Avian Influenza Risk Perception and Preventive Behavior among Traditional Market Workers and Shoppers in Taiwan: Practical Implications for Prevention

Pei-Chun Kuo, Jiun-Hau Huang and Ming- Der Liu

PLOS ONE, 2011, vol. 6, issue 9, 1-6

Abstract: Background: Avian influenza (AI) can be highly pathogenic and fatal. Preventive behavior such as handwashing and wearing face masks has been recommended. However, little is known about what psychosocial factors might influence people's decision to adopt such preventive behavior. This study aims to explore risk perception and other factors associated with handwashing and wearing face masks to prevent AI. Methodology/Principal Findings: An interviewer-administered survey was conducted among 352 traditional market workers and shoppers in Taiwan between December 2009 and January 2010. Factors associated with the recommended AI preventive behavior (i.e., when in a traditional market, wearing a face mask and also washing hands after any contact with poultry) included: having correct knowledge about the fatality rate of AI (adjusted odds ratio [AOR] = 4.18), knowing of severe cases of AI (AOR = 2.13), being informed of local AI outbreaks (AOR = 2.24), living in northeastern Taiwan (AOR = 6.01), having a senior high-school education (AOR = 3.33), and having a university or higher education (AOR = 6.86). Gender interactive effect was also found among participants with a senior high-school education, with males being less likely to engage in the recommended AI preventive behavior than their female counterparts (AOR = 0.34). Conclusions/Significance: Specific information concerning AI risk perception was associated with the recommended AI preventive behavior. In particular, having correct knowledge about the fatality rate of AI and being informed of severe cases and local outbreaks of AI were linked to increased AI preventive behavior. These findings underscore the importance of transparency in dealing with epidemic information. These results also have practical implications for prevention and policy-making to more effectively promote the recommended AI preventive behavior in the public.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0024157

DOI: 10.1371/journal.pone.0024157

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