Burnout Study of Clinical Nurses in Vietnam: Development of Job Burnout Model Based on Leiter and Maslach's Theory
Asian Nursing Research
;
: 42-49, 2018.
Article
in English
| WPRIM
| ID: wpr-713603
ABSTRACT
PURPOSE:
This study aimed to create a Vietnamese version of both the Maslach Burnout Inventory-General Survey (MBI-GS) and Areas of Worklife Scale (AWS) to assess the burnout state of Vietnamese clinical nurses and to develop a causal model of burnout of clinical nurses.METHODS:
We conducted a descriptive design using a cross-sectional survey. The questionnaire was hand divided directly by nursing departments to 500 clinical nurses in three hospitals. Vietnamese MBI-GS and AWS were then examined for reliability and validity. We used the revised exhaustion +1 burnout classification to access burnout state.We performed path analysis to develop a Vietnamese causal model based on the original model by Leiter and Maslach's theory.RESULTS:
We found that both scales were reliable and valid for assessing burnout. Among nurse participants, the percentage of severe burnout was 0.7% and burnout was 15.8%, and 17.2% of nurses were exhausted. The best predictor of burnout was “on-duty work schedule” that clinical nurses have to work for 24 hours. In the causal model, we also found similarity and difference pathways in comparison with the original model.CONCLUSION:
Vietnamese MBI-GS and AWS were applicable to research on occupational stress. Nearly one-fifth of Vietnamese clinical nurses were working in burnout state. The causal model suggested a range of factors resulting in burnout, and it is necessary to consider the specific solution to prevent burnout problem.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Vietnam
/
Weights and Measures
/
Cross-Sectional Studies
/
Reproducibility of Results
/
Nursing
/
Classification
/
Asian People
/
Hand
Type of study:
Observational study
/
Prevalence study
/
Prognostic study
/
Risk factors
Limits:
Humans
Country/Region as subject:
Asia
Language:
English
Journal:
Asian Nursing Research
Year:
2018
Type:
Article
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