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Beyond Health Belief: Modeling the Predictors of COVID-19 Vaccine Uptake among Social Media Users in Nigeria

Author

Listed:
  • Joshua Aghogho Erubami
  • Philo Igue Okpeki
  • Edith Ugochi Ohaja
  • Uchenna Chijindu Anorue
  • Martins Ndubisi Ezugwu

Abstract

There have been sustained global efforts to promote the uptake of COVID-19 vaccines, yet studies suggest the upsurge of vaccine resistance around the world. Considering the wide adoption of social media as crucial sources of health information, the nature of popular online debates on vaccination initiatives can significantly sway people’s vaccine-related decisions. This study develops a structural equation model for the predictors of COVID-19 vaccine uptake among Nigerian social media users. Using an online survey of 436 respondents, the study fundamentally extends the constructs of the Health Belief Model by examining the unique roles of social media exposure, fear, and anticipated regret in the prediction of individuals’ vaccination decisions. We found that perceived susceptibility to and perceived severity of vaccination risk, perceived barriers to vaccination, exposure to vaccine-critical posts on social media, fear of vaccination risk, and anticipated regret for vaccine uptake significantly predicted COVID-19 vaccine uptake. However, the perceived benefits of COVID-19 vaccine uptake and anticipated regret for inaction related to vaccination did not predict COVID-19 vaccine-related decisions. The findings accentuate why stakeholders in the public health sector should pay adequate attention to social media-related trends on public health promotion schemes, and counter any detected falsehood with credible information.

Suggested Citation

  • Joshua Aghogho Erubami & Philo Igue Okpeki & Edith Ugochi Ohaja & Uchenna Chijindu Anorue & Martins Ndubisi Ezugwu, 2022. "Beyond Health Belief: Modeling the Predictors of COVID-19 Vaccine Uptake among Social Media Users in Nigeria," Studies in Media and Communication, Redfame publishing, vol. 10(2), pages 39-52, December.
    • Handle: RePEc:rfa:smcjnl:v:10:y:2022:i:2:p:39-52
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    References listed on IDEAS

    as
    1. Joseph F. Hair & Christian M. Ringle & Siegfried P. Gudergan & Andreas Fischer & Christian Nitzl & Con Menictas, 2019. "Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 115-142, April.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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