Article Type : Research Article
Authors : Heeja NA
Keywords : Gender; Scaling; Patient; Job stress; Infection control; Job fatigue; Covid; Age
Objective: This study aims to use it as basic data to find efficient dental hygiene manpower management measures by identifying dental hygienists' COVID-19 infection control job stress and infection control fatigue, correlating infection control job stress with infection control fatigue, and identifying factors affecting dental hygienists' work.
Methods: This study conducted a survey of 264 dental workers at Y Dental Clinic, I Dental Clinic, H Dental Clinic, and S Dental Hospital in Gwangju Metropolitan City from May 1 to May 10, 22. Survey participants agreed to understand the purpose of the study and participate in the study, and the survey was conducted in a self-fill manner. When the sample is selected based on the general significance level of .05 and the effect size of 0.3 power of 0.95, using the G-power 3.1 program, the appropriate number of samples is 264. The questionnaire was measured on the Likert 5-point scale, and 5 points were given to the Likert 5-point scale of 'very important' and 1 point to 'not important at all', meaning that the higher the score, the higher the practicality. The data collected in this study were analyzed using the SPSS 21.0 program. The mean and standard deviation were obtained to understand the general characteristics of the subjects, and the independent sample t-test was analyzed at the significance level of 0.05 for gender and multiple job stress of scaling patients. A significant two-sided test was obtained at the 0.01 level of correlation between job stress and infection management fatigue, and a two-way analysis of the number of nursing patients, wearing protective clothing, and fear of infection was conducted on the 1st. In addition, infection control job stress and fatigue regression analysis for age were analyzed at the significance level of .05.
Discussion: In the regression analysis of infection control job stress and fatigue for age, the F statistical value of the number of nursing patients per day was 2.329, and the significance level.05. There is a significant difference (t=2.298, p=.022) The F statistic for fatigue wearing protective clothing is 2.329, which is significant.be significant at .05(t= 2.414, p=.0160. The total amount of change according to age is explained as 60% (34% according to the correction factor).
Conclusion: In the gender and scaling patient multiple job stress independent sample t-test in this study, the mean and standard deviation of men is 43.955 (952) and the mean and standard deviation of women is 3.703 (1.070). The t-value for the multiple job stress of scaling patients in men and women was 1.467 significance probability of .034, which showed a significant difference in the multiple job stress of scaling patients according to gender at the significance level of .05. In the correlation analysis between job stress and job fatigue, gender and overtime stress are -.161**, gender and no substitute workforce stress is -.161**, overtime stress and no replacement 1.000**, overtime stress and peer employee hand hygiene job stress .269**, overtime stress and new pandemic job stress.176**, overtime stress and confirmed during infection job stress .243**, overtime stress and scaling patient multiple job stress.243**, extended work stress, and job stress when performing various tasks simultaneously were found to be 167**. No substitute workforce No job stress and peer employee hand hygiene quarantine No job stress .269**, no substitute workforce Increased job stress and new pandemic job stress.176**, no substitute workforce and confirmed during infection Job stress.243**, no substitute workforce job stress and scaling patient multiple job stress .243**, no substitute workforce job stress and various simultaneous job stress .167**.Increasing job stress and protecting the hand hygiene quarantine of fellow employees.567**,The increase in job stress caused by a new epidemic and various simultaneous job stress.682** were found. Various simultaneous job stress and job stress of protecting the hand hygiene quarantine of fellow employees were found.691**. in addition, the number of nursing patients per day, wearing protective clothing, and fatigue from infection to the patient. The results of the two-way variance analysis showed that there was no significant difference in the fatigue of wearing protective clothing at the significance level of .056 and the significance probability of .852 at the significance level of .399.It was not significant at .05 Fatigue in wearing protective clothing * F statistic is 2.889 and significance probability is 2.889, which is a significance level. There was a significant difference in .05.
In order to prevent the occurrence, prevention, and spread
of infectious diseases in hospitals, the KCDC revised the standard precautions
for medical infections that recommend hand hygiene and wearing protective gear
such as masks, gowns, and gloves [1].
