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Development of Perception and Attitude Scales Related with COVID-19 Pandemia/ COVID-19 Pandemisine İlişkin Algı ve Tutum Ölçeklerinin Geliştirilmesi

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Aim: The aim of this study is to develop scales that can enable to evaluate perceptions and attitudes associated with the outbreak during the COVID-19 pandemic. ___Materials and Methods: The research sample was composed of 352 healthcare workers and 507 non-healthcare workers. In the study, perceptions and attitudes regarding COVID-19 were evaluated on five scales: Perception of COVID-19 (P-COVID-19), Perception of Causes of COVID-19 (PCa-COVID-19), Perception of Control of COVID-19 (PCo-COVID-19), Avoidance Attitudes from COVID-19 (AA-COVID-19), and Attitudes Towards the COVID-19 Vaccine (ATV-COVID-19). In the study, scales were evaluated with appearance validity, content validity, structural validity (explanatory and confirmatory factor analysis) and Cronbach alpha internal reliability coefficients. ___Results: After the explanatory factor analysis, the scales were found to be suitable for factor analysis and had sub-dimensions. The P-COVID-19 scale had "Dangerousness" and "Contagiousness", the PCo-COVID-19 scale had "Macro Control", "Personal Control" and "Controllability", the PCaCOVID-19 scale had "Conspiracy", "Environment" and "Faith", the AA-COVID- 19 scale had "Cognitive" and "Behavioral avoidance", and the ATV-COVID-19 scale had "Positive" and "Negative Attitude" subscales. The determined subdimensions were evaluated by confirmatory factor analysis and good fit indexes were observed. Cronbach alpha coefficients were 0.74 for the P-COVID-19 scale, 0.79 for the PCo-COVID-19 scale, 0.88 for the PCa-COVID19 scale, 0.88 for the AA-COVID-19 scale, and 0.80 for the ATV-COVID-19 scale. ___Conclusion: When the validity and reliability analyze of the scales are evaluated together, it can be said that the scales have a valid and reliable structure that measures the perceptions and attitudes regarding COVID-19 both in healthcare workers and non-healthcare workers.
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DEVELOPMENT OF PERCEPTION AND ATTITUDE SCALES RELATED
WITH COVID-19 PANDEMIA
Dr. Bahadır Geniş
MD, Çaycuma State Hospital, Department of Psychiatry,
Zonguldak/Turkey
ORCID ID : 0000-0001-8541-7670
Nermin GÜRHAN
Prof. Dr., Tokat Gaziosmanpasa University, Faculty of Health Sciences,
Psychiatric Department of Nursing, Tokat/Turkey
ORCID ID: 0000-0002-3472-7115
Medine KOÇ
Assistant Professor, Tokat Gaziosmanpasa University, Faculty of Health
Sciences, Psychiatric Department of Nursing, Tokat/Turkey
ORCID ID: 0000-0001-9298-8885
Çiğdem GENİŞ
Master of Science, Çaycuma State Hospital, Health Care Services,
Zonguldak/Turkey
ORCID ID: 0000-0003-2244-1547
Burak ŞİRİN
Research Assistant, Tokat Gaziosmanpasa University, Faculty of Health
Sciences, Psychiatric Department of Nursing, Tokat/Turkey
ORCID ID: 0000-0002-8485-5756
Okan Cem ÇIRAKOĞLU
Associate Professor, Başkent University, Faculty of Science and Letters,
Department of Psychology, Ankara/Turkey
ORCID ID: 0000-0002-1607-3293
Behcet COŞAR
Prof. Dr., Gazi University Hospital, Department of Psychiatry, Ankara/Turkey
ORCID ID: 0000-0002-6422-499X
Abstract
Aim: The aim of this study is to develop scales that can enable to evaluate
perceptions and attitudes associated with the outbreak during the COVID-19
pandemic.
Materials and Methods: The research sample was composed of 352
healthcare workers and 507 non-healthcare workers. In the study,
perceptions and attitudes regarding COVID-19 were evaluated on five scales:
Perception of COVID-19 (P-COVID-19), Perception of Causes of COVID-19
(PCa-COVID-19), Perception of Control of COVID-19 (PCo-COVID-19),
Avoidance Attitudes from COVID-19 (AA-COVID-19) and Attitudes Towards
the COVID-19 Vaccine (ATV-COVID-19). In the study, scales were evaluated
with appearance validity, content validity, structural validity (explanatory and
confirmatory factor analysis) and Cronbach alpha internal reliability
coefficients.
Results: After the explanatory factor analysis, the scales were found to
be suitable for factor analysis and had sub-dimensions. The P-COVID-19
scale had "Dangerousness" and "Contagiousness", the PCo-COVID-19 scale
had "Macro Control", "Personal Control" and "Controllability", the PCa-
COVID-19 scale had "Conspiracy", "Environment" and "Faith", the AA-COVID-
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19 scale had "Cognitive" and "Behavioral avoidance", and the ATV-COVID-19
scale had "Positive" and "Negative Attitude" subscales. The determined sub-
dimensions were evaluated by confirmatory factor analysis and good fit
indexes were observed. Cronbach alpha coefficients were 0.74 for the P-
COVID-19 scale, 0.79 for the PCo-COVID-19 scale, 0.88 for the PCa-COVID-
19 scale, 0.88 for the AA-COVID-19 scale, and 0.80 for the ATV-COVID-19
scale.
Conclusion: When the validity and reliability analyze of the scales are
evaluated together, it can be said that the scales have a valid and reliable
structure that measures the perceptions and attitudes regarding COVID-19
both in healthcare workers and non-healthcare workers.
Key Words: COVID-19; perception; attitude; avoidance behavior; social
perception
INTRODUCTION
Coronaviruses is a common virus family which is known for a long period
and has an infection potential on all living things. Human type coronaviruses
have been detected since mid-1960s, and there are seven types of coronavirus
except New Type Coronavirus-19. Coronaviruses were considered among the
factors of human cold for many years, it has been determined that
coronaviruses which have entered our lives with Severe Acute Respiratory
Syndrome (SARS) since 2003 cause cold as well as severe clinical
manifestations. It was determined that SARS in 2003 and Middle East
Respiratory Syndrome (MERS) diseases and coronaviruses with the possibility
of transmission from animal to human and between humans were determined
in 2012 (1). Studies were started in order to identify the microorganism and
pandemic control by development of pulmonary infection in employees and
visitors of a market which sell seafood and living animals in Wuhan, China in
December, 29, 2019. 12. World Health Organization (WHO) called the virus
as new coronavirus (2019-nCoV) in January, 12, 2020. The New Type
Coronavirus Disease (COVID-19) which rapidly spreads was declared as
pandemic in March, 11, 2020 (2, 3).
COVID-19 pandemic has negative effects on mental health of the
community (4). All countries including our country have focused on effects of
pandemic on physical health (1, 5). However, psychosocial aspect should
urgently be discussed. Previous studies reported psychological effects of
pandemic and changes in perception and attitudes of individuals during
pandemics (6, 7). When outbreaks occur, public health agencies implement a
variety of pharmaceutical and non-pharmaceutical interventions to prevent
the spread of the epidemic, such as vaccination, school closures, social
distancing measures, hygienic measures (8). Knowledge, attitudes and
practices of the general population are the most critical factors in preventing
infection during pandemic periods (9, 10). Research has shown that the lack
of knowledge about the transmission and prevention methods of infectious
agents increases the likelihood of the spread of the epidemic (11). It was
emphasized that informing society about the infectious agent causing the
epidemic is the most basic need in order to control the epidemics (7, 12).
Individuals behave according to the representation of diseases in their minds.
Outbreaks are perceived as a situation that threatens their health and harms
the environment of trust in their lives for many individuals (13, 14). In this
case, individuals generally experience anxiety and fear. This situation also
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affects the behavior of individuals (15). In a study conducted during the avian
flu epidemic, it was shown that the perceptions of the lethality and stress
associated with avian flu are increased in individuals. It has been stated that
this stress causes avoidance behaviors in individuals such as not going to
hospital, not eating poultry meat, and not using public transportation (16).
Success in combating the epidemic is closely related to individuals'
compliance with the measures. Therefore, how individuals perceive the
epidemic and their attitudes for control of the epidemic are important. In
addition, the awareness of these perceptions and attitudes by health
authorities is very valuable in both managing the epidemic and achieving
success in combating the epidemic.
In a previous study conducted in Hong Kong after SARS, more than 90%
of the participants reported that public health measures were effective for
prevention, 40.4% reported that the disease would come back, and 70% stated
that they needed to wear masks in public places, and the disease is spread
by droplets as well as non-living objects, sewage water or from animals. In
the present study, 16% of the sample experienced post-traumatic symptoms,
it was stated that 48.4% of them had increased stress in the work and family
environment (6). It was shown in another study conducted in Australia that
even after the term "pandemic influenza" was explained to the participants,
there was an increase in the behaviours of individuals such as complying with
quarantine at home, staying away from public space and restricting their
social relations (7). This study is obvious evidence that the disease perception
in the community may play an effective role in the control of the pandemic.
Therefore, it is “vital” to evaluate society's perceptions and attitudes about the
disease in controlling infectious diseases. Changes in the illness perception
may be reflected in the attitudes of individuals and the increasing deaths may
be prevented. From this point of view, we aimed to develop scales that evaluate
perceptions and attitudes related to COVID-19.
MATERIALS AND METHODS
Study universe and sample
The population of the study consists of the healthcare professionals
around the researchers and their relatives. Snowball sampling method was
used to reach the participants who would represent the universe. An online
questionnaire link created digitally was sent to healthcare professionals
electronically via social media platforms. Inclusion criteria were determined
as cognitive, being over the age of 18, understanding the Turkish language,
and being volunteer to participate in the study. There were 876 individuals
who have accepted to participate into the study. Totally 859 questionnaires
which include full and complete date were evaluated. Majority of the sample
(80.1%) were college graduate. Among the participants, 41% (n=309) were
healthcare professionals whereas 59% (n=507) represented a society beyond
healthcare sector.
Preliminary study stage
There are many similarities between Swine Flu and Coronavirus Disease.
Both diseases are mainly droplet-borne and viral diseases that mainly affect
the respiratory system. In order to prevent both Swine Flu (H1N1) and
Coronavirus Disease, there are similar measures after contact including
frequent hand washing, wearing a mask and paying attention to social
distancing (4). That's why we adapted the scales developed by Çırakoğlu
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against swine flu in 2011 to COVID-19 (15). Newly developed scales were as
follows; Perception of COVID-19 (P-COVID-19), Perception of Control of
COVID-19 (PCo-COVID-19), Perception of Causes of COVID-19 (PCa-COVID-
19), Avoidance Attitudes from COVID-19 (AA-COVID-19) and Attitudes
Towards the COVID-19 Vaccine (ATV-COVID-19)
The expression “swine flu” in Perception and Attitude Scales related to
Swine Flu (H1N1) pandemic developed by Cirakoglu. Instead, general terms
such as “disease” or “virus” were used. The aim of developed scales was to
ensure that the scales developed were used both in the coronavirus epidemic
and in other epidemics.
