HAP Research

Paid sick leave as disease prevention

Taylor Thomas — Tue, 03 Feb 2026 17:18:24 +0000

Paid sick leave as disease prevention Taylor Thomas Tue, 02/03/2026 - 12:18

In This Story

Key Takeaways:

New research from the �鶹��Ƶ College of Public Health suggests paid sick leave should be understood not only as an employee benefit, but as a preventive public health intervention.
Among home service workers who regularly enter private homes, such as home nurses and aides and appliance repair technicians, researchers found that stress and perceived infection risk rise before a confirmed diagnosis, when workers must decide whether to stay home sick or risk losing income.
When paid sick leave is unavailable, those pressures compound. The George �鶹��Ƶ study links lack of paid sick leave to higher job stress and lower job satisfaction, effects that ripple beyond individual workers into public health.

Photo via Freepik.

Home service workers—those who provide care, inspections, or repairs inside private homes—can often lack paid sick leave, making illness a direct financial risk. New research from �鶹��Ƶ College of Public Health suggests paid sick leave should be understood not only as an employee benefit, but as a preventive health intervention.

In the study led by assistant nursing professor Suyoung Kwon, paid sick leave was linked to lower perceived infection risk, reduced job stress, and higher job satisfaction. During the early months of COVID-19, the research team surveyed more than 1,600 home service workers in South Korea, including home nurses, childcare workers, appliance repair technicians, and gas meter inspectors.

Notably, workers reported that their highest level of stress was not after a confirmed diagnosis of COVID, but during the window when workers are deciding whether to show up sick or stay home.

“Paid sick leave can function much like personal protective equipment or vaccination for workers in high-contact roles,” said Kwon. “It reduces exposure before harm occurs.”

The study was published in the Journal of Occupational and Environmental Medicine.

Study findings

Workers with paid sick leave reported significantly lower perceived risk of COVID-19 exposure than those with unpaid leave or no leave at all.
Higher perceived risk of infection was associated with greater job stress, which in turn predicted lower job satisfaction. Paid sick leave interrupted that chain.
Workers with no access to sick leave experienced both direct and indirect drops in job satisfaction, suggesting compounded harms when workers lack any safety net.

Why it matters

Many home service workers enter multiple private homes each day. When paid sick leave is available only after a documented diagnosis (like a positive test for COVID-19), workers face a high-stakes choice during their most contagious period: lose income or risk exposing others.

The researchers contend that paid sick leave should be treated as a preventive mechanism that allows workers to stay home when symptoms first appear—before diagnosis or transmission. As policymakers revisit pandemic lessons and prepare for future public health emergencies, this study suggests that expanding paid sick leave is not only a worker protection, but a population-level prevention strategy.

Topics

$3 million National Institute on Aging grant will provide much-needed support to underserved dementia caregivers

Taylor Thomas — Wed, 15 Oct 2025 13:11:07 +0000

$3 million National Institute on Aging grant will provide much-needed support to underserved dementia caregivers Taylor Thomas Wed, 10/15/2025 - 09:11

More than 7 million Americans live with Alzheimer's disease and related dementias (ADRD), supported by 12 million unpaid family caregivers whose contributions are valued at $413 billion annually. As the U.S. population continues to age, the number of people with dementia and their caregivers will nearly triple by 2050. Innovative solutions to support family caregivers are urgently needed.

Y. Alicia Hong. Photo provided.

Now, with a $3 million grant from the National Institute on Aging (NIA), �鶹��Ƶ digital health intervention researcher Y. Alicia Hong is poised to change that. Hong led an interdisciplinary team to develop the Wellness Enhancement for Caregivers (WECARE) as a culturally tailored, digital health intervention to enhance caregiving skills and improve the well-being of dementia caregivers. The new grant will allow her team to further refine WECARE using artificial intelligence (AI) and evaluate it with a randomized controlled trial.

“WECARE is one of the first personalized digital interventions for dementia caregivers,” said Hong, a professor in the College of Public Health's Department of Health Administration and Policy. "Though it is designed for Chinese American dementia caregivers, it can be adapted for other groups and serve the growing demand for digital support for dementia caregivers in an aging society

The seven-week program will provide participants with informational ADRD multimedia content, quiz games, social networking with other caregivers, personalized feedback, and additional individualized resources. WECARE’s success will be evaluated by measuring the depressive symptoms reported by participants. The project also intends to identify barriers to and facilitators of WECARE’s adoption and long-term use.

