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Burnout Study of Clinical Nurses in Vietnam: Development of Job Burnout Model Based on Leiter and Maslach's Theory

Open AccessPublished:February 07, 2018DOI:https://doi.org/10.1016/j.anr.2018.01.003

      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.

      Keywords

      Introduction

      Stress is an important phenomenon that is related to an individual's physiological and psychological behavior [
      • Schuler R.S.
      Definition and conceptualization of stress in organizations.
      ]. In Vietnam, stress is rising as a common problem which has been studied in variety of fields, such as psychology, physiology, and medical aspect. But the research on job stress was still limited [
      • Nguyen H.T.
      • Ta B.T.
      Job stress in medical staff.
      ]. Different individuals of job stress, such as general workers or medical staff, were examined. Typically, Pham investigated work-related depression at a shoe-manufacturing factory [
      • Pham K.M.
      Work-related depression and associated factor in a shoe manufacturing factory in Hai Phong city, Viet Nam.
      ]. According to Nguyen and Ta's survey in 2005 implemented at three central hospitals, doctors had the highest stress levels compared with nurses and other health workers [
      • Nguyen H.T.
      • Ta B.T.
      Job stress in medical staff.
      ]. In their research on nurses, Le, Tran, and Tran [
      • Le T.T.
      • Tran L.T.
      • Tran X.N.
      Job stress researching on nurses.
      ] found that nearly half of nurses had high stress. High level of job stress may result in burnout. The job burnout among clinical nurses in Vietnam has been concerned, but no study has been found at all.
      The Vietnamese researchers used several different measurement scales to assess stress level. Le et al [
      • Le T.T.
      • Tran L.T.
      • Tran X.N.
      Job stress researching on nurses.
      ] applied the questionnaire by Fontana [
      • Fontana D.
      Professional life stress scale – managing stress.
      ] to stress evaluation although they did not examine the validity and reliability of this scale. The instrument that has been validated to measure job stress in Vietnam is the Job Content Questionnaire (JCQ) by Karasek [
      • Karasek R.
      • Brisson C.
      • Kawakami N.
      • Houtman I.
      • Bongers P.
      • Amick B.
      The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessment of psychosocial job characteristics.
      ]. In fact, a group researcher produced a valid Vietnamese version of the JCQ [
      • Hoang G.T.
      • Corbiere M.
      • Negrini A.
      • Pham K.M.
      • Reinharz D.
      Validation of the Karasek-job content questionnaire to measure job strain in Viet Nam.
      ], which was used in the research by Pham [
      • Pham K.M.
      Work-related depression and associated factor in a shoe manufacturing factory in Hai Phong city, Viet Nam.
      ] to evaluate job stress in shoe factory workers.
      Worldwide, many job stressor instruments have been available, such as The National Institute for Occupational Safety and Health (NIOSH) [
      • Hurrell J.J.
      • Mc Laney M.A.
      Exposure to job stress – a new psychometric instrument.
      ], JCQ [
      • Karasek R.
      • Brisson C.
      • Kawakami N.
      • Houtman I.
      • Bongers P.
      • Amick B.
      The Job Content Questionnaire (JCQ): an instrument for internationally comparative assessment of psychosocial job characteristics.
      ], and Areas of Worklife Survey (AWS) [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife survey manual.
      ]. According to the NIOSH, job stress can be defined as the harmful physical and emotional responses that occur when the requirements of the job do not match the capabilities, resources, or needs of the worker. Job stress can lead to poor health and even injury. The NIOSH has created the NIOSH general job stress questionnaire including both job stress and job stressor measurement. The JCQ preferred to mention on three sub-domains of psychological demands, decision latitude, and social support at work. Leiter and Maslach [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife: a structured approach to organization predictor of job burnout.
      ] identified six key domains that lead to burnout; then, the AWS has been generated and suggested as a reasonable scale to estimate burnout at work. AWS's validity and reliability have been shown in USA, Canada, Finland, and Italy [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife: a structured approach to organization predictor of job burnout.
      ]. However, only the JCQ has been translated and validated in Vietnam, impeding further progress in research. Because there is a need for more scales to be translated and validated for research purposes in Vietnam, in this study, a Vietnamese version of the AWS will be generated.
      To deal with job stress, a number of job stress measures are recommended. The General Health Questionnaire [
      • Goldberg D.P.
      Manual of the general health questionnaire.
      ] is used to detect psychological issues such as depression or anxiety. It assesses the respondent's current state and asks if that differs from his or her usual state. It is therefore sensitive to short-term psychiatric disorders but not long-standing attributes of the respondent. Further, the Maslach Burnout Inventory (MBI) [
      • Maslach C.
      • Jackson S.E.
      • Leiter M.P.
      Maslach burnout inventory manual.
      ] has been used in many studies to assess burnout level. The MBI has been adapted to many kinds of people with different scales of MBI-Human Services Survey for human service professions, MBI-Educator Survey for educator, and MBI-General Survey (MBI-GS) for general workers [
      • Kitaoka K.
      • Nakagawa H.
      • Morikawa Y.
      • Ishizaki M.
      • Miura K.
      • Naruse Y.
      • et al.
      Construct validity of the Maslach burnout inventory–general survey.
      ]. The MBI has not been introduced to researchers on occupational stress in Vietnam. This study will be the first to translate and examine the MBI-GS for validation in Vietnam. It is essential to assess job stressor and stress with globally used scales for further development of occupational health in Vietnam.
      Our objectives are as follows. First, we create a Vietnamese version of MBI-GS and AWS. Then, we assess the burnout state of Vietnamese clinical nurses using the translated MBI-GS. Finally, we develop a causal model of burnout among clinical nurses in Vietnam using two scales. We apply Leiter and Maslach's theory [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife: a structured approach to organization predictor of job burnout.
      ] to our frame work.
      Leiter and Maslach developed the causal model of burnout. They collected data from a normative sample in USA, Canada, Finland, and Italy which included health-care professionals such as nurses, using the MBI-GS and AWS. Furthermore, they tested the model applying to Canadian nurses. Therefore, Leiter and Maslach's model might be working in describing nurses' burnout in Vietnam.

