The Effects of Work Satisfaction and Work Flexibility on Burnout in Nurses : Journal of Nursing Research

Secondary Logo

Journal Logo

ORIGINAL ARTICLES

The Effects of Work Satisfaction and Work Flexibility on Burnout in Nurses

LEE, Huan-Fang1,∗; CHANG, Ying-Ju2

Author Information
doi: 10.1097/jnr.0000000000000522
  • Open

Abstract

Introduction

The World Health Organization (WHO, 2016) has identified the nursing workforce and nursing capacity as vital to achieving universal health. Although the number of professionals has been increasing gradually, nurse staffing numbers remain insufficient to meet current healthcare demands. Therefore, countries should strengthen the nursing workforce and nursing capacity by ensuring adequate equipment and resource supplies, including the provision of appropriate working conditions and remuneration, to promote nursing staff recruitment and retention efforts (WHO, 2016).

According to the 20th International Council of Nurses Asia Workforce Forum in 2019, the WHO has identified continuing shortages in the care workforce in East Asia as well as in Africa and Southeast Asia, which are expected to be the regions experiencing the worst care-workforce shortages by 2030 (L. Wang et al., 2017). In a large-sample survey, a positive relationship was found between work flexibility policies and human resources management (Huang et al., 2016). Therefore, hospitals have been encouraged to develop flexible working conditions that meet the job needs of nursing staff to improve job satisfaction levels. According to the Ministry of Health and Welfare, Taiwan, ROC (2019), the turnover rate for the country's nursing workforce is about 10%, and 35%–75% of hospitals face difficulties recruiting nurses. Moreover, the pool of nurses aged 20–30 years is declining annually, and an increasing number of nurses are retiring early, when they are in their 40s.

An important relationship between the reasons for nursing shortages and burnout has been shown in previous studies (Back et al., 2020; Kelly et al., 2021; Lee et al., 2019). Burnout is an emotional condition arising from interacting with one's environment that includes three dimensions: emotional exhaustion, low sense of personal accomplishment, and depersonalization. Individuals who are under continuous work stress may perceive their environment as dehumanizing and promoting a reduced sense of personal achievement.

A survey of a stratified random sample of nursing staff at 35 hospitals in Taiwan showed that 80% reported moderate or severe burnout (Lee & Yen, 2017), indicating that the problem of nursing staff burnout in Taiwan is critical and should be treated proactively. The International Council of Nurses has encouraged fostering positive practice environments that promote job satisfaction and reduce burnout in nurses to promote higher rates of retention. High-quality workplace environments have been shown to increase staff satisfaction and reduce burnout in nurses (Asiret et al., 2017; L. Wang et al., 2017; Wu et al., 2020), which may be expected to reduce intention to leave.

Liu et al. (2016) presented three characteristics of nursing job satisfaction: (a) The working environment meets the expectations of the nurse, (b) the working conditions make the nurse happy, and (c) the nurse feels the value and fairness of the work. Tzeng et al. (2017) identified the following five components of job satisfaction in nurses: (a) supportive practice environment, (b) professional autonomy and development, (c) interpersonal interaction and cooperation, (d) leadership style of supervisors, and (e) workload. Therefore, the factors that affect job satisfaction in nursing staff are multifaceted and need to be considered based on multiple aspects of the entire practice environment such as work job demand, job control, and social support (Abadi et al., 2021). Other researchers have identified a positive relationship between professional autonomy and personal accomplishment (Carvalho et al., 2020; O'Connor et al., 2018) and that excessive task workloads increase burnout (Hornung et al., 2019; MacPhee et al., 2017; Yestiana et al., 2019). Furthermore, interpersonal interaction has been shown to be an important factor underlying emotional exhaustion (S. Wang et al., 2015; Zhao & Jiang, 2021).

