Health Scholar Showcase

Permanent URI for this collectionhttps://hdl.handle.net/10877/16500

The Health Scholar Showcase is an annual event hosted by Texas State University’s Translational Health Research Center, which seeks to improve health by connecting faculty and community partners to engage in innovative research. Health Scholar Showcase highlights some of the best health research happening on campus.

Learn more about Health Scholar Showcase: https://healthresearch.txst.edu/events/health-scholar-showcase.html

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Recent Submissions

Now showing 1 - 20 of 90
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    The Predictive Factors of Hospital Bankruptcy: A Longitudinal Analysis
    (2024-03) Beauvais, Brad; Ramamonjiarivelo, Zo; Kruse, C. Scott; Fulton, Lawrence; Shanmugam, Ram; Sharma, Arvind; Tomic, Aleksander
    This study develops an explanatory and predictive logistic model for hospital bankruptcy utilizing only 8 financial and hospital-level variables (drawing from 3,091 hospitals spanning 2008-2021). This robust tool may prove useful to healthcare leaders to more accurately assess and predict financial distress and bankruptcy in their own institutions in the future.
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    A Study of Weight Stigma, Body Appreciation, and Disordered Eating Behaviors among Promotores and Community Health Workers​ in Texas
    (2024-03) Johnson, Cassandra M.; Biediger-Friedman, Lesli; Menge, Lindsey; Butler, Lauren; Lang, Julianne
    Weight stigma, a form of discrimination, affects around 40% of the US population. Previous research suggests that weight stigma is: - negatively associated with body appreciation, an indicator of positive body image. - positively associated with disordered eating behaviors. Due to systemic inequities, racial and ethnic minority groups, including persons of Mexican heritage, may be more vulnerable to weight stigma. Promotores and community health workers (CHWs) serve a dual role as healthcare provider and community member, particularly in Hispanic communities in Texas (TX).  A formative study of weight stigma among promotores and CHWs is important to developing systems level, destigmatizing community-engaged interventions in TX.
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    Texas Community Health News
    (2024-03) Carter, Daniel; Fox, Kym
    Supporting Texas' health news ecosystem by creating resources, sharing expertise and training the next generation of data-driver reporters.
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    The Role of STEM Self-Efficacy, Research Confidence, and Belonging in Student Development: Fostering STEM Workforce Development Through an Institutional STEM Conference
    (2024-03) Chang, Carolyn
    The United States science, technology, engineering, and mathematics (STEM) workforce stimulates innovation and provides significant contributions to the nation. As science and technology advance, increasing demand for technically skilled employees follows. Today, almost a quarter (24%) of the U.S. workforce is employed in STEM occupations (NCSES, 2023).​ ​Representation of different groups based on sex, race or ethnicity, and disability status varies throughout the STEM workforce, with representation in STEM occupations unevenly distributed for these groups compared to all the working age population (NCSES, 2023). As the workforce demand in STEM continues to increase, along with a push for better representation among different groups, interventions to support STEM student career development are needed.​ Although research has demonstrated the impact of research experiences on degree and career plans, the benefits of attending and presenting research at professional conferences has been minimally investigated (Casad, et al., 2016). These few studies highlight the effectiveness of student professional conferences as an intervention that increases representation and success of underrepresented minority (URM) students in science. As travel to national conference is cost-prohibitive for many students, we sought out to investigate the impact that a student-focused institutional STEM conference intervention would have on student science self-efficacy, research confidence, sense of belonging in STEM. We also evaluated additional outcome measures related to education and career.
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    Alliance of Researchers in Aging
    (2024-03) Hee Chee, Kyong; Deason, Rebecca; Adi, Nadim; Westerberg, Carmen
    The Alliance of Researchers in Aging (ARIA) supports interdisciplinary research on cognition, cognitive decline and dementia, mental health, caregiving, and physical, social, and spiritual wellbeing in later stages of the life course. ARIA is committed to enhancing wellbeing among older adults in Central Texas and beyond through research, education, and service through partnerships with community stakeholders. ARIA began in May 2019 with 12 TXST faculty members. Today, ARIA consists of 16 members, 6 affiliates, and 5 community partners: Members represent 13 departments/schools and 5 laboratories in San Marcos and Round Rock. ARIA is currently led by Executive Committee comprising Chair, Associate Chair, Communications Coordinator, and Outreach Coordinator.
