Original Article
Public Health
Kasmera 48(1):e48106042020, Enero-Junio, 2020
P-ISSN 0075-5222 E-ISSN 2477-9628
https://doi.org/10.5281/zenodo.3827988
Validation of a short scale for measuring the level of
basic knowledge about Coronavirus, Peru (KNOW-P-COVID-19)
Validación de
una escala breve para la medición del nivel de conocimientos básicos acerca del
Coronavirus, Perú (KNOW-P-COVID-19)
Mejia
Christian R (Autor de
correspondencia). https://orcid.org/0000-0002-5940-7281.
Universidad Continental. Facultad de Medicina Humana. Huancayo-Junín. Perú.
Dirección Postal: Av. Las Palmeras 5713, Los Olivos, Lima, Perú. CP: 15304.
Teléfono: (511) 997643516. E-mail: christian.mejia.md@gmail.com
Rodríguez-Alarcón J Franco. https://orcid.org/0000-0003-4059-8214.
Universidad Ricardo Palma. Facultad de Medicina Humana “Manuel Huamán
Guerrero”. Lima, Perú. Asociación Médica de Investigación y Servicios en Salud.
Lima, Perú. E-mail: franco.investigacion.peru@gmail.com
Carbajal Macarena. https://orcid.org/0000-0003-1960-2952.
Universidad Hermilio Valdizán. Sociedad Científica de Estudiantes de Medicina
de Huánuco. Huánuco-Huánuco. Perú. E-mail: macarena_cv10@hotmail.es
Sifuentes-Rosales
Jhesly. https://orcid.org/0000-0003-3740-2188.
Universidad Hermilio Valdizán. Sociedad Científica de Estudiantes de Medicina
de Huánuco. Huánuco-Huánuco. Perú. E-mail: jhesly0131@gmail.com
Campos-Urbina
Alejandra M. https://orcid.org/0000-0003-3187-4846.
Universidad Nacional Hermilio Valdizan. Facultad de Medicina Humana. Huanuco,
Huanuco, Perú. E-mail: alecampur0196@gmail.com
Charri
Julio C.
https://orcid.org/0000-0002-3613-3791. Universidad Nacional Daniel
Alcides Carrión. Facultad de Medicina Humana. Cerro de Pasco-Pasco. Perú. E-mail: juliocesarcv1907@gmail.com
Garay-Rios Lizet. https://orcid.org/0000-0002-0577-7391. Universidad
Nacional del Centro del Perú. Facultad de Medicina Humana. Huancayo-Junín.
Perú. E-mail: ligari98822@gmail.com
Al-Kassab-Cordova Ali. https://orcid.org/0000-0003-3718-5857.
Universidad
Peruana de Ciencias Aplicadas. Escuela de Medicina. Sociedad Científica de
Estudiantes de Medicina de la Universidad Peruana de Ciencias Aplicadas. Lima. Perú. E-mail: aliac1998@gmail.com
Mamani-Benito Oscar. https://orcid.org/0000-0002-9818-2601. Universidad
Peruana Unión. Escuela Profesional de Psicología. Juliaca-San Román. Perú. E-mail:
psicobenito@gmail.com
Apaza-Tarqui
Edison Effer. https://orcid.org/0000-0002-6520-3795.
Facultad de Ingeniería y Arquitectura. Universidad Peruana Unión. Lima, Perú. E-mail:
effer@upeu.edu.pe
Abstract
The coronavirus has generated the last pandemic,
therefore, knowing this disease is important in all populations. For this, a
short scale was validated to measure basic knowledge about Coronavirus
(KNOW-P-COVID-19). First, it carried out a bibliographic search, then it was
systematized and obtained the most important aspects, then a validation of the
construct with experts, then exploratory factor analysis and the survey was
applied to a large Peruvian population group. All items received a favorable
evaluation from the experts (Aiken's V> 0.70); all the lower limit values
(Li) of the 95% CI are appropriate (Li> 0.59) and all the values of the V
coefficient were statistically significant. In the Exploratory Factor Analysis
(AFE), the KMO Coefficient = 0.690 and the p value of the chi square <0.001;
the GFI index (Goodness of Fit Index) = 0.992; the CFI (Comparative Fit Index)
= 0.916 and the RMSEA indicator (Root Mean Square Error of Approximation) =
0.034. The final scale was left with 9 indicators, with two factors:
"indications or actions post infection" and "the previous
symptoms and knowledge". A basic knowledge scale in the disease caused by
COVID-19 was validated.
Keywords: validation study, coronavirus, knowledge, pandemic,
SARS-CoV-2
Resumen
El
coronavirus ha generado la última pandemia, por lo que, el conocer a esta
enfermedad es importante en todas las poblaciones. Para eso se validó una
escala breve para la medición de los conocimientos básicos acerca del
Coronavirus (KNOW-P-COVID-19). Primero realizó una búsqueda bibliográfica,
luego se sistematizó y obtuvo los aspectos más importantes, luego una
validación del constructo con expertos, posteriormente el análisis factorial
exploratorio y se aplicó la encuesta a un gran grupo poblacional peruano. Todos
los ítems recibieron una evaluación favorable de los expertos (V de Aiken >
0,70); todos los valores del límite inferior (Li) del IC 95% son apropiados (Li
> 0,59) y todos los valores del coeficiente V fueron estadísticamente
significativos. En el Análisis Factorial Exploratorio (AFE), el Coeficiente de
KMO = 0,690 y el valor p del chi cuadrado <0,001; el índice GFI (Goodness of Fit
Index) = 0,992; el CFI (Comparative
Fit Index) = 0,916 y el
indicador RMSEA (Root Mean Square Error of Approximation) = 0,034. La escala
final se quedó con 9 indicadores, con dos factores: “indicaciones o acciones
post infección” y “los síntomas y conocimiento previos”. Se validó una escala
del conocimiento básico en la enfermedad causada por COVID-19.
Palabras claves: estudios de validación, coronavirus,
conocimiento, pandemias, SARS-CoV-2
Received: 06-04-2020 / Accepted: 09-05-2020 / Published: 18-05-2020
Hot to Cite: Mejia
CR, Rodríguez-Alarcón JF, Carbajal M, Sifuentes-Rosales J, Campos-Urbina AM, Charri JC, Garay-Rios L, Al-Kassab-Cordova A, Mamani-Benito
O, Apaza-Tarqui EE. Validación de una escala breve para la medición del nivel
de conocimientos básicos acerca del Coronavirus, Perú (KNOW-P-COVID-19). Kasmera. 2020;48(1):e48106042020. doi: 10.5281/zenodo.3827988
Introduction
The coronavirus has generated the most recent
pandemic and highlighting that it is the first pandemic caused by a coronavirus
(1). This is because currently more than 200
countries have confirmed cases and deaths. Some of them, even have tens of
thousands of infected and deceased, which as of April the fourth amounts to 1.2
million infected. One quarter of these cases are in the United States.
Furthermore, more than a quarter of the 64,000 deaths have occurred in Italy (2,3).
This situation requires that people from all
sectors must have up-to-date knowledge about this new disease. Thus, various
entities, such as the World Health Organization (WHO) and the governments of
each country, have been providing information through different media (4,5). This is also due to the short time the virus has spread since its
discovery (6). However, time has not been a limitation for
researchers from around the world who have been developing different documents
with new useful information (7). Although this information has been available to the vast majority of
the world's population, it is known that it has not reached all, or that not
all of them had taken sufficient interest to lead them to search for this data,
so it is possible to speak of the "other pandemic", which is
disinformation (8). This is why it has been necessary to
synthesize and generate measurement scales that can be used to assess knowledge
about the virus. Taking as a reference the countries that have already passed
the first stages of this pandemic, and that now use this experience to inform
the rest of the world (9).
It is important to know the information that the
population handles about this disease, since having basic knowledge about the
symptoms or knowing how to detect the disease are protective factors against a
pandemic (10). If it is shown that the population does not
have enough knowledge in this regard, it will be imperative to generate
strategies to solve it, since they may be exposed to not knowing how to detect
it, acting inappropriately, a greater probability of becoming infected and even
complications. For example, there could be indiscriminate use of antibiotics even
though the disease is known to be viral in etiology (11). For all these reasons, the objective of this study is to validate a
short scale to measure basic knowledge about Coronavirus. (KNOW-P-COVID-19) in
the healthcare personnel, patients with comorbidities and the general
population.
Methods
Type and design of research: a instrumental analytical
cross-sectional study was carried out for validation (12). This was carried out in the Peruvian cities of Amazonas, Áncash, Apurímac, Arequipa, Ayacucho, Cajamarca, Cusco,
Huancavelica, Huánuco, Ica, Junín, La Libertad, Lambayeque, Lima, Loreto, Madre
de Dios, Moquegua, Pasco, Piura, Puno, San Martin, Tacna, Tumbes and Ucayali.
Population and sample: the background validation of the instrument was carried out in two
stages. In the first, 30 professionals from different specialties collaborated,
such as: epidemiologists, infectologist, internists,
critical care physicians, clinical pathologists, health workers, nurses, among
others. In the second stage, 9 professionals collaborated to verify the final
test, which shows the Aiken's V values in Table 1. In neither of the two
stages did these professionals participate in the form validation, since they
did not answer the items contained in the data collection instrument.
On the other hand, the validation necessary for
the factor analysis was carried out through a sample of 3913 participants of
both sexes (convenience sampling), where 1745 were men (44.8%) and 2148 were
women (55.2%) , whose ages ranged from 18 - 87 years (median age = 23 years and
interquartile range = 20-28 years). This
sample was made up of health personnel (including doctors, nurses, medical
interns, and others), patients in risk groups (older adults, cancer patients,
diabetics, hypertensive patients, immunosuppressed patients, etc.) and the
general public. These were recruited and the instrument was applied to them
through the internet, due to the quarantine state in which our country has been
during the realization of the project. Children under 18 years of age, those
who did not complete the instrument or who did not want to participate were
excluded. Although non-probability sampling was carried out during all stages
of the study, an attempt was made to include proportional numbers of
participants from the 3 regions of the country (coastal, highlands and jungle).
Procedures: in order to determine which variables were the most accurate to
evaluate within the proposed scale, a bibliographic search was carried out in
the most consulted databases: PubMed, Cochrane and SciELO;
as well as in the Google Scholar search engine. The following terms were used
as keywords: SARS-CoV-2, COVID - 19, coronavirus. In addition, filters were
used for the dates from December 2019 (to differentiate previous publications
from other Coronavirus infections). With these data, the first draft of the
scale was carried out, which was evaluated and improved.
Instrument: the knowledge scale about
COVID-19 (KNOW-P-COVID-19) measures knowledge about basic aspects of the
coronavirus such as mortality, vulnerable populations according to their
mortality, transmission routes and prevention. It was created by the authors of
the present study based on the conceptual model according to Germain, 2016 (13). It was validated through the judgment of 30 experts and the
reconfirmation of 9 experts, in order to determine if the content of the
evidence was clear, precise and consistent. In conclusion, the scale consists
of 9 items with a multiple-choice answer, with a single correct or valid
option, where the participant must choose the most appropriate option.
Data collection: The study had several
phases. First, the KNOW-P-COVID-19 Scale was analyzed and reviewed by the
research team. Second, the evidence of the content validity was analyzed with
the help of 30 experts, in order to determine the relevance, representativeness
and clarity of the items (14). Third, the necessary changes were made based on the expert´s observations,
and after the author's last approval, the final version of the scale was
prepared. Fourth, the variables of the scale were transferred to a sheet of
Google Forms, with the aim of being able to share it digitally with thousands
of patients, respondents and health personnel. The call for participants was
made through invitations through social networks, emails, invitation to friends
and family, phone calls, among others. All this information was transferred to
a database, using a Microsoft Excel 2019 sheet. Fifth, the statistical analysis
was carried out (descriptive, factor analysis and others). Finally, a final
consultation was made with 9 experts to corroborate the final version.
Data analysis: firstly, to analyze the
validity evidence, 4 classificatory criteria were taken into account to
evaluate each of the items. These criteria evaluated by the experts ranged from
0 to 3, with 0 not at all relevant / representative / clear and 3 totally
relevant / representative / clear. In addition, the quantification of the
degree of relevance, representativeness and clarity was determined by means of
the Aiken’s V coefficient and its 95% confidence intervals (95% CI), with
significant values that were taken from ≥ 0.70 and ≥ 0.59; respectively for
each one.
Then an exploratory factor analysis (EFA) was
performed, according to the unweighted least squares and with a Promax
rotation. In addition, the KMO and chi square coefficient values (with 36
degrees of freedom) were obtained. Thus, the distribution of the items in 2
generated factors was determined. In addition, a goodness-of-fit index was
generated, as a parameter to demonstrate how robust the instrument is, taking
into account the values of the GFI (Goodness of Fit Index), CFI (Comparative
Fit Index) and RMSEA (Root Mean Square Error of Approximation); determining as
acceptable values for GFI> 0.950, CFI> 0.9 and RMSEA <0.05. Finally,
the standardized regression coefficients were obtained to determine the
contribution of each item on each factor. Analysis were run on IBM SPSS Amos 24
software.
Ethical aspects: this research work took the
following ethical considerations: protection of the identities of each
participant, free entry to the research (with prior consent), the right to
answer questions and respect for international standards for this type of
research. This project was accepted by an ethic committee of a north Peruvian
university.
Result
Table 1 shows the results of the relevance, representativeness and clarity of
the items on the KNOW P-COVID-19 Scale, obtained using the Aiken’s V coefficient.
All the items received a favorable evaluation by the experts (V> 0.70).
Regarding relevance, it is observed that item 8 is more essential or important
(V = 1.00; 95% CI: 0.88-1.00). Regarding representativeness, it can be seen that
items 5 and 6 are more representative (V = 0.96; 95% CI: 0.82-0.99). Regarding
clarity, item 4 was the best evaluated (V = 0.93; 95% CI: 0.77-0.98). Likewise,
it can be seen that all the values of the lower limit (Li) of the 95% CI are
appropriate (Li> 0.59) and all the values of the coefficient V were
statistically significant. Therefore, KNOW-P-COVID-19 reports evidence of
content-based validity.
Table 1. Aiken’s V for evaluating the relevance,
representativeness and clarity of items on the KNOW-P-COVID-19 Scale
Items |
Relevance (n
= 9) |
Representativeness (n
= 9) |
Clarity (n
= 9) |
|||||||||
M |
DE |
V |
IC 95% |
M |
DE |
V |
IC 95% |
M |
DE |
V |
IC 95% |
|
Item 1 |
2,89 |
0,33 |
0,96 |
0,82-0,99 |
2,78 |
0,44 |
0,93 |
0,77-0,98 |
2,56 |
0,73 |
0,85 |
0,68,094 |
Item 2 |
2,89 |
0,33 |
0,96 |
0,82-,099 |
2,56 |
0,73 |
0,85 |
0,68-,094 |
2,56 |
0,73 |
0,85 |
0,68-,094 |
Item 3 |
2,78 |
0,67 |
0,92 |
0,77-0,98 |
2,56 |
0,73 |
0,85 |
0,68-0,94 |
2,67 |
0,71 |
0,89 |
0,72-0,96 |
Item 4 |
2,33 |
1,12 |
0,77 |
0,59-0,89 |
2,56 |
0,73 |
0,85 |
0,68-0,94 |
2,78 |
0,67 |
0,93 |
0,77-0,98 |
Item 5 |
2,89 |
0,33 |
0,96 |
0,82-0,99 |
2,89 |
0,33 |
0,96 |
0,82-0,99 |
2,67 |
0,50 |
0,89 |
0,72-0,96 |
Item 6 |
2,89 |
0,33 |
0,96 |
0,82-0,99 |
2,89 |
0,33 |
0,96 |
0,82-0,99 |
2,44 |
1,01 |
0,81 |
0,63-0,92 |
Item 7 |
2,67 |
0,71 |
0,88 |
0,72-0,96 |
2,44 |
0,88 |
0,81 |
0,63-0,92 |
2,44 |
0,88 |
0,81 |
0,63-0,92 |
Item 8 |
3,00 |
0,00 |
1,00 |
0,88-1,00 |
2,56 |
0,88 |
0,85 |
0,68-0,94 |
2,44 |
0,88 |
0,81 |
0,63-0,92 |
Item 9 |
2,56 |
0,73 |
0,85 |
0,68-0,94 |
2,56 |
0,73 |
0,85 |
0,68-0,94 |
2,33 |
0,87 |
0,78 |
0,59-0,89 |
Item 10 |
3,00 |
0,00 |
1,00 |
0,88-1,00 |
2,78 |
0,67 |
0,93 |
0,77-0,98 |
2,44 |
0,88 |
0,81 |
0,63-0,92 |
M: mean; DE: standard deviation; V: Aiken coefficient
V; IC 95%: 95% confidence interval for Aiken's V.
Table 2 presents the result of the Exploratory Factor Analysis (EFA), where a
KMO coefficient = 0.690, a Chi square value = 1645.66, with 36 degrees of
freedom and a p value of <0.001 (which indicates that the model is
suitable). The method for finding the factors was the unweighted least squares
method, which had a better result than the Principal Components method. In
addition, Promax rotation was used, since the indicators were nominal. Finally,
a result with 9 indicators was obtained. Item 9, which inquired about incorrect
coronavirus prevention measures, is not relevant. With these 9 questions, 2
factors were found, which explain the variable under study. Therefore, it is
valid to be able to carry out a Confirmatory Factor Analysis (CFA).
Table 2. Exploratory factor
analysis of the KNOW-P-COVID-19 Scale.
Indicators |
Factor |
|
1 |
2 |
|
p7. What indication should be given to a
person who has initial (non-severe) coronavirus infection?) r7. Blood
transfusion, relieve respiratory symptoms, antibiotics, send to nearer
hospital. |
0,625 |
|
p10. What would you do if you have symptoms
of a cold and suspect that you are infected with coronavirus? r10. I
Will go to hospital, I will stay in home until I will feel better, I will go
to the drugstore, I will follow with my normal life. |
0,447 |
|
p5. What is the probability of dying
(mortality percentage) from coronavirus in the general population? r5. Less
than 50%, less than 30%, less than 10%, less than 5%. |
0,398 |
|
p8. What is the diagnostic method used to
confirm a coronavirus infection? r8. Blood
analysis, echography, nasal and oral swabbed, urine analysis. |
0,235 |
|
p3. What are the common symptoms that a
person with coronavirus infection can have? r3. Like
a flu/cold, cardiac symptoms, neurological symptoms, stomach symptoms). |
|
0,370 |
p4. Which of the following is NOT one of
the most common symptoms of coronavirus infection? r4. Diarrhea, cough, fever, dyspnoea. |
|
0,367 |
p6. Of the following alternatives, in whom
is the coronavirus mortality rate higher? r6. Women,
men, elders, children. |
|
0,335 |
p2. How long is the incubation time or how
long can coronavirus symptoms manifest? r2. Until
5 days, until 10 days, until 14 days, until 60 days. |
|
0,295 |
p1. How is coronavirus transmitted or what
is the transmission mechanism? r1. Sexual,
air way, vertical way, by infected animals. |
|
0,263 |
Extraction
method: unweighted least squares.
Rotation method: Promax with Kaiser normalization
The Figure 1 shows the Structural
Equation System (SEM), where two factors were found through Exploratory Factor
analysis. The first factor contains 5 indicators, which have a high effect on
it. The second factor contains 4 indicators, which also have a high effect or
influence on it. Furthermore, the relationship between the factors which is
0.5, indicating a strong relationship between the two dimensions of the KNOW-P-COVID
19 Scale.
Figure 1. Distribution of the
questions recorded in the two factors of the KNOW-P-COVID-19 Scale
Table 3 presents the validation of the construct. A Chi square = 161.75 was
obtained, with 26 degrees of freedom (p <0.01). The goodness of fit indices
had the following results: the GFI (Goodness of Fit Index) = 0.992 (which,
being greater than 0.950, indicates that the proposed model is acceptable); the
CFI (Comparative Fit Index) = 0.916 (which is acceptable for being greater than
0.9); while, the RMSEA indicator (Root Mean Square Error of Approximation) =
0.034 (which is acceptable for being less than 0.05).
