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April 2025, Swosu Bulldog Wellness Committee

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A New Member Benefit: The Talk Space Go App, Lisa Knowles Dds

The Journal of the Michigan Dental Association

This article introduces TalkSpace Go, a new ADA member benefit providing mental health support for dentists. Dr. Lisa Knowles explains how the app offers private access to therapists, courses, and workshops to help manage professional stress and prevent burnout. The piece highlights that 82% of dentists experience clinical burnout symptoms and emphasizes the importance of prioritizing mental well-being. Knowles describes her personal experience with burnout and using the app alongside the ADA's Well-Being Index assessment tool. The article includes instructions for accessing both resources, which are free for ADA/MDA members.

Words Of Advice: How To Write The Story Of A Patient For A Problem-Based Learning Session In A Healthcare Education Program, Andrew D Bergemann, Matthew Mcmillin, Miriah C Gillispie-Taylor, Gareth Gingell, R Taylor Surles, Rachel Wallace

Faculty and Staff Publications

Medical education is in the process of a pedagogical revolution. Traditional lectures are playing a progressively smaller role, with more of the content being delivered through student-centered small-group sessions. Problem-based learning (PBL) has become a centerpiece of education for many medical schools, in large part because of its focus on the learners identifying their own knowledge gaps. As junior scientists seek faculty appointments in institutions focused on healthcare education, they will find that skills in PBL are valued by the academic community. Among the necessary skills is the capability to lead efforts in PBL case writing. The cases, each of …

Factors Affecting Nurse Retention In A Private Healthcare System In Malaysia, Zarin Ikmal Zan Mohd Zain, Annamma Kunjukunju, Govethamma Subramaniam, Nur Izzana Tajuddin

Jurnal Keperawatan Indonesia

Nurse retention has become increasingly challenging in the post-pandemic era, particularly for private hospitals. This study aimed to identify the significant predictors of nurse retention in selected private hospitals in Malaysia. A quantitative, descriptive, cross-sectional design was employed. A pre-validated, self-administered questionnaire, distributed via Google Forms, was used for data collection. The respondents included 532 registered nurses employed at three private hospitals in Malaysia. Data analysis was conducted using descriptive statistics and correlation studies, including Spearman’s rho and multiple regression analysis. Among the participants, 54% reported good job satisfaction, 27.37% expressed organizational commitment, 25.97% were satisfied with human resource practices, …

Assessment Of Nurses’ Knowledge Of Multiple Sclerosis In Morocco, Rachid Lotfi, Hind Bel Amgharia, Mourad Chikhaoui, Abdeslam El Kardoudi, Fatiha Chigr

Jurnal Keperawatan Indonesia

Nurses are essential in early detection, education, symptom management, treatment administration, and care coordination for patients with multiple sclerosis (MS). This role requires both theoretical and practical knowledge. This study evaluates the knowledge level among nurses regarding multiple sclerosis in Morocco. We conducted this cross- sectional study on 326 nurses in Morocco using a purposive sampling method, which involves selecting nursing specialties that have direct contact with patients with MS, aiming to target the most relevant professionals for the study. The data are collected using an anonymous questionnaire distributed individually to participants. We opted for multi- variable logistic regression models …

Resilience, Social Support, And Quality Of Life Among People Living With Hiv/Aids, Firman Firman, Sri Yona, Agung Waluyo

Jurnal Keperawatan Indonesia

One of the most common challenges faced by people living with human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) is a low quality of life, particularly during the coronavirus disease 2019 (COVID-19) pandemic, as they are considered a vulnerable group. This study aimed to examine the relationship between resilience, social support, and quality of life among people living with HIV/AIDS during the pandemic. Conducted as a cross- sectional study, it involved 433 respondents. Data collection was carried out using a questionnaire, with Connor–Davidson Resilience Scale-25 (CD-RISC-25), Multidimensional Scale of Perceived Social Support (MSPSS), and World Health Organization Quality of Life–HIV Brief …

