Research Faculty

Dr. Bendixen ‘s translational research focuses on the clinically and scientifically important topic of infant nutrition. This area intersects maternal/infant healthcare with the biological and physiological mechanisms of insufficient mothers’ own milk (MOM) volume among mothers who deliver an infant(s) admitted to the neonatal intensive care unit (NICU).

Dr. Bjarnadottir’s area of expertise is Nursing Informatics, Data Science, Clinical Decision Support, Quality of Care, Underserved Populations.

Leveraging health informatics and data science to improve health care quality for underserved populations. Dissertation research examined home care nurses’ assessment and documentation of patients’ sexual orientation and gender identity. Has also explored EHR implementation and nurses experiences with documentation systems in the long-term care setting. In current research, uses text-mining methods to identify factors associated with risk of patient falls in acute care nurses’ progress notes.

Dr. Booker’s areas of expertise are aging, pain assessment and management, and health/pain disparities in ethnic/racial minorities.

Dr. Carrington’s areas of expertise include Informatics, electronic health record, human factors, and communication.

Dr. Cho’s areas of expertise are nursing informatics, electronic health records, clinical decision support, mobile health, usability, symptom science, innovative methods, health disparities and underserved populations. Her recent research focuses on how to design and tailor technology-based interventions for vulnerable groups. Technology-based intervention have the potential to be an effective delivery mode of health information for underserved populations with chronic diseases because these populations often face barriers to accessing health information. An important part of her research is evaluating the usability of health information technology with an in-depth understanding of interactions between user, system, task, and real-world environment. As usability factors are major obstacles to technology adoption, usability must be considered before and after prototyping takes place to support the quality of technology in use. Dr. Cho has conducted multi-level usability evaluations using the most appropriate evaluation methods at each stage throughout the development process of the technology, including both quantitative as well as qualitative approaches, such as an innovative eye-tracking method, a card sorting technique, a heuristic evaluation, a cognitive walk-through, think-aloud protocols, focus groups and in-depth interviews.

Dr. Cousin’s areas of expertise are cancer prevention and survivorship, cardiovascular health, psychosocial care, and health disparities research.

Dr. Dungan’s primary area of scientific expertise is in the use of genetic epidemiology approaches to the study of complex cardiovascular diseases and outcomes. Specific areas of expertise involve: candidate gene and genome-wide association studies of large cardiovascular genetics datasets; and, survival-, age- and sex-associated analyses involving genetic predictors. Dr. Dungan is also interested in collaborating on projects related to women’s heart disease, functional genetic studies of coronary disease candidate genes, and clinical and genetic biorepositories.

Health disparities in pain management, particularly, healthcare injustice, a psychological stressor, as an explanatory factor for the disparities; pain and symptom management for people with sickle cell disease or cancer; palliative care for end-of-life cancer patients; biobehavioral research including cortisol as a biomarker of stress and use of computer technologies for stress and pain measurement, and delivery of stress reduction intervention in sickle cell disease.

Expertise in ethnic-minority immigrant health disparities research, mental health/well-being, distress symptoms, immigration-related stress/stressors

Pain and aging; pain management in persons with dementia, predictors of persistent post-surgical pain; and pain at end of life.

Dr. Keenan’s innovative research focuses on capturing standardized nursing and clinical data for improving the planning, delivery, cost and health outcomes of nursing care across the continuum. She has developed HANDS, the “Hands-on Automated Nursing Data System”, that provides rich data that represents nursing care provision, measures care impact and supports care planning over time.

Dr. Keenan’s research priorities include:

1. Continuously refining and expanding a simple universal automated method for collecting a “Big Picture” standardized clinical data set (HANDS) for the multiple purposes of:

— Providing a current and historical summary of care wherever the patient presents that is always in the same format and utilizes standardized terminologies

— Supporting day to day communication and handoffs (SHARER) of members of the patient’s care team within and across settings

— Connecting universally to all EHRs

— Generating standardized data for use in evaluating care, identifying and disseminating best practices, and benchmarking across systems

2. Building and continuously improving methods of analyzing standardized data captured in HANDS and translating this into meaningful and immediately useful decision support at the point of care.

3. Demonstrating the impact of the HANDS “Big Picture” method on reducing the cost of care for chronically ill patients (sickle cell, cardiac, eol and others)

4. Demonstrating the value of HANDS data in identifying nurse training and competency needs as well as providing rationale for appropriate staffing

5. Enabling wide scale diffusion of HANDS into education/practice

She is currently involved in the following research activities:

Dr. Keenan’s research focuses on developing and refining a feasible automated methodology for collecting a standardized clinical data set for the purpose of improving the planning, delivery, cost and health outcomes of nursing care across the continuum. She is currently involved in the following research activities:

HANDS Research Project Refinement of a web based software and method for nurses to document their patient care in the electronic health record and communicate with other members of the interdisciplinary team. The Hands-on Automated Nursing Data System (HANDS) is a standardized plan of care method in which the patient’s plan is updated at every nurse hand-off allowing the interdisciplinary team to track the story about care and progress toward desired outcomes in a standardized format across time and units. The HANDS Method includes a standardized interface, database, rules of data entry and rules for use of the plan in hand-offs and in interdisciplinary communication.

