi Patel, Mahdieh Gozali, Tahereh Ebrahimi, Amy Scarborough, Vahideh Tarhriz, Eric Lazartigues

School of Medicine Faculty Publications

The renin-angiotensin system (RAS) is central to cardiovascular diseases such as hypertension and cardiomyopathy, yet the functions of many RAS genes remain unclear. This study developed a multi-label deep learning model to systematically annotate RAS gene functions and elucidate their roles in biological pathways. A total of 39,463 RAS-related publications from PubMed and PMC were processed into text format. Feature matrices were generated using TF-IDF and token processing, followed by dimensionality reduction via Principal Component Analysis (PCA). A Multi-Layer Perceptron (MLP) was applied for multi-label classification, with performance evaluated using Precision, F1-Score, Ranking Loss, and ROC-AUC metrics. The model outperformed …

Childhood Loneliness And Cognitive Decline And Dementia Risk In Middle-Aged And Older Adults, Jinqi Wang, Danyang Jiao, Xiaoyu Zhao, Yixing Tian, Haibin Li, Xia Li, Chen Sheng, Lixin Tao, Hui Chen, Zhiyuan Wu, Xiuhua Guo

Research outputs 2022 to 2026

Importance: Adult loneliness has been linked to cognitive decline and dementia risk, but the long-term implications of childhood loneliness remain underexplored. Objectives: To investigate whether childhood loneliness is associated with cognitive decline and dementia risk and whether adult loneliness mediates or modifies these associations. Design, Setting, and Participants: This cohort study used data from the China Health and Retirement Longitudinal Study, a nationally representative cohort study conducted between June 1, 2011, and December 31, 2018, with a maximum follow-up of 7 years. Data analyses were performed from October 1, 2024, to January 15, 2025. Exposure: Childhood loneliness was defined as …

Age-Dependent Brain Responses To Mechanical Stress Determine Resilience In A Chronic Lymphatic Drainage Impairment Model, Zachary Gursky, Zohaib Nisar Khan, Sunil Koundal, Ankita Bhardwaj, Joaquin Caceres Melgarejo, Kaiming Xu, Xinan Chen, Hung-Mo Lin, Xianfeng Gu, Hedok Lee, Jonathan Kipnis, Yoav Dori, Allen Tannenbaum, Laura Santambrogio, Helene Benveniste

2020-Current year OA Pubs

The outflow of 'dirty' brain fluids from the glymphatic system drains via the meningeal lymphatic vessels to the lymph nodes in the neck, primarily the deep cervical lymph nodes (dcLN). However, it is unclear whether dcLN drainage is essential for normal cerebral homeostasis. Using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and computational fluid dynamics, we studied the impact of long-term mechanical stress from compromised dcLN drainage on brain solute and fluid outflow in anesthetized rats. We found that in young, but not middle-aged, rats, impairment of dcLN drainage was linked to moderately increased intracranial pressure and the emergence of extracranial …

Applying Artificial Intelligence And Chatbots To Enhance Collection Development In Health Sciences Libraries, Ivan Portillo, David Carson

Library Presentations, Posters, and Audiovisual Materials

The continuous advancement of artificial intelligence (AI) and large language models (LLMs) has presented several opportunities for librarians to reduce their workload and become more efficient. This session will explore the potential of generative AI chatbots in assisting health sciences librarians with collection development. Two methods that will be discussed include the potential of AI to help discover new titles and how AI can evaluate your library collection for any potential gaps based on a college program’s curriculum.

Women's Unique Health Needs And The Sustainable Development Goals: A Meeting Report From The 79th United Nations General Assembly Science Summit, Irene Aninye, Sarah Chew, Nicole Althaus, Michele Barry, Ru-Fong Cheng, Carolyn Harris, Eleanor Nwadinobi, Beth Battaglino, Aisha Brooks, Marleen Temmerman

Centre of Excellence in Women and Child Health

Biological sex, hormones, and gender uniquely affect health and disease, often resulting in disparities for women across the lifespan and from different racial and ethnic groups, geographical locations, and socio economic backgrounds. Without intentional investment and infrastructure to support good health and wellbeing for women,half of the world’s population remains vulnerable to preventable morbidity and mortality. The Society for Women’s Health Research and ECHAlliance–The Global Health Connector convened a women’s health programas part of the 10th Annual Science Summit during the United Nations 79th General Assembly. This hybrid event was held in New York, NY, (USA) and virtually in September …

Enhancing Preparedness: A Genetic Study Of Sar-Cov-2 And Other Microbial Public Health Threats In Wastewater From A College Town, Christian N. Hutchinson