This resource comes at a critical time as the aging population grows, and more people with ADRD require caregivers. Additionally, most family caregivers have chronic conditions due to prolonged and intensive dementia caregiving, causing an increased need for resources that sustain the health of family caregivers.

Hong’s grant titled “WECARE: A Personalized Intervention for Underserved Chinese American Dementia Caregivers” will take place from September 2025 to August 2030, for a total of $3,088,427. WECARE is directly responsive to NIA’s priority of effective interventions for ADRD-affected populations.

Hong studies the intersection of health services delivery and consumer informatics. Her work explores chronic care and self-care solutions through innovative digital technologies to improve patient-centered outcomes and enhance health care accessibility. Hong’s research focuses on implementation and dissemination science and leveraging digital technologies to enhance health services delivery.

In This Story

Y. Alicia Hong, PhD

Grand Challenge Initiative

Learn more

Topics

GCI-Grand Challenge Initiative

Artificial Intelligence

George �鶹��Ƶ’s Health Services Research PhD students and faculty share policy research at AcademyHealth 2025

Mary Cunningham — Wed, 18 Jun 2025 14:46:55 +0000

George �鶹��Ƶ’s Health Services Research PhD students and faculty share policy research at AcademyHealth 2025 Mary Cunningham Wed, 06/18/2025 - 10:46

In This Story

Alison Evans Cuellar, PhD, MBA

Debora Goetz Goldberg, PhD, MHA, MBA

Gilbert Gimm, PhD, FGSA

Y. Alicia Hong, PhD

Jeah Jung, PhD, MPH

Health Services Research PhD students and faculty from the Department of Health Administration and Policy (HAP) in �鶹��Ƶ’s College of Public Health presented their research at the 2025 AcademyHealth Annual Research Meeting (ARM), held June 7 to 10 in Minneapolis, Minnesota.

As the nation’s premier forum for health services research, AcademyHealth’s Annual Research Meeting brings researchers and health system leaders together to examine how policy, payment, and technology affect cost, access, and quality of care.

HAP PhD students and faculty delivered a range of presentations, covering healthcare worker burnout, digital health interventions, and Medicare policy. Their participation underscores HAP's commitment to applied research, interdisciplinary collaboration, and real-world impact.

PhD student presenter, Ge Song, reflected on her experience at the conference, where she presented her recent research on using circadian patterns in vital signs to improve hospital mortality prediction:

“Presenting my findings at the 2025 AcademyHealth Annual Research Meeting was a rewarding experience. I had the opportunity to connect with clinical researchers who offered thoughtful suggestions, particularly around clinical interpretation and modeling, that will shape the next phase of my analysis.”

Yiwen Li shared her perspective as a first-year doctoral student:

“Attending AcademyHealth ARM 2025 has been a wonderful experience. In my session, I was honored to present our WeCare 2.0 outcome evaluation and share how culturally tailored digital health interventions can support underserved family dementia caregivers. Beyond my own session, I also learned a lot from other presentations focusing on innovative care models and methods addressing health disparities, especially among aging, minority, and high-need populations.”

Why It Matters

Presenting at AcademyHealth is a vital part of advancing the field of health services research. It reflects the mission of �鶹��Ƶ’s Health Services Research PhD program to train future scholars who can generate evidence and effectively communicate findings to improve healthcare delivery and policy. By presenting research in person, HAP students, faculty, and alumni engage with national thought leaders, foster interdisciplinary collaborations, and shape healthcare systems.

“By showing up in person to share our work, the HAP department is contributing to a growing field that aims to improve access to health care services and, in turn, the well-being of families and individuals,” said Gilbert Gimm, director of the Health Services Research PhD program. “It’s also a fun way to build new connections and potential collaborations.”