In addition, infection control guidelines for COVID-19 were
declared as dental prevention guidelines by the Centers for Disease Control and
Prevention [2]. Recently, infection control has emerged important for dental
workers as COVID-19 spreads. In addition to the basic tasks of dental
hygienists such as scaling, implant prevention, orthodontic treatment, etc.,
education on the basic principles and practices of dental workers to prevent
the spread of infection should include blood carrier education and patient
safety. Job or task, training and training should be provided during at least
annual orientation when a new task or procedure is introduced [3,4]. It should
also address industrial health needs, including exposure or infection control
of the necessary personnel of dental care. In a previous paper, it was said
that infection control job stress becomes infection control job stress by
working at a dentist with a high risk of infection, nursing patients with a
high risk of infection, and exposure to infection risk factors [5,6]. It is
required to understand the factors affecting dental hygienists' infection
control job stress due to the recent COVID-19 epidemic. Job stress due to
strengthening dental medical-related infection control guidelines increases
fatigue [7]. In the previous paper, the nurse's burnout deteriorates the
quality of nursing services for infected patients [8]. Even in clinical
dentistry, dental hygienists with high stress or fatigue have lower ability to
cope with infection control and reduce their performance as professional dental
hygienists. In particular, due to the spread of COVID-19, the number of nursing
patients per day in dental clinic, wearing protective clothing, and fatigue
from infection to patients are showing a deep correlation, increasing job
stress. Therefore, the stress of dental hygienists' COVID-19 infection
management and job-related fatigue can affect other people besides themselves.
According to previous papers, the higher the job stress, the higher the degree
of burnout, and the lower the burnout, the higher the performance of infection
control guidelines, the lower the medical-related infection rate [9]. In this
study, due to the lack of papers on infection control job stress and infection
control fatigue, it is necessary to prepare an intervention strategy to lower
infection by grasping infection control job stress and infection control
fatigue for dental hygienists. Therefore, this study attempted to use it as
basic data to find an efficient infection management plan by identifying the
dental hygienist's infection management stress and job-related fatigue, and to
increase the efficiency of dental hygienists' work.
Materials and Methods
From May 1 to May 10, 2022, 264
dental workers were surveyed at Y Dental Clinic, I Dental Clinic, H Dental
Clinic, and S Dental Hospital in Gwangju Metropolitan City. Survey participants
agreed to understand the purpose of the study and participate in the study, and
the survey was conducted in a self-fill manner. This study was conducted with
the consent of the IRB (NO1041223-HR-04) Honam University's BioScience Ethics
Committee. When the sample is selected based on the general significance level
of .05 and the effect size of 0.3 power of 0.95, using the G-power 3.1 program,
the appropriate number of samples is 264. The questionnaire was measured on the
Likert 5-point scale, and 5 points were given to the Likert 5-point scale of
'very important' and 1 point to 'not important at all', meaning that the higher
the score, the higher the practicality. In the questionnaire, infection control
job stress loophole [10] and infection control fatigue were used by Koo [11].
Research Tool
Infection
control job stress
Infection management job stress was
measured using the infection management nurse's job stress tool developed by
Heo (10). It consists of 9 questions of infection control job stress. The
question score is on the Likert scale of 1 point from "very not" and
5 points from "very not", and a high score means high job stress. In
this study, the reliability Cronbach's alpha was .641.
Infection
control fatigue
Infection management fatigue was
measured using the infection management fatigue tool developed by Koo Hyo (11),
and the burden factors due to infection concerns and excessive interest are
composed of 11 questions. Each question is on a 5-point Likert scale of 1 point
from "very not" to "very not", and the higher the score,
the higher the fatigue. The reliability of this study, Cronbach's alpha, was
.717.
Analysis Method
The data collected in this study were
analyzed using the SPSS 21.0 program. The mean and standard deviation were
obtained to understand the general characteristics of the subjects, and the
independent sample t-test was analyzed at the significance level of 0.05 for
gender and multiple job stress of scaling patients. A significant two-sided
test was obtained at the 0.01 level of correlation between job stress and
infection management fatigue, and a two-way analysis of the number of nursing
patients, wearing protective clothing, and fear of infection was conducted on
the 1st. In addition, infection control job stress and fatigue regression
analysis for age were analyzed at the significance level of .05
Results
General
characteristics of subjects
In the general matters of this study, 264 participants. In
age, 95 people aged 23 years old were 36.5%, 53 people aged 24 years old were
20.1%, 74 people aged 25 years old were 28.0%, 38 people aged 26 years old were
14.4%, and 4 people aged 27 years old were 1.5%. In gender, it was 17.0% for
male 45 and 83.0% for female 219, and in education, it was 49.2% for 130
students, 28.0% for Bachelor of art 74, 6.8% for high school 18 students, and
4.5% for Etc. In marriage, single 228 people 86.4% and married 36 people 13.6%.
In the number of nursing patients per day, 25.8% of 15
preson 68 people, 25.8% of 20 preson 68 people, 29.9% of 25 preson 79 people,
8.7% of 30 preson 23 people, and 9.8% of 35 preson 26 people. In the Infection
management education experience with a year, 24.2% of 64 people in 1 time,
22.7% of 60 people in 2 time, 20.5% of 54 people in 3 time, 18.9% of 50 people
in 4 time, and 13.6% of 36 people in 5 time (Table 1).
Gender
and scaling patients multiple job stress independent sample t-test
In the gender and scaling patients multiple job stress independent sample t-test, the mean and standard deviation of men is 43.955 (9.952) and the mean and standard deviation of women is 3.703 (1.070). The t-value for the multiple job stress of scaling patients in men and women is 1.467, and the significance probability is .034, and it seems that there is a significant difference in the multiple job stress of scaling patients according to gender at the significance level of .05 (Table 2).Correlation analysis between job stress and infection control fatigue
In the correlation analysis between job stress and job
fatigue, gender and overtime stress are -.161**, gender and no substitute
workforce stress is -.161**, overtime stress and no replacement 1.000**,
overtime stress and peer staff hand hygiene protection job stress .269**,
overtime stress and new pandemic job stress increase.176**, overtime stress and
infection confirmed during infection.243**, overtime stress and scalding
patient multiple job stress.243**, extended work stress, and job stress when
performing various tasks simultaneously were found to be 167**. No substitute
workforce No job stress and peer employee hand hygiene quarantine No job stress
.269**, No substitute workforce No job stress and new pandemic No job stress
Increase.176**, No substitute workforce No job stress and infection confirmed
job stress.243**, no substitute workforce job stress and scaling patient
multiple job stress .243**, no substitute workforce job stress and various
simultaneous job stress .167**. Increasing job stress and protecting the hand
hygiene quarantine of fellow employees.567**, The increase in job stress caused
by a new epidemic and various simultaneous job stress.682** were found. Various
work simultaneous job stress and peer employee hand hygiene isolation protective
job stress .691** (Table 3).
Technical
statistics on the number of nursing patients per day, wearing protective
clothing, and fatigue from infection
The two-way ANOVA, which analyzed the number of nursing
patients as independent variables of wearing protective clothing and risk of
infection to patients, has a mean and standard deviation of 27.500 (3.535) and
a mean and standard deviation of 24.459 (6.211) 37, a mean and standard of
22.09 (6.03) and a mean and standard. In other words, the number of nursing
patients per day, wearing protective clothing, and fatigue from infection to
the patient were high (Table 4).
The
results of the two-way analysis of the number of nursing patients per day,
wearing protective clothing, and the risk of infection to patients
According to the results of the two-way analysis of the
number of nursing patients per day, the wearing of protective clothing, and the
risk of infection to the patient, F statistical values of 2.556 and
significance probability of .056 showed no significant difference in the
fatigue of wearing protective clothing at the significance level of .05 and the
risk of infection to the patient. The F statistical value is .399 with a
significance probability of .852, a significance level. It was not significant
at 05. Fatigue for protective clothing * The F statistic is 2.889 and the
significance probability is 2.889, which is significant. There was a
significant difference in (Table 5).
Regression
analysis of infection control job stress and fatigue in age
In the regression analysis of
infection control job stress and fatigue for age, the F statistic of the number
of nursing patients per day was 2.329 and the significance level was 0.05,
showing a significant difference (t=2.298, p=.022) The F statistics of fatigue
in wearing protective clothing are significant at 2.329 and the significance
level of .05(t= 2.414, p=.0160). The total amount of change according to age is
explained as 60% (34% according to the modification coefficient).
Discussion
The data collected in this study were
analyzed using the SPSS 21.0 program. The mean and standard deviation were
obtained to understand the general characteristics of the subjects, and gender
and scaling patients' multiple job stress were the independent sample t-test
was analyzed at the significance level of .05. A significant bilateral test was
obtained at the 0.01 level of correlation between job stress and infection
control fatigue analysis. A two-way analysis of the number of nursing patients
and the wearing of protective clothing and the risk of infection to the patient
was conducted on the 1st. In addition, infection control job stress and fatigue
regression analysis for age were analyzed at the significance level of .05.
From May 1 to May 10, 2022, 264 dental workers were surveyed at Y Dental
Clinic, I Dental Clinic, H Dental Clinic, and S Dental Hospital in Gwangju
Metropolitan City. Survey participants agreed to understand the purpose of the
study and participate in the study, and the survey was conducted in a self-fill
manner. If the sample is selected based on the general significance level of
.05 and the effect size of 0.3 power of 0.95, using the G-power 3.1 program,
the appropriate number of samples is 264. The questionnaire was measured on the
Likert 5-point scale, and 5 points were given to the Likert 5-point scale of
'very important' and 1 point to 'not important at all', meaning that the higher
the score, the higher the practicality.
The general point is that 264 people
participated in this study. In age, 95 people aged 23 years old were 36.5%, 53
people aged 24 years old were 20.1%, 74 people aged 25 years old were 28.0%, 38
people aged 26 years old were 14.4%, and 4 people aged 27 years old were 1.5%.
In gender, 17.0% were male 45 and 83.0% were female 219, and in education,
49.2% were 130 students, 28.0% were Bachelor of art 74, 6.8% were high school
18 students, and 4.5% were 12 students. In marriage, single 228 people 86.4%
and married 36 people 13.6%. In the number of nursing patients per day, 25.8%
of 15 person 68 people, 25.8% of 20 person 68 people, 29.9% of 25 person 79
people, 8.7% of 30 person 23 people, and 9.8% of 35 person 26 people. In the
Infection management education experience with a year, 24.2% of 64 people in 1
time, 22.7% of 60 people in 2 time, 20.5% of 54 people in 3 time, 18.9% of 50
people in 4 time, and 13.6% of 36 people in 5 time.
In the gender and scaling patients
multiple job stress independent sample t-test, the mean and standard deviation
of men is 43.955 (9.952) and the mean and standard deviation of women is 3.703
(1.070). The t-value for the multiple job stress of scaling patients in men and
women is 1.467 significance probability .034, and it seems that there is a
significant difference in the multiple job stress of scaling patients according
to gender at the significance level of .05. (Table 2).
