Margaret McCarthy


Margaret M. McCarthy headshot

Margaret McCarthy


Assistant Professor

1 212 992 5796

433 First Ave
New York, NY 10010
United States

Accepting PhD students

Margaret McCarthy's additional information

Margaret McCarthy, PhD, RN, FNP-BC, FAHA, is an assistant professor at NYU Rory Meyers College of Nursing. She is a family nurse practitioner and an exercise physiologist. Her research focuses on promoting exercise in populations at risk for cardiovascular disease. She has conducted research in adults with both type 1 and type 2 diabetes. Her future research goal is to develop interventions to promote exercise in these populations, focusing on the use of technology in clinical settings. 

McCarthy received her PhD from New York University, MS in family nursing from Pace University, MA in exercise physiology from Adelphi University, and BSN from Binghamton University. She completed post-doctoral training in nursing at Yale University.

Post-doctoral training, Nursing - Yale
PhD - New York University
MS, Family Nursing Practitioner - Pace University
MA, Exercise Physiology - Adelphi University
BSN - Binghamton University

Non-communicable disease
Adult health

American Association of Nurse Practitioners
American Heart Association
Eastern Nursing Research Society
Society of Behavioral Medicine

Faculty Honors Awards

Fellow, New York Academy of Medicine (2018)
Fellow, American Heart Association (2017)
Overall Distinguished Student, NYU College of Nursing (2013)


Factors Associated With the Cardiovascular Health of Black and Latino Adults With Type 2 Diabetes

McCarthy, M. M., Fletcher, J., Wright, F., Del Giudice, I., Wong, A., Aouizerat, B. E., Vaughan Dickson, V., & Melkus, G. D. (2024). Biological Research for Nursing. 10.1177/10998004241238237
Aims: The purpose of this study was to assess the levels of cardiovascular health (CVH) of Black and Latino adults with type 2 diabetes (T2D) and examine the association of individual and microsystem level factors with their CVH score. Methods: This was a cross-sectional design in 60 Black and Latino Adults aged 18–40 with T2D. Data were collected on sociodemographic, individual (sociodemographic, diabetes self-management, sleep disturbance, depressive symptoms, quality of life, and the inflammatory biomarkers IL-6 and hs-CRP) and microsystem factors (family functioning), and American Heart Association’s Life’s Simple 7 metrics of CVH. Factors significantly associated with the CVH score in the bivariate analyses were entered into a linear regression model. Results: The sample had a mean age 34 ± 5 years and was primarily female (75%) with a mean CVH score was 8.6 ± 2.2 (possible range of 0–14). The sample achieved these CVH factors at ideal levels: body mass index <25 kg/m2 (8%); blood pressure <120/80 (42%); hemoglobin A1c < 7% (57%); total cholesterol <200 mg/dL (83%); healthy diet (18%); never or former smoker > one year (95%); and physical activity (150 moderate-to-vigorous minutes/week; 45%). In the multivariable model, two factors were significantly associated with cardiovascular health: hs-CRP (B = −0.11621, p <.0001) and the general health scale (B = 0.45127, p =.0013). Conclusions: This sample had an intermediate level of CVH, with inflammation and general health associated with overall CVH score.

Intersection of social determinants of health with ventricular assist device therapy: An integrative review

Chehade, M., Murali, K. P., Dickson, V. V., & McCarthy, M. M. (2024). Heart and Lung: Journal of Acute and Critical Care, 66, 56-70. 10.1016/j.hrtlng.2024.04.002
BACKGROUND: Social determinants of health (SDOH) may influence the clinical management of patients with heart failure. Further research is warranted on the relationship between SDOH and Ventricular Assist Device (VAD) therapy for heart failure.OBJECTIVES: The purpose of this integrative review was to synthesize the state of knowledge on the intersection of SDOH with VAD therapy.METHODS: Guided by Whittemore and Knafl's methodology, this literature search captured three concepts of interest including VAD therapy, SDOH, and their domains of intersection with patient selection, decision-making, treatment outcome, and resource allocation. CINAHL, Embase, PsycINFO, PubMed, and Web of Science were searched in March 2023. Articles were included if they were peer-reviewed publications in English, published between 2006 and 2023, conducted in the United States, and examined VAD therapy in the context of adult patients (age ≥ 18 years).RESULTS: 22 quantitative studies meeting the inclusion criteria informed the conceptualization of SDOH using the Healthy People 2030 framework. Four themes captured how the identified SDOH intersected with different processes relating to VAD therapy: patient decision-making, healthcare access and resource allocation, patient selection, and treatment outcomes. Most studies addressed the intersection of SDOH with healthcare access and treatment outcomes.CONCLUSION: This review highlights substantial gaps in understanding how SDOH intersect with patient and patient selection for VAD. More research using mixed methods designs is warranted. On an institutional level, addressing bias and discrimination may have mitigated health disparities with treatment outcomes, but further research is needed for implementing system-wide change. Standardized assessment of SDOH is recommended throughout clinical practice from patient selection to outpatient VAD care.

