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Development of the ECU Behavioral and Lifestyle Risk Factor Assessment in Cardiology

dc.access.optionRestricted Campus Access Only
dc.contributor.advisorSears, Samuel F
dc.contributor.authorAnthony, Scarlett
dc.contributor.departmentPsychology
dc.date.accessioned2022-02-11T17:31:04Z
dc.date.available2024-02-09T09:01:59Z
dc.date.created2021-12
dc.date.issued2021-12-08
dc.date.submittedDecember 2021
dc.date.updated2022-02-08T15:32:36Z
dc.degree.departmentPsychology
dc.degree.disciplineMA-Clinical Psychology
dc.degree.grantorEast Carolina University
dc.degree.levelMasters
dc.degree.nameM.A.
dc.description.abstractBackground: Atrial fibrillation (AF) occurs when rapid and disorganized electrical signals cause the atria in the heart to irregularly beat, not allowing blood to effectively flow from the atria to the ventricles. Over time, AF can decrease the heart's pumping ability which can lead to heart failure, blood clots, or a stroke. AF etiology, recurrence, and burden are influenced by both modifiable and non-modifiable risk factors spanning biological, behavioral, and demographic factors. Therefore, there is increased interest in understanding and measuring behavioral risk factors (e.g. ETOH, sedentariness, smoking) associated with AF, in order to reduce stroke risk. Method: This study aimed to develop a risk factor score to predict AF associated outcomes and burden. At the East Carolina Heart Institute (ECHI) and University of Arkansas for Medical Sciences (UAMS), patients were recruited by their physician to complete the ECU Behavioral and Lifestyle Assessment for Atrial Fibrillation and the Cardiac Anxiety Questionnaire. Results: A total of 110 patients were enrolled in the study. Descriptive analyses indicated that the mean (SD) age of patients was 69 (10.18) years, 38.2% of the sample was female (n = 42), and most patients identified as White (71.8%) or African American/Black (26.4%). The major findings of this study included a) total risk factor scores found that no patients achieved a score of zero, b) cardiac anxiety scores and risk factor scores were positively correlated, c) health care utilization was predicted by smoking and breathlessness, multiple risk factors predicted cardiac anxiety scores, and CVD related ED visits, clinic visits, and CVD related hospitalizations were predicted by the risk factor total scores. Conclusion: The creation and implementation of a risk factor score helps aid in AF treatment plans to improve health outcomes. Results from this study indicate that AF patients are experiencing high rates of cardiac anxiety, and some components of health care utilization were able to be predicted by patient and provider risk factor scores highlighting its benefit.
dc.embargo.lift2023-12-01
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10342/9765
dc.language.isoen
dc.publisherEast Carolina University
dc.subjectcardiac risk factors
dc.subjectcardiac electrophysiology
dc.subject.lcshAtrial fibrillation
dc.subject.lcshHeart--Diseases--Case studies
dc.subject.lcshHeart--Diseases--Patients--Mental health
dc.subject.lcshAnxiety--Testing
dc.subject.lcshEast Carolina University
dc.titleDevelopment of the ECU Behavioral and Lifestyle Risk Factor Assessment in Cardiology
dc.typeMaster's Thesis
dc.type.materialtext

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