Master's Theses

Problem

The SARS-CoV-2 (COVID-19) pandemic revealed both the systemic vulnerabilities of our healthcare system as well as the importance of timely, localized data for informing public health responses. Traditional testing approaches were essential but often failed to capture the full extent of viral spread, especially in those with mild or asymptomatic conditions that relied on at home testing. This underreporting hindered effective allocation of resources and made developing effective intervention strategies difficult. We also realized the potential for wastewater surveillance to be applied to tracking antimicrobial resistance gene markers. Taken together, this approach should have important implications for improving public …

Variational Temporal Deconfounder Network For Individualized Treatment Effect Estimation With Longitudinal Observational Data, Hao Dai, Yu Huang, Yuxi Liu, Xing He, Jingchuan Guo, Mattia Prosperi, Jiang Bian

Faculty, Staff and Student Publications

Objective: By leveraging real-world electronic health record (EHR) data, this study set out to estimate individualized treatment effects (ITE) in longitudinal observational settings to advance personalized medicine, addressing key challenges that are often observed in real-world clinical scenarios and pose statistical challenges, including hidden confounding and dynamic treatment regimens.

Methods: We propose the Variational Temporal Deconfounder Network (VTDNet), a novel framework designed to account for time-varying hidden confounding using a variational recurrent transformer-based autoencoder. Specifically, VTDNet comprises three critical components: a temporal Encoder-Decoder structure to capture hidden representation, a Treatment Block that captures interdependencies among multiple treatments, and a Potential …

"I Probably Wouldn't Be As Happy": Childhood Parental Separation And Posttraumatic Growth Narratives From Eight College Students, Meagan C. Arrastia-Chisholm, Hoa Nguyen, Africa Pippin, Heather M. Kelley Ph.D.

Journal of Higher Education & Student Affairs

Parental separation during childhood leads to long-lasting psychological and socioemotional impact on the lives of emerging adults as they transition into higher education. The long-term effects of childhood parental separation on college students' academic performance, physical health, and overall mental wellbeing are well-documented. However, students can develop resilience to cope with challenging family and life experiences and even demonstrate post-traumatic growth. Post-traumatic growth refers to the positive changes and experiences college students discover after enduring life disruptions, such as being separated from their parents at an early age. To better understand the connection between parental separation and posttraumatic growth, a …

High-Fidelity Finite Element Modeling Technique To Improve Sensitivity To Bone Tissue Changes Of Older Adults With Obesity Undergoing Intensive Lifestyle Intervention, Michael A K Liebschner, Daeseung Kim, Nina Klonis, Giulia Gregori, Reina Armamento-Villareal, Clifford Qualls, Dennis T Villareal

Faculty, Staff and Students Publications

Introduction: Obesity presents a significant health risk for the aging population. Research shows that weight loss and regular exercise can greatly improve the functional status of older adults who are obese. However, weight loss may also result in a decrease in bone mass. To properly assess changes in fracture risk due to lifestyle interventions, a direct biomechanical evaluation of bone strength and fracture risk at metabolically active sites is essential.

Methods: Computed tomography scans taken at two different time points of ten human volunteers provided the foundation for this study. A high-fidelity segmentation and modeling approach was taken to generate …

A Consensus Guide To Preclinical Indirect Calorimetry Experiments, Alexander S Banks, David B Allison, Thierry Alquier, Ansarullah, Steven N Austad, Johan Auwerx, Julio E Ayala, Joseph A Baur, Stefania Carobbio, Gary A Churchill, Morten Dall, Rafael De Cabo, Jose Donato, Nathalia R V Dragano, Carol F Elias, Anthony W Ferrante, Brian N Finck, Jose E Galgani, Zachary Gerhart-Hines, Laurie J Goodyear, Justin L Grobe, Rana K Gupta, Kirk M Habegger, Sean M Hartig, Andrea L Hevener, Steven B Heymsfield, Corey D Holman, Martin Hrabě De Angelis, David E James, Lawrence Kazak, Jae Bum Kim, Martin Klingenspor, Xingxing Kong, Sander Kooijman, Louise Lantier, K C Kent Lloyd, James C Lo, Irfan J Lodhi, Paul S Maclean, Owen P Mcguinness, Gema Medina-Gómez, Raghavendra G Mirmira, Christopher D Morrison, Gregory J Morton, Timo D Müller, Yoshihiro Ogawa, David Pajuelo-Reguera, Matthew J Potthoff, Nathan Qi, Marc L Reitman, Patrick C N Rensen, Jan Rozman, Jennifer M Rutkowsky, Kei Sakamoto, Philipp E Scherer, Gary J Schwartz, Radislav Sedlacek, Mohammed Selloum, Saame Raza Shaikh, Shuai Chen, Gerald I Shulman, Vojtěch Škop, Alexander A Soukas, John R Speakman, Bruce M Spiegelman, Gregory R Steinberg, Katrin J Svensson, John P Thyfault, Tony Tiganis, Paul M Titchenell, Nigel Turner, Licio A Velloso, Antonio Vidal-Puig, Christopher S Ward, Ashley S Williams, Christian Wolfrum, Allison W Xu, Ying Xu, Juleen R Zierath, International Indirect Calorimetry Consensus Committee (Iiccc)