In order to better evaluate this sub-dimension, the item “P-9” was added
to the “Contagiousness” sub-dimension of the P-COVID-19 scale. Since places
like schools and shopping malls were closed in accordance with the measures
taken for pandemic counteracting, "AA-8" and "AA-10" items were removed
from the AA-COVID-19 scale. The PCo-COVID-19 was removed due to the fact
that PCo-10 item in the "Personal control" sub-dimension is another item with
similar content (PCo-8). Since COVID-19 Causes Perception (PCa-COVID-19)
Scale "environment" sub-dimension PCa-9 has a similar content (PCa-10, 11,
12) was removed.
The Content and Appearance Validity
During the scope validity phase of these forms, nine experts who had
sufficient equipment and knowledge in the fields of psychiatry, psychology
and public health and could allocate sufficient time to the study were
determined. Six of nine experts were lecturers under different titles.
Remaining the individuals were specialists psychiatrists. The content validity
of the template form was performed according to Law. According to this
technique, the content validity ratio (CVR) performed with nine experts was
0.75. The P-3 item (CVR= 0.55) in the dangerousness sub-dimension of P-
COVID-19 scale below this value, AA-6 (CVR = 0.55) and AA-7 (CVR = 0.33)
and PCa-COVID-19 scales in the cognitive avoidance sub-dimension of the AA
COVID-19 scale, and PCa -10 (CVR = 0.33) and PCa -11 (CVR = 0.55) articles
were removed from relevant scales. Brief descriptions of the articles that
specialists consider inadequate were in the following:
Items P-3 and AA-7 were related to healthcare professionals.
Conduction of the study on healthcare professionals might have affected the
results.
Since items PCa -10 and PCa -11 of environment sub-dimension of the
PCa-COVID-19 scale were similar to each other, they were suggests to be
removed as there is another similar item (PCa -12).
A group of healthcare professionals and individuals beyond healthcare
professionals were interviewed personally to ensure apparent validity and
comprehensibility of the scale items. It was determined that there was no
problem of meaning and expression integrity in these interviews.
After the scope and appearance validity studies, P-COVID-19 scale was
planned as 8 items, PCo-COVID-19 scale was planned as 13 items, PCa-
COVID-19 scale was planned 15 items, AA-COVID-19 scale was planned as
12 items, and ATV-COVID-19 scale was planned in 9 items. A five-point Likert
form was used to determine the participation of the participants into the items
in the draft scales. These levels of participation were Definitely Disagree (1),
Disagree (2), Undecided (3), Agree (4), and Strongly Agree (5) in P-COVID-19,
PCa-COVID-19, PCo-COVID-19, and ATV-COVID-19 scales. In the AA-
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COVID-19 scale, it was I definitely do not do (1), I do not do (2), I am undecided
(3), I do (3) and I absolutely do (5). The total score obtained from each sub-
dimension in the scales is divided by the number of items in the sub-
dimension and a score between 1 to 5 is obtained.
In the power analysis performed to determine the sample size before the
study, it was aimed to access to at least 582 people within the confidence
interval of 95%, with an effect size and power by 0.2 and 0.80, respectively.
In the calculation of the effect size in the power analysis, the work done by
Cirakoglu was taken as a basis (15). Following these studies, validity and
reliability studies were started.
Data Collection Tools
Sociodemographic form, P-COVID-19, PCo-COVID-19, PCa-COVID-19,
AA-COVID-19, ATV-COVID-19 and Perceive Stress Scale (PSS) were used in
the present study (8).
The sociodemographic form included socio-demographic characteristics
(age, gender, marital status, educational status, profession, alcohol and
smoking) of 7 items prepared by the researchers.
The Perception of COVID-19 (P-COVID-19) scale was designed with eight
items and two sub-dimensions (Dangerousness and Contagiousness). The
“Dangerousness” sub-dimension evaluates the perceptions and beliefs about
the danger posed by the disease; however, the “Contagiousness” sub-
dimension evaluates the perceptions about the contagiousness of the disease.
Some expressions in the scale is reversely scored. The high scores in both
sub-dimensions indicate that the perception in that area is also higher.
The Perception of Control of COVID-19 (PCo-COVID-19) scale evaluates
beliefs about the control of the spread of the epidemic at individual,
institutional or global level. The template scale consists of thee sub-
dimensions and 13 items. The “Macro Control” sub-dimension evaluates the
beliefs about the measures taken at institutional, national or global level. The
“Personal (Micro) Control” sub-dimension evaluates the beliefs about the
personal precautions taken to prevent or catch the disease. The
“Controllability” sub-dimension evaluates the beliefs about the controllability
of the disease with the measures taken for the disease. Some items in the
scale are reversely scored. High scores in the macro and personal control
dimension reflect the belief that control may be achieved at a good level with
the measures taken, while the high scores in the controllability sub-
dimension reflect the belief that the disease may be controlled with the
measures taken.
The Perception of Causes of COVID-19 (PCa-COVID-19) evaluates the
beliefs related to possible causes of the pandemic. The template scale with
three sub-dimensions consists of 17 items. The “Conspiracy” sub-dimension
includes beliefs that the virus which is commonly seen in the media regarding
the epidemic is a biological weapon, and the epidemic is an attempt to sell
vaccines or a political game of developed countries. The “Environment” sub-
dimension includes items in which the main cause of the epidemic is
suggested like an unhealthy lifestyle, pollution of clean water resources and
environmental pollution. The “Faith” sub-dimension evaluates the belief that
the epidemic is a punishment of God due to inflicts against religion or social
degradation. There is not any opposite item in the scale. High scores in the
sub-dimensions show that the belief in that dimension is higher.
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Avoidance Attitudes from COVID-19 (AA-COVID-19) scale was designed
as a 12-item and five-point likert structure. There is not any opposite item in
this scale including three factors as cognitive avoidance, avoidance of
common space and personal contact. High scores obtained from sub-
dimensions show that avoidance in the relevant area is higher.
Attitudes Towards the COVID-19 Vaccine (ATV-COVID-19) scale has 9
items and two sub-dimensions (positive and negative attitude). The items are
scored reversely in the negative attitude sub-dimensions. Higher scores
obtained from positive attitude sub-dimension indicate that the attitude
towards vaccination is positive. The items in the negative attitude sub-
dimension are calculated after reversing, and higher scores in this sub-
dimension indicate that the negative attitude towards vaccination is less.
PSS was developed by Cohen et al. (17). ASO consists of 14 items and is
designed to measure how some situations in a person's life are perceived as
stressful. Higher scores obtained from sub-dimensions show that avoidance
in the relevant area is higher. The scale scores on five-Likert type varies
between 0 (Never) and 4 (Very common). The expressions included as positive
are scored reversely. Validity and reliability study of the scale in Turkish
language was performed by Eskin et al (18).
Ethical Dimension of the Study
The study was started by approval 08.05 of Ethical Committee of Social
and Human Sciences Researches of XXXX University on June, 5, 2020. The
study was conducted between June, 6, 2020 and June, 13, 2020 after
approval of the ethical committee. Furthermore, a permit was also obtained
for the study from Directorate of Healthcare Services of Turkish Ministry of
Health. On the first page of the link posted online, participants were informed
about the objectives of the study, and they were instructed that they could
withdraw from the study at any stage without stating a reason. The data of
the participants who ticked the checkbox that they agreed to participate in
the study were evaluated.
Statistical Analysis
SPSS 22.0 and AMOS 22.0 program were used for statistical analysis in
the study. Descriptive statistics were shown in frequency, percentage, mean
and standard deviation values. Since skewness/kurtosis values of the data
on numeric variables are between (±2), data was accepted to be distributed
normally (19). Pearson’s correlation test was used to assess the association
between numeric variables. Descriptive Factor Analysis (DFA) was used to
determine the validity of the structure. Cronbach alpha coefficient was
calculated for reliability of sub-dimensions and whole of the scale. Principal
Components Analysis method and varimax conversion method were used in
DFA. After the explanatory factor analysis, Confirmatory Factor Analysis
(CFA) was performed in order to test the accuracy of the scale factors
structure obtained in the scales. Maximum Likelihood Method Approach was
used in CFA. Statistical significance level was accepted as p<0.05 in analyses.
RESULTS
Sample characteristics
The participants included 529 (61.6%) females and 448 (52.2%) males.
Age average of the participants was 34.04±8.33 (median=32; min.=20, max.=
66) A significant part of the sample is college graduate (80.1%) and
undergraduate (15.0%). Healthcare professionals consisted of 41% (n=52) of
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the participants; and 59% (n=507) of the participants were individuals other
than healthcare professionals. Among healthcare professionals, 16.1% (n=57)
were physicians, 50% (n=176) were nurses, and 33.8% (n=119) were other
healthcare personnel. Individuals beyond healthcare professionals included
47 (9.2%) unemployed individuals, 141 (27.7%) private sector employees, 78
(15.3%) teachers, 45 (8.8%) academic personnel and 196 (38.5%) public
officers. Smoker rate of the sample was 35.4% (n=304), and 41.3% (n=355) of
the sample were using alcohol.
Item Analysis
In the present study, the corrected item / total correlation value was
taken to determine the scale items, and items with this value above ≥0.25
were included in the scales. P-COVID-19, corrected item / total correlation
values were reviewed. Correlation coefficients were found between 0.084 and
0.622. Since the item "P-4" in the Dangerousness sub-dimension of the scale
had a correlation coefficient of 0.084, it was excluded from the scale. PCo-
COVID-19, corrected item / total correlation values were between 0.102 and
0.582. Since the item " PCo -5" in the Macro-control sub-dimension of the
scale had a correlation coefficient of 0.102, it was excluded from the scale.
PCa-COVID-19, corrected item / total correlation values were between 0.151
and 0.704. The item " PCa -18" in the Belief sub-dimension of the scale had a
correlation coefficient of 0.151; therefore it was excluded from the scale. Since
corrected item/total correlation value of ATV-COVID-19 scale was between
0.298 and 0.696, AA-COVID-19 scale correlation value was between 0.515
and 0.728.
Descriptive Factor Analysis and Structure Validity
In Descriptive Factor Analysis, the adequacy of the sample was evaluated
through the Kaiser-Meyer-Olkin (KMO) test, and the suitability of the data for
factor analysis was evaluated through the Bartlett Sphericity (BS) test.
KMO values for P-COVID-19, PCa-COVID-19, PCo-COVID-19, AA-
COVID-19 and ATV-COVID-19 scales were 0.741, 0.872, 0.797, 0.877, and
0.828, respectively. Such analysis demonstrated that the sample size is
sufficient. The BS test results performed on P-COVID-19 (X2=1965.73; df=21;
p<0.001), PCa-COVID-19 (X2=10842.80; df=91; p<0.001), PCo-COVID-19
(X2=4050.84; df=66; p<0.001), AA-COVID-19 (X2=9987.88; df=45; p<0.001)
and ATV-COVID-19 (X2=6517.24; df=36; p<0.001) scales revealed that the
scales were consistent to factor analysis.
