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Content may be subject to copyright.
Address for correspondence: Bahadır Geniş, Çaycuma Devlet Hastanesi, Psikiyatri Bölümü, Zonguldak, Turkey
Phone: +90 372 615 82 22 E-mail: bahadirgenis06@gmail.com ORCID: 0000-0001-8541-7670
Submitted Date: November 21, 2019 Accepted Date: June 03, 2020 Available Online Date: December 07, 2020
©Copyright 2020 by Journal of Psychiatric Nursing - Available online at www.phdergi.org
DOI: 10.14744/phd.2020.60590
J Psychiatric Nurs 2020;11(4):275-283
JOURNAL OF
PSYCHIATRIC NURSING
Original Article
Factors aecting mental status and eects
of shift work system in healthcare workers
Shift work system has existed for centuries but become
more widespread with the industrial revolution after the
invention of electricity. Due to the rapid progress in modern
communication and the development of global economies,
shift work system has become more common in work and
social life. Shift work system has become a requirement es-
pecially for the business lines related to security, health, and
industry, where employees should work for 24 hours. Howev-
er, working in various shift systems has caused diculties in
social and health-related elds.
The shift work system constitutes approximately 20% to 25%
of the workforce in industrialized countries,[1] and this rate is
increasing. The rate of working in shifts increased from 17% in
2005 and 2010 to 21% in 2015 in the European Union coun-
tries.[2] This rate diers by country; it is 38% in the United States
of America and 11% in Turkey in 2019. It is most frequently
Objectives: Shift work system causes many physical and mental health problems. This study aimed to investigate the
eects of shift work on sleep quality, mental status, and quality of life of healthcare personnel. It also aimed to deter-
mine the population at risk for depression and anxiety disorders by assessing dierences among the occupational
groups.
Methods: This study was carried out with 219 healthcare personnel at Gazi University Hospital. Employees were clas-
sied according to their more recent working schedule (shift, non-shift) and occupational groups (doctor, nurse, and
other). Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Pittsburg Sleep Quality Index (PSQI), Morning-
ness-Eveningness Questionnaire (MEQ), Perceived Stress Scale (PSS), and Professional Quality of Life Scale (ProQOL)
were administered to the employees.
Results: The BDI (p<0.000), BAI (p<0.001), PSS stress perception subscale (p=0.032), PSQI (p<0.001), and ProQOL burn-
out subscale (p<0.001) scores were signicantly higher in shift personnel than non-shift personnel. When the partici-
pants were analyzed according to occupational groups, BAI scale scores were signicantly higher in nurses (p=0.001)
than doctors or others, whereas stress perception and burnout were signicantly higher in physicians (p=0.003;
p=0.005, respectively). There was no signicant dierence between the occupational groups in terms of BDI and occu-
pational satisfaction (p=0.101; p=0.778, respectively). In the regression analysis, the most important predictor of the
BDI and BAI score was working 41 hours or more. The most important predictor of the PSQI score was shift work.
Conclusion: According to these results, especially nurses and doctors working in shifts are at serious risk for depres-
sion, anxiety, and sleep disorders. Employees’ awareness should be increased regarding the associated risk of smoking,
which is a risk factor. Health care workers should be trained in stress management and sleep hygiene to prevent the
occurrence of mental illnesses.
Keywords: Anxiety disorders; burnout; depression; health personnel; shift work sleep disorder.
Bahadır Geniş,1 Behcet Cosar,2 Mustafa Ender Taner2
1Department of Psychiatry, Çaycuma State Hospital, Zonguldak, Turkey
2Department of Psychiatry, Gazi University Hospital, Ankara, Turkey
Abstract
276 Psikiyatri Hemşireliği Dergisi - Journal of Psychiatric Nursing
used in the health sector (40%), followed by the transporta-
tion (33%) and industry (28%) sectors.[3]
Studies on the eects of working at dierent hours have re-
ported that it increases the risk of diseases and disorders such
as gastritis, ulcers, hypertension, coronary heart disease, deep
venous thrombosis and venous insuciency, breast cancer,
colon cancer, diabetes mellitus, metabolic disorders, depres-
sion, and sleep disorders,[4] and as a result, humans, who are
biopsychosocial creatures, experience burnout and decreased
quality of life.[5]
Humans’ requirements and daily life activities occur in a
rhythm, which changes during the daily life activities of peo-
ple who work in shifts. This vital cycle, called circadian rhythm,
is the fundamental system that regulates physical and mental
health by regulating body temperature, fatigue, blood pres-
sure, hormone release, mood, etc.[6] The synchronization of
this rhythm depends on daylight. Melatonin, which regulates
sleep and has an antioxidant eect, is not released in daylight
causing impaired homeostasis. Previous studies have report-
ed that shift work system impairs sleep quality due to chang-
es in the rapid eye movement (REM) and non-REM (NREM)
second phase sleep periods.[6,7] Furthermore, sleep disorders
cause chronic fatigue, weakness in memory and attention,
and mental disorders, in particular depression.[4,8] Studies
have shown that older employees who work in shifts have
lower sleep quality, have diculties adapting to the require-
ments of working in shifts, and react less to the phase changes
in daylight compared to younger employees.[9] In addition to
older employees, female employees constitute another group
aected by shift work system. It has been reported that diur-
nation and additional psychological symptoms are observed
frequently in women working in shifts.[8,10] In nursing, where
women constitute a large part of the workforce, shift work sys-
tem triggers many psychiatric disorders, including particularly
sleep disorders and depression as well as somatization, anxi-
ety, and social dysfunction.[11] A study in Turkey reported that
the rates of somatization, obsessive-compulsive symptoms,
interpersonal sensitivity, anxiety, and paranoid ideation were
higher and quality of life was lower among the nurses who
worked in shifts.[12]
Shift work system is one of the most important factors that
aect healthcare professionals’ moods, in addition to other
important factors such as sleep disorders, perceived stress, in-
tense working hours, years worked in the profession, burnout,
or satisfaction with their profession.[13] These factors depend
on each other. For example, sleep disorders increase the ten-
dency for depression and anxiety disorders. Depressed and
anxious individuals have reduced satisfaction with their pro-
fession and experience increased burnout,[14] which in turn
aects their quality of life. Deterioration of one factor often
leads to deterioration of another factor, and improvement in
one factor will contribute to the improvement of other factors.
