Medicine and Health Sciences Commons^™

Virtual Surgical Planning In Craniomaxillofacial Surgery: A Structured Review, Kaye Verlarde, Rentor Cafino, Armando Isla Jr., Karen Mae Ty, Xavier-Lewis Palmer, Lucas Potter, Larry Nadorra, Luchin Valrian Pueblos, Lemuel Clark Velasco

Electrical & Computer Engineering Faculty Publications

Craniomaxillofacial (CMF) surgery is a challenging and very demanding field that involves the treatment of congenital and acquired conditions of the face and head. Due to the complexity of the head and facial region, various tools and techniques were developed and utilized to aid surgical procedures and optimize results. Virtual Surgical Planning (VSP) has revolutionized the way craniomaxillofacial surgeries are planned and executed. It uses 3D imaging computer software to visualize and simulate a surgical procedure. Numerous studies were published on the usage of VSP in craniomaxillofacial surgery. However, the researchers found inconsistency in the previous literature which prompted the …

Technology Adoption Of Computer-Aided Instruction In Healthcare: A Structured Review, Queenie Kate Cabanilla, Frevy Teofilo-Orencia, Rentor Cafino, Armando T. Isla Jr., Jehan Grace Maglaya, Xavier-Lewis Palmer, Lucas Potter, Dave E. Marcial, Lemuel Clark Velasco

Electrical & Computer Engineering Faculty Publications

Computer-Aided Instruction (CAI) is one of the interactive teaching methods that electronically presents instructional resources and enhances learner performance. In health settings, using CAI is one of the important ways to improve learners' knowledge and usefulness in their healthcare specialization yet there is still a lack of research that offers a comprehensive synthesis of investigating into the adoption of CAI in healthcare. This research aims to provide a comprehensive review of related literatures on the enablers and barriers for technology adoption of CAI in healthcare. 31 journals were analyzed and revealed that several studies were utilizing the Unified Theory of …

An Explainable Artificial Intelligence Framework For The Predictive Analysis Of Hypo And Hyper Thyroidism Using Machine Learning Algorithms, Md. Bipul Hossain, Anika Shama, Apurba Adhikary, Avi Deb Raha, K. M. Aslam Uddin, Mohammad Amzad Hossain, Imtia Islam, Saydul Akbar Murad, Md. Shirajum Munir, Anupam Kumur Bairagi

Electrical & Computer Engineering Faculty Publications

The thyroid gland is the crucial organ in the human body, secreting two hormones that help to regulate the human body's metabolism. Thyroid disease is a severe medical complaint that could be developed by high Thyroid Stimulating Hormone (TSH) levels or an infection in the thyroid tissues. Hypothyroidism and hyperthyroidism are two critical conditions caused by insufficient thyroid hormone production and excessive thyroid hormone production, respectively. Machine learning models can be used to precisely process the data generated from different medical sectors and to build a model to predict several diseases. In this paper, we use different machine-learning algorithms to …

Exploring Correlates Of Student Preferences For Virtual Or In-Class Learning Among Neurodiverse Adolescents Using A Single-Case Design Methodology, Taryn A. Myers, John D. Ball, Mindy Gumpert, Mary Roberts

Human Movement Studies & Special Education Faculty Publications

The purpose of the current study is to explore several correlates of adolescent students’ preferences for at-home virtual or in-class in-person learning in a single case of a school that serves students with learning differences. Correlates of interest were the Big Five personality traits (Openness to Experience, Conscientiousness, Extroversion, Agreeableness, Neuroticism) and the students’ self-reported learning engagement. Participants were recruited from a single independent school for students with neurodiversity and special learning needs, where they had high exposure to computer-/internet-assisted learning. Twenty-seven students responded to questionnaires measuring preferred learning modes, personality traits, and learning engagement. Despite teacher reports …

Let's Count The Ways We Can Utilize Technology To Improve Instructional Practices For Individuals With Autism, Heather Coleman, Annemarie L. Horn, Selena J. Layden, Christian Coogle

Human Movement Studies & Special Education Faculty Publications

To maximize instruction and learning outcomes, it is essential that educators and family members who support individuals with autism have adequate training and support required to implement evidence-based practices (EBPs) with fidelity. Research shows various coaching methods, including self-coaching and classroom-based feedback, yield positive outcomes in terms of increasing practical application and sustained use of EBPs. With the growing prevalence of autism, it is essential to find effective coaching methods that can be utilized equitably across geographic locations and learning environments. Fortunately, technology affords educators and others the opportunity to receive quality coaching and feedback without facing traditional barriers (e.g., …

The Effect Of Training Program On Autism Spectrum Quotient Scores, Hossein Nazary Sharif, Sarvin Salar, Justin Anthony Haegele

Human Movement Studies & Special Education Faculty Publications

Background: Autism Spectrum Quotient (AQ) functions as an evaluative instrument designed to assess traits associated with autism. Variances exist within the brain of individuals on the autism spectrum. Moreover, certain exercises have the potential to impact specific regions of the brain.

