Keywords
sleep quality - work hours - nurses
Introduction
Continuity is important in the care of patients, so nurses should work in shifts so
that care is not disrupted. As the largest workforce in hospitals, nurses have heavy
responsibilities regarding patient care. Nurses suffer from poor sleep, especially
in hospitals.[1] In recent years, this has been a thoroughly-discussed issue worldwide in terms of
ethical, legal, medical, educational, and managerial aspects, for there have been
many deaths and injuries related to medical errors globally.[2]
[3] Medical errors are often either directly caused by healthcare professionals or are
the result of the healthcare systems.[4]
[5]
The nursing profession, which is one of the occupational groups that has to work in
shifts, makes up an important risk group in terms of high sleep disorders and low
sleep quality due to working hours that are not suitable for the natural biological
rhythm of humans.[6]
[7]
[8] In the nursing profession, sleep quality is essential to be able to provide proper
care to patients. Nursing also requires high levels of concentration, the performance
of complex tasks, and it entails huge responsibilities. Factors such as the pace of
work, overtime, and shift work may produce stress, which may increase the probability
of suffering from sleep disorders.[9] In the study conducted by Dong et al.,[1] the sleep quality of emergency nurses in public hospitals in China was found to
be poor. Some studies[10]
[11]
[12] have shown that night-shift nurses have significantly worse sleep quality scores
than day-shift nurses.
Medical errors are largely preventable.[4] Globally, as many as 4 in 10 patients are harmed in primary and outpatient health
care. In the study by Jember et al.,[13] the rate of reports of medication error among nurses was found to be of 57.4%. In
the study by Vaziri et al.,[14] the results of the meta-analysis indicate that the overall prevalence of medication
error was of 50%. The most detrimental errors are related to diagnosis, prescription,
and the use of medicines.[15] Among health professionals, medical errors are mostly committed by nurses.[9]
[16] The heavy working conditions for nurses (who are in constant communication with
patients, caring for critical patients, exposed to intense stress, and have to perform
many procedures at the same time) always increase the possibility of making mistakes.
Various studies[2]
[16]
[17] have shown that conditions such as working in stressful environments, long working
hours, working shifts, insomnia, and lack of personnel increase the tendency to commit
medical errors. Di Simone et al.[16] found a significant relationship between the risk of committing medication errors
and poor sleep quality among nurses.
In order not to cause medical harm to patients, nurses should be careful not to perform
practices that endanger patient safety and to evaluate patients holistically. In addition,
they should be aware of the conditions that increase the risk of committing medical
errors and take precautions to avoid legal problems that may occur.[2]
According to the literature, the tendency of nurses to commit medical errors is high,
and their sleep quality is low, but this depends on many factors. Nonetheless, studies
on the relationship between nurses'1 sleep quality and their tendency to commit medical
errors are limited. There are separate studies on nurses' tendency to commit medical
errors[3]
[4]
[8] and their sleep quality[7] in Turkey, but no study on the relationship between those two concepts has been
found. In this context, the present study was conducted to examine the relationship
between the sleep quality of nurses working shifts and their tendency to commit medical
errors.
Research Questions
-
What is the level of quality of sleep among nurses and their tendency to commit medical
errors?
-
Do sociodemographic factors and work characteristics affect nurses' sleep quality
and tendency to commit medical errors?
-
Is there a relationship between the sleep quality of nurses and their tendency to
commit medical errors?
Materials and Methods
Study Design
The present research was conducted as a descriptive and correlational study to determine
the relationship between nurses' sleep quality and their tendency to commit medical
errors. The research was conducted between September 2020 and October 2021 with nurses
working shifts at a state hospital (N = 235), a private hospital (N = 278), and a
university hospital (N = 757) in a province in the west of Turkey.
Study Population
The population of the study consisted of 1,270 nurses working at these three hospitals.