Fostering a positive working environment requires providing good working conditions for staff and a flexible system that increases willingness to stay on the job (Huang et al., 2016). Huang and colleagues explored the relationship between intention to leave and flexibility related to working conditions, finding that more-flexible working conditions led to greater work engagement among nurses. Flexibility in working conditions was found to comprise the dimensions of (a) task, (b) numerical, (c) divisional, (d) temporal, (e) wages, and (f) leadership (Huang et al., 2016; Huang & Lu, 2017). Task flexibility refers to functional changes used to improve employee mobility and adaptability or to develop the multiple skills necessary to respond quickly to changes in job requirements and technological developments. Numerical flexibility refers to when an enterprise, in the face of changes in output demand, adjusts the number of employees in a timely manner to meet real needs, maintain the balance between labor supply and demand, and reduce labor costs. Divisional flexibility refers to the division of the required manpower into core and peripheral human resources. Temporal flexibility refers to providing employees with the flexibility to work and take time off by changing hours or the number of hours worked to meet both the employee's needs and the needs of the business in terms of operational patterns and customer needs. Wage flexibility refers to changing the traditional fixed pay structure and adopting a personalized and payroll system. Leadership flexibility refers to the need for leaders to be flexible in terms of leadership and management in the face of changes and challenges in the practice environment (Huang & Lu, 2017). Task flexibility has also been found to be correlated with clinical competence, with the capacity to face complex tasks higher at higher levels of competence (Hornung et al., 2019; Ose et al., 2019) and job-induced stress affecting the level of emotional exhaustion (Liao et al., 2020).

The effects of working condition flexibility and job satisfaction on burnout in nurses remain unclear in extant research. Thus, the purpose of this study was to explore the effects of flexibility in terms of working conditions and job satisfaction on burnout.

Methods

Design and Sample

This cross-sectional study was designed to explore the relationships between burnout and, respectively, work satisfaction and work flexibility. The study setting was the medical, surgical, and intensive care units of the nursing department in a medical center in southern Taiwan. On the basis of the G*Power estimation (effect size f2 = 0.15, error probability = .05, power = 0.8, number of predictors = 11), the required minimum sample size was 123. However, as the participants were from three different areas (general surgical, general medical, and adult intensive care units), the final sample size targeted was 369. After considering the 20% loss rate, 450 participants were enrolled. The inclusion criterion was nurses who had worked for over 1 month, and the exclusion criterion was nurses who had taken sick leave for over 1 month. Data were collected from May to June 2019.

Instruments

The data collected included demographic data as well as three inventories, including the Taiwanese Hospital Nurses' Job Satisfaction Scale, the Working Conditions and Flexible System Scale (WCFS), and the Maslach Burnout Inventory-Chinese Version.

The Taiwanese hospital nurses' job satisfaction scale

The Taiwanese Hospital Nurses' Job Satisfaction Scale, developed by Tseng et al. (2017), comprises five dimensions with 31 items measured using a 5-point Likert scale ranging from 1 = very unsatisfactory to 5 = very satisfactory. The five dimensions include supportive working environment (nine items), professional autonomy and growth (nine items), interpersonal interaction and collaboration (six items), leadership style (four items), and nursing workload (three items), for which the Cronbach's α values are .96, .93, .93, .88, .95, and .86, respectively.

The working conditions and flexible system scale

The WCFS, developed by Huang et al. (2016), is a 113-item working conditions and flexible system scale with six dimensions, including task (19 items), numerical (eight items), divisional (eight items), temporal (21 items), wages (24 items), and leading flexibility (33 items). The WCFS is measured using a 5-point Likert scale ranging from 1 = very unimportant to 5 = very important. The overall Cronbach's α is .88.

The Maslach burnout inventory-Chinese version

The 22-item Maslach Burnout Inventory with three dimensions was developed by Maslach (1982). The Maslach Burnout Inventory is scored using a 7-point Likert scale ranging from 0 = never to 6 = always. The three dimensions include emotional exhaustion (eight items), low personal accomplishment (nine items), and depersonalization (five items). The 20-item Maslach Burnout Inventory-Chinese Version with three dimensions was modified by Lee et al. (2013) to include emotional exhaustion (eight items), low personal accomplishment (eight items), and depersonalization (four items). The overall Cronbach's α values for overall, emotional exhaustion, low personal accomplishment, and depersonalization are .85, .91, .86, and .65, respectively.

