Symptom Clusters, Psychological Distress, and Quality of Life in Patients with Atrial Fibrillation

Author:

Bang Chohee1,Park Sookyung2

Affiliation:

1. Department of Nursing, College of Health Science, Honam University, Gwangju 62399, Republic of Korea

2. School of Nursing, Korea University, Seoul 02841, Republic of Korea

Abstract

Background: Patients with atrial fibrillation (AF) experience diverse symptoms such as palpitations, dizziness, and fainting that lead to depression, anxiety, and poor quality of life. Management of symptoms is fundamental for AF, and with the increasing prevalence of AF, studies on management of symptoms in patients with AF are needed. Objectives: This study aimed to assess symptom clusters according to symptom severity in patients with atrial fibrillation and evaluate the relationships between symptom cluster groups and the psychological distress and quality of life of these patients. Design: A descriptive survey was used in this study. Methods: A total of 175 patients were included in this study. Data regarding symptoms, psychological distress, and quality of life were obtained using structured questionnaires and analyzed using frequency and percentage, mean and standard deviation, cluster analysis, t-testing, Chi-square testing, Pearson’s correlation coefficient, and multiple regression analysis. The Euclidean distance square of the hierarchical cluster was used to form symptom cluster groups. Results: Two groups of symptom clusters were formed based on the seven most common symptoms (i.e., chest palpitations, fatigue/tiredness, dizziness, lack of energy, pulse skipping, insomnia, and heavy breathing) of atrial fibrillation patients. Psychological distress and quality of life showed significant correlations with the symptom cluster groups (p < 0.001). Conclusion: Symptoms of atrial fibrillation increased patients’ depression and anxiety, and further affected their quality of life. Therefore, management of symptoms is critical to maintaining a high quality of life. Nursing interventions based on the characteristics of symptom cluster groups must be developed and attempted.

Publisher

MDPI AG

Subject

Health Information Management,Health Informatics,Health Policy,Leadership and Management

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