The Impact of an Electronic Best Practice Advisory on Patients’ Physical Activity and Cardiovascular Risk

McCarthy, M., Szerencsy, A., Fletcher, J., Taza-Rocano, L., Hopkings, S., Weintraub, H., Applebaum, R., Schwartzbard, A., Mann, D. M., D’Eramo Melkus, G., Vorderstrasse, A., & Katz, S. (2023). Journal of Cardiovascular Nursing.

Implementing Remote Patient Monitoring of Physical Activity in Clinical Practice

McCarthy, M., Jevotovsky, D., Mann, D., Veerubhotla, A., Muise, E., Whiteson, J., & Rizzo, J. R. (2023). Rehabilitation Nursing, 48(6), 209-215. 10.1097/RNJ.0000000000000435
Purpose Remote patient monitoring (RPM) is a tool for patients to share data collected outside of office visits. RPM uses technology and the digital transmission of data to inform clinician decision-making in patient care. Using RPM to track routine physical activity is feasible to operationalize, given contemporary consumer-grade devices that can sync to the electronic health record. Objective monitoring through RPM can be more reliable than patient self-reporting for physical activity. Design and Methods This article reports on four pilot studies that highlight the utility and practicality of RPM for physical activity monitoring in outpatient clinical care. Settings include endocrinology, cardiology, neurology, and pulmonology settings. Results The four pilot use cases discussed demonstrate how RPM is utilized to monitor physical activity, a shift that has broad implications for prediction, prevention, diagnosis, and management of chronic disease and rehabilitation progress. Clinical Relevance If RPM for physical activity is to be expanded, it will be important to consider that certain populations may face challenges when accessing digital health services. Conclusion RPM technology provides an opportunity for clinicians to obtain objective feedback for monitoring progress of patients in rehabilitation settings. Nurses working in rehabilitation settings may need to provide additional patient education and support to improve uptake.

Time, Technology, Social Support, and Cardiovascular Health of Emerging Adults with Type 1 Diabetes

McCarthy, M. M., Yan, J., Jared, M. C., Ilkowitz, J., Gallagher, M. P., & Dickson, V. V. (2023). Nursing Research, 72(3), 185-192. 10.1097/NNR.0000000000000645
Background Emerging adults with Type 1 diabetes (T1DM) face an increased risk of cardiovascular disease; however, there are both barriers and facilitators to achieving ideal cardiovascular health in this stage of their lives. Objectives The aim of this study was to qualitatively explore the barriers and facilitators of achieving ideal levels of cardiovascular health in a sample of emerging adults with T1DM ages 18-26 years. Methods A sequential mixed-methods design was used to explore achievement of ideal cardiovascular health using the seven factors defined by the American Heart Association (smoking status, body mass index, physical activity, healthy diet, total cholesterol, blood pressure, and hemoglobin A1C [substituted for fasting blood glucose]). We assessed the frequency of achieving ideal levels of each cardiovascular health factor. Using Pender's health promotion model as a framework, qualitative interviews explored the barriers and facilitators of achieving ideal levels of each factor of cardiovascular health. Results The sample was mostly female. Their age range was 18-26 years, with a diabetes duration between 1 and 20 years. The three factors that had the lowest achievement were a healthy diet, physical activity at recommended levels, and hemoglobin A1C of <7%. Participants described lack of time as a barrier to eating healthy, being physically active, and maintaining in-range blood glucose levels. Facilitators included the use of technology in helping to achieve in-range blood glucose and social support from family, friends, and healthcare providers in maintaining several healthy habits. Discussion These qualitative data provide insight into how emerging adults attempt to manage their T1DM and cardiovascular health. Healthcare providers have an important role in supporting these patients in establishing ideal cardiovascular health at an early age.