George �鶹��Ƶ faculty and PhD student presenters at the 2025 AcademyHealth Annual Research Meeting

Alison Cuellar, PhD, �鶹��Ƶ
Panel Speaker: Opportunities for Improving and Learning from Transparency in Coverage Data
Gilbert Gimm, PhD, �鶹��Ƶ
Poster Presentation: Assessing Cannabis Smoking, Vaping, and Edible Use Among U.S. Adults by Disability Status in 2022
Debora Goldberg, PhD, MHA, MBA, �鶹��Ƶ
Poster Presentation: Exploring Job Satisfaction and Burnout Among Healthcare Workers Using the Surgeon General's Framework for Workplace Mental Health and Well-Being
Session Chair: From Burnout to Retention: Bridging Individual Struggles and Systemic Solutions
Y. Alicia Hong, PhD, �鶹��Ƶ
Podium Presentation: Evaluation of Stronger2 Project: A Community-Government-Academic Partnership to Enhance Resilience and Reduce Health Disparities
Jeah Jung, PhD, �鶹��Ƶ
Poster Presentation: Use of Low-Value Cancer Treatments in Medicare Advantage Versus Traditional Medicare
Yiwen Li, MPH, PhD student, �鶹��Ƶ
Podium Presentation: Evaluation of WeCare 2.0: A Digital Health Intervention for Chinese American Dementia Caregivers
Ge Song, PhD student, �鶹��Ƶ
Poster Presentation: Integrating Circadian Rhythms of Vital Signs into In-Hospital Mortality Prediction Models

Beyond the Conference

�鶹��Ƶ’s engagement with AcademyHealth extends beyond the ARM. The university is home to an official AcademyHealth Student Chapter, offering students year-round access to leadership opportunities, national events, and professional development in health services research.

Looking Ahead

Involvement in national conferences such as AcademyHealth, the American Medical Informatics Association (AMIA), and the American Public Health Association (APHA) affirms �鶹��Ƶ’s growing presence in research on health policy, informatics, and public health. With each presentation, the HAP department is preparing the next generation of leaders in health services research.

Topics

PhD in Health Services Research

Groundbreaking mobile app captures and documents bruises to help survivors of interpersonal violence

mthomp7 — Thu, 05 Jun 2025 16:47:09 +0000

Groundbreaking mobile app captures and documents bruises to help survivors of interpersonal violence mthomp7 Thu, 06/05/2025 - 12:47

Anonymous donor commits additional $5.3 million to advance research

An interdisciplinary �鶹��Ƶ research team is breaking new ground in using artificial intelligence to support victims of interpersonal violence. Led by Kat Scafide and Janusz Wojtusiak of the College of Public Health and David Lattanzi of the College of Engineering and Computing, the Evidence-based AI Software for Injury Detection (EAS-ID) project has successfully completed Phase 1: development of a working prototype of a mobile app designed to accurately capture and document bruises.

The tool has the potential to transform how clinicians and frontline professionals identify, record, and communicate evidence of injury, particularly in cases of interpersonal violence.

The EAS-ID (Evidence-based AI Software for Injury Detection) project has successfully completed Phase 1: development of a working prototype of a mobile app designed to accurately capture and document bruises. An anonymous donor recently committed an additional $5.3 million to advance the technology. Photo by Mary Cunningham/College of Public Health

The EAS-ID app acts as a digital guidance system—similar to mobile check-deposit apps that help users capture clear, usable images. When a clinician uses the tablet-based tool, the app detects the presence of a bruise and provides real-time guidance to ensure the image meets clinical and legal standards. A rectangle tracks the injury area, much like facial recognition technology, ensuring the final image captures exactly what’s needed to document the bruise effectively.

The research team announced $4.85 million in initial funding from the same anonymous donor in March 2024.

“Initially, we were laser-focused on detection—how to identify whether a bruise was present,” said Scafide, a forensic nurse. “But Phase 1 taught us that detection is only a small part of the clinical and legal challenge. The real complexity lies in documentation.”

That documentation must be both clinically sound and legally reliable. Forensic nurses—the app’s initial target users—often assess injuries while juggling multiple tasks: shining a light, holding a camera, completing paperwork. The EAS-ID tool reduces that burden by enabling simultaneous photo capture and structured documentation.

The app’s workflow is tailored to the real-world conditions of forensic nursing. It walks users through a standardized documentation process built directly into the interface, making it possible to create accurate, consistent records that can hold up in court—even years later.

“The documentation that nurses create is reviewed by many others in the criminal justice system,” noted Lattanzi, a civil engineer. “It must be reliable—not a liability.”

To ensure the app meets forensic standards, the team conducted extensive focus groups with practicing forensic nurses. These sessions were crucial to understanding not just what needed to be documented, but how clinicians make decisions in real time under pressure. Their insights helped shape the app into a useful tool with intuitive guide rails and legal relevance.