Aim: This study aims to investigate how the program training of this study impact Autism—Spectrum Quotient.

Materials and Methods: Forty-two children aged 7-10 years with ASD were recruited to participate in this study. These children were randomly divided into two groups: the control group (N=10, 7.80±1.35 years) and the experimental group (N=32, age: 8.16±1.16 years). The experimental group underwent …

Contributing Factors To Withdrawal Decisions Of Military And Nonmilitary Nursing Students, Beth Tremblay, Janice E. Hawkins, Robert E. Hawkins, Karen Higgins, Lynn Wiles, Jamela Martin

Ellmer School of Nursing Faculty Publications

Retaining nursing students in courses is key to increasing the number of new nurses. This study examined factors associated with nursing course or program withdrawal among students with and without prior military experience. The purpose of this study was to uncover differences between groups of students who withdrew compared to those who did not. A cross-sectional study using an online questionnaire surveyed current or recent nursing students (n = 420) using the Educational Requirement Subscale and the Student Withdrawal Questionnaire from Jeffreys’ toolkit. Uncovering differences between groups of students who did and did not withdraw from nursing courses or programs …

A Quality Improvement Project To Improve Management Of Urinary Tract Infections In A System Of Pediatric Urgent Care Centers, Benjamin Klick, Tammy Speerhas, Jessica Parrott, Jeffrey Bobrowitz, Anne Mcevoy, Debra Conrad, Theresa Guins

Ellmer School of Nursing Faculty Publications

Background and objective: Urinary tract infections (UTIs) are a common problem in pediatric urgent care medicine. There are multiple quality improvement (QI) projects related to the management of UTIs documented in the pediatric literature. We developed a project to decrease the prescribing of ultimately unneeded antibiotics for possible UTIs in a pediatric urgent care setting. A similar project has not been described in the pediatric literature.

Methods: We first reviewed the charts of patients presenting to a system of pediatric urgent care centers with a possible UTI over a 2-year period. We then launched a QI project with three plan, …

Use Of The Rasch Model For Fit Statistics And Rating Scale Diagnosis For The Student Perception Appraisal- Revised, Robert J. Hawkins, Janice Hawkins, Beth Tremblay, Lynn Wiles, Karen Higgins

Ellmer School of Nursing Faculty Publications

Background and Purpose: Nursing student retention is essential to meet workforce demands. Jeffrey's Nursing Student Retention Student Perception Appraisal-Revised (SPA-R1) has been used extensively to understand factors that impact retention. Psychometric testing of the SPA-R1 contributes to greater confidence in the instrument's reliability and validity.

Methods: Item response theory and specifically, the single parameter polytomous Rasch model was used as a framework for fit statistic testing and rating scale diagnostics of the SPA-R1. This was a secondary analysis of a convenience sample of undergraduate prelicensure nursing students. The setting for the previous study was virtual, and the study period was …

A Comparison Of Chief Complaints, Specific Diagnoses, And Demographics Of Pediatric Urgent Care Visits Before And During The Covid-19 Pandemic: A Retrospective Study, Zaharoula A. Viennas, Julie Martin, Benjamin Klick, Tammy Speerhas, Turaj Vazifedan, Danielle Millspaugh, Jennifer Ferris, Margret Bedle, Lauren Paluch, Theresa Guins

Ellmer School of Nursing Faculty Publications

There was an increased incidence of pediatric patients who presented with injuries caused by falls not related to sports or other recreational activities, as well as for animal bites, during the early pandemic period of April 2020. Education of parents and caregivers of young children is warranted to raise awareness of the even greater potential for falls and animal bites when children are confined at home for longer than typical periods of time, as occurred with the stay-at-home government orders during the initial period of the COVID-19 pandemic.

