Date of Award

December 2020

Degree Type

Thesis

Degree Name

Master of Arts (MA)

Department

Media Studies

Advisor(s)

Joon Soo Lim

Keywords

Institutional trust, Moral norm, PM2.5, Risk-reduction behavior, Theory of planned behavior

Subject Categories

Social and Behavioral Sciences

Abstract

Understanding and encouraging people to perform PM2.5 risk-reduction behaviors is essential to reduce the health risks caused by PM2.5 and to promote a healthy lifestyle. This study aims to predict the effects of psychological factors (attitude, perceived behavioral control, subjective norm and moral norm) on individual’s PM2.5 risk-reduction intention. It also looks into how contextual factors (exposure to communication channels and institutional trust) can influence behavioral intention and make contributions to the predicting powers of the theory of planned behavior. To achieve this goal, I analyze the secondary survey data that randomly selected residents living in three regions known for heavy air pollution in China. Confirmatory factor analysis (CFA) is conducted to validate the reliability and construct validity for each theoretical concept. Then, I assess the underlying structure of exposure to communication channels to two dimensions (news vs. socially mediated communication) through a principal axis factor analysis. Hierarchical regression analysis indicates that individual’s attitudes, perceived behavioral control, and self-efficacy are important factors of individual’s PM2.5 risk-reduction intention. Moral norm plays an important role in the study and predicts a significant additional variance in intention. Furthermore, two types of exposure to communication channels have a significant effect on intention to perform risk-reduction behavior. In addition, institutional trust is found to be positively associated with intention and has positive correlations with all of the components of the theory of planned behavior. The study also finds that items regarding behavioral adjustment to external air (pollution) quality are the most helpful and will make the most difference in predicting PM2.5 risk-reduction behavioral intentions.

Access

Open Access

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