Factor loads of P-COVID-19, PCa-COVID-19, PCo-COVID-19, AA-
COVID-19 and ATV-COVID-19 scales were presented in Tables 1, 2, 3, 4, and
5, respectively. Factor loads of the scales were detected as follows; P-COVID-
19 scale between 0.629-0.890; PCa-COVID-19 scale between 0.660 and
0.934; PCo-COVID-19 scale between 0.665 and 0.890; AA-COVID-19 scale
between 0.824 and 0.972; and ATV-COVID-19 scale between 0.649 and
0.972.
It was found that the items in the P-COVID-19 scale explained 61% of
the total variance and the scale had a two-factor structure (Table 1).
"Contagiousness" sub-dimension consisted of 4 items; and "Dangerousness"
sub-dimension consisted of 3 items. Items in these sub-dimensions explained
42% and 19% of the total variance, respectively. Items on the PCa-COVID-19
scale explained 76% of the total variance (Table 2). The scale consisted of three
sub-dimensions including “Conspiracy” (6 items), “Environment” (5 items),
and “Faith” (3 items). Items in these sub-dimensions explained 42%, 19% and
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14% of the total variance, respectively. Items on the PCo-COVID-19 scale
explained 64% of total variance (Table 3). This scale had a three-factor
structure including "Macro Control" (4 items), "Personal Control" (4 items),
and "Controllability" (4 items). Items in these sub-dimensions explained 32%,
18%, and 13% of the total variance, respectively. It was found that the items
in the AA-COVID-19 scale explained 83% of the total variance and the scale
had a two-factor structure (Table 4). The sub-dimensions of avoiding common
space and avoiding personal contact were evaluated under one dimension as
"Behavioural Avoidance". Items of "Behavioural Avoidance" (5 items) and
"Cognitive Avoidance" (5 items) sub-dimensions respectively explained 49%
and 33% of the total variance. It was found that the items in the ATV-COVID-
19 scale explained 70% of the total variance and the scale had a two-factor
structure (Table 5). “Positive Attitude” sub-dimension consisted of 4 items;
and “Negative Attitude" sub-dimension consisted of 5 items. Items in these
sub-dimensions respectively explained 41% and 28% of the total variance.
Screen plot graphics of the scales were also presented in figures (Figure 1).
Confirmatory Factor Analyses
Confirmatory factor analysis (CFA) was performed on the same data set
to verify the factors obtained from the scales as a result of DFA.
Goodness of fit indices of P-COVID-19 scale (X2=30.336, df=13, p=0.004,
X2/df=2.334,Root Mean Square Error of Approximation (RMSEA) = 0.039,
Standardized Root Mean Square Residual (SRMR) =0.026, Goodness of fit
Index (GFI) = 0.990, AGFI (Adjusted Goodness of fit Index) = 0.978; Normed
Fit Index (NFI)=0.985 and Comparative Fit Index (CFI)=0.991) was detected
quite well.
It was detected from review of goodness of fit indices of PCo-COVID-19
scale that ratio of X2/df (X2=268.040, df=51, p<0.001) was slightly over 5
which is acceptable in a wide sample (5.256). Other fit indices of this scale
(RMSEA = 0.070, SRMR = 0.054, GFI = 0.949, AGFI = 0.921; NFI = 0.934 and
CFI = 0.946) were at acceptable levels. Modification suggestions were
reviewed. It was determined that the error correlation between " PCo -11" and
" PCo -12" items in the Inevitability sub-dimension was higher. An error
association was made for these items and CFA was re-evaluated. After the
analyses, fit indices (X2=236.450, df=50, p<0.001, X2/df=4.729,
RMSEA=0.066, SRMR=0.051, GFI=0.956, AGFI=0.932; NFI=0.942 and
CFI=0.953) were detected improved and data presented a better compliance.
The goodness of fit indices of the PCa-COVID-19 scale were reviewed.
X2/df ratio was 6.560. Other fit indices of the scale (RMSEA=0.080,
SRMR=0.039, GFI=0.920, AGFI = 0.886; NFI = 0.956 and CFI = 0.962) were
at acceptable levels. Review of modification suggestions reviewed that the
error correlation between "PCa-4" and “PCa-5”" items in the Inevitability sub-
dimension was higher. An error association was made for these items and
CFA was reviewed. In the new model obtained, the fit indices (X2 = 341.604,
df = 73, p <0.001, X2 / df = 4.680, RMSEA = 0.065, SRMR = 0.039, GFI =
0.942, AGFI = 0.917; NFI = 0.969 and CFI = 0.975) were detected improved.
It was detected from review of the goodness of fit indices of the AA-
COVID-19 scale that X2/df ratio was 11.880. Since this value was above the
acceptable limit, modification suggestions were considered. Error correlations
were made between items AA-1 and AA-2 in the Cognitive Avoidance sub-
dimension. In the analysis after this association, X2/df ratio was detected
5.583. Although it is close to an acceptable limit, error correlations were also
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performed between items AA-9 and AA-11 within the "Behavioural Avoidance"
sub-dimension. Fit indices of the scale were observed at acceptable levels
(X2=133.621, df=32, p<0.001, X2/df=4.176, RMSEA=0.061, SRMR=0.022,
GFI=0.972, AGFI=0.951; NFI=0.987 and CFI=0.990) after such association.
Review of the goodness of fit indices of the ATV-COVID-19 scale revealed
that X2/df ratio was 5.302. Other fit indices of this scale (RMSEA=0.071,
SRMR=0.046, GFI=0.966, AGFI=0.942; NFI=0.979 and CFI=0.983) were at
acceptable levels. Modification suggestions were reviewed. It was determined
that the error correlation between "ATV-8" and "ATV-9" items in the negative
attitude sub-dimension was higher. An error association was made for these
items and CFA was re-evaluated. After the analyses, fit indices (X2=93.805,
df=25, p<0.001, X2/df=3.752, RMSEA=0.057, SRMR=0.039, GFI=0.977,
AGFI=0.959; NFI=0.986 and CFI=0.989) were detected improved and data
presented a better compliance. Corrective factor analyses of the scales were
presented (Figure 1).
Reliability Analysis Results
According to the results obtained from the factor analysis, the sub-
dimensions of the scales and the internal consistency of the whole scale were
evaluated through Cronbach alpha coefficient. The Cronbach alpha coefficient
was detected as 0.74 for P-COVID-19 scale, 0.88 for PCa-COVID-19, 0.79 for
PCo-COVID-19, 0.88 for AA-COVID-19 and 0.80 for ATV-COVID-19 (Tables 1,
2, 3, 4 and 5, respectively). The Cronbach's alpha internal consistency
coefficient in the sub-dimensions of the scales ranged between 0.64 and 0.97.
Correlations Between sub-dimensions of the scales
Results of correlation analysis between the scales used in the study were
provided in the table (Table 6). The main objective of the scales used in this
study was to reach descriptive data evaluating perceptions and attitudes
about Coronavirus Disease. No cut-off score was calculated in the scales. The
relationships between the scale sub-dimensions are in an expected direction
(presence of a significant relationship between the sub-dimensions that make
up the scale); this shows that the scale is adequate for the study objective.
There was a positive and significant association between Perceives Stress
scale scores and Dangerousness (r = 0.087; p <0.05) and Contagiousness (r =
0.080; p <0.05) sub-dimensions of the P-COVID-19 scale; the Conspiracy (r =
0.081; p) of the PCa-COVID-19 scale; <0.05), Behavioural Avoidance (r =
0.071; p <0.05) and Total Avoidance (r = 0.073; p <0.05) subscale scores of
the AA-COVID-19 scale. A significantly negative association was detected
between ASÖ scores and Macro Control (r = -0.120, p <0.01), Personal Control
(r = -0.081, p <0.05), and Controllability (r = -0.140, p <0.01) sub-dimension
scores of PCo-COVID-19 scale.
DISCUSSION
Perceptions and attitudes about infectious diseases are affected by many
individual and social factors. Feeling in-danger and helplessness is effective
on past experiences, beliefs, perceptions and attitudes of the individual in
her/his social and cultural environment (20). Increasing anxiety and fear
during pandemic periods change the perception and attitude of illness (6). For
instance; it may not be questioned whether the influenza flu seen every year
is a biological war or whether the governments have taken adequate measures
in the control of the disease. However, as in the past swine flu epidemic, there
are many inquiries about these issues in both social media and traditional
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media for COVID-19 (21, 22). Previous studies indicated that a positive
change in the perception of individuals and societies is also effective in
epidemic control (7). Therefore, in our study, the aim was to develop scales to
evaluate perceptions and attitudes associated with pandemic of COVID-19.
In the item pooling phase of scale development, the scale items developed
by Çırakoğlu who was one of our researchers in 2010 were used after
rearrangement (15). In the literature, it was stated that methods such as
asking open-ended questions, benefiting from similar studies in the literature
and starting from clinical observations may be used during creation of an item
pool (23). Swine flu and COVID-19 are very similar for basic organs affected
by the disease, the route of transmission and, measures taken (4). Therefore,
we used scales in which perceptions and attitudes about H1N1 are evaluated
in this study.
Validity is a concept related to the degree to which the individual
correctly evaluates the feature of a scale. Among the validity techniques,
appearance, scope and structure validity are usually preferred (24). The
appearance validity of a scale is that the characteristics requested to be
measured by the scale may be clearly understood (25). Validity of the scope is
an indicator of whether the items of the scale are sufficient in terms of
quantity and quality in order to measure the feature to be measured. In
particular, it was stated that one of the logical ways to test the validity of scope
in measurement tools with more than one sub-dimension is to seek expert
opinion (24). In our study, personal validity of personal interviews was
performed with twelve people; and content validity was carried out with nine
experts in the field outside the research team. In line with expert opinions,
one item was removed from the P-COVID-19 scale, and two items were
removed from each of the PCa-COVID-19 and AA-COVID-19 scales.
Structural validity and reliability analyses were performed on the data
obtained from 859 participants via online connection. One of the important
validity techniques in the scale validity stage is to evaluate the construct
validity. Factor analysis is often used for construct validity. In the descriptive
factor analysis, factors are tried to be found depending on the association
between variables (25). Therefore, descriptive factor analysis was used in the
present study. The data compliance for factor analysis was examined through
KMO coefficient and the Barlett Sphericity (BS) test. In factor analysis, KMO
is expected to be higher than 0.60 for suitability in terms of sample size (25).
KMO values were found between 0.741 and 0.877 in the scales of our study.
This result shows that scales are adequate for factor extraction. The BS test
reviews the relationship between variables on the basis of partial correlations,
and a significant chi-square value indicates the suitability of the data matrix
(23-25). BK test results of the scales in our study were found to be significant
(p<0.001, for each). This significance indicates that the data in our study are
suitable for factor analysis.
Although there are many techniques used in factorization, the most
frequently used one is Principal Component analysis. Load values in the factor
are very important to determine which sub-factor the items in the scale belong
to. The value at and above 0.45 is a criterion for selection (24). The factor
values in the scales in our study were found between 0.629 and 0.972.
Another important parameter in factor analysis is the variance ratio
explained. The variance rate explained in one-dimensional scales is expected
to be at least 30%; however, this rate is expected to be higher in
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multidimensional scales (24, 25). The variance rate explained was 61% for the
P-COVID-19 scale, 76% for the PCa-COVID-19 scale, 64% for the PCo-COVID-
19 scale, 83% for the AA-COVID-19 scale, and 70% for the ATV-COVID-19
scale. According to these results, it was detected that factors in the scale
explain a significant portion of total variance in the items and variance related
to the scale.
CFA was performed to verify the factorial structure and goodness of fit
obtained with DFA. The chi-square value was detected significant in all scales
developed. It was stated that this value could be significant in larger sample
groups (26). When the X2/df ratios were examined, this value was detected
below five in the P-COVID-19 scale. In other scales, it was observed that items
with high error correlation decreased X2 / df values and it indicates the good
fit after error correlation. When other fit indices in the scales are examined,
the RMSEA value is below 0.80 in all scales, and the GFI, NFI and CFI values
are above 0.90 demonstrating that the model fit is very good (27).
Reliability is defined as the consistency between the responses of the
individuals in the scale items. Cronbach alpha internal reliability coefficient
and item-total item score correlation coefficients are generally used in
reliability analysis. A reliability coefficient calculated for a psychological test
of 0.70 or higher was reported to be adequate for the reliability of the scale
scores (25). The cronbach alpha internal reliability coefficients of the scales
in our study ranged between 0.74 and 0.88. Item / total correlation explains
the relationship between the scores obtained from the scale items and total
score of the scale. Elevation of these correlation coefficients indicates that the
item is adequate for general structure of the scale and its internal consistency
is high. It was reported that the corrected item / total correlation value must
be 0.20 and above (24, 25). We took the lower limit of this value as 0.25. As a
result of the analyses performed in our study, item P-4 in P-COVID-19 scale
(0.084), item PCo -5 of PCo-COVID-19 scale (0.102), and item PCa -18 of
COVID-19 PCa (0.151) were excluded from the study since their correlation
coefficient is below 0.25. In the analysis performed after excluding these
items, it was found that the corrected item / total correlation coefficients in
the scales were between 0.296 and 0.728 in our study. According to these
results, it is seen that all scales in our study have higher internal consistency
and reliability in their final form.
When the relationships between the scales and their sub-dimensions are
examined; the high dangerousness and contagiousness perceptions about
COVID-19 have been found to be associated with high stress. A similar
relationship has been observed in many past epidemics (6, 28). In individuals
with high perceptions of dangerousness, contagiousness, and lethality related
to the infectious agent, stress and psychiatric disorders were found to be
more common (28-30). In addition to this relationship, it has been observed
that individuals with high perceived stress have more conspiracy thoughts
about the causes of COVID-19. Conspiracy thoughts have been on the agenda
in many past epidemics (15, 31). It has been observed that these conspiracy
thoughts disrupt the relationship of trust at both individual and social levels.
In addition, research has shown that dominating conspiracy thoughts leads
to being closed to the innovations brought by science and rejecting science
(32). This is a serious problem during epidemic periods. Because during these
periods, individual and social cohesion is very valuable. Disruptions in social
cohesion lead to bias and refusal of treatments. For example, many
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conspiracy theories have been proposed regarding vaccines developed in past
epidemic periods, and these theories have been observed to reduce
vaccination rates (33). In our study, it was observed that the positive attitude
towards the COVID-19 vaccine decreased with the increase of conspiracy
thoughts. This relationship may be a finding that can be addressed by health
authorities. One of the results determined in our study that should be taken
into consideration by health authorities is that as the perception of stress
increases, individuals find the measures taken by health authorities to be
insufficient. No matter how effective measures are taken by health authorities,
if the stress and anxiety of individuals are not addressed, individuals may not
see the measures taken as sufficient. In a study conducted during the MERS
epidemic, it was observed that generally sensitive individuals were 17.8 times
more stressed than non-sensitive individuals. It has been observed that these
differences in stress levels among individuals cause significant differences in
reliability of preventive behaviors, application of preventive behaviors,
handwashing and reliability of policies (34). Similar to the results of this
study, in our study, it was found that the perception that the personal
precautions taken would not be sufficient to control the epidemic and that the
epidemic could not be controlled was dominant in stressed individuals. The
hopeless approach of individuals with these perceptions, the epidemic may
adversely affect the outcome in combating the epidemic. Past research has
shown that the higher the community participation in struggles, the higher
the success (16). One of the areas where social participation plays an
important role in combating the epidemic is vaccine therapy (8). It is stated
that vaccination rates have decreased in our country in recent years (35). It
is currently unclear what attitudes will the individuals take in to account
about the vaccine which is going to be developed for COVID-19. Along with
this uncertainty, it was found in our study that individuals with high
perception of stress have a higher negative attitude towards vaccination. This
also is one of the results to be taken into account. Among the scales, there
are important results, both sociologically and psychologically. For example,
individuals who have more religious faiths about the causes of COVID-19
think that health authorities are sufficient to combat and personal
precautions may be sufficient to control the epidemic, but they think it may
be difficult to control the epidemic. Many comments can be made for these
important relationships detected between the sub-dimensions of the scales.
However, since the main purpose of this study is to develop scales to
determine perceptions about COVID-19, these comments will not be
interpreted.
Our study has some limitations. First, it may be assumed that we have
reached a more educated population, considering that 80.1% of our sample
is college graduates and the study is conducted online in an electronic
environment. Therefore, findings obtained from the scales in further studies
on other parts of the society should be interpreted carefully. Second, even if
the reliability coefficient of the Dangerousness sub-dimension of the P-
COVID-19 scale is at an acceptable level, this partial decrease should be
considered during use of the scale. Third, the present study depends on self-
report scales. Lack of clinical interviews can be considered as a limitation.
Fourth limitation of the present study not providing a sufficient space for
findings and discussion of associations in sub-dimensions since the actual
objective of the study was to develop perception and attitude scales related to
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COVID-19 pandemic. Discussion of such associations in further studies
would make a great contribution to the literature.
CONCLUSIONS
P-COVID-19, PCa-COVID-19, PCo-COVID-19, AA-COVID-19 and ATV-
COVID-19 scales have considerably higher validity and reliability. Scales
developed may evaluate individual and social perceptions and attitudes
during the COVID-19 pandemic. These evaluations may play an important
role in disease counteracting both in the COVID-19 pandemic and in future
epidemics. However, it should be considered that valid and reliable structures
of all developed scales may also change in the long term, as perceptions and
attitudes of individuals on the pandemic may change in the future.
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TABLES AND FIGURES
Table 1. Validity and Reliability Analysis of P-COVID-19
Items no
Items
Mean ± SD
Dangerousness
Contagiousness
AI/TC
P-1
This disease is not as dangerous as told. (O)
4.24±1.08
0.731
0.296
P-2
Media exaggerates the pandemic. (O)
4.25±0.94
0.817
0.443
P-3*
Healthcare professionals exaggerate the pandemic. (O)
-
-
-
-
P-4**
This disease has a treatment. (O)
3.46±1.12
-
-
-
P-5
Virus causes a fatal disease.
4.61±0.60
0.759
0.501
P-6
This disease may spread to anybody.
3.89±1.06
0.629
0.426
P-7
The disease spreads easily.
4.50±0.87
0.890
0.659
P-8
Possibility of spread to women and men is similar.
4.50±0.84
0.875
0.629
P-9
The virus may spread via cargo or any shopping product
3.87±1.14
0.644
0.381
Eigenvalue
1.340
2.976
Variance
19.148
42.516
Cronbach alpha
0.64
0.75
Total Scale values; Content Validity Index=0.85; Variance=61.664; Cronbach alpha=0.74
P: Perception of COVID-19, AI/TC: Adjusted Item/Total Correlation, O: Opposite Item, df: degrees of freedom, SD: Standard Deviation
*Items excluded from the scale due to CVR smaller than 0.75
** Items excluded from the scale due to Adjusted Item/Total Correlation value below 0.25
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Table 2. Validity and Reliability Analyses of PCa-COVID-19
Item No Item
Components
AI/TC
Mean ±
SD
Conspiracy
Environment Faith
PCa -1
This disease is a political game revealed by developed countries.
2.26±1.12
0.924
0.691
PCa -2
The cause of this pandemic is the effort of developed countries to sell
drugs and vaccines
2.20±1.08
0.919 0.719
PCa -3
This virus is spread on purpose in order to make a contribution to
economic system
2.15±1.07
0.915 0.703
PCa -4
This disease was produced as a biological weapon.
2.39±1.18
0.916
0.696
PCa -5
This pandemic is a part of a great experiment.
2.31±1.15
0.913
0.698
PCa -6
The cause of this disease is economic crisis.
2.09±1.05
0.797
0.680
PCa -7
Environmental pollution is one of the important causes of the disease.
3.00±1.24
0.847
0.477
PCa -8
One of the causes of the pandemic is contamination of water
resources.
2.77±1.20
0.865 0.492
PCa -9***
This pandemic appeared because of unhealthy nutrition
-
-
-
-
-
PCa -10*
Hormones in vegetables and fruits cause the disease
-
-
-
-
-
PCa -11*
Foods with additives provided spread of the disease.
-
-
-
-
-
PCa -12
This disease is caused by the unhealthy life style.
2.86±1.27
0.753
0.435
PCa -13
Global warming is one of the causes of the pandemic.
2.60±1.18
0.805
0.489
PCa -14
These pandemics are effort of the nature to establish a balance.
2.93±1.20
0.660
0.345
PCa -15
Such pandemics are God's punishment for departure from religion.
1.72±1.13
0.932
0.493
PCa -16
This pandemic is a wrath of God against social degradation.
1.74±1.14
0.934
0.481
PCa -17
This pandemic is in our destiny.
1.83±1.16
0.825
0.397
PCa -18**
Consumption of wild animal (bat, etc.) meat causes illness.
3.33±1.18
-
-
-
-
Eigenvalue
5.948
2.749
2.069
Variance
42.487
19.638
14.781
Cronbach alpha
0.96
0.85
0.90
Total Scale Values; Scope Validity Index = 0.84, Variance = 76.906, Cronbach alpha = 0.88
PCa: Perception of Causes of COVID-19, AI/TC: Adjusted Item/Total Correlation, df: degrees of freedom, SD: Standard Deviation
*Items excluded from the scale due to CVR smaller than 0.75
** Items excluded from the scale due to Adjusted Item/Total Correlation value below 0.25
*** It was removed from the draft form during the preliminary study phase by the researchers.
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Table 3. Validity and Reliability Analyses of PCo-COVID-19
Item No Item Mean ± SD
Components
AI/TC
Macro
Control
Personal
Control
Controllability
PCo -1
Preventive studies in our country are enough.
2.09±1.03
0.871
0.503
PCo -2
What is done to stop the spread of the disease is sufficient
1.94±0.94
0.890
0.507
PCo -3
The work of health institutions is sufficient to fight against the
disease.
2.55±1.11 0.768 0.444
PCo -4
Preventive studies in the world are enough.
2.08±0.84
0.665
0.344
PCo -5**
Vaccination would prevent spread of the disease
3.28±1.02
-
-
-
-
PCo -6
I do not get the disease if I care my personal hygiene
2.90±1.00
0.819
0.567
PCo -7
If I care about my diet, the disease does not affect me
2.77±0.99
0.814
0.455
PCo -8
It is possible to prevent the disease by taking personal
precautions.
3.13±1.06 0.727 0.512
PCo -9
It is enough for everybody to wash their hands frequently to stop
the pandemic.
2.43±1.06 0.723 0.387
PCo -10***
The personal precautions taken are sufficient to avoid this
disease.
- - - - -
PCo -11
The individual cannot control to get the disease (O)
2.75±1.16
0.768
0.389
PCo -12
It is not possible to avoid a virus that you have not seen. (O)
3.33±1.26
0.800
0.316
PCo -13
Although we take precautions, we may not be able to prevent
the transmission of the disease. (O)
2.66±1.19 0.766 0.407
PCo -14
The personal precautions I take will be insufficient to protect me
from the disease. (O)
2.83±1.08 0.749 0.514
Eigenvalue
3.877
2.224
1.608
Variance
32.308
18.532
13.339
Cronbach alpha
0.83
0.80
0.78
Total Scale Values; Content Validity Index = 0.90, Variance = 64.238, Cronbach alpha = 0.79
PCo: Perception of Control of COVID-19, O: Opposite Item, AI/TC: Adjusted Item/Total Correlation, df: degrees of freedom, SD: Standard Deviation
** Items excluded from the scale due to Adjusted Item/Total Correlation value below 0.25
*** It was removed from the draft form during the preliminary study phase by the researchers.
PEARSON JOURNAL OF SOCIAL SCIENCES & HUMANITIES
2020
Volume 5 Issue 7 http://www.pearsonjournal.com/
Table 4 Validity and Reliability Analysis of the AA-COVID-19
Item No Item Mean ± SD
Components
AI/TC
Cognitive
Avoidance
Behavioural
Avoidance
AA-1
Distracting your attention when exposed to news about the disease
2.46±1.26
0.872
0.541
AA-2
Thinking about other things when talking about illness
2.30±1.20
0.886
0.547
AA-3
Not reading news about pandemic
2.34±1.26
0.824
0.515
AA-4
Changing the channel when news about the disease appears on TV
2.15±1.16
0.891
0.516
AA-5
Changing the subject to terminate talks about the disease
2.24±1.18
0.884
0.547
AA-6*
Getting away from the environment when there are conversations about the
disease around
- - - -
AA-7*
Avoiding to go to hospital or doctor to prevent the disease
-
-
-
-
AA-8***
Avoiding to go to shopping malls to prevent the disease
-
-
-
-
AA-9
Avoiding to participate into social activities to prevent the disease (movie,
theatre etc.)
4.09±1.33 0.939 0.702
AA-10***
Avoiding to go to work/school to prevent the disease
-
-
-
-
AA-11
Avoiding to take public transport to prevent getting sick
3.97±1.35
0.919
0.655
AA-12
Not kissing when greeting people, you know to avoid being sick
4.12±1.33
0.972
0.728
AA-13
Not shaking hands when greeting people to avoid being sick
4.12±1.32
0.966
0.715
AA-14
Avoiding to go to use public toilets to prevent the disease
3.94±1.37
0.914
0.672
Eigenvalue
3.361
4.943
Variance
33.607
49.434
Cronbach alpha
0.92
0.97
Total Scale Values; Scope Validity Index = 0.88, Variance = 83.041, Cronbach alpha = 0.88
AA: Avoidance Attitudes from COVID-19, AI/TC: Adjusted Item/Total Correlation, df: degrees of freedom, SD: Standard Deviation
*Items excluded from the scale due to CVR smaller than 0.75
*** It was removed from the draft form during the preliminary study phase by the researchers.
PEARSON JOURNAL OF SOCIAL SCIENCES & HUMANITIES
2020
Volume 5 Issue 7 http://www.pearsonjournal.com/
Table 5. Validity and Reliability Analyses of ATV-COVID-19
Item
No Item Mean ± SD
Components
AI/TC
Positive
Attitude
Negative
Attitude
ATV-
1
I want my family to have the vaccine to be developed / developed for this
disease.
3.50±1.30 0.966 0.689
ATV-
2
I want to have the vaccine to be developed / developed for this disease as
much as possible.
3.49±1.31 0.972 0.696
ATV-
3
I think everybody should have the vaccine to be developed / developed for
this disease.
3.51±1.29 0.970 0.689
ATV-
4
I trust to explanations made for the vaccine to be developed/developed 3.24±1.25 0.865 0.538
ATV-
5
The vaccine to be developed / developed
may cause spread of the disease (O)
3.38±1.12 0.725 .298
ATV-
6
I think the vaccine to be developed / developed will not / does not have a
protective effect. (O)
3.34±0.99 0.754 0.478
ATV-
7
The vaccine to be developed / developed is dangerous (O) 3.31±1.14 0.867 0.464
ATV-
8
I think the effectiveness of the vaccine to be developed / developed will not
be/has not been tested adequately. (O)
2.67±1.20 0.674 0.336
ATV-
9
I think I may survive the epidemic without a vaccine. (O) 2.74±1.10 0.649 0.306
Eigenvalue
3.759
2.579
Variance
41.762
28.653
Cronbach alpha
0.96
0.78
Total Scale Values; Scope Validity Index = 0.89, Variance = 70.415; Cronbach alpha = 0.80
ATV: COVID-19 Vaccination Attitude Scale, O: Opposite Item, AI/TC: Adjusted Item/Total Correlation, df: degrees of freedom, SD: Standard Deviation
PEARSON JOURNAL OF SOCIAL SCIENCES & HUMANITIES
2020
Volume 5 Issue 7 http://www.pearsonjournal.com/
Table 6 Correlations Between Sub-dimensions of scales
Scales and sub-
dimensions
1 2 3 4 5 6 7 8 9 10 11 12 13 14
P
(1)
Dangerousness
1
(2)
Contagiousness
0.330**
1
PCa
(3) Conspiracy
-
0.260
**
-
0.159
**
1
(4)
Environment
-0.067*
-0.006
0.250** 1
(5) Faith
-
0.188
**
-
0.192
**
0.332** 0.174** 1
PCo
(6) Macro
Control
-
0.238
**
-
0.138
**
0.159** 0.028 0.258** 1
(7) Personal
Control
-
0.130
**
-0.033
0.150** 0.082* 0.116** 0.354** 1
(8)
Controllability
0.022
-
0.071
*
-
0.121
**
-
0.117
**
-
0.096
**
0.139** 0.244** 1
AA
(9) Cognitive
Avoidance
0.006 -0.027
0.057 -0.074* 0.016 0.033 0.037 0.107** 1
(10) Behavioral
Avoidance
0.070* 0.011 0.015 -0.035 0.047 0.012 -0.016 0.004 0.176** 1
(11) Total
Avoidance
0.053 -0.008
0.044 -0.068* 0.042 0.028 0.011 0.066 0.717** 0.812**
1
ATV
(12) Positive
Attitude
0.169**
0.066
-
0.089
**
-
0.094
**
-0.024 0.002 -0.049 0.024 0.006 -0.024 -0.013 1
(13) Negative
Attitude
-0.086*
-
0.072
*
0.121** 0.043 0.054 0.029 0.013 -0.035 -0.010 -0.027 -0.025 0.122**
1
(14) PSS 0,087* 0.080*
0.081* 0.048 0.022
-
0.120
**
-0.081*
-
0.140
**
0.038 0.071* 0.073* 0.049
-
0.080
*
1
Mean
4,37
4.19
2.23
2.83
1.76
2.17
2.81
2.89
2.30
4.05
6.35
3.43
3.09
26.80
Standard Deviation
0,68
0.75
1.02
0.97
1.05
0.80
0.81
0.91
1.06
1.27
1.79
1.22
0.81
9.02
Scale Score Range
1-5
1-5
1-5
1-5
1-5
1-5
1-5
1-5
1-5
1-5
2-10
1-5
1-5
0-56
*p <0,05, **p <0,01
P: Disease Perception of COVID-19, PCo: Perception of Control of COVID-19, PCa: Perception of Causes of COVID-19, AA: Avoidance Attitudes from COVID-
19, ATV: Attitudes Towards the COVID-19 Vaccine, PSS: Perceived Stress Scale
PEARSON JOURNAL OF SOCIAL SCIENCES & HUMANITIES
2020
Volume 5 Issue 7 http://www.pearsonjournal.com/
Figure 1. Screen Plot Graphs of Scales and Confirmatory Factor Analysis
COVID-19 Hastalık Algısı Ölçeği (Perception of COVID-19 [P-COVID-19])
Tehlikelilik alt boyutu
Cronbach alfa=0,74
Varyans=61,664
1
Bu hastalık söylendiği kadar tehlikeli değil. (T)
Cronbach alfa=0,64
Varyans=19,148
2
Medya salgını abartıyor. (T)
3
Virüs ölümcül bir hastalığa neden olmaktadır.
Bulaştırıcılık alt boyutu
4
Bu hastalık herkese bulaşabilir.
Cronbach alfa=0,75
Varyans=42,516
5
Kolayca bulaşan bir hastalıktır.
6
Hastalığın kadınlara ve erkeklere bulaşma olasılığı
benzerdir.
7
Virüs kargo veya alışveriş ürünlerinden
bulaşabilir.
T= Ters maddeler
COVID-19 Hastalık Algısı Ölçeği, yedi maddeden oluşmaktadır. Beşli likert yapıda olan ölçek, “Tehlikelilik”
ve “Bulaştırıcılık” olmak üzere iki alt boyuttan oluşmaktadır. Bulunan ifadeler “Kesinlikle katılmıyorum (1)”,
“Katılmıyorum (2)”, “Kararsızım (3)”, “Katılıyorum (4)”, “Kesinlikle katılıyorum (5)” şeklinde
değerlendirilmektedir.
Tehlikelilik olarak isimlendirilen ilk alt boyut hastalığın COVID-19 yarattığı tehlikeye ilişkin algıları ve
inançları kapsamaktadır. Bulaşıcılık olarak isimlendirilen ikinci bileşen ise hastalığın bulaşıcılığına ilişkin
algılarla ilgili maddelerden oluşmaktadır. Ölçeğin Tehlikelilik alt boyutundaki bazı maddeler ters olarak
kodlanmaktadır.
Ölçek alt boyutundaki madde puanlarının toplanmasıyla elde edilen toplam puanın o alt boyuttaki madde
sayısına bölünmesiyle 1-5 arasında bir değer elde edilir.
Tehlikelilik alt boyutundaki yüksek puanlar, hastalıkla ilgili tehlikelilik algısının yüksek olduğunu,
bulaştırıcılık alt boyutundaki yüksek puanlar ise virüsün bulaştırıcılığının fazla olduğu algısını gösterir.
Ters maddeler 15; 24; 33; 42; 51 şeklinde kodlanmaktadır.
COVID-19’un Nedenleri Algısı Ölçeği (Perception of Causes of COVID-19 [PCa-COVID-19])
Komplo alt boyutu
Cronbach alfa=0,88
Varyans=76,906,
1
Bu hastalık gelişmiş ülkelerin ortaya koyduğu politik
bir oyundur.
Cronbach alfa=0,96
Varyans= 42,487
2
Bu salgının nedeni gelişmiş ülkelerin ilaç ve aşı
satma çabasıdır.
3
Bu virüs ekonomik sisteme katkı sağlamak için
bilinçli olarak yayıldı
4
Bu hastalık biyolojik bir silah olarak üretildi.
5
Bu salgın büyük bir deneyin parçasıdır.
6
Bu hastalığın nedeni ekonomik krizdir.
Çevre alt boyutu
7
Çevre kirliliği hastalığın önemli nedenlerinden biridir
Cronbach alfa=0,85
Varyans= 19,638
8
Salgının nedenlerinden biri su kaynaklarının
kirlenmesidir
9
Bu hastalık sağlıksız yaşam tarzının bir sonucudur.
10
Küresel ısınma salgının nedenlerinden bir tanesidir.
11
Bu tür salgınlar tabiatın dengesini kurması çabasıdır.
İnanç alt boyutu
12
Bu tür salgınlar toplumun dinden uzaklaşmasına
karşı Tanrının verdiği bir cezadır.
Cronbach alfa= 0,90
Varyans= 14,781
13
Bu salgın toplumsal bozulmaya karşı Tanrının bir
gazabıdır.
14
Bu salgın kaderimizde var.
COVID-19’un Nedenleri Algısı Ölçeği, on dört madde ve üç alt boyuttan oluşmaktadır. Ölçek beşli likert
yapıdadır. Bulunan ifadeler “Kesinlikle katılmıyorum (1)”, “Katılmıyorum (2)”, “Kararsızım (3)”,
“Katılıyorum (4)”, “Kesinlikle katılıyorum (5)” şeklindedir.
Ölçekteki ilk alt boyut “Komplo” olarak isimlendirilmiştir ve hastalığın nedenlerine dair medyada da sıklıkla
dile getirilen komplo inançlarını (biyolojik savaş, aşı satma çabaları vb.) kapsamaktadır. İkinci bileşen
COVID-19 salgınının olası nedenleri olarak sosyal ve fiziksel çevreyi gösteren “Çevre” bileşenidir. Bu
bileşende sağlıksız beslenme, küresel ısınma, doğal kaynakların kirletilmesi gibi nedenlere değinilmektedir.
Son bileşen ise “İnanç” olarak isimlendirilmiştir. Bu bileşendeki maddeler COVID-19‟un nedeni olarak dini
ve ruhsal açıklamalara olan algılarla ilgilidir. Örneğin salgının kaderimizde olduğu veya salgının toplumsal
bozulmaya karşı Tanrı‟nın bir gazabı olduğu gibi inançları içerir. Ölçekte ters madde yoktur.
Ölçek alt boyutundaki madde puanlarının toplanmasıyla elde edilen toplam puanın o alt boyuttaki madde
sayısına bölünmesiyle 1-5 arasında bir değer elde edilir. Bu değerin yüksekliği o alt boyuttaki algının
yüksekliğini gösterir.
COVID-19’un Kontrolü Algısı Ölçeği (Perception of Control of COVID-19 [PCo-COVID-19])
Makro Kontrol
Cronbach alfa=0,79
Varyans=64,238
1
Ülkemizdeki önleyici çalışmalar yeterlidir
Cronbach alfa=0,83
Varyans= 32,308
2
Hastalığın yayılmasını durdurmak için yapılanlar
yeterlidir
3
Hastalıkla mücadele için sağlık kurumlarının yaptığı
çalışmalar yeterlidir
4
Dünyadaki önleyici çalışmalar yeterlidir
Kişisel (Mikro) Kontrol
5
Kişisel temizliğime dikkat edersem hastalık bana
bulaşmaz
Cronbach alfa=0,80
Varyans= 18,532
6
Beslenmeme dikkat edersem bu hastalık beni
etkilemez
7
Hastalıktan kişisel tedbirler alarak korunmak
mümkündür
8
Salgını durdurmak için herkesin ellerini sıkça yıkaması
yeterli olur
Kontrol Edilebilirlik
9
Hastalığa yakalanmak kişinin kendi elinde değildir. (T)
Cronbach alfa=0,78
Varyans= 13,339
10
Görmediğin bir virüsten kaçınmak mümkün değildir.
(T)
11
Ne kadar önlem alınırsa alınsın hastalığın bulaşmasını
engelleyemeyebiliriz. (T)
12
Alacağım kişisel tedbirler hastalıktan korunmam için
yetersiz kalır. (T)
T= Ters maddeler
COVID-19’un Kontrolü Algısı Ölçeği, on iki maddeden oluşmaktadır. Ölçek beşli likert yapıdadır. Bulunan
ifadeler “Kesinlikle katılmıyorum (1)”, “Katılmıyorum (2)”, “Kararsızım (3)”, “Katılıyorum (4)”, “Kesinlikle
katılıyorum (5)” şeklinde değerlendirilmektedir. Makro kontrol, kişisel (mikro) kontrol ve kontrol edilebilirlik
olmak üzere üç alt boyuttan oluşmaktadır.
Makro kontrol; kurumsal, ulusal ya da küresel düzeyde alınan tedbirlerin etkililiğine ilişkin inançlarla ilgilidir.
Kişisel kontrol olarak isimlendirilen ikinci alt boyut hastalığa yakalanmamak için alınan kişisel tedbirlerin
etkililiği ile ilgilidir. Son alt boyut ise hastalığın kontrol edilebilirliği ile ilgili algıyı değerlendiren boyutudur.
Kontrol edilebilirlik alt boyutundaki maddeler ters olarak puanlanmaktadır. Ölçek alt boyutundaki madde
puanlarının toplanmasıyla elde edilen toplam puanın o alt boyuttaki madde sayısına bölünmesiyle 1-5 arasında
bir değer elde edilir.
Makro kontrol alt boyutundaki yüksek puanlar alınan önlemlerin yeterli olduğunu, kişisel kontrol boyutundaki
yüksek puanlar kişisel tedbirlerle hastalığın kontrolün iyi düzeyde sağlanabileceğini ve kontrol edilebilirlik
alt boyutundaki yüksek puanlar ise hastalığın kontrol edilebileceği inancını yansıtmaktadır
Ters maddeler 15; 24; 33; 42; 51 şeklinde kodlanmaktadır.
COVID-19’dan Kaçınma Tutumları Ölçeği (Avoidance Attitudes from COVID-19 [AA-COVID-19])
Bilişsel Kaçınma
Cronbach alfa=0,88
Varyans=83,041
1
Hastalıkla ilgili haberlere maruz kaldığınızda
dikkatinizi başka yere çevirmek
Cronbach alfa=0,92
Varyans=33,607
2
Hastalıkla ilgili konulardan söz edilirken başka şeyler
düşünmek
3
Salgınla ilgili haberleri okumamak
4
TV’de hastalıkla ilgili haberler çıktığında kanalı
değiştirmek
5
Hastalıkla ilgili konuşmaları sonlandırmak için konuyu
değiştirmek
Davranışsal Kaçınma
6
Hasta olmamak için sosyal etkinliklere katılmamak
(sinema, tiyatro vs.)
Cronbach alfa=0,97
Varyans= 49,434
7
Hasta olmamak için toplu taşıma araçlarına binmemek
8
Hasta olmamak için tanıdığınız insanlarla
selamlaşırken onları öpmemek
9
Hasta olmamak için tanıdığınız insanlarla
selamlaşırken ellerini sıkmamak
10
Hasta olmamak için umumi tuvaletleri kullanmamak
COVID-19’dan Kaçınma Tutumları Ölçeği, 10 maddeli ve beşli likert yapıdadır. Bilişsel kaçınma ve
davranışsal kaçınma olmak üzere iki alt boyutu vardır. Ölçekte bulunan ifadeler; Kesinlikle yapmıyorum (1),
Yapmıyorum (2), Kararsızım (3), Yapıyorum (3) ve Kesinlikle yapıyorum (5) şeklinde değerlendirilmektedir.
Ölçekte ters madde bulunmamaktadır. Ölçek alt boyutundaki madde puanlarının toplanmasıyla elde edilen
toplam puanın o alt boyuttaki madde sayısına bölünmesiyle 1-5 arasında bir değer elde edilir. Alt boyutlardan
alınan yüksek puanlar ilgili alandaki kaçınmanın yüksek olduğunu göstermektedir.
COVID-19 Aşısına Yönelik Tutumlar Ölçeği (Attitudes Towards the COVID-19 Vaccine [ATV-COVID-
19])
Olumlu Tutum
Cronbach alfa=0,80
Varyans=70,415
1
Ailemdekilerin bu hastalıkla ilgili
geliştirilecek/geliştirilen aşıyı olmasını isterim
Cronbach alfa=0,96
Varyans=41,762
2
İlk fırsatta bu hastalıkla ilgili geliştirilecek/geliştirilen
aşıyı olmak isterim
3
Bence herkes bu hastalıkla ilgili
geliştirilecek/geliştirilen aşıyı yaptırmalı
4
Geliştirilecek/geliştirilen aşı hakkında yapılan
açıklamalara güveniyorum
Olumsuz Tutum
5
Geliştirilecek/geliştirilen aşı hastalığın bulaşmasına
neden olabilir. (T)
Cronbach alfa=0,78
Varyans= 28,653
6
Geliştirilecek/geliştirilen aşının koruyucu etkisinin
olmayacağını/olmadığını düşünüyorum. (T)
7
Geliştirilecek/geliştirilen aşı tehlikelidir. (T)
8
Geliştirilecek/geliştirilen aşının etkililiği yeterince test
edilmeyeceğini/edilmediğini düşünüyorum. (T)
9
Aşı olmadan da salgını atlatabileceğimi düşünüyorum.
(T)
T= Ters maddeler
COVID-19 Aşısına Yönelik Tutumlar Ölçeği, 9 maddeli olup, iki alt boyuta (olumlu ve olumsuz tutum)
sahiptir. Ölçekte bulunan ifadeler “Kesinlikle katılmıyorum (1)”, “Katılmıyorum (2)”, “Kararsızım (3)”,
“Katılıyorum (4)”, “Kesinlikle katılıyorum (5)” şeklinde değerlendirilmektedir
Olumsuz tutum alt boyutlarındaki maddeler ters olarak puanlanmaktadır. Ölçek alt boyutundaki madde
puanlarının toplanmasıyla elde edilen toplam puanın o alt boyuttaki madde sayısına bölünmesiyle 1-5 arasında
bir değer elde edilir.
Olumlu tutum alt boyutundan alınan yüksek puanlar, aşıya yönelik tutumun olumlu olduğunu göstermektedir.
Olumsuz tutum alt boyutundaki maddeler ters çevrildikten sonra hesaplanır ve bu alt boyut puanlarındaki
yükseklik, aşıya karşı olumsuz tutumun daha az olduğunu göstermektedir.
Ters maddeler 15; 24; 33; 42; 51 şeklinde kodlanmaktadır.
... The sixth and final part was the Attitudes Toward COVID-19 Vaccine Scale (ATV-COVID19), which was first developed by Geniş et al. (2020). [12]. ...
... The sixth and final part was the Attitudes Toward COVID-19 Vaccine Scale (ATV-COVID19), which was first developed by Geniş et al. (2020). [12]. This scale also has nine items and consists of two domains: positive (4 items) and negative (5 items). ...
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... Bu doğrultuda bu çalışmada, Tarsus Devlet Hastanesi sağlık çalışanlarının COVID-19'a karşı aşılanmalarından sonra, bu aşılara tutumlarının değerlendirilmesi amaçlanmıştır. (6) . ...
... Çalışmamızda, Geniş ve ark.'nın geliştirdiği "COVID-19 Aşısına Yönelik Tutum" ölçeği kullanılmıştır.Ölçek beşli Likert tipi şeklinde hazırlanmış olup, 9 sorudan oluşmaktadır. Anket 3 ana bölümden oluşmaktadır(6) . İlk bölümde, ankete katılanların yaş, cinsiyet, eğitim düzeyi ve aylık gelirleri gibi sosyodemografik özellikleri; ikinci bölümde, katılımcıların sağlık durumu, COVID-19 geçirme durumu ve aşı geçmişi; üçüncü bölümde de COVID-19 aşısına karşı sağlık çalışanlarının tutumu hakkında bilgi toplanmıştır.COVID-19 Aşısına Yönelik Tutumlar Ölçeği Puanlaması:Geniş ve ark. ...
... An online survey including the sociodemographic form in addition to 52 multiple choice questions divided into five scales regarding perception and attitudes (6) was conducted among ophthalmologists (please see supplementary material). The survey designed in the local language was constructed using Google Forms and the link of the survey was shared via WhatsApp groups or personally to participants in the contact lists of the investigators. ...
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Aim: To investigate the level of perceptions and attitudes regarding COVID-19 among Turkish ophthalmologists in a tertiary eye care referral center. Material and Method: A cross-sectional survey-based study including the sociodemographic form in addition to 52 multiple-choice questions was conducted in March 2021. The questions were to assess the perception of three concepts separately: The disease, the causes of COVID-19, and the control of COVID-19. Along with this, it also included questions to evaluate the attitudes of avoidance of COVID-19 and attitudes towards the COVID-19 vaccine. Results: A total of 43 (15 males and 28 females) ophthalmologists completed the online survey. The perception of dangerousness and contagiousness was strong among ophthalmologists. The scores in the sub-dimensions of the perception of the causes of COVID-19 presented a moderate level. Statistically significant differences revealed between as follows: resident physicians and faculty in Macro Control (p=0.02), Controllability (p=0.38), and perception of the control of COVID-19 (p=0.022); males and females (p=0.009) along with resident physicians and faculty (p=0.023) in the behavioral avoidance attitudes from COVID-19; resident physicians and faculty in attitudes towards the COVID-19 vaccine (p=0.034). Conclusion: COVID-19 was perceived as dangerous and contagious among ophthalmologists. The perception of the control of COVID-19 was stronger among faculty than resident physicians. Females and faculty developed higher behavioral avoidance attitudes from COVID-19. Faculty exhibited less negative attitudes than resident physicians towards the COVID-19 vaccine. These assessments could shed light on our path in combating the disease, both in the COVID-19 pandemic and in future outbreaks.
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Nursing and midwifery students are an important resource in increasing COVID-19 vaccine acceptance among women of reproductive age. In this study, it was aimed to determine the thoughts of midwifery and nursing senior students to recommend COVID-19 vaccine to women of reproductive age and related factors. The data of the cross-sectional study were collected from 504 midwifery and nursing senior students across Türkiye between March 15th - April 30th, 2022, using the "Individual Identification Form", "Vaccine Opinion Form" and "Scale of Attitudes towards COVID-19 Vaccine" in the online environment with snowball sampling method. Data were evaluated with t test, chi-square analysis, correlation analysis, ANOVA, logistic regression, and decision tree analysis. Of the students, 84.3% were women, 50.2% were in the nursing department, and 97.6% had at least two doses of COVID-19 vaccine. While 44.4% of the students stated that they would not recommend vaccination to any of the women that pregnant, breastfeeding and planning to pregnancy, 22.6% reported that they could recommend the COVID-19 vaccine to all three groups. Students who thought they could be counselled on vaccines and had received a previous flu shot were more likely to recommend a COVID-19 vaccine, while students who did not find vaccines safe and believed they could be harmful and did not receive adequate training on vaccines were less likely to recommend vaccines. Counselling self-efficacy of students was affected by education and up-to-date information. It is recommended to develop knowledge and counselling skills so that nursing and midwifery students can recommend COVID-19 vaccine to women of reproductive age.
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Objective: The aim of this study is to investigate the effect of perceptions on the COVID-19 pandemic on the quality of life and suicidal ideation in both healthy controls and individuals with psychiatric disorders. Method: The study was conducted on 4 different groups with 83 depressive disorders, 90 anxiety disorders and 61 schizophrenia patients who have been followed in Gazi University Medical Faculty Hospital Mental Health and Diseases outpatient clinic since before the COVID-19 pandemic period and another group of 93 healthy volunteers. Participants were evaluated with Sociodemographic Data Form, Suicide Probability Scale (SPS), SF-36 Quality of Life Scale (SF- 36), Perception of COVID-19 Scale (P-COVID-19), and Perception of Causes of COVID-19 Scale (PCa-COVID-19). Results: The perception on the danger and contaigiousness of P-COVID-19 scored lowest in the schizophrenia group, compared to other groups and PCa-COVID-19's Conspiracy and Belief subdimension scores were highest. In all groups, a significant negative correlation was found between the P-COVID-19's dangerousness subdimension score and the SF-36 scale's Mental Health sub-dimension. Again, in all groups, significant positive correlations were found between the Dangerousness sub-dimension score of P-COVID-19 and the anger/impulsivity, hopelessness/loneliness and suicidal thoughts sub-dimensions of the SPS. Conclusion: The negative effects of perceptions associated with COVID-19 on mental health were observed both in groups with a psychiatric disorder and in healthy controls. The higher number of participants and longitudinal research will provide a better understanding of the effects of perceptions associated with COVID-19 and will guide the necessary treatment interventions.
Article
Aim: To identify healthcare professionals' attitudes toward the coronavirus vaccine. Background: Controlling the coronavirus pandemic depends on achieving a high level of herd immunity. Accordingly, it is very important that healthcare professionals become role models by displaying positive attitudes toward vaccination. Methods: This cross-sectional study was conducted between March and April 2021 with a total of 309 healthcare professionals. Data were collected via an online surveys using an "Introductory Information Form" and "Attitudes Towards the COVID-19 Vaccine Scale." One-way variance analysis and Bonferroni correction were used for the comparison of nonnormally distributed quantitative variables between more than two groups. The Kruskal-Wallis test and Dunn-Bonferroni test were used to compare non-normally distributed quantitative variables between more than two groups. Pearson correlation analysis was performed to evaluate the relationships between the quantitative variables. Results: Regarding the healthcare professionals' attitudes towards the COVID-19 vaccine, the average score of positive attitudes was 3.52 ± 0.87, and the average score of negative attitudes was 3.39 ± 0.68. A statistically significant weak relationship was found between the ages of the participants and the average score of their positive attitudes towards the COVID-19 vaccine. The negative attitude score of the individuals who wanted to get the coronavirus vaccine was significantly higher than those who were undecided or did not want to get the vaccine. Conclusions: Healthcare professionals completely agreed with the opinion "I would persuade everyone around me to get the coronavirus vaccine," and completely disagreed with the opinion "I believe that they will inject microchips to people with the coronavirus vaccine." Healthcare professionals have positive attitudes toward the COVID-19 vaccine. COVID-19-vaccinated participants' positive and negative attitude scores were found higher than those who were not vaccinated. Implications for nursing and health policy: Supportive social activities should be organized in the public sense so that healthcare professionals act as a role model by displaying positive attitudes toward vaccination.
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Background: The aim of this research is to develop a multidimensional scale that reveals the psychosocial impact of coronavirus disease 2019 (COVID-19) pandemic on people with its dimensions. Methods: An item pool of 155 questions was created by examining the literature, and these items were turned into a questionnaire with 76 questions by taking expert opinions. During the pilot study, this questionnaire was applied to 335 people from the general population, who were reached with the snowball sampling model. The second phase of the study was carried out with a second new sample group consisting of 826 participants, and confirmatory factor analysis, mean explained variance and compound reliability, and Cronbach's alpha analyses were applied to the obtained data. The test-retest study of the scale was reapplied to the second sample group, reaching 826 participants with an interval of 3 weeks. Results: The explained variance value of the scale was 81.352%. As a result of confirmatory factor analysis, the factor loads of the items of the scale were between 0.59 and 0.91, and the relationships between the items and the latent variables were significant at the P < .01 level; fit criteria is excellent and acceptable; Cronbach's alpha coefficient was found to be between 0.897 and 0.957, and as a result of the test-retest, the reliability coefficients were found to be between 0.948 and 0.950.
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Objective: The effects of the COVID-19 pandemic on both the physical and psychological well-being of individuals have not yet been clearly understood. Especially during the early period of the pandemic, the most prevalent psychological effects included fear, preoccupation with health, anxiety, and feeling of loneliness caused by a general sense of uncertainty. The incidence of headache was as high as 70% among the mild COVID-19 cases. Findings from the past coronavirus outbreaks indicated that neuropsychiatric symptoms might cause a significant health burden and adversely affect the patients’ quality of life. The present study aimed to investigate the anxiety-related clinical conditions of the patients diagnosed with primary headache, who presented to the neurology polyclinic during the prolonged pandemic period. Methods: The research was designed as a two-center, prospective case-control study. Patients diagnosed with primary headache, who presented to the neurology outpatient clinic, and healthy volunteers without a primary headache diagnosis were included in the study. Data collection tools included the sociodemographic data form, Headache Impact Test, Coronavirus Anxiety Scale Short Form, and COVID-19 Disease Perception Scale. Results: Data collected from a total of 869 participants, including 408 (47%) patients diagnosed with headache and 461 (53%) healthy volunteers, were investigated. The results of the Headache Impact Test-6 suggested a severe effect on quality of life in 187 participants (45.8%) in the headache group and 73 participants (15.8%) in the Control Group (p=0.001). There was coronavirus anxiety in 59 (14.5%) participants with headache and 8 (1.7%) participants in the Control Group (p=0.001). Furthermore, the rate of coronavirus anxiety in participants that had and did not have COVID-19 was 44 (13.7%) and 22 (4.1%), respectively (p=0.001). Conclusion: The study results revealed that patients with headache and COVID-19 presented with a higher rate of coronavirus anxiety than healthy controls and those not diagnosed with COVID-19. Further studies on larger samples are necessary for investigating the long term neuropsychiatric effects of COVID-19 in individuals.