Addressing Diabetic Retinopathy Prevalence In Low-Income Communities: Barriers To Quality Healthcare And Strategies For Equitable Treatment Access, Morkeia A. Mutchelknaus

Honors Thesis

Studies have shown a strong correlation between diabetes and individuals in low-income communities, which often lack access to equitable healthcare for a variety of reasons. This honors thesis will focus on diabetic retinopathy, its prevalence, prevention, and treatment strategies in both low- and high-income communities. A comprehensive literature review was conducted to define diabetic retinopathy, assess its prevalence, and review past and present approaches to its treatment and prevention. This paper aims to identify strategies to improve healthcare accessibility in low-income communities by analyzing current strategies in place to prevent and treat diabetic retinopathy and proposing potential solutions that will …

Evaluation Of The Use Of Structural Gamification-Based Applications By Users In Makassar City, Indonesia, Andi Fitria Idham, Ade Putrawan, Firdi Athaya, Fitrah Ramadhan, Arnis Puspitha Rasyid

Jurnal Keperawatan Indonesia

Structural gamification is a trending concept in today’s application landscape that leverages various elements and features from game design for nongame contexts. This concept has become increasingly common in various health applications today, such as Lose It!, Fat Secret, and Google Fit. This study aims to evaluate respondents’ use of structural gamification- based health applications. The research method employed in this study is quantitative and descriptive, involving data collection through questionnaires administered from July 2023 to September 2023 in Makassar City, Indonesia. The research results indicate that 90% of the respondents appreciated the ease of access and attractive interface of …

Peran Tempat Persalinan Dalam Inisiasi Menyusu Dini: Analisis Survei Demografi Dan Kesehatan Indonesia Tahun 2017, Siti Sunya Kumala, Besral Besral

Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan

Cakupan inisiasi menyusu dini (IMD) di Indonesia lebih rendah dibandingkan rata-rata ASEAN. Padahal cakupan persalinan di fasilitas kesehatan dan dibantu oleh tenaga kesehatan telah melampaui 70%. Penyedia layanan kesehatan menjadi faktor pendukung ibu untuk melakukan IMD. Penelitian ini bertujuan untuk mengetahui peran tempat persalinan dalam IMD di Indonesia. Penelitian dilakukan dengan desain potong lintang, dan menggunakan data Survei Demografi Kesehatan Indonesia tahun 2017. Sampel penelitian adalah wanita usia 15-49 tahun dari seluruh provinsi di Indonesia. Regresi logistik ganda dilakukan untuk menganalisis IMD dari berbagai tempat persalinan. Proporsi IMD pada tahun 2017 adalah 60,7%. Proporsi IMD paling banyak di poskesdes/polindes (72,8%), …

Harnessing Sociodemographic And Anthropometric Insights To Predict Type 2 Diabetes Risk: A Machine Learning Approach, Rico Kurniawan, Rezki Yunanda, Okky Assetya Pratiwi

Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan

The complexity of diabetes makes early diagnosis and effective management challenging for healthcare settings. This study developed and evaluated models using machine learning algorithms to predict the risk of diabetes. The data were primarily sourced from the Indonesia Family Life Survey (IFLS). Diabetes status was identified using A1c whole blood sample values (A1c WBS ³5.7%). Sociodemographic and anthropometric factors were set as predictors, most of which were significantly correlated with diabetes status. Discrete machine learning algorithms such as decision tree, k-nearest neighbors (KNN), random forest (RF), naïve Bayer, support vector machine (SVM), and neural network (MLP) were applied to construct …

Analisis Kepuasan Pengguna Simrs Pada Klaim Jkn Di Rsud Khidmat Sehat Afiat, Kota Depok Tahun 2023, Robiatul Adawiyah, R Sutiawan

Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan

Keberlangsungan klaim JKN di RSUD Khidmat Sehat Afiat Kota Depok sekurang-kurangnya harus didukung oleh SIMRS yang dapat diintegrasikan dengan E-Klaim INA-CBG’s dan V-Claim. Maka pada tahun 2019 SIMRS dilakukan integrasi dengan kedua sistem informasi tersebut guna meningkatkan keberhasilan klaim JKN. Namun, sejak SIMRS diintegrasi, hingga saat ini belum pernah dilakukan analisis. Padahal, E-Klaim INA-CBG’s dan V-Claim terus mengalami perubahan yang menjadikan banyaknya fitur yang belum tersedia pada SIMRS yang berujung membuat proses pengajuan klaim JKN menjadi terhambat. Desain penelitian ini menggunakan teori Delone dan McLean dengan jenis penelitian kuantitatif dan pendekatan cross-sectional. Pengambilan sampel menggunakan proportional stratified random sampling …

Vaccination As A Protective Factor Against Hospitalization For Sars-Cov-2 Infections: An Observational Study Using Surveillance Data, Chandrayani Simanjorang, Kristin Mutiara Tarigan, Diva Anita Churiana Sudrajat, Rana Zahra Raniyah Wangsawinangun, Asy Syifa Anwari Zahra

Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan

Death due to SARS-CoV-2 generally occurs in patients requiring hospital care (hospitalization). However, it is still unclear whether vaccination acts as a protective factor against hospitalization in SARS-CoV-2 patients in Indonesia. This study examines the association between vaccination and hospitalization among SARS-CoV-2 patients. It employs a quantitative, cross-sectional design using secondary data from SARS-CoV-2 surveillance records at the Jakarta Health Agency (January–August 2021). Findings show that patients who received the 1st vaccine dose had a 0.34 times lower risk of hospitalization compared to unvaccinated individuals (aPOR=0.34; 95% CI=0.31–0.38). Those who received the 2nd dose had an even lower risk (aPOR=0.16; …

Video Animation: Improving Older Adults Patients Knowledge And Motivation Related To Hypertension Diet, Gusti Ayu Kade Budiarti, Sri Susanty, Ruslan Madjid, Ramadhan Tosepu

Jurnal Keperawatan Indonesia

Hypertension is a dangerous medical condition that can increase the risk of heart, brain, and renal problems, among other issues. A balanced diet is an essential hypertension control intervention. This study seeks to examine the efficiency of employing animation media to explain the application of diets that prevent hypertension and boost the understanding and motivation of senior patients at Bahteramas Regional General Hospital. In both the control and intervention groups, a quantitative-quasi-experimental design was adopted, with pre-test and post-tests. Data was obtained via questionnaires from 92 respondents chosen using a purposive sampling approach, with 46 in the intervention group from …

Ransomware In Healthcare: Threats, Impacts, And Mitigation Strategies, Mackenzie Dotson, Kasi Gorli, Alberto Coustasse

Management Faculty Research

Excerpt: The growing digitalization of healthcare has exposed hospitals to significant cybersecurity threats, particularly ransomware attacks. The Health Sector Cybersecurity Coordination Center (HC3) reported that as of mid-2024, there were 730 cyber-attacks worldwide against healthcare institutions, with 530 targeting the U.S. (AHA, 2024). Half of these incidents involved ransomware, a type of malware that restricts access to critical data until a ransom is paid (HHS, 2021). Hospitals are attractive targets for cybercriminals due to their essential role in patient care. Cybercriminals exploit vulnerabilities in hospital networks, often causing severe operational and financial damage. Factors such as understaffed IT teams, outdated …

Smart Radiology: Using Artificial Intelligence For Better Imaging Outcomes, Jordan Watts, Jeffrey Larson, Kasi Gorli, Alberto Coustasse

Management Faculty Research

We hypothesize that the use of Artificial Intelligence (AI) in radiology improves the quality of care by increasing diagnostic accuracy, reducing interpretation time, and enhancing clinical workflow efficiency by minimizing imaging acquisition errors.

