Ying Liu1,2, Yupin Aungsuroch2. 1. School of Nursing, Dalian Medical University, Dalian, China. 2. Faculty of Nursing, Chulalongkorn University, Bangkok, Thailand.
Abstract
AIM: To propose a hypothesized theoretical model and apply it to examine the structural relationships among work environment, patient-to-nurse ratio, job satisfaction, burnout, intention to leave and quality nursing care. BACKGROUND: Improving quality nursing care is a first consideration in nursing management globally. A better understanding of factors influencing quality nursing care can help hospital administrators implement effective programmes to improve quality of services. Although certain bivariate correlations have been found between selected factors and quality nursing care in different study models, no studies have examined the relationships among work environment, patient-to-nurse ratio, job satisfaction, burnout, intention to leave and quality nursing care in a more comprehensive theoretical model. DESIGN: A cross-sectional survey. METHODS: The questionnaires were collected from 510 Chinese nurses in four Chinese tertiary hospitals in January 2015. The validity and internal consistency reliability of research instruments were evaluated. Structural equation modelling was used to test a theoretical model. RESULTS: The findings revealed that the data supported the theoretical model. Work environment had a large total effect size on quality nursing care. Burnout largely and directly influenced quality nursing care, which was followed by work environment and patient-to-nurse ratio. Job satisfaction indirectly affected quality nursing care through burnout. CONCLUSIONS: This study shows how work environment past burnout and job satisfaction influences quality nursing care. Apart from nurses' work conditions of work environment and patient-to-nurse ratio, hospital administrators should pay more attention to nurse outcomes of job satisfaction and burnout when designing intervention programmes to improve quality nursing care.
AIM: To propose a hypothesized theoretical model and apply it to examine the structural relationships among work environment, patient-to-nurse ratio, job satisfaction, burnout, intention to leave and quality nursing care. BACKGROUND: Improving quality nursing care is a first consideration in nursing management globally. A better understanding of factors influencing quality nursing care can help hospital administrators implement effective programmes to improve quality of services. Although certain bivariate correlations have been found between selected factors and quality nursing care in different study models, no studies have examined the relationships among work environment, patient-to-nurse ratio, job satisfaction, burnout, intention to leave and quality nursing care in a more comprehensive theoretical model. DESIGN: A cross-sectional survey. METHODS: The questionnaires were collected from 510 Chinese nurses in four Chinese tertiary hospitals in January 2015. The validity and internal consistency reliability of research instruments were evaluated. Structural equation modelling was used to test a theoretical model. RESULTS: The findings revealed that the data supported the theoretical model. Work environment had a large total effect size on quality nursing care. Burnout largely and directly influenced quality nursing care, which was followed by work environment and patient-to-nurse ratio. Job satisfaction indirectly affected quality nursing care through burnout. CONCLUSIONS: This study shows how work environment past burnout and job satisfaction influences quality nursing care. Apart from nurses' work conditions of work environment and patient-to-nurse ratio, hospital administrators should pay more attention to nurse outcomes of job satisfaction and burnout when designing intervention programmes to improve quality nursing care.
Authors: Daniel S Tawfik; Annette Scheid; Jochen Profit; Tait Shanafelt; Mickey Trockel; Kathryn C Adair; J Bryan Sexton; John P A Ioannidis Journal: Ann Intern Med Date: 2019-10-08 Impact factor: 25.391
Authors: Douglas Aninng Opoku; Nana Kwame Ayisi-Boateng; Joseph Osarfo; Alhassan Sulemana; Aliyu Mohammed; Kathryn Spangenberg; Ali Baba Awini; Anthony Kwaku Edusei Journal: Nurs Res Pract Date: 2022-07-12
Authors: Yi-Chuan Chen; Yue-Liang Leon Guo; Li-Chan Lin; Yu-Ju Lee; Pei-Yi Hu; Jiune-Jye Ho; Judith Shu-Chu Shiao Journal: Int J Environ Res Public Health Date: 2020-01-19 Impact factor: 3.390