Coronavirus Disease 2019 (COVID-19): A Cross-Sectional Survey of the Knowledge, Attitudes, Practices (KAP) and Misconceptions in the General Population of Katsina State, Nigeria

  1. Isah, M. B.
  2. Abdulsalam, M.
  3. Bello, A
  4. Usman A. R.
  5. Ibrahim, M. I
  6. Usman, A.
  7. Nasir, A.
  8. Abdulkadir, B.
  9. Ibrahim, K. M.
  10. Sani, A.
  11. Aliu, M.
  12. Kabir, S. A.
  13. Shuaibu, A.
  14. Nass, S. S.

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Abstract

Over six million cases of Coronavirus Disease 2019 (COVID-19) were reported globally by the second quarter of 2020. This study assessed the COVID-19 related knowledge, attitudes, practices and misconceptions in Katsina state, Nigeria. The study is across-sectional survey of 722 respondents using an electronic questionnaire through the WhatsApp media platform. One thousand five hundred questionnaires were sent to the general public with a response rate of 48%. Among the respondents, 60% were men, and 56% held bachelor’s degree and above. The respondents have good knowledge of COVID-19 (80% correct rate on questions related to knowledge). Being more educated is associated with both higher average COVID-19 knowledge score and positive COVID-19 related practices. Overall, >70% of the respondents have a positive attitude towards successful COVID-19 control. Male were more likely than female (Fisher’s exact test P value < 0.05) to have recently attended a crowded place. Among the respondents, 83% held at least one misconception related to COVID-19. Respondents at all levels of education frequently chose to trust health unit and health care workers for relevant COVID-19 information. In conclusion, although there is high COVID-19 related knowledge among the respondents, misconceptions are widespread among them. These misconceptions have consequences on the short- and long-term control efforts against the disease and hence should be incorporated in targeted campaigns. Healthcare related personnel should be at the forefront of the campaign.  

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  1. Version published to 10.47430/ujmr.2161.004
  2. ScreenIT

    SciScore for 10.1101/2020.06.11.20127936: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: The questionnaire for the knowledge, attitudes and practices towards COVID-19 was a modification of the questionnaire developed by Zhong et al. (2020), adopted with the Authors’ consent.
    IRB: The study was approved by the research ethics committee of the State Ministry of Health, Katsina State (REF: MOH/ADM/SUB/1152/1/375).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data analysis: Statistical analysis was conducted using SPSS V26.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.06.11.20127936 on medRxiv