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The ongoing COVID-19 pandemic is shaking the foundations of public health governance all over the world. Researchers are challenged by informing and supporting authorities on acquired knowledge and practical implications. This Editorial applies established theories of risk perception research to COVID-19 pandemic, and reflects on the role of risk perceptions in these unprecedented times, and specifically in the framework of the International Journal of Environmental Research and Public Health Special Issue “Research about risk perception in the Environmental Health domain”.
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As infectious disease outbreaks emerge, public health agencies often enact vaccination and social distancing measures to slow transmission. Their success depends on not only strategies and resources, but also public adherence. Individual willingness to take precautions may be influenced by global factors, such as news media, or local factors, such as infected family members or friends. Here, we compare three modes of epidemiological decision-making in the midst of a growing outbreak using network-based mathematical models that capture plausible heterogeneity in human contact patterns. Individuals decide whether to adopt a recommended intervention based on overall disease prevalence, the proportion of social contacts infected, or the number of social contacts infected. While all strategies can substantially mitigate transmission, vaccinating (or self isolating) based on the number of infected acquaintances is expected to prevent the most infections while requiring the fewest intervention resources. Unlike the other strategies, it has a substantial herd effect, providing indirect protection to a large fraction of the population.
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Background Infectious disease outbreaks have the potential to cause a high number of fatalities and are a very serious public health risk. Objectives Our aim was to utilise an indepth method to study a period of time where the H1N1 Pandemic of 2009 was at its peak. Methods A data set of n = 214 784 tweets was retrieved and filtered, and the method of thematic analysis was used to analyse the data. Results Eight key themes emerged from the analysis of data: emotion and feeling, health related information, general commentary and resources, media and health organisations, politics, country of origin, food, and humour and/or sarcasm. Discussion A major novel finding was that due to the name ‘swine flu’, Twitter users had the belief that pigs and pork could host and/or transmit the virus. Our paper also considered the methodological implications for the wider field of library and information science as well as specific implications for health information and library workers. Conclusions Novel insights were derived on how users communicate about disease outbreaks on social media platforms. Our study also provides an innovative methodological contribution because it was found that by utilising an indepth method it was possible to extract greater insight into user communication.
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Introduction: Despite its proven efficacy, vaccination rates with influenza vaccine are considerably low. This study aimed to investigate the vaccination rates with influenza-vaccine and the factors affecting attitude toward vaccination. Materials and methods: A questionnaire was applied to patients presenting to outpatient clinic between October 2011-January 2012. Result: Of these 1251 (671 F, 580 M) patients with a mean age of 47.7 ± 15.1, 61.9% had an indication for influenza-vaccination. The rate of vaccination was 33.4%. Among the vaccinated patients, the ratio of patients with an educational level of high-school or above (60.6%) was greater than that of patients with a lower educational level (39.4%) (p= 0.01). The vaccination rates were greater among those with chronic lung disease (43.6%), heart disease (21.2%), and diabetes (19.3%) (p< 0.001, p= 0.02, and p= 0.03, respectively). A multivariate regression analysis revealed that the independent variables associated with vaccination were considering the vaccine protective (OR, 2.13; CI, 1.85-4.24, p= 0.03), getting vaccinated to protect oneself (OR, 6.31; CI, 3.25-12.63, p< 0.001), getting vaccinated to protect one's family against influenza (OR, 5.42; CI, 3.11-9.54, p= 0.02), the vaccine being recommended by a physician (OR, 4.15; CI, 2.03-7.45, p< 0.001), being regularly-vaccinated (OR, 5.32; CI, 3.24-6.35, p< 0.001), and suffering from chronic lung disease (OR, 2.21; CI, 1.64-4.32, p< 0.001). The reasons of not getting vaccinated were considering the vaccine useless (OR, 2.46; CI, 0.77-3.98; p= 0.01),having concerns about side-effects (OR, 2.14; CI, 0.16-3.25; p= 0.02),and having inadequate knowledge (OR, 7.12; CI, 4.23-12.56; p< 0.001). Men, as compared to women, had a significantly greater rate of considering the vaccine useful (p< 0.001), getting vaccinated during campaigns held by workplaces (p= 0.002), and obtaining information through bills, brochures, or bulletins (p= 0.003). Patients vaccinated with the influenza-vaccine significantly more commonly consider the pneumococcal-vaccine useful (p= 0.02), and they had a significantly greater rateofvaccination with pneumococcal-vaccine (p< 0.001). Conclusions: The vaccination rate remains low. Opinions about the vaccine that had favourable effect on vaccination rate were that the vaccine was beneficial and that it would protect one's family against the disease. The unvaccinated patients had inadequate knowledge of the vaccine. Obtaining information from a physician boosts vaccination rate. Men having a greater rate of vaccination through campaigns of workplaces as well as a greater rate of being informed can be explained by a higher employment rate in men.
Article
Numerous patients with asthma or COPD are likely to be infected with SARS-CoV-2 virus. Although data is limited, patients with severe and/or uncontrolled asthma and those with COPD appear to be at increased risk of a more severe course of COVID-19 infection. Usual recommendations for management of asthma and COPD remain valid despite the ongoing epidemic. However, lung function testing and nebulisers should be performed with caution during the COVID-19 pandemic due to a potential risk of virus aerosolisation and contagion during the procedure. Particular care must be taken to identify and protect patients who are particularly vulnerable to COVID-19 infection. Asthma and COPD treatments should be pursued and adapted to ensure optimal control of the lung disease throughout the epidemic, thus reducing the risk of severe COVID-19 disease.
Article
China has been severely affected by Coronavirus Disease 2019(COVID-19) since December, 2019. We aimed to assess the mental health burden of Chinese public during the outbreak, and to explore the potential influence factors. Using a web-based cross-sectional survey, we collected data from 7,236 self-selected volunteers assessed with demographic information, COVID-19 related knowledge, generalized anxiety disorder (GAD), depressive symptoms, and sleep quality. The overall prevalence of GAD, depressive symptoms, and sleep quality of the public were 35.1%, 20.1%, and 18.2%, respectively. Young people reported a significantly higher prevalence of GAD and depressive symptoms than older people. Compared with other occupational group, healthcare workers were more likely to have poor sleep quality. Multivariate logistic regression showed that age (< 35 years) and time spent focusing on the COVID-19 (≥ 3 hours per day) were associated with GAD, and healthcare workers were at high risk for poor sleep quality. Our study identified a major mental health burden of the public during the COVID-19 outbreak. Young people, people spending too much time thinking about the outbreak, and healthcare workers were at high risk of mental illness. Continuous surveillance of the psychological consequences for outbreaks should become routine as part of preparedness efforts worldwide.
Article
Novel Corona Virus Disease (COVID-19) originating from China has rapidly crossed borders, infecting people throughout the whole world. This phenomenon has led to a massive public reaction; the media has been reporting continuously across borders to keep all informed about the pandemic situation. All these things are creating a lot of concern for people leading to heightened levels of anxiety. Pandemics can lead to heightened levels of stress; Anxiety is a common response to any stressful situation. This study attempted to assess the knowledge, attitude, anxiety experience, and perceived mental healthcare need among adult Indian population during the COVID-19 pandemic. An online survey was conducted using a semi-structured questionnaire using a non-probability snowball sampling technique. A total of 662 responses were received. The responders had a moderate level of knowledge about the COVID-19 infection and adequate knowledge about its preventive aspects. The attitude towards COVID-19 showed peoples' willingness to follow government guidelines on quarantine and social distancing. The anxiety levels identified in the study were high. More than 80 % of the people were preoccupied with the thoughts of COVID-19 and 72 % reported the need to use gloves, and sanitizers. In this study, sleep difficulties, paranoia about acquiring COVID-19 infection and distress related social media were reported in 12.5 %, 37.8 %, and 36.4 % participants respectively. The perceived mental healthcare need was seen in more than 80 % of participants. There is a need to intensify the awareness and address the mental health issues of people during this COVID-19 pandemic.
Article
Since December 2019, a series of unexplained pneumonia cases have been reported in Wuhan, China. On 12 January 2020, the World Health Organization (WHO) temporarily named this new virus as the 2019 novel coronavirus (2019‐nCoV). On 11 February 2020, the WHO officially named the disease caused by the 2019‐nCoV as coronavirus disease (COVID‐19). The COVID‐19 epidemic is spreading all over the world, especially in China. Based on the published evidence, we systematically discuss the characteristics of COVID‐19 in the hope of providing a reference for future studies and help for the prevention and control of the COVID‐19 epidemic. Research Highlights • Currently, the world is watching the progress of Corona Virus Disease 2019 (COVID‐19) epidemic. The purpose of our article is to give people a comprehensive understanding of COVID‐19, so that they can better prevent it. We review the latest published papers on COVID‐19. In this paper, the origin of the virus, the mechanism of virus infection, the clinical characteristics of COVID‐19 and the treatment and prevention of COVID‐19 are comprehensively elaborated. We hope this article will help for the prevention and control of the COVID‐19 epidemic.
Article
Background: This study aimed to identify nurses' experiences of care for patients with Middle East respiratory syndrome-coronavirus (MERS-CoV). Their experiences can be useful to establish a safer healthcare system in preparation for infectious disease outbreaks. Methods: Data were collected through in-depth individual interviews and analyzed using Colaizzi's phenomenological method. Participants were 12 nurses. Results: Nurses' experiences of care for patients with MERS-CoV were categorized as follows: "Going into a dangerous field," "Strong pressure because of MERS-CoV," "The strength that make me endure," "Growth as a nurse," and "Remaining task." Conclusions: It is necessary to examine the difficulties and demands of healthcare providers for establishing a safe healthcare system to respond effectively when national disasters occur. In addition, it is necessary to develop strategies to protect healthcare providers from severe physical and psychological stress.
Article
OBJECTIVE: To examine the level of stated compliance with public health pandemic influenza control measures and explore factors influencing cooperation for pandemic influenza control in Australia. METHODS: A computer-assisted telephone interview survey was conducted by professional interviewers to collect information on the Australian public's knowledge of pandemic influenza and willingness to comply with public health control measures. The sample was randomly selected using an electronic database and printed telephone directories to ensure sample representativeness from all Australian states and territories. After we described pandemic influenza to the respondents to ensure they understood the significance of the issue, the questions on compliance were repeated and changes in responses were analysed with McNemar's test for paired data FINDINGS: Only 23% of the 1166 respondents demonstrated a clear understanding of the term "pandemic influenza". Of those interviewed, 94.1% reported being willing to comply with home quarantine; 94.2%, to avoid public events; and 90.7%, to postpone social gatherings. After we explained the meaning of "pandemic" to interviewees, stated compliance increased significantly (to 97.5%, 98.3% and 97.2% respectively). Those who reported being unfamiliar with the term "pandemic influenza," male respondents and employed people not able to work from home were less willing to comply. CONCLUSION: In Australia, should the threat arise, compliance with containment measures against pandemic influenza is likely to be high, yet it could be further enhanced through a public education programme conveying just a few key messages. A basic understanding of pandemic influenza is associated with stated willingness to comply with containment measures. Investing now in promoting measures to prepare for a pandemic or other health emergency will have considerable value.