The study sample was determined by using the sampling of the known universe formula:
n = N × t2 × p × q ÷ d2 × (N - 1) + t2 × p × q.
In the present study, the calculation of the sample was based on a confidence level
of 95%, an error margin of 5%, and t = 1.96 and d = 0.05 were used in the formula.
Accordingly, the sample size for the total number of 1,270 nurses was calculated at
a 0.05 significance level as follows:
N = 1,270 × (1.96)2 × (0,5 × 0,5) ÷ (0,05)2 × (1,270 - 1) + (1.96)2 × (0.5 × 0.5);
n = 1,270 × 3.8416 × 0.25 ÷ 0.0025 × 1,269 + 3.8416 × 0,25;
n = 295.
Based on this equation, and considering the ± 5% tolerable sampling error, 95% confidence
level, and the assumption of a heterogeneous universe, the minimum sample size was
determined as 295 subjects. Considering data loss, a total of 378 nurses were reached.
Nurses who were not on leave at the time of the study and volunteered to participate
were included. Verbal and written consent was obtained from the nurses by providing
the necessary information about the purpose of the study and data collection forms.
The data were collected through face-to-face interviews. Filling out the forms took
an average of 15 minutes.
The independent variables included sociodemographic characteristics (age, gender,
level of schooling, and marital status), information about their job (the institution
in which they work, total work experience, shift schedule [8 am–4pm: 8 hours; 8am–8pm:
12 hours; 4pm–8am: 16 hours; and permanent night shift: midnight–8am: 8 hours], the
number of patients they provide care for, the difficulties they experience in the
workplace etc.), and individual characteristics (alcohol and cigarette use, daily
tea/coffee consumption, presence of chronic disease, drugs regularly used) that are
thought to affect sleep quality.
The dependent variables included the mean scores on the Medical Error Tendency Scale
in Nursing (METSN) and the Pittsburgh Sleep Quality Index (PSQI). The inclusion criteria
were working as a nurse for at least one year and working shifts, and the exclusion
criteria were nurses who were away from work during the data collection period, and
those who worked in the polyclinic or were only working the day shift.
Data Collection
The data collection tools were a sociodemographic data form, which reflects the sociodemographic
characteristics of nurses, the METSN, and the PSQI.
Sociodemographic Data Form
This form was developed by the researchers following a review of the literature. It
consists of 14 questions, including sociodemographic characteristics, information
about the nursing profession, and individual characteristics that are thought to affect
sleep quality.[10]
[12]
[17]
[18]
METSN
This scale was developed by Özata and Altunkan[18] to determine the tendency of working nurses to commit medical errors, and its validity
and reliability study was conducted by the same authors. The scale is used to evaluate
the routine care activities of nurses working at a hospital. High total scores on
the scale are interpreted as a decrease in the tendency to commit medical errors,
and the scale has a 5-point Likert-type structure that consists of 49 items and 5
subdimensions, namely: drug and transfusion applications (18 items); prevention of
infections (12 items); patient follow-up and material-device safety (9 items); prevention
of falls (5 items); and communication (5 items), which include the activities that
nurses perform daily in terms of in-patient care. Each item contains 5 answer options:
1) never; 2) rarely; 3) sometimes; 4) usually; and 5) always.[18] The internal consistency (Cronbach alpha) of the original scale was of 0.95, while
it was found to be of 0.80 in the present study. The internal consistency of the subdimensions
of the scale were calculated as follows; 0.70 for drug and transfusion practices;
0.71 for prevention of infections; 0.74 for patient follow-up and material-device
safety; 0.79 for prevention of falls; and 0.80 for communication.
PSQI
Developed by Buysse et al.,[19] the PSQI is a self-report screening and evaluation test that provides detailed information
on sleep quality and the type and severity of sleep disturbances in the last month.
It consists of 24 questions divided into 7 components: subjective sleep quality; sleep
latency; sleep duration; sleep efficiency; sleep disturbance; use of sleep medication;
and daytime dysfunction. The total score, which ranges from 0 to 21, is obtained by
adding the scores on each component; scores between 0 and 4 indicate good sleep quality,
and those above 5 indicate that the person has serious trouble in at least two areas
of sleep or has mild or moderate distress in more than three areas. The Turkish validity
and reliability study of the index was conducted by Ağargün et al.,[20] and the Cronbach alpha coefficient was of 0.80, the same value found in the present
study.
Ethical Considerations
We obtained approval from the Ethics Committee for Non-Interventional Research (date:
2021/01-38;5844-GOA), as well as written permission from the hospitals where the research
was conducted and the provincial health directorate. Moreover, permission from the
authors to use the METSN and PSQI was obtained via e-mail.
Before the study was initiated, the nurses were informed about its purpose and that
participation was voluntary; then, we obtained their informed consent.
Data Analysis
The statistical analysis was conducted using the IBM SPSS Statistics for Windows (IBM
Corp., Armonk, NY, United States) software, version 24.0, and the normality of the
data was evaluated through the Kolmogorov-Smirnov test. Descriptive statistics for
normally-distributed continuous variables were reported as mean ± standard deviation
(SD) values. Descriptive statistics of the non-normally-distributed variables were
calculated as median (minimum–maximum) values. The independent t-test or the Mann-Whitney U test was used for the comparison of continuous variables
between two independent groups depending on the normal distribution of the data. When
the quantitative variables were compared in groups of three or more, one-way analysis
of variance (ANOVA) was used for the normally-distributed data, and the Kruskal-Wallis
test was used for data that were not normally distributed. We used non-parametric
tests in paired and multiple comparisons, since the weekly working hours of the nurses
and the mean PSQI scores did not show normal distribution. Parametric tests were used
in paired and multiple comparisons, such as those regarding sociodemographic variables
and variables related to working conditions, and the total and subdimension scores
on the METSN showed normal distribution. The Spearman correlation coefficient was
used to measure the relationship involving the non-normally distributed scores. Significance
was evaluated within a 95% confidence interval (95%CI) and set as values of p < 0.05.
Results
Sociodemographic and Work Characteristics
The mean age of the 378 nurses was of 29.27 ± 7.79 years, 81.7% were female, 65.1%
were single, and 56.9% had an undergraduate degree. In total, 47.1% worked in private
hospitals, 58.7% worked shifts, 48.1% were on duty 6-10 times a month, 86.2% worked
more than 40 hours a week, and 39.4% provided care to at least 1 to 5 patients while
33.1%, to 6 to 10 patients ([Table 1]).
Table 1
Data collected on the nurses' work (n = 378).
|
n
|
%
|
|
Institution served
|
|
Public hospital
|
70
|
18.5
|
|
University Hospital
|
130
|
34.4
|
|
Private hospital
|
178
|
47.1
|
|
Shift schedule
|
|
8am–4pm
|
78
|
20.6
|
|
8am–8pm
|
11
|
2.9
|
|
4pm–8am
|
23
|
6.6
|
|
Permanent night shift (midnight–8am)
|
44
|
11.7
|
|
Shift
|
222
|
58.7
|
|
Working on weekends
|
|
Yes
|
355
|
93.9
|
|
No
|
23
|
6.1
|
|
Number of seizures per month
|
|
No
|
65
|
17.2
|
|
1–5
|
59
|
15.6
|
|
6–10
|
182
|
48.1
|
|
11–15
|
65
|
17.2
|
|
≥ 16
|
7
|
1.9
|
|
Weekly working hours
|
|
40
|
52
|
13.8
|
|
> 40
|
326
|
86.2
|
|
Number of patients to whom daily care is provided
|
|
1–5
|
149
|
39.4
|
|
6–10
|
125
|
33.1
|
|
11–15
|
46
|
12.2
|
|
15–20
|
27
|
7.1
|
|
> 21
|
31
|
8.2
|
|
TOTAL
|
378
|
100.0
|
Comparison of Sociodemographic and Work Characteristics and Mean METSN Scores
The mean total METSN score was of 230.29 ± 14.15, and mean scores on the sub-dimensions
of the scale were as follows: drug and transfusion applications – 85.99 ± 4.92; infection
prevention – 56.63 ± 4.58; patient follow-up and material-device safety – 39.81 ± 4.57;
prevention of falls – 23.88 ± 1.67; and communication – 23.98 ± 1.37.