Associations of insomnia symptoms with sociodemographic, clinical, and lifestyle factors in persons with HF: Health and retirement study

Gharzeddine, R., McCarthy, M. M., Yu, G., & Dickson, V. V. (2022). Research in Nursing and Health, 45(3), 364-379. 10.1002/nur.22211
Insomnia symptoms are very common in persons with heart failure (HF). However, many of the correlates and predictors of insomnia symptoms in this population remain unclear. The purpose of this study is to investigate the associations of sociodemographic, clinical, and lifestyle factors with insomnia symptoms in persons with HF. A theoretical framework was adapted from the neurocognitive model of chronic insomnia to guide the study. Data from the health and retirement study were used for the analysis. Parametric and nonparametric bivariate and multivariate analyses were conducted to investigate these associations. Age, depressive symptoms, comorbidity, dyspnea, pain, and smoking had significant bivariate associations with all insomnia symptoms. Race, Hispanic ethnicity, marital status, household income, poverty, and physical activity were associated with difficulty initiating sleep (DIS) and early morning awakening (EMA). Female sex, education, and alcohol consumption had a significant bivariate association with DIS. Sleep-disordered breathing and body mass index were significantly associated with EMA. Multivariate analysis suggested that depressive symptoms, comorbidity, dyspnea, and pain had independent associations with each insomnia symptom. Age explained DIS and difficulty maintaining sleep, and significant interaction effects between age and physical activity on DIS and EMA were revealed. Results suggest that insomnia symptoms are associated with several sociodemographic, clinical, and lifestyle factors. Age below 70 years, depressive symptoms, comorbidity, dyspnea, and pain might be considered as a phenotype to identify persons with HF who are at increased risk for insomnia symptoms.

Cardiovascular health in emerging adults with type 1 diabetes

McCarthy, M., Yan, J., Jared, M. C., You, E., Ilkowitz, J., Gallagher, M. P., & Vaughan Dickson, V. (2022). European Journal of Cardiovascular Nursing, 21(3), 213-219. 10.1093/eurjcn/zvab062
Aims: Individuals with type 1 diabetes (T1D) face increased risk for cardiovascular disease (CVD). Controlling individual cardiovascular risk factors can prevent or slow the onset of CVD. Ideal cardiovascular health is associated with a lower incidence of CVD. Identifying areas of suboptimal cardiovascular health can help guide CVD prevention interventions. To assess cardiovascular health and explore the barriers and facilitators to achieving ideal cardiovascular health in a sample of young adults with T1D. Methods and results: We used a sequential mixed-method design to assess the seven factors of cardiovascular health according to American Heart Association. Qualitative interviews, guided by Pender's Health Promotion Model, were used to discuss participant's cardiovascular health results and the barriers and facilitators to achieving ideal cardiovascular health. We assessed the frequency of ideal levels of each factor. The qualitative data were analysed using content analysis. Qualitative and quantitative data were integrated in the final analysis phase. The sample (n = 50) was majority female (70%), White (86%), with a mean age of 22 ± 2.4 and diabetes duration of 10.7 ± 5.5 years. Achievement of the seven factors of cardiovascular health were: non-smoking (96%); cholesterol <200 mg/dL (76%); body mass index <25 kg/m2 (54%); blood pressure <120/<80 mmHg (46%); meeting physical activity guidelines (38%); haemoglobin A1c <7% (40%); and healthy diet (14%). Emerging qualitative themes related to the perceived benefits of action, interpersonal influences on their diabetes self-management, and perceived self-efficacy. Conclusion: We found areas of needed improvement for cardiovascular health. However, these young adults expressed a strong interest in healthy habits which can be supported by their healthcare providers.