Health Profession Students' Interprofessional Socialization And Values Toward A College-Based Virtual Interprofessional Education Activity, Denise Claiborne, Praveen Durgampudi, Anne C. Dumadag, Emily J. Hawkins, Patricia Laverdure, Amy Laurie Meeker, Barbara Kraj, Angela Wilson, Muge Akpinar-Elci

Dental Hygiene Faculty Publications

Purpose: The inclusion of interprofessional education (IPE) is essential for the health professions curricula and establishes the expectation of collaborative patient-centered care. The COVID-19 pandemic has required educators to develop innovative methods for IPE student engagement. The purpose of this study was to evaluate a college-based virtual IPE activity for first-year health profession students and measure their interprofessional socialization and values (ISVS) toward IPE teams. The validated interprofessional socialization and valuing scales (ISVS-9A/9B) were used.

Methods: A one-group pre-post-test design examined health profession students' ISVS from seven health programs before and after a virtual IPE activity. The IPE activity was …

A Global Perspective Of Advanced Practice Nursing Research: A Review Of Systematic Reviews Protocol, Kelley Kilpatrick, Isabelle Savard, Li-Anne Audet, Abby Kra-Friedman, Reneé Atallah, Mira Jabbour, Wentao Zhou, Kathy Wheeler, Elissa Ladd, Deborah C. Gray, Colette Henderson, Lori A. Spies, Heather Mcgrath, Melanie Rogers

Ellmer School of Nursing Faculty Publications

Introduction

In 2020, the World Health Organization called for the expansion and greater recognition of all nursing roles, including advanced practice nurses (APNs), to better meet patient care needs. As defined by the International Council of Nurses (ICN), the two most common APN roles include nurse practitioners (NPs) and clinical nurse specialists (CNSs). They help ensure care to communities as well as patients and families with acute, chronic or complex conditions. Moreover, APNs support providers to deliver high quality care and improve access to services. Currently, there is much variability in the use of advanced practice nursing roles globally. A …

Climate And Health: Impact Of Climate Education On Nursing Student Knowledge, Confidence, And Intent To Act, Beth Tremblay, Janice Hawkins

Ellmer School of Nursing Faculty Publications

Background: Because climate change negatively impacts human health, nurses need skills to mitigate climate change and nurse educators need effective educational strategies to teach climate change content in undergraduate nursing programs. To address this need, we embedded an energy efficiency treasure hunt and Climate for Health Ambassador Training into our prelicensure nursing curricula.

Purpose: To evaluate the impact of these educational activities on self-reported knowledge, confidence, and intent to engage in climate action.

Methods: A quasi-experimental one-group posttest design examined the effectiveness of 2 educational interventions on increasing knowledge, confidence, and intent to engage in climate action. A convenience sample …

Identifying The Serious Clinical Outcomes Of Adverse Reactions To Drugs By A Multi-Task Deep Learning Framework, Haochen Zhao, Peng Ni, Qichang Zhao, Xiao Liang, Di Ai, Shannon Erhardt, Jun Wang, Yaohang Li, Jiianxin Wang

Computer Science Faculty Publications

Adverse Drug Reactions (ADRs) have a direct impact on human health. As continuous pharmacovigilance and drug monitoring prove to be costly and time-consuming, computational methods have emerged as promising alternatives. However, most existing computational methods primarily focus on predicting whether or not the drug is associated with an adverse reaction and do not consider the core issue of drug benefit-risk assessment-whether the treatment outcome is serious when adverse drug reactions occur. To this end, we categorize serious clinical outcomes caused by adverse reactions to drugs into seven distinct classes and present a deep learning framework, so-called GCAP, for predicting the …

Cellbrf: A Feature Selection Method For Single-Cell Clustering Using Cell Balance And Random Forest, Yunpei Xu, Hong-Dong Li, Cui-Xiang Lin, Ruiqing Zheng, Yaohang Li, Jinhui Xu, Jianxin Wang

Computer Science Faculty Publications

Motivation

Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to dissect the complexity of biological tissues through cell sub-population identification in combination with clustering approaches. Feature selection is a critical step for improving the accuracy and interpretability of single-cell clustering. Existing feature selection methods underutilize the discriminatory potential of genes across distinct cell types. We hypothesize that incorporating such information could further boost the performance of single cell clustering. Results

We develop CellBRF, a feature selection method that considers genes’ relevance to cell types for single-cell clustering. The key idea is to identify genes that are most important for discriminating …

Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …

Msdrp: A Deep Learning Model Based On Multisource Data For Predicting Drug Response, Haochen Zhao, Xiaoyu Zhang, Qichang Zhao, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning and deep learning have been proposed to predict drug response in vitro. However, most of these methods capture drug features based on a single drug description (e.g. drug structure), without considering the relationships between drugs and biological entities (e.g. target, diseases, and side effects). Moreover, most of these methods collect features separately for drugs and cell lines but fail to consider the pairwise interactions between drugs and cell …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

