Comparing two Behavior Change Approaches in predicting the Intention and COVID-19 Preventive Behaviors among the general population 

Abstract

Background The COVID-19 is a highly contagious illness with high mortality rates worldwide. Due to the vaccine inability in creating permanent immunity, the merely way to combat with the illness is to adopt COVID-19 preventive behaviors (CPBs). To comprehend CPBs compliance, it's important to know factors affecting people’s decision-making about CPBs. The constructs of health promotion theories/models can predict behavior. Hence, this study aimed to compare Health Belief Model (HBM) and Theory of Planned Behavior (TPB) in predicting intention and CPBs. Methods This cross-sectional study examined 500 Urmia citizens who were chosen by utilizing snowball and available sampling method. Data were collected by applying a valid and reliable researcher-made electronic questionnaire including demographic variables, knowledge items, items of HBM and TPB constructs and CPBs. Data were analyzed by utilizing descriptive statistics, Pearson correlation coefficient and linear regression in SPSS software. Results The mean and standard deviation of intention and CPBs were 21.53 ± 3.67 and 22.37 ± 3.22, respectively. The constructs of HBM and TPB predicted 47% and 65% of the variance of CPBs and 53% and 73% of the variance of the intention of CPBs, respectively. Based on HBM, self-efficacy was the strongest predictor of intention and behavior. Based on TPB, perceived behavioral control (β=0.604, P=0.001) and behavioral intention (β=0.345, P=0.001) were the strongest predictors of intention and behavior, respectively. Conclusions The TPB better than the HBM can be used for predicting intention and CPBs. Hence, TPB especially perceived behavioral control and behavioral intention constructs can be utilized in developing educational programs and interventions to change citizens' behavior towards COVID-19.