암 환자의 수면의 질과 극복력이 삶의 질에 미치는 영향
The Impact of Quality of Sleep and Resilience on the Quality of the Life of Patients with Cancer
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Purpose: The aim of this study was to investigate the impact of quality of sleep and resilience on the quality of life of patientswith cancer. Methods: Data were collected from September to November, 2023, through questionnaires distributed to158 patients with cancer. Data were analyzed using descriptive statistics, t-test, one-way ANOVA, pearson’s correlationcoefficient, and stepwise multiple regression analysis using SPSS/WINdows version 27.0. Results: Quality of life wassignificantly correlated with resilience (r=.52, p<.001) and quality of sleep (r=-.38, p<.001). The stepwise multipleregression analysis, used to determine the variables affecting patients’ quality of life, resulted in a significant regressionmodel (F=44.95, p<.001), that accounted for approximately 45.6% of the explanatory power. Resilience (β=.48, p<.001),quality of sleep (β=-.34, p<.001) and recurrence (β=.25, p<.001) were revealed to affect quality of life. Conclusion: Theresults of this study confirmed that cancer patients' quality of sleep, resilience, and recurrence in patients with canceraffected quality of life. Based on the results of this study, tspecific nursing intervention strategies can be developed andapplied to improve the quality of life of patients with cancer.
Abstract
Purpose: The aim of this study was to investigate the impact of quality of sleep and resilience on the quality of life of patientswith cancer. Methods: Data were collected from September to November, 2023, through questionnaires distributed to158 patients with cancer. Data were analyzed using descriptive statistics, t-test, one-way ANOVA, pearson’s correlationcoefficient, and stepwise multiple regression analysis using SPSS/WINdows version 27.0. Results: Quality of life wassignificantly correlated with resilience (r=.52, p<.001) and quality of sleep (r=-.38, p<.001). The stepwise multipleregression analysis, used to determine the variables affecting patients’ quality of life, resulted in a significant regressionmodel (F=44.95, p<.001), that accounted for approximately 45.6% of the explanatory power. Resilience (β=.48, p<.001),quality of sleep (β=-.34, p<.001) and recurrence (β=.25, p<.001) were revealed to affect quality of life. Conclusion: Theresults of this study confirmed that cancer patients' quality of sleep, resilience, and recurrence in patients with canceraffected quality of life. Based on the results of this study, tspecific nursing intervention strategies can be developed andapplied to improve the quality of life of patients with cancer.