Progenitor Cell Isolation From Mouse Epididymal Adipose Tissue And Sequencing Library Construction, Qianglin Liu, Chaoyang Li, Yuxia Li, Leshan Wang, Xujia Zhang, Buhao Deng, Peidong Gao, Mohammad Shiri, Fozi Alkaifi, Junxing Zhao, Jacqueline M. Stephens, Constantine A. Simintiras, Joseph Francis, Jiangwen Sun, Xing Fu

Computer Science Faculty Publications

Here, we present a protocol to isolate progenitor cells from mouse epididymal visceral adipose tissue and construct bulk RNA and assay for transposase-accessible chromatin with sequencing (ATAC-seq) libraries. We describe steps for adipose tissue collection, cell isolation, and cell staining and sorting. We then detail procedures for both ATAC-seq and RNA sequencing library construction. This protocol can also be applied to other tissues and cell types directly or with minor modifications.

For complete details on the use and execution of this protocol, please refer to Liu et al. (2023).¹

*¹ Liu, Q., Li, C., Deng, B., Gao, P., …

A Single-Cell Atlas Of Bovine Skeletal Muscle Reveals Mechanisms Regulating Intramuscular Adipogenesis And Fibrogenesis, Leshan Wang, Peidong Gao, Chaoyag Li, Qianglin Liu, Zeyang Yao, Yuxia Li, Xujia Zhang, Jiangwen Sun, Constantine Simintiras, Matthew Welborn, Kenneth Mcmillin, Stephanie Oprescu, Shihuan Kuang, Xing Fu

Computer Science Faculty Publications

Background: Intramuscular fat (IMF) and intramuscular connective tissue (IMC) are often seen in human myopathies and are central to beef quality. The mechanisms regulating their accumulation remain poorly understood. Here, we explored the possibility of using beef cattle as a novel model for mechanistic studies of intramuscular adipogenesis and fibrogenesis.

Methods: Skeletal muscle single-cell RNAseq was performed on three cattle breeds, including Wagyu (high IMF), Brahman (abundant IMC but scarce IMF), and Wagyu/Brahman cross. Sophisticated bioinformatics analyses, including clustering analysis, gene set enrichment analyses, gene regulatory network construction, RNA velocity, pseudotime analysis, and cell-cell communication analysis, were performed to elucidate …

Comparison Of Physics-Based Deformable Registration Methods For Image-Guided Neurosurgery, Nikos Chrisochoides, Yixun Liu, Fotis Drakopoulos, Andriy Kot, Panos Foteinos, Christos Tsolakis, Emmanuel Billias, Olivier Clatz, Nicholas Ayache, Andrey Fedorov, Alex Golby, Peter Black, Ron Kikinis

Computer Science Faculty Publications

This paper compares three finite element-based methods used in a physics-based non-rigid registration approach and reports on the progress made over the last 15 years. Large brain shifts caused by brain tumor removal affect registration accuracy by creating point and element outliers. A combination of approximation- and geometry-based point and element outlier rejection improves the rigid registration error by 2.5 mm and meets the real-time constraints (4 min). In addition, the paper raises several questions and presents two open problems for the robust estimation and improvement of registration error in the presence of outliers due to sparse, noisy, and incomplete …

Detecting Deceptive Dark-Pattern Web Advertisements For Blind Screen-Reader Users, Satwick Ram Kodandaram, Mohan Sunkara, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users' experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via …

Unttangling Irregular Actin Cytoskeleton Architectures In Tomograms Of The Cell With Struwwel Tracer, Salim Sazzed, Peter Scheible, Jing He, Willy Wriggers

Computer Science Faculty Publications

In this work, we established, validated, and optimized a novel computational framework for tracing arbitrarily oriented actin filaments in cryo-electron tomography maps. Our approach was designed for highly complex intracellular architectures in which a long-range cytoskeleton network extends throughout the cell bodies and protrusions. The irregular organization of the actin network, as well as cryo-electron-tomography-specific noise, missing wedge artifacts, and map dimensions call for a specialized implementation that is both robust and efficient. Our proposed solution, Struwwel Tracer, accumulates densities along paths of a specific length in various directions, starting from locally determined seed points. The highest-density paths originating …

College Of Health Sciences Newsletter, College Of Health Sciences, Old Dominion University

Ellmer College of Health Sciences Newsletters

December 2022 issue of Old Dominion University's College of Health Sciences Newsletter.