      Methods

      Study design

      A cross-sectional study was used to carry out the survey.

      Setting and sample

      Participants were clinical nurses working in different departments at three public hospitals in Hai Phong, Vietnam: one general hospital and two specialty hospitals (a children's hospital and an obstetric hospital).

      Ethical considerations

      Nurse participants in this survey were volunteers and were anonymous. Participants fully understood the research and agreed to respond to the questionnaire. Instruments using in this study has been approved according to Permissions Letter issued by Mind Garden. This study was approved by the Kanazawa University Medical Ethics Committee, Japan (Approval no. 649-1) dated on January 6, 2016. This research conforms to the provisions of the Declaration of Helsinki in 1995 (as revised in Edinburgh 2000). We obtained the consent of the managing board of the three hospitals and departments before implementing the survey.

      Measurements

      Three sets of questionnaires were administered to the participants: (1) a demographic questionnaire, (2) a MBI-GS questionnaire [
      • Maslach C.
      • Jackson S.E.
      • Leiter M.P.
      Maslach burnout inventory manual.
      ], and (3) an AWS questionnaire [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife survey manual.
      ]. The demographic questionnaire related to sex, age, marital status, children, age of children, years of nursing work, workplace, nursing position, on-duty work schedule, and education level.
      The MBI-GS consists of three scales totaling 16 items: exhaustion with five items, cynicism with five items, and professional efficacy with six items. Each item is scored using a 7-point Likert scale (never, a few times a year, once a month, a few times a month, once a week, a few times a week, and daily) ranging from 0 to 6. We obtained permission from Mind Garden to use and translate the MBI-GS into the Vietnamese language. The translation process entailed two phases: (1) forward translation, involving translation of the MBI-GS from English to Vietnamese by a bilingual researcher; and (2) back-translation, involving two independent bilingual translators, both of whom majored in English teaching and translation. Afterward, two researchers carefully compared the back-translated version with the original English version item-by-item to evaluate conceptual equivalence.
      The 28-item AWS questionnaire consists of six key domains: workload (5 items), control (4), rewards (4), community (5), fairness (6), and value (4). Each scale contains both a positive word item [e.g., “I have enough time to do what's important in my job” (workload)] and a negative word item [e.g., “I do not get recognized for my contributions at work” (rewards)]. Participants indicated their degree of agreement with these statements using a 5-point Likert scale ranging from 1 (strongly disagree) to 3 (hard to decide) to 5 (strongly agree). Scoring for the negative word item is reversed. The translation process of the AWS questionnaire was identical to that of the MBI-GS questionnaire. Vietnamese version of AWS also obtained permission from Mind Garden to use and translate.

      Data collection

      We calculated the intended sample size using a formula for sample size estimation in a cross-sectional study, with an alpha value of .05 and an estimated p value of .50. Calculated sample size was 385 nurses, which was a safe sample size for this study. To avoid nonresponse, 500 administered questionnaires were delivered to clinical nurses at three hospitals using random sampling. In Vietnam, a general hospital, a children's hospital, and an obstetrics hospital are run by the local government for citizens, and those three hospitals are located in each province.
      Based on the number of nurses at each hospital, 260 questionnaires were sent to the general hospital, 90 to the children's hospital, and 150 to the obstetrics hospital. Overall, 443 questionnaires were returned (general hospital, n = 234; children's hospital, n = 80; obstetrics hospital, n = 129) with a response rate of 88.6% (general hospital, 90.0%; children's hospital, 88.8%; obstetrics hospital, 86.0%). However, among 443 responses, there were 13 invalid responses with the same answer given for the entire scale or where there were missing data for some questions. Therefore, we obtained a final sample size of 430 nurses (general hospital, n = 230; children's hospital, n = 78; obstetrics hospital, n = 122) for statistical analysis.
      The nurses received a clear explanation of the study before filling out the questionnaires. Researchers gave the questionnaires to nurses during their morning daily meeting and made an appointment to retrieve them. Data collection was implemented from January 2016 to March 2016.

      Data analysis

      To verify the factorial validity of the translated MBI-GS and AWS, we used explanatory factor analysis (maximum likelihood and promax rotation). We then assessed the reliability of the MBI-GS and AWS subscales by Cronbach α to indicate internal consistency. Then, we conducted a one-way analysis of variance to analyze the differences in burnout scores among variable groups, using multiple regression analysis to predict burnout-related factors and applying the revised exhaustion+1 burnout classification [
      • Kitaoka K.
      • Masuda S.
      Classification of burnout according to the Maslach Burnout Inventory-General Survey; Five classifications according to the exhaustion+1 criterion.
      ] by Chi-square test to assess burnout state. Finally, we performed path analysis by using comparative fit index (CFI), goodness of fit index (GFI), root mean square error of approximation (RMSEA), and Akaike's information criterion (AIC) to create a causal model and test the model fit indices of the Vietnamese version based on the original hypothesized model of Leiter and Maslach [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife: a structured approach to organization predictor of job burnout.
      ] in the Figure 1.