An Assessment Of The Performance Of Different Chatbots On Shoulder And Elbow Questions, Mohamad Y. Fares, Tarishi Parmar, Peter Boufadel, Mohammad Daher, Jonathan Berg, Austin Witt, Brian W. Hill, John G. Horneff, Adam Z. Khan, Joseph A. Abboud

Rothman Institute Papers

Background/Objectives: The utility of artificial intelligence (AI) in medical education has recently garnered significant interest, with several studies exploring its applications across various educational domains; however, its role in orthopedic education, particularly in shoulder and elbow surgery, remains scarcely studied. This study aims to evaluate the performance of multiple AI models in answering shoulder- and elbow-related questions from the AAOS ResStudy question bank.

Methods: A total of 50 shoulder- and elbow-related questions from the AAOS ResStudy question bank were selected for the study. Questions were categorized according to anatomical location, topic, concept, and difficulty. Each question, along with the …

Patient Access As A Vehicle For Growth: Leveraging Technology & Stakeholder Engagement, Celeste Gagliardi, Ryan Patterson, Scott Guttridge

Jefferson Hospital Staff Papers and Presentations

Introduction Statement:

Prior to the work outlined here, Jefferson Medical Group's local scheduling controls led to inconsistent scheduling rules, inefficient staffing models, and a less than desirable patient experience. Fueled by the conversion to Epic in late 2016, JMG has been on a journey to improve access through technology enablers that have fostered significant growth for the organization while simultaneously improving the experiences of our patients, providers, and staff.

Unlocking Precision Using K-Means++- Improved Genetic Algorithm-Radial Basis Function Neural Network: Data-Driven Evolution Of Smart Gloves For Gesture Recognition, Liang Xiao Ding, Kuan Way Chee, Hong Lü, Anand Paul, Jeonghong Kim, Jang Myung Lee

School of Public Health Faculty Publications

Human-computer interaction technologies have been used since the 1970s but have only gained growing popularity in recent years with new design paradigms. Ongoing research and development in gesture recognition systems with broad application prospects have focused on improving accuracy and real-time performance as well as the robustness of specific machine learning algorithms against environmental conditions. This paper addresses the accuracy enhancement of a novel Fifth Dimension Technologies data-glove-based gesture recognition system using a genetic-algorithm (GA)-trained k-means++-improved radial basis function (RBF) or GK-RBF neural network. First, we analyzed and modeled the sensor distribution in the data glove and proposed joint constraints …

Enhancing Interprofessional Staff Competence In Culturally Sensitive Patient Education: A Web-Based Health Literacy Toolkit For Brazilian Immigrants In Florida, Faila Reis Pereira Dos Santos

Student Scholarly Projects

Practice Problem: Brazilian immigrants in Florida face cultural and language barriers that hinder their ability to understand and engage with healthcare services. Additionally, healthcare providers often lack the cultural competency needed to deliver effective patient education, contributing to poor health literacy within this population.

PICOT: The PICOT question that guided this project was: For healthcare interprofessional staff supporting Brazilian immigrants in Florida (P), how does the development of a web-based health literacy toolkit (I), compared to standard educational methods (C), influence their competency in delivering culturally sensitive patient education (O)?

Evidence: Research demonstrates that culturally tailored health literacy interventions improve …

Sexual Health In The Era Of Artificial Intelligence: A Scoping Review Of The Literature, Elia Abou Chawareb, Brian H. Im, Sherry Lu, Muhammed A.M. Hammad, Tiffany R. Huang, Henry Chen, Faysal A. Yafi

Student Papers, Posters & Projects

INTRODUCTION: Artificial Intelligence (AI) has witnessed significant growth in the field of medicine, leveraging machine learning, artificial neuron networks, and large language models. These technologies are effective in disease diagnosis, education, and prevention, while raising ethical concerns and potential challenges. However, their utility in sexual medicine remains relatively unexplored.

OBJECTIVE: We aim to provide a comprehensive summary of the status of AI in the field of sexual medicine.