The HANDS related research and researchers have been nominated and received numerous awards. The research agenda is currently funded by NINR for a 4 year R01 focused on thoroughly evaluating HANDS standardized data (through datamining and statistical analyses) and generating best practices and benchmarks for EOL hospitalized patients. Also the research grant is funding the immediate translation of findings into useful and meaningful decision support at the point of care.

Research goals are directed toward understanding the biological mechanisms and behaviors that mediate symptoms of chronic illness, with a population focus in oncology.

Dr. Lynch Kelly’s primary research goals are directed toward understanding the biological mechanisms and behaviors that mediate symptoms of chronic illness, with a population focus in oncology. She has worked closely with cancer survivors managing persistent, distressing symptoms and has studied the effects of inflammation on symptoms. Her future research plans are aimed at further describing the relationships of inflammatory and genetic markers and symptom expression in individuals with cancer. Ultimately she will explore interventions that may be used as adjuvant therapies to mitigate distress of symptoms. Her national certification is as an oncology certified nurse.

Symptom management, including complementary modalities, in women with breast cancer and other chronic illnesses. Biobehavioral research, including molecular markers of inflammation and genetic markers.

Dr. Macieira is an expert in nursing informatics, standardized terminologies, and data science, with experience in applying machine learning methods in research on aging, mainly the impact of nursing care on patient outcomes for cognitively impaired older adults. Throughout her career, she has examined the impact of nursing care on patient outcomes for populations with life-limiting chronic conditions (e.g., older adults, critically ill inpatients) through the analysis of nursing data retrieved from electronic health records (EHRs) from diverse health settings. Her post-doctoral fellowship focused on the identification of methods for integrating nursing care plan data gathered in EHRs into the statewide OneFlorida Clinical Research Consortium Data Trust (i.e., OneFlorida Data Trust).

Using technology for cancer prevention and control, specifically, the treatment of nicotine dependence.

Dr. Menzies area of expertise is nonpharmacological interventions and symptom management in fibromyalgia and other non-malignant chronic pain syndromes with expertise in examining underlying biological mechanisms. Recently she has shifted her research focus to identifying individual characteristics and social determinants of health that increase risk for chronic pain, with the long-term goal of designing interventions that mitigate chronic pain in high-risk individuals.

Nutrition of critically ill and premature infants. Increasing delivery of breast milk. Decreasing insufficient milk supply and delayed lactogenesis stage II. Assessment of gastric residuals.

Dr. Pruinelli’s program of research leverages innovative applied clinical informatics tools and data science methods to investigate the trajectories of complex disease conditions, such as sepsis, solid organs transplantation, and pain management, to improve the patient care experience and increase the quality of health care delivery. She developed foundations for new personalized strategies for disease treatment and management over time, including addressing national initiatives for holistic models of care. Her scholarship reflects a strategic transition from an acute care nurse to a researcher, leveraging nursing informatics based on consistent formal education, previous clinical care experiences, and nursing science to build new knowledge. To guide her program of research, Dr. Pruinelli adopt the Applied Data Science Framework for Healthcare Leaders, a roadmap she developed, where shows the life-cycle process to build personalized models of care suitable of clinical applications. Similarly, with the heavily adoption of machine learning across her projects and the adoption of such models to lay the foundation for intelligent systems, she has been deeply involved in discussions around responsible Artificial Intelligence (AI). For more than 10 years she have mainly centered on using data for solid organ transplantation research. Besides survivorship, she has been investigating other factors that has impact on the overall health status and wellbeing of liver and kidney transplants patients, such as the health conditions amenable of change with targeted interventions. This work is a life-long project, due to the complexity of these patients and the multiples factors contributing to successful outcomes.

Prospective students may want to check Dr. Pruinelli’s Advising Philosophy.

Dr. Scarton, a citizen of Choctaw Nation, focuses her research on reducing health disparities among American Indian populations through the development of culturally informed interventions delivered across multiple generations and designed to improve health outcomes for persons with type 2 diabetes and T2D linked cancers.

Type 2 diabetes self-management, family interventions, health disparities, health promotion in American Indian populations.

Mental health, health promotion, social health determinants, community-based interventions, minority and underserved populations, mixed-methods and social network analysis.