Children’s Nutrition Research Center Staff Publications

Understanding the complex factors influencing mammalian metabolism and body weight homeostasis is a long-standing challenge requiring knowledge of energy intake, absorption and expenditure. Using measurements of respiratory gas exchange, indirect calorimetry can provide non-invasive estimates of whole-body energy expenditure. However, inconsistent measurement units and flawed data normalization methods have slowed progress in this field. This guide aims to establish consensus standards to unify indirect calorimetry experiments and their analysis for more consistent, meaningful and reproducible results. By establishing community-driven standards, we hope to facilitate data comparison across research datasets. This advance will allow the creation of an in-depth, machine-readable data …

Bone Quality Response To Lifestyle Intervention In Older Adults With Obesity (Limb-Q Trial): A Randomised Controlled Trial, Giulia Gregori, Sanjay Mediwala, Michael Liebschner, Daeseung Kim, Mon S Bryant, Nina Klonis, Reina Armamento-Villareal, Clifford Qualls, Dennis T Villareal

Faculty, Staff and Students Publications

Background: Lifestyle interventions for weight loss might exacerbate age-related bone loss and osteoporosis. However, there is limited knowledge about their effects on bone quality. We examined whether lifestyle intervention can preserve or enhance bone quality, despite reductions in bone mineral density.

Methods: The Lifestyle Intervention to Improve Bone Quality (LIMB-Q) study was a randomised controlled trial conducted at Baylor College of Medicine and the Michael E DeBakey VA Medical Center (Houston, TX, USA) including older adults (aged 65-85 years) with obesity (BMI ≥30 kg/m2). Participants were randomly assigned to receive either an intensive lifestyle intervention (intensive lifestyle group, consisting of …

Expression Graph Network Framework For Biomarker Discovery, Yang Liu, Jason Huse, Kasthuri Kannan

Faculty, Staff and Student Publications

Biomarker discovery for complex diseases, such as cancer, hinges on uncovering molecular signatures that capture intricate, interconnected relationships within biological data-a challenge that traditional statistical and machine learning methods often fail to meet due to the complexity of high-dimensional gene expression profiles. To overcome this, we introduce the expression graph network framework (EGNF). This cutting-edge graph-based approach integrates graph neural networks with network-based feature engineering to enhance the predictive identification of biomarkers. EGNF constructs biologically informed networks by combining gene expression data and clinical attributes within a graph database, utilizing hierarchical clustering to generate dynamic, patient-specific representations of molecular interactions. …

Auprc: A Metric For Evaluating The Performance Of In-Silico Perturbation Methods In Identifying Differentially Expressed Genes, Hongxu Zhu, Amir Asiaee, Leila Azinfar, Jun Li, Han Liang, Ehsan Irajizad, Kim-Anh Do, James P Long

Faculty, Staff and Student Publications

In silico perturbation models, computational methods that can predict cellular responses to perturbations, present an opportunity to reduce the need for costly and time-intensive in vitro experiments. Many recently proposed models predict high-dimensional cellular responses, such as gene or protein expression to perturbations such as gene knockout or drugs. However, evaluating in silico performance has largely relied on metrics such as $R^{2}$, which assess overall prediction accuracy but fail to capture biologically significant outcomes like the identification of differentially expressed (DE) genes. In this study, we present a novel evaluation framework that introduces the AUPRC metric to assess the precision …

Braingenebot: A Framework For Variant Prioritization And Generative Pretrained Transformer-Informed Interpretation Across Polygenic Risk Score Studies, Gang Qu, Nitesh Enduru, Xinyi Liu, Xiaoqian Jiang, Zhongming Zhao

