Yu-Ling Bai1, Liu-Yuan Lai2, Bih-O Lee3, Yong-Yuan Chang4, Chou-Ping Chiou5. 1. Department of Nursing, Chung Hwa University of Medical Technology, Tainan, Taiwan. 2. Department of Nursing, Fooyin University Hospital, Pingtung, Taiwan. 3. Department of Nursing, Chang Gung University of Science and Technology, Chia-Yi, Taiwan. 4. Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan. 5. School of Nursing, I-Shou University, Kaohsiung, Taiwan.
Abstract
AIMS AND OBJECTIVES: To investigate the fatigue levels and important fatigue predictors for patients undergoing haemodialysis. BACKGROUND: Fatigue is a common symptom for haemodialysis patients. With its debilitating and distressing effects, it impacts patients in terms of their quality of life while also increasing their mortality rate. DESIGN: A descriptive correlational study. METHODS: Convenience sampling was conducted at six chosen haemodialysis centres in Southern Taiwan. Data were collected via a structured questionnaire from 193 haemodialysis patients. The scales involved in this study were socio-demographic details, the Center for Epidemiologic Studies Depression Scale, and the Fatigue Scale for haemodialysis patients. Data analysis included percentages, means, standard deviations and hierarchical multiple regression analysis. RESULTS: The fatigue level for haemodialysis patients was in the moderate range. Results from the hierarchical multiple regression analysis indicated that age, employment status, types of medications, physical activity and depression were significant. Of those variables, depression had the greatest impact on the patients' fatigue level, accounting for up to 30·6% of the explanatory power. The total explanatory power of the regression model was 64·2%. CONCLUSION: This study determined that for haemodialysis patients, unemployment, increased age, taking more medications or lower exercise frequencies resulted in more severe depression, which translated in turn to higher levels of fatigue. Among all these factors, depression had the greatest impact on the patients' fatigue levels. RELEVANCE TO CLINICAL PRACTICE: Not only is this finding beneficial to future studies on fatigue as a source of reference, it is also helpful in our understanding of important predictors relating to fatigue in the everyday lives of haemodialysis patients. It is recommended that when caring for fatigued patients, more care should be dedicated to their psychological states, and assistance should be provided in a timely way so as to reduce the amount of fatigue suffered.
AIMS AND OBJECTIVES: To investigate the fatigue levels and important fatigue predictors for patients undergoing haemodialysis. BACKGROUND:Fatigue is a common symptom for haemodialysis patients. With its debilitating and distressing effects, it impacts patients in terms of their quality of life while also increasing their mortality rate. DESIGN: A descriptive correlational study. METHODS: Convenience sampling was conducted at six chosen haemodialysis centres in Southern Taiwan. Data were collected via a structured questionnaire from 193 haemodialysis patients. The scales involved in this study were socio-demographic details, the Center for Epidemiologic Studies Depression Scale, and the Fatigue Scale for haemodialysis patients. Data analysis included percentages, means, standard deviations and hierarchical multiple regression analysis. RESULTS: The fatigue level for haemodialysis patients was in the moderate range. Results from the hierarchical multiple regression analysis indicated that age, employment status, types of medications, physical activity and depression were significant. Of those variables, depression had the greatest impact on the patients' fatigue level, accounting for up to 30·6% of the explanatory power. The total explanatory power of the regression model was 64·2%. CONCLUSION: This study determined that for haemodialysis patients, unemployment, increased age, taking more medications or lower exercise frequencies resulted in more severe depression, which translated in turn to higher levels of fatigue. Among all these factors, depression had the greatest impact on the patients' fatigue levels. RELEVANCE TO CLINICAL PRACTICE: Not only is this finding beneficial to future studies on fatigue as a source of reference, it is also helpful in our understanding of important predictors relating to fatigue in the everyday lives of haemodialysis patients. It is recommended that when caring for fatiguedpatients, more care should be dedicated to their psychological states, and assistance should be provided in a timely way so as to reduce the amount of fatigue suffered.
Authors: Christine Horvat Davey; Allison R Webel; Ashwini R Sehgal; Joachim G Voss; Anne Huml Journal: Nephrol Nurs J Date: 2019 Sep-Oct Impact factor: 0.959