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Studying Heuristic‐Systematic Processing of Risk Communication

Author

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  • LeeAnn Kahlor
  • Sharon Dunwoody
  • Robert J. Griffin
  • Kurt Neuwirth
  • James Giese

Abstract

Using a model of risk information seeking and processing developed by Griffin, Dunwoody, and Neuwirth (1999), this study looks at predictors of the processing strategies that people apply to health risk information. Specifically, this article focuses on one relationship within the model—the relationship between perceived amount of information needed to deal with a risk and heuristic‐systematic processing. Perceived amount of information needed refers to the gap between one's understanding of a risk and the level of understanding that one needs in order to make a decision about that risk. Building on the work of Chaiken (cf. 1980), the Griffin et al. model predicts—and finds—that the larger the gap, the more likely one will process information systematically. The study employs a novel measure of information processing in a survey setting by sending actual information to participants and then asking them how they attended to it; the researchers evaluate this strategy. Finally, the researchers discuss how these findings might help agencies and practitioners create more effective risk messages.

Suggested Citation

  • LeeAnn Kahlor & Sharon Dunwoody & Robert J. Griffin & Kurt Neuwirth & James Giese, 2003. "Studying Heuristic‐Systematic Processing of Risk Communication," Risk Analysis, John Wiley & Sons, vol. 23(2), pages 355-368, April.
  • Handle: RePEc:wly:riskan:v:23:y:2003:i:2:p:355-368
    DOI: 10.1111/1539-6924.00314
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    Cited by:

    1. 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.
    2. Branden B. Johnson, 2008. "Public Views on Drinking Water Standards as Risk Indicators," Risk Analysis, John Wiley & Sons, vol. 28(6), pages 1515-1530, December.
    3. 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.
    4. Branden B. Johnson, 2005. "Testing and Expanding a Model of Cognitive Processing of Risk Information," Risk Analysis, John Wiley & Sons, vol. 25(3), pages 631-650, June.
    5. Shu-Chu Sarrina Li & Shih-Yu Lo & Tai-Yee Wu & Te-Lin Chen, 2022. "Information Seeking and Processing during the Outbreak of COVID-19 in Taiwan: Examining the Effects of Emotions and Informational Subjective Norms," IJERPH, MDPI, vol. 19(15), pages 1-13, August.
    6. Wang, Fei & Zhang, Zhentai & Lin, Shoufu, 2023. "Purchase intention of Autonomous vehicles and industrial Policies: Evidence from a national survey in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    7. Isaac M. Lipkus, 2007. "Numeric, Verbal, and Visual Formats of Conveying Health Risks: Suggested Best Practices and Future Recommendations," Medical Decision Making, , vol. 27(5), pages 696-713, September.
    8. 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.
    9. Blanca I. Hernández-Ortega & Michael A. Stanko & Rishika Rishika & Francisco-Jose Molina-Castillo & José Franco, 2022. "Brand-generated social media content and its differential impact on loyalty program members," Journal of the Academy of Marketing Science, Springer, vol. 50(5), pages 1071-1090, September.
    10. Unji Baek & Seul Ki Lee, 2023. "Pandemic Dining Dilemmas: Exploring the Determinants of Korean Consumer Dining-Out Behavior during COVID-19," Sustainability, MDPI, vol. 15(10), pages 1-15, May.
    11. Jiyoun Kim & Sara K. Yeo & Dominique Brossard & Dietram A. Scheufele & Michael A. Xenos, 2014. "Disentangling the Influence of Value Predispositions and Risk/Benefit Perceptions on Support for Nanotechnology Among the American Public," Risk Analysis, John Wiley & Sons, vol. 34(5), pages 965-980, May.
    12. Z. Janet Yang, 2016. "Altruism During Ebola: Risk Perception, Issue Salience, Cultural Cognition, and Information Processing," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1079-1089, June.
    13. Lu, Hang & Song, Hwanseok & McComas, Katherine, 2021. "Seeking information about enhanced geothermal systems: The role of fairness, uncertainty, systematic processing, and information engagement intentions," Renewable Energy, Elsevier, vol. 169(C), pages 855-864.
    14. Michael Greenberg & Kristen Crossney, 2006. "The changing face of public concern about pollution in the United States: A case study of New Jersey," Environment Systems and Decisions, Springer, vol. 26(4), pages 255-268, December.
    15. Weidan Cao & Qinghua Yang & Xinyao Zhang, 2023. "Understanding Information Processing and Protective Behaviors during the Pandemic: A Three-Wave Longitudinal Study," IJERPH, MDPI, vol. 20(5), pages 1-15, February.
    16. Craig W. Trumbo & Katherine A. McComas & John C. Besley, 2008. "Individual‐ and Community‐Level Effects on Risk Perception in Cancer Cluster Investigations," Risk Analysis, John Wiley & Sons, vol. 28(1), pages 161-178, February.
    17. Jooyoung Kim & Hye‐Jin Paek, 2009. "Information Processing of Genetically Modified Food Messages Under Different Motives: An Adaptation of the Multiple‐Motive Heuristic‐Systematic Model," Risk Analysis, John Wiley & Sons, vol. 29(12), pages 1793-1806, December.
    18. 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.
    19. Chris M. R. Smerecnik & Ilse Mesters & Math J. J. M. Candel & Hein De Vries & Nanne K. De Vries, 2012. "Risk Perception and Information Processing: The Development and Validation of a Questionnaire to Assess Self‐Reported Information Processing," Risk Analysis, John Wiley & Sons, vol. 32(1), pages 54-66, January.

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