Factors affecting face mask-wearing behaviors to prevent COVID-19 among Thai people: A binary logistic regression model

Author:

Kaewpan Wonpen,Rojpaisarnkit Kunwadee,Pengpid Supa,Peltzer Karl

Abstract

ObjectivesFace mask wearing is a standard preventive measure, in addition to handwashing and physical distancing. Individuals may find that wearing a face mask protects their physical health and prevents viral transmission. However, none of the studies in Thailand identified factors associated with face mask-wearing behaviors among Thai people. Therefore, this study aims to determine factors affecting face mask-wearing behaviors to prevent COVID-19.MethodsThis research is analytical survey research. The data used in this study were under the project title “The assessment of psychosocial and behavioral response and compliance to restriction measures to prevent and control COVID-19: A series of the rapid survey.” A total of 6,521 people participated in an online survey by multi-stage sampling. Bivariate logistic regression analysis was used to examine the factors associated with face mask-wearing behaviors.ResultsAfter adjusting for independent variables (i.e., gender, age, education, career, smoking, and comorbidity disease), the bivariate logistic regression analysis revealed that gender, age, and career were statistically significant to the face mask-wearing behaviors (p < 0.05). Level of education, smoking, and comorbidity disease were not statistically significant with face mask-wearing behaviors among Thai people.ConclusionFurther study should explore broader on individual face mask perceptions and wearing in the continuing of COVID-19 across gender, age, and careers to better understand their health behaviors and to inform further policy. In addition, the development of an intervention to promote face mask wearing should target men who age below 30 yrs. and did not work in government services careers as this group of the population was likely not to wear a face mask outside the home.

Publisher

Frontiers Media SA

Subject

General Psychology

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