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    Increasing Texas Small Business Disaster Resilience: BeforeDuringAfter.com
    (2024-03) Davio, Rebecca; Pantuso, Matt
    Small businesses have limited financial resources. There are also few information resources targeted specifically at small businesses. Because of their connections to their community, small businesses can act as force multipliers before, during, and after disasters. To do that, they need to know what to do throughout the disaster cycle. Our research aims to provide small businesses with that information to improve their resilience and the resilience of everyone in their communities.
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    A Pilot Study Introducing How Rural Texas Librarians Can Convene Community Resiliency Collaborations
    (2024-03) Eger, Elizabeth; Long, Rex; McNally, Allister; Tonciu, Anca; Vasallo, Johnny; Lamper, Rowan
    Our pilot project incorporated Communication Studies theories of community collaboration to adapt the COPEWELL (Composite of Post-Event Well-Being) framework to address resiliency planning in rural Texas communities. This project positioned Library Directors from two rural Texas libraries as community conveners for resiliency planning. Through our partnership with Maria Freed of the Texas State Library and Archives Commission (TSLAC), 34 libraries expressed interest in participating in our pilot project. The Pottsboro Library in Pottsboro, TX, and the Lee-Bardwell Public Library in Gladewater, TX, were selected as finalists after our interviews with semi-finalists. Working with the Library Directors, we utilized requisite diversity(Heath & Isbell, 2017) to assemble stakeholders in each community to best represent a variety of interests, identities, and perspectives. This approach led to valuable conversations and insights, and the development of actionable next steps to address core community needs. Our data collection process with both libraries and their stakeholders included: •Two 90-minute focus groups •A COPEWELL self-assessment adapted into survey format (20-30 minutes) •Individual exit interviews with stakeholders and librarians (60-80 minutes) Our project also developed best practices and lessons learned that librarians and researchers can use in adapting the COPEWELL framework and addressing community resiliency in their areas. Across both project sites, we found a need for increased and improved communication between the communities and local governments, and that local stakeholders should collaborate on grants and create initiatives to implement community resiliency goals. This poster will highlight site-specific insights and our overall takeaways and recommendations for utilizing our community resiliency collaboration process. Use the link or QR code associated with each section to access our applied reports for further reading. This project has been made possible through our partnership with TXST's Translational Health Research Center.
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    Center for Analytics and Data Science
    (2024-03) Eken, Tahir; Hutchins, Maggie
    We are a university-level center with faculty from every college. Our core affiliate faculty include methods experts in areas such as statistics, optimization, artificial intelligence and computing in addition to domain experts from agriculture, criminal justice, engineering, geography, and health, among others.
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    Mapping Resilience for a Transdisciplinary Research Conceptualization: An AI-Augmented Semi-Systematic Review of 50 Years of Resilience Literature
    (2024-03) Ekren, Elizabeth; Tomasso, Maria; Villagran, Melinda
    Resilience is an increasingly common research topic across disciplines, but it is often conceptualized or applied differently. This leads to difficulties defining, planning, emphasizing, and measuring components of resilience. Prior work attempting to synthesize resilience research is constrained by scope or discipline. PURPOSE OF PROJECT 1 Address prior gaps using AI-augmented approaches to review content of 50 years of multidisciplinary resilience research. 2 Provide a methodological blueprint for large-scale literature reviews and text analyses using AI-augmented processes 3 Help all resilience researchers make sense of existing resilience conceptualizations to make more informed research choices
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    Optimizing Personalized Lung Cancer Screening Policies: A Markov Chain Approach to Cost-Effectiveness Analysis for Patients with Lung Nodules
    (2024-03) Zhu Fainman, Emily; Su, Qiang; Liu, NaiJia; Wu, Ting; Zhu, YuFeng
