Introduction disorder in the Diagnostic and Statistical Manual

Introduction

Burnout
is a psychological term for the experience of long-term exhaustion and
diminished interest. Despite this, burnout is not a recognized disorder in the
Diagnostic and Statistical Manual of Mental Disorders (1).
It was first described in the mid-1970s by Freudenberg and ever since it has
been the subject of many studies (2).
Burnout focuses on specific stressors in the workplace and the environmental
pressures affecting the health of employed people (3).
Healthcare workers, particularly physicians, are exposed to high levels of
distress at work. Persistent tension can lead to exhaustion, psychological,
and/or physical distress. Moreover, burnout syndrome may increase the risk of
medical errors and decrease job satisfaction, which incites early retirement (4).

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Burnout
has three interrelated dimensions: emotional exhaustion (EE), depersonalization
(DP), and low personal accomplishment (PA). Prolonged exposure to stress is
usually the main cause of emotional exhaustion and it manifests through the
loss of enthusiasm for work, feeling helpless, trapped, and defeated. Depersonalization
occurs when physicians treat patients indifferently, objectify them, and
develop a negative attitude toward their colleagues and profession.
Inefficiency, or the lack of a sense of personal achievement, is characterized
by the individual’s withdrawal from responsibilities and detachment from the
job (5).

The
level of burnout among physicians varies in different studies conducted in
different regions of the world. One study conducted described high level of
burnout among physicians by reporting 46% to 80% of physicians with moderate to
high levels of emotional exhaustion, 22% to 93% of them with moderate to high
levels of depersonalization and 16% to 79% of them with moderate to low level
of personal achievement (6).

Burnout
is an increasing problem among medical staff and is highly prevalent in
health-care settings. It is associated with difficult working conditions and
feelings of dissatisfaction with work (7).
The modern medical workplace is a complex environment, and physicians’
responses to it vary greatly. Some find it stimulating and exciting, whereas
others become stressed and burned out from their heavy workload. Several
personal, interpersonal and organizational factors have been reported to be
related to job satisfaction, stress and burnout in the medical environment (8-10).

Study
from developed countries showed that severe burnout syndrome was presented in
25% – 70% of physicians (11).
For instance, burnout within a Canadian-based intensive care unit was ranged
from 36% – 65%, with the highest level of burnout among intensive care
physicians (12).
Another study reported that close to half of the intensive care physicians
wished to quit their jobs (13).
Another study carried in Egypt showed that 39.7% high, 37.7% average and 22.6%
low emotional exhaustion; 22.6% high, 45.6% average and 31.8% low
depersonalization; 0.8 %  average  and 99.2% 
low level of personal accomplishment (14).

In
African countries, burnout studies are scarce and most have only been developed
in the last decade. The debilitation of health systems due to the human
resources crisis has provoked a heavy and complex workload in health care’s and
substantial workforce burnout. Study conducted in Malawi reported that burnout
level among maternal health staff at a referral hospital; 72% emotional
exhaustion, 43% depersonalization and 74% low level of personal accomplishment (15).
Developing countries had a higher burden of disease and fewer health
professionals than the developed countries. For example, the ratio of nurses:
doctors ranges from nearly 8:1 in the African Region to 1.5:1 in the West (16).
In Ethiopia, there were health workforce densities particularly physicians that
showed 0.027 per 1000 population (17).

As
far as the researcher investigated, there is no similar study conducted in
Ethiopia on burnout level and its associated factors among physicians. In
addition, Ethiopian physician number is not comparable with patient volume so
that the physicians in the work become over stressed. This was evidenced that
the number of physicians in Ethiopia was estimated to be 1 544. This implies a
physician to population ratio of 1:42 706 in Ethiopia and 1: 74
161 in SNNPRS but the World Health Organization (WHO) minimum standard was 1:10
000 (18).
Thus, this study designed to address the problems by assessing the burnout
level and its associated factors among physicians in public hospitals of
Southern Nations, Nationalities and Peoples’ Regional State (SNNPRS) in which
case the findings of  this  study will 
help  health  care 
institutions; particularly hospitals to recognize  factors 
related to  burnout in medical
staff  and help  them to take corrective measures  in 
attempt  to improve the health
status of their employees.

