Volume 24, Number 4 (1-2015)                   J Holist Nurs Midwifery 2015, 24(4): 9-19 | Back to browse issues page


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Baghaie Lake M, Rahimi S, Adib M, Kazem Nejad Leili E, Monfared A. redictive Personal factors of quality of life in hemodialysis patient. J Holist Nurs Midwifery. 2015; 24 (4) :9-19
URL: http://hnmj.gums.ac.ir/article-1-361-en.html

, Sara.rahimi45@yahoo.com
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Predictive Personal factors of quality of life in hemodialysis patients
 

By: Baghaei M 1, Rahimi S 2*, Adib M3, Kazemnejad Leili E 4, Monfared A3

1) Department of Nursing(medical-surgical), Instructor, Social Determinants of Health Research Center, School of Nursing and Midwifery, Guilan University of Medical Sciences, Rasht, Iran

2) Department of Emergency Medicine, Instructor, School of Paramedical, Gazvin University of Medical Sciences, Qazvin, Iran

3) Department of Nursing (medical-surgical), Instructor, School of Nursing and Midwifery, Guilan University of Medical Sciences, Rasht, Iran

4) Bio-Statistics, Assistant professor, Social Determinants of Health Research Center, School of Nursing and Midwifery, Guilan University of Medical Sciences, Rasht, Iran

Received: 2013/01/02

Accepted: 2013/07/31

Abstract

Introduction: Assessing quality of life and its related factors in hemodialysis patients is necessary to promote their quality of life.

Objective: This study aimed to determine predictive personal factors of quality of life among hemodialysis patients referring to hemodialysis centers affiliated to Guilan University of Medical Sciences.

Methods: This analytic cross-sectional study was conducted on 241 hemodialysis patients referring to 12 Guilan dialysis centers chosen by randomized-stratified method from adult patients with inclusion criteria. Data was gathered by a researcher-made questionnaire on personal factors and Kidney Disease Quality of Life Short Form with 3 domains of physical, mental and specified kidney disease. The relationship between personal factors and three domains of  uality of life were analyzed using descriptive (distributions, mean and SD) and analytic statistics (Smirnov Kolmogorov for normal distribution of data, t-student, ANOVA and Linear regression).

Results: The least mean and SD was in job status subscale (19.1±2.9) and physical domain of quality of life (46.99±1.94) in comparison to two other domains.

Patients’ quality of life score was 54.00±13.33. There was a significant relationship between lower quality of life scores and female gender (p=0.0001), older age (p=0.002), lower education (p=0.0001), unemployment (P=0.0001), without family responsibility (p=0.003), suburban residential place (p=0.043), and without history of kidney transplantation (p=0.038).

Conclusion: Female gender and unemployment were predictors of poor quality of life. Associations of poor health related quality of life with controllable factors such as job, highlights necessitation of greater focus on social support and medical and nursing interventions in these patients.

Keywords: Kidney Diseases, Renal Dialysis, Quality of Life

*Corresponding Author: Sara Rahimi, Gazvin, School of Paramedical

  Email: Sara.rahimi45@yahoo.com                                          

Type of Study: Research | Subject: Special
Received: 2014/12/9 | Accepted: 2014/12/9 | Published: 2014/12/9

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