Tyler (2002) found that the public is more likely to participate “in their communities when they feel that they are respected members of those communities” (p. 2067). Showing respect, therefore, is important for stakeholder engagement. The resources required for such an engagement of stakeholders, however, must be weighed against the need for such actions, given the context of the decision, including consideration of the potential health risks, the costs associated with the potential regulatory options, and the magnitude, sources, and nature or type of the uncertainty associated with the decision.
• Incorporating uncertainty analysis into a systematic framework, such as a modified version of the decision framework in Science and Decisions (NRC, 2009), provides a process for decision makers, stakeholders, and analysts to discuss the appropriate and necessary uncertainty analyses.
• Involvement of decision makers in the planning and scoping of uncertainty analyses during the initial, problem-formulation phase will help ensure that the goals of the uncertainty analysis are consistent with the needs of the decision makers.
• Involvement of stakeholders in the planning and scoping of uncertainty analyses during the initial problem-formulation phase will help define analytic endpoints and identify population subgroups as well as heterogeneity and other uncertainties.
• Uncertainty analysis must be designed on a case-by-case basis. The choice of uncertainty analysis depends on the context of the decision, including the nature or type of uncertainty (that is, heterogeneity and variability, model and parameter uncertainty, or deep uncertainty), and the factors that are considered in the decision (that is, health risk, technology availability, and economic, social, and political factors) as well as the data that are available.
• When assessing variability and heterogeneity:
Analyses of statistical distributions, including extreme-value analyses, are useful for assessing uncertainty in data on health effects (that is, estimates of risks). The use of safety or default factors (using statistics) can also be helpful under certain circumstances.
Direct assessments and technological choice or risk analyses developed using statistics can be helpful for assessing technological availability.