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The present study aims to examine the frequency of sleep disorders and the
level of sleep quality, as well as their relationship with health-related
quality of life in cancer patients.
Methods:
This multi-center cross-sectional survey included 333 cancer patients ranging
in age from 16 to 72 years, between June 15, 2017, and August 30, 2018 at
the Ankara Oncology Hospital and Erciyes University Kemal Dedeman Oncology
Hospital Polyclinic. Data were collected via various surveys conducted
through face-to-face interviews, including following measurement tools:
Short Form 36 Health Questionnaire, the Pittsburgh Sleep Quality Index, the
Epworth Sleepiness, and the Berlin Sleep Questionnaire for obstructive sleep
apnea. Face-to-face interviews were carried out with patients who presented
for an initial examination or follow-up and were awaiting their
appointments.
Results:
The most commonly reported sleep disorders were daytime sleepiness (36.9%),
sleep respiratory disorders (34.8%), insomnia (29.4%), and parasomnias
(28.8%). Good sleepers were found to have significantly higher physical
(40.20±10.08 vs. 33.21±8.06; P<0.001) and mental
component scores (43.54±8.25 vs. 38.20±7.52; P<0.001)
than poor sleepers. Conversely, individuals with insomnia (P<0.01),
daytime sleepiness (P<0.001), sleep-respiratory disorders
(P<0.05), and bruxism (P<0.001) showed significantly lower
scores in both physical and mental components. Additionally, those with
restless legs syndrome had a significantly lower physical component score
(P<0.001), and those with parasomnias had significantly lower mental
component scores.
Conclusion:
Cancer patients exhibited moderate average sleep quality scores, with over
half of them demonstrating low quality sleep patterns. Sleep disorders
significantly impacted their health-related quality of life.
Cancer's rising incidence, partly due to an aging population, is
noteworthy. By 2030, the number of older adults with cancer is expected to
increase by 67% from 2010 in the United States [1]. Advances in early detection and treatment have extended cancer
patients' life expectancy. Consequently, effective treatment, minimizing
treatment side effects, and improving patients' quality of life (QoL) are
vital goals. Identifying factors that hinder cancer patients' daily
activities, functional capacity, and QoL is crucial. Factors like pain,
depression, fatigue, and sleep disorders still significantly affect their QoL
[2,3].
Sleep disorders, affecting 9%–33% across ages [4], are particularly concerning for cancer patients,
impairing their daily life and health-related QoL (HRQoL) [5,6]. These disorders
are more severe in cancer patients due to the disease's direct impact,
treatment side effects, and comorbid conditions [7]. Insomnia, a common sleep disorder, affects daily activities and
is more prevalent in cancer patients (30%–69%) compared to the general
adult population (30%) and elderly (23%–50%) [8]. In some cancer cases, insomnia prevalence can be as high
as 30%–93% [9].
Sleep disorders and symptom burden greatly diminish older cancer patients'
health, functionality, and QoL, potentially worsening disease progression and
side effects [10]. Older patients with
sleep disturbances face physical and psychosocial challenges, including
musculoskeletal, gastrointestinal issues, anxiety, and depression [11]. Insomnia correlates with reduced daily
activity, increased fall risk, and cognitive issues [12]. Factors like hospitalization, pain, treatment side
effects, immune alterations, and physiological changes contribute to sleep
disorders. Insomnia, combined with depression and anxiety, can adversely affect
long-term QoL. It impairs immune functions by altering cytokine expression,
impacting disease trajectory and mortality [13]. Insomnia is also associated with decreased natural killer cell
numbers and activity due to abnormal cortisol synthesis [13,14]. Recognizing,
diagnosing, and treating sleep disorders in cancer patients are essential. This
helps manage disease prognosis, prevent recurrence, and enhance patient QoL.
Despite their importance, sleep disorders are often overlooked in patient
care.
Objectives
This study aimed to evaluate sleep disorders and sleep quality, along with their
impact on the overall QoL, by using universally recognized measurement tools
that are highly sensitive and specific. These tools were based on self-reported
data and diagnostic questions administered to cancer patients.
Methods
Ethics statement
The Ethics Committee in Clinical Research on Human Subjects at Erciyes
University, Faculty of Medicine, approved this study (Decision date and no.:
2013/232). All participants provided both verbal and written consent before data
collection commenced.
