About: Knowledge and attitude towards COVID-19 in Bangladesh: Population-level estimation and a comparison of data obtained by phone and online survey methods

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Knowledge and attitude towards COVID-19 in Bangladesh: Population-level estimation and a comparison of data obtained by phone and online survey methods
Creator	Affiliations, Ahm, ; Akter, Mashkura Akter, Mastura Aziz, Tahera Banu, Tahmina Bhuiyan, Hossain Hayee, Samira Karim, Anwarul Kuri, Ashish Mazid, Thafikul Niaz, Nashid Nur, Md Orindom, ; Pulock, Shing Rashid, Humayun Singh, Orindom Tahmina Banu, ; Tasmiah, ; Uddin, Forhad
Source	MedRxiv
abstract	Adherence of people to the guidelines and measures suggested in fighting the ongoing COVID-19 pandemic is partly determined by the Knowledge, Attitude, and Practices (KAP) of the population. In this cross-sectional study, we primarily addressed two key issues. First, we tried to determine whether there is a significant difference in the estimated COVID-19 knowledge level from the online and phone survey methods. Second, we tried to quantify the knowledge and attitude of COVID-19 in Bangladeshi adult population. Data were collected through phone calls (April 14-23, 2020) and online survey (April 18-19, 2020) in Bangladesh. The questionnaire had 20 knowledge questions with each correct response getting one point and incorrect/do not know response getting no point (maximum total knowledge score 20). Participants scoring >17 were categorized as having good knowledge. The percentages of good knowledge holders were 57.6%, 75.1%, and 95.8% in the phone (n=1426), online non-medical (n=1097), and online medical participants (n=382), respectively. Comparison between phone and online survey showed that, overall, online survey might overestimate knowledge level than that of phone survey, although there was no difference for elderly, poor, and rural people. Male gender, higher education, living in town/urban areas, good financial condition, and use of internet were positively associated with good knowledge. However, higher knowledge was associated with having less confidence in the final control of COVID-19. Our adult population-level estimates showed that only 32.6% (95% CI 30.1-35.2%) had good knowledge. This study provides crucial information that could be useful for the researchers and policymakers to develop effective strategies.
has issue date	2020-05-26(xsd:dateTime)
bibo:doi	10.1101/2020.05.26.20104497
has license	medrxiv
sha1sum (hex)	747a14bd6677b04e987ed11c6365de7fab960c7c
schema:url	https://doi.org/10.1101/2020.05.26.20104497
resource representing a document's title	Knowledge and attitude towards COVID-19 in Bangladesh: Population-level estimation and a comparison of data obtained by phone and online survey methods
resource representing a document's body	covid:747a14bd6677b04e987ed11c6365de7fab960c7c#body_text
is schema:about of	named entity 'internet' named entity 'good' named entity 'COVID-19' named entity '95% CI' named entity 'cross-sectional study' named entity 'good' named entity 'Farjana' named entity 'Munia' named entity 'FINAL' named entity 'ONGOING' named entity 'SCORE' named entity 'CORRECT' named entity 'RESEARCHERS' named entity 'GOOD' named entity 'HIGHER EDUCATION' named entity 'BANGLADESH' named entity 'ATTITUDE' named entity 'phone calls' named entity 'survey' named entity 'adherence' named entity 'COVID-19' named entity 'online survey' named entity 'suggested' named entity 'Bangladesh' named entity 'study' named entity 'medical' named entity 'develop' named entity 'Comparison' named entity 'However' named entity 'Humayun' named entity 'Family Planning' named entity 'COVID-19' named entity 'urban areas' named entity 'online survey' named entity 'Koushik' named entity 'Ashish Kumar' named entity 'Humayun' named entity 'public health' named entity 'COVID-19' named entity 'COVID' named entity 'medRxiv' named entity 'world health organization' named entity 'lockdown' named entity 'binary logistic regression' named entity 'COVID-19' named entity 'selection bias' named entity 'multinomial logistic regression' named entity 'Bangladesh' named entity 'preprint' named entity 'COVID' named entity '12 minutes' named entity 'washing hands' named entity 'Chattogram' named entity 'COVID' named entity 'Bangladesh' named entity 'independent variable' named entity 'COVID-19' named entity 'statistical significance' named entity 'WHO' named entity 'COVID' named entity 'COVID-19' named entity 'COVID' named entity 'Multinomial logistic regression' named entity 'Google Forms' named entity 'Bangladesh' named entity 'COVID'

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