      Results

      Characteristics of participants

      Table 1 shows participants' characteristics. There were more female nurses (88.1%) than male (11.9%). Average age of participants was 31.64 ± 6.72. Most nurses were already married (78.8%) and had children aged under 11 years (75.3%). As for job factors, average years of nursing work was 8.6 ± 6.48, and working year group from 1 to 5 years had the highest percentage of 41.9%. Conversely, the group with more than 15 years of working was 13.9%. The most common on-duty work schedule was two days per week (63.5%), and most nurses had completed a two-year nursing diploma (65.3%).
      Table 1Subscale Scores of Vietnamese MBI-GS by Characteristics (N = 430).
      Variablesn (%)ExhaustionCynicismProfessional efficacy
      Mean ± SDF or tpMean ± SDF or tpMean ± SDF or tp
      Sex
       Female379 (88.1)3.05 ± 1.050.63.4292.67 ± 0.970.49.4823.98 ± 0.740.62.432
       Male51 (11.9)2.92 ± 1.072.57 ± 1.044.07 ± 0.82
      Age group (yr)
       20–29206 (47.9)3.33 ± 1.0116.65<.0012.86 ± 0.978.79<.0013.80 ± 0.6413.90<.001
       30–39164 (38.1)2.78 ± 1.072.45 ± 0.984.14 ± 0.82
       Above 3960 (14.0)2.72 ± 0.882.54 ± 0.884.24 ± 0.75
      Marriage status
       Married339 (78.8)2.92 ± 1.0418.47<.0012.58 ± 0.979.94.0024.07 ± 0.7518.89<.001
       Unmarried91 (21.2)3.45 ± 1.022.95 ± 0.973.69 ± 0.69
      Children
       With315 (73.5)2.91 ± 1.0516.89<.0012.58 ± 0.987.77.0064.07 ± 0.7615.11<.001
       Without115 (26.7)3.37 ± 0.992.88 ± 0.963.76 ± 0.67
      Age of children (yr)
       Above 1178 (24.7)2.76 ± 0.909.53<.0012.57 ± 0.903.88.0214.25 ± 0.7410.73<.001
       Below 11237 (75.3)2.96 ± 1.092.58 ± 1.004.02 ± 0.76
      Year of nursing work
       1–5180 (41.9)3.37 ± 1.0011.94<.0012.87 ± 0.936.07<.0013.77 ± 0.6312.06<.001
       6–10126 (29.3)2.87 ± 1.102.61 ± 1.044.03 ± 0.76
       11–1564 (14.9)2.74 ± 1.012.32 ± 0.974.25 ± 0.82
       Above 1560 (13.9)2.67 ± 0.882.50 ± 0.894.03 ± 0.77
      Workplace
       Surgical124 (28.8)2.96 ± 1.130.67.5742.47 ± 1.122.84.0384.16 ± 0.726.02.001
       Medical106 (24.7)3.11 ± 1.112.65 ± 1.043.99 ± 0.80
       Pediatric78 (18.1)3.12 ± 0.952.86 ± 0.734.06 ± 0.61
       Obstetric122 (28.4)2.98 ± 1.002.72 ± 0.883.77 ± 0.77
      Position
       Staff nurse398 (92.6)3.11 ± 1.0134.18<.0012.75 ± 0.9256.67<.0013.91 ± 0.7064.93<.001
       Head nurse32 (7.4)2.02 ± 1.041.48 ± 0.924.95 ± 0.70
      On-duty work schedule
       0 day29 (6.7)2.01 ± 1.0128.21<.0011.52 ± 1.0427.39<.0015.04 ± 0.6228.59<.001
       1 day57 (13.3)2.68 ± 1.012.3 ± 0.893.90 ± 0.81
       2 days273 (63.5)3.01 ± 0.952.71 ± 0.903.99 ± 0.69
       More than 2 days71 (16.5)3.80 ± 0.853.21 ± 0.853.65 ± 0.55
      Qualification
       Four years BScN degree79 (18.4)2.41 ± 0.9818.43<.0012.00 ± 1.0323.99<.0014.50 ± 0.7925.27<.001
       College Nursing Diploma70 (16.3)3.08 ± 0.942.77 ± 0.873.92 ± 0.69
       Two-year Nursing Diploma281 (65.3)3.19 ± 1.042.82 ± 0.923.86 ± 0.69
      Total430 (100.0)3.03 ± 1.052.66 ± 0.983.99 ± 0.75
      Note. ANOVA=Analysis of variance test; MBI-GS=Maslach Burnout Inventory-General Survey; SD = standard deviation.

