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The Influence of Mapped Hazards on Risk Beliefs: A Proximity‐Based Modeling Approach

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  • Dolores J. Severtson
  • James E. Burt

Abstract

Interview findings suggest perceived proximity to mapped hazards influences risk beliefs when people view environmental hazard maps. For dot maps, four attributes of mapped hazards influenced beliefs: hazard value, proximity, prevalence, and dot patterns. In order to quantify the collective influence of these attributes for viewers’ perceived or actual map locations, we present a model to estimate proximity‐based hazard or risk (PBH) and share study results that indicate how modeled PBH and map attributes influenced risk beliefs. The randomized survey study among 447 university students assessed risk beliefs for 24 dot maps that systematically varied by the four attributes. Maps depicted water test results for a fictitious hazardous substance in private residential wells and included a designated “you live here” location. Of the nine variables that assessed risk beliefs, the numerical susceptibility variable was most consistently and strongly related to map attributes and PBH. Hazard value, location in or out of a clustered dot pattern, and distance had the largest effects on susceptibility. Sometimes, hazard value interacted with other attributes, for example, distance had stronger effects on susceptibility for larger than smaller hazard values. For all combined maps, PBH explained about the same amount of variance in susceptibility as did attributes. Modeled PBH may have utility for studying the influence of proximity to mapped hazards on risk beliefs, protective behavior, and other dependent variables. Further work is needed to examine these influences for more realistic maps and representative study samples.

Suggested Citation

  • Dolores J. Severtson & James E. Burt, 2012. "The Influence of Mapped Hazards on Risk Beliefs: A Proximity‐Based Modeling Approach," Risk Analysis, John Wiley & Sons, vol. 32(2), pages 259-280, February.
  • Handle: RePEc:wly:riskan:v:32:y:2012:i:2:p:259-280
    DOI: 10.1111/j.1539-6924.2011.01700.x
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    References listed on IDEAS

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    1. Brian J. Zikmund-Fisher & Dylan M. Smith & Peter A. Ubel & Angela Fagerlin, 2007. "Validation of the Subjective Numeracy Scale: Effects of Low Numeracy on Comprehension of Risk Communications and Utility Elicitations," Medical Decision Making, , vol. 27(5), pages 663-671, September.
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    3. Wouter Poortinga & Patrick Cox & Nick F. Pidgeon, 2008. "The Perceived Health Risks of Indoor Radon Gas and Overhead Powerlines: A Comparative Multilevel Approach," Risk Analysis, John Wiley & Sons, vol. 28(1), pages 235-248, February.
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    1. Dolores J. Severtson & Jeffrey D. Myers, 2013. "The Influence of Uncertain Map Features on Risk Beliefs and Perceived Ambiguity for Maps of Modeled Cancer Risk from Air Pollution," Risk Analysis, John Wiley & Sons, vol. 33(5), pages 818-837, May.
    2. Branden B. Johnson, 2018. "Residential Location and Psychological Distance in Americans’ Risk Views and Behavioral Intentions Regarding Zika Virus," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2561-2579, December.
    3. Eoin O'Neill & Finbarr Brereton & Harutyun Shahumyan & J. Peter Clinch, 2016. "The Impact of Perceived Flood Exposure on Flood‐Risk Perception: The Role of Distance," Risk Analysis, John Wiley & Sons, vol. 36(11), pages 2158-2186, November.
    4. Ronald L. Schumann & Kevin D. Ash & Gregg C. Bowser, 2018. "Tornado Warning Perception and Response: Integrating the Roles of Visual Design, Demographics, and Hazard Experience," Risk Analysis, John Wiley & Sons, vol. 38(2), pages 311-332, February.

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