Ethical Considerations

Data collection began after approval from the institutional review board of the National Cheng Kung University Hospital, Taiwan (No. A-ER-108037). No information that could be used to identify individual participants was collected. The participants answered the questionnaires via an online Google sheet, and nurse leaders were not informed regarding who participated in the study or the survey results.

Data Analysis

The data were analyzed using IBM SPSS Statistics Version 18.0 (IBM Inc., Armonk, NY, USA). The descriptive data were presented in a frequency and percentage format for categorical data and in a mean and standard deviation format for continuous data. Pearson's product–moment correlation coefficient was used to measure the correlations between the continuous data. The predictive value of the variables was analyzed using a hierarchical regression.

Results

Demographic Characteristics

Four hundred fifty inventories were delivered to nurses, and 437 responses were received. Because of incomplete data, 435 were included in the final analysis.

Most of the participants were female and educated at the bachelor's level. The mean age was 29 years, 83.1% were unmarried, 81% had no prior working experience in other hospitals, and 65.5% were employed at a senior (over 2 years) level. The mean burnout score was 1.99, and the scores for the three subscales were all less than 3, indicating that the participants experienced burnout around 2 times per month. Emotional exhaustion earned the highest score of the three subscales. The mean score for work satisfaction was 3.77 and ranged between 3.40 and 3.87 for the subscales. This meant that the participants' satisfaction with the leadership was ranked the highest. The mean score for work flexibility was 3.66, and all subscales earned scores over 3.5, indicating that the participants considered work flexibility to be important, with task flexibility earning the highest subscale score (Table 1).

Table 1. - Demographic Characteristics of Participants (N = 435)
Variable n %
Gender
 Male 19 4.4
 Female 416 95.6
Education a
 College 12 2.8
 University 422 97.2
Marital status a
 Single 360 83.1
 Married 73 16.9
Working experience in other hospitals a
 No 349 81.2
 Yes 81 18.8
Nursing competence level a
 Novice (under 2 years) 154 35.5
 Senior (over 2 years) 280 65.5
Mean SD
Age 29.00 6.15
Seniority 5.77 7.55
Burnout total 1.99 0.85
 Burnout: emotional exhaustion 2.93 1.26
 Burnout: low personal accomplishment 1.78 0.99
 Burnout: depersonalization 1.27 1.25
Satisfaction total 3.77 0.51
 Satisfaction: supportive environment 3.81 0.57
 Satisfaction: professional autonomy 3.76 0.54
 Satisfaction: interpersonal interaction 3.86 0.55
 Satisfaction: leadership 3.87 0.69
 Satisfaction: workload 3.40 0.72
Work flexibility total 3.66 0.82
 Work flexibility: task 3.86 0.55
 Work flexibility: numerical 3.83 0.69
 Work flexibility: divisional 3.72 0.70
 Work flexibility: temporal 3.49 0.63
 Work flexibility: wage 3.73 0.72
 Work flexibility: leadership 3.81 0.65
a Missing data.

Correlations Among Burnout, Satisfaction With the Hospital, and Work Flexibility

A low-to-medium negative correlation was found between the emotional exhaustion dimension of burnout and all dimensions of satisfaction with the hospital (r = −.312 to −.425). Moreover, a low correlation (r = −.274 to −.328) was identified between emotional exhaustion and all dimensions of work flexibility. The two variables (the professional autonomy dimension of satisfaction and the divisional dimension of work flexibility) exhibited the strongest correlations with emotional exhaustion. With regard to the low personal accomplishment dimension of burnout, a low and negative correlation was identified between low personal accomplishment and all dimensions of satisfaction with the hospital (r = −.129 to −.278). Similar results were also found for all dimensions of work flexibility (r = −.117 to −.182), with a low negative correlation between the depersonalization dimension of burnout and all dimensions of satisfaction with the hospital (r = −.185 to −.264) and work flexibility (r = −.123 to −.203).

The supportive environment dimension of satisfaction with the hospital was found to be highly related to all dimensions of work flexibility (r = .608 to .720), especially task work flexibility (r = .720; Table 2).