Methods and Materials

Study Setting and
Sampling

This study was carried out from
March 13 to April 11, 2017 in all primary, general and specialized public
hospitals of SNNPRS. Administratively the Region is divided into 14 zones, 1
City Administration zone and 4 special woredas. According to Central Statistical
Agency (CSA) 2007 census, the regional total population was 14929548 ( male
49.7% and female 50.3%) (2). Currently there are 40 (8 general
and 32 primary) hospitals reporting to health bureau of the region and 6
specialized/teaching hospitals in the region (3).
Institutional based
cross sectional study design was employed to investigate burnout among
physicians in public hospitals of Southern Nations, Nationalities and Peoples’
Regional State (SNNPRS), Ethiopia and all physicians (491) who were working in
all public hospitals of the region during data collection period were included
in the study.  

Data collection and measurements

Structured
questionnaires were adopted from English version  of 
Maslach’s  Burnout  Inventory-Human  Services 
Survey  (MBI-HSS)  to collect data on levels  of 
burnout among physicians. It comprised of  22 
items  regrouped  into 
3  subscales:  emotional 
exhaustion  (EE;  nine 
items), depersonalization (DP; five items), and personal accomplishment
(PA; eight items). Each item was answered on a 7-point likert scale ranging
from “never” (=0) to “daily” (=6). Each aspect of the burnout syndrome was
measured and scored separately. Thus 
a  high  score 
on  emotional  exhaustion 
and  depersonalization,  and 
a  low  score  on  personal accomplishment was reflected as a
high level of burnout. A low level of burnout was considered as equivalent to a
low score on emotional exhaustion and depersonalization, and a high score on
personal accomplishment (19).
Instruments were prepared in English language. Participants were  asked to provide information  with 
regard  to  their 
age, sex, marital status, educational level, area of work and years of
experience, duty hours, recognition from others regarding work, professional
training, smoking, chat chew,  work
overload,  monthly income, conflict with
colleagues, and  intention  to 
leave  work  within 
next six months.

Data Analysis

Data
was checked manually for completeness and consistency. Collected data were
compiled, cleaned, coded and entered into Epi Data version 3.1
software and SPSS version 21 was used for statistical data analysis. Errors, missing values and outliers
were checked and treated accordingly. Factor analysis based on principal
component extraction followed by varimax rotation was used within the adopted
22-item scale. Three factors were obtained, with eigenvalues of 4.94, 3.02, and
2.46. The total variance explained was 50.0%. The three factors identified, in
order of percentage variance explained, represented by emotional exhaustion
dimension (23.6%), depersonalization (14.4%), and personal accomplishment (12%)
and the final scale consisted of 21 items. Internal consistency of the
measurement scale was investigated through Cronbach’s alpha coefficient and was found to be 0.720 for emotional exhaustion, 0.846 for depersonalization
dimension and 0.701 for personal accomplishment. Presence of statistical
association between independent and dependent variables was observed by
bivariate analysis and candidate variables with P-value < 0.25 was included into multiple linear regression analysis. Multivariate linear regression analysis was done through enter method to identify the most significant predictors. Assumptions in multiple linear regressions (linearity, normality, and constant variance) were checked. Significant independent predictors were declared at 95% confidence interval and P-value of less than 0.05 and unstandardized ? was used for interpretation. Result Four hundred ninety one participants were involved in the study with 100 % response rate. More than two third (70.9% & 67.6%) of study participants were male and single respectively. Majority (86.6%) of the respondents were general practitioners (Table 1). As to work related characteristics of the respondents, close to one third 142(28.9%) and half, 215(43.8%) were working in medical department and specialized/teaching hospitals respectively. The mean professional work experience and mean working hours per month was found to be 1.92 years and 120.65 hours respectively. Regarding interpersonal conflict about half (48.7%) of study participants experienced conflict with their colleagues (Table 2). Regarding burnout level of study participants, 320(65.2%) scored high degree of emotional exhaustion, 418(85.1%) scored high degree of personalization and 447(91%) experienced low levels of personal accomplishment (Table 3). Bivariate Linear Regression Analysis Bivariate analysis was conducted to identify candidate variables for multiple linear regression analysis at p < 0.25. Accordingly age (p-value = 0.001), monthly salary (p= 0.229), number of patients observed per week (p=0.001), sleeping hours in working day (p=0.108), average working hours per week (p=0.003), having any support from family and or organization (p=0.002), professional training (p=0.011) and receiving recognition from others regarding work (p=0.009) were found to be candidates variable. Multi Variable Linear Regression Analysis In the multivariate model, receiving recognition from others regarding work (? = -0.05, 95%CI = -0.09, -0.01), monthly salary (? = -0.01, 95%CI= 0.01-0.02) and age (? = -0.01, 95%CI: -0.01, -0.01) were negatively associated with emotional exhaustion score. Whereas number of patients observed per week (?= 0.01, 95%CI= 0.001, 0.01) was positively associated with emotional exhaustion score. Multicollinearity was checked and the variance inflation factor (VIF) for all variables found to be < 10 and the tolerance > 0.2 (Table 4).

