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Research Article

Cognitive and Affective Routes to the Adoption of Protective Behaviors Against Health Risks of PM2.5 in China

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ABSTRACT

The current research examines how risk appraisals of PM2.5 influence Chinese people’s behavioral intentions to adopt government-recommended protective behaviors through negative affect. In testing the appraisal-based protective behavior model, this research also takes institutional trust and media sensationalism into account. An online survey is conducted with participants (N = 1,569) randomly drawn from heavily polluted Chinese regions. As predicted, negative affect mediates the effects of perceived susceptibility and perceived severity on individuals’ intentions to take preventive measures against the PM2.5 risk. Institutional trust appears to increase people’s behavioral intentions. However, media sensationalism decreases people’s behavioral intentions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. The Chinese governmental health department suggests that residents in the air pollution areas wear a mask, stay at home with windows closed when the air pollution is severe, use air purifiers indoors, take public transportation to reduce car emissions, etc. Chinese people can learn about these government’s recommended protective measures from Chinese government websites (e.g., http://www.gov.cn/fuwu/2019-12/10/content_5459931.htm) and news media reports (e.g., http://news.sina.com.cn/c/nd/2017-01-08/doc-ifxzkfuh6096191.shtml).

2. These three regions are Beijing-Tianjin-Hebei region (North China), the Yangtze River Delta (East China), and the Cheng-Yu area (Southwest China), densely industrialized and populated metropolitan areas. These regions are affected by the large amounts of coal combustion emissions and motor vehicle exhaust emissions. The topography of these three regions prevents air pollutants from dispersing in a timely manner, which let them suffer from the most severe haze problem in China.

Additional information

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea [NRF-2018S1A3A2074932].

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