      Psychometric properties of the Vietnamese MBI-GS and AWS

      Table 2 shows factor loading of the Vietnamese MBI-GS. Initially, four factors with an eigenvalue more than one were presented. However, in the original MBI-GS version, exploratory factor analysis showed three factors. Therefore, we chose three factors for rotation. After extraction, factor 1 was identified as exhaustion, factor 2 as professional efficacy, and factor 3 as cynicism. The Cronbach α of exhaustion, professional efficacy, and cynicism reached values of .89, .80, and .77, respectively. For exhaustion and professional efficacy, loading of all items indicated a sufficient value greater than .30. However, for cynicism, three items (i.e., 8, 9, and 13) did not load significantly (less than .30) [
      • Hoang G.T.
      • Corbiere M.
      • Negrini A.
      • Pham K.M.
      • Reinharz D.
      Validation of the Karasek-job content questionnaire to measure job strain in Viet Nam.
      ]. According to factor loading, these items should be located within the exhaustion subscale. Therefore, based on these results, we did not score items 8, 9, and 13 in the present study.
      Table 2Exploratory Factor Analysis of Vietnamese MBI-GS (N = 430).
      ItemsFactor
      123
      Exhaustion (α = .89)
      MBI-GS 2.99.04−.15
      MBI-GS 1.99.10−.15
      MBI-GS 3.76−.01.08
      MBI-GS 4.75.02.15
      MBI-GS 6.52−.05.21
      Professional efficacy (α = .80)
      MBI-GS 10−.06.80.24
      MBI-GS 11−.08.75.07
      MBI-GS 12−.01.70.01
      MBI-GS 7.10.59−.12
      MBI-GS 16.01.55−.06
      MBI-GS 5.21.53−.11
      Cynicism (α = .77)
      MBI-GS 15−.01.01.88
      MBI-GS 14.06.01.74
      MBI-GS 9.43−.17.29
      MBI-GS 8.35−.22.28
      MBI-GS 13.31.15.20
      Factor correlation matrix
      1−.52.60
      2−.45
      Note. Extraction method: maximum likelihood; Rotation method: promax with Kaiser normalization.
      MBI-GS=Maslach Burnout Inventory-General Survey.
      Table 3 shows exploratory factor analysis of the Vietnamese AWS. Initially, by natural loading, eight factors were extracted with eigenvalue more than one. As in the original AWS version, six factors were constructed. Therefore, we chose six factors for rotation. We did not score subscale items 5 (workload), 6 (control), 14 and 15 (community), and 21 (fairness) because they did not satisfy factorability criteria (at least .30). We calculated internal consistency of each subscale using Cronbach α. Alpha values were acceptable when the following five items were not scored: .74 for workload (without item 5), .62 for control (without item 6), .68 for community (without items 14 and 15), and .77 for fairness (without item 21). Alpha values of rewards and value were .71 and .81, respectively.
      Table 3Exploratory Factor Analysis of Vietnamese AWS (N = 430).
      ItemsFactor
      123456
      Workload (α = .42) (α = .74 without AWS 5)
      AWS 1
      Reversed item
      .00
      The results were shown up to the second decimal place.
      −.03.72−.06.00
      The results were shown up to the second decimal place.
      .00
      The results were shown up to the second decimal place.
      AWS 3
      Reversed item
      −.18.07.66.01−.02.05
      AWS 4.10−.09.65.11−.05−.02
      AWS 2
      Reversed item
      .06.11.47.14.08−.06
      AWS 5−.08−.01−.21−.06−.14−.02
      Control (α = .57) (α = .62 without AWS 6)
      AWS 9−.07.03.02.60.01−.11
      AWS 8.16−.06.02.58−.03−.01
      AWS 7.04−.01.07.55−.05.04
      AWS 6.08−.05.05.20.00b.00
      The results were shown up to the second decimal place.
      Rewards (α = .71)
      AWS 12
      Reversed item
      −.08.02.02−.03.80−.14
      AWS 13
      Reversed item
      −.01−.08.04.02.62.09
      AWS 11−.01−.08−.05.39.40.06
      AWS 10−.03−.02.03.30.32.09
      Community (α = .51) (α = .68 without AWS 14 and 15)
      AWS 17.04−.05−.02−.04−.05.92
      AWS 16−.03.03.06.00
      The results were shown up to the second decimal place.
      −.01.78
      AWS 18
      Reversed item
      −.07.09−.05−.03.05.35
      AWS 14.14.15−.12−.10.46.04
      AWS 15−.09−.02−.01.11.02.00
      The results were shown up to the second decimal place.
      Fairness (α = .73) (α = .77 without AWS 21)
      AWS 22−.04.76−.08.15−.09−.04
      AWS 23
      Reversed item
      .06.74.09−.16.03.00
      The results were shown up to the second decimal place.
      AWS 24
      Reversed item
      −.00.63.04−.16.11.04
      AWS 19−.09.44−.05.39−.08.09
      AWS 20.11.30−.03.20.08.05
      AWS 21.17.00
      The results were shown up to the second decimal place.
      .13.17−.09−.07
      Value (α = .81)
      AWS 27.89.01.00
      The results were shown up to the second decimal place.
      −.12.06.05
      AWS 28.81.04.08−.14−.02−.01
      AWS 26.62−.06−.12.18−.05−.04
      AWS 25.59.04−.03.21.00
      The results were shown up to the second decimal place.
      −.03
      Factor correlation matrix
      1.34.24.42.32.20
      2.36.48.43.48
      3.44.37.22
      4.50.42
      5.44
      Note. Extraction method: Maximum likelihood; Rotation method: Promax with Kaiser normalization;
      AWS=Areas of Worklife Scale.
      a Reversed item
      b The results were shown up to the second decimal place.

