Volume 5, No. 11 November, 2024
p
ISSN 2723-6927-e ISSN 2723-4339
Job Demands and Job Resources as
Antecedents of Work Engagement Among Inpatient Nurse in X Hospital
Quintina Paramina1,
Rokiah Kusumapradja2, Intan Silviana Mustikawati3
Study Program of Hospital Administration
University of Esa Unggul, Jakarta123
Email: qparamina@student.esaunggul.ac.id1, rokiah.kusumapradja@esaunggul.ac.id2, intansilviana@esaunggul.ac.id3
ABSTRACT
Work engagement within hospitals may be impacted by job demands and job
stress, underscoring the necessity to augment work resources as a protective
measure. Initial investigations conducted at Hospital X have revealed a
deficiency in work engagement, particularly in the absorption aspect. This
study seeks to assess the effects of job demands and job resources on work
engagement, with job stress serving as a mediating factor. Employing a quantitative
survey methodology with a cross-sectional design, the study involved 104
inpatient nurses as participants. The method used is the Three Box Method and
statistical analysis. The findings indicate that work engagement escalates with
increased job resources, while higher job demands correlate with decreased work
engagement. Furthermore, enhancing job resources has the potential to alleviate
job stress, whereas elevated job demands are associated with heightened job
stress levels. Notably, work engagement diminishes with escalating job stress.
Through the mediation of job stress, job resources, and job demands, there is a
discernible impact on work engagement.
Keywords: Job Demands, Job Resources, Job Stress, Work Engagement.
Introduction
The quality of service in a hospital hinges not only on competent
human resources but also on a profound emotional connection to the organization
and work, commonly referred to as work engagement. Work engagement is
influenced by factors such as job demands and resources (Leiter & Bakker, 2010). According to the Job Demands- Job Resources Model, high job
demands coupled with low job/positive resources lead to increased stress and
burnout (Leiter & Bakker, 2010).
Data from multiple studies indicates that in Indonesia, only 15.4%
of employees feel a sense of attachment to their work, while 76.5% do not, and
the remaining 10.3% are unhappy at work (Gallup et al., 2017). Findings from a
study conducted at a hospital in Bandung revealed that 36.7% of nurses fell
into the high work engagement category, with the remaining 63.3% categorized as
having low work engagement (Syafira, 2017).
Preliminary research at RS revealed that 46% of respondents felt
less supported by work resources, lacked skills to improve and develop
abilities, had limited participation in decision-making, and encountered poor
relationships with co- workers leading to miscommunication. Additionally, 59%
reported experiencing job stress, including fatigue, sleepiness, lack of
concentration, and feelings of worry while working. Building on this
foundation, the study was conducted to analyze the impact of job demands and resources
on work engagement, with job stress as a mediating factor, among nursing staff
at X Hospital.
Research Methods
The research methodology employed in this study is quantitative
research utilizing a Field Research approach. The study conducted is a cross-sectional
study. The research variables consist of two independent variables (X),
Knowledge of Job Demands (X1) and Job Resources (X2), one dependent variable
(Y), Work Engagement (Y), and one mediating variable (Z), Job Stress (Z). The
dimensions of job demands include high job pressure and emotional conditions
related to work, while job resources encompass physical and social aspects.
Work engagement is measured through the dimensions of enthusiasm, dedication,
and absorption. Job stress, the mediating variable, is characterized by
physical, psychological, and behavioral dimensions. The research model is
illustrated in Figure 1, outlining the relationships among the variables. Based
on this model, the research hypotheses are formulated as follows:
H1: There is a notable
relationship between job demands, job resources, engagement, and job stress as
an intervening factor for nurses at X Hospital.
H2: There is a notable
relationship between job demands, job resources, and job stress on nurses' work
engagement at X Hospital concurrently.
H3: There is a notable correlation
between job demands and nurses' job stress at X Hospital.
H4: There is a notable correlation
between job resources and nurses' job stress at X Hospital.
H5: There is a notable correlation
between job demands and nurses' work engagement at X Hospital.
H6: There is a notable correlation
between job resources and nurses' work engagement at X Hospital.
H7: There is a notable correlation
between job stress and the work commitment of nurses at X Hospital.
The sample size was determined using a saturated sampling
technique, encompassing all inpatient nurses at RS. As recommended by (Hair Jr et al., 2014), a minimum sample size of 100 is advised for estimating SEM
parameters in this panel research. Data collection utilized a Likert scoring
system questionnaire distributed via a Google form to respondents.
Subsequently, respondent data underwent tabulation and analysis employing the
three box method for descriptive data and SEM analysis to test hypotheses.
Ethical approval for this research was obtained from the Esa Unggul University
Code of Ethics Enforcement Council, Research Ethics Commission under the reference
number: 0924-06.022/ DPKE- KEP/ FINAL-EA/ UEU/ VI/ 2024.
Figure 1. Research Configuration
Results and Discussion
Respondent demographic information is presented in table 1, while
descriptive findings of respondents in relation to the research variables are
displayed in table 2.
Descriptive analysis utilizing the three-box method indicates that
job demands and job resources fall into the high category, whereas job stress
and work engagement are classified as medium. Consequently, all three factors
have not fully optimized nurses' work engagement.
SEM Analysis (Structural Equation
Modeling)
This study employs Structural Equation Modeling (SEM) analysis
with the assistance of SMART-PLS software to address research inquiries. In
SEM-PLS® (Partial Least Squares), it comprises two measurement models: the
outer model and the inner model.
Table 1. Respondents' Characteristics
|
Characteristics of Respondents |
Frequency |
Precentage |
|
|
Gender |
Male |
12 |
11.54% |
|
Female |
92 |
88.46% |
|
|
Age |
< 25 Years Old |
7 |
6.7% |
|
25 – 30 YearsOld |
53 |
50.96% |
|
|
31 – 35 Years Old |
33 |
31.73% |
|
|
> 35 Years Old |
11 |
10.58% |
|
|
Latest Education |
D3 |
15 |
14.42% |
|
S1 |
89 |
85.58% |
|
|
Duration flabor |
< 1 Years |
7 |
6.73% |
|
1 – 2 Years |
32 |
30.77% |
|
|
2 – 3 Years |
44 |
42.31% |
|
|
3 – 4 Years |
10 |
9.62% |
|
|
> 4 Years |
11 |
10.58% |
|
|
Jumlah |
104 |
100% |
|
Source: Data derived from surveys (2024)
The analysis of respondent characteristics presented in Table 4.1
reveals a predominance of female respondents, totaling 92, compared to 12 male
respondents. Additionally, the majority of respondents fall within the 25-30
age range, with 53 individuals, and specifically, 26-30 years old, accounting
for 33 respondents. Furthermore, respondents with a bachelor's degree
constitute the largest group at 89 individuals. The majority of respondents
have work experience ranging from 2 to 3 years, with 44 participants, closely
followed by those with 1 to 2 years of experience, totaling 32 respondents.
Table 2. Research Variable Matrix
|
Variable |
Respondent's Response Position |
Behavior |
||
|
Low |
Moderate |
High |
||
|
Job Demands |
|
|
✔ |
Demand |
|
Job Resources |
|
|
✔ |
Optimal |
|
Job Stress |
|
✔ |
|
Exhausted |
|
Work Engagement |
|
✔ |
|
Indifferent |
Source: Data derived from surveys (2024)
Outer Model Test
The criteria for evaluating the outer model include validity tests
encompassing convergent and discriminant validity, as well as a reliability
test based on the Composite Reliability value.
Subsequently, multicollinearity is assessed to facilitate hypothesis testing.
The results of the outer model test are depicted in Figure 2. The findings
indicate loading factor values exceeding 0.70 and AVE values surpassing 0.5,
confirming the validity and homogeneity of all indicator items in the study.
Furthermore, in the reliability assessment, both the Composite Reliability and
Cronbach's Alpha values exceeded 0.7, affirming the reliability and consistency
of all questionnaire indicators in measuring variables.
Figure 2 displays the outer
model of the PLS Research Model Algorithm.
Processed Results from SmartPLS Version 3.3 (2024)
Figure 3. Research Model for
Bootstrapping Internal Model
Processed Results from SmartPLS Version 3.3 (2024)
Inner Model Test
Evaluation of the structural model or inner model seeks to establish the
connection between constructs, significance value, R- square (R2), Q-square
predictive relevance (Q2), and f-square effect size (f2) within a research
model. The assessment of the structural model involves R-square for the
dependent variable and the path coefficient value for the independent variable.
The analysis of the structural model in this research employed the
bootstrapping method in SmartPLS version 3.3, with a
significance level of 0.05. The examination of the inner model is illustrated
in Figure 3.
The R-Square value pertaining to work engagement is 0.926, indicating
that job demands, job resources, and job stress can collectively account for
92.6% of the variance in work engagement, with the remaining 7.4% attributed to
other variables not included in the study. Additionally, the R-Square value for
job stress is 0.938, demonstrating that job demands and job resources can
explain 93.8% of the variance in job stress, leaving 6.2% to be explained by
external variables not considered in this research.
To obtain the Q2 value, you can compute the following:
Q2 = 1 – (1 – R1) (1 – R2)
Q2 = 1 – (1 – 0.926) (1 – 0.938)
Q2 = 1 – (0.074) (0.062)
Q2 = 1 – 0.004588
Q2 = 0.9954
Based on the Q2 results, which are close to 1, it can be inferred that
the model already exhibits a strong predictive relevance. Additionally, the
F-Square calculations indicate that the impact of job demands on work
engagement falls within the weak category, with values ranging from 0.02 to 0.14.
Conversely, the impact of job demands on job stress is classified as strong,
with an f- square value exceeding 0.35. Similarly, the effect of job resources
on work engagement is categorized as weak, with f-square values ranging from
0.02 to 0.14, while the influence of job resources on job stress is considered
strong, with a value surpassing
0.35. The impact of job stress on work engagement is also deemed weak,
with an f- square value ranging from 0.02 to 0.14.
Table 3. Estimated Path
Coefficients and Statistical Tests
|
|
Original Sample (O) |
T Statistics (|O/STD EV|) |
P Values |
Hipotesis |
|
Job Stress
-> Work Engagement |
-0.299 |
2.283 |
0.023 |
Accepted |
|
Job Resources -> Work Engagement |
0.306 |
2.707 |
0.007 |
Accepted |
|
Job Resources -> Job Stress |
-0.485 |
6.439 |
0 |
Accepted |
|
Job Demands -> Work Engagement |
-0.327 |
3.381 |
0.001 |
Accepted |
|
Job Demands -> Job Stress |
0.433 |
5.626 |
0 |
Accepted |
|
Job Resources ->
Job Stress-> Work
Engagement |
0.145 |
2.06 |
0.04 |
Accepted |
|
Job Demands -> Job Stress-> Work Engagement |
-0.13 |
2.105 |
0.036 |
Accepted |
The subsequent phase involves hypothesis testing using the
estimated path coefficients and T-Statistics values displayed in table 3.
According to the hypothesis testing results in table 3, it can be demonstrated
that:
1. Hypothesis 1: The impact of job demands and
job resources on engagement and job stress as an intervening variable for
inpatient nurses at Hospital X has been accepted. An indirect relationship
exists between job resources and job demands concerning work engagement through
job stress, supported by p-values below 0.05 and t- statistics exceeding 1.96.
Conclusions drawn from the three-box method and research findings indicate that
hospital inpatient nurses experience a negative correlation between job stress
and job demands with work engagement, a negative correlation between job
demands and job resources, and a positive correlation between job resources and
work engagement. Consistent with theoretical frameworks by (Leiter & Bakker, 2010) and Robbins (2012), along with research by Emilisa et al. (2020)
and Meijman et al. (2007), it is evident that job stress can mediate the impact
of job demands and job resources on work engagement.
2. Hypothesis
2: The impact of job demands, job resources, and job stress on the work
engagement of inpatient nurses at Hospital X concurrently: accepted.
There is a significant relationship among job demands, job
resources, and job stress on work engagement, as indicated by the r square
value nearing 1. Conclusions drawn from the three-box method and research
findings reveal that inpatient nurses at Hospital X face high job demands, high
job resources, and medium job stress levels. This situation impacts nurses'
work engagement, which remains at a medium level, reflecting the
interconnectedness of these variables. High job demands and abundant job resources,
coupled with escalating job stress, lead to decreased work engagement.
According to (Schaufeli et al., 2009), high job demands and insufficient resources can result in
fatigue and diminished work engagement. Conversely, ample job resources,
regardless of high or low job demands, foster heightened motivation and
engagement. Studies by (Oshio et al., 2018) and (Inoue et al., 2013) support the notion that work engagement correlates with job
demands and resources, aligning with the JD-R model's theoretical framework.
Work engagement acts as a moderator in the relationship between specific job
demands, resources, and psychological distress.
3. Hypothesis
3: The impact of job demands on the job stress of inpatient nurses at Hospital
X has been accepted. There is a significant relationship between job demands
and job stress, supported by p-values below 0.05 and t-statistics exceeding
1.96. The findings are derived from the three-box method, indicating that
inpatient nurses at Hospital experience notable work demands. The correlation between
variables reveals that job stress and job demands align positively, meaning
higher job demands lead to increased job stress among nurses. Meijman et al.
(2007) highlight that job demands act as stressors when employees exert high
effort without adequate recovery. (Bakker & Demerouti, 2007) suggest a reciprocal relationship between work demands and
burnout. (Van den Broeck et al., 2017) note that the service and health sectors exhibit the highest
workload, while the industrial and public sectors have lower workloads.
4. Hypothesis 4:
The impact of job resources on the job stress of inpatient nurses at Hospital X
has been accepted. There is a significant relationship between Job Resources
and Job Stress, supported byp-values below 0.05 and t- statistics above 1.96.
The job resources of inpatient nurses at hospitals show a direct correlation
between job stress and job demands. Increasing job resources is crucial to
mitigate the impact of high job demands, as they have been proven to alleviate turnover intention and work fatigue.
Workload and emotional demands positively contribute to burnout, while all job
resources are linked to increased work engagement and decreased burnout. Social
support acts as a buffer in the relationship between workload and burnout.
5. Hypothesis 5 regarding the
impact of job demands on the work engagement of inpatient nurses at Hospital X
has been accepted. A notable correlation between work demands and work
engagement has been established, supported by p-values below 0.05 and t- statistics
exceeding 1.96. Through the three box method and research findings, it is
evident that the work demands of inpatient nurses at Hospital X fall within the
medium category. This relationship underscores an inverse connection between
job demands and work engagement, indicating that heightened job demands lead to
decreased work engagement among nurses. These outcomes align with Ahmed's
(2017) research, which highlighted a significant negative effect of emotional
demands on work engagement. The study affirms the detrimental impact of job
demands, such as workload and emotional stress, on employees' well-being at
work, consequently diminishing work engagement. According to Van den Broeck et
al. (2010), while workload can be viewed as demanding, it has the potential to
enhance work engagement, particularly when paired with high skill levels.
6. Hypothesis
6 regarding the impact of job resources on the work engagement of inpatient
nurses at Hospital X has been accepted.
A notable relationship exists between job resources and work
engagement, supported by p-values below 0.05 and t- statistics exceeding 1.96.
The job resources of inpatient nurses at Hospital In hospitals show a positive
correlation with work engagement, indicating that increased job resources lead
to higher work engagement levels among nurses.
The outcomes align with (Bakker & Demerouti, 2007) work engagement theory, which suggests that job resources
influence work engagement. (Patience et al., 2020) similarly found that job demands (emotional demands) and job
resources (meaningful work and career advancement) are expected to enhance
nurses' work engagement in public hospitals. Meaningful work, as a job resource,
was the primary factor affecting work engagement among public and private
nurses. Leader-member exchange boosts work engagement among private sector
nurses. Meaningful work emerges as a professional asset for enhancing work
engagement among nurses in public and private healthcare facilities.
7. Hypothesis
7 regarding the impact of job stress on the work engagement of inpatient nurses
at Hospital X has been accepted.
A significant relationship exists
between job stress and work engagement, supported by p-values below 0.05 and t-
statistics exceeding 1.96. Findings from the three-box method and research
indicate that inpatient nurses at Hospital So do not achieve optimal work
engagement due to their job stress, reflected in the medium- level work
engagement variable index category. The analysis reveals an inverse correlation
between job stress and work engagement, indicating that higher job stress leads
to lower work engagement among nurses.
The findings align with prior
research carried out by (Rothmann, 2008), specifically regarding the facets of job satisfaction (ranging
from pleasure to displeasure), job stress (ranging from anxiety to comfort),
fatigue (ranging from tiredness to enthusiasm), and engagement (ranging from
enthusiasm to depression) being interconnected. Coetzee et al. (2010) noted
that the origin of job stress is significantly associated with the extent of
employee work engagement.
Based on the research findings, the primary influential variable
is job resources impacting job stress, exhibiting a negative correlation. In
essence, higher job resources correspond to lower job stress levels. The
secondary influential variable is the relationship between job demands and job
stress, showing a positive correlation. This indicates that increased job
demands result in higher job stress levels experienced by inpatient nurses.
Additionally, job stress negatively affects work engagement, with higher job
stress leading to lower work engagement.
Conclusion
The research findings indicate that job
demands and job resources have an impact on work engagement among inpatient
nurses at Hospital job stress, with job stress serving as a mediating factor.
Recommendations and implications for hospitals include:
a. To reduce
high work demands, an evaluation of the assignment system (division of tasks,
division of energy, work schedule and rest hours) is needed regarding employee
work demands so that employees can concentrate fully while working.
b. To increase
work resources, a conducive work environment is needed, superiors who can
communicate well, care about obstacles felt by employees, provide limits on
authority, provide feedback on employee performance and can be an example and
motivation for employees. The hospital can also hold regular meetings with each
division, to carry out evaluations and receive input from employees in order to
improve the work system.
c. To reduce
work stress, regular health checks are needed for employees, both physical and
psychological/counseling (complaints related to psychological conditions). So
if there are employees who experience stress or illness due to work, early
treatment can be carried out to prevent complications or worsening conditions
that will affect work engagement.
d. To increase
work engagement, you can provide appreciation for every effort made by
employees, provide education or training related to work engagement for
employees so that patient service runs better. Gathering/outing activities can
also be held to strengthen employee cooperation, or invite special motivators
to increase employee work motivation. Questionnaires related to work engagement
are also given to all employees and surveys need to be conducted regarding
assessments of hospital management and what employees expect, so that employee
aspirations are conveyed.
REFERENCE
Bakker,
A. B., & Demerouti, E. (2007). The job demands‐resources model: State
of the art. Journal of Managerial Psychology, 22(3), 309–328.
https://doi.org/doi.org/10.1108/02683940710
Hair Jr, J. F., Sarstedt, M., Hopkins, L., &
Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling
(PLS-SEM): An emerging tool in business research. European Business Review.
Inoue, A., Kawakami, N., Tsuno, K., Shimazu, A.,
Tomioka, K., & Nakanishi, M. (2013). Job demands, job resources, and work
engagement of Japanese employees: a prospective cohort study. International
Archives of Occupational and Environmental Health, 86, 441–449.
Leiter, M. P., & Bakker, A. B. (2010). Work
engagement: introduction. Work Engagement: A Handbook of Essential Theory
and Research, 1(9). https://doi.org/doi.org/10.4324/97802038530 47
Oshio, T., Inoue, A., & Tsutsumi, A. (2018).
Associations among job demands and resources, work engagement, and
psychological distress: fixed-effects model analysis in Japan. Journal of
Occupational Health, 60(3), 254–262.
Patience, M. G., De Braine, R., & Dhanpat, N.
(2020). Job demands, job resources, and work engagement among South African
nurses. Journal of Psychology in Africa, 30(5), 408–416.
https://doi.org/10.1080/14330237.2020.1821315
Rothmann, S. (2008). Job satisfaction, occupational
stress, burnout and work engagement as components of work-related wellbeing. SA
Journal of Industrial Psychology, 34(3), 11–16.
https://doi.org/10.4102/sajip.v34i3.424
Schaufeli, W. B., Bakker, A. B., & Van Rhenen, W.
(2009). How changes in job demands and resources predict burnout, work
engagement, and sickness absenteeism. Journal of Organizational Behavior:
The International Journal of Industrial, Occupational and Organizational
Psychology and Behavior, 30(7), 893–917.
https://doi.org/doi.org/10.1002/job.595
Van den Broeck, A., Vander Elst, T., Baillien, E.,
Sercu, M., Schouteden, M., De Witte, H., & Godderis, L. (2017). Job
demands, job resources, burnout, work engagement, and their relationships: an
analysis across sectors. Journal of Occupational and Environmental Medicine,
59(4), 369–376.
LePine, J. A., & Rich, B. L. (2010). Linking job demands and resources to employee engagement and
burnout: A theoretical extension and meta-analytic test. Journal of Applied Psychology,
95(5), 834–848. https://doi.org/10.1037/a0019364
Fiabane, E., Giorgi, I., Sguazzin, C., & Argentero, P. (2013). Work engagement
and occupational stress in nurses and other healthcare workers: the role of
organisational and personal factors. Journal of clinical nursing, 22(17-18),
2614–2624. https://doi.org/10.1111/jocn.12084 Galanakis MD and Tsitouri E. (2022). Positive psychology in the
working environment. Job demands-resources theory, work engagement and burnout:
A systematic literature review. Front. Psychol. 13:1022102. doi:
10.3389/fpsyg.2022.1022102
Hakanen, Jari & Demerouti, Evangelia & Xanthopoulou, Despoina.
(2007). Job Resources Boost Work Engagement, Particularly When Job Demands Are
High. Journal of Educational Psychology. 99. 10.1037/0022-0663.99.2.274.
Helmi, A., Widhiarso, W., Marvianto, R., Priwati, A., Mustari, M., &
Artikasari, Y. (2020). The Fourth Dimensions of the Job Demands- Resources
(JD-R) Model of Work Engagement in Indonesian Context. Jurnal Psikologi, 47(3),
206-219. doi:https://doi.org/10.22146/jpsi.5668 2
Karatepe, Osman & Yavas, Ugur & Babakus, Emin & Deitz, George.
(2018). The effects of organizational and personal resources on stress,
engagement, and job outcomes. International Journal of Hospitality Management.
74.147-161. 10.1016/j.ijhm.2018.04.005.
K. J. Preacher and G. J.
Leonardelli, “Calculation for the Sobel Test: An Interactive Calculation Tool for
Mediation Tests [Online software],” 2010. http://quantpsy.org/sobel/sobel.htm
Macdonald, Wendy. (2003). The Impact of Job Demands and Workload on Stress
and Fatigue. Australian Psychologist - AUST PSYCHOL. 38. 102-117.
10.1080/00050060310001707107.
Mauno S., Kinnunen U., Ruokolainen M. (2007). Job demands and resources as
antecedents of work engagement: A longitudinal study. Journal of Vocational
Behavior. 70(1). 149-171.
Mazzetti, G., Robledo, E., Vignoli, M., Topa, G., Guglielmi, D., &
Schaufeli, W. B. (2023). Work Engagement: A meta- Analysis Using the Job
Demands- Resources Model. Psychological Reports, 126(3), 1069-1107.https://doi.org/10.1177/003329412110
51988
Mercia Gerida Patience , Roslyn De Braine & Nelesh Dhanpat (2020). Job
demands, job resources, and work engagement among South African nurses, Journal
of Psychology in Africa, 30:5, 408-416, DOI: 10.1080/14330237.2020.1821315
Nickum, M., & Desrumaux, P. (2023). Burnout among lawyers: effects of
workload, latitude and mediation via engagement and over-engagement.
Psychiatry, Psychology and Law, 30(3), 349-361.
Padula, R. S., Chiavegato, L. D., Cabral, C. M., Almeid, T., Ortiz, T.,
& Carregaro, R. L. (2012). Is occupational stress associated with work
engagement?. Work (Reading, Mass.), 41 Suppl 1, 2963–2965.https://doi.org/10.3233/WOR-2012-0
549-2963 Pulido-Martos, M., Cortés-Denia, D., Luque- Reca, O. et al. (2023). Authentic
leadership and personal and job
demands/resources: A person-centered approach and links with work-related
subjective well- being. Curr Psychol 42, 28994–29011.https://doi.org/10.1007/s12144-022-0
3938-7
Qureshi, Muhammad Asif & Ahmed, Umair & Shah, Muzaffar &
Siddiqui, Benazir & Samad, Dahri. (2017). Troubling Job Demands at Work:
Examining the Deleterious Impact of Workload and Emotional Demands on Work
Engagement. International Journal of Academic Research in Business and Social
Sciences. 7. 96-106. 10.6007/IJARBSS/v7 i6/2949.
Sonnentag, Sabine & Mojza, Eva & Demerouti, Evangelia. (2012). Reciprocal
Relations Between Recovery and Work Engagement: The Moderating Role of Job
Stressors. The Journal of applied psychology. 97. 842-53. 10.1037/a0028292.
Tooren, Marieke & Rutte, Christel. (2015). Explaining Emotional
Exhaustion and Work Engagement: The Role of Job Demands-Resources and Type D
Personality. International Journal of Stress Management. 23. 10.1037/a0039754.
Weinberg, A., & Creed, F. (2000). Stress and psychiatric disorder in
healthcare professionals and hospital staff. Lancet (London, England),
355(9203), 533–537. https://doi.org/10.1016/S0140-6736(9
9)07366-3
Yudhaputri N., Dewi I., Lunarindiah G. (2020). The Impact of Job Demands
and Job Resources to Work Engagement and Job Stress Mediated by Job Crafting: A
Study from Event Organizer’s Employees. International Journal of Advanced
Science and Technology, 29(05), 558-566
Zhang, M., Zhang, P., Liu, Y., Wang, H., Hu, K., & Du, M. (2021).
Influence of perceived stress and workload on work engagement in
front‐line nurses during COVID‐19 pandemic. Journal of clinical
nursing, 30(11-12), 1584-1595.
|
Quintina Paramina1,
Rokiah Kusumapradja2, Intan Silviana Mustikawati3 (2024) |
|
First Publication Right: Journal of Health Science |
|
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