Based on Phase 1 progress, the team is preparing to broaden its focus to include a wider range of users. “We’re exploring how to adapt the app for clinicians—and even non-clinicians—who don’t have a forensic background but still need to document injuries,” said Scafide.

Wojtusiak, a machine learning expert, added: “Think of it like TurboTax. You don’t need to be a CPA to file your taxes. We want to make it possible for someone who sees fewer IPV cases—or who isn’t an expert in injury documentation—to still collect reliable evidence.”

Behind the app, a powerful AI engine is being trained to distinguish bruises from other skin discolorations and guide users through appropriate documentation steps. To train the AI, the team is building a massive, diverse dataset. So far, they’ve partnered with Inova Health System and Adventist Healthcare Shady Grove Medical Center to collect tens of thousands of images across different skin tones, body types, and medical conditions.

“Deep learning requires scale—and the team has set a goal of collecting one million images,” said Wojtusiak.

This summer, the team will launch a crowdsourcing initiative to expand the dataset beyond clinical settings. “All of our current data was collected in labs, under controlled conditions,” explained Scafide. “But real-world data is messier. We need to understand what the photos and data will look like when collected by the public, outside of protocols.”

The app’s architecture was designed with that in mind. Using machine learning, the app evolves over time—each new image improves its performance. This allows for continual refinement, even after the app is deployed.

The project has moved at an unusually fast pace for an academic endeavor, thanks in part to the support of students and research assistants whose contributions have accelerated development while gaining invaluable experience. Continued progress has been made possible by a second round of funding from the same anonymous donor.

With a patent pending on the app’s innovative integration of image capture and health assessment data, the EAS-ID team is now preparing to scale development, deepen partnerships, and explore commercialization pathways.

“Our goal is to get this technology into the hands of people who need it—quickly,” said Scafide. “The faster we can deploy, the faster we can support the professionals working to protect and care for victims.”

Grand Challenge Initiative

Explore George �鶹��Ƶ’s Grand Challenge Initiative addressing the greatest threats to humanity’s ability to live a peaceful, healthy, prosperous, and just existence.

“Think of it like TurboTax. You don’t need to be a CPA to file your taxes. We want to make it possible for someone who sees fewer IPV cases—or who isn’t an expert in injury documentation—to still collect reliable evidence.”

In This Story

Katherine Scafide, PhD, RN, FAAN, FAAFS

Janusz Wojtusiak, PhD

David Lattanzi

Topics

EAS-ID

Bruise Visibility

Research

College of Public Health

College of Engineering and Computing

CEIE Success Stories

GCI-Grand Challenge Initiative

Interprofessional George �鶹��Ƶ researchers awarded more than $1 million to improve outcomes for patients with depression

Jennifer Pocock — Tue, 10 Dec 2024 18:25:35 +0000

Interprofessional George �鶹��Ƶ researchers awarded more than $1 million to improve outcomes for patients with depression Jennifer Pocock Tue, 12/10/2024 - 13:25

Researchers Farrokh Alemi and Kevin Lybarger receive �鶹��Ƶ’s first Patient-Centered Outcomes Research Institute (PCORI) award to develop innovative Artificial Intelligence (AI) technology, including large language models, for improving antidepressant recommendations.

Farrokh Alemi and Kevin Lybarger

AI will soon receive a dose of empathy with the goal of helping to match people with depression to their best-fit medication. A team led by Farrokh Alemi, a professor in the College of Public Health (CPH), and Kevin Lybarger, an assistant professor in the College of Engineering and Computing (CEC), received $1,049,998 in research funding from the Patient-Centered Outcomes Research Institute (PCORI) to continue their work on developing an AI system that helps patients find the right depression medications.

With this funding support, Co-PIs Alemi and Lybarger will hone large language models (LLMs) to address known challenges in AI, including mitigating biases, reducing the potential for inaccurate information, and incorporating an empathetic tone, according to Alemi.

The new study will introduce an innovative way for AI to help patients make medication decisions. The AI system will engage patients in natural-language conversations to collect information about their medical history. The system will draw upon more than 10 million patient experiences with 15 different oral antidepressants and a National Institutes of Health All of Us database, which includes records from more than 80,000 participants with major depressive disorders, to help create a plan that is statistically likely to succeed. Alemi and Lybarger believe this will help alleviate the trial and error that can lead to negative patient outcomes.

The researchers will also introduce a first-of-its-kind patient simulator capable of mimicking various medical, linguistic, and behavioral characteristics. This simulator will be used to test and refine the AI system by simulating diverse patient scenarios, including infrequent but critical events such as suicidal ideation, to ensure the system’s recommendations are safe, culturally sensitive, and empathetic.

“This study was selected for its potential to address a high-priority methodological gap in patient-centered comparative clinical effectiveness research,” said PCORI Executive Director Nakela L. Cook. “We look forward to following the study’s progress and working with George �鶹��Ƶ to share the results.”

This is the first PCORI-funded study that George �鶹��Ƶ has received. “Depression is a major public health problem and we are excited to see the development of new AI-based decision tools, leveraging the multidisciplinary talents of our college to help tackle it,” said CPH Associate Dean of Research Alison Cuellar.

"This innovative study promises to generate methodologies for using AI for medical decision-support and for empowering patients to make critical health decisions beyond mental health,” says Özlem Uzuner, chair of CEC’s Department of Information Sciences and Technology.

This study is one of the latest funded by PCORI to examine which medical treatments work best, where and when treatment falls flat, and how to address the gaps. These studies deliver results that guide researchers in planning future studies and provide patients, their caregivers, and clinicians with the evidence-based information needed to make better-informed health and health care decisions.

In This Story

Farrokh Alemi, PhD

Kevin Lybarger

Alison Evans Cuellar, PhD, MBA

Özlem Uzuner

Research at George �鶹��Ƶ

Topics

grants

Depression

antidepressants

natural language processing

Artificial Intelligence

Strategic Direction

CEC faculty research

�鶹��Ƶ Momentum

Online learning expert suggests best practices for promoting academic honesty

Jennifer Pocock — Tue, 13 Aug 2024 17:44:33 +0000

Online learning expert suggests best practices for promoting academic honesty Jennifer Pocock Tue, 08/13/2024 - 13:44

In This Story

John Cantiello, PhD, FACHCA

The growing popularity of easy-to-use artificial intelligence (AI) interfaces has reignited discussions about cheating in academics. Academic dishonesty, however, is a long-standing concern for faculty and a burgeoning area of research for online coursework. Whether cheating is more or less prevalent in remote coursework has been the topic of debate since online coursework went mainstream in the early 2000s. While online learning provides access to education for nontraditional students and in nontraditional circumstances (such as the COVID-19 pandemic), it’s important to ensure that students are authentically learning the material.

John Cantiello. Photo provided

To understand the prevalence of cheating and help teachers address it, John Cantiello, a professor of the Department of Health Administration and Policy, reviewed the existing literature on the topic. In the Journal of Health Administration Education, Cantiello, who was honored last year as an online teacher of distinction by the Stearns Center of Teaching and Learning, reports that many methods for preventing academic dishonesty are effective.

Not everyone agrees on what constitutes “dishonesty,” he points out. While some forms of cheating are clear-cut—having others do assignments or take tests in the place of the student, plagiarism, or copying answers, others are not. Up for debate are the use of tools like artificial intelligence, or consulting publications that, in a professional setting, would be available to them while solving problems.

“This paper illustrates varying results on the frequency of cheating in online, college-level courses,” Cantiello said. “Tools and strategies for preventing academic dishonesty vary in effectiveness, but some show significant success.”

Cantiello examined many different interventions to prevent online academic dishonesty, including frequent discussions on what constitutes cheating and plagiarism (e.g., can they use AI tools in this course?), technology (e.g., biometric hardware and software such as Turnitin or Examity), and varied testing strategies (e.g., limiting testing times, multiple versions of tests, and leaking fake answers online).

He suggests that a combination of strategies is the best way to limit cheating. “A holistic approach to course design that incorporates these elements and includes a variety of learning activities fosters an effective learning environment where academic integrity can be upheld,” Cantiello said. However, he says, more research is needed on how often and in what capacity cheating happens.

“Preventing Academic Dishonesty in Online Courses: Best Practices to Discourage Cheating” was published online in March 2024 in the Journal of Health Administration Education. Renee Hotchkiss Geschke is co-author on the paper.

