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부인암 환자의 증상 클러스터, 활동정도, 정서상태가삶의 질에 미치는 영향

Impacts of Symptom Clusters, Performance and Emotional Status on the Quality of Life of Patients with Gynecologic Cancer

이소연|정향미|배은정
한국모자보건학회 (The Korean Society Of Maternal And Child Health)|2019.01|한국모자보건학회지 (JOURNAL OF KOREAN MATERNAL AND CHILD HEALTH)|제23권 제1호|pp. 45-55|DOI 10.21896/jksmch.2019.23.1.45

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키워드

emotionsymptomquality of life
주제분류예방의학/직업환경의학

초록

Purpose: To determine impacts of symptom clusters, performance and emotional status on the quality of life of gynecologic cancer patients. Methods: Subjects completed questionnaires consisting of four measurements: symptom cluster, performance and emotional status, and the quality of life. A total of 104 completed data sets were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and a multiple regression analysis using the SPSS 21.0 program. Results: Fatigue was identified as the most prevalent symptom (77.9%) and sweating (2.08) as the most severe and uncomfortable symptom (1.80). Six symptom clusters, performance status, anxiety and depression were negatively correlated with quality of life. Four symptom clusters were positively correlated with performance status, and six symptom clusters were positively correlated with anxiety and depression. Factors affecting quality of life were abdominal discomfort cluster (β=-0.23, p=0.005), performance status (β=-0.20, p=0.020), and depression (β=-0.42, p<0.001). The model was statistically significant explaining 42.5% of variance (F=26.369, p<0.001). Conclusion: The findings supported that symptom clusters and depression negatively influence the quality of life and need to be addressed as we are caring for patients and promoting quality of life.

Abstract

Purpose: To determine impacts of symptom clusters, performance and emotional status on the quality of life of gynecologic cancer patients. Methods: Subjects completed questionnaires consisting of four measurements: symptom cluster, performance and emotional status, and the quality of life. A total of 104 completed data sets were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and a multiple regression analysis using the SPSS 21.0 program. Results: Fatigue was identified as the most prevalent symptom (77.9%) and sweating (2.08) as the most severe and uncomfortable symptom (1.80). Six symptom clusters, performance status, anxiety and depression were negatively correlated with quality of life. Four symptom clusters were positively correlated with performance status, and six symptom clusters were positively correlated with anxiety and depression. Factors affecting quality of life were abdominal discomfort cluster (β=-0.23, p=0.005), performance status (β=-0.20, p=0.020), and depression (β=-0.42, p<0.001). The model was statistically significant explaining 42.5% of variance (F=26.369, p<0.001). Conclusion: The findings supported that symptom clusters and depression negatively influence the quality of life and need to be addressed as we are caring for patients and promoting quality of life.

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