Table
3. Goodness of fit index
of the KNOW-P-COVID-19 Scale
Chi
cuadrado |
gl |
p
valor |
GFI |
CFI |
RMSEA |
161,75 |
26 |
<0,001 |
0,992 |
0,916 |
0,034 |
Table 4 presents the standardized regression coefficients, which shows a highly
significant effect or influence for each factor found, with p2 having the
strongest weight within the first factor (0.359), followed by indicator p4
(0.354). While, for the second factor, those with the greatest weight were
indicator p7 (0.57) and indicator p5 (0.437). The first factor measured the
"indications or actions after COVID-19 infection" and the second
"the symptoms and knowledge prior to COVID-19 infection"
Table 4. Standardized regression coefficients of the KNOW-P-COVID-19
Scale
Questions
by factor |
Estimates |
p value |
||
p1 |
<--- |
F1 |
0.260 |
0,000 |
p2 |
<--- |
F1 |
0.359 |
0,000 |
p3 |
<--- |
F1 |
0.288 |
0,000 |
p4 |
<--- |
F1 |
0.354 |
0,000 |
p6 |
<--- |
F1 |
0.338 |
0,000 |
p5 |
<--- |
F2 |
0.437 |
0,000 |
p7 |
<--- |
F2 |
0.570 |
0,000 |
p8 |
<--- |
F2 |
0.260 |
0,000 |
p10 |
<--- |
F2 |
0.435 |
0,000 |
Discussion
A quick survey on the knowledge of COVID-19 was
validated. This scale can be used in the student population, general
population, health population or others in which it has been validated.
Considering that this only measure basic knowledge of the disease, there is a
limitation that it cannot measure advanced knowledge or more specific elements
about the disease. However, this scale can help in rapid testing of those who
have a basic understanding of symptoms, prevention, important mortality data,
and to know what actions should be taken once the disease is established or
suspected.
The first factor that the instrument measures is
related to the indications or actions after COVID 19 infection. This evaluates
what indication should be given to a person who has a non-serious initial
infection, what they would do if they have symptoms or suspect that they are
infected, what is the probability of dying from coronavirus in the general
population and what is the diagnostic method used to confirm a coronavirus
infection. It is important that the population knows the symptoms of the
coronavirus so that they know how to act when they suspect they have been
infected or when they are infected (15). Some of the distracting alternatives make mention of going to the hospital,
knowing that going to the hospital immediately is not recommended. All
international organizations recommend that when you suspect an infection, what
you should do is stay home, treat the initial symptoms as if it were a cold
and, if necessary, call the emergency lines that have been established in each
country , so they can go to the home to make a diagnosis (16). If these recommendations are not taken into account, there could be a
greater chance of having to go to a hospital or health service and getting infected
from other patients who are infected. This is due to the possibility of
confusion due to the fact that the symptoms are very similar to those of a cold
or flu. As for the question 10, about what to do if you have cold symptoms, the
appropriate answer is to treat respiratory symptoms, especially until you have
confirmed that you have the coronavirus disease. The option of taking
antibiotics when the initial symptoms appear is totally inadequate, not only
due to the fact that a self-medication should not be generated, but, the same
question refers to cold symptoms or suspicions of Coronavirus, which in both
cases are of viral etiology, where antibiotics have no effect (17).
The probability of dying from COVID-19 in the
general population is also mentioned, knowing that in most populations the
mortality rate is less than 5% (18). Although there are some exceptions, such as in the case of Italy,
which has reached values close to 10% (19,20). Conversely, some countries have reached very low values (even less
than 1%), such as in South Korea or Germany (21). This is important to verify that the population knows that the disease
has a low mortality, but despite this, they must follow the indications and
remain calm. The last question that corresponds to this factor tells us which
is the best method to confirm a coronavirus infection, so far the most widely
used diagnostic method is real-time RT-PCR, which detects the RdRp gene (envelope gene [E] and nucleocapsid gene [N])
from nasopharyngeal swab samples (22,23). It is important to know that there are other tests, such as
serological tests that detect IgG and IgM in early stages of the infection,
being also useful to support the diagnosis of SARS-CoV-2 or in the follow-up of
cases, but they can produce a cross-reaction with SARS-CoV
or false positives for dengue (24–26). This is because it does not detect genetic material, as in the gold
standard test.
Another important factor is the one that
encompasses five questions that inquire about symptoms and knowledge prior to
coronavirus infection. The first two questions are about the common symptoms of
the disease, which are of vital importance to inquire whether the population
knows how to recognize which are the most frequent and which are not, due to
their great similarity with other respiratory diseases. It is important that
they have this knowledge so that a false alarm is not generated in the
population and to avoid that for any minimal symptom they think they have the
disease (27).
This test also shows us who has the highest
mortality rate and who has a higher risk factor, taking into account that the
elderly are more affected by this disease. In
addition, it asks about the incubation time or in what time the virus symptoms
can manifest, knowing that the average range is up to 14 days. We cannot forget
that there may be very exceptional cases, where there is evidence of a shorter
or longer incubation time; but at a general level the WHO and many
organizations have shown that the incubation period is from 2 to 14 days.
Finally, the question shows how the coronavirus
is transmitted or what the transmission mechanism is. This is very important to
reassure the population about the form of transmission of this disease, since
many other forms of transmission have been speculated (especially the one that
mentions that it is transmitted by animals). Actually, the most common form of
transmission is through air because it is a coronavirus, which belongs to the
family of cold viruses (28).
It is relevant to mention that there is a limitation
that is a scale that only measures basic knowledge, with important questions to
know the most basic and essential aspects of the disease, the symptoms and
other aspects before or during the disease. Therefore, it is important that
other scales be developed with a greater number of questions or with a more
technical content, which could be used by doctors or other populations.
However, our objective was to generate a short scale that includes very
important aspects that the general population and other important populations
should know. Another important limitation is that in view of the great research
that is generated daily on the coronavirus, it is probable that some concepts
may vary slightly over time. For example: the patients could have a shorter or
longer incubation time, different presentations, rare symptoms, among other
possible variations that may occur. However, we consider that the validity of
the scale will remain in force since it tries to measure basic concepts that
have already been widely proven.
Conflict of relationships and activities
The authors declare not to have any relationships or activities conflict.
Financing
This research was financed by the authors.
Acknowledgments
We thank the participants of the 18th Research
Group of the SOCEM's (GIS) Huánuco-2019, since, in this activity, the test was
developed. Furthermore, we thank the research group COVID-19-GIS-Peru, which
supported the collection of the almost 4,000 surveys throughout Peru. Finally, we
thank the members of the
following scientific societies of medical students: Sociedad Científica de Estudiantes de Medicina de
Huánuco SOCIEMHCO), Sociedad Científica de Estudiantes de Medicina de la
Universidad Nacional Daniel Alcides Carrión-Pasco (SOCIEM UNDAC-PASCO),
Sociedad Científica de Estudiantes de Medicina del Centro (SOCIEMC) and
Sociedad Científica de Estudiantes de Medicina de la Universidad Nacional
Federico Villareal (SOCEMVI).
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Authors Contribution:
MJR, RAJF, CM, SRJ, CUAM, CJC, GRL, AKCA,
MBO y APEE: participaron
en la conceptualización, metodología,
software, validación, análisis formal, investigación, recursos, curación de
datos, redacción-preparación del borrador original, redacción-revisión y
edición.
©2020. Los Autores. Kasmera. Publicación del Departamento de Enfermedades
Infecciosas y Tropicales de la Facultad de Medicina. Universidad del Zulia.
Maracaibo-Venezuela. Este es un artículo de acceso abierto
distribuido bajo los términos de la licencia Creative
Commons atribución no comercial (https://creativecommons.org/licenses/by-nc-sa/4.0/) que permite el uso no comercial, distribución y
reproducción sin restricciones en cualquier medio, siempre y cuando la obra
original sea debidamente citada.