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Hypothesis: There is a significant influence of internet use, risk awareness, and
demographic characteristics in preventive behavior and COVID 19 pandemic testing.
Research question: To what extent are internet use, risk awareness, and demographic
characteristics associated with preventive behaviors and Covid 19 testing in the United States?
Accordingly, the new infectious condition, COVID 19 pandemic, did stimulate a
considerable jump in doubts among the population. Indeed, the majority from different corners
of the world got the opportunity to learn more about the pandemic from online materials (Barua
& S, 2020). The author had in mind a significant influence of internet use because the internet
defines a valuable platform with crucial aspects of health information. With many studies
around, it has been noted that the majority of the population spent more time online searching for
the info on COVID 19 pandemic. Indeed, the author became aware that most people get
information via active searches, and as well, the population is open to online information on
health. The online platforms present information on health information, which reduces the gap in
acquiring health knowledge and affects the population’s health decision-making. In the ability,
the author hypothetically relates the internet users that provide a unique way of getting
information at an individual level. The research question now in place asks to what extent is the
utility interrelated with commitment in preventive behavior and examining of COVID 19
pandemic in the United States. Again, the author is worried about risk awareness and its
significance in preventing and testing Covid 19 in the USA community (Geldsetzer & P, 2020).
The virus is dispatched via individual contacts and perception of the disease in one’s social
environment that incorporates close family members, friends, relatives, and the surrounding
population. The author is guided by the research question of what extent this is happening. The
influence on population’s danger awareness and commitment in protective behavior and COVID
19 examination was probably significant.
Notably, the research question and the hypothesis related to the initial studies presented different
demographic features that attended to be compared with preventive behavior in the time of a
pandemic. Considerably, the author addresses the demographic characteristics around age and
sex-linked with COVID 19 death rates. The suggestion placed a necessity on the responsibility of
demographic elements in determining behavioral replies around the time of COVID 19 disease.
Therefore, with all these in mind, the author is exploring the online application, threat
perception, and sociodemographic features that interrelates with protective practices and COVID
19 examination in the United States. Essentially, the author addresses the use of the internet with
COVID 19 information on online activities alongside the data for effective online search and live
receptive publicity. The communication on threat sensitivity interrogates how the US community
knows about infections in their social environments. The demographics by the author
communicate characteristics of age, sex, race, earnings, education, marital status, and working
status as significant areas to be explored.
The study presented ethical certification obtained from the matching university of the
writer. The research participants were enrolled from Amazon Mechanical Turk (MTurk), an
online crowdsourcing labor marketplace. The data obtained were of quality standards as
occasioned from other possible cases. The research survey was abstracted and executed through
application of Qualtrics (version 12; Qualtrics International Inc). Qualtrics recorded participants’
responses to the study except the MTurk account data, and therefore anonymity of the
participants was maintained. The participants were given the US $0.75 each for participating.
The descriptive survey was used with open and closed questionnaires (Li et al., 2020). Data
collection began on April 10, 2020, and was finalized on April 14, 2020. It followed obtaining
the consent of the participants, who were then informed to finish the survey questioning about
their insights and behavior pertaining to the COVID-19 pandemic. The design was used
appropriately, with 1080 Mturk employees able to fill out the online questionnaires. For data
quality, the attention checks were incorporated in the questionnaire. The study included 979
participants. There was ordinal logistic regression for 5-level self-disclosure commitment in
preventive behavior and binomial logistic regression analysis for the binary testing behavior. The
SPSS 26(IBM Corp) was used for analysis.
The findings show a higher trend for community to involve in specific preventive
behavior more than others do. Even though the documentation display that as the disease
continues, persons become more familiar with risks around health pointed by the COVID 19
virus and participate in defensive behavior as the rate increases. The findings showed that the
development is not equal among the different types of preventive behavior. Again, there were
constructive relationships between the point of acquiring the virus online information and
consultation in every aspect of the preventive behavior (Remuzzi et al., 2020). Many received
online recommendations on preventative measures. In a way, it could enhance population
worries about the disease and bring motivation to precautionary measures.
In comparison, the clear cases in their families had a less frequent engagement in every
preventive behavior. Even though these results are counterintuitive, the implication would result
to a greater infection risk among family members. Close families and contacts are more at risk of
transmission. The study information demonstrated that old, female, or nonwhite was interrelated
with a greater probability of embracing preventive behavior in a pandemic surrounding
respiratory nature conditions.
The article presented was well presented with the findings orderly, with every issue addressed
separately. The study lacked a separate research question and problem statement, making it
challenging to understand problems comprehensively.
The study can improve evaluation and demonstrate causal relationships among the
different variables. These include social environment engagement with the people for preventive
behavior in COVID 19 pandemic. The research could improve the random selection of the
participants and the comparison made with the distribution of critical variables. The online
option only allowed for the young educated population. To qualify on the response bias in selfreported data since it was low with anonymity online compared to telephone or in-person.
Barua, S. (2020). Understanding Coronanomics: The economic implications of the coronavirus
(COVID-19) pandemic. Available at SSRN 3566477.
Geldsetzer, P. (2020). Use of rapid online surveys to assess people’s perceptions during
infectious disease outbreaks: a cross-sectional study of COVID-19. Journal of medical
Internet research, 22(4), e18790.
Li, S., Feng, B., Liao, W., & Pan, W. (2020). Internet use, risk awareness, and demographic
characteristics associated with preventive behaviors and testing engagement: a crosssectional survey on COVID-19 in the United States. Journal of medical Internet
research, 22(6), e19782.
Remuzzi, A., & Remuzzi, G. (2020). COVID-19 and Italy: what next?. The lancet, 395(10231),

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