Counselor Perceived Competence Diagnosing Disorders From Dsm-5 Diagnostic Categories Survey Results And The Development And Validation Of Scores On The Diagnostic Self-Efficacy Scale, Erin Elizabeth Woods

Counseling & Human Services Theses & Dissertations

This dissertation focused on the diagnostic self-efficacy of mental health counselors. The diagnosis of mental health disorders serves a wide array of functions in the counseling field including communication, treatment planning, and third-party reimbursement. Self-efficacy, or one’s belief in their own ability to accomplish a task, is considered a factor in successful task completion. The literature lacked information about which mental health disorders counselors are most confident diagnosing and an instrument which measured the self-efficacy of counselors specific to the diagnostic process. The MEASURE approach was employed to create the Diagnostic Self-Efficacy Scale and validate scores on this instrument with …

Dental Hygienists’ Practices, Attitudes, And Confidence In Providing Care To Child Patients With Autism Spectrum Disorder (Asd), Fatimah Abdulrahman Alshehri

Dental Hygiene Theses & Dissertations

Problem: Given the growing number of children diagnosed with autism spectrum disorder (ASD) over the past decades and their significant need for access to dental care, it becomes essential to have dental hygienists adequately prepared to provide care to child patients with ASD. This study aimed to assess dental hygienists’ practices, attitudes, and confidence levels in providing care for child patients with ASD. Methods: An 18–item, adapted survey was validated and administered to participants at the Virtual ODU Continuing Education Annual Conference. Data was collected via Qualtrics® from 187 dental hygienist attendees. The survey domains studied included demographics, practice settings, …

T-Cell Antigen Receptors In Multiple Sclerosis, Lisa Lanée Keyes Jones

Biomedical Sciences Theses & Dissertations

Multiple Sclerosis (MS) is T-cell mediated autoimmune disease characterized by inflammation, demyelination, and degeneration of axons in the brain and spinal cord. A T cell-mediated immune response in MS is directed against myelin components and possibly other antigens in genetically susceptible individuals and is triggered by a viral infection. The T-cell antigen receptor (TCR) on T cells is responsible for antigen recognition and determines specificity. Our overall hypothesis is to determine whether clonally expanded T cells in patients with MS recognize viral or self-antigens and to determine whether molecular mimicry is involved in the development of the disease. To study …

Measuring The Economic Impact Of Recurrent Flooding On Workforce Productivity And Property, Joshua G. Behr, Wie Yusuf, George Mcleod, Sarah Stafford, Derek Loftis, Afi Anuar, Rafael Diaz

Presentations, Lectures, Posters, Reports

From the Executive Summary:

This research draws upon expertise across multiple disciplines and fields. Leveraged are natural systems data and social-behavioral data. The high-level objective is to advance our understanding of how very recent recurrent flooding has impacted residents within the City of Portsmouth, and then forecast these impacts under projections of sea level rise. While this research draws upon data for the City of Portsmouth, the findings may be generalized to the broader Hampton Roads region.

Npgreat: Assembly Of The Human Subtelomere Regions With The Use Of Ultralong Nanopore Reads And Linked Reads, Eleni Adam, Desh Ranjan, Harold Riethman

Computer Science Faculty Publications

Background: Human subtelomeric DNA regulates the length and stability of adjacent telomeres that are critical for cellular function, and contains many gene/pseudogene families. Large evolutionarily recent segmental duplications and associated structural variation in human subtelomeres has made complete sequencing and assembly of these regions difficult to impossible for many loci, complicating or precluding a wide range of genetic analyses to investigate their function.

Results: We present a hybrid assembly method, NanoPore Guided REgional Assembly Tool (NPGREAT), which combines Linked-Read data with mapped ultralong nanopore reads spanning subtelomeric segmental duplications to potentially overcome these difficulties. Linked-Read sets of DNA sequences identified …

Fear And Trembling While Working In A Pandemic: An Exploratory Meta-Analysis Of Workers’ Covid-19 Distress, William P. Jimenez, Ian M. Katz, Elissa A. Liguori

Psychology Faculty Publications

The global COVID-19 pandemic has disrupted the lives of workers and taken its toll on health and well-being. In line with recent calls for more inductive and abductive occupational health science research, we exploratorily meta-analyzed workers’ COVID-19 distress, defined as psychological and psychosomatic strain contextualized to experiencing the virus and pandemic broadly. We identified many existing COVID-19 distress measures (e.g., Fear of COVID-19 Scale by Ahorsu et al., 2020; Coronavirus Anxiety Scale by Lee, 2020a) and correlates, including demographic variables (viz., gender, marital status, whether worker has children), positive well-being (e.g., quality of life, perceived social support, resilience), negative well-being …