Study design
This was a multi-center cross-sectional survey study. It was described according
to the STROBE statement (https://www.strobe-statement.org/).
Setting
This study was conducted with 333 volunteer cancer patients ranging in age from
16 to 72 years, between June 15, 2017, and August 30, 2018. Face-to-face
interviews were carried out with patients who presented at the Ankara Oncology
Hospital and Erciyes University Kemal Dedeman Oncology Hospital Polyclinic for
an initial examination or follow-up and were awaiting their appointments. As
tools for data collection, we utilized self-administered questionnaires, scales,
indexes, and a selection of diagnostic and support questions.
Participants
Participants who were unable to complete the interview and questionnaires due to
medical reasons (e.g., cognitive impairment), were excluded from the study. The
response rate was 90%.
Variables
Demographic data and topics of questionnaires were outcome variables.
Measurement
The research data were collected using questionnaires that addressed
sociodemographic variables (8 questions), the Short Form 36 Health Questionnaire
(SF-36; 11 questions) [15], the
Pittsburgh Sleep Quality Index (PSQI; 19 questions), the Epworth Sleepiness
Scale (ESS; 8 questions) [16,17], and the Berlin Sleep Questionnaire for
obstructive sleep apnea (10 questions) [18]. Additional information was obtained through questions derived
from the original scales' global diagnostic criteria for insomnia (3
questions) [19], parasomnias (6
questions), restless legs syndrome (RLS; 5 questions) [20], and bruxism (3 questions). A more specific description
on the measurement tools are presented in Supplement 1. Socio-demographic data
was obtained from the participants that are presented in Supplement 2.
Bias
Since the subject population participated in this survey study voluntarily, there
may be sampling bias. The persons who did not participated in the study, may be
in worse health or a state of lack of strength.
Study size
Sample size estimations were not made since only voluntary participants were
included during the limited period.
Statistical methods
The data were analyzed using the IBM SPSS Statistics Standard Concurrent User V
25 (IBM, Armonk, NY, USA) software. To assess the normality of quantitative
variables, the Shapiro-Wilk test was employed. Descriptive statistics for
continuous numerical variables that followed a normal distribution are presented
as the mean±SD. For variables that conformed to parametric assumptions,
Student's t-test was utilized, while the Mann-Whitney U test was applied
to those that did not. The chi-square test and Fisher exact test were used for
categorical variables. Sleep disorders were converted into dichotomous (yes/no)
data by employing global scale/index scores, cut-off points, and diagnostic
criteria questions. Linear regression analysis was conducted to determine the
impact of sleep disorders and sleep quality on physical and mental health QoL.
In this analysis, the physical health QoL summary score (PCS) and mental health
QoL summary score (MCS) were treated as dependent variables. Independent
variables included the PSQI, RLS, sleep-disordered breathing, parasomnias,
daytime sleepiness, and total insomnia scores. The significance level for
statistical evaluation was set at P<0.05.
Results
Participants
Socio-demographic characteristics were presented in Table 1. A significant proportion of cancer patients (83.8%)
reported being unemployed, non-smokers (88.8%), and non-alcohol drinkers (92.8%)
1. Regarding treatment, 25.8% of cancer patients underwent isolated
chemotherapy, 1.5% received only radiotherapy, and 14.1% underwent a combination
of chemotherapy and radiotherapy.
Table 1.
Socio-demographic characteristics of oncology patients
(n=333)
Variables
No.
%
Gender
Female
188
56.5
Male
145
43.5
Age group (years),
mean±SD: 50.81±11.31 (min-max:16−72)
16−35
32
9.6
36−45
59
17.7
46−55
109
32.7
56−72
133
39.9
Marital status
Married
291
87.4
Single/separated/widowed
42
12.6
Educational status
Primary school
148
44.4
Secondary and high school
103
30.9
University
26
7.8
Monthly income (TL),
mean±SD: 1,409.10±818.45 (min-max:
200−5,900)
Low (200−1,400)
194
58.3
Middle
(1,401−5,900)
139
41.7
Active working status
Working
54
16.2
Not working
279
83.8
Smoking
Yes
40
12
No
293
88.8
Alcohol consumption
Yes
24
7.2
No
309
92.8
PSQI, mean±SD:
6.17±3.83
Good sleepers (≤5
points)
136
40.8
Poor sleepers (>5
points)
181
59.2
Stage of cancer
Receiving treatment
261
78.3
Completed treatment
72
21.7
Types of treatment
Chemotherapy
86
25.8
Radiotherapy
5
1.5
Chemotherapy+radiotherapy
47
14.1
Treatment for medical
support
9
2.7
Chemotherapy and medical
support
80
24
Chemotherapy, radiotherapy,
and medical support (e.g., pain control, intake drugs and
screening)
Number of cancer patients according to the organs or systems, and
sex
When assessing the prevalence of cancer by sex, cancers of the respiratory
system were the most common in men, accounting for 33.8% of cases. Cancers
of the gastrointestinal system followed at 25.5%, and hematological cancers
ranked third at 20.0%. In women, cancers of the breast and endocrine organs
were the most prevalent, making up 41.5% of cases. Gynecological cancers,
including those of the ovary, fallopian tubes, uterus, cervix, vagina, and
vulva, were the second most common (18.1%), and hematological cancers were
the third most common, representing 13.3% of cases.
Number of cancer patient according to organs or systems are presented in
Table 2.
Table 2.
Distribution of cancer according to organs or systems by
gender
Types of cancer
No. (%)
Statistical
assessment
Male
Female
Total
χ2/P
Gastrointestinal system
(esophagus, stomach, duodenal, colorectal, hepatobiliary,
pancreatic) cancers
Respiratory system
(lung-bronchial, oto-rhino-laryngeal) cancers
49 (84.5)
9 (15.5)
58 (17.4)
33.434/<0.001
Other (skin and its appendages;
malignant melanoma, squamous cell, orthopedic, primary bone,
etc.) cancers
30 (53.6)
26 (46.4)
56 (16.8)
2.754/0.198
Ages of cancer patients
Approximately 40% of the participants were elderly. The treatments for these
patients typically include chemotherapy and radiotherapy. The most common
types of cancer among the elderly were breast and endocrine system cancers
(including breast and thyroid) at 48.5%, respiratory system cancers (such as
lung, bronchus, and oto-rhino-laryngeal) at 33.2%, and gastrointestinal
system cancers (including colorectal, hepatobiliary, and pancreatic) at
18.3%. Compared to other age groups, elderly participants tended to have the
same types of cancers. The prevalence of sleep disorders among elderly
cancer patients was as follows: daytime sleepiness in 41.3% (55
individuals), sleep-related respiratory disorders in 27% (36 individuals),
insomnia in 20.3% (27 individuals), and parasomnias in 11.4% (15
individuals). It is noteworthy that RLS and bruxism were not observed as
sleep disorders in this group, although they were common among other
participants.
Sleep disorders
The prevalence of sleep disorders among cancer patients was presented in
Table 3. While sleep disorders
did not show statistically significant relationships with sex, with the
exception of parasomnias, they tended to be more severe in men. Excessive
daytime sleepiness (38.6% vs. 35.6%), sleep respiratory disorders (38.6% vs.
34.9%), insomnia (33.1% vs. 26.6%), parasomnias (34.5% vs. 24.5%, P=0.045),
and bruxism (19.3% vs. 13.8%) were more prevalent in men than in women.
Conversely, RLS, which was generally reported in 23.1% of patients, was more
common in women than in men (25.5% vs. 20.0%; Table 3).
Table 3.
Distribution of cancer patients with sleep disorders according to
gender
Sleep disorders
No. (%)
χ2/P
Male
Female
Total
Restless legs syndrome
29 (20.0)
48 (25.5)
77 (23.1)
1.409/0.242
Insomnia
48 (33.1)
50 (26.6)
98 (29.4)
1.669/0.196
Parasomnias
50 (34.5)
46 (24.5)
96 (28.8)
4.002/0.045
Excessive daytime sleepiness
56 (38.6)
67 (35.6)
123 (36.9)
0.313/0.576
Sleep respiratory disorders
50 (34.5)
66 (35.1)
116 (34.8)
0.014/0.906
Bruxism
28 (19.3)
26 (13.8)
54 (16.2)
1.810/0.180
Sleep quality
The mean PSQI score among cancer patients was 6.17±3.83 (95% CI,
5.75−6.58; P<0.001). Of these patients, 136 (40.8%) had normal
(good) sleep quality, with PSQI scores of 5 or less, while 181 (59.2%)
experienced poor sleep quality, with PSQI scores ranging from 6 to 16. The
mean PSQI score for men was slightly higher at 6.30±3.82, compared to
6.06±3.85 for women, although this difference was not statistically
significant (P>0.05; Table 1).
All sleep disorders, except for parasomnias, showed significant associations
with sleep quality (Table 4).
Table 4.
Association between sleep disorders and level of sleep quality in
cancer patients (n=333)
Sleep disorders
PSQI score
Level of sleep
quality
Mean±SD
P-value
Good (PSQI: ≤5
points)
Poor (PSQI: 6−16
points)
Total
χ2/P
No. (%)
No. (%)
No. (%)
Restless legs
syndrome
Yes
7.57±3.91
<0.001
32 (41.6)
45 (58.4)
77 (23.1)
6.590/0.010
No
5.75±3.71
149 (58.2)
107(41.8)
256 (76.9)
Insomnia
Yes
8.67±3.83
<0.001
26 (26.5)
72 (73.5)
98 (29.4)
43.331/<0.001
No
5.12±3.32
155 (66.0)
80 (34.0)
235 (70.6)
Parasomnias
Yes
7.09±3.96
0.005
45 (46.9)
51 (53.1)
96 (28.8)
3.032/0.090
No
5.79±3.72
101 (42.6)
136 (57.4)
237 (71.2)
Epworth Sleepiness
Scale
Yes
7.47±3.99
<0.001
47 (38.2)
76 (61.8)
123 (36.9)
20.486/<0.001
No
5.40±3.53
134 (63.8)
76(36.2)
210 (63.1)
Sleep respiratory
disorder
Yes
7.07±3.87
0.002
48 (41.4)
68 (58.6)
116 (34.8)
12.079/0.001
No
5.68±3.73
133 (61.3)
84 (38.7)
217 (65.2)
Bruxism
Yes
7.59±4.28
0.003
18 (33.3)
36 (66.7)
54 (16.2)
11.479/0.001
No
5.89±3.68
163 (58.4)
152 (45.6)
279 (83.8)
PSQI, Pittsburgh Sleep Quality Index.
Upon investigating the relationship between mean PSQI scores, sleep quality
level, and sleep disorders, it was revealed that individuals experiencing
excessive daytime sleepiness (36.9%) had a mean PSQI score of
7.47±3.99 (P<0.001), with 61.8% of them exhibiting poor sleep
quality (χ2=12.079, P=0.001). Additionally, a significant
positive association was noted between daytime sleepiness and sleep quality
(χ2=20.486; P<0.001). Those with
sleep-disordered breathing (34.8%) had a mean PSQI score of 8.67±3.83
(P<0.001), and 58.6% were found to have poor sleep quality
(χ2=12.079, P=0.001). Participants with insomnia
(29.4%) had a mean PSQI score of 8.67±3.83 (P<0.001), with
73.5% reporting poor sleep quality (χ2=43.331;
P<0.001). The mean PSQI score for patients with RLS (23.1%) was
7.57±3.91 (P<0.001), and 58.4% had poor sleep quality
(χ2=6.590, P=0.010). Lastly, participants with bruxism
(16.2%) had a mean PSQI score of 7.59±4.28 (P=0.003), with 66.7%
experiencing poor sleep quality (χ2=11.479, P=0.001).
Patients with insomnia, bruxism, and RLS exhibited higher mean PSQI scores
than their counterparts, indicating that these groups had lower sleep
quality levels.
Associations between sleep disorders and health-related quality of
life
When assessing the relationship between sleep disorders and HRQoL using
summary scores for physical and mental health components, it was observed
that the average mental health QoL scores across all sleep disorders were
significantly higher than those for physical health QoL. However, when
evaluating physical health QoL on its own, patients with all types of sleep
disorders—except for parasomnia—exhibited significantly lower
scores. Conversely, patients with all sleep disorders, with the exception of
RLS, had significantly lower mental health QoL scores. Additionally,
individuals with RLS had the lowest PCS scores, while those with bruxism had
the lowest MCS scores (Table 5).
Table 5.
Association between sleep disorders and health-related QoL in
cancer patients (n=333)
Sleep disorders
No.
SF-36 summary
scores
PCS score
P-value
MCS score
P-value
Mean±SD
Mean±SD
Restless legs
syndrome
Yes
77
31.30±8.38
<0.001
39.10±7.63
0.120
No
256
37.50±9.44
40.77±8.39
Insomnia
Yes
98
33.51±9.13
0.002
38.46±7.67
0.006
No
235
37.13±9.56
41.19±8.36
Parasomnia
Yes
95
36.23±9.82
0.842
38.20±8.82
0.002
No
238
36.00±9.48
41.27±7.85
Epworth Sleepiness
Scale
Yes
123
32.05±7.19
<0.001
38.22±7.47
<0.001
No
210
38.42±10.00
41.65±8.42
Sleep respiratory
disorders
Yes
116
34.30±8.36
0.009
38.67±7.58
0.004
No
217
37.01±10.04
41.30±8.45
Bruxism
Yes
54
31.68±7.92
<0.001
36.79±7.31
<0.001
No
279
36.92±9.63
41.08±8.24
Sleep quality
Good sleepers (≤5
points)
136
40.20±10.08
<0.001
43.54±8.25
<0.001
Poor sleepers (>5
points)
197
33.21±8.06
38.20±7.52
QoL, quality of life; SF-36, Short Form-36; PCS, physical
component summary; MCS, mental component summary.
Sleep quality and health-related quality of life
All sub-dimensions of the SF-36 and the summary scores for the physical and
mental health components were found to be significantly lower in poor
sleepers. The scores for the physical and emotional role difficulty
sub-dimensions were particularly impacted, markedly reducing the QoL in
these patients. Poor sleep quality was found to affect the physical health
component of QoL more significantly than the mental health component, as
shown in Table 6. Conversely,
patients classified as good sleepers had significantly higher scores in the
sub-dimensions of bodily pain, social functioning, and mental health than
those classified as poor sleepers. These patients also had relatively higher
scores in the sub-dimensions of vitality, general health, and physical
functioning.
Table 6.
Association between sleep quality and health-related QoL in
cancer patients (n=333)
SF-36 domains
Level of sleep
quality
Good sleepers (PSQI: 0−5
points)
Poor sleepers (PSQI: 6−16
points)
Overall SF-36
P-value
(n=181)
(n=152)
(n=333)
PF
52.48±34.21
34.47±26.95
44.26±32.34
<0.001
RP
40.33±44.83
8.55±23.91
25.82±40.01
<0.001
BP
61.51±24.10
42.90±22.35
53.02±25.07
<0.001
GH
53.76±18.05
41.82±17.11
48.31±18.58
<0.001
VT
54.58±19.23
40.88±17.18
48.33±19.53
<0.001
SF
62.63±25.65
46.62±23.59
55.33±25.95
<0.001
RE
47.14±45.94
15.57±33.42
32.73±43.59
<0.001
MH
62.29±15.81
51.84±14.75
57.52±16.17
<0.001
PCS
40.20±10.08
33.21±8.06
36.07±9.56
<0.001
MCS
43.54±8.25
38.20±7.52
40.38±8.24
<0.001
Values are presented as mean±SD.
QoL, quality of life; SF-36, Short Form-36; PSQI, Pittsburgh
Sleep Quality Index; PF, physical function; RP, role difficulty
(physical); BP, bodily pain; GH, general health; VT, vitality;
SF, social function; RE, role difficulty (emotional); MH, mental
health; PCS, physical component summary; MCS, mental component
summary.
Predictive factors of health-related quality of life
In the linear regression analysis, the PCS and MCS dimension scores are
treated as dependent variables, while sleep quality, parasomnias,
sleep-disordered breathing, excessive daytime sleepiness, bruxism, RLS, and
insomnia are considered independent variables. Poor sleep quality and sleep
disorders accounted for 50.95% (95% CI, 37.10%–64.80%;
R2=0.293; P<0.001) of the deterioration in physical health
QoL and 28.25% (95% CI, 15.60%–40.89%; R2=0.207;
P<0.001) of the impairment in mental health QoL. Additionally, 51.65%
(95% CI, 33.46%–69.84%, R2=0.291; P<0.001) of the
physical health QoL deterioration and 35.26% (95% CI, 19.28%–51.23%;
R2=0.283; P<0.001) of the mental health QoL impairment
can be attributed to these factors.