Statistically significant differences were found regarding total and subdimension
METSN scores in terms of age group, marital status, level of schooling, the hospital
in which the nurses worked, shift schedule, and weekly working hours (p < 0.05). Accordingly, the total and subdimension METSN scores were higher among nurses
aged between 20 and 35 years, who were high school graduates, worked in a private
hospital, were single, worked on the 4pm to 8am shift, and worked more than 40 hours
per week ([Table 2]).
Table 2
Comparison of sociodemographic and work characteristics and mean METSN scores(n = 378).
|
n
|
Drug and transfusion applications: mean ± SD
|
Prevention of infections: mean ± SD
|
Fall prevention: mean ± SD
|
Patient monitoring and material-device safety: mean ± SD
|
Communication: mean ± SD
|
METSN total score
Mean ± SD
|
|
Age in years
|
|
20–35 (1)
|
301
|
86.54 ± 4.79
|
56.99 ± 4.46
|
24.12 ± 1.47
|
40.06 ± 4.57
|
23.99 ± 1.34
|
231.70 ± 13.70
|
|
36–50 (2)
|
69
|
83.58 ± 4.75
|
55.14 ± 4.72
|
22.84 ± 2.11
|
38.65 ± 4.55
|
23.97 ± 1.59
|
224.19 ± 14.38
|
|
≥ 51 (3)
|
8
|
85.88 ± 5.69
|
55.88 ± 5.69
|
24.25 ± 1.04
|
40.13 ± 3.80
|
23.88 ± 0.83
|
230.00 ± 16.69
|
|
Test
|
|
F: 10.697;
p
= 0.001;*
2 > 3; 2 > 1; 3 > 1
|
F: 4.741;
p
= 0.009;*
2 > 3; 2 > 1; 3 > 1
|
F: 18.097; p
= 0.001;*
2 > 1; 2 > 3; 1 > 3
|
F: 2.705;
p
= 0.048;*
2 > 1; 2 > 3; 1 > 3
|
F: 0.131;
p = 0.269
|
F: 8.210;
p
= 0.001;*
2 > 3; 2 > 1; 3 > 1
|
|
Marital status
|
|
Married
|
132
|
84.48 ± 5.01
|
55.58 ± 4.92
|
23.38 ± 1.93
|
38.62 ± 4.84
|
24.02 ± 1.33
|
234.49 ± 12.36
|
|
Single
|
246
|
87.52 ± 4.62
|
57.68 ± 4.15
|
24.41 ± 1.95
|
40.98 ± 4.32
|
23.94 ± 1.42
|
230.29 ± 14.15
|
|
Test
|
|
t: 3.231;
p
= 0.001*
|
t: 2.294;
p
= 0.004*
|
t: 4.142;
p
= 0.001*
|
t: 3.252;
p
= 0.001*
|
t: 0.174;
p = 0.934
|
t: 5.685;
p
= 0.001*
|
|
Level of schooling
|
|
High school (1)
|
51
|
88.84 ± 4.51
|
58.47 ± 2.47
|
24.08 ± 1.94
|
43.18 ± 2.54
|
24.57 ± 0.83
|
239.14 ± 9.11
|
|
Prebachelor's (2)
|
105
|
87.80 ± 4.00
|
58.20 ± 3.51
|
24.45 ± 1.17
|
41.94 ± 3.15
|
24.26 ± 1.06
|
236.65 ± 11.39
|
|
Bachelor's (3)
|
215
|
84.42 ± 4.87
|
55.43 ± 5.04
|
23.58 ± 1.73
|
38.02 ± 4.70
|
23.74 ± 1.53
|
225.19 ± 14.19
|
|
Master's/Doctorate (4)
|
7
|
86.29 ± 3.99
|
56.43 ± 4.96
|
23.57 ± 1.99
|
38.00 ± 2.16
|
23.00 ± 1.53
|
227.29 ± 11.64
|
|
Test
|
|
F: 20.483;
p
= 0.001;*
3 > 4; 3 > 2; 3 > 1;
4 > 2; 4 > 1
|
F: 12.918;
p
= 0.001;*
3 > 4; 3 > 2; 3 > 1;
4 > 2; 4 > 1
|
F: 7.057; p
= 0.001;*
3 > 4; 3 > 2; 3 > 1;
4 > 2; 4 > 1
|
F: 36.078; p
= 0.001;*
3 > 4; 3 > 2; 3 > 1; 4 > 2; 4 > 1
|
F: 8.294; p
= 0.001;*
3 > 4; 3 > 2; 3 > 1; 4 > 2; 4 > 1
|
F: 28.146; p
= 0.001;*
3 > 4; 3 > 2; 3 > 1;
4 > 2; 4 > 1
|
|
Institution served
|
|
Public hospital (1)
|
70
|
83.30 ± 4.48
|
55.41 ± 4.37
|
22.47 ± 2.21
|
37.89 ± 3.75
|
23.76 ± 1.78
|
222.83 ± 12.12
|
|
University hospital (2)
|
130
|
84.18 ± 5.05
|
54.77 ± 5.36
|
23.88 ± 1.29
|
37.61 ± 4.88
|
23.60 ± 1.49
|
224.04 ± 14.72
|
|
Private hospital (3)
|
178
|
88.37 ± 3.78
|
58.46 ± 3.13
|
24.44 ± 1.31
|
42.16 ± 3.33
|
24.35 ± 0.95
|
237.79 ± 10.19
|
|
Test
|
|
F: 30.572; p
= 0.001;*
1 > 2; 1 > 3; 2 > 3
|
F: 31.909; p
= 0.001;*
1 > 2; 1 > 3; 2 > 3
|
F: 42.881; p
= 0.001;*
1 > 2; 1 > 3; 2 > 3
|
F: 58.556; p
= 0.001;*
1 > 2; 1 > 3; 2 > 3
|
F: 13.293; p
= 0.001;*
1 > 2; 1 > 3; 2 > 3
|
F: 33.073; p
= 0.001;*
1 > 2; 1 > 3; 2 > 3
|
|
Shift schedule
|
|
8am–4pm (1)
|
78
|
87.71 ± 3.92
|
58.23 ± 3.11
|
24.12 ± 1.65
|
41.72 ± 3.33
|
24.40 ± 0.83
|
236.17 ± 10.74
|
|
8am–8pm (2)
|
11
|
84.73 ± 5.10
|
54.91 ± 5.03
|
24.09 ± 0.94
|
39.73 ± 3.95
|
23.73 ± 1.10
|
227.18 ± 14.96
|
|
4pm–8am (3)
|
23
|
80.91 ± 3.87
|
51.86 ± 4.42
|
22.59 ± 1.59
|
37.73 ± 3.38
|
23.55 ± 0.91
|
216.64 ± 12.80
|
|
Permanent night shift (midnight–8am) (4)
|
44
|
84.80 ± 5.21
|
55.23 ± 5.49
|
24.14 ± 1.00
|
38.02 ± 4.97
|
23.75 ± 1.16
|
225.93 ± 15.12