In the correlation analysis between
job stress and job fatigue, gender and overtime stress -.161**, gender and no
substitute workforce stress is -.161**, overtime stress and no replacement
1.000**, overtime stress and peer employee hand hygiene job stress .269**,
overtime stress and new pandemic job stress.176**, overtime stress and
confirmed during infection job stress .243**, overtime stress and scaling
patient multiple job stress.243**, extended work stress, and job stress when
performing various tasks simultaneously were found to be 167**. No substitute
workforce No job stress and peer employee hand hygiene quarantine No job stress
.269**, no substitute workforce Increased job stress and new pandemic job
stress.176**, no substitute workforce and confirmed during infection Job stress.243**,
job stress without substitute manpower and multiple job stress .243** in
scaling patients, job stress without substitute manpower and various
simultaneous job stress .167**. Increasing job stress and protecting hand
hygiene quarantine of fellow employees due to the outbreak of new infectious
diseases
Job stress .567**, The increase in
job stress caused by a new epidemic and various simultaneous job stress.682**
were found. Various simultaneous job stress and peer employee hand hygiene
quarantine protective job stress.691** (Table 3).
The number of nursing patients per
day, wearing protective clothing, and the risk of infection to the patient were
high (Table 4).
The number of nursing patients per
day, wearing protective clothing, and the risk of infection to patients, the
two-way analysis showed that the F statistics were 2.556 and The significance
probability was .056, and there was no significant difference in the fatigue of
wearing protective clothing at the significance level of .05. The F statistical
value of fatigue, which is feared to be infected with the patient, is .399,
with a significance probability of .852, a significance level.It was not
significant at .05. Fatigue for protective clothing * The F statistic is 2.889
and the significance probability is 2.889, which is significant. There was a
significant difference in Table 5.
In the regression analysis of
infection control job stress and fatigue for age, the F statistical value of
the number of nursing patients per day was 2.329, and the significance
level.05. It shows a significant difference (t=2.298, p=).022)
The F statistic for fatigue wearing
protective clothing is 2.329, which is significant.be significant at 05 (t=
2.414, p=.0160). The total amount of change according to age is explained as
60% (34% according to the modification coefficient).
Conclusion
Recently,
due to the coronavirus-19 epidemic, the application of infection control
procedures and infection control guidelines has led to more work than usual and
experiencing greater stress [12]. In this study, there were significant
differences in job stress and infection control fatigue according to general
characteristics of COVID-19 infection control in age, gender, education,
marriage, number of patients per day, and Infection management education
experience with a year. In previous studies, the group aged over 40 years old
and under 29 years old had higher burnout than the group aged 30-39, and the
group of unmarried people had higher burnout than the group of married people. According to previous studies, unmarried people feel
psychological instability (Maslach, 1976) compared to married people, so job
stress and job fatigue are higher in unmarried people than married people [13].
In the general matters of this study, 264 participants. In age, 95 people aged
23 years old were 36.5%, 53 people aged 24 years old were 20.1%, 74 people aged
25 years old were 28.0%, 38 people aged 26 years old were 14.4%, and 4 people
aged 27 years old were 1.5%. In gender, it was 17.0% for male 45 and 83.0% for
female 219, and in education, it was 49.2% for 130 students, 28.0% for Bachelor
of art 74, 6.8% for high school 18 students, and 4.5% for Etc. In marriage,
single 228 people 86.4% and married 36 people 13.6%. In the number of patients
per day, 15 preson 68 people 25.8 percent, 20 preson 68 people 25.8 percent, 25
preson 79 people 29.9%, 30 preson 23 people 8.7%, It was found that the number
of 35 preson 26 people was 9.8%. In the regression analysis of infection
control job stress and fatigue for the age of this study, the F statistical
value of the number of nursing patients per day was 2.329, and the significance
level was .05, showing a significant difference(t=2.298, p=.022) The F
statistic for fatigue wearing protective clothing is 2.329, a significance
level.be significant at .05 (t= 2.414, p=.0160).The total amount of change
according to age is explained as 60% (34% according to the modification
coefficient). According to a previous paper, Freudenberger (1975) found that
during the first year of work, the work was repeated at a high stress level due
to the freshness of the first working life and the ability to train in the
curriculum, making it easy to be disillusioned and troubled [14]. In this
study, the Infection management education experience with a year included 24.2%
of 64 people in 1 time, 22.7% of 60 people in 2 time, 20.5% of 54 people in 3
time, 18.9% of 50 people in 4 time, and 13.6% of 36 people in 5time t = 32.619,
p = .000. In addition, in this study's gender and scaling patient multiple job
stress independent sample t-test, the mean and standard deviation of men is
43.955 (952) and the mean and standard deviation of women is 3.703 (1.070). The
t-value for the multiple job stress of scaling patients in men and women is
1.467 significance probability .034, and it seems that there is a significant
difference in the multiple job stress of scaling patients according to gender
at the significance level of .05. According to previous studies, the higher the
infection control fatigue of nurses, the higher the infection control job
stress was, which was consistent with the results of this study [15]. In the
correlation analysis between job stress and job fatigue of COVID-19 infection
control in this study, gender and overtime stress are -.161**, gender and no
substitute workforce stress is -.161**, overtime stress and no replacement
1.000**, overtime stress and peer employee hand hygiene job stress .269**,
overtime stress and new pandemic job stress.176**, overtime stress and
confirmed during infection job stress .243**, overtime stress and scaling
patient multiple job stress.243**, extended work stress, and job stress when
performing various tasks simultaneously were found to be 167**. No substitute
workforce No job stress and peer employee hand hygiene quarantine No job stress
.269**, no substitute workforce No job stress and new pandemic job stress
Increase.176**, no substitute workforce No job stress and confirmed during
infection Job stress.243**, no substitute workforce Job stress and scaling
patient multiple job stress .243**, no substitute workforce job stress and
various simultaneous job stress .167**.It was found that there was an increase
in job stress caused by a new pandemic, a job stress of not protecting the hand
hygiene isolation of fellow employees.567**, an increase in job stress caused
by a new pandemic, and various job stress at the same time.682** Various
simultaneous job stress and non-compliance with hand hygiene quarantine of
fellow employees.691**. in a previous paper The higher the infection control
fatigue, the higher the burnout, but the more required infection control tasks
other than the nurse's original work, the more difficult infection control
procedures, fear of infection transmission, and the new role of infection
control and the patient's needs [16]. In this study, the number of nursing
patients per day, wearing protective clothing, and fatigue from infection to
patients were high. In addition, the number of nursing patients per day and the
risk of infection in patients with protective clothing were 2.556 and .056,
indicating no significant difference in fatigue from wearing protective
clothing at the significance level of .05, and the F statistic was .399 and a
significance of .852.It was not significant at 05. Fatigue in wearing
protective clothing * The F statistic is 2.889 and the significance probability
is 2.889, which is a significance level. There was a significant difference.
This study aims to use it as basic data to find efficient dental hygiene manpower
management measures by identifying dental hygienists' COVID-19 infection
control job stress and infection control fatigue, correlating infection control
job stress with infection control fatigue, and identifying factors affecting
dental hygienists' work. Namely Personnel management should be divided into
personal and exposure accident management, hand hygiene, equipment
reprocessing, hygiene principles for employee safety, transport, washing,
checking, drying, sterilization and sterilization, sterilization monitoring,
records, administrative procedures, etc. Future research requires repeated
studies on infection control behavior targeting dental hygienists with various
careers and fields. The practical aspect of clinical dental hygienists is
meaningful in that they have proposed practical measures and interventions to
reduce infection control job stress and fatigue through work analysis to
allocate appropriate dental hygienists.
Clinical Relevance (Original
Articles and Review Articles)
This study
attempted to improve the efficiency of dental hygienists' work by using it as
basic data to find efficient dental hygienists' infection control measures by
identifying the factors affecting coronavirus infection control stress and
job-related fatigue.
Authorship
Dear
author: heeja conceived this study, analyzed the data, and led the writing.
Acknowledgments
We would
like to thank the dental workers at Y Dental Clinic, I Dental Clinic, H Dental
Clinic, and S Dental Hospital in Gwangju Metropolitan City for allowing us to
fill out the questionnaire for this study.
Conflict of Interest
No
potential conflict of interest relevant to this article was reported.
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