      Burnout state of Vietnamese clinical nurses

      In Table 1, the mean score on exhaustion was 3.03 ± 1.05, cynicism has an overall mean score of 2.66 ± 0.98, and professional efficacy has an overall mean score of 3.99 ± 0.75. There were significant differences in each factor except gender. Nurses who worked for more than two days had the highest scores for exhaustion and cynicism and the lowest for professional efficacy.
      Table 4 presents predictors for burnout. “On-duty work schedule” was a significant predictor in three subscales. The best predictors of professional efficacy were marriage status, years of nursing work, workplace, and position. The best predictors of cynicism were workplace, position, and qualifications.
      Table 4Burnout Predictors Using Stepwise Multiple Regression (N = 430): Standardized Coefficients.
      VariablesExhaustionCynicismProfessional efficacy
      βpβpβp
      Sex
      Age group (yr)
      Marriage status.11.030
      Age of children (yr)
      Year of nursing work.12.026
      Workplace.16.001.14.004
      Position.15.038−.23.001
      On-duty work schedule.39<.001.22.002−.19.004
      Qualification−.16.009
      Total R2.18.24.25
      Total R2 Adjusted.15.21.21
      Table 5 presents results of the burnout state according to five burnout classifications [
      • Kitaoka K.
      • Masuda S.
      Classification of burnout according to the Maslach Burnout Inventory-General Survey; Five classifications according to the exhaustion+1 criterion.
      ]. In general, most nurses (62.8%) were healthy, whereas 17.2% were classified as exhausted, 15.8% with burnout, 3.5% as depressed, and 0.7% with severe burnout. We found no relationship between gender, workplace, and burnout level. Among the age group of nurses older than 39, 80.0% were in good health. The burnout rate of unmarried nurses without children was twice that of married nurses with children. As for job factors, the least healthy was the group with 1–5 years of nursing work (50.0%). A higher rate of staff nurses than head nurses was represented in most burnout categories. Nurses with more than two days on duty had the highest rate of burnout and exhaustion.
      Table 5Burnout Level by Characteristics (N = 430).
      VariablesSeverely burnoutBurnoutExhaustedDepressedHealthyχ2p
      n (%)n (%)n (%)n (%)n (%)
      Sex
       Female2 (0.5)61 (16.1)69 (18.2)14 (3.7)233 (61.5)4.59.332
       Male1 (2.0)7 (13.7)5 (9.8)1 (2.0)37 (72.5)
      Age group (yr)
       20–292 (1.0)42 (20.4)48 (23.3)10 (4.9)104 (50.5)33.51<.001
       30–390 (0.0)24 (14.6)20 (12.2)2 (1.2)118 (72.0)
       Above 391 (1.7)2 (3.3)6 (10.0)3 (5.0)48 (80.0)
      Marriage status
       Married3 (0.9)42 (12.4)55 (16.2)13 (3.8)226 (66.7)17.97.001
       Unmarried0 (0.0)26 (28.6)19 (20.9)2 (2.2)44 (48.4)
      Children
       With3 (1.0)39 (12.4)51 (16.2)13 (4.1)209 (66.3)14.34.006
       Without0 (0.0)29 (25.2)23 (20.0)2 (1.7)61 (53.0)
      Age of children (yr)
       Above 111 (1.3)7 (9.0)7 (9.0)3 (3.8)60 (76.9)20.26.009
       Below 112 (0.8)32 (13.5)44 (18.6)10 (4.2)149 (62.9)
      Year of nursing work
       1–51 (0.6)38 (21.1)44 (24.4)7 (3.9)90 (50.0)34.12.001
       6–101 (0.8)21 (16.7)16 (12.7)5 (4.0)83 (65.8)
       11–150 (0.0)7 (10.9)9 (14.1)0 (0.0)48 (75.0)
       More than 151 (1.7)2 (3.3)5 (8.3)3 (5.0)49 (81.7)
      Workplace
       Surgical1 (0.8)19 (15.3)22 (17.7)6 (4.8)76 (61.3)4.42.923
       Medical1 (0.9)20 (18.9)20 (18.9)3 (2.8)62 (58.5)
       Pediatric0 (0.0)13 (16.7)11 (14.1)3 (3.8)51 (65.4)
       Obstetric1 (0.8)16 (13.1)21 (17.2)3 (2.5)81 (66.4)
      Position
       Staff nurse3 (0.8)68 (17.1)71 (17.8)15 (3.8)241 (60.6)12.41.015
       Head nurse0 (0.0)0 (0.0)3 (9.4)0 (0.0)29 (90.6)
      On-duty work schedule
       0 day0 (0.0)0 (0.0)3 (10.3)1 (3.4)25 (86.2)48.91<.001
       1 day0 (0.0)2 (3.5)8 (14.0)2 (3.5)45 (78.9)
       2 days2 (0.7)41 (15.0)44 (16.1)9 (3.3)177 (64.8)
       More than 2 days1 (1.4)25 (35.2)19 (26.8)3 (4.2)23 (32.4)
      Qualification
       Four years BScN degree0 (0.0)3 (3.8)6 (7.6)3 (3.8)67 (84.8)25.93.001
       College Nursing Diploma0 (0.0)11 (15.7)10 (14.3)3 (4.3)46 (65.7)
       Two-year Nursing Diploma3 (1.1)54 (19.2)58 (20.6)9 (3.2)157 (55.9)
      Total3 (0.7)68 (15.8)74 (17.2)15 (3.5)270 (62.8)
      Note. BScN = Bachelor of Science in Nursing.