Table 2. - Correlations Among Burnout, Satisfaction, and Work Flexibility (N = 435)
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1. B-EE 1 .115* .490** −.312** −.425** −.412** −.342** −.398** −.274** −.287** −.328** −.304** −.274** −.323**
2. B-LPA .197** −.157** −.278** −.173** −.129** −.092 −.182** −.117* −.131** −.094 −.143** −.172**
3. B-DP −.241** −.229** −.264** −.185** −.210** −.203** −.155** −.172** −.123* −.128** −.192**
4. S-SE .709** .636** .604** .526** .720** .612** .649** .608** .630** .705**
5. S-PA .718** .621** .612** .697** .535** .596** .577** .573** .679**
6. S-II .660** .574** .677** .529** .611** .554** .555** .660**
7. S-L .518** .602** .564** .553** .530** .514** .653**
8. S-WL .560** .489** .559** .551** .476** .540**
9. WF-Task .709** .721** .648** .662** .746**
10. WF-Numerical .703** .660** .658** .664**
11. WF-Divisional .677** .679** .685**
12. WF-Temporal .724** .698**
13. WF-Wage .804**
14. WF-Leadership 1
Note. B = burnout; EE = emotional exhaustion; LPA = low personal accomplishment; DP = depersonalization; S = satisfaction; SE = supportive environment; PA = professional autonomy; II = interpersonal interaction; L = leadership; WL = workload; WF = work flexibility.
*p < .05. **p < .01.

The Hierarchical Regression Analysis of the Variables Predicting Burnout

The demographic variables and all dimensions of satisfaction and work flexibility were included in the hierarchical regression analysis (Table 3). The four variables of professional autonomy (beta = −.252, p = .002), interpersonal interaction (beta = −.194, p = .008), low workload (beta = −.171, p = .005), and task flexibility (beta = −.273, p = .001) were found to be significant predictors of emotional exhaustion, with an adjusted variance of explanation of 21.2%. This finding indicates that professional autonomy, interpersonal interaction, workload, and task flexibility are negatively related to emotional exhaustion. Thus, emotional exhaustion should decrease in nurses with greater professional autonomy, better interpersonal interaction, lower workloads, and higher task flexibility.

Table 3. - Hierarchical Linear Regression of the Factors Related to the Burnout Subscales (N = 435)
Model Emotional Exhaustion Low Personal Accomplishment Depersonalization
Model 1 Model 2 Model 1 Model 2 Model 1 Model 2
Beta p Beta p Beta p Beta p Beta p Beta p
Level 1
 Constant < .001 < .001 < .001 < .001 .110 < .001
 Gender (ref.: male) .022 .653 0 1 −.062 .209 −.046 .346 .111 .023 .089 .067
 Age −.047 .580 .017 .826 −.012 .881 −.025 .757 −.101 .233 −.046 .585
 Education (ref.: college) .042 .401 .014 .751 −.067 .177 −.052 .284 −.007 .893 .006 .901
 Marital status (ref.: unmarried) .058 .302 .045 .375 .096 .081 .092 .087 −.053 .333 −.060 .266
 Other experience (ref.: no) −.031 .596 −.028 .595 .005 .930 −.006 .916 −.013 .818 −.016 .778
 Length of service −.053 .454 −.101 .109 .038 .585 .057 .399 −.016 .818 −.039 .568
 Competence (ref.: novice) .033 .575 .033 .540 .051 .382 .013 .818 .196 .001 .184 .002
Level 2
 Supportive environment .023 .756 −.055 .496 −.128 .109
 Professional autonomy −.252 .002 .338 <.001 −.086 .314
 Interpersonal interaction −.194 .008 .051 .521 −.139 .075
 Leadership −.036 .581 −.034 .627 .037 .592
 Workload −.171 .005 −.075 .255 −.098 .132
 Task flexibility −.273 .001 .035 .698 .054 .549
 Numerical flexibility −.066 .361 .001 .991 −.023 .769
 Divisional flexibility −.122 .125 .058 .505 −.016 .850
 Temporal flexibility −.006 .937 −.120 .137 .121 .122
 Wage flexibility .014 .873 .084 .360 .051 .571
 Leadership flexibility < .001 .999 −038 .713 −.044 .669
R 2 .011 .246 .026 .117 .048 .126
Adjusted R 2 .006 .212 .009 .077 .032 .086
R 2 .011 .235 .026 .091 .048 .077
F change .675 11.258 1.544 3.724 2.982 3.207
p .694 < .001 .151 < .001 .005 < .001

However, only professional autonomy (beta = .338, p < .001) was found to significantly predict personal accomplishment, with an adjusted variance of explanation of 7.7%. This finding indicates that improving professional autonomy has a positive effect on personal accomplishment.