|
|
Shift (5)
|
222
|
86.18 ± 4.91
|
56.88 4.44
|
23.87 ± 1.77
|
39.71 ± 4.77
|
23.95 1.57
|
230.59 14.00
|
|
Test
|
|
F: 8.065;
p
= 0.001;*
3 > 2; 3 > 4; 3 > 5; 2 > 4; 2 > 5; 4 > 5
|
F: 8.893;
p
= 0.001;*
3 > 2; 3 > 4; 3 > 5; 2 > 4; 2 > 5; 4 >
|
F: 3.372;
p
= 0.005;*
3 > 5; 3 > 2; 3 > 1;
3 > 4; 5 > 2; 5 > 1; 5 > 4
|
F: 5.368; p
= 0.001;*
3 > 4; 3 > 5; 3 > 2; 4 > 5; 4 > 2; 5 > 2
|
F: 3.249; p
= 0.007;*
3 > 2; 3 > 4; 3 > 5; 2 > 4; 2 > 5; 4 > 5
|
F: 8.527; p
= 0.001;*
3 > 4; 3 > 2; 3 > 5; 4 > 2 4 > 5; 2 > 5
|
|
Weekly working hours
|
|
40
|
52
|
86.09 ± 6.09
|
56.65 ± 3.34
|
24.66 ± 2.25
|
39.87 ± 4.27
|
23.90 ± 0.89
|
230.34 ± 12.59
|
|
> 40 hours
|
326
|
85.04 ± 4.73
|
56.46 ± 4.74
|
22.07 ± 1.48
|
39.36 ± 4.62
|
23.52 ± 1.42
|
228.59 ± 14.37
|
|
Test
|
|
U: 3.002;
p
= 0.018*
|
U: 1.076; p
= 0.786*
|
U: 33.814; p
= 0.001*
|
U: 0.543; p = 0.461
|
U: 8.947; p
= 0.003*
|
U: 1.096; p
= 0.296*
|
Abbreviations: METSN, Medical Error Tendency Scale in Nursing; SD, standard deviation.
Notes: t: independent t-test. F: one-way analysis of variance (ANOVA). U: Mann-Whitney U test. Differences:
Bonferroni test. *Statistically significant (p < 0.05).
Distribution of PSQI Scores According to Descriptive Characteristics
The mean PSQI score was of 8.25 ± 4.81, and– 78.31% of the nurses had poor sleep quality
(PSQI > 5), while 21.69% had healthy sleeping habits (PSQI ≤ 5) ([Table 3]).
Table 3
Frequency distribution of sleep quality (n = 378).
|
Pittsburgh Sleep Quality Index (PSQI)
|
N
|
%
|
|
Good sleeper (PSQI ≤ 5)
|
82
|
21.69
|
|
Bad sleeper (PSQI > 5)
|
296
|
78.31
|
|
Total
|
378
|
100.00
|
Statistically significant differences were found regarding the mean PSQI scores in
terms of age, marital status, level of schooling, shift schedule, and weekly working
hours (p < 0.05) ([Table 4]).
Table 4
Distribution of Pittsburgh Sleep Quality Index (PSQI) scores according to sociodemographic
and work data (n = 378).
|
N
|
PSQI: mean ± standard deviation
|
Test
|
|
Age in years
|
|
|
20–35
|
301
|
8.22 ± 4.83
|
|
|
36–50
|
69
|
8.33 ± 4.79
|
|
|
≥ 51
|
8
|
8.52 ± 4.54
|
Kruskal-Wallis = 8.907; p = 0.001*
|
|
Gender
|
|
|
Female
|
309
|
8.25 ± 4.81
|
|
|
Male
|
69
|
8.23 ± 4.81
|
Mann-Whitney U = 1.023; p = 0.338
|
|
Marital status
|
|
|
Married
|
132
|
8.32 ± 4.78
|
|
|
Single
|
246
|
8.11 ± 4.95
|
Kruskal-Wallis = 2.401 p = 0.008*
|
|
Level of schooling
|
|
|
High school
|
51
|
8.39 ± 4.72
|
|
|
Prebachelor's degree
|
105
|
8.24 ± 4.76
|
Kruskal-Wallis = 10.690; p = 0.014*
|
|
Bachelor's degree
|
215
|
8.26 ± 4.89
|
|
|
Master's or Doctorate
|
7
|
7.54 ± 4.56
|
|
|
Institution served
|
|
|
Public hospital
|
70
|
8.33 ± 4.68
|
Kruskal-Wallis = 4.771; p = 0.214
|
|
University Hospital
|
130
|
8.28 ± 4.43
|
|
Private hospital
|
178
|
8.04 ± 4.52
|
|
Shift schedule
|
|
|
|
|
8am–4pm
|
78
|
7.53 ± 4.18
|
Chi-squared = 7.015; p = 0.001*
|
|
8am–8pm
|
11
|
8.05 ± 4.33
|
|
4pm–8am
|
23
|
8.14 ± 4.72
|
|
Permanent night shift (midnight–8am)
|
44
|
8.48 ± 4.83
|
|
Shift
|
222
|
8.54 ± 4.92
|
|
Weekly working hours
|
|
|
|
|
40
|
52
|
8.28 ± 4.63
|
|
|
> 40
|
326
|
9.34 ± 4.51
|
Mann-Whitney U = 2.031; p = 0.036*
|
Note: *Statistically significant (p < 0.05).
Correlations regarding METSN and PSQI Scores
There was a moderate and statistically significant negative correlation between the
METSN and PSQI scores (p < 0.001; r = −0.548): as the sleep quality deteriorated, the tendency to commit medical errors
increased. According to the Spearman correlation analysis, there were statistically
significant, negative, and weak correlations involving the PSQI scores and the scores
on the following METSN subdimensions: drug and transfusion applications (p < 0.001; r = −0.218); prevention of infections (p = 0.004; r = −0.146); prevention of falls (p = 0.130; r = −0.369); patient monitoring and material-device safety (p < 0.003; r = −0.338); and communication (p = 0.036; r = −0.488). As the sleep quality deteriorated, the tendency to commit medical errors
increased ([Table 5]).
Table 5
Correlations regarding the total score son the METSN and PSQI.
|
total and subdimension METSN scores
|
Total PSQI score
|
|
rp
|
p
|
|
Drug and transfusion applications
|
−0.218
|
0.001*
|
|
Prevention of infections
|
−0.146
|
0.004*
|
|
Fall prevention
|
−0.369
|
0.130
|
|
Patient monitoring and material-device safety
|
−0.338
|
0.003*
|
|
Communication
|
−0.488
|
0.036*
|
|
Total METSN score
|
−0.548
|
0.001
|
Abbreviations: METSN, Medical Error Tendency Scale in NursingPSQI, Pittsburgh Sleep
Quality Index.
Note: *Statistically significant (p < 0.05).
Discussion
In the present study, the mean PSQI score was > 5 (8.25 ± 4.81), and 78.31% of the
sample had poor sleep quality, which is in line with some of the studies in the literature.
Palhares et al.[21] found a mean PSQI score of 7.3 ± 3.6, and 34.9% of the nurses in their sample had
a mean PSQI score ≥ 5. Kamkar et al.[22] reported that nurses had poor sleep quality. Analyzing Turkish studies on the sleep
quality of nurses, Pirinçci et al.[7] found a mean PSQI score of 6.70 ± 3.35, and 55.8% had poor sleep quality. In the
study by Tarhan et al.,[23] the rate of poor sleep quality was of 61.9%, and Khatony et al.[24] found a rate of 77.4%.
In the present study, a significant difference was found between age and sleep quality:
sleep quality deteriorated as age increased (p < 0.05). Aliyu et al.[25] and Morimato et al.[26] differ from our research, for they have reported that sleep quality does not change
according to age. Tarhan et al.[23] found that nurses aged ≥ 41 years were 9.5 times more likely to be in the group
with low sleep quality than nurses aged ≤ 25 years, and that advanced age was a risk
factor for poor sleep quality. In the study by Khatony et al.,[24] younger nurses experienced more sleep problems, and Kamkar et al.[22] found that age was an important factor affecting sleep quality.
In the present study, marital status was one of the factors affecting sleep quality.
Studies, such as the one by Kamkar et al.,[22] have shown that the sleep quality of married nurses is worse than that of single
nurses. However, Salehi et al.[27] found no relationship between marital status and sleep quality.
Shift work has significantly changed the sleep patterns of nurses. Sleep problems
are prevalent among shift nurses, and they have a negative effect on health, the quality
of the care provided, and job satisfaction.[11] In the present study, we found a significant difference between sleep quality and
shift schedule. In particular, nurses working shifts and constantly at night had higher
mean PSQI scores and worse sleep quality (p < 0.05). Bazrafshan et al.[28] found that working shifts negatively affected the sleep quality of nurses. Dong
et al.,[1] McDowall et al.,[29] and Khatony et al.[24] found that the sleep quality of nurses working shifts in general and of those working
the night shift was low. Tarhan et al.[23] emphasized that the sleep quality of nurses working the day shift was better, and
that the sleep quality of those working the night shift was 14.1 times lower.
In the present study, when the mean PSQI score was examined according to the weekly
working hours, the sleep quality of those who worked more than 40 hours was found
to be low, and the difference was significant. Dong et al.,[1] Stimpfel et al.,[30] and Farag et al.,[31] found that sleep quality decreased in parallel with the increase in weekly working
hours.
We found that the tendency of nurses to commit medical errors was low (230.29 ± 14.15),
which is in line with the studies by Ozer et al.,[4] Özen et al.,[32] and Sabanciogullari et al.[8] Karadağ et al.[17] found that nurses had a higher tendency to make medical errors in drug administration
and transfusions and in preventing falls, and a lower tendency to make medical errors
in communication and in prevention of infection.
In the present study, we found a significant difference between the shift schedule
and the tendency to commit medical errors: nurses working on the 4pm to 8am shift
had a higher tendency to commit medical errors (p < 0.05), which corroborates the
findings of Kiymaz and Koç,[2] and Özen et al.[32] We also found a statistically significant difference between the level of schooling
and the tendency to commit medical errors, unlike Özen et al.[32]
We found a moderate and statistically significant negative correlation between the
PSQI and METSN scores (r = −0.548; p < 0.001): as the sleep quality deteriorates, the tendency to commit medical errors
increases. Working shifts and particularly the night shift can disrupt the circadian
sleep rhythm and cause fatigue, inattention, and poor performance, resulting in medical
errors.[8] Di Simone et al.[16] found a significant relationship between the risk of committing medication errors
and poor sleep quality among nurses. No other study was found in the literature on
nurses' sleep quality and their tendency to commit medical errors. Therefore, it is
a topic that should be more thoroughly discussed.
Conclusion
In the present study, we found that the tendency of nurses to commit medical errors
was low, and there were significant differences regarding the mean METSN scores, age,
level of schooling, and the hospital in which they worked. We concluded that nurses
had poor sleep quality, and there were statistically significant differences involving
the mean PSQI scores and age, level of schooling, shift schedule, and weekly working
hours. Moreover, there was a statistically significant negative and moderate relationship
regarding the METSN and PSQI scores and the tendency to commit medical errors increased
as the sleep quality deteriorated.
To improve sleep quality and minimize medical errors, the number of nurses in health
institutions should be increased as much as possible, the number of shifts should
be reduced, and the working and resting hours should be rearranged. Nurses should
be provided education on medical errors at regular intervals. It is thought that arranging
the work life by taking sociodemographic and work characteristics into account may
effectively increase nurses' sleep quality and reduce the rate of medical errors.