      Causal model of burnout

      A path analysis of the hypothesized model produced the following results: Chi-square (χ2 = 204.37, p < .001), CFI = .82, GFI = .92, RMSEA = .16, and AIC = 260.38. These results did not meet criteria for model fit. We then performed a modified model with the control setup as the foundation. After analysis, these results (χ2 = 58.47, p < .001; CFI = .96; GFI = .97; RMSEA = .08; AIC = 120.46) met criteria for model fit. All paths were significant with 14 degrees of freedom. Regression coefficients are shown in Figure 2. The modified model presents different paths to compare with the original model, not only workload but also rewards and fairness directly linked to exhaustion. Control and community were directly linked to professional efficacy. There was also a direct path from control to five other work domains. From the hypothesized model, we identified three factors (rewards, community, and fairness) that were relevant to value, although only fairness showed a direct path to value in the modified model. In addition, value led to three domains of burnout in both causal and hypothesized models.

      Discussion

      Vietnamese versions of the MBI-GS and AWS

      We chose to translate and test the validity and reliability of the MBI-GS and AWS as no research on measurement scales to assess job stressor and burnout has yet been carried out despite the rising levels of job stress in Vietnam [
      • Le T.T.
      • Tran L.T.
      • Tran X.N.
      Job stress researching on nurses.
      ]. The MBI-GS and AWS are well used in the domain of occupational health research. The translated versions of MBI-GS exist such as the Japanese version [
      • Kitaoka K.
      • Nakagawa H.
      • Morikawa Y.
      • Ishizaki M.
      • Miura K.
      • Naruse Y.
      • et al.
      Construct validity of the Maslach burnout inventory–general survey.
      ], Malaysian version [
      • Chen W.S.
      • Haniff J.
      • Siau S.C.
      • Seet W.
      • Loh F.S.
      • Jamil A.H.M.
      • et al.
      Translation, cross-cultural adaptation and validation of the Malay version of the Maslach burnout inventory (MBI) in Malaysia.
      ], and Chinese version [
      • Wu S.
      • Zhu W.
      • Wang Z.
      • Wang M.
      • Lan Y.
      Relationship between burnout and occupational stress among nurses in China.
      ], even in Asian countries. The Vietnamese version we created in the present study would be useful to develop occupational health research in Vietnam.
      The construct validity evaluation supported a three-factor structure of the MBI-GS. But our analysis suggested that items 8, 9, and 13 of the scale should have been located in the exhaustion rather than cynicism subscale. The same issue has been mentioned in the Malaysian version, and authors suggested it to be mainly the result of differences in cultural knowledge and experience [
      • Chen W.S.
      • Haniff J.
      • Siau S.C.
      • Seet W.
      • Loh F.S.
      • Jamil A.H.M.
      • et al.
      Translation, cross-cultural adaptation and validation of the Malay version of the Maslach burnout inventory (MBI) in Malaysia.
      ]. However, both of Japanese [
      • Kitaoka K.
      • Nakagawa H.
      • Morikawa Y.
      • Ishizaki M.
      • Miura K.
      • Naruse Y.
      • et al.
      Construct validity of the Maslach burnout inventory–general survey.
      ] and Chinese versions [
      • Wu S.
      • Zhu W.
      • Wang Z.
      • Wang M.
      • Lan Y.
      Relationship between burnout and occupational stress among nurses in China.
      ] have supported the original version. The factor structure of the AWS was supported in the present study, but factor loadings of five items (5, 6, 14, 15, and 21) were insufficient. For item 5 of workload scale, “I leave my work behind when I go home at the end of the workday” conflicts with Vietnamese culture, which is unfamiliar with the concept of leaving one's job behind. The Japanese version of AWS [
      • Kitaoka K.
      • Masuda S.
      • Morikawa Y.
      • Nakagawa H.
      Japanese version of the Areas of Worklife Survey (AWS): six mismatches between person and job environment.
      ] has the same issue regarding item 5. For item 21 of fairness scale, “There are effective appeal procedures available when I question the fairness of a decision” refers to procedures that actually do not exist at the three hospitals in the present study. The Spanish version supported original version without any eliminated item [
      • Gascon S.
      • Leiter M.P.
      • Stright N.
      • Santed M.A.
      • Marin J.M.
      • Andres E.
      • et al.
      A factor confirmation and convergent validity of the “area of worklife scale” (AWS) to Spanish translation.
      ]. The German version [
      • Brom S.S.
      • Buruck G.
      • Horvath I.
      • Richter P.
      • Leiter P.M.
      Areas of worklife as predictors of occupational health – a validation study in two German samples.
      ] has excluded two items in which one item from fairness sub-scale and other item belongs to value sub-scale because of increasing internal consistency for satisfactory and possible explanation was that item content did not differ among the participants. Item 15 of community domain “I am a member of a supportive work group” might confuse Vietnamese nurses as “supportive work group” is not a fully understood concept in the Vietnamese health-care system. Finally, item 6 “I have control over how I do my work” and item 14 “People trust one another to fulfill their roles” require more attention and examination. In general, the Vietnamese versions of the MBI-GS and AWS can be used because both scales have the same factor structure as the original ones. But further examination is needed regarding issues aforementioned to be resolved. Meanwhile, we recommend scoring both scales based on results from the analysis researcher performance.