Associations of Insomnia Symptoms With Cognition in Persons With Heart Failure

Gharzeddine, R., Yu, G., McCarthy, M. M., & Dickson, V. V. (2021). Western Journal of Nursing Research, 43(12), 1105-1117. 10.1177/0193945920988840
Although cognitive impairment is common among persons with heart failure and negatively impacts self-care, hospitalization, and mortality, the associations between cognitive impairment and insomnia symptoms are not clearly understood. The purpose of this study was to explore these associations and examine if they are maintained after adjusting for relevant sociodemographic, clinical, and lifestyle factors. Guided by the Neurocognitive model of insomnia and sleep and the self-care conceptual model, a cross-sectional data analysis using parametric testing was conducted on the Health and Retirement Study wave 2016. Difficulty initiating sleep and early morning awakening, but not difficulty maintaining sleep were significantly associated with poorer cognitive performance in the bivariate and multivariate analysis. Our results are suggestive of different phenotypes of insomnia symptoms that may have different associations with cognition in persons with heart failure. Further research using objective measurements of insomnia symptoms and detailed neuropsychiatric testing of cognition is needed to confirm this conclusion.

Factors associated with work ability in adults with diabetes

McCarthy, M., Yan, J., & Dickson, V. V. (2021). Applied Nursing Research, 61. 10.1016/j.apnr.2021.151478
Aims: The aims of this study were to explore associations between clinical and diabetes-related factors with work ability in a sample of working adults with diabetes. Background: Adults with diabetes may face challenges in the workplace, including managing their diabetes and overall physical and mental health. Methods: This was a cross-sectional design with a sample of 101 working adults. Subjects completed valid and reliable surveys assessing depressive symptoms, diabetes self-care, fear of hypoglycemia, diabetes distress, cardiovascular health using American Heart Association's Life's Simple 7 (range 0–7) and work ability. Factors significantly associated with work ability at bivariate level were included in linear and logistic regression. Results: The majority of the sample was female (65%) (mean age 54.1 ± 10.5), White (74%), non-Hispanic (93%), worked full-time (65%) and had type 2 diabetes (87%) (mean duration 12.4 ± 9.5 years). The majority (55%) had low diabetes distress, but 24% had high distress and 28% had depressive symptoms. The sample achieved 2.5 ± 1.4 ideal AHA heart health indices and 33% rated their work ability as excellent. In linear regression higher depressive scores were associated with lower work ability scores (b = −0.45, p = .002). In logistic regression, scores on heart health (OR = 1.4; 95%CI:1.0–1.9, p = .03) and diabetes distress (OR = 0.6, 95%CI:0.4–0.9, p = .048) were significantly associated with work ability at its best. Conclusion: Both cardiovascular and psychological health may impact work ability in adults with diabetes. Routinely screening for diabetes distress and depression while also promoting ideal cardiovascular health may improve overall health and work ability in this population.

Implementing the physical activity vital sign in an academic preventive cardiology clinic

McCarthy, M. M., Fletcher, J., Heffron, S., Szerencsy, A., Mann, D., & Vorderstrasse, A. (2021). Preventive Medicine Reports, 23. 10.1016/j.pmedr.2021.101435
The aims were to implement physical activity (PA) screening as part of the electronic kiosk check-in process in an adult preventive cardiology clinic and assess factors related to patients’ self-reported PA. The 3-question physical activity vital sign (PAVS) was embedded in the Epic electronic medical record and included how many days, minutes and intensity (light, moderate, vigorous) of PA patients conducted on average. This is a data analysis of PAVS data over a 60-day period. We conducted multivariable logistic regression to identify factors associated with not meeting current PA recommendations. Over 60 days, a total of 1322 patients checked into the clinic using the kiosk and 72% (n = 951) completed the PAVS at the kiosk. The majority of those patients were male (58%) and White (71%) with a mean age of 64 ± 15 years. Of the 951 patients completing the PAVS, 10% reported no PA, 55% reported some PA, and 35% reported achieving at least 150 min moderate or 75 min vigorous PA/week. In the logistic model, females (AOR = 1.4, 95%CI: 1.002–1.8, p =.049) vs. males, being Black (AOR = 2.0, 95%CI: 1.04–3.7, p =.038) or ‘Other’ race (AOR = 1.5, 95%CI: 1.02–2.3, p =.035) vs. White, unknown or other types of relationships (AOR = 0.0.26, 95%CI: 0.10–0.68, p =.006) vs. being married/partnered, and those who were retired (AOR = 1.9, 95% CI: 1.4–2.8, p <.001) or unemployed (AOR = 2.2, 95%CI: 1.3–3.7, p =.002) vs. full-time workers were associated with not achieving recommended levels of PA. The PAVS is a feasible electronic tool for quickly assessing PA and may prompt providers to counsel on this CVD risk factor.