Furthermore, nursing competence (beta = .184, p = .002) was the only variable identified as a predictor of depersonalization, with an adjusted variance of explanation of 8.6%. This finding indicates that, for nurses, competence level is positively associated with depersonalization.

Discussion

In this study, the perceptions of the participants related to satisfaction with the hospital and work flexibility ranged between moderately satisfied and satisfied and reflected low levels of burnout. Moreover, a high and positive correlation was found between satisfaction and work flexibility, and a low and negative correlation was found between burnout and both satisfaction and work flexibility. The predictors of emotional exhaustion were identified as follows: professional autonomy, interpersonal interaction, workload, and task flexibility. Professional autonomy was the only predictor of low personal accomplishment, and nursing competence level was the predictor of depersonalization.

Professional autonomy was found to be a predictor of emotional exhaustion and low personal accomplishment, which is similar to the findings of previous studies (Carvalho et al., 2020; O'Connor et al., 2018). In an unhealthy work environment, emotional exhaustion is perceived to be more significant when professional autonomy is restricted. Professional autonomy is also related to the concept of personal accomplishment, under which personal accomplishment is increased when professional autonomy is strengthened (Carvalho et al., 2020). Therefore, when nurses have insufficient professional autonomy or competence, they become stressed or do not trust themselves, leading to emotional exhaustion and a reduced sense of personal accomplishment.

High workload was also found to be a predictor of burnout in this study. According to Yestiana et al. (2019), nurse workload may be distinguished into quantitative and qualitative workloads, both of which may result in burnout, with the former referring to the number of patient care services provided by nurses and the latter referring to the level of responsibility nurses have related to patient care. In the nursing context, Macphee et al. (2017) also identified high workload as associated with perceptions of time pressure and lack of sufficient time to complete work tasks. The number of patients under their care is positively associated with the physical labor burden of nurses, whereas self-perceived level of responsibility and time pressure are positively associated with mental stress. Finally, once nurses perceive themselves as unable to cope with their workloads, they will experience burnout. Therefore, balancing job demand and resources is an important factor in increasing job satisfaction (Abadi et al., 2021).

Task flexibility was also identified as a predictor of burnout in this study. Previously, Hornung et al. (2019) identified three types of individual-level task flexibility (active use of task autonomy, self-initiated job crafting, and negotiation of task-related by superiors) as affecting burnout levels, with higher task overload resulting in more emotional exhaustion and lower job autonomy resulting in higher levels of emotional exhaustion (Hornung et al., 2019). The professional competence of nurses has been shown to be a critical factor affecting the relationship between patients and nurses (Billeter-Koponen & Fredén, 2005). Nurses who have the professional competence to meet patient needs experience a greater sense of personal accomplishment. Nursing competence includes not only clinical experience and capacity but also self-efficacy, as when nurses obtain the respect of others, their sense of accomplishment and belongingness increases (Li et al., 2012). However, nurses at higher levels of professional nursing status and competence typically assume greater responsibility in clinical settings and are thus more likely to perceive higher levels of stress and have a lower sense of accomplishment when not supported by their organization or society (Liao et al., 2020).

Furthermore, interpersonal interaction was found in this study to be a predictor of emotional exhaustion. An imbalance in interpersonal interaction may decrease team cooperation and result in emotional exhaustion (Zhao & Jiang, 2021). In a previous study, S. Wang et al. (2015) found that the relationship between physicians and nurses affects the perception of burnout. Therefore, interpersonal interaction affects not only the emotions of individuals but also the degree of team cooperation.

