IDEAS home Printed from https://ideas.repec.org/a/taf/oabmxx/v9y2022i1p2031682.html
   My bibliography  Save this article

The health belief model: Evaluating governmental public health messages on social media aimed at preventing a COVID-19 epidemic in Kuwait

Author

Listed:
  • Rashed Alhaimer

Abstract

This study aimed to examine the effect of embracing the Health Belief Model (HBM) in governmental public health messages on social media during the coronavirus disease 2019 pandemic. Adoption of the HBM seeks to improve the level of response of Kuwaiti people towards governmental messages regarding social distancing, staying at home, and self-protection. To fulfil the study’s aim, a quantitative research design was adopted in which data were collected from 746 respondents in Kuwait to examine the effect of perceived susceptibility, severity, benefits, barriers, health motivation, and cues to action, based on each individual’s behaviour. Data were analysed through AMOS 22.0 and the findings showed that governmental messages on social media should consider the above-mentioned aspects in order to positively impact the behaviour of Kuwaiti individuals.

Suggested Citation

  • Rashed Alhaimer, 2022. "The health belief model: Evaluating governmental public health messages on social media aimed at preventing a COVID-19 epidemic in Kuwait," Cogent Business & Management, Taylor & Francis Journals, vol. 9(1), pages 2031682-203, December.
  • Handle: RePEc:taf:oabmxx:v:9:y:2022:i:1:p:2031682
    DOI: 10.1080/23311975.2022.2031682
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23311975.2022.2031682
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/23311975.2022.2031682?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:oabmxx:v:9:y:2022:i:1:p:2031682. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://cogentoa.tandfonline.com/OABM20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.