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Multiple Health Risk Perception and Information Processing Among African Americans and Whites Living in Poverty

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  • Shelly Hovick
  • Vicki S. Freimuth
  • Ashani Johnson‐Turbes
  • Doryn D. Chervin

Abstract

We investigated the risk‐information‐processing behaviors of people living at or near the poverty line. Because significant gaps in health and communication exist among high‐ and low‐income groups, increasing the information seeking and knowledge of poor individuals may help them better understand risks to their health and increase their engagement in health‐protective behaviors. Most earlier studies assessed only a single health risk selected by the researcher, whereas we listed 10 health risks and allowed the respondents to identify the one that they worried about most but took little action to prevent. Using this risk, we tested one pathway inspired by the risk information seeking and processing model to examine predictors of information insufficiency and of systematic processing and extended this pathway to include health‐protective action. A phone survey was conducted of African Americans and whites living in the southern United States with an annual income of ≤$35,000 (N= 431). The results supported the model pathway: worry partially mediated the relationship between perceived risk and information insufficiency, which, in turn, increased systematic processing. In addition, systematic processing increased health‐protective action. Compared with whites and better educated respondents, African Americans and respondents with little education had significantly higher levels of information insufficiency but higher levels of systematic processing and health‐protective action. That systematic processing and knowledge influenced health behavior suggests a potential strategy for reducing health disparities.

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  • Shelly Hovick & Vicki S. Freimuth & Ashani Johnson‐Turbes & Doryn D. Chervin, 2011. "Multiple Health Risk Perception and Information Processing Among African Americans and Whites Living in Poverty," Risk Analysis, John Wiley & Sons, vol. 31(11), pages 1789-1799, November.
    • Handle: RePEc:wly:riskan:v:31:y:2011:i:11:p:1789-1799
    DOI: 10.1111/j.1539-6924.2011.01621.x
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    References listed on IDEAS

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    Cited by:

    1. Peng Cheng & Zhe Ouyang & Yang Liu, 0. "The effect of information overload on the intention of consumers to adopt electric vehicles," Transportation, Springer, vol. 0, pages 1-20.
    2. Janet Z. Yang, 2019. "Whose Risk? Why Did the U.S. Public Ignore Information About the Ebola Outbreak?," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1708-1722, August.
    3. Quan Gao & Hye Eun Lee, 2021. "How Framed Messages Influence Depression Assessment Intentions: Interactivity of Social Media as a Moderator," IJERPH, MDPI, vol. 18(4), pages 1-15, February.
    4. Jingguo Wang & Nan Xiao & H. Raghav Rao, 2015. "Research Note—An Exploration of Risk Characteristics of Information Security Threats and Related Public Information Search Behavior," Information Systems Research, INFORMS, vol. 26(3), pages 619-633, September.
    5. Jay D. Hmielowski & Meredith Y. Wang & Rebecca R. Donaway, 2018. "Expanding the Political Philosophy Dimension of the RISP Model: Examining the Conditional Indirect Effects of Cultural Cognition," Risk Analysis, John Wiley & Sons, vol. 38(9), pages 1891-1903, September.
    6. Michelle McDowell & Thorsten Pachur, 2020. "Availability, Affect, and Decisions to Seek Information about Cancer Risks," Medical Decision Making, , vol. 40(8), pages 941-945, November.
    7. Chuanhui Liao & Yu Luo & Weiwei Zhu, 2020. "Food Safety Trust, Risk Perception, and Consumers’ Response to Company Trust Repair Actions in Food Recall Crises," IJERPH, MDPI, vol. 17(4), pages 1-16, February.
    8. Jiuchang Wei & Ming Zhao & Fei Wang & Peng Cheng & Dingtao Zhao, 2016. "An Empirical Study of the Volkswagen Crisis in China: Customers’ Information Processing and Behavioral Intentions," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 114-129, January.
    9. Guanglu Xu & Ming Xue & Jidi Zhao, 2023. "The Relationship of Artificial Intelligence Opportunity Perception and Employee Workplace Well-Being: A Moderated Mediation Model," IJERPH, MDPI, vol. 20(3), pages 1-16, January.

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