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Using Time Intervals Between Expected Events to Communicate Risk Magnitudes

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  • Neil D. Weinstein
  • Kathryn Kolb
  • Bernard D. Goldstein

Abstract

Because members of the public have difficulty understanding risk presented in terms of odds ratios (e.g., 1 in 1000) and in comparing odds ratios from different hazards, we examined the use of time intervals between expected harmful events to communicate risk. Perceptions of the risk from a hypothetical instance of naturally‐occurring, cancer‐causing arsenic in drinking water supplies was examined with a sample of 705 homeowners. The risk was described as either 1 in 1000 or 1 in 100,000 and as present in a town of 2000 people or a city of 200,000 people. With these parameters, the time intervals ranged from 1 expected death in 3500 years (1 in 100,000 risk, small town) to 1 death every 4 months (1 in 1000 risk, city). The addition of time intervals to the odds ratios significantly decreased perceived threat and perceived need for action in the small town but did not affect response for the city. These framing effects were nearly as large as a 100‐fold difference in actual risk. Instances when this communication approach may be useful are discussed.

Suggested Citation

  • Neil D. Weinstein & Kathryn Kolb & Bernard D. Goldstein, 1996. "Using Time Intervals Between Expected Events to Communicate Risk Magnitudes," Risk Analysis, John Wiley & Sons, vol. 16(3), pages 305-308, June.
    • Handle: RePEc:wly:riskan:v:16:y:1996:i:3:p:305-308
    DOI: 10.1111/j.1539-6924.1996.tb01464.x
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    References listed on IDEAS

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    1. Paul Slovic, 1986. "Informing and Educating the Public About Risk," Risk Analysis, John Wiley & Sons, vol. 6(4), pages 403-415, December.
    2. Neil D. Weinstein & Peter M. Sandman, 1993. "Some Criteria for Evaluating Risk Messages," Risk Analysis, John Wiley & Sons, vol. 13(1), pages 103-114, February.
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    Cited by:

    1. Howard Kunreuther, 2001. "Risk Analysis and Risk Management in an Uncertain World," Center for Financial Institutions Working Papers 02-08, Wharton School Center for Financial Institutions, University of Pennsylvania.
    2. W. J. Wouter Botzen & Erwann Michel-Kerjan & Howard Kunreuther & Hans Moel & Jeroen C. J. H. Aerts, 2016. "Political affiliation affects adaptation to climate risks: Evidence from New York City," Climatic Change, Springer, vol. 138(1), pages 353-360, September.
    3. Stone, Eric R. & Sieck, Winston R. & Bull, Benita E. & Frank Yates, J. & Parks, Stephanie C. & Rush, Carolyn J., 2003. "Foreground:background salience: Explaining the effects of graphical displays on risk avoidance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 90(1), pages 19-36, January.
    4. de Jong, Piet & Tickle, Leonie & Xu, Jianhui, 2020. "A more meaningful parameterization of the Lee–Carter model," Insurance: Mathematics and Economics, Elsevier, vol. 94(C), pages 1-8.
    5. Howard Kunreuther, 2002. "Risk Analysis and Risk Management in an Uncertain World," Risk Analysis, John Wiley & Sons, vol. 22(4), pages 655-664, August.
    6. Howard Kunreuther & Elke U. Weber, 2014. "Aiding Decision-Making to Reduce the Impacts of Climate Change," NBER Working Papers 19776, National Bureau of Economic Research, Inc.
    7. Howard Kunreuther & Elke Weber, 2014. "Aiding Decision Making to Reduce the Impacts of Climate Change," Journal of Consumer Policy, Springer, vol. 37(3), pages 397-411, September.
    8. Branden B. Johnson, 2004. "Varying Risk Comparison Elements: Effects on Public Reactions," Risk Analysis, John Wiley & Sons, vol. 24(1), pages 103-114, February.
    9. Marielle Brunette, 2012. "Do risk communication methods perform to generate rationality?," Working Papers - Cahiers du LEF 2012-01, Laboratoire d'Economie Forestiere, AgroParisTech-INRA.
    10. Michael Siegrist, 1997. "Communicating Low Risk Magnitudes: Incidence Rates Expressed as Frequency Versus Rates Expressed as Probability," Risk Analysis, John Wiley & Sons, vol. 17(4), pages 507-510, August.

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