METHODS: A comprehensive search was conducted using MeSH keywords, including "artificial intelligence," "sexual medicine," "sexual health," and "machine learning." Two investigators screened articles for eligibility within the PubMed and MEDLINE databases, with …

The Present And Future Of Robotic Surgery In Breast Cancer And Breast Reconstruction, Brett Allen, Alexis Knutson, Noama Iftekhar, Casey Giles, Jarrell Patterson, Joshua Macdavid, Richard Baynosa

Department of Plastic Surgery Faculty Research

Background: Breast cancer is the second most common cancer in women with an improving mortality rate and a growing need for reconstruction following oncologic resection. Advancements in robotic surgery and minimally invasive techniques have offered refinement to traditional open techniques of flap harvest for reconstruction, particularly regarding improved donor site morbidity. Methods: The literature review was based on a PubMed database search using the keyword “Robotic breast reconstruction” in conjunction with the Boolean operators “Flap”, “Latissimus”, and “DIEP” to specify the search. In total, 106 results were generated, which were then manually reviewed and condensed for a comprehensive stance on …

A Brief Commentary On Human-Ai Attachment And Possible Impacts On Family Dynamics, Brandon T. Mcdaniel Phd, Amanda Coupe, Allison Weston, Jessica A. Pater

Health Services and Informatics Research

Objective: In this brief commentary article, we outline an emerging idea that it may be possible that as Conversational Artificial Intelligence (CAI) becomes a part of an individual’s environment and interacts with them their attachment system may become activated, potentially leading to behaviors—such as seeking out the CAI to feel safe in times of stress—that have typically been reserved for human-to-human attachment relationships. We term this attachmentlike behavior, but future work must determine if these behaviors are driven by a Human-AI attachment or something else entirely. Background: CAI is an emerging technical advancement that is the cornerstone of many everyday …

Perceptions Of Artificial Intelligence In Healthcare: A Qualitative Study Among Physicians And Nurses In Florida, Aaron Miri

MUSC Theses and Dissertations

This investigation will leverage participant focus group interviews with 32 clinicians (16 nurses / 16 physicians) to study what, if anything, is inhibiting AI adoption across the hospital. Specific physicians will be sourced across the key service lines of primary care, oncology, cardiology, behavioral health, and emergency department medicine, as these tend to be patient volume driven and thus have the maximum amount of potential for positive impact leveraging AI. Nurses in these same departments will be assessed to analyze if there is a similarity or difference between the nursing and physician AI adoption barriers.

A Deep Sparse Capsule Network For Non-Invasive Blood Glucose Level Estimation Using A Ppg Sensor, Narmatha Chellamani, Saleh Ali Albelwi, Manimurugan Shanmuganathan, Palanisamy Amirthalingam, Emad Muteb Alharbi, Hibah Qasem Salman Alatawi, Kousalya Prabahar, Jawhara Bader Aljabri, Anand Paul

School of Public Health Faculty Publications

Diabetes, a chronic medical condition, affects millions of people worldwide and requires consistent monitoring of blood glucose levels (BGLs). Traditional invasive methods for BGL monitoring can be challenging and painful for patients. This study introduces a non-invasive, deep learning (DL)-based approach to estimate BGL using photoplethysmography (PPG) signals. Specifically, a Deep Sparse Capsule Network (DSCNet) model is proposed to provide accurate and robust BGL monitoring. The proposed model’s workflow includes data collection, preprocessing, feature extraction, and predictions. A hardware module was designed using a PPG sensor and Raspberry Pi to collect patient data. In preprocessing, a Savitzky–Golay filter and moving …

Using Ehr Reminders To Control Hypertension, Umme Kulsoom Ghous, Logan Mcculley, Danielle C. Hall, Linda Katherine Lambert, Laura Reed Dnp, Aprn, Fnp-Bc, Cne

Doctor of Nursing Practice Projects

Purpose/Background

Hypertension is a significant risk factor for cardiovascular and kidney diseases but is often under-diagnosed and poorly managed. Electronic Health Records (EHR) can help by providing automated reminders to recheck elevated blood pressure (BP) readings, ensuring accurate measurements, and guiding clinical interventions. This study aims to determine if EHR-based reminders improve BP control in adult patients aged 21 and older, focusing on hypertension diagnosis accuracy and timely management.

