When can scientific studies promote consensus among conflicting stakeholders?

While scientific studies may help conflicting stakeholders come to agreement on a best management option or policy, often they do not. We review the factors affecting trust in the efficacy and objectivity of scientific studies in an analytical-deliberative process where conflict is present, and show how they may be incorporated in an extension to the traditional Bayesian decision model. The extended framework considers stakeholders who differ in their prior beliefs regarding the probability of possible outcomes (in particular, whether a proposed technology is hazardous), differ in their valuations of these outcomes, and differ in their assessment of the ability of a proposed study to resolve the uncertainty in the outcomes and their hazards--as measured by their perceived false positive and false negative rates for the study. The Bayesian model predicts stakeholder-specific preposterior probabilities of consensus, as well as pathways for increasing these probabilities, providing important insights into the value of scientific information in an analytic-deliberative decision process where agreement is sought. It also helps to identify the interactions among perceived risk and benefit allocations, scientific beliefs, and trust in proposed scientific studies when determining whether a consensus can be achieved. The article provides examples to illustrate the method, including an adaptation of a recent decision analysis for managing the health risks of electromagnetic fields from high voltage transmission lines.

Communicating about xenotransplantation: models and scenarios.

Xenotransplantation entails using organs from genetically modified animals as a way to solve the shortage of human organs for transplantation. As with other novel technologies, if xenotransplantation is to be judged fairly, proponents must explain its complex, uncertain, and unfamiliar risks and benefits. Xenotransplantation's risks include the possibility of a recombinant virus infecting human transplant recipients, potentially causing an epidemic of an unfamiliar disease. Using materials vetted by scientific experts, we communicated the variables and relationships determining this risk in three formally equivalent formats: (a) a graphic model, (b) scenarios structured by the graphic model, and (c) both the model and the scenarios. Participants were randomly assigned to receiving one set of materials. They rated them as equally clear and studied them equally long, suggesting similar ease of cognitive processing. Compared to participants receiving the scenarios, those who received the graphic model better identified causes and effects of the risk, and saw less risk of xenotransplantation. Participants who received both the model and the scenarios generally showed intermediate responses. The study demonstrates a general procedure for developing and evaluating formally equivalent graphic and scenario communications regarding highly uncertain risks. In this application to xenotransplantation, presenting a graphic representation improved people's understanding of the risk.