Pain and Symptom Management, Self-Management Science, Oncology & Chronic Disease Management, Opioid Addiction, Intervention Development and Evaluation, Patient Reported Outcomes, Genomics/Omics

Dr. Terry’s areas of expertise include the influence of biopsychosocial factors on pain and pain processing, health disparities in chronic pain, knowledge in the etiology and course of various mental disorders (e.g., Major Depressive Disorder, Anxiety Disorder), the use of cognitive-behavioral therapy and other related therapies for the treatment of mental disorders, and the use of cognitive-behavioral therapy for chronic pain and pain-related psychosocial factors (e.g., pain catastrophizing).

Dr. Weaver’s research interests are in applied statistics and health prevention and promotion.

Statistical analysis, emphasizing advanced multivariate techniques; research methods; and health promotion. Ongoing Research Support

R21 NR017749 Kelly (PI) 09/27/2018–07/31/2020 Developing the Biobehavioral Foundation for Self-Management of Psychoneurological Symptoms in Hematopoietic Cell Transplant (HCT) Survivors The long-term goal of this pilot study is to elucidate the complex biobehavioral mechanisms of symptoms in individuals receiving hematopoietic cell transplantation (HCT) in order to develop targeted self-management interventions to obtain and maintain optimal quality of life (QOL) of this vulnerable patient population. To achieve this goal, we will longitudinally examine 50 adult (age > 18 years) HCT survivors and characterize associations among selected patient factors (age, sex, race/ethnicity, BMI, lifestyle habits, and clinical factors [cancer diagnosis, conditioning regimen, type of transplant] ), PN symptoms (neurocognitive dysfunction, fatigue, anxiety, depression, and pain), inflammation (cytokines and C-reactive protein), GM (richness and diversity) and Diet (macronutrients: carbohydrates, fats, and protein).

R01 NR016964 Parker (PI) 08/03/2018-05/31/2022 Optimal Feeding Tube Dwell Time in VLBW to Reduce Feeding Tube Contamination The overall objective of this 4-year study is to determine if a maximum feeding tube dwell time of 48 hours reduces contamination compared to a maximum feeding tube dwell time of 7 days (current practice), thereby improving neonatal health outcomes. Role: Statistician/Co-Investigator.

R01 NR016986 Lyon & Stechmiller (MPI) 04/01/2018-01/31/2023 Biobehavioral mechanisms underlying symptoms and healing outcomes in older individuals with CVLU The overall purpose of this study is to identify relationships between bio-behavioral factors that influence symptoms, healing trajectory, and biofilm in the wound environment in patients with chronic venous leg ulcers. The long-term goal is to elucidate the complex biobehavioral mechanisms responsible for symptoms and healing outcomes in older adults with venous leg ulcers (VLUs) for the development of targeted therapies that address both the patient-oriented outcomes and healing outcomes in this growing group of affected individuals.

Completed Research Support (last 3 years)

R01 NR014019 Parker (PI) 03/18/2013-01/31/2017 Routine Aspiration of Residual Gastric Contents in Very Low Birth Weight Infants The primary purpose of this study is to determine nutrition outcomes and risks to GI integrity and function of aspirating for Routine Gastric Contents prior to feeding in order to translate into evidence-based practice in the care of VLBW infants. The long-term goal of this program of research is to improve short and long-term health outcomes for premature VLBW infants by improving nutrition and decreasing complications due to prematurity. Role: Statistician/Co-Investigator

1I01HX001076-01 Daggett (PI) 01/01/2013-12/31/2017 Telephone Assessment and Skill-Building Intervention for Informal Caregivers The objectives of this study are to evaluate (a) the efficacy of the revised Telephone Assessment and Skill-building Kit (TASK II) in informal caregivers of veterans with stroke, and (b) estimate effect sizes for the TASK II-TBI intervention for informal caregivers of veterans with TBI. Role: Co-Investigator-Statistician

Use of informatics to promote patient-centered care; pain assessment; palliative and end-of-life care; biobehavioral therapies for cancer pain; behavioral correlates of cancer pain; sickle cell disease pain mechanisms, assessment and management; reproductive choices for people with sickle cell disease or sickle cell trait; intervention research.

Dr. Yao has expertise in study design, power analysis, including longitudinal analysis and missing data processing; machine learning, including dimensionality reduction, model estimation, selection, validation, and testing.

Research interests include 1) interventions with use of complementary and alternative medicines (CAM) modalities to improve nutritional status, cancer-cachexia and symptom management in adult patients with gastrointestinal cancers, 2) herbal supplement use to manage symptoms and health promotion in older adults, and 3) palliative care related to cancer-cachexia in patients with GI cancers.