Topics

College of Public Health

Artificial Intelligence

College of Public Health receives NIH grant to pilot AI chatbot for African Americans with depression

Mary Cunningham — Mon, 10 Jun 2024 17:03:05 +0000

College of Public Health receives NIH grant to pilot AI chatbot for African Americans with depression Mary Cunningham Mon, 06/10/2024 - 13:03

In This Story

Farrokh Alemi, PhD

Janusz Wojtusiak, PhD

Kevin Lybarger

As a leader in innovative health solutions, �鶹��Ƶ’s College of Public Health received a National Institutes of Health (NIH) AIM-AHEAD program grant to pilot an artificial intelligence (AI) chatbot for Black and African Americans with depression. Professor Farrokh Alemi will enhance his first-of-its-kind, evidence-based artificial intelligence tool to address the medication needs of African Americans with depression.

Professor of Health Informatics Farrokh Alemi

The existing AI tool recommends antidepressants for 16,775 general-population patient subgroups, each representing a unique combination of medical history. For each of these subgroups, the current project will analyze the effectiveness and appropriateness of the recommendations for African Americans, using the NIH All of Us database and existing published literature.

To the researchers' knowledge, this is the first research focused on developing and evaluating an antidepressant recommendation system for Black and African American people.

“Antidepressant medications are a first-line treatment for depression; however, a majority of depressed patients do not experience improvement with their first antidepressant. Additionally, minority populations, including Black and African Americans, are not well represented in antidepressant studies, contributing to reduced antidepressant effectiveness in these populations,” said Alemi. “There is a significant need to synthesize available evidence regarding antidepressant effectiveness and provide personalized treatment recommendations, and this project addresses a major gap in the management of Black and African Americans with depression.”

Researchers will develop a Knowledge-enhanced Antidepressant Recommendation Dialogue System (KARDS), which will engage users in a back-and-forth conversation to acquire the patient information needed to identify the appropriate antidepressant medication. The AI will provide the patient with a list of recommended medications, list of the relevant studies, and an explanation for the medication decisions. The system will automatically send the patient’s clinician a brief point-of-care recommendation and explanation, with an option to examine a complete record of the conversation and the supporting evidence.

“Chatbots—or patient-facing dialogue systems like the one we will create—hold transformative potential for the health care sector and are increasingly prominent in psychiatric applications, predominantly through therapy-bot implementations,” said Alemi. “Our chatbot will help improve the detailed, time-consuming, medical history intake process, and provide point-of-care summary and prescription recommendations to the patients’ clinicians. The chatbot will make patients more comfortable because the natural language modality provides an intuitive, empathetic, stigma-free interface.”

Once the AI chatbot is developed, the team will test the dialogue system with Black and African American patients to evaluate system functionality and user preferences. Additionally, the project will train a Black or African American doctoral or master’s student in AI, expanding the available workforce and building the community’s capacity to address AI.

Alemi will lead the research team, which includes Janusz Wojtusiak, a George �鶹��Ƶ professor of Health Informatics and the director of the Machine Learning and Inference Laboratory, and Kevin Lybarger, a George �鶹��Ƶ assistant professor in the Department of Information Sciences and Technology in the College of Engineering and Computing. All three members have collaborated previously to diagnose COVID at home from presenting symptoms.

The $70,906 grant is part of the NIH’s AIM-AHEAD (Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity) program, which aims “to establish mutually beneficial and coordinated partnerships to increase the participation and representation of researchers and communities currently underrepresented in the development of AI/machine learning models and enhance the capabilities of this emerging technology, beginning with electronic health record data.”

Innovate for Good is an ongoing series that examines how George �鶹��Ƶ faculty in the College of Public Health are harnessing technology to improve health outcomes.

If you have stories to share as part of the Innovate for Good series, email Mary Cunningham at mcunni7@gmu.edu.

Topics

Tech Talent Investment Program (TTIP)

Artificial Intelligence

George �鶹��Ƶ researchers harness the power of artificial intelligence to match patients with the most effective antidepressant for their unique needs

Mary Cunningham — Wed, 29 May 2024 19:46:58 +0000

George �鶹��Ƶ researchers harness the power of artificial intelligence to match patients with the most effective antidepressant for their unique needs Mary Cunningham Wed, 05/29/2024 - 15:46

Researchers in �鶹��Ƶ’s College of Public Health have leveraged the power of artificial intelligence (AI) analytical models to match a patient’s medical history to the most effective antidepressant, allowing patients to find symptom relief sooner. The free website, MeAgainMeds.com, provides evidence-based recommendations, allowing clinicians and patients to find the optimal antidepressant the first time.

Farrokh Alemi, principal investigator and professor of health informatics at �鶹��Ƶ’s College of Public Health

“Many people with depression must try multiple antidepressants before finding the right one that alleviates their symptoms. Our website reduces the number of medications that patients are asked to try. The system recommends to the patient what has worked for at least 100 other patients with the same exact relevant medical history,” said Farrokh Alemi, principal investigator and professor of health informatics at �鶹��Ƶ’s College of Public Health.

AI helped to simplify the very complex task of making the thousands of guidelines easily accessible to patients and clinicians. The guidelines that researchers created are complicated because of the amount of clinical information that is relevant in prescribing an antidepressant; AI seamlessly simplifies the task.

With AI at its core, MeAgainMeds.com analyzes clinician or patient responses to a few anonymous medical history questions to determine which oral antidepressant would best meet the specific needs. The website does not ask for any personal identifiable information and it does not prescribe medication changes. Patients are advised to visit their primary health care provider for any changes in medication.

In 2018, the Centers for Disease Control reported that more than 13% of adults use antidepressants, and the number has only increased since the pandemic and other epidemics since 2020. This website could help millions of people find relief more quickly.

Alemi and his team analyzed 3,678,082 patients who took 10,221,145 antidepressants. The oral antidepressants analyzed were amitriptyline, bupropion, citalopram, desvenlafaxine, doxepin, duloxetine, escitalopram, fluoxetine, mirtazapine, nortriptyline, paroxetine, sertraline, trazodone, and venlafaxine. From the data, they created 16,770 subgroups of at least 100 cases, using reactions to prior antidepressants, current medication, history of physical illness, history of mental illness, key procedures, and other information. The subgroups and remission rates drive the AI to produce an evidence-based medication recommendation.

“By matching patients to the subgroups, clinicians can prescribe the medication that works best for people with similar medical history,” said Alemi. The researchers and website recommend that patients who use the site take the information to their clinicians, who will ultimately decide whether to prescribe the recommended medicine.

Alemi and his team tested a protype version of the site in 2023, which they advertised on social media. At that time, 1,500 patients used the website. Their goal is to improve the website and expand its user base. The initial research was funded by the Commonwealth of Virginia and by the Robert Wood Johnson Foundation.

The researchers’ most recent paper in a series of papers on response to antidepressants analyzed 2,467 subgroups of patients who had received psychotherapy. “Effectiveness of Antidepressants in Combination with Psychotherapy” was published online in March 2024. Additional authors include Tulay G Soylu from Temple University, and Mary Cannon and Conor McCandless from Royal College of Surgeons in Dublin, Ireland.

In This Story

Farrokh Alemi, PhD

Discover more Research from the College of Public Health

Topics

Artificial Intelligence

Tech Talent Investment Pipeline (TTIP)

TTIP

Tech Talent Investment Program

Research

In the George

�鶹��Ƶ CARES intervention reduces stress and feelings of burden of family caregivers of older adults with dementia

Mary Cunningham — Wed, 29 May 2024 15:50:53 +0000

�鶹��Ƶ CARES intervention reduces stress and feelings of burden of family caregivers of older adults with dementia Mary Cunningham Wed, 05/29/2024 - 11:50

In This Story

Dr. Cathy Tompkins

Gilbert Gimm, PhD, FGSA

According to the U.S. Centers for Disease Control and Prevention, 80% of those living with dementia receive informal care from family members or friends. This equates to 16 million family caregivers in the U.S. However, caring for family members with dementia is often associated with increased caregiver burden (which includes emotional, physical, and financial strain), stress, and worse physical health for the caregiver.

Catherine Tompkins, principal investigator, professor of social work, and associate dean of faculty and staff affairs in the College of Public Health.

A recent study published in the Journal of Applied Gerontology, led by �鶹��Ƶ researchers, found that a 9-week online stress management intervention program for family caregivers reduced burden scores by 15% for 97 family caregivers of older adults living with dementia. The Stress-Busting Program for Family Caregivers TM, intervention was specifically designed to help family caregivers manage their own stress when caring for older adults living with dementia or a chronic illness

“In this study, we found evidence of a range in average caregiver burden levels based on the dementia severity category of care recipients. The findings show that an online Zoom intervention in a peer group setting can be beneficial for family caregivers of older adults with mild, moderate, or severe dementia,” said Catherine Tompkins, principal investigator, professor of social work, and associate dean of faculty and staff affairs in the College of Public Health.

The intervention provided family caregivers with education and strategies to manage stress when caring for someone living with dementia. Examples of self-care techniques included breathing and meditation; troubleshooting behaviors associated with dementia; and peer-to-peer support within a virtual group setting.

Associate Professor Gilbert Gimm

“Reducing caregiver burden and managing stress are critical to the well-being of families. These findings show that effective stress management interventions for family caregivers can be facilitated through online peer groups,” said Gilbert Gimm, first author and associate professor of health administration and policy.

“�鶹��Ƶ Caregivers Aiming for Resilience, Empowerment, and Support Study: Assessing Family Caregiver Burden Post-Intervention” was published online in April 2024. Co-authors include George �鶹��Ƶ Associate Professor Megumi Inoue, Professor Emily Ihara, �鶹��Ƶ CARES Project Manager Shannon Layman, and Master of Social Work alumna graduate Harveen Pantleay. This study was supported by a grant (#2021048) from the Retirement Research Foundation (RRF).

The study is part of a larger project, entitled �鶹��Ƶ CARES (Caregivers Aiming for Resilience, Empowerment, and Support), that implemented and assessed interventions for family caregivers.

Topics

Tech inefficiencies, piles of (electronic) paperwork, and increased patient volume contribute to burnout of primary care physicians, study finds

Mary Cunningham — Tue, 30 Jan 2024 18:11:13 +0000

Tech inefficiencies, piles of (electronic) paperwork, and increased patient volume contribute to burnout of primary care physicians, study finds Mary Cunningham Tue, 01/30/2024 - 13:11

In This Story

Debora Goetz Goldberg, PhD, MHA, MBA

Burnout is an occupational phenomenon that results from chronic workplace stress, according to the World Health Organization.

Burnout often includes emotional exhaustion, negative feelings or mental distance from one’s job, and a low sense of accomplishment at work. COVID-19 increased feelings of burnout in primary care physicians, and a new study, sought to understand primary care clinicians’ perspectives on burnout during the COVID-19 pandemic, the causes of burnout, and strategies to improve clinician well-being.

Debora Goldberg

Inefficiencies of electronic health records systems and high levels of documentation contribute to burnout, according to clinicians participating in a recent study led by Debora Goldberg, associate professor in �鶹��Ƶ’s College of Public Health. Other contributors to burnout included high patient volume, staffing shortages, and expectations for responding to patient emails and telephone calls. Most participants also described the need to work after clinic hours to complete documentation.

“The results of this study provide an in-depth view of participating clinicians’ experiences and perceptions of burnout and other mental health challenges. These viewpoints can improve awareness of the issues and strategies to improve the health and well-being of our clinician workforce,” said Goldberg, the principal investigator.

Most of the suggested strategies to improve clinician well-being were changes at the organizational level and included increasing efforts to improve work-life balance, enhancing the use of team-based care models, optimizing electronic health record functions, providing accessible mental health services, granting additional administrative time to complete documentation, and increasing institutional awareness and recognition of the issues surrounding burnout.

Additionally, clinicians reported experiencing traumatic events during the pandemic and in some cases reported both burnout and depression. The study findings align with previous research that reported primary care physicians indicated dramatic increases in their workload since the beginning of the pandemic and an escalation in staffing issues, both contributing to an increase in burnout and stress among clinicians.

This research was funded by the Health Resources and Services Administration, Health and Public Safety Workforce Resiliency Training Program (1 U3NHP45404-01-00), and �鶹��Ƶ College of Public Health Intramural Pilot Study Funding.

“Anxiety, COVID, Burnout and Now Depression”: a Qualitative Study of Primary Care Clinicians’ Perceptions of Burnout” was published in the Journal of General Internal Medicine in November 2023. Tulay Soylu from Temple University; Carolyn Faith Hoffman, a �鶹��Ƶ doctoral student; and Rachel E. Kishton and Peter F. Cronholm from the University of Pennsylvania are co-authors.