      Burnout state of Vietnamese clinical nurses

      As a whole, we found that Vietnamese clinical nurses were healthy (62.8%), but this finding was slightly higher than that reported in Japanese mental health nurses (53%) and much lower than that in Finnish mental health nurses (93.5%) [
      • Kitaoka K.
      • Masuda S.
      • Ohnishi K.
      • Nakahara J.
      • Takezawa S.
      • Morikawa Y.
      • et al.
      Rate of burnout among Japanese mental health nurses assessed using the revised exhaustion+1 criterion: a comparison across occupations and countries.
      ]. The burnout rate in the present study was also higher than that of Japanese neurosurgeons but lower than that of Japanese mental health nurses. In contrast, the number of nurses suffering from exhaustion was quite high (17.2%) in the present study compared with that of nurses from Japan (10.6%) and Finland (3.7%) [
      • Kitaoka K.
      • Masuda S.
      • Ohnishi K.
      • Nakahara J.
      • Takezawa S.
      • Morikawa Y.
      • et al.
      Rate of burnout among Japanese mental health nurses assessed using the revised exhaustion+1 criterion: a comparison across occupations and countries.
      ]. Such a high exhaustion rate represents a potential problem if nothing is done to prevent burnout in these nurses.
      The highlight of our research was finding that “on-duty work schedule” was the most significant predictor in three subscales of burnout. More on-duty days (more than two days) per week led to severe exhaustion. The term “on-duty work schedule” in Vietnam means that clinical nurses keep working on wards for 24 hours according to health-care system regulations (8 hours per day and 16 hours all night) followed by a day’s off [
      • Vietnamese Government
      Stipulating some specific allowances for civil servants, officials, workers in the public health facilities [Internet].
      ]. In reality, at the three hospitals in this study, only two nurses are assigned to provide all-night care to an ever-changing number of patients in the department (excluding special units such as intensive care unit or emergency). When patient numbers are high and nursing staff are inadequate, work overload can certainly lead to exhaustion. Logically, more exhaustion easily leads to reduced professional efficacy. A strong relationship between stress and being on duty work was found by medical staff in a job stress research [
      • Nguyen H.T.
      • Ta B.T.
      Job stress in medical staff.
      ]. Another study stated that high level of burnout in exhaustion was found in midwives who had night-shift schedule [
      • Shahriari M.
      • Shamali M.
      • Yazdannik A.
      The relationship between fixed and rotating shifts with job burnout in nurses working in critical care areas.
      ]. A greater degree of stress and burnout was detected among nurses on shift duty. Nurses with smaller hospital type and no shift work were also associated with lower exhaustion and depersonalization together with higher personal accomplishment [
      • Xie Z.
      • Wang A.
      • Chen B.
      Nurse burnout and its association with occupational stress in a cross-sectional study in Shanghai.
      ]. Therefore, it is recommended to arrange appropriate number of nurse staff in each department or to adjust work shift schedules to prevent this growing problem.

