Journal of Preventive Medicine

Introduction
The coronavirus disease 2019 (COVID-19) was first reported in Wuhan, China, and after a short time, it turned into a pandemic with economic, social, and health consequences. The speed of the spread of this disease caused countries to face a high number of infected cases. This disease spreads through the air and by touching surfaces and objects contaminated with respiratory droplets of infected people, which shows the need to observe personal hygiene. According to the World Health Organization, washing hands regularly, wearing masks, social distancing, and avoiding shaking hands and hugging are important preventive behaviors against COVID-19. Considering the importance of knowing the effective factors in preventing COVID-19 and considering the role of masks in preventing the transmission of respiratory droplets from infected people to healthy people, this study aims to investigate the predictors of mask use based on the protection motivation theory (PMT) in Shahrekord, Iran.

Methods
This descriptive cross-sectional study was conducted in 2021. The study population consists of all people living in Shahrekord city who had the ability to connect to the Internet and use virtual networks and answer the questions. Non-local people and those who returned incomplete questionnaires were excluded from the study. The sample size was calculated by considering α=0.05, d=0.05, and p=0.5, which was obtained 384. Overall, 388 people participated in this study. The instruments included two parts. The first part surveys demographic information (13 questions), and the second part is a questionnaire developed based on the PMT constructs (41 items) using a 5-point Likert scale from completely disagree (0 points) to completely agree (4 points). The validity of the questionnaire was confirmed using the opinions of a panel of experts. The internal consistency of the questionnaire was assessed by a pilot study on 30 people. Cronbach’s alpha was obtained 0.75, which was acceptable. In the data analysis stage, the frequency and percentage were used to describe the qualitative variables, and the mean and standard deviation were used for the quantitative variables. Pearson correlation test and linear regression analysis were used for data analysis in SPSS software, version 20. The significance level was set at 0.05.

Results
Among participants, 66% were female and 34% were male; 18.3% were in the age group of 35-40 years, 66.1% were married, and 87% had Fars ethnicity. Moreover, 34.3% were employees, 50.5% had a university education, and 93.3% were living in urban areas. The mean score of mask-wearing behavior was 66.17±62.46. The PMT constructs of self-efficacy, response efficacy, and rewards had a statistically significant relationship with the mask-wearing behavior (P=0.001). The regression analysis showed that the constructs of self-efficacy (P=0.018), response efficiency (P=0.038), and rewards (P=0.041) predicted mask-wearing behavior, where the self-efficacy domain was the strongest predictor (Table 1).


They together predicted 0.38% of mask-wearing behavior.

Discussion
The findings showed that the people in Shahrekord city had relatively favorable mask-wearing behaviors during the COVID-19 pandemic. The PMT constructs of self-efficacy, response efficacy, and rewards had a statistically significant relationship with their mask-wearing behaviors. They could significantly predict their mask-wearing behaviors. The self-efficacy domain was the strongest predictor. Considering the psychological and economic effects of COVID-19 on the family and society and the necessity of preventive behaviors against it, it is recommended to carry out targeted educational programs based on the PMT model to increase people’s self-efficacy and attitudes towards wearing masks.

Ethical Considerations
Compliance with ethical guidelines
This study was approved by the ethics committee of Shahrekord University of Medical Sciences (Code: R.SKUMS.REC.1400.057). 

Funding
This study was funded by Shahrekord University of Medical Sciences. 

Authors' contributions
Design and writing: Zahra Mohammad Yousefi Vardanjani; Data analysis, writing, and review: Elahe Tavassoli; Editing: Pooran Khalafian; Data collection: Homeira Maleki  and Parisa Rostami.

Conflicts of interest
The authors declared no conflict of interest.

Acknowledgements
The authors would like to thank the deputy for Research and Technology of Shahrekord University of Medical Sciences and all participants for their support and cooperation.

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