    The incidence and mortality rates of lung cancer globally, including in China [1], are alarmingly high, with late-stage diagnoses resulting in a dismal five-year survival rate of 17.4% [2]. Early detection through screening is crucial, enabling timely intervention, particularly through definitive surgery, leading to significantly improved treatment outcomes [3]. This approach offers substantial benefits, including reduced mortality rates and enhanced quality of life. Furthermore, early detection alleviates disease-related symptoms, as many cases are asymptomatic initially [4]. Patients diagnosed early also have a higher likelihood of survival post-resection compared to those diagnosed at advanced stages [5]. Screening programs not only decrease the prevalence of advanced lung cancer but also mitigate treatment-related morbidity [6]. Moreover, screening initiatives can prompt lifestyle changes and smoking cessation [7], bolstering overall public health. Utilizing low-dose CT scans (LDCT) for screening enables the identification of pulmonary nodules, offering a critical window for early diagnosis and intervention before symptomatic manifestation. However, lung cancer screening also presents potential risks, including false-negative and false-positive results, radiation exposure, overdiagnosis from incidental findings, ineffective detection of invasive disease, anxiety, and financial costs [8]. Therefore, it is crucial for lung cancer screening programs to carefully balance these potential risks against the benefits and choose the appropriate timing for intervention. Despite the importance of such programs, there is currently no unified standard for lung cancer screening, leading to variations in guidelines among different medical and health institutions [9-12]. These variations extend to recommended ages for initiating and concluding screening. Consequently, within the clinical community, opinions diverge on the optimal lung cancer screening policies. While physicians are generally aware of existing guidelines, specific screening recommendations can vary significantly.
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    AI-Powered Auxiliary Medical Diagnostic Systems
    (2024-03) Farias, Mylène C. Q.
    Deep Learning models are being used to analyze medical data and, most specifically, medical images, and to identify patterns and abnormalities that may not be (YET) visible to radiologists and physicians in general. These auxiliary diagnostic systems allow for an early detection of chronic diseases, such as heart conditions and cancer. AI models can process large amounts of data quickly and accurately. They can also be used to track health data over time and identify suspicious changes. Finally, AI models can be used to identify rare diseases and conditions that are difficult for humans to diagnose. But the area still faces several challenges: Availability of balanced datasets; Assurance of accuracy and reliability; Explainability; Privacy and security; Robustness to diversity in formats, degradations, etc.
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    Polyvagal Theory and the Alba Method Enhancing Mental Wellness Through Emotional Effector Patterns
    (2024-03) Glasheen, Kate; McAllister, Matthew
    No abstract prepared.
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    Response of Pulmonary Cells to Bolus and Incremental Doses of Engineered Nanoparticles
    (2024-03) Hoops, Jordan A.; Brenza, Timothy; Walker, Travis W.
    Chronic respiratory diseases, including chronic obstructive pulmonary disease (COPD), asthma, interstitial lung diseases, and pneumoconiosis, are the third leading cause of death worldwide, accounting for 4 million deaths in 2019. Inhaled particulate matter (PM) from environmental and occupational sources introduces exogenous pro-oxidants to the respiratory space, increasing the risk of pulmonary disease development and exacerbation.
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    Foundational Public Health Services Framed in Equity: An Essential Lens for Public Health Leadership
    (2024-03) Hughes, Monica
    The public health workforce is currently 80,000 fulltime employees short of what is required to provide essential public health services in the USA. Public health has recognized the deep imperative to address social determinants of health and other issues creating health disparities nationally and needs fresh strategies that incorporate the equity focus of the Foundational Public Health Services (FPHS) while retaining public health employees. Attrition in the public health workforce puts the health of communities and approaches to achieve health equity at risk. New methods are needed to facilitate employee retention, renew motivation, and promote meaning employees.
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    Effect of acidic biochar extracts and biofertilizers on seed germination
    (2024-03) Islas-Valdez, Samira; Wagner, Nicole C.
    At least 33% of all croplands are moderately or highly degraded due to synthetic fertilizers, pesticides, intensive tillage, monocropping, and yield-based management systems (FAO, 2015). Soil degradation has led to mineral and nutrient decline in foods, as well as reduced soil-water holding capacity and microbiological diversity (Montgomery & Biklé, 2022). Most agricultural soils globally have lost 30-75% of their original organic carbon, resulting in atmospheric CO2 (Global Carbon Project 2019). In response to these global challenges, biochar is being investigated as a soil amendment to restore degraded soils. Biochar is produced from organic waste material (e.g. woody materials, crop residues, manures) that is partially combusted with limited oxygen. Biochars have been shown to improve soil health, plant growth and soil microbial dynamics; sequester carbon; and reduce greenhouse gas emissions (Lehman and Joseph, 2015). While biochar has been used for millennia to improve soil health and plant productivity, gaps in applying soil to alkaline soils, such as those in Texas, remain.
