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Examining Psychometrics and Polarization in a Single‐Risk Case Study

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  • Craig W. Trumbo

Abstract

This project incorporates two steps. First, the psychometric model of risk perception is evaluated for its validity under field conditions. Second, individuals are classified as risk amplifiers or attenuators and the characteristics of those groups are explored. Survey data from an ongoing case study is employed in the analysis. The case study involves a Midwestern community in which a controversy exists over the possibility of the existence of a cancer cluster caused by the operation of a small reactor. Results show that the psychometric model of risk perception, while failing to be reproduced precisely, does has utility under the field conditions in this study. Use of the psychometric model to classify individuals as risk amplifiers or risk attenuators produces a useful dichotomy that reveals differences between the two polar groups in terms of demographics, satisfaction with institutional response to the risk, concern over individual and social levels of risk, and the evaluation of various communication channels as having been useful in coming to a judgment about the risk. A final model comparing the two groups suggests that, in this case, evaluation of personal risk and satisfaction with institutional response are important determinants of individual's risk reactions. Subordinate to these forces are the demographic variables of education, gender, and years of residence in the community. The model also illustrates that aggregate‐level observations may not be representative of subgroups.

Suggested Citation

  • Craig W. Trumbo, 1996. "Examining Psychometrics and Polarization in a Single‐Risk Case Study," Risk Analysis, John Wiley & Sons, vol. 16(3), pages 429-438, June.
    • Handle: RePEc:wly:riskan:v:16:y:1996:i:3:p:429-438
    DOI: 10.1111/j.1539-6924.1996.tb01477.x
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    References listed on IDEAS

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    1. Craig W. Trumbo & Katherine A. McComas, 2003. "The Function of Credibility in Information Processing for Risk Perception," Risk Analysis, John Wiley & Sons, vol. 23(2), pages 343-353, April.
    2. Henry H. Willis & Michael L. DeKay & Baruch Fischhoff & M. Granger Morgan, 2005. "Aggregate, Disaggregate, and Hybrid Analyses of Ecological Risk Perceptions," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 405-428, April.
    3. Craig W. Trumbo, 1999. "Heuristic‐Systematic Information Processing and Risk Judgment," Risk Analysis, John Wiley & Sons, vol. 19(3), pages 391-400, June.
    4. Katherine A. McComas, 2003. "Public Meetings and Risk Amplification: A Longitudinal Study," Risk Analysis, John Wiley & Sons, vol. 23(6), pages 1257-1270, December.
    5. Robert J. Griffin & Sharon Dunwoody & Fernando Zabala, 1998. "Public Reliance on Risk Communication Channels in the Wake of a Cryptosporidium Outbreak," Risk Analysis, John Wiley & Sons, vol. 18(4), pages 367-375, August.
    6. Kristoffer Wikstrom & Hal T. Nelson, 2022. "Spatial Validation of Agent-Based Models," Sustainability, MDPI, vol. 14(24), pages 1-13, December.
    7. Craig W. Trumbo & Katherine A. McComas & Prathana Kannaovakun, 2007. "Cancer Anxiety and the Perception of Risk in Alarmed Communities," Risk Analysis, John Wiley & Sons, vol. 27(2), pages 337-350, April.
    8. Kenneth Lachlan & Patric R. Spence, 2010. "Communicating Risks: Examining Hazard and Outrage in Multiple Contexts," Risk Analysis, John Wiley & Sons, vol. 30(12), pages 1872-1886, December.
    9. 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.

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