Psychiatric nurses provide services in the protection and pro-
motion of individual, family, and community mental health as
well as in cases of mental disease. They play a key role and
actively participate in the evaluation of problems experienced
by healthcare personnel working in shifts who are at serious
risk for mental and physical diseases.[15] A study that analyzes
the variables such as depression, anxiety disorder, perceived
stress, sleep disorders, and quality of life, as indicated above,
for all mental health personnel, particularly psychiatric nurs-
es and doctors would make a signicant contribution to the
literature. Therefore, this study analyzes the eects of shift
work system on healthcare professionals’ mental status, sleep
quality, and quality of life, compares the levels of depression,
anxiety, burnout, sleep quality, and quality of life in doctors,
nurses, and other healthcare personnel, and determines the
population at risk for mental disorders. Determination of the
population at risk is critical for providing psychiatric nursing
services eectively and eciently.
Materials and Method
Study Type
This study was designed as a descriptive and cross-sectional
study.
Study Population and Sample
The study was conducted with the healthcare professionals
working at Gazi University Hospital in March and April 2016.
The study population consisted of 670 nurses, 245 doctors, and
590 other healthcare professionals. The sample size was calcu-
lated using the G*Power 3 program considering the mean and
standard deviation values of the variables of depression and
anxiety in healthcare professionals in another study.[12,16] Ac-
cordingly, the researchers aimed to include a minimum of 158
healthcare professionals to achieve a condence limit of 95%,
a margin of error of 5%, and a testing power of 95%.
The prole of healthcare personnel indicates that nurses and
doctors constitute the largest group among all healthcare
professionals. They were also the main group in the present
study. The “other healthcare professions” group in the present
study included medical secretaries, medical ocers, physio-
therapists, psychologists, and caregivers. These groups were
combined because they had inadequate numbers separately.
The study sample consisted of 219 participants: 55 doctors, 80
What is known on this subject?
• Working in shifts impairs the sleep quality of healthcare professionals
and causes a tendency for depression and anxiety disorders. These ef-
fects have a greater impact on the mental health of female employees,
impairing their quality of life.
What is the contribution of this paper?
• Female healthcare personnel who are working in shifts and smoke are at
serious risk of depression and anxiety disorders.
What is its contribution to the practice?
• All healthcare professionals, particularly female employees who are
working in shifts and smoke, should be provided with training to in-
crease their awareness on stress management and support for smoking
cessation.
277
Bahadır Geniş, Shift work and health workers / dx.doi.org/10.14744/phd.2020.60590
nurses, and 84 other healthcare professionals. This sample size
was higher than the number of participants determined in the
power analysis, and all participants’ data were analyzed con-
sidering that they represent the population better.
Data Collection and Assessment Tools
After the participants were informed and their consent was
obtained, the prepared forms were distributed. The forms
were collected from 250 healthcare professionals who agreed
to participate in the study. Of the forms, 31 were not analyzed
as they were only partially lled out or contained inconsistent
answers. Consequently, 219 assessment forms were statistical-
ly analyzed.
The data were collected using a General Information Form,
the Beck Anxiety Scale (BAS), the Beck Depression Inventory
(BDI), the Morningness-Eveningness Questionnaire (MEQ), the
Perceived Stress Scale (PSS), the Pittsburgh Sleep Quality In-
dex (PSQI), and the Professional Quality of Life Scale (ProQOL).
The General Information Form was prepared by the researcher
based on the literature and included the participants’ sociode-
mographic data and information on their working life.
The BAS was developed by Beck et al.[17] as a self-assessment
tool to determine the prevalence of anxiety symptoms expe-
rienced by individuals. Ulusoy et al.[18] tested the BAS for va-
lidity and reliability in Turkish and found its Cronbach’s alpha
coecient to be 0.93. It is a four-point Likert type scale with
21 items. Higher scale scores indicate higher anxiety levels. In
the present study, the Cronbach’s alpha coecient was 0.89.
The BDI was developed by Beck et al.[19] to determine the in-
dividuals’ risk for depression and measure the severity of de-
pression. It is a four-point Likert type scale with 21 items. It
was tested for validity in Turkish by Hisli[20] in 1988. Higher
scale scores indicate higher severity of depression. Its Cron-
bach’s alpha coecient was 0.80 in the Turkish validity study
and 0.91 in the present study.
The MEQ was developed by Horne and Ostberg.[21] It consists
of 19 questions assessing when individuals’ physical and psy-
chological performance is better within a 24 hour period and
their preferences during sleep and wakefulness. The question-
naire was tested for reliability in Turkish.[22] Its Cronbach’s alpha
coecient was 0.81 both in the Turkish reliability study and
in the present study. Higher scale scores indicate increased
morningness characteristics.
The PSS was developed by Cohen et al.[23] It consists of 14 items
and assesses the extent to which individuals perceive some sit-
uations in their lives as stressful. The participants assess each
item on a 5-point Likert type scale from “Never (0)” to “Very Of-
ten (4).” It was tested for validity and reliability in Turkish by Es-
kin et al.[24] Its Cronbach’s alpha coecient was 0.84 both in the
Turkish reliability study and in the present study. Higher scale
scores indicate higher perceived stress in individuals.
The PSQI is a questionnaire with 11 sections used to deter-
mine sleep quality. It was developed by Buysse et al. in 1989.[25]
It was tested for validity and reliability in Turkish by Ağargün
et al. in 1996.[26] The PSQI has seven components, and its Cron-
bach’s alpha coecient is 0.80. The components are subjec-
tive sleep quality, sleep latency, sleep duration, sleep ecien-
cy, sleep disturbance, use of sleep medication, and daytime
dysfunction, which yields a total score between 0 and 21. A
total score higher than 5 indicates impaired sleep quality. In
the present study, the Cronbach’s alpha coecient was 0.74.
The ProQOL, developed by Stamm,[27] consists of 30 items un-
der three subscales. The compassion satisfaction subscale as-
sesses the sense of satisfaction and pleasure experienced by
employees when they help someone in need in a eld related
to their profession or job. The burnout subscale assesses the
sense of burnout that emerges when employees have dicul-
ty coping with the problems that occur in their working life
and experience hopelessness. The compassion fatigue sub-
scale assesses the symptoms that emerge when employees
encounter stressful events. The participants assess each item
on a 6-point Likert type scale from “Never (0)” to “Very Often.
[6]” It was tested for validity and reliability in Turkish by Yeşil et
al.[28] They found the Cronbach’s alpha coecients of the com-
passion satisfaction, burnout, and compassion fatigue sub-
scales to be 0.84, 0.62, and 0.83, respectively. In the present
study, the Cronbach’s alpha coecients were 0.85, 0.73, and
0.82, respectively.
Ethical Consideration
Ethical approval was obtained from the Ethics Committee of
Gazi University with number 2017-78 on 2/10/2017. The aim
and scope of the study were explained to the participants, and
they were informed that their participation was voluntary and
their personal information would be kept condential. Any
questions were answered and their written consent was ob-
tained.
Data Analysis
The statistical analyses were performed using the SPSS 23.0
program. The descriptive statistics were presented as frequen-
cy, percentage, mean, and standard deviation. The qualitative
data were compared using the chi-square test, and when the
expected frequencies could not be met, using the Fisher Exact
test. Whether the data are normally distributed was assessed
using the Kolmogorov Smirnov test, which yielded insignif-
icant results. However, it was reported that parametric tests
show signicant power and can be used when the sample
size is higher than 30 in the analyzed groups and the kurto-
sis/skewness coecients are between ±2.[29,30] Therefore, the
One-Way Variance Analysis was used to compare the variables
among the three groups and the Levene Analysis was used to
assess the homogeneity of the groups’ variances. The Tukey
post hoc test was used when the variances were homoge-
neous, and the Tamhane’s T2 test was used when they were
heterogeneous. The independent samples t-test was used to
compare the data of two groups. The scores of the BDI, BAS,
278 Psikiyatri Hemşireliği Dergisi - Journal of Psychiatric Nursing
and PSQI were used as dependent variables in the multiple
linear regression analysis. It was reported that while numerical
variables are mainly used in multiple linear regression analy-
sis, binary categorical variables or ordered variables such as
education level can also be used.[31] Therefore, in the multiple
linear regression analysis, categorical variables such as gender,
marital status, and smoking were addressed in addition to the
numerical variables such as age, body mass index, and years
of working. Signicance levels were accepted to be p<0.05 for
the statistical analysis.
Study Limitations
Doctors and nurses were analyzed as separate groups. How-
ever, medical secretaries, medical ocers, physiotherapists,
psychologists, caregivers, etc. were categorized under the
“other professions” group because each group did not have
Table 1. Participants’ sociodemographic characteristics according to working system (n=219)
Variable Non-shift Shift Total X2 p
(n=109) (n=110) (n=219)
n % n % n %
Gender
Female 85 78.0 65 59.1 150 68.5 8.199 0.004
Male 24 22.0 45 40.9 69 31.5
Age group
21–30 years 27 24.8 63 57.3 90 41.1 28.943 <0.001
31–40 years 42 38.5 33 30.0 75 34.2
41 and older 40 36.7 14 12.7 54 24.7
Marital status
Single 29 26.6 46 41.8 75 34.2 12.455 0.002
Married 69 63.3 63 57.3 132 60.3
Widow 11 10.1 1 0.9 12 5.5
Profession
Doctor 19 17.4 36 32.7 55 25.1 7.257 0.027
Nurse 42 38.5 38 34.5 80 36.5
Other 48 44.0 36 32.7 84 38.4
Education level
Primary school 7 6.4 3 2.7 10 4.6 7.976 0.047
Middle school 3 2.8 13 11.8 16 7.3
High school 17 15.6 16 14.5 33 15.1
University 82 75.2 78 70.9 160 73.1
Income level
3000 TL and lower 27 24.8 32 29.1 59 26.9 0.323 0.570
3001 TL and higher 82 75.2 78 70.9 160 73.1
Working hours
Less than 40 hours 8 7.3 1 0.9 9 4.1 88.898 <0.001
40 hours 71 65.1 15 13.6 86 39.3
41 to 48 hours 23 21.1 46 41.8 69 31.5
49 to 56 hours 5 4.6 25 22.7 30 13.7
57 hours and more 2 1.8 23 20.9 25 11.4
Smoking
No 82 75.2 76 69.1 158 72.1 0.744 0.388
Yes 27 24.8 34 30.9 61 27.9
Alcohol
No 95 87.2 78 70.9 173 79.0 7.758 0.005
Yes 14 12.8 32 29.1 46 21.0
Having children
No 33 30.3 63 57.3 96 43.8 15.130 <0.001
Yes 76 69.7 47 42.7 123 56.2
279
Bahadır Geniş, Shift work and health workers / dx.doi.org/10.14744/phd.2020.60590
enough participants for statistical analysis. These personnel’s
working conditions, working hours, or dierent shift systems
may have created a variance. The higher average age of the
personnel not working in shifts compared to those working
in shifts may have played a confounding role in the analyses
of many variables. Similarly, the higher percentage of female
personnel was also a limitation. The categorization of the non-
shift and shift work systems was based on the latest schedule
the participant worked. This may have caused a limitation on
the assessment of the eect of the working system on mental
status and quality of life if the most recent schedule did not
reect the usual working system.
Results
Table 1 shows the participants’ sociodemographic charac-
teristics. Of the participants, 150 (68.5%) were female, 90
(41.1%) were aged between 21 and 30, 132 (60.3%) were
married, and 160 (73.1%) had graduated from university. Of
them, 160 (73.1%) had an income of 3001 TL and higher, 86
(39.3%) worked 40 hours a week, 110 (50.2%) worked in shifts,
61 (27.9%) smoked, 46 (21.0%) consumed alcohol, and 123
(56.2%) had children (Table 1).
Table 2 shows the assessment of the scales administered to
the participants according to their working system. A statis-
tically signicant dierence was found between the partici-
pants working and not working in shifts in terms of the BDI,
the BAS, the stress perception subscale of the PSS, the PSQI,
and the compassion satisfaction, burnout, and compassion fa-
tigue subscales of the ProQOL (Table 2).
Table 3 shows the comparison of the mean scale scores ac-
cording to profession. No statistically signicant dierence
Table 2. Comparison of the scale scores according to the working system
Variable Non-shift (n=109) Shift (n=110) Total (n=219) t p
Mean±SD Mean±SD Mean±SD
BDI 6.96±7.71 11.54±9.71 9.25±9.07 -3.863 <0.001
BAS 5.52±6.59 8.77±8.47 7.10±7.75 -3.121 <0.001
PSS - Insucient self-ecacy perception 10.90±3.75 10.87±4.05 10.86±3.89 0.067 0.946
PSS - Stress perception 12.37±4.57 13.79±5.29 13.07±4.99 -2.115 0.036
PSQI 5.44±3.33 7.61±3.59 6.50±3.61 -4.646 <0.001
ProQOL - Compassion satisfaction 33.54±8.66 30.98±9.67 32.36±9.12 2.062 0.040
ProQOL - Burnout 15.69±7.24 19.56±7.74 17.61±7.74 -3.813 <0.001
ProQOL - Compassion Fatigue 13.66±7.95 15.77±8.51 14.72±8.28 -1.890 0.049
MEQ 50.59±8.40 46.16±9.72 48.36±9.34 3.607 <0.001
BDI: Beck Depresson Inventory; BAS: Beck Anxety Scale; PSS: Perceved Stress Scale; PSQI: Pttsburgh Sleep Qualty Index; ProQOL: Professonal Qualty of Lfe Scale; MEQ:
Mornngness-Evenngness Questonnare; Mean: Mean value; SD: Standard devaton.
Table 3. Comparison of the scale scores according to profession
Variables Doctor1 (n=55) Nurse2 (n=80) Other3 (n=84) Post Hoc
Mean±SD Mean±SD Mean±SD F p Binaries p
BDI 9.63±9.66 10.62±9.60 7.72±7.89 2.186 0.115
BAS 6.49±6.02 9.98±9.90 4.83±5.20 10.099 <0.001 1–2 0.021
2–3 <0.001
PSS - Insucient Self-Ecacy 10.92±4.00 10.95±3.66 10.80±4.08 0.030 0.971
Perception
PSS - Stress Perception 14.67±4.64 13.28±457 11.85±5.30 5.627 0.004 1–3 0.004
PSQI 7.40±3.30 6.71±4.29 5.79±2.96 3.470 0.033 1–3 0.029
ProQOL-Compassion Satisfaction 32.16±10.19 31.78±9.00 32.76±8.92 0.229 0.795
ProQOL-Burnout 20.03±7.47 18.02±7.81 15.70±7.40 5.606 0.004 1–3 0.003
ProQOL-Compassion Fatigue 13.36±7.32 16.29±8.58 14.14±8.45 2.389 0.094
MEQ 45.83±9.01 49.23±7.88 48.54±10.71 1.103 0.334
1: Doctor, 2: Nurse, 3: Other. BDI: Beck Depresson Inventory; BAS: Beck Anxety Scale; PSS: Perceved Stress Scale; PSQI: Pttsburgh Sleep Qualty Index; ProQOL: Professonal Qualty
of Lfe Scale; MEQ: Mornngness-Evenngness Questonnare; Mean: Mean value; SD: Standard devaton.
280 Psikiyatri Hemşireliği Dergisi - Journal of Psychiatric Nursing
was found between the professions in terms of the
BDI, the insucient self-ecacy perception of the
PSS, and the compassion satisfaction and compas-
sion fatigue subscales of the ProQOL. The compari-
son of the mean scores on the BDI, the stress percep-
tion subscale of the PSS, the PSQI, and the burnout
subscale of the ProQOL indicated a statistically sig-
nicant dierence between the professions. Nurses
had the highest mean score on the BAS, whereas
doctors had the highest mean scores on the stress
perception subscale of the PSS, the PSQI, and the
burnout subscale of the ProQOL (Table 3).
Table 4 shows the results of the multiple linear re-
gression analysis, which analyzed the healthcare
professionals’ scores on the BDI, BAS, and PSQI.
Accordingly, the most important factor that aect-
ed depression in the healthcare professionals was
weekly working hours, followed by an education
level of university and higher, smoking, and female
gender, respectively. The predictors of the BAS,
which assesses anxiety disorder, were working for
41 hours and longer, female gender, an education
level of university and higher, and body mass index
(BMI), respectively, in the order of importance. The
predictors of the PSQI, which assesses sleep disor-
der, were shift work system, an education level of
university and higher, smoking, and female gender,
respectively, in the order of importance.
Discussion
This study determined the eect of shift work sys-
tem on healthcare professionals’ mental status,
sleep quality, and quality of life. It also analyzed the
dierences between these variables according to
profession. Depression, anxiety disorder, sleep dis-
order, burnout, and stress perception levels were
higher in the participants working in shifts. Nurses
had the highest level of anxiety symptoms, where-
as doctors had the highest level of sleep disorders,
stress perception, and burnout. The most important
predictor of depression and anxiety disorders was
long working hours, whereas shift work system was
the most important predictor of sleep disorders.
Considering the participants’ mental status, it can be
said that those working in shifts had a higher stress
perception and a tendency for depression and anxi-
ety disorders. The participants’ higher stress percep-
tion scores may have caused an inclination towards
depression and anxiety disorders. In a study con-
ducted with 979 healthcare professionals working in
shifts, the participants reported their mental health.
[11] Of the participants, 45.4% were found to have
mild to severe mental disorders. Anxiety and somati-
zation disorders were at the highest rates (43.2% and
Table 4. Results of the Multiple Linear Regression Analysis for the Prediction of the BDI, BAS, and PSQI Scores
BDI BAS PSQI
Variable β (95% CI) p β (95% CI) p β (95% CI) p
Age -0.231 (-0.604; 0.058) 0.106 0.035 (-0.247; 0.318) 0.805 0.017 (-0.123; 0.139) 0.907
Gender (Female=1/Male=2) -0.155 (-5.827; -0.216) 0.035 -0.238 (-6.351; -1.559) 0.001 -0.143 (-2.228; -0.006) 0.049
Marital status (Single=1/Married=2) -0.092 (-6.087; 2.600) 0.430 0.032 (-3.181; 4.238) 0.779 -0.123 (-2.658; 0.782) 0.284
Education Level (High School and lower=1/University 0.200 (0.792; 7.357) 0.015 0.175 (0.238; 5.844) 0.034 0.217 (0.470; 3.069) 0.008
and higher=2)
Income Level (3000 TL and lower=1/3001 TL and higher=2) -0.053 (-4.097; 1.957) 0.487 0.008 (-2.439; 2.732) 0.911 -0.036 (-1.492; 0.905) 0.629
Body mass index 0.100 (-0.109; 0.667) 0.158 0.147 (0.020; 0.683) 0.038 0.079 (-0.065; 0.243) 0.254
Having Children (No=1/Yes=2) 0.030 (-4.212; 5.299) 0.822 -0.015 (-4.294; 3.828) 0.910 0.071 (-1.363; 2.403) 0.587
Years of working 0.198 (-0.008; 0.043) 0.175 -0.057 (-0.026; 0.017) 0.695 -0.099 (-0.013; 0.006) 0.490
Working system (Non-shift=1/Shift=2) 0.140 (-0.411; 5.478) 0.091 0.085 (-1.206; 3.823) 0.306 0.250 (0.644; 2.975) 0.003
Weekly working hours (40 hours and less=1/41 hours 0.218 (0.910; 7.026) 0.011 0.280 (1.761; 6.985) 0.001 0.058 (-0.786; 1.636) 0.490
and more=2)
Smoking (No=1/Yes=2) 0.155 (0.392; 5.846) 0.025 0.129 (-0.100; 4.558) 0.061 0.166 (0.261; 2.421) 0.015
Alcohol consumption (No=1/Yes=2) -0.016 (-3.513; 2.796) 0.823 -0.007 (-2.828; 2.561) 0.922 0.047 (-0.834; 1.664) 0.513
F 3.517 3.596 4.030
p <0.001 <0.001 <0.001
R2 0.170 0.173 0.190
BDI: Beck Depression Inventory; BAS: Beck Anxiety Scale; PSQI: Pittsburg Sleep Quality Index.
281
Bahadır Geniş, Shift work and health workers / dx.doi.org/10.14744/phd.2020.60590
34.5%, respectively). The prevalence of depression was 11.2%.
In the present study, a tendency for depression showed no
dierence according to profession. This nding suggests that
all healthcare professionals seemed to have a similar risk of
depression. Virtanen et al. prospectively followed 2123 health-
care professionals without psychiatric morbidity for mental
diseases.[32] They found that those working in shifts were at
approximately two times higher risk of depression even after
adjusting for sociodemographic variables, chronic diseases,
alcohol consumption, smoking, and job-related factors. In the
present study, although the doctors’ and nurses’ BDI scores
were higher than those of the other healthcare professionals,
the dierence was not statistically signicant. Nevertheless,
it was close to the signicance level (p=0.101). Accordingly, it
can be concluded that the burden of shift work system increas-
es the risk for depression and anxiety in healthcare personnel,
particularly doctors and nurses. However, some studies indi-
cated that depression and shift work system were not directly
related but indirectly related due to long working hours and
sleep disorders.[33] Another study partially supports this result,
showing that the symptoms of anxiety and depression were
more frequently observed in those who worked in shifts and
had impaired sleep quality.[34]
Sleep quality and duration were reported to reduce in those
working in shifts.[35] The present study also found that sleep
quality was poorer in those working in shifts. Doctors had
poorer sleep quality compared to the other healthcare pro-
fessionals. It is known that employees experience sleepiness
the day after shift work due to low sleep quality, which im-
pairs their social life and cognitive function.[36,37] A study that
assessed sleepiness in working systems with a larger sample
reported that the rate of sleepiness was highest in those work-
ing at night and lowest in those working in the daytime. It has
been reported that sleep is aected in at least three-quarters
of those working in shifts and the prevalence of sleep disor-
ders is approximately 10% in them.[38]
Job satisfaction and burnout are important issues that aect
the quality of life. A study conducted with nurses compared
their job satisfaction according to dierent shift working sys-
tems (constantly days, constantly nights, and rotating shifts)
and found that the nurses working in rotating shifts had the
lowest job satisfaction.[39] It also reported that 54.9% of the
participant nurses might have been at risk for mental dis-
eases. The present study also found compassion satisfaction
to be higher in those working in the non-shift system, which
supports the literature. However, no dierence was found be-
tween the professions in terms of compassion satisfaction.
Another sub-factor of quality of life, burnout, was signicant-
ly higher in those working in shifts (according to the working
system) and in doctors (according to profession) in the pres-
ent study. Burnout is frequently observed in healthcare profes-
sionals who have intense contact with people, which causes
an increase in the prevalence of various mental disorders, de-
pression in particular, as well as a decrease in quality of life and
job and life satisfaction.[40–42] Young age, female gender, high
expectations in the workplace, and employees’ low control
over the consequences of their work are risk factors for burn-
out.[43]
Compassion fatigue is dened as the physical, social, and men-
tal burnout experienced by caregivers, which causes reduced
willingness, and skills of empathize with and caregiving to
others.[44] It is expressed as the cost of caregiving for health-
care professionals arising as a natural result of the caregiving
relationship. Yoder conducted a study in 2010 and found that
15% of the nurses experienced compassion fatigue.[45] Khan
et al.[46] reported that compassion fatigue was observed at a
higher level in doctors and nurses compared to paramedical
personnel. In the present study, compassion fatigue was sig-
nicantly higher in the participants working in shifts. Although
no signicant dierence was found between the professions
in terms of compassion fatigue, nurses obtained the highest
mean scores.
The present study indicated that the most important factor
that aects depression and anxiety disorder was weekly work-
ing hours, whereas shift work system was the most important
factor that aects sleep disorders. Virtanen et al.[47] reported
that working for 40 hours or more in a week increased the
tendency for depression by a factor of 1.66 and for anxiety
disorders by a factor of 1.74 for the healthcare professionals
whom they followed for 5 years. They also found that working
for 40 hours or more in a week increased the risk for depres-
sion by a factor of 2.67 and for anxiety disorder by a factor of
2.84 for female healthcare professionals. Their study suggests
that working for long periods aects female personnel more.
The present study found a similar result. Female gender was
a signicant predictor for depression, anxiety, and sleep dis-
orders in healthcare professionals. Another variable that may
be related to these psychiatric disorders is education level. Al-
though the studies analyzing the relationship between edu-
cation level and depression are inconsistent, it seems to be a
more common opinion that depression level decreases with a
higher education level. A recent study reported that the pos-
sibility of depression decreased with a higher education dura-
tion.[48] Another study indicated that the prevalence of depres-
sion varied by education level. It showed that depression level
was 7% in the uneducated participants, 38% in primary school
graduates, 41% in middle school graduates, and 8% in univer-
sity graduates.[49] This suggests that lower awareness of the
uneducated participants may protect them from depression.
This prevalence may decrease with a higher education level
as educated people may seek a diagnosis of and treatment
for depression. In the present study, an education level of uni-
versity and higher was found to increase the tendency for de-
pression, perhaps because participants with higher education
levels were mostly included in the doctor or nurse groups.
While the level of smoking has decreased within the last 20
years, it has remained at relatively similar levels for those hav-
ing a psychiatric disease.[50] There are a few hypotheses that try
to explain smoking in those who have a psychiatric disease.
282 Psikiyatri Hemşireliği Dergisi - Journal of Psychiatric Nursing
The most important hypotheses are smoking for self-med-
ication and the fact that nicotine temporarily reduces the
symptoms of anxiety/depression. However, considering its
long-term eects, smoking is a precipitating agent for psychi-
atric disorders. A study conducted with 701 healthcare profes-
sionals determined depression in 37% of the smoking nurses
and 17% of the non-smoking nurses.[51] The present study also
found that smoking was one of the most important predictors
of depression and sleep disorders in healthcare professionals.
It is also suggested that shift work system increases the rate of
smoking and caeine intake by personnel to stay awake and
increase their performance.[47] Accordingly, it can be conclud-
ed that shift work system may increase depression directly or
may increase the tendency for depression indirectly through
smoking.
Conclusion
Healthcare professionals, particularly nurses and doctors, are
at serious risk for depression, anxiety, and sleep disorders. The
reduction of long working hours is regarded as one of the
most signicant ways to prevent depression and anxiety dis-
orders. The working and resting hours should be regulated in
accordance with international criteria to reduce these psychi-
atric disorders in healthcare professionals. Psychiatric nurses
and doctors play an important role in early diagnosis, preven-
tion, and guiding the treatment of these disorders in health-
care professionals. The results of the present study serve as a
guidance for psychiatric personnel as it shows the diculties
experienced by the healthcare professionals working in shifts.
The risk for depression and sleep disorders was higher for fe-
male healthcare professionals who were smoking and had a
higher education level. It is recommended that awareness be
raised in this population regarding stress and sleep manage-
ment and training programs be organized to decrease burn-
out and compassion fatigue. Psychiatric nurses should inform
healthcare professionals about the fact that smoking increas-
es depression and sleep disorders, increase the awareness on
smoking cessation treatments, and provide guidance to ac-
cess the treatment.
Conict of interest: There are no relevant conicts of interest to
disclose.
Peer-review: Externally peer-reviewed.
Authorship contributions: Concept – B.G., M.E.T.; Design – B.G.,
M.E.T.; Supervision – B.G., M.E.T., B.C.; Fundings - B.G.; Materials –
B.G.; Data collection &/or processing – B.G., B.C.; Analysis and/or
interpretation – B.G., B.C.; Literature search – B.G., B.C.; Writing –
B.G., M.E.T., B.C.; Critical review – B.G., M.E.T., B.C.
References
1. Faraut B, Bayon V, Léger D. Neuroendocrine, immune and oxi-
dative stress in shift workers. Sleep Med Rev 2013;17:433–44.
2. Eurofound. Sixth European Working Conditions Survey –
Overview report (2017 update). Luxembourg: Publications
Oce of the European Union; 2017.
3. Eurofound. Working conditions in a global perspective. Pub-
lications; Luxembourg: International Labour Organization;
2019.
4. DeMoss C, McGrail M Jr, Haus E, Crain AL, Asche SE. Health and
performance factors in health care shift workers. J Occup En-
viron Med 2004;46:1278–81.
5. Flo E, Pallesen S, Magerøy N, Moen BE, Grønli J, Hilde Nordhus
I, et al. Shift work disorder in nurses--assessment, prevalence
and related health problems. PLoS One 2012;7:e33981.
6. Akerstedt T. Shift work and disturbed sleep/wakefulness. Oc-
cup Med (Lond) 2003;53:89–94.
7. Culpepper L. The social and economic burden of shift-work
disorder. J Fam Pract 2010;59:3–11.
8. Shields M. Shift work and health. Health Rep 2002;13:11–33.
9. Duy JF, Zeitzer JM, Czeisler CA. Decreased sensitivity to
phase-delaying eects of moderate intensity light in older
subjects. Neurobiol Aging 2007;28:799–807.
10. Ogińska H, Pokorski J, Ogiński A. Gender, ageing, and shift-
work intolerance. Ergonomics 1993;36:161–8.
11. Ardekani ZZ, Kakooei H, Ayattollahi SM, Choobineh A, Seraji
GN. Prevalence of mental disorders among shift work hospital
nurses in Shiraz, Iran. Pak J Biol Sci 2008;11:1605–9.
12. Selvi Y, Özdemir PG, Özdemir O, Aydın A, Beşiroğlu L. Sağlık
çalışanlarında vardiyalı çalışma sisteminin sebep olduğu genel
ruhsal belirtiler ve yaşam kalitesi üzerine etkisi. Dusunen
Adam The Journal of Psychiatry and Neurological Sciences
2010;23:238–43.
13. Miró E, Solanes A, Martínez P, Sánchez AI, Rodríguez Marín J.
Relationship between burnout, job strain, and sleep charac-
teristics. Psicothema 2007;19:388–94.
14. Alvaro PK, Roberts RM, Harris JK. A Systematic Review Assess-
ing Bidirectionality between Sleep Disturbances, Anxiety, and
Depression. Sleep 2013;36:1059–68.
15. Sarıkoç G, Özcan CT, Elçin M. Psikiyatri Hemşireliği Eğitiminde
Yenilikçi Bir Uygulama: Standart Hastalar. Dokuz Eylül Üniver-
sitesi Hemşirelik Fakültesi Elektronik Dergisi 2016;9:61–6.
16. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a exible
statistical power analysis program for the social, behavioral,
and biomedical sciences. Behav Res Methods 2007;39:175–
91.
17. Beck AT, Epstein N, Brown G, Steer RA. An inventory for mea-
suring clinical anxiety: psychometric properties. J Consult Clin
Psychol 1988;56:893–7.
18. Ulusoy M, Hisli Şahin N, Erkmen H. Turkish Version of the Beck
Anxiety Inventory: Psychometric Properties. J Cogn Psychoth-
er 1998;12:163–72.
19. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An in-
ventory for measuring depression. Arch Gen Psychiatry
1961;4:561–71.
20. Hisli N. Beck Depresyon Envanterinin Geçerliği Üzerine Bir
Çalışma. Psikoloji Dergisi 1988;22:118–26.
21. Horne JA, Ostberg O. A self-assessment questionnaire to
determine morningness-eveningness in human circadian
rhythms. Int J Chronobiol 1976;4:97–110.
283
Bahadır Geniş, Shift work and health workers / dx.doi.org/10.14744/phd.2020.60590
22. Pündük Z, Gür H, Ercan İ. Sabahçıl-Akşamcıl Anketi Türkçe
Uyarlamasında Güvenilirlik Çalışması. Turk Psikiyatri Derg
2005;16:1–6.
23. Cohen S, Kamarck T, Mermelstein R. A global measure of per-
ceived stress. J Health Soc Behav 1983;24:385-–96.
24. Eskin M, Harlak H, Demirkıran F, Dereboy Ç. Algılanan Stres
Ölçeğinin Türkçeye uyarlanması: Güvenilirlik ve geçerlilik an-
alizi. New/Yeni Symposium Journal 2013;51:132–40.
25. Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ.
The Pittsburgh Sleep Quality Index: a new instrument for psy-
chiatric practice and research. Psychiatry Res 1989;28:193–
213.
26. Ağargün MY, Kara H, Anlar Ö. Validity and Reliability of the
Pittsburgh Sleep Quality Index. Turk Psikiyatri Derg 1996;7.
27. Stamm BH. The ProQOL manual: The Professional Quality of
Life Scale: Compassion Satisfaction, Burnout and Compassion
Fatigue/Secondary Trauma scales. Pocatello: Idaho State Uni-
versity and Sidran Press; 2005.
28. Yeşil A, Ergün Ü, Amasyalı C, Er F, Olgun NN, Aker T. Validity and
Reliability of the Turkish Version of the Professional Quality of
Life Scale. Noro Psikiyatr Ars 2010;47:111–7.
29. Privitera GJ. Statistics for the Behavioral Sciences. 2nd ed. Unit-
ed States: SAGE Publications; 2015.
30. Tabachnick BG, Fidell LS. Using multivariate statistics. 6th ed.
United States: Pearson Education; 2013.
31. Karagöz Y. SPSS 22 Uygulamalı Biyoistatistik. 2nd ed. Ankara:
Nobel Akademik Yayıncılık; 2015.
32. Virtanen M, Stansfeld SA, Fuhrer R, Ferrie JE, Kivimäki M. Over-
time work as a predictor of major depressive episode: a 5-year
follow-up of the Whitehall II study. PLoS One 2012;7:e30719.
33. Nakata A. Work hours, sleep suciency, and prevalence of
depression among full-time employees: a community-based
cross-sectional study. J Clin Psychiatry 2011;72:605–14.
34. Kalmbach DA, Pillai V, Cheng P, Arnedt JT, Drake CL. Shift work
disorder, depression, and anxiety in the transition to rotating
shifts: the role of sleep reactivity. Sleep Med 2015;16:1532–8.
35. Pilcher JJ, Lambert BJ, Hucutt AI. Dierential eects of per-
manent and rotating shifts on self-report sleep length: a me-
ta-analytic review. Sleep 2000;23:155–63.
36. Smith L, Tanigawa T, Takahashi M, Mutou K, Tachibana N, Kage
Y, et al. Shiftwork locus of control, situational and behavioural
eects on sleepiness and fatigue in shiftworkers. Ind Health
2005;43:151–70.
37. Caruso CC. Reducing Risks to Women Linked to Shift Work,
Long Work Hours, and Related Workplace Sleep and Fatigue
Issues. J Womens Health (Larchmt) 2015;24:789–94.
38. Drake CL, Roehrs T, Richardson G, Walsh JK, Roth T. Shift work
sleep disorder: prevalence and consequences beyond that of
symptomatic day workers. Sleep 2004;27:1453–62.
39. Tarhan M, Dalar L. Mental Health Status of Nurses and Af-
fecting Factors. Gazi University Journal of Health Sciences
2016;1:25–39.
40. Erol A, Saricicek A, Gülseren S. Burnout in residents: associa-
tion with job satisfaction and depression. Anadolu Psikiyatr
Derg 2007;8:241–7.
41. Embriaco N, Azoulay E, Barrau K, Kentish N, Pochard F, Loundou
A, et al. High level of burnout in intensivists: prevalence and
associated factors. Am J Respir Crit Care Med 2007;175:686–
92.
42. Kokkinos CM. Job stressors, personality and burnout in prima-
ry school teachers. Br J Educ Psychol 2007;77:229–43.
43. Śliwiński Z, Starczyńska M, Kotela I, Kowalski T, Kryś-Noszczyk
K, Lietz-Kijak D, et al. Life satisfaction and risk of burnout
among men and women working as physiotherapists. Int J
Occup Med Environ Health 2014;27:400–12.
44. McHolm F. Rx for compassion fatigue. J Christ Nurs 2006;23:12–
9.
45. Yoder EA. Compassion fatigue in nurses. Appl Nurs Res
2010;23:191–7.
46. Khan AA, Khan MA, Malik NJ. Compassion fatigue amongst
health care providers. Pak Armed Forces Med J 2015;65:286–9.
47. Virtanen M, Ferrie JE, Singh-Manoux A, Shipley MJ, Stansfeld
SA, Marmot MG, et al. Long working hours and symptoms of
anxiety and depression: a 5-year follow-up of the Whitehall II
study. Psychol Med 2011;41:2485–94.
48. Viinikainen J, Bryson A, Böckerman P, Elovainio M, Pitkänen N,
Pulkki-Råback L, et al. Does education protect against depres-
sion? Evidence from the Young Finns Study using Mendelian
randomization. Prev Med 2018;115:134–9.
49. Fernández-Niño JA, Bonilla-Tinoco LJ, Astudillo-García CI,
Manrique-Hernández EF, Giraldo-Gartner V. Association be-
tween the employment status and the presence of depressive
symptoms in men and women in Mexico. Cad Saude Publica
2018;34:e00219617.
50. Fluharty M, Taylor AE, Grabski M, Munafò MR. The Association
of Cigarette Smoking With Depression and Anxiety: A System-
atic Review. Nicotine Tob Res 2017;19:3–13.
51. Kooistra LC, Wiersma JE, Ruwaard JJ, Riper H, Penninx BWJH,
van Oppen P. Six-year healthcare trajectories of adults with
anxiety and depressive disorders: Determinants of transition
to specialised mental healthcare. J Aect Disord 2018;241:226–
34.
