RESEARCH

Our faculty are recognized experts in their areas of interdisciplinary research. There are three main areas of research focus in the School of Nursing including: aging; symptom science; and big data and trends in health care. The faculty have external funding from a variety of sources, including NIH, Veterans Administration, and various foundations.

FEATURED RESEARCHER

Mari Griffioen, PhD, RN

School of Nursing, University of Delaware
361 McDowell Hall, Newark, DE

Dr. Griffioen’s program of research focuses on symptom biology and in particular, understanding the underlying physiological, psychological, and genetic/genomic factors that contribute to the risk of developing chronic pain following injuries. Understanding how acute pain transitions to chronic pain is important as patients with chronic pain following injury are more likely to miss more days of work and seek medical care more frequently than patients who do not develop chronic pain following injury. In addition, these patients report high levels of pain, anxiety, and depression affecting their quality of life. To comprehensively characterize acute and chronic pain, Dr. Griffioen employs a standardized pain phenotyping protocol that includes 1) measuring peripheral sensory nerve functioning using Quantitative Sensory Testing and Current Perception Threshold testing, 2) collecting self-reported data on psychological factors such as pain, anxiety, depressive symptoms, pain catastrophizing, and effectiveness of treatment administered for pain (opioid vs. non-opioids), and 3) next generation sequencing of RNA from blood to examine the expression of candidate pain genes. Dr. Griffioen is funded by a NINR R01 to examine the transition from acute to chronic pain in patients with lower extremity fractures using the above-mentioned strategies to fully characterize the clinically relevant problem of chronic post-traumatic fracture pain, with the goals of building predictive risk models of susceptibility to chronic pain and identifying new therapeutic targets to improve the clinical management of these patients and improve quality of life.

RESEARCH AREAS OF EXCELLENCE

Aging

Symptom science

Big data and trends in health care

Aging

Experts in aging at the UD School of Nursing focus on physical function and mobility, cognitive function, cardiovascular health and chronic disease management. To measure mobility and function our experts utilize innovative methods in tracking technology to predict adverse events such as falls, urinary tract infections, and other adverse events across health care settings.

Faculty Researchers: 

Several resources exist with the SON that specifically support aging-related research.  The SON is fortunate enough to have a Jeanne K. Buxbaum Endowed chair in Aging.  Dr. Lorraine Phillips holds the Buxbaum Chair.

The SON is a member of The Multi-Professional Consortium on Gerontology, a group of professionals with expertise in gerontology, both applied and academic, with a passion for advancing the interests and welfare of older adults in our community through advocacy, activism, and scholarship.

In our Interdisciplinary labs in the STAR Tower there are shared laboratory spaces in the Aging and Symptom Translational Research Lab and Adaptive Living Apartment which focus on preventing poor outcomes and managing chronic conditions across multiple older adult populations.

Symptom science

Symptom science experts have research programs focused on the pain, sleep, mental health, disease self-management and medication adherence.

Within symptom science, experts at the UD School of Nursing focus on innovative methods and measures of pain, sleep quantity and quality across patient populations and diabetes self-management and life course transitions.

Pain:

Sleep:

Diabetes:

Big data and trends in health care

In the UD School of Nursing, nurse scientists in this area aim to understand nursing staff needs and other health care trends across patient populations, utilizing big data at the state, regional, and national levels

Faculty Researchers: