An assessment of the health belief model (HBM) properties as predictors of COVID-19 preventive behaviour

Author:

Subedi Sashikala,Leal Filho Walter,Adedeji AdekunleORCID

Abstract

Abstract Background Public participation in preventive efforts is crucial in preventing infection and reducing mortality attributed to infectious diseases. The health belief model (HBM) suggests that individuals will likely participate in these efforts when experiencing a personal threat or risk, but only if the benefits of acting outweigh the risk or perceived barriers. Methods The current study explores the properties of the HBM as predictors of the public’s compliance with COVID-19 preventive behaviour. Quantitative data on HBM properties, COVID-19 preventive behaviour, socioeconomic (SES) and demographic characteristics were collected from a sample of 674 adults in Hamburg, Germany. Binary logistic regression was computed to examine the effect of the properties of HBM on COVID-19 vaccination. Multiple linear regression was calculated to investigate the impacts of HBM properties on the likelihood of participants’ face mask usage as a protective measure against COVID-19 infection. Results The logistic regression model was statistically significant, X2(13) = 149.096, p < .001. The specificity and sensitivity for the model is 58.1% and 99.4%, respectively. Similarly, the multiple regression model results showed a good fit for the data. F (13, 650) = 17.093, p < .001, and adjusted R2= .240, suggesting that HBM properties predict face mask usage. Conclusion This study’s findings provide robust evidence to recommend that the concerned public health professionals consider individuals’ health beliefs when designing an effective COVID-19 preventive programme. Public health messaging should consider highlighting the benefits of preventive actions and the potential lethality of COVID-19 to evoke an individual’s appropriate concern.

Funder

Hochschule für Angewandte Wissenschaften Hamburg (HAW Hamburg)

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3