The findings of this study suggest several recommendations for nursing practice. First, hospital administrators should, based on considerations of professional autonomy, implement strategies to promote mutual respect within the organization and a cooperative organizational culture and provide opportunities for nurses to participate in decision-making committees. Second, policies related to staffing and task arrangement should be evaluated regularly, especially with regard to emergent situations such as significant and critical patient needs and severe health events. Third, educational programs targeting the communication skills necessary to build a positive working environment, various leadership styles and skills, and the simplification of care models and processes should be provided to leaders and primary nurses at different professional levels.

Conclusions

Professional autonomy and work flexibility are important predictors of burnout and job satisfaction in nurses. It is recommended that organizations provide preliminary and advanced training programs based on the needs of nurses to develop professional competence and higher professional autonomy in nurses. By improving their professional competence and job satisfaction through in-service education programs, nurses may effectively reduce and avoid job-related burnout.

Acknowledgments

This study was funded by the Taiwan Nurses Association (TWNA-1081017). We thank the nurses who participated in this study.

Author Contributions

Study conception and design: HFL, YJC

Data collection: HFL

Data analysis and interpretation: HFL

Drafting of the article: HFL, YJC

Critical revision of the article: HFL, YJC

References

Abadi M. B. H., Taban E., Khanjani N., Konjin Z. N., Khajehnasiri F., Samaei S. E. (2021). Relationships between job satisfaction and job demand, job control, social support, and depression in Iranian nurses. The Journal of Nursing Research, 29(2), Article e143. https://doi.org/10.1097/jnr.0000000000000410
Asiret G. D., Kapucu S., Kose T. K., Kurt B., Ersoy N. A. (2017). Attitudes and satisfaction of nurses with the work environment in Turkey. International Journal of Caring Sciences, 10(2), 771–780.
Back C. Y., Hyun D. S., Jeung D. Y., Chang S. J. (2020). Mediating effects of burnout in the association between emotional labor and turnover intention in Korean clinical nurses. Safety and Health at Work, 11(1), 88–96. https://doi.org/10.1016/j.shaw.2020.01.002
Billeter-Koponen S., Fredén L. (2005). Long-term stress, burnout and patient–nurse relations: Qualitative interview study about nurses' experiences. Scandinavian Journal of Caring Sciences, 19(1), 20–27. https://doi.org/10.1111/j.1471-6712.2005.00318.x
Carvalho A. E. L. D., Frazão I. D. S., Silva D. M. R. D., Andrade M. S., Vasconcelos S. C., Aquino J. M. D. (2020). Stress of nursing professionals working in pre-hospital care. Revista Brasileira de Enfermagem, 73(2), 1–6. https://doi.org/10.1590/0034-7167-2018-0660
Hornung S., Höge T., Rousseau D. M. (2019). Task flexibility through individualized work redesign—Probing a three-pronged approach. Psychologie des Alltagshandeln/Psychology of Everyday Activity, 12(2), 60–72.
Huang C.-I., Lu M.-S. (2017). The effectiveness of a strategy for the flexible management of nursing human resources: A pilot study. The Journal of Nursing, 64(6), 56–66. https://doi.org/10.6224/JN.000083 (Original work published in Chinese)
Huang C.-I., Yu C., Yu C.-C. (2016). An exploration of working conditions and flexible system for hospital nurses. The Journal of Nursing, 63(2), 80–90. https://doi.org/10.6224/JN.63.2.80 (Original work published in Chinese)
Kelly L. A., Gee P. M., Butler R. J. (2021). Impact of nurse burnout on organizational and position turnover. Nursing Outlook, 69(1), 96–102. https://doi.org/10.1016/j.outlook.2020.06.008
