Competing perspectives on public involvement: Planning for risk characterization and risk communication about radiological contamination from a national laboratory

Abstract

Public involvement is increasingly emphasized as part of government agencies' responses to environmental health hazards, including risk characterization and risk communication. For example, there is a growing body of literature on health and risk communication proposing best practices and evaluating processes, yet there has been little attention to the ways that preferences for process features and criteria for evaluating success may vary among stakeholders and between stakeholders and government agency staff. This paper reports on a study into how participants associated with an effort to address public health risks from the distribution of plutonium contaminated sewage sludge in Livermore, California, think about the most appropriate way to conduct a process integrating public involvement. Using Q method this paper identifies five perspectives about what constitutes a good collaborative process in this case. The lessons for organizers and participants of risk characterization and risk communication efforts when people subscribe to different (sometimes competing) perspectives about process are discussed.

Keywords:

• Public involvement
• risk communication
• evaluation
• Q method
• department of Energy

Acknowledgments

We thank the people who agreed to participate in our case study, Gina Margillo of the Environmental Health Investigations Branch of the California Department of Health Services for her help in understanding the process we studied and identifying people to participate in our study, and Will Focht of Oklahoma State University for his advice on Q methodology. We would also like to thank the reviewers for their helpful comments. This material is in part based on work supported by the National Science Foundation under grant 0114784. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the National Science Foundation.

Notes

1 One measure by which we are confident that our statements are broadly representative is that after each Q sort we asked if the subject could think of any additional elements that would be important to him or her that were not represented in the Q statements. None of the 117 people who completed sorts in our ten case studies in our full research project suggested additional elements.

2 A question has arisen among researchers using Q methodology about whether the pattern into which people are required to sort the Q statements, such as the normal distribution shown in Figure 1, matters to the results that are obtained. The conclusion among researchers of Q is that the use of a normal distribution makes little or no difference to the results of a study. We elected to use the normal distribution because we find it helps people sort the cards and because it enables us to use software that we prefer.