Impact of leadership on ICU clinician's burnout
ABSTRACT
Introduction: Global spreads of burnout among healthcare practitioners, particularly
within intensive care units (ICUs), has been described as a growing crisis with a
variety of unwanted consequences as drawbacks (1).
Aim of the work: Our primary objective was to explore the prevalence of burnout in
this area among different healthcare givers; we also focused on identifying the
contributing factors as well as the role of empowerment and leadership impact.
Methodology: We employed a cross-sectional descriptive study with purposive
sampling. A combined methodological approach (quantitative and qualitative) was
used with questionnaires. We used five instrument: Conditions of work effectiveness
scale (CWES), Work stress scale
(WSS), Maslasch Burnout scale (MBI-HSS),
Leadership scale (LS), and Empowerment scale (ES).
Results: We studied 200 healthcare practitioners within medical and surgical ICUs.
The case study that focused on Qatari intensive care confirmed a high prevalence of
burnout (25.5%), where physicians, nurses, and respiratory therapists were equally at
risk (p=0.19). Younger individuals were more likely to burn out (p=0.000). We report
a high association of burnout with the instruments that we used. Both positive
leadership and empowerment had a negative effect on burnout variance (12.4 and
3.8%, respectively) when considering practitioner burnout.
Conclusion: The reported high burnout rate among practitioners in ICU settings
necessitates special attention in terms of positive leadership attitudes; empowerment
could serve as an ameliorating factor.
Key words: burnout, ICU, practitioners
Introduction
Care of critically ill patients recognized as highly demanding and challenging
profession, it requires extensive effort and communication between the staff during
which professionals are exposed to variable degrees of work-related stress. Pressures
related from financial demands as well as diagnostic, monitoring and therapeutic
techniques put extra burden on intensive care unit (ICU) staff.
According to Miller, et al., (1990 existence of stress and burnout in the workplace
as well as related outlay affect many variable levels in the community. The ICU is
one of the front lines in dealing with health care related crisis that could place the
providers on variable degrees of psychological stress [1]. Staffing in ICU involved
multiple specialties (physicians, nurses, respiratory therapists, and clinical
pharmacists), and dealing with these diversified practitioners is a difficult task that
needs knowledge, skills and proper communication [2].
In an attempt for ICU leaders to get higher performance, burnout problem needs
to be looked at with special attention as prophylaxis is better than treatment in
medicine and it seems that having burnout oriented field with tools for the early
management seems to be attractive goal. It is reasonable that leader empowerment of
the staff could have a positive impact on the overall progress, execution and
engagement at work.
Burnout could be presented with irritability, insomnia, feeding problems and
depressive attitude as well as increased leave requests among staff. Low performance
at workplace and high resigning intentions could be attributed to emotional
exhaustion. Job satisfaction depends on work and organization; the former is related
to workload, social backup, and autonomy while the latter is related to authority and
decision-making. Individual characters, work conditions as overload, feeling of
valueless job, and disputes predispose to burnout [3].
Linkage between emotional stress and burnout exist as expressed in a study
conducted in UK physicians, higher stress associates higher emotional exhaustion.
Emotional tiredness, depersonalization, and reduced personal and professional
achievements characterized the burnout. The high association in healthcare may result
2
from daily management of complex, stressful situations and intense interpersonal
relations [4]. The decision-making could involve conditions of life and death as well
as withdrawing and withholding life supportive measures. Staff retention is another
risk factor. Nurses are more exposed to burnout than physicians, at least one-third
experienced severe burnout syndrome symptoms at certain time. Burnout could be
attributed to conflicts at workplace between practitioners and younger age of the
practitioners is more susceptible [5].
According to Aiken, et al., (2002) different forms of leadership may be required
through professional career development, however complexity in the leadership and
burnout relation exists. Protection against the depersonalization could be attributed to
transformational leadership [6]. Stress released from the physical and social factors
as well as vagueness of roles, but leadership management could significantly lead to
increased emotional exhaustion levels. [7].
Leader-empowering
attitude
significantly
enhanced
staff
approach
to
empowerment structures that is linked with reduction of the encountered job tension
and enhancement of work effectiveness [8]. Nurses working with sounding leaders
got significantly lower levels of emotional exhaustion and associated stress, and they
got also preferable communication with physicians, superior satisfaction with their
leaders and their jobs, which reflected on improvement of patient care demands than
did nurses working for discordant leaders [9].
Empowerment as a factor in burnout, that latter affects attraction and retention of
the experienced health care staff. Positive work environments rely heavily on the
leaders who heavily influence medical staff performance and response to working
conditions as well as the quality of care supplied to the customers. Empowerment
techniques seem to offer the staff more satisfaction as sharing in decision making,
enhancing the work value, facilitating target achievements, trusting high execution,
and releasing bureaucratic boundaries to have more autonomy. Leader empowering
attitude involved adequate control in terms of clear roles and responsibilities,
3
adequate reward system, fairness and conformity between organization and
employee's needs [10].
Empowerment is hypothesized to improve nurses and patients capabilities to
convey their requirements that could manage their lives [11].
Wise & Billi (1995)
mentioned that implementing, work support methodology should involve clinical
leaders to carry the organizational or the governmental messages through endorsing
and adopting guidelines in the regional or local circumstances [12].
Objectives of the study
This study predominates at investigating the burnout problem which is poorly
estimated in health care; the author aim at the present study the prevalence of burnout
within the intensive care settings in a particular institution, and whether the leadership
attitude could increase or ameliorate the problem. As well the effect of participant
empowerment on ameliorating this condition will be considered.
Methodology
Settings
This study conducted in two intensive care units (ICU), in a tertiary hospital in the
Middle East. The number of beds in each ICU was 20 and 12 respectively.
The
participants were screened for socio-demographic data such as age, gender, profession,
marital state, education, native country, years of experience, weekly working hours and
salary. The questionnaire were clarified to the potential respondents in order to clear any
poor understanding. English used as the official language in the organization; translation of
the used instruments to individual mother languages is not required.
Design
Cross-sectional descriptive survey with purposeful sampling. Mixed qualitative and
quantitative methodology used in this dissertation. Invitations to participate through the
corporate mail, anonymous questionnaire survey were presented to the staff members
including physicians, nurses and respiratory therapists who work as full time.
Instrumentation
4
The used instrumentation is questionnaire that is divided into the following sections:
A) Condition of work effectiveness questionnaire (CWEQ): This scale consisted of 19
items developed by Kanter, (1977) measured by a 5 point Likert type response [13].
B) Occupational stress scale (WSS): A three-point scale was used in which low stress = 1,
moderate stress = 2, and extreme stress = 3. The total number of declaration in the scale
will be 15 [14]. C) Maslach Burnout Inventory human services survey (MBI-HSS): The
scale is a standardized instrument to measure burnout it utilize 9 items related to emotional
exhaustion and it is most frequently used in health care researches, the nine items are
calculated to get the whole score, scores of 27 and more signaled high burnout [15]. The
percentage of high degree of burnout was used for advanced analysis. We got permission
to use this scale from (Mindgarden.com, USA). D) Psychological Empowerment Scale
(ES): A 12 items scale considering work meaning, efficiency, autonomy, and impact
(Spreitzer, 1995). Each of the preceding four components is measured by three items
through 7 point Likert scale ranging from very strong disagreement (1 point) to very
strong agreement (7 points). Calculating the total 12 items to get the total Psychological
Empowerment score. [16].E) Leadership Behaviours scale (LS): The staff discernment of
managers’ leadership attitude were measured using the 11 item Manager Action Scale.
[17].
The questionnaires were submitted in English form; no need for translation, as health
care practitioners in the organization, must practice English that is the official language at
workplace. The results of the analysis will be presented using descriptive methods. The
quantitative and qualitative data will be analyzed statistically, the relations between the
variables will be interpreted, the relation between burnout score and socio-demographic
variables, occupational stress score, and empowerment scale will be assessed statistically
using (t-test, analysis of variance, correlation efficient and regression).
Ethical Considerations:
Participant identity kept confidential, final report would not contain any identity.
Comprehensive explanation for the participants about the questionnaires, the type, purpose
of the study and outcome was done, early rejection, or late withdrawal was permissive.
Ethical approval was obtained according to the corporate regulations. The ethical consent
5
attached after being approved from university of Liverpool and medical research center.
IRB Approval 14281/14 by HMC research center.
Data Collection Procedures
The purpose of the study was explained to the managing directors in the hospitals.
Clarifying the study to managers of the units after initial hospital authorization was
procured. The questioners (appendix A) were driven through the corporate mail to the
respondents. Survey-Monkey was used to deliver the questioners and to receive the
responses. The questioners composed of 5 sections (Appendix A).
Statistical analysis
Data were presented as mean ± SD for quantitative data and frequency and proportion
for qualitative data. Median and range were calculated for non-normal continuous
distributed data. Statistical significance tests included: For quantitative data, the student's ttests and Mann-Whitney U tests (if data is not non-normally distributed); and Chi-square
tests for categorical variables. A P-value of <0.05 (two tailed) was considered the
statistical significant level. Multivariate regression analysis performed for significant data
in a univariate analysis, both within group agreement (rwg) and interclass correlation
(ICC) assessed. Individual data could not be aggregated to the level of the group if rwg
median equal or was less than 0.7. Variability between the groups should be higher that
variability within groups (James, Demaree, & Wolf, 1984). Clinical and laboratory data
was entered into a database (Microsoft Excel 2013, Redmond, WA, USA) and statistical
analyses performed (SPSS Inc., Version 21. Chicago IL, USA).
Results
Descriptive Statistics
The participant's background initially determined all were health care practitioners
highly educated. Then the contents were transferred to statements. The validity was
established through face validity where questionnaires intention of measurement was
addressed, making sure it represent the contents, appropriate for the studied
population, and appearance of the instrument look like a questionnaire [18]. A pilot
test including 20 subjects who not enrolled in study sample was tested to check the
reliability of the questionnaires, the collected data were analyzed by SPSS [18].
Missing Data
6
The missing data managed statistically; it comprised less than 6% for all scales and
most in demographic variables. The “highest degree” was the main missing variable
in the demographics ad it was missing 4% of the time.” No specific missing pattern
identified after examination with t-test and Chi-square.
Questionnaires were distributed to 390 health care practitioners including
physicians, nurses and respiratory therapists working on two inpatient medical and
surgical intensive care units. Two hundred practitioners completed and returned the
questionnaires, for a 51.8% response rate. The response rates for all participating units
reached 200 participants, which was the desired target. The mean ageSD of the
participants was 36.36.7, the rest of the demographic characteristics were shown in
(table 1)
Validity and reliability of the questionnaires
The validity of the five used instruments demonstrated in previous literatures.
However, the design of the survey included a blend of the instruments for which
validity needed to confirmation. Reliability is tested by Cronbach’s alpha and ICC.
Adequate ICC is .72 but .8 is preferred denoting high-reliability level. The mean rwg
(in group agreement) was 0.827 denoting adequate intergroup aggregation above ICC
was .60 and the rwg was .70, the instrument was considered to be in composition
form [19].
Individual data distribution
The distribution of individual data for the MBI-HSS used instrument was examined
to and found to have normally distribution (Figure 1) accordingly parametric statistics
were suitable.
Statistical test of hypothesis
The prevalence of burnout in ICU staff is high in our study, we found that 51
respondents (25.5%) suffered a high degree of burnout, while 29 respondent (14.5%)
suffered moderate degree of burnout The only significant relation was encountered
with the gender distribution (table 3).
7
The relation between Maslach burnout score for human social services and the rest
of the other used instruments was studied using Pearson correlation (table 4). We
found significant correlation with age (p=0.000), CWES (p=0.008), WSC (p=0.000),
ES (p=0.006), and LS (p=0.000) by 2-tailed test. Linear regression was attempted to
draw relation between burnout measured by MBI and work condition subscale (table
5), where significant predictors for burnout accordingly were item 1 (challenging
work) p=0.001, item 14 (seeking out ideas from professionals other than physicians)
p=0.029, and item 6 (goals of management) p= 0.033. The r2 for this model was 0.309
thus work related conditions account for 37.9% of the variation in burnout. Linear
regression was attempted to draw relation between burnout measured by MBS and
leadership subscale, where no significant predictors for burnout among the subscale.
Next the leadership influence on high burnout was studied with linear path analysis
with burnout measured by MBI as an outcome variable and leadership as a predictor
variable. The path coefficient was .35 (p<.001). The result was statistically
significant, however, r2 was .124, indicating that leadership accounted for only 12.4%
of variance in practitioners burnout (figure 2)
Linear regression was attempted to draw relation between MBS and empowerment
subscale (table 7), where significant predictors for burnout accordingly were item 4
(My impact on what happens in my department is large) p=0.004, and item 2 (The
work that I do is important to me) p=0.048. Next the empowerment influence on high
burnout was studied with linear path analysis with burnout as an outcome variable and
empowerment as a predictor variable. . The path coefficient was .35 (p<.006). The
result was statistically significant, however, r2 was .038, indicating that leadership
accounted for only 3.8% of variance in practitioners burnout (figure 3).
Discussion
The salient findings of this study are: high prevalence of burnout found in the
Qatari ICU settings and it is below the international levels. Respiratory therapists
similarly got burnout as the rest of the critical care practitioners. Higher burnout
found in males according to our results. We noted involvement of Syrian nationality
more with high burnout and more burnout in medical ICU. We observed higher level
of burnout in the younger age population.
8
Strong relations between the used instruments and high burnout including work
condition, work stress, leadership and empowerment scales were found in our work.
Among the condition at work items challenging work, and goals of management were
strong burnout predictors among the work conditions scale. Positive leadership
attitude had the negative effect on high burnout, where leadership accounted for only
12.4% of the variance in practitioner's burnout.
Burnout term is a psychological one associated with reduction of the work interest
in certain situations after experiencing long-term exhaustion. Lack of recover after
disbursing too much effort in work could be the striking. Healthcare practitioners are
vulnerable to burnout, especially in areas with more stress [20]. The ICU pattern of
work could typically lead to burnout which is reflected on health care practitioners
well-being and work performance. Retention of the caregivers could be affected to a
greater extent and leaders in health care organizations suffer from a shortage in ICU
staff that threatens the given services [21].
Poncet et al. (2007) reported high
association of burnout symptoms in ICU staff; where up to 45% of the practitioners
got burnout symptoms that vary from insomnia, to irritability up to the blown full
picture of depression [22].
This aim of this study was to discover prevalence of burnout within the ICU in Qatar,
find the precipitating demographics and working conditions for burnout, and to
explore the influence of leadership as well as empowerment on burnout.
Two hundred participants were involved in this study, where questionnaires were
distributed to 390 health care practitioners including physicians, nurses and
respiratory therapists form two ICUs (table 1).
Demographics
We found that 51 respondents (25.5%) suffered a high degree of burnout with
higher association in physicians (table 3). In a multicenter study conducted in France
Embriaco, et al., (2007) reported high level of burnout in more than have of the
physicians and one third of the nurses working in ICUs suffered the same phenomena
[20]. Respiratory therapists suffer the same stressors as other health care practitioners
but only few studies addressed the association of burnout in this group [23].
9
Guntupalli et al., (2014) reported 25% severe burnout in respiratory therapist in USA
[24]. Similarly Shelledy, et al., (1992) went through stress in ICU professionals, and
find that this group suffered burnout as the rest of the ICU staff where leader
recognition of these factors is needed for enhancing retention [25].
Few studies went through healthcare burnout in the Middle East [26, 27] but no
studies went through in Qatari ICU settings where practitioners are vulnerable to
stressors. All respondents in our study were non-Qatari practitioners. Similarly in
Saudi Arabia study that share similar demographics with the rest of the Gulf countries
most of the nursing workforce is from other countries that enhance the work related
stress [26]. Close to Qatar in an Egyptian cross-sectional survey targeting physician
burnout, the authors find that 62.2% of their studied population suffered experienced
emotional exhaustion, 56.1% had depersonalization, and 58.2% got reduced
individual capacity. Egypt got different demographics from the Gulf group where
lacks of job support and salary dissatisfaction were the strongest predictors in this
study [27]. Abdulla, Al-Qahtani & Al-Kuwari (2011), studied burnout in Qatar but in
general health practitioners. The authors found level of high burnout about 12.5% that
was below the international level, however Qatari physicians suffered the high
incidence of burnout syndrome than other population in same study [28].
In our study males got higher burnout than females (table 3). Embriaco, et al.,
(2007a) found high level in ICU women [20], similarly Abdulla, Al-Qahtani & AlKuwari (2011), found higher burnout in female primary physicians [28]. Variable
level of high burnout reported in the diverse population and different population. We
encountered higher level of burnout in physicians (35.4%) followed by respiratory
therapists (25%) followed by nurses (19%).
The Syrians suffered the highest burnout percentage (table 4). The influence
related to specific nationality could differ the evolvement of burnout Al-Turki et al.,
(2010) found that non-Saudi nurses were significantly more susceptible to emotional
10
exhaustion (27.3 ± 12.1 versus 21.6 ± 2.9) than Saudi nurses [26]. Syrians suffer from
civil war since 3 years which could add to the faced stressors.
High burnout was more in younger age groups 25-34 than older groups. People
who got lower years of professional experience (less than five years) experienced
high degree of burnout (57.1%) than professionals with more years of experience
(table 3). High degree of burnout had high significant relation p=0.000 with the lower
age group by Pearson relation (table 4). This was similar to the results of Abdulla, AlQahtani & Al-Kuwari (2011) who find higher burnout in younger professionals [28].
Age less than 30 years was in a multicenter European study was significantly
associated with high burnout [21]. But on the other hand the study of Koivula,
Paunonen & Laippala, (2000) indicated that burnout increases with age [29].
High burnout was equally distributed in participants with variable years of
experience within the same organization 25% each in our study. However, Koivula,
Paunonen & Laippala, (2000) reported lower level of burnout in practitioners with
shorter work experience [29]. Furthermore in a more recent study managerial
situation and years of experience did not impact burnout [30], this was concomitant to
findings of Merlani, et al., (2011), where years of experience in ICU did not affect the
burnout association [21].
Participants with higher level of had higher burnout than those with lower level of
education but it did not reach statistical significance. Koivula, Paunonen & Laippala,
(2000), reported experience of high burnout level in participants with a secondary
education level laboring on psychiatric wards. The authors also found that continuous
professional education could ameliorate the burnout level [29]. Similarly Zaghloul &
El Enein, (2009), found that higher educational level suffered more burnout among
practitioners. Perhaps the demands and social support is higher in the later group [31].
Unmarried participants in our study were more involved in higher burnout than the
married one. This was consistent with findings of Keane, Ducette & Adler (1985), but
11
the authors were able to identify significantly high burnout in unmarried nurses [32].
No major differences encountered in our study related to satisfaction with the salary
where high burnout with more in unsatisfied than satisfied participants (57% versus
48.5%). Houkes, et al., (2001) emphasized that low salary lower employees
satisfaction [33].
The last contrast was related to working unit we found that participants who work
in medical ICU are more involved in high burnout than who work in surgical ICU
(30.2% versus 18.5%). Guntupalli et al., (2014) also found higher percentage of
burnout in medical ICU when compared with the surgical. In our settings this could
be explained by higher workload and more difficult to manage patients [24]. The only
significant relation was encountered with the gender distribution (Table 3).
High burnout relations with other score
The Pearson correlation between Maslach burnout score for human social services
and the rest of the other used instruments contained in (Table 4).
We found
significant correlation with age, CWEQ, WSC, ES, and LS by 2-tailed test.
In our study lower score of CWEQ, was significantly associated with increase
burnout, and this was statistically significant . Consequently, working conditions that
allow data access, and resources as well as formal and informal empowerment could
guard against the development of burnout syndrome. Kinzl, et al., (2005) mentioned
that control over work conditions had a positive impact on practitioner's satisfaction
[34]. However, in our study work condition were not the only influential factors for
burnout. This was proportionate with finding of Lederer, et al., (2006) who indicated
that job conditions and work environment contribute more than personality structure
in the development of burnout [35]. Great importance had been attributed to changing
of the work conditions in ameliorating burnout which act better than behavioral
prevention in terms of advocating healthy behavior of the individual [36].
To identify the predictors for burnout among the condition at work linear
regression was done between burnout measured by MBI and condition at work
12
effectiveness (table 5), where significant predictors for burnout accordingly were item
1 (challenging work), item 14 (seeking out ideas from professionals other than
physicians), and item 6 (goals of management). Work related conditions account for
37.9% of the variation in burnout. According to Houkes, et al., (2001) it is possible to
predict the outcome of stress and burnout when work conditions and characteristics
are recognized [33]. On the other hand, challenging work assignments could be
associated with the higher workload [37]. Physician burnout was studied by
Gundersen, (2001) who confirmed that characters of the work that make it
challenging as autonomy, social contacts and skill variation influence intrinsic work
motivation. Emotional exhaustion could evolve with aspects of work demands, loss of
social support [38].
The second instrument used in our study was the WSS. According to. In our study
high burnout was significantly related to work stress scale. Zaghloul (2008), found
that privacy inadequacy, shortage of staff, excess workload, fluctuation in workload,
patient difficult to manage are the high initiating factors in this scale [14]. Zaghloul
& El Enein (2009), found that health care practitioners suffered from stress exposure
regardless of the organizational and hierarchical structure. Stress reduction and
resources coping should be undertaken to reduce burnout. Job security and
occupational health education seems to do better in this context [31].
According to Zaghloul (2008), the basic element for staff burnout is the workload
which eventually could lead to increasing turnover. The used scale could be
convenient as it is short reliable and could be used as a valuable tool for managers
[14].
A statistical significant relation was found between leadership and burnout by tvalue for a Pearson correlation (table 4). The growing demands for decisions and
actions in health care on robust evidence basis require promoting the staff autonomy
seems to be a perfect goal. Al-Hamdan et al., (2013) mentioned that leaders decisions
and organizational pursuit based on scientific evidence. Leadership scale looks to be
usable to the Jordanian settings [17].
13
Linear regression was attempted to draw relation between burnout measured by
MBS and leadership subscale, where no significant predictors for burnout among the
subscale (Table 6). Encouraging practitioner through certain action that promote
autonomy was a high predictor for reducing burnout in Al-Hamdan et al., (2013)
study [17]. Delegating 24-hours responsibility in decision-making in variable
situations was noted. This was also similar to the report of Abdullah & Shaw (2007)
who concluded that better outcome could be achieved with participative decisionmaking especially when practitioners got involved in capital planning which in turn
enhance the given autonomy [39]. Also there is no identical study summarized the
effect of leadership on burnout in different health care practitioners, Greco et al.,
(2006) found that leaders’ behaviors had an indirect effect on lowering emotional
exhaustion and possible burnout [40].
Next the leadership influence on high burnout was studied with linear path analysis
with burnout measured by MBI as an outcome variable and leadership as a predictor
variable which statistically significant. However, r2 was .124, indicating that
leadership accounted for only 12.4% of the variance in practitioners burnout (figure
2). Leaders perceived by the followers as the prominent individuals in the
organizational environments. The practice of leaders makes a difference in the
occurrence of burnout and got implications as well in its prevention (Stordeur,
D'hoore & Vandenberghe, 2001). Close to our results is the multivariate analyses
done by the authors, they found that more variation in emotional exhaustion is more
likely to be explained by work stressors than with dimensions of leadership (22% vs.
9%). Work stressors identified were physical environments, social environments and
role obscurity. [41]
Empowerment had been defined as intrinsic task motivation in the work stings, so
empowering symbolized by energizing, where tasks are basic targets, external
circumstances and subjective interpretation (Thomas and Velthouse, 1990). Here is
existing worldwide utilization of empowerment with variable tools and strategies
[42].
14
In a landmark study in health care was done by Laschinger et al., (2003) who
tested the work empowerment predictive power for burnout in nurses [8]. They found
direct empowerment effect on emotional exhaustion. In our study, we did linear path
analysis with burnout as an outcome variable and empowerment as a predictor
variable. We got significant relation where path coefficient was .35 (p<.006).
However, r2 was .038, indicating that leadership accounted for only 3.8% of variance
in practitioner's burnout (figure 3). Multiple achievements had been reported due to
empowerment including decreased work Fewer manifestations of burnout and
reduced leave days stress (Wåhlin,
Ek
& Idvall, 2010) [43], enhanced work
satisfaction and commitment at work area (Kuokkanen, Leino-Kilpi & Katajisto,
2003)[44] and efficiency (Laschinger et al., 2001) [45].
Linear regression was attempted to draw relation between MBS and empowerment
subscale (Table 7), to find the significant predictors for burnout, we found statistical
relation with item 4 (My impact on what happens in my department is large) , and
item 2 (The work that I do is important to me). Greco, Laschinger & Wong (2006),
noted that strategies to enhance involvement and decrease burnout are essential
improving work environments [40]. The later needed to be pushed by the leaders,
which is reflected on the quality of care. Laschinger et al. (1999) concluded that
empowering attitude by the leaders like boosting the work meaning, decision making
involvement, smooth target achievements, providing autonomy, hasten bureaucratic
boundaries and expressing confidence in high performance were associated with
increased feelings of empowerment by practitioners in critical care settings [9].
Our results were similar to Kuokkanen, Leino-Kilpi & Katajisto, (2003) who found
that strengthening and empowering ICU staff could be raised when there is feeling of
doing something good suggesting the possible benefit from overwhelming prevention
on basis of support and enabling good leadership [44].
Study limitation
15
A limitation of this study is a single center, done only in a single country. The number
is relatively limited. A survey covering different organizations within the same
territory or different countries could yield a better outcome.
Conclusion: The reported high burnout rate among practitioners in ICU settings
necessitates special attention in terms of positive leadership attitudes; empowerment
could serve as an ameliorating factor. Further studies are required to countenance our
findings in the same region and individual groups.
List of abbreviations
CWEQ: Condition of work effectiveness questionnaire;
ES: Psychological Empowerment Scale;
ICU: intensive care unit;
LS: Leadership Behaviours scale: LS;
MBI-HSS: Maslach Burnout Inventory human services survey;
WSS: Occupational stress scale:
Recommendation for future research:
Key messages:
1) Prevalence of high burnout in Qatari ICUs.
2) Work empowerment could be utilized in this context.
3) High burnout relation with the leadership, empowerment, and work
conditions,
4) Specific managerial action could ameliorate the resulting burnout.
References
1) Miller KI, Ellis BH, Zook EG & Lyles JS. An integrated model of communication,
stress, and burnout in the workplace. Communic Res. 1990; 17(3), 300-326.
16
2) Saini R, Kaur S & Das K. Assessment of stress and burnout among intensive care
nurses at a tertiary care hospital. J Men Health Hum Beh. 2011; 16(1), 43-48.
3) Myhren, H., Ekeberg, Ø., & Stokland, O. Job satisfaction and burnout among
intensive care unit nurses and physicians. Crit Care Res Prac. 2013; 2013: 786176.
4) McManus IC, Winder BC & Gordon D. The causal links between stress and burnout
in a longitudinal study of UK doctors. Lancet 2002; 359(9323), 2089-2090.
5) Teixeira C, Ribeiro O, Fonseca AM & Carvalho AS. Burnout in intensive care units-a
consideration of the possible prevalence and frequency of new risk factors: a
descriptive correlational multicentre study. BMC Anesthesiol. 2013; 13(1), 38.
6) Aiken LH, Clarke SP, Sloane DM, Sochalski JA, Busse R, Clarke H & Shamian J.
Nurses’ reports on hospital care in five countries. Health affairs. 2001; 20(3), 43-53.
7) Stordeur S, D'hoore W & Vandenberghe C. Leadership, organizational stress, and
emotional exhaustion among hospital nursing staff. J Adv Nurs. 2001; 35(4), 533542.
8) Laschinger HKS, Wong C, McMahon L & Kaufmann C. Leader behavior impact on
staff nurse empowerment, job tension, and work effectiveness’. J Nurs Adm.1999;
29(5), 28-39.
9) Cummings G, Hayduk L & Estabrooks C. Mitigating the impact of hospital
restructuring on nurses: the responsibility of emotionally intelligent leadership. Nurs
Res. 2005; 54(1), 2-12.
10) Greco, P., Laschinger, H. K. S., & Wong, C. (2006). 'Leader empowering
behaviours, staff nurse empowerment and work engagement/burnout'. Nursing
Leadership, 19(4), 41-56 [Online].
11) Gibson CH. A concept analysis of empowerment. J Adv Nurs. 1991; 16(3), 354-361.
12) Wise CG & Billi JE. A model for practice guideline adaptation and implementation:
empowerment of the physician. Jt Comm J Qual Improv. 1995; 21(9), 465-476.
13) Kanter RM. Men and women of the corporation. A Division of Harper Collins
Publishers.1977;5049
14) Zaghloul AA. Developing and validating a tool to assess nurse stress’. The J
Egypt Public Health Assoc.2007; 83(3-4), 223-237.
15) Maslach C, Jackson SE & Leiter MP. Maslach Burnout Inventory Manual. Palo Alto,
California. 1996; 3rd Ed
16) Spreitzer, G. M. (1995). ‘Psychological empowerment in the workplace:
Dimensions, measurement, and validation’. Academy of manage
Journal,38(5), 1442-1465 [Online].
17) Al-Hamdan Z, Bawadi H, Bawadi H & Mrayyan MT. Nurse Managers’ Actions
(NMAs) Scale to Promote Nurses’ Autonomy: Testing a New Research Instrument.
Int J Humanities Soc Sci. 2013; 3(8), 271-278
18) Radhakrishna RB. Tips for developing and testing questionnaires/instruments. J
Exten. 2007; 45(1), 1-4.
19) Klein KJ & Kozlowski SW. Multilevel theory, research, and methods in
organizations: Foundations, extensions, and new directions. Jossey-Bass; 2000.
20) Embriaco N, Azoulay E, Barrau K, Kentish N, Pochard F, Loundou A & Papazian L.
High level of burnout in intensivists: prevalence and associated factors. Am J Resp
Crit Care Med. 2007; 175(7), 686-692.
21) Merlani P, Verdon M, Businger A, Domenighetti G, Pargger H & Ricou B. Burnout
in ICU caregivers: a multicenter study of factors associated to centers. Am J Resp Crit
Care Med. 2011; 184(10), 1140-1146.
22) Poncet MC, Toullic P, Papazian L, Kentish-Barnes N, Timsit JF, Pochard F &
Azoulay E. Burnout syndrome in critical care nursing. Am J Resp Crit Care
Med.2007; 175(7), 698-704 [Online].
23) Hoffman LA, Happ MB, Scharfenberg C, DiVirgilio-Thomas D & Tasota FJ.
Perceptions of physicians, nurses, and respiratory therapists about the role of
acute care nurse practitioners. Am J Crit Care 2004; 13(6), 480-488 [Online].
17
24) Guntupalli KK, Wachtel S, Mallampalli A & Surani S. Burnout in the intensive care
unit professionals. Indian J Crit Care Med. 2014; 18(3), 139 [Online].
25) Shelledy DC, Mikles SP, May DF & Youtsey JW. Analysis of job satisfaction,
burnout, and intent of respiratory care practitioners to leave the field or the
job. Resp Care. 1992; 37(1), 46-60.
26) Al-Turki HA, Al-Turki RA, Al-Dardas HA, Al-Gazal MR, Al-Maghrabi GH, AlEnizi NH & Ghareeb BA. Burnout syndrome among multinational nurses working in
Saudi Arabia. Ann Afr Med. 2010; 9(4).
27) Shams T & El-Masry R. Job Stress and Burnout among Academic Career
Anaesthesiologists at an Egyptian University Hospital’. Sultan Qaboos Univ Med J.
2013; 13(2), 287.
28) Abdulla L, Al-Qahtani DM & Al-Kuwari MG. Prevalence and determinants of
burnout syndrome among primary healthcare physicians in Qatar. South Afr Fam
Prac. 2011; 53(4), 380-383.
29) Koivula M, Paunonen M & Laippala P. Burnout among nursing staff in two Finnish
hospitals. J Nurs Manage. 2000; 8(3), 149-158 .
30) Ilhan MN, Durukan E, Taner E, Maral, I & Bumin MA. Burnout and its correlates
among nursing staff: questionnaire survey. J Adv Nurs. 2008; 61(1), 100-106.
31) Zaghloul AA & El Enein NYA. Nurse stress at two different organizational settings
in Alexandria. J Multidiscip Healthc.2009; 2, 45.
32) Keane A, Ducette J & Adler DC. Stress in ICU and non-ICU nurses. Nurs Res
1985; 34(4), 231-236 [Online].
33) Houkes I, Janssen PP, de Jonge J & Nijhuis FJ. Specific relationships between work
characteristics and intrinsic work motivation, burnout and turnover intention: A
multi-sample analysis. Europ J Work Organiz Psychol. 2001; 10(1), 1-23.
34) Kinzl JF, Knotzer H, Traweger C, Lederer W, Heidegger T & Benzer A.
Influence of working conditions on job satisfaction in anaesthetists’. Br J
Anaesth. 2005; 94(2).
35) Lederer W, Kinzl JF, Trefalt E, Traweger C & Benzer A. Significance of working
conditions on burnout in anesthetists. Acta Anaesthesiol Scand. 2006; 50(1), 58-63.
36) Ramirez AJ, Graham J, Richards MA, Gregory WM & Cull A. Mental health of
hospital consultants: the effects of stress and satisfaction at work. Lancet.
1996; 347(9003), 724-728.
37) Janssen PP, De Jonge J & Bakker AB. Specific determinants of intrinsic work
motivation, burnout and turnover intentions: a study among nurses. J Adv Nurs.
1999; 29(6), 1360-1369.
38) Gundersen L. Physician burnout. Ann Intern Med. 2001; 135(2), 145-148.
39) Abdullah MT & Shaw J. A review of the experience of hospital autonomy in
Pakistan. Int J Health Plann Manage. 2007; 22(1), 45-62 [Online].
40) Greco P, Laschinger HKS & Wong C. Leader empowering behaviours, staff
nurse empowerment and work engagement/burnout. Nurs Leadersh
2006; 19(4), 41-56.
41) Stordeur S, D'hoore W & Vandenberghe C. Leadership, organizational stress, and
emotional exhaustion among hospital nursing staff. J Adv Nurs. 2001; 35(4), 533542.
42) Thomas KW & Velthouse BA. Cognitive elements of empowerment: An
“interpretive” model of intrinsic task motivation. Academy Manage Rev. 1990; 15(4),
666-681.
43) Wåhlin I, Ek AC & Idvall E. Staff empowerment in intensive care: nurses’ and
physicians’ lived experiences. Intensive Crit Care Nurs. 2010; 26(5), 262-269.
44) Kuokkanen L, Leino-Kilpi H & Katajisto J. Nurse empowerment, job-related
satisfaction, and organizational commitment. J Nurs Care Qual. 2003; 18(3), 184192.
18
45) Laschinger H.K.S., Finegan J., Shamian J. & Wilk P. (Impact of structural and
psychological empowerment on job strain in nursing work settings’. J Nurs Adm.
2001; 31, 260–272.
19
Variable (s)
Age
Gender
Marriage
Years in profession
Years in the hospital
Years in the unit
Working unit
Highest education
Profession
Salary Satisfaction
Description
Range
26
Minimum-Maximum
25-51
Mean SD
36.36.7
Female
109 (54.5)
Male
89 (45.5)
Married
144 (72.5)
Unmarried
55 (27.5)
Range
24
Minimum-Maximum
1-25
Mean SD
10.516.2
Range
14
Minimum-Maximum
1-15
Mean SD
4.36.6
Range
13
Minimum-Maximum
1-14
Mean SD
2.83.2
Medical
106 (53)
Surgical
65 (32)
Both
26 (13)
Diploma
48 (24)
Bachelorette
97 (48.5)
Master or higher
49 (24.5)
Physician
65 (32.5)
Nurse
96 (48)
Respiratory therapist
28 (14)
Strongly agree
6 (3)
Agree
29 (14.5)
Neither agree or disagree
77 (38.5)
20
Disagree
80 (40)
Strongly disagree
6 (3)
Table 1. Demographic variables among the studied group
Reliability
Validity
Cronbach’s alpha ICC Rwg
CWES
.815 to .828
.83
0.61
WSS
704 to .785
.756 0.608
MBI-HSS 849 to .905
.899 1.57
LS
879 to .907
.881 .979
ES
815 to .896
.879 1.014
Table 2) Reliability and validity and r of the used instruments
Adequate ICC is .72 but .8 is preferred denoting high-reliability level. The mean rwg (in group
agreement) was 0.827 denoting adequate intergroup aggregation
Based on the criteria, if the
ICC was .60 and the rwg was .70, the instrument was considered to be in composition
form. (Klein & Kozlowski, 2000)
21
High Burnout
Moderate
burnout
Mild or no
burnout
Pvalue
0.229
Number (%)
Age (years)
25-34
18 (25.4)
14 (19.7)
39 (54.9)
35-44
31 (26.7)
15 (12.9)
70 (60.3)
45-54
2 (15.4)
0
11 (84.6)
Less than 5 years
8 (57.1)
2 (14.3)
4 (28.6)
5-10 years
28 (25.2)
17 (15.3)
66 (59.5)
11-15
9 (18.4)
8 (16.3)
32 (65.3)
More than 15
6 (23.1)
2 (7.7)
18 (69.2)
Less than 5 years
41 (25.5)
23 (14.3)
97 (60.2)
More than 5 years
10 (25.6)
6 (15.4)
23 (59)
Less than 3 years
34 (22.8)
25 (16.8)
90 (60.4)
More than 3 years
16 (32.7)
4 (8.2)
29 (59.2)
0.193
Female
22 (20)
21 (19.1)
67 (60.9)
0.049
Male
28 (31.5)
8 (9)
53 (59.6)
Married
34 (23.6)
19 (13.2)
91 (63.2)
Unmarried
17 (30.9)
9 (16.4)
29 (52.7)
Egyptian
8 (28.6)
5 (17.9)
15 (53.6)
Indian
13 (16.2)
12 (15)
55 (68.8)
Philippine
14 (26.9)
7 (13.5)
31 (59.6)
Syrian
7 (43.8)
1 (6.2)
8 (50)
Years of profession
0.107
Years within organization
0.983
Years within unit
Gender
Marital state
0.4
Nationality
0.29
22
Others
9 (37.5)
4 (16.7)
11 (45.8)
Baccalaureate degree
28 (28.9)
16 (16.5)
53 (54.6)
Diploma
8 (16.7)
9 (18.8)
31 (64.6)
Master
14 (28.6)
4 (8.2)
31 (63.3)
Medical CCU
32 (30.2)
16 (15.1)
58 (54.7)
Surgical CT-ICU
12 (18.5)
10 (15.4)
43 (66.2)
Both
5 (19.2)
2 (7.7)
19 (73.1)
Physician
23 (35.4)
8 (12.3)
34 (52.3)
Nurse
19 (19.8)
15 (15.6)
62 (64.6)
Respiratory therapist
7 (25)
2 (7.1)
19 (67.9)
Agree
17 (48.5)
5 (14.2)
13 (37.1)
Neither agree or disagree
23 (29.8)
11 (14.2)
43 (55.8)
Disagree
58 (57)
13 (15.1)
15 (17.4)
Highest education level
0.289
Working unit
0.277
Profession
0.191
Salary satisfaction
0.46
Table 3. Burnout distribution among the studied group
23
Variable
MBS
Sig. (2-tailed)
Age
Pearson Correlation
-.466**
.000
CWES
Pearson Correlation
-.186**
.008
WSS
Pearson Correlation
.469**
.000
ES
Pearson Correlation
-.196**
.006
LS
Pearson Correlation
-.353**
.000
*. Correlation is significant at the 0.01 level (2-tailed)..
Table 4. Burnout relation to the other scores and age.
24
Standardized
t
Sig.
95.0% Confidence Interval for B
Coefficients
Beta
Lower Bound
Upper Bound
stress1
.270
3.335
.001
2.306
9.040
stress2
.009
.121
.904
-2.790
3.153
stress3
-.005
-.051
.959
-3.240
3.076
sresss4
.159
1.814
.072
-.268
6.133
stress5
-.103
-1.182
.240
-5.765
1.455
stress6
.194
2.159
.033
.282
6.497
stress7
-.020
-.223
.824
-3.404
2.716
stress8
.089
.958
.340
-1.750
5.032
stress9
-.001
-.014
.989
-3.970
3.915
stress10
.063
.618
.538
-2.560
4.883
stress11
.179
1.951
.053
-.051
7.144
stress12
-.048
-.595
.553
-3.404
1.831
stress13
-.174
-1.974
.051
-6.370
.008
stress14
.194
2.211
.029
.325
5.895
Table 5. Relation between work condition subscales and burnout
25
Standardized
t
Sig.
95.0% Confidence Interval for B
Coefficients
Beta
Lower Bound
(Constant)
Upper Bound
8.768
.000
30.567
48.336
leader1
.013
.141
.888
-2.447
2.823
leader2
-.138
-1.325
.187
-4.965
.977
leader3
-.005
-.047
.962
-2.290
2.183
leader4
-.020
-.184
.854
-3.270
2.711
leader5
-.147
-1.242
.216
-4.977
1.133
leader6
.014
.132
.895
-2.649
3.030
leader7
-.068
-.514
.608
-4.173
2.450
leader8
-.130
-.963
.337
-4.914
1.692
leader9
-.046
-.441
.660
-3.238
2.055
leader10
.001
.014
.989
-1.979
2.007
Table 6. Relation between leadership subscales and burnout
26
Standardized
t
Sig.
95.0% Confidence Interval for B
Coefficients
Beta
Lower Bound
(Constant)
Upper Bound
4.942
.000
17.803
41.548
emp1
-.268
-1.743
.084
-6.874
.433
emp2
.305
1.837
.048
-.265
7.197
emp3
.257
1.806
.073
-.210
4.643
emp4
-.455
-2.951
.004
-6.690
-1.322
emp5
.108
.912
.363
-1.049
2.845
emp6
-.087
-.743
.459
-3.124
1.417
emp7
.009
.069
.945
-2.513
2.696
emp8
-.193
-1.672
.097
-3.771
.316
emp9
-.072
-.668
.505
-2.443
1.209
emp10
-.103
-.941
.348
-2.806
.997
emp11
.134
1.114
.267
-.806
2.885
emp12
.076
.589
.557
-1.446
2.674
Table 7. Relation between empowerment subscales and burnout
27
Figure 1. Distribution of Scores for the Maslash Burnout Scale
28
Figure 2. linear relation between MBI and leadership scale (predicting burnout
through leadership)
29
Figure 3. Linear relation between MBI and empowerment scale (predicting burnout
through empowerment)
30