Lee H.-F., Chiang H.-Y., Kuo H.-T. (2019). Relationship between authentic leadership and nurses' intent to leave: The mediating role of work environment and burnout. Journal of Nursing Management, 27(1), 52–65. https://doi.org/10.1111/jonm.12648
Lee H.-F., Chien T.-W., Yen M. (2013). Examining factor structure of Maslach burnout inventory among nurses in Taiwan. Journal of Nursing Management, 21(4), 648–656. https://doi.org/10.1111/j.1365-2834.2012.01427.x
Lee H.-F., Yen M. (2017). Nurse burnout in Taiwan. Journal of Nursing and Women's Health, 2, 1–5. https://doi.org/10.29011/2577-1450.100007
Li Y.-H., Lin L.-D., Tsai C.-C., Chou M.-C., Lin M.-H. (2012). Factors of influence on willingness to participate in the N3 nursing clinical ladder program. The Journal of Nursing, 59(1), 41–50. https://doi.org/10.6224/JN.59.1.40 (Original work published in Chinese)
Liao R.-W., Yeh M.-L., Lin K.-C., Wang K.-Y. (2020). A hierarchical model of occupational burnout in nurses associated with job-induced stress, self-concept, and work environment. The Journal of Nursing Research, 28(2), Article e79. https://doi.org/10.1097/JNR.0000000000000348
Liu Y., Aungsuroch Y., Yunibhand J. (2016). Job satisfaction in nursing: A concept analysis study. International Nursing Review, 63(1), 84–91. https://doi.org/10.1111/inr.12215
MacPhee M., Dahinten V. S., Havaei F. (2017). The impact of heavy perceived nurse workloads on patient and nurse outcomes. Administrative Sciences, 7(1), Article 7. https://doi.org/10.3390/admsci7010007
Maslach C. (1982). The cost of caring. Prentice-Hall.
Ministry of Health and Welfare, Taiwan, ROC. (2019). Nursing policy and regulations. https://www.mohw.gov.tw/dl-51566-d64a9c62-d75e-4278-9f70-e5fde541de8f.html
O'Connor K., Neff D. M., Pitman S. (2018). Burnout in mental health professionals: A systematic review and meta-analysis of prevalence and determinants. European Psychiatry, 53, 74–99. https://doi.org/10.1016/j.eurpsy.2018.06.003
Ose S. O., Tjønnås M. S., Kaspersen S. L., Færevik H. (2019). One-year trial of 12-hour shifts in a non-intensive care unit and an intensive care unit in a public hospital: A qualitative study of 24 nurses' experiences. BMJ Open, 9(7), Article e024292. https://doi.org/10.1136/bmjopen-2018-024292
Tzeng W. C., Lin C. F., Lin L. Y., Lu M. S., Chiang L. C. (2017). Development and testing of the Taiwanese hospital nurses' job satisfaction scale. The Journal of Nursing, 64(2), 44–54. https://doi.org/10.6224/JN.000023 (Original work published in Chinese)
Wang L., Tao H., Bowers B. J., Brown R., Zhang Y. (2017). Influence of social support and self-efficacy on resilience of early career registered nurses. Western Journal of Nursing Research, 40(5), 648–664. https://doi.org/10.1177/0193945916685712
Wang S., Liu Y., Wang L. (2015). Nurse burnout: Personal and environmental factors as predictors. International Journal of Nursing Practice, 21(1), 78–86. https://doi.org/10.1111/ijn.12216
World Health Organization. (2016). Global strategic directions for strengthening nursing and midwifery 2016–2020. https://www.who.int/hrh/nursing_midwifery/global-strategic-midwifery 2016-2020.pdf
Wu Y., Wang J., Liu J., Zheng J., Liu K., Baggs J. G., Liu X., You L. (2020). The impact of work environment on workplace violence, burnout and work attitudes for hospital nurses: A structural equation modelling analysis. Journal of Nursing Management, 28(3), 495–503. https://doi.org/10.1111/jonm.12947
Yestiana Y., Kurniati T., Hidayat A. A. A. (2019). Predictors of burnout in nurses working in inpatient rooms at a public hospital in Indonesia. The Pan African Medical Journal, 33, Article 148. https://doi.org/10.11604/pamj.2019.33.148.18872
Zhao H., Jiang J. (2021). Role stress, emotional exhaustion, and knowledge hiding: The joint moderating effects of network centrality and structural holes. Current Psychology, 2021, 1–13. https://doi.org/10.1007/s12144-021-01348-9
Keywords:

nurses' burnout; work satisfaction; working condition flexibility

Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc.