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\begin{document}

\title{EFFECT OF SHIFT WORK IN INTENSIVE CARE ON ATTENTION DISORDER IN NURSES}



\author[1]{Süleyman Dönmezdil}%
\author[1]{Songül Araç}%
\affil[1]{Diyarbakir Gazi Yasargil Training and Research Hospital}%


\vspace{-1em}



  
  \date{June 14, 2024}


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\selectlanguage{english}
\begin{abstract}
Aim: The purpose of this study is to determine the level of attention
between shifts and to make recommendations about the regulation of
shifts. Methods:The researchers applied the Hamilton Depression Rating
Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), Pittsburgh Sleep
Quality Index (PSQI) and Stroop color word interaction test (SCWI) in 72
intensive care workers working in different shifts. Result: The study
included a total of 72 participants, including 30 (43.3\%) females and
42 (58.3\%) males. There were statistically significant differences
between the groups in the sub-items of the HAM-D and SCWI test (Table
3). There was a significant elongation in the night shift employees at
all times within the SCWI sub-items. A significant height in the number
of errors and corrections in the cards applied in the continuation of
the test was also determined in the night shift group. Conclusion: This
study revealed a significant decrease in the level of attention in the
night-shift compared to the day-shift. This increase in attention
deficit may also be a preventable cause of increased mortality in the
night-shift What is already known about this topic? * Mortality rates in
intensive care units are higher than in other clinics. What this paper
adds? * Our study reported significantly poor results of the SCWI test
in the night-shift compared to the day-shift. The implications of this
paper: * This study revealed a significant decrease in the level of
attention in the night-shift compared to the day-shift. We believe that
it will be beneficial to shorten the shift times, to keep the number of
patients per staff at international standards, to set active rest
periods and to plan personnel and hours to reduce the lack of attention
observed in the night shift. KEYWORDS Attention, healthcare worker,
night-shift, intensive care%
\end{abstract}%



\sloppy


\textbf{Summary statement}

What is already known about this topic?

Mortality rates in intensive care units are higher than in other
clinics.

What this paper adds?

Our study reported significantly poor results of the SCWI test in the
night-shift compared to the day-shift.

The implications of this paper:

This study revealed a significant decrease in the level of attention in
the night-shift compared to the day-shift. We believe that it will be
beneficial to shorten the shift times, to keep the number of patients
per staff at international standards, to set active rest periods and to
plan personnel and hours to reduce the lack of attention observed in the
night shift.

\textbf{Keywords}

Attention, healthcare worker, night-shift, intensive care

\textbf{Introduction}

Intensive care units are the units that provide uninterrupted health
services for the treatment of critically ill patients. Although the
indications for hospitalization in intensive care units include
departmental and diagnostic differences, the criticality of the
patient's condition is considered a general-accepted reason for
hospitalization. The general international rule is that qualified and
certified healthcare professionals should work in intensive care units.
In this regard, our country and many other countries provide in-service
trainings and try to increase the number of qualified health personnel.

Mortality rates in intensive care units are higher than in other
clinics. Studies have found different mortality rates, ranging from 8 to
30\%\textsuperscript{1--3}. Common causes of mortality include
respiratory diseases, coronary heart diseases, infectious causes, and
cerebrovascular diseases\textsuperscript{1,4}. There are studies
reporting higher rates of mortality in intensive care units in the
night-shift and at the weekend shifts compared to the weekday
day-shift\textsuperscript{5--8}. In these studies, the leading causes of
mortality included insufficient number of healthcare professionals,
difficult access to invasive procedures, and the presence of cases with
high mortality rates, etc.

There are studies in the literature reporting that the level of
attention decreases in night shifts. In a study, Y\selectlanguage{polish}ı\selectlanguage{english}ld\selectlanguage{polish}ı\selectlanguage{english}z et
al\textsuperscript{9}revealed lower scores of the visual attention test
for women working in the night-shift compared to those working in the
day-shift. In another study, Osterode et al. found a decrease in
cognitive functions in the night-shift in the visual memory test applied
to physicians.

In health care services in our country, the night-shift usually starts
from the end of the day-shift at 16.00 and continues until the beginning
of the day-shift at 08.00. In case of insufficient number of healthcare
professionals, the duration of the shift can be extended up to 24 hours.
For healthcare professionals working in the Intensive Care Units at the
Gazi Ya\selectlanguage{polish}ş\selectlanguage{english}argil Training and Research Hospital, which is the center of our
research, the night-shift covers sixteen hours from 16.00 to 08.00 on
the next day. The day shift group was selected from nurses working in
the day shift for the past month. Thus, it was aimed to exclude the
possibility of shift-related deterioration in sleep rhythm and hormonal
balance in day-shift workers.

\textbf{Materials and Methods}

The present study was conducted on nurses working in the reanimation
unit and internal medicine, coronary and neurology intensive care units
at Gazi Ya\selectlanguage{polish}ş\selectlanguage{english}argil Training and Research Hospital between January 20, 2020
and March 20, 2020. The sample of the study was selected from nurses
working in intensive care units, independent of all other departments in
the hospital. The day-shift group included nurses working from 08.00 to
16.00, and the night-shift group included nurses working from 16.00
until 08.00 on the next day.

The study included a total of 80 volunteers, including 40 day-shift and
40 night-shift employees, by getting their informed consent and giving
information that they can leave the research at any time. The data of
the five volunteers were excluded due to their declaration of requesting
to leave the study. The study excluded a volunteer because of declaring
the use of benzodiazepine, which is likely to impair executive
functions, after participation in the study and 2 volunteers due to
incomplete completion of the scale. The data of 72 volunteers, 31 in the
day-shift and 41 in the night-shift, were included in the evaluation.

The demographic data of the sample groups were obtained by the
sociodemographic data form prepared by the researchers. The researchers
applied the Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety
Rating Scale (HAM-A), Pittsburgh Sleep Quality Index (PSQI) and Stroop
color word interaction test (SCWI) in both groups. All tests were
performed at 15:00 in the day-shift group and at 7:00 in the night-shift
group. Thus, tests were applied in both groups one hour before the end
of the shift.

Evaluation

The Hamilton depression rating scale measures the level and the change
in severity of depression. It contains seventeen questions, scored
between zero and four, providing the highest total score of 51.

Hamilton anxiety rating scale was prepared by Hamilton (1959)(Hamilton,
1959) to determine the level of anxiety and distribution of symptoms and
to measure the change in severity. It consists of 14 items that question
both mental and physical symptoms.

The Pittsburg sleep quality index was developed by Buysse et al
(1989)\textsuperscript{11} PSQI is a 19-item self-report scale that
evaluates sleep quality and disorder in the last month.

Stroop color word interaction test (SCWI) is a neuropsychological test
that reflects the activity of the frontal region. It measures the
ability to suppress a habitual behavior pattern and execute unusual
behavior, which are among the frontal lobe functions. SCWI task and
related tests are accepted as the golden standard for measuring
attention level in the literature. \textsuperscript{12}

Statistical Analysis

Statistical analysis was performed using Statistical Package for Social
Sciences (SPSS) software version 22.0 (SPSS, Chicago, Ill., USA).
Analysis of categorical data was performed using Chi-square test. The
Student's t-test for paired groups was used to analyze quantitative
data. A p value of \textless{}0.05 was considered statistically
significant.

Ethical Approval

This study was approved by the ethics committee of Gazi Ya\selectlanguage{polish}ş\selectlanguage{english}argil
Education and Research Hospital with the decision numbered 410 and dated
January 17, 2020. Written informed consent was obtained from all
participants at each stage of the study.

\textbf{Results}

The study included a total of 72 participants, including 30 (43.3\%)
females and 42 (58.3\%) males. Analysis of sociodemographic data did not
show a significant statistical difference between groups. Most of the
participants lived with their families (76.4\%). In 88.9\% of the
participants, there was no previous application for psychiatry
outpatient clinic. In the remaining socio-demographic data, there was no
statistically significant difference between the groups (Table 1).

There were no significant difference between the groups in terms of tea
and coffee consumption. This was important in that the cognitive test
applied eliminated the possibility of being affected by psychostimulant
intake, such as caffeine. There was no significant difference in the
remaining sociodemographic data (Table 2).

There were statistically significant differences between the groups in
the sub-items of the HAM-D and SCWI test (Table 3). There was a
significant elongation in the night shift employees at all times within
the SCWI sub-items. A significant height in the number of errors and
corrections in the cards applied in the continuation of the test was
also determined in the night shift group. This indicates that cognitive
impacts are higher in night shift workers.

Although there were a difference in PSQI and HAM-A scores between
groups, this difference was not statistically significant (Table 3).

\textbf{Discussion}

Human physiology is arranged to sleep at night and to be awake in the
daytime. This can be evidenced by hormones released in the circadian
rhythm. Among these hormones, melatonin is released during nighttime
sleep, but not during daytime sleep. Sudden changes in melatonin release
can produce a jet-lag-like condition, resulting in a disruption in human
mental health and sleep rhythm. Similarly, the shift system that
requires staying awake at night can affect sleep physiology and many
other hormonal mechanisms. Studies have reported that the night-shift
can be associated with a wide range of negative conditions, from
decreased visual acuity, lack of attention and sleep disorders to
psychiatric comorbidities.

There are many studies on psychiatric disorders associated with
nighttime insomnia. These studies addressed problems such as impaired
sleep physiology, decreased quality of life, depression and anxiety
disorders. However, there is no study literature investigating the
concentration and maintenance of attention in healthcare professionals
in intensive care units and the risks that might otherwise arise for
patients.

The necessity of providing uninterrupted health care services worldwide
requires many healthcare professionals to work in the night-shift
system. It would not be wrong to say that health problems associated
with night-shifts can also be seen in healthcare workers.

As per their duties, healthcare professionals are responsible for
carefully monitoring the vital signs of patients and correcting
potential disorders. These disorders may be respiratory or cardiac
problems that require immediate action. The timely recognition and
correction of these situations is directly related to the ability of
healthcare professionals to collect and maintain their attention.

Indeed, in a study on shift-working nurses, Zion et
al.\textsuperscript{13} reported poorer results of cognitive function
tests at 3am than at 7am, suggesting that the night-shift caused a
disruption in cognitive functions during night hours. Our study also
reported significantly poor results of the SCWI test in the night-shift
compared to the day-shift. This study has shown that a more regular
circadian rhythm, attention-enhancing activities (visit, patient
relatives visit, patient care, etc.) and a higher concentration of
people in the day-shift than at night-shift, may result in faster
collection of the attention and increased ability to focus due to the
greater number of stimuli. Lack of stimuli and deterioration of sleep
rhythm may result in distraction and loss of vital data that may require
immediate attention. This highlights the patient-related causes of high
mortality in the night-shift, as well as factors associated with
healthcare professionals. As a result, deaths due to health personnel
are among the preventable causes of death.

Studies that prove a decrease in attention level in night-shift workers
also draw attention to the cases of self-injury due to carelessness in
healthcare workers. Niu et al.\textsuperscript{5} applied the D2 test to
nurses working in 3 shifts (day-, evening-, and night-shift), and
reported an increase in selective error rate and a decrease in attention
level in the night-shift. In this study, there was a day-shift group
including nurses working from 08.00 to 16.00 and a night-shift group
including nurses working from 16.00 until 08.00 on the next day. Given
the longer duration of the night-shift (16 hours), the longer duration
of the night-shift (16 hours), it is suggested that the decrease in the
attention level of workers in the night-shift may be due to longer
periods of work and sleeplessness. The longer duration of the
night-shift in this study shows the potential higher rate of poor
results when compared to the working hours in the studies by Niu et
al.\textsuperscript{5}. SCWI test showed a significant deterioration in
duration, error and correction scores in the night-shift group, which
seems to be consistent with the data of the literature studies.

Apart from the reduction in the attention level, it is also
scientifically possible to predict an increase in the level of fatigue
among night-shift workers. The study by Thompson et
al.\textsuperscript{14} can be considered as proof of this prediction.
It was reported in this study that performance-based fatigue increased
in those working in the night-shift compared to those in the day-shift.
It should not be ignored that serious risks may arise for both the
patient and the healthcare professionals in case of a decrease in the
level of attention in addition to the increase in fatigue. It should be
remembered that there may be errors in the regulation of treatments, as
well as an increased risk of self-injury in healthcare workers. It can
be argued that the risk of injury to patients or healthcare workers will
be higher for the night-shift group in our study, given the longer
duration of the night-shift in our study (16 hours) compared to the
duration of the night-shift (12 hours) in the study by Thompson et
al.\textsuperscript{14}

The imbalance of melatonin levels are known to be involved in the
etiology of depression\textsuperscript{15,16}. A study of hormonal
changes reported a decrease in melatonin levels and an increase in
inflammatory markers in night-shift workers\textsuperscript{17,18}.
Depending on the imbalance of melatonin levels, a depressive mood
becomes inevitable in the night-shift employees. In our study, a
significant difference in the scores of Hamilton depression scale
between the employees working in the night-shift and day-shift was found
to be compatible with the literature. Although Gumenyuk et
al.\textsuperscript{19}reported a disturbance in sleep quality as well
as distraction in night-time healthcare workers, there was no difference
between the groups in our study in terms of the results of PUKI, a test
that assesses sleep quality. The difference between the sleep quality
scores of our study and the study by Gumenyuk et
al.\textsuperscript{19}can be attributed to differences in sample size.
Gumenyuk et al. used a total of 28 subjects in two groups.

This study was planned based on the hypothesis that a decrease in
attention levels may have a significant effect on patient mortality.
Literature studies have reported higher mortality rates in nighttime and
weekend shifts in patients hospitalized in intensive care units.
Although the researchers have tried to attribute high mortality rates to
factors such as diagnostic and interventional disruptions, there is an
overlook of the high rate of factors that make it difficult to collect
attention during the weekend and night-shifts. Attention levels can be
negatively affected by factors such as lower concentration of people and
longer shift times during weekend and night-shifts, which is believed to
contribute to an increase in mortality rates. In addition, the lower
number of employees in night and weekend shifts should not be
overlooked. The excessive number of chief nurses, support staff,
clinicians and intensive care physicians during the day-shift causes the
distribution of the burden of patient care. However, we believe that the
absence of support staff in the night-shift, the decrease in the
frequency of intensive care visits by the physician working in multiple
units, and the excess of the number of patients per nurse also
contributes to the reduction of attention by increasing the workload.

This study revealed a significant decrease in the level of attention in
the night-shift compared to the day-shift. We believe that it will be
beneficial to shorten the shift times, to keep the number of patients
per staff at international standards, to set active rest periods and to
plan personnel and hours to reduce the lack of attention observed in the
night shift.

\textbf{References}

1. Ara\selectlanguage{ngerman}ç E, Kaya \selectlanguage{polish}Ş, \selectlanguage{english}Parlak E, et al. Evaluation of infections in
intensive care units: A multicentre point-prevalence
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2. Haque M, Sartelli M, McKimm J, Bakar MA. Health care-associated
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3. WHO. Report on the Burden of Endemic Health Care-Associated Infection
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5. Niu SF, Chu H, Chen CH, et al. A Comparison of the Effects of Fixed-
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6. Laupland KB, Shahpori R, Kirkpatrick AW, Stelfox HT. Hospital
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7. Lee SK, Lee DSC, Andrews WL, Baboolal R, Pendray M, Stewart S. Higher
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8. Lin YC, Ho KJ. Night-shift work and risk of compromised visual acuity
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10. Hamilton M. The assessment of anxiety states by rating.\emph{British
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12. MacLeod CM. The Stroop task: The ``gold standard'' of attentional
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13. Zion N, Shochat T. Cognitive functioning of female nurses during the
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doi:10.1080/07420528.2018.1497642

14. Thompson BJ, Stock MS, Banuelas VK. Effects of Accumulating Work
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15. \selectlanguage{ngerman}Özçelik F, Erdem M, Bolu A, Gülsün M. Melatonin: Genel Özellikleri
ve Psikiyatrik Bozukluklardaki Rolü - Melatonin: General Features and
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16. Macchi MM, Bruce JN. Human pineal physiology and functional
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17. Sundberg I, Rasmusson AJ, Ramklint M, Just D, Ekselius L, Cunningham
JL. Daytime melatonin levels in saliva are associated with inflammatory
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18. Nabavi SM, Nabavi SF, Sureda A, et al. Anti-inflammatory effects of
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and nutrition} . 2019;59:S4-S16. doi:10.1080/10408398.2018.1487927

19. Gumenyuk V, Howard R, Roth T, Korzyukov O, Drake CL. Sleep Loss,
Circadian Mismatch, and Abnormalities in Reorienting of Attention in
Night Workers with Shift Work Disorder. \emph{Sleep} .
2014;37(3):545-556. doi:10.5665/sleep.3494\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Day-shift n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Night-shift n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Total n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
X\textsuperscript{2} p\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Gender Female Male\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
17 (56.7) 14 (33.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
13 (43.3) 28 (66.7)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
30 (41.7) 42 (58.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3.886 0.58\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Marital status Single Married\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
13 (33.3) 18 (54.5)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
26 (66.7) 15 (45.5)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
39 (54.2) 33 (45.8)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3.280 0.95\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Lives with Family / spouse-child Alone\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
24 (43.6) 7 (41.2)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
31 (56.4) 10 (58.9)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
55 (76.4) 17 (23.6)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.032 1\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Psychiatric Admission Yes No\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3 (37.5) 28 (43.8)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
5 (62.5) 36 (56.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
8 (11.1) 64 (88.9)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.113 1\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 1} : Analysis of the socio-demographic data of the
participants\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Day-shift n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Night-shift n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Total n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
X\textsuperscript{2} p\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Gender Female Male\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
17 (56.7) 14 (33.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
13 (43.3) 28 (66.7)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
30 (41.7) 42 (58.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3.886 0.58\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Marital status Single Married\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
13 (33.3) 18 (54.5)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
26 (66.7) 15 (45.5)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
39 (54.2) 33 (45.8)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3.280 0.95\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Lives with Family / spouse-child Alone\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
24 (43.6) 7 (41.2)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
31 (56.4) 10 (58.9)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
55 (76.4) 17 (23.6)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.032 1\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Psychiatric Admission Yes No\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3 (37.5) 28 (43.8)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
5 (62.5) 36 (56.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
8 (11.1) 64 (88.9)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.113 1\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2:} The sociodemographic data of the groups and the
frequency of psychoactive products taken while on duty. No statistically
significant difference was found between the data.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Day-shift n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Night-shift n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
Total n (\%)\strut
\end{minipage} & \begin{minipage}[b]{0.19\columnwidth}\raggedright\strut
X\textsuperscript{2} p\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Gender Female Male\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
17 (56.7) 14 (33.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
13 (43.3) 28 (66.7)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
30 (41.7) 42 (58.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3.886 0.58\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Marital status Single Married\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
13 (33.3) 18 (54.5)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
26 (66.7) 15 (45.5)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
39 (54.2) 33 (45.8)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3.280 0.95\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Lives with Family / spouse-child Alone\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
24 (43.6) 7 (41.2)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
31 (56.4) 10 (58.9)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
55 (76.4) 17 (23.6)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.032 1\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
Psychiatric Admission Yes No\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
3 (37.5) 28 (43.8)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
5 (62.5) 36 (56.3)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
8 (11.1) 64 (88.9)\strut
\end{minipage} & \begin{minipage}[t]{0.19\columnwidth}\raggedright\strut
0.113 1\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 3:} The relationship between HAM-D, HAM-A, PSQI and Stroop
data between groups. HAM-D: Hamilton Depression scale, HAM-A: Hamilton
Anxiety Scale, PSQI: Pittsburg Sleep Quality Index SCWI: Stroop color
word interaction test *: p \textless{}0.05 **: p \textless{}0.01, ***: p
\textless{}0.001

\selectlanguage{english}
\FloatBarrier
\end{document}