Discussion

The
present study aimed to assess burnout level and to identify some associated
factors that trigger burnout among physicians. In this study the respondents
were experienced high burnout by reflecting high emotional exhaustion 65.2%
(95%CI= 61.1, 69.7), high depersonalization 85.1% (95%CI= 81.7, 87.9) and low
personal accomplishment 91% (95%CI= 88.6, 93.3). Similar study carried out in
Riyadh reported high burnout with 53.5% of respondents scored high for
emotional exhaustion, 38.9% for depersonalization and 28.5% low for personal
accomplishment (20).
Another similar study conducted by Sami Al-Dubai in Yemen showed that high
burnout levels by reflecting 63.2% emotional exhaustion, 19.4% high
depersonalization and 33.0% low personal accomplishment among physicians (21).
The current study finding showed higher level of burnout. Possible explanation
for this difference might be variation in culture and poor employment
condition.

Another
study carried out in Egypt showed that 39.7% high emotional exhaustion; 22.6%
high depersonalization and 99.2% low level of personal accomplishment (14).
Our results for both emotional exhaustion and depersonalization are higher but
lower for low level of personal accomplishment. Probable reason for higher
finding was over stressed at work and less human resources but for lower case
competition among the professionals might be higher to achieve the work. In
general probable reason for the difference in the prevalence of burnout
syndrome across different countries can possibly be explained by variations in
culture, the nature of the health system (including structural and service
delivery problems in different countries) and the role of physicians as
health-care providers.

In
this study burnout level as measured by the three dimensions were predicted by
age, monthly salary, hospital type, receiving recognition from others regarding
work, professional training and having support from family and or organization.
This findings noted that being hospitals type of primary (?= -0.07, P-V
<0.001) was negatively associated with depersonalization dimension of burnout level. On the other hand study done in shanghai showed that hospital type of primary (?= 0.17; p<0.05) was positively associated with depersonalization dimension of burnout (22). The possible differences for this finding was the level of primary care services might be better in our country as compared to shanghai.  In this study average numbers of patients examined per week (?= 0.001; p<0.001) was positively associated with emotional exhaustion dimension of burnout level. Similar study done in a Province in Eastern Anatolia also identified average number of patients examined per week (?= 2.64; p<0.05) was positively associated with emotional exhaustion dimension of burnout level (23). Another study carried out in Turkey showed that number of patients examined was positively associated with emotional exhaustion dimension of burnout level (24). In current study age was negatively associated with emotional exhaustion (?= -0.007; p<0.001)   and depersonalization (?= -0.011; p<0.001) dimensions of burnout. In another context as age increase, emotional exhaustion and depersonalization decreases by controlling other variables. A possible reason is that younger physicians are less experienced and they may become more cognitively overwhelmed with the workload of a routine work day. But the study conducted in Turkey showed that age was not significant predictor for emotional exhaustion and depersonalization dimensions of burnout and positively associated for only personal accomplishment dimension of burnout (25). The study conducted in Shanghai showed that average working hours per week (?= 0.1; p<0.5) was positively associated with emotional exhaustion dimension of burnout (22) but in our finding working hours per week was not significant predictors of emotional exhaustion dimensions of burnout. The probable reason for this might be high work overload in Shanghai compared to our country. Conclusion and recommendation Burnout was measured in three dimensions and it was found in a high level among physicians currently working in public hospitals of South Nations Nationalities and Peoples region. Receiving recognition from others, age, working in primary hospital, monthly salary having any support from family and organization, and getting professional training can possibly minimize the level of burnout among physicians in the region. On the contrary, increase in the number of patients observed per week increases burnout. All the concerned bodies should work collaboratively to decrease the risk of burnout by addressing the contributing factors identified by this study.