Discussion
Key results
It has shown that people who sleep well typically have considerably higher scores
in physical (average score of 40.20 compared to 33.21; with a significance level
P<0.001) and mental health components (average score of 43.54 compared to
38.20; with a significance level P<0.001) than those who sleep poorly. On
the other hand, individuals suffering from insomnia, daytime sleepiness,
sleep-respiratory disorders, and bruxism were found to have significantly lower
scores in both physical and mental health aspects. Moreover, people with RLS had
notably lower physical health scores, and those with parasomnias had
significantly lower mental health scores.
Interpretation/comparison with previous studies
Prevalence of sleep disorders
Our analysis of patients with various cancers showed that the most common
sleep disorders were excessive daytime sleepiness (36.9%), sleep-disordered
breathing (34.8%), and insomnia (29.4%). These findings align with Davidson
et al. [21], who reported leg
restlessness, insomnia, and excessive daytime sleepiness as most prevalent,
though the order varied. Our prevalence of excessive daytime sleepiness was
higher than Davidson et al. [21] but
lower than Jaumally et al. [14]. We
found a 35.8% prevalence of sleep-related breathing disorders, notably high
in patients with respiratory system cancers (43.1%). Dreher et al. [22] reported a 49% prevalence in lung
cancer patients, and Huppertz et al. [23] found a 90% prevalence in head and neck cancer patients.
Insomnia prevalence was 29.5%, with the highest rate (46.6%) in respiratory
system cancer patients [24].
Types of cancer and sleep quality
The average PSQI score among our cancer patients was 6.17, indicating
moderate sleep quality disorder. Over half (59.2%) were poor sleepers. While
no significant relationship was found between cancer type and sleep quality,
higher prevalence of poor sleep quality was observed in patients with
respiratory system, hematological, and breast cancers. Other studies
reported varying rates of poor sleep quality in lung [25] and breast [26] cancer patients, and in those with advanced cancers [27].
Relationship among sleep disorders, sleep quality, and health-related
quality of life
Patients with sleep disorders had higher PSQI scores, reflecting worse sleep
quality. The prevalence ranged from 16% to 37%, with bruxism and insomnia
patients showing the highest PSQI scores. Cheng and Lee [28] identified insomnia as a major
troubling symptom for cancer patients. Sleep disorders were linked to
reduced physical health QoL, except for parasomnias. RLS and bruxism
patients experienced significant declines in physical and mental health QoL,
respectively [10]. Chronic insomnia
can lead to neuropsychological disorders and weaken immune defenses [9].
Our study found a strong association between poor sleep quality and lower
physical health QoL. Poor sleepers showed notable reductions in physical and
emotional-role functioning. Linear regression analysis identified poor sleep
quality as a primary factor for the decline in physical and mental health
QoL. A recent study [29] found a
significant negative correlation between sleep disturbances and all QoL
domains, with psychological aspects more affected than physical health.
Prior studies have linked sleep disorders with reduced QoL, depression
[30], concentration difficulties
[31], fatigue, and lower survival
rates [12]. The connection between
sleep problems and physical or mental health concerns remains varied, with
some studies [32] finding a stronger
link to physical health issues, while others [33] noted a stronger association with mental health
factors.
Limitations
As mentioned in the methods section, the sampling is conventional. Only voluntary
participants were included.
Suggestion for further studies
Future research should investigate patients' sleep patterns prior to
medical care or the onset of illness. Furthermore, present study is a
descriptive. Therefore, cohort study or randomized-controlled study is required
to compare the QoL of cancer patients with sleep disorders.
Conclusion
Improving the sleep quality of cancer patients through early detection and social
support is comparably important to disease treatment. Addressing factors that impact
the QoL of cancer patients, such as pain, sleep disorders, fatigue, and anxiety, can
lead to improvements in their QoL. Neglecting these issues; however, can have a
detrimental effect on patient well-being, as these symptoms can exacerbate each
other and lead to further decline. By understanding the importance of social support
and motivation, healthcare professionals and family members of patients can actively
contribute to alleviating sleep problems and enhancing the QoL of those affected by
cancer.
Authors' contributions
Conceptualization: Temircan Z
Formal analysis: Şenol V
Investigation: Temircan Z
Methodology: Şenol V
Project administration: Temircan Z
Writing – original draft: Şenol V, Temircan Z
Writing – review & editing: Şenol V, Temircan Z
Conflict of interest
No potential conflict of interest relevant to this article was reported.
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