Methods

After a literature review, the study took place in a primary care clinic and only included patients with an existing diagnosis of hypertension. Thirty patients were included in the study. …

Development Of A Personal Health Recommendation System Based On Data And Machine Learning To Improve User Wellbeing, Eliyah Acantha Manapa Sampetoding, Andi Alisha Faiqihah, Yulita Sirinti Pongtambing

Jurnal Administrasi Bisnis Terapan

The development of personal health recommendation systems has become a significant focus of research, along with the increasing need to improve user well-being. This research critically examines options in data and data mining and Machine Learning to support the establishment of systems to recommend better and improved healthcare services. Drawing on the results of a systematic review of past literature, the study shows that the application of Machine Learning algorithms in disease opinion learning, health condition classification, and demographics is emerging as a prospect for driving clinical decisions. Various models, from Deep Learning to traditional machine learning models such as …

The Interplay Between Endothelial Glycocalyx Maturity And Both The Toxicity And Intracellular Uptake Of Charged Nanoparticles, Claire A. Bridges, Lu D. Fu, Jonathan A. Yeow, Xiaojing D. Huang, Miriam D. Jackson, Rhiannon P. Kuchel, James D. Sterling, Shenda M. Baker, Megan S. Lord

Business and Information Technology Faculty Research & Creative Works

Nanoparticles are widely studied for delivering treatments to target tissues, but few have reached clinical use. Most nanoparticles encounter blood vessels on their way to target tissues. The inner surface of these vessels is lined with endothelial cells covered by a glycocalyx, an extracellular matrix rich in anionic glycans. The role of the glycocalyx in nanoparticle interactions is not well understood. Here, we demonstrate that endothelial cells need extended culture times to synthesize a mature glycocalyx. Our research shows that branched polyethyleneimine functionalized gold nanoparticles bind to endothelial cells expressing either a developing or mature glycocalyx, with the interaction involving …

Leveraging Ai In Teledermatology: A Literature Review On Advancing Health Equity For Underserved Populations, Jared Hensley, Smaran Marupudi, Blake Martin, Neharika Penmetcha, Maria Villegas

Research Symposium

Background: Health disparities in dermatological care tend to disproportionately affect underserved populations, particularly those in rural and resource-limited settings. Teledermatology, augmented by artificial intelligence (AI), presents an opportunity to address these inequities by providing underserved populations with improved diagnostic capabilities. Despite its promise, AI models in teledermatology can often exhibit biases, such as reduced diagnostic efficacy for Fitzpatrick skin types IV-VI, due to their training on non-representative datasets. This literature review explores AI's role in teledermatology and potential strategies to enhance its utility for underserved populations.

Methods: A comprehensive review of peer-reviewed literature was conducted to evaluate the integration of …

Could Telemedicine Approaches Improve Inclusivity In Spinal Cord Injury Care And Research?: Insights From Epidemiological Texas Data, Anesu Karen Murambadoro, Daniel Salinas, Victoria Elizondo, Kevin Garcia Valdez, Blake Martin, Paul Bonilla, Kelsey Baker

Research Symposium

Background: Spinal cord injury (SCI) affects hundreds of Texans, with annual healthcare costs exceeding $43,800 per individual, with the bulk of these costs coming from frequent rehabilitation visits. In a geographically vast state with only two major SCI rehabilitation centers, Texans with SCI may face substantial barriers to accessing specialized care, particularly in rural and underserved areas. Telemedicine, which encompasses remote delivery of healthcare services and rehabilitation, has offered promising solutions in easing travel burden and improving physician reach. For example, nationally, in 2021, 37.0% of individuals utilized telemedicine. Furthermore, telemedicine usage was greatest among individuals living in West and …

Be Safe Out There, Lance Plunkett Jd, Llm

The New York State Dental Journal

In recent months, NYSDA has experienced a series of cyberattacks, where members received fake e-mails purporting to be from NYSDA Trustees. These are known as phishing attacks, a form of cyberattack that attempts to engage the recipient into falling for some scam or into clicking on a link that activates malicious software.