Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population

BACKGROUND: The novel coronavirus (COVID-19) has infected nearly 9.5 million people in 216 countries, areas, or territories in the world. The fight against the COVID-19 has become a very serious international challenge. The aim of this study was to determine the predictors of COVID-19-preventive behaviors using the health belief model (HBM). MATERIALS AND METHODS: This cross-sectional study was conducted with the participation of 558 samples from the adult population of Iran. The online convenience sampling was conducted in this research. The online 68-item questionnaire link was published all over Iran through social networks including Telegram and WhatsApp, which are common in Iran. The data were analyzed using SPSS software version 19. Descriptive statistics, bivariate Pearson's correlation test, and multiple linear regression were used to analyze the data. RESULTS: The mean age of the subjects was 33.3 +/- 10.01 years. The participants were often female (61.3%), married (57.9%), and resident of the city (81.0%) with university educational level (78.8%). The results showed that the HBM structures predicted 29.3% of the preventive behaviors of COVID-19 in the subjects. The perceived benefits, perceived barriers, and self-efficacy significantly predicted the preventive behaviors, but the perceived susceptibility and perceived severity were not significant in the regression model. The internet and virtual social networks (49.8%), broadcast (33.5%), and healthcare providers (15.8%) were the most important sources of information related with COVID-19. In response to COVID-19-related internal cues to action, 36.6% did not pay attention and 34.7% tried to self-medicate. Only 28.5% of the subjects referred to the hospital, healthcare center, or physician. CONCLUSION: Self-efficacy, perceived barriers, and perceived benefits were the key determinants of COVID-19-preventive behaviors in the subjects. It can be concluded that the HBM is a good tool to predict COVID-19-preventive behaviors in Iranian population.

Automated summary

The key determinants of COVID-19 preventive behaviors in the subjects were self-efficacy, perceived barriers, and perceived benefits. The participants mainly obtained information related to COVID-19 through the internet and virtual social networks. The results of the data analysis showed that the HBM structures predicted 29.3% of the preventive behaviors of COVID-19 in the subjects.