Evidence map›Paper›PMID 33507906›Full record

ArticlePloS one2021

The knowledge and practice towards COVID-19 pandemic prevention among residents of Ethiopia. An online cross-sectional study.

Daniel Bekele, Tadesse Tolossa, Reta Tsegaye, Wondesen Teshome

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  14. Bayesian spatial modeling of COVID-19 case-fatality rate inequalities.Spatial and spatio-temporal epidemiology · 2022
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Daniel BekeleDepartment of Statistics, College of Natural and Computational Sciences, Dire Dawa University, Dire Dawa, Ethiopia.ORCID 0000-0003-0092-3756
Tadesse TolossaDepartment of Public Health, Institute of Health Science, Wollega University, Nekemte, Ethiopia.
Reta TsegayeDepartment of Nursing, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia.
Wondesen TeshomeDepartment of Statistics, College of Natural and Computational Sciences, Dire Dawa University, Dire Dawa, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe disease from the novel coronavirus (COVID-19) has been considered as an international concern and a pandemic starting from the declaration of the World Health Organization (WHO) as an outbreak disease.

objectiveThe objective of this study is to assess the prevention of knowledge and practices towards the COVID-19 pandemic among the residents of Ethiopia.

methodsAn online cross-sectional study was conducted among a sample of Ethiopian residents via social platforms of the author's network with popular social media such as Facebook, Telegram, and email. The snowball sampling was employed to recruit participants. In doing so, we collected the responses of 341 participants successfully from April 15 to 22, 2020. The collected data were analyzed by STATA version 14 software and descriptive statistics were employed to summarize the knowledge and practices of the community towards the COVID-19 pandemic.

resultsThe majority of respondents 80.5% were male. About 91.2% of the participants heard about the COVID-19 pandemic. Moreover, out of 341 participants 90.0%, 93.8% of them knew that the COVID-19 pandemic was prevented by maintaining social distance and frequent handwashing, respectively. This shows that the prevention knowledge of the participants towards the COVID-19 by maintaining social distance and frequent handwashing was high. However, out of 341 participants only 61%,84% of them practiced social distance and frequent handwashing toward COVID-19, respectively.

conclusionsThe majority of the participants knew the ways to protect themselves from the novel coronavirus (COVID-19), but there was a great problem of changing this prevention knowledge to practices. This shows that there is an action gap between having prevention knowledge of the COVID-19 and implementing it into practices to tackle the spread of the COVID-19 among communities. Therefore, the concerned body should be focused on providing awareness and education for the community regarding the implementation of prevention knowledge to practices.

Indexed as

Health Knowledge, Attitudes, PracticeAdultCOVID-19Cross-Sectional StudiesEthiopiaFemaleHumansMaleMiddle AgedPandemicsSARS-CoV-2Social MediaSurveys and Questionnaires

Identifiers

PMID33507906
PMCPMC7843015

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.