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    Increasing Self-Efficacy to Support the Health and Resiliency of Texas Workers in Extreme Heat and Cold Environments
    (2024-03) Kisi, Krishna; Vasallo, Johnny; Pokharel, Manusheela
    Heat stress and cold stress are two common forms of environmental stressors that can adversely affect workers' health and productivity. According to the Texas Department of State Health Services (2023), approximately 279 people died in 2022 due to Texas’ rising exposure to extreme heat. Heat stress can negatively affect cognitive performance, impairing decision-making, reducing attention span, and decreasing memory (Parsons 2014). To navigate the concerns of occupational safety in extreme temperatures, this study adopts Badura’s (1977) self-efficacy model, a theoretical framework that establishes the concept of self-efficacy as the central role when interpreting and analyzing changes derived from avoidant and fearful behaviors. RESEARCH OBJECTIVES: Determine how extreme temperature training influences workers' self-efficacy and proactive behaviors in responding to heat and cold stress conditions. Explore how incorporating multicultural messaging into training programs affects engagement, self-efficacy, and behavioral intentions among workers from diverse cultural backgrounds. Determine the effects of information sharing on enhancing workplace safety, reducing incidents, and fostering a culture of safety within organizations.
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    Middle-Class Retirees at the Frontier of Health Care: An Example from the Frontera de Salud Project in West Texas
    (2024-03) Kotarba, Joseph; Perez, Norma
    The purpose of this study is to explore ethnographically the health concerns and health care availability among largely middle-class retirees in the far west Texas frontier. The Frontera de Salud project at UTMB has focused on assessing and ameliorating health care concerns among working-class and indigenous residents in the Big Bend area, but students and faculty have also begun mapping the shifting demographic and socio-cultural contours of health and health care in the entire population.
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    An Empirical Study on AI-Powered Edge Computing Architectures for Real-Time IoT Applications
    (2024-03) Ngu, Anne H. H.; Yasmin, Awatif
    Edge computing is indispensable for IoT applications, handling data from billions of devices and expected to surpass 41.6 billion installations by 2023. It facilitates swift decision-making at the device level. It conserves network bandwidth by processing data locally, making it suitable for resource-constrained or costly networks. Bolsters privacy and security by storing data locally, particularly crucial for applications that involves processing personal data.
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    The Impact of Synthetic Data on Fall Detection Application
    (2024-03) Ngu, Anne H. H.; Debnath, Minakshi
    The accurate recognition of the dynamic of fall using deep learning requires a lot of data. Three different methods for creating realistic synthetic fall data utilizing generative AI with diffusion, fall data extraction from 2D video recordings, and traditional data augmentation techniques are explored.
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    Screening of PotentialAntiviral Compounds - Assessing Efficacies Against Dengue Virus
    (2024-03) Olanrewaju, Adeyemi A.; Esan, Taiwo
    Epidemiology Dengue viruses (DENV) are spread to people through the bite of an infected Aedes species (Ae. Aegypti or Ae. albopictus)mosquito. Approximately, more than 3 billion people live in areas with high risk of dengue. It is the leading cause of illness in areas with risk vector borne disease (CDC, 2023). Genome DENV is a member of the Flavivirus genus of single-stranded positive-sense RNA viruses that causes severe generalized diseases in humans. There are four DENV serotypes (1, 2, 3 and 4), with type 2 and 3 being the most virulent forms (Vicente et al. 2016). Structure Mature DENV particles have a diameter of approximately 500nm. The surface is made up of a lipid bilayer which incorporate two transmembrane viral proteins to form a glycoprotein shell. The core contains the nucleocapsid formed by a viral RNA genome complex with capsid protein. The glycoprotein shell has 180 copies of envelope (E) and membrane protein (M or prM). The capsid (C) protein interacts with the viral RNA genome during assembly of the virus (Murugesan and Manoharan 2019).