Faculty, Staff and Student Publications

Polygenic risk scores (PRS) are widely used to assess genetic susceptibility in Alzheimer's disease (AD) research. However, the rapid expansion of PRS studies has led to dataset-specific biases-stemming from factors like population makeup, genotyping methods, and analysis pipelines-that result in inconsistent variant prioritization and limit generalizability and reproducibility. To address these challenges, we propose a transductive learning framework that integrates multiple PRS datasets for more robust risk variant prioritization, incorporating genome-wide association study (GWAS) priority scores as biologically informed priors. Additionally, we introduce BrainGeneBot, an AI-driven tool leveraging generative pretrained transformers with retrieval-augmented generation technology to streamline genomic analyses in …

Access To Information On Toddler Family Development Program And Family Participation In Child Growth And Development, Dita Dhammayanti, Demsa Simbolon, Lissa Ervina, Yusran Fauzi

Kesmas

The comprehension of the Toddler Family Development (TFD) Program among families in Indonesia remains limited, likely due to insufficient access to information and low participation rates. Limited participation can negatively affect a family’s ability to support optimal child growth and development. This study examined the relationship between access to information on the TFD Program and family participation in child growth and development. Using secondary data from the 2019 Program Performance and Accountability Survey in Indonesia, the cross-sectional analysis included 21,497 respondents. The results revealed an association between access to information on the TFD Program and family participation in child growth …

Can Artificial Intelligence Models Provide Reliable Medical Counselling To Fertility Patients?, Idan Alcalay, Ariel Weissman, Hadas Ganer Herman, Avi Tsafrir, Matan Friedman, Eran Weiner, Raoul Orvieto, Nikolaos P. Polyzos, Michael H. Dahan, Alex Polyakov, Robert Fischer, Sandro C. Esteves, Baris Ata, Jason M. Franasiak, Yossi Mizrachi

Department of Obstetrics and Gynecology Faculty Papers

RESEARCH QUESTION: Can generative artificial intelligence (AI) models provide reliable counselling to fertility patients regarding real-world clinical questions?

DESIGN: In this cross-sectional study, 12 clinical questions were developed to reflect common, real-life dilemmas encountered during fertility workup and treatment. Responses to each question were generated by two experienced fertility specialists, and two AI models - ChatGPT and Gemini. Eight leading internationally recognized fertility experts, blinded to the source of each reply, independently rated all the responses on a scale from 1 (strongly disagree) to 10 (strongly agree). Ratings were compared across all four repliers using non-parametric statistical tests.

RESULTS: The …

Exploring Stunting In South Kalimantan Province Using R Programming-Based Data Visualization, Muhammad Hudaya, Wahyudin Nor, Mellani Yuliastina, Muhammad Nordiansyah

Kesmas

South Kalimantan Province continues to face the challenge of relatively high stunting prevalence despite being endowed with abundant coal resources that could serve as a source of funding for public health. Therefore, this study aimed to examine differences in stunting prevalence among cities, mining districts, and non-mining districts in South Kalimantan to raise stakeholder awareness of disparities across these regional types. This study was conducted between April and December 2024, using secondary data obtained from the Indonesian Ministry of Health and the South Kalimantan Provincial Government. R programming was used to process the data, generate visualizations, and perform analysis of …

Hurricane Katrina Archive: Faculty Publications Bibliography 2015-2019, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 19 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2015 and December 2019.

Hurricane Katrina Archive: Faculty Publications Bibliography 2020-2025, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 10 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2020 and August 2025.

Hurricane Katrina Archive: E-Books And E-Journals A To Z Bibliography 2020-2025, Lsu Health Sciences Center - New Orleans Libraries, Elizabeth H. Holt

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 43 electronic books and edited collections created on the topic of Hurricane Katrina by authors and others affiliated with LSU Health Sciences Center - New Orleans between September 2005 and August 2025.

Empowering Youth Tackle Football Athletes: A Content Analysis Of Nonlinear Pedagogy’S Influence On Autonomy And Practical Applications In Youth Tackle Football, Benjamin Jay Andelman

Masters Theses

Youth tackle football offers an environment that promotes both positive mental and physical benefits for young athletes. Despite the positive benefits associated with sports, participation is on the decline. The content analysis found connections between the prevailing prescriptive coaching methods in youth tackle football and the adverse mental effects on young athletes. This study, utilizing a qualitative content analysis of existing academic literature, proposes a practical application of Nonlinear Pedagogical principles in the youth tackle football practice context to develop a coaching model that promotes athlete autonomy, thereby increasing positive mental benefits for the youth athlete. Leveraging Ecological Dynamics, Constraints-Led …