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

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.