      Causal model of burnout

      The primary purpose of this research was to identify contributory factors to worklife to predict burnout. This study is the first one that targets clinical nurses in Vietnam. In general, we found both similar and different directions of effect as compared with the Leiter and Maslach's model [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife: a structured approach to organization predictor of job burnout.
      ], whereas some studies significantly supported the original model described by Leiter and Maslach such as their structural model found most similar pattern in significance and direction of effects [
      • Gascon S.
      • Leiter M.P.
      • Stright N.
      • Santed M.A.
      • Marin J.M.
      • Andres E.
      • et al.
      A factor confirmation and convergent validity of the “area of worklife scale” (AWS) to Spanish translation.
      ,
      • Brom S.S.
      • Buruck G.
      • Horvath I.
      • Richter P.
      • Leiter P.M.
      Areas of worklife as predictors of occupational health – a validation study in two German samples.
      ]. Other study partly supported the original model as different relationship between AWS dimensions and each aspect of burnout was shown [
      • Portoghese I.
      • Galletta M.
      • Coppola R.C.
      • Finco G.
      • Campagna M.
      Burnout and workload among health care workers: the moderating role of job control.
      ]. All of these research studies have come from Europe and America.
      In identical fashion of this study, control has a strong pathway to other aspects of work environment and plays a central role in burnout prediction. However, the original model posits that control has an indirect impact on professional efficacy, whereas we found that control had a direct effect on professional efficacy. It makes sense that lack of control might lead to low productivity or reversal. This result is also mentioned in a study where employees have ability to give influence decision that affects their work that they are more likely to do an effective job [
      • Maslach C.
      • Leiter M.P.
      Understanding the burnout experience: recent research and its implications for psychiatry.
      ]. The issue of control reflects the opportunity for decision-making and independence at work, and lack of participation in decision-making has been most predictive of reduced professional efficacy [
      • Lasalvia A.
      • Bonetto C.
      • Bertani M.
      • Bissoli S.
      • Cristofalo D.
      • Marrella G.
      • et al.
      Influence of perceived organizational factors on job burnout: survey of community mental health staff.
      ].
      Workload is strongly related to exhaustion [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife: a structured approach to organization predictor of job burnout.
      ,
      • Maslach C.
      • Leiter M.P.
      Understanding the burnout experience: recent research and its implications for psychiatry.
      ]. However, besides workload, our findings showed that rewards and fairness also led to exhaustion. The strong relationship between these factors suggests that unequal treatment and feeling unrecognized or unappreciated at work can cause feelings of exhaustion. Regarding fairness, our results support this premise considering the lack of effective appeals procedures available in Vietnam for nurses who question the fairness of a decision (item 21 of the AWS). Furthermore, inadequate nurse staff can make it difficult to fairly allocate resources in a hospital. Consequently, these issues can be emotionally draining on nurses. In another study, workplace fairness was a strong predictor of emotional exhaustion among male and female police in Nigeria [
      • Adebayo D.O.
      • Sunmola A.M.
      • Udegbe I.B.
      Workplace fairness and emotional exhaustion in Nigeria police: the moderating role of gender.
      ]. In addition, perceived unfairness at work has been shown to predict depression and burnout [
      • Herr R.M.
      • Loerbroks A.
      • Bosch J.A.
      • Seegel M.
      • Schneider M.
      • Schmidt B.
      Associations of organizational justice with tinnitus and the mediating role of depressive symptoms and Burnout-Findings from a cross-sectional study.
      ]. As for rewards, instead of being linked to value as in the original model, we proposed a relationship between rewards and exhaustion. It is understandable that lack of recognition and appreciation for contributions at work can lead to feelings of exhaustion. Recent publication has introduced the concept of effort–reward imbalance, which has been positively related to emotional exhaustion [
      • Feuerhahn N.
      • Kühnel J.
      • Kudielka B.M.
      Interaction effects of effort-reward imbalance and overcommitment on emotional exhaustion and job performance.
      ]. Job reward also had a strong correlation with exhaustion but weaker prediction of cynicism [
      • Shahriari M.
      • Shamali M.
      • Yazdannik A.
      The relationship between fixed and rotating shifts with job burnout in nurses working in critical care areas.
      ].
      Lasalvia et al has argued that rewards and fairness are directly linked to job efficacy and that poor rewards and unequal treatment were most predictive of professional efficacy. On the other hand, community was directly linked to job effectiveness in the present study [
      • Lasalvia A.
      • Bonetto C.
      • Bertani M.
      • Bissoli S.
      • Cristofalo D.
      • Marrella G.
      • et al.
      Influence of perceived organizational factors on job burnout: survey of community mental health staff.
      ]. The term “community” has a variety of meanings, including trusting one another, work-group cohesion, and human relations at work [
      • Leiter M.P.
      • Maslach C.
      Areas of worklife: a structured approach to organization predictor of job burnout.
      ]. Without trust and support in group work, nurses might find it difficult to function effectively. Lasalvia et al [
      • Lasalvia A.
      • Bonetto C.
      • Bertani M.
      • Bissoli S.
      • Cristofalo D.
      • Marrella G.
      • et al.
      Influence of perceived organizational factors on job burnout: survey of community mental health staff.
      ] also argued that work groups with poorer connections are at higher risk of burnout. Furthermore, coworker support has been more closely related to accomplishment or efficacy, whereas supervisor support was said to be more consistent with exhaustion [
      • Halbesleben J.R.
      Sources of social support and burnout: a meta-analytic test of the conversation of resources model.
      ]. When staff received good relationship with other people on the job, they seem to get more job engagement [
      • Maslach C.
      • Leiter M.P.
      Understanding the burnout experience: recent research and its implications for psychiatry.
      ].
      The original model of Leiter and Maslach's theory is well known and mostly supported by population of countries in the European Union and North America. In other countries, studies regarding relationship between burnout and AWS model have not been published yet, besides our study. In summary, their theory would also be working in describing Vietnamese nurses' burnout. Both burnout and causes of burnout among nurses can be presented in their model as we mentioned previously. However, our study also contributed some valuable knowledge that their original model might need to be revised in terms of Asian sample including Vietnam. Further examinations would give us resolution.

      Conclusion

      Based on our findings, the reliability and validity of the Vietnamese MBI-GS and AWS are acceptable for use in future investigations. Taking into consideration the state of burnout in Vietnam, approximately 20% of clinical nurses were in burnout including severe burnout. It is nearly the same rate as nurses with exhausted feeling; those nurses could be easily in danger of burnout if no prevention was done. More days' on-duty work strongly predicted burnout. The causal model proposed that control played an important role as the exogenous factor for burnout prediction, whereas exhaustion was directly caused not only by workload and value but also by rewards and fairness. Professional efficacy was strongly involved in community as well as control and value. Cynicism was caused only by value.
      Our results suggest various factors leading to burnout. According to these results, many solutions or interventions can be applied for burnout prevention, such as consideration of more nurses and appropriate work schedules. Solutions to limit exhaustion might also include minimizing favoritism by managers and ensuring fair distribution of opportunities. In addition, rewarding excellent performance with bonuses or promotions might effectively reduce exhaustion among nurses. Finally, work group support might greatly help increase profession efficacy. Further studies are necessary to research on other participants for the overall picture of burnout in Vietnam.

      Conflicts of interest

      There is no conflict of interest regarding this study.

      Acknowledgments

      This study was self-supported. The authors are grateful to and sincerely thank the management boards of the hospitals, clinical nurses at selected hospitals, and nursing faculty of Hai Phong University of Medicine and Pharmacy, Vietnam. The authors also thank the Kanazawa University Medical Ethics Committee, Japan, for approving their research.

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