NSF-SSRC: Risk communication in low- and high-affect contexts

University Of Oregon Eugene, Eugene OR

Investigators

Abstract

Healthcare professionals attempt to inform the public about health risks including by translating complex statistics. People, however, often misunderstand or remain unmotivated to change behavior. This project investigates best methods to present quantifiable health risks to increase comprehension and healthy behaviors. Doing so is important to the nation’s health given growing efforts to discuss statistical risks with patients and patients’ greater access to statistical information about diseases, treatments, and preventives. How statistics are presented can matter as much as what statistics are presented. A theory-based taxonomy of effective risk formats is developed to better communicate risks and improve decisions, potentially improving societal well being by increasing patient autonomy, avoiding harms of aggressive treatments, improving quality of life, and saving money and lives. The research team integrates this knowledge into ongoing science-communication trainings in the Center for Science Communication Research. They also will increase public science literacy and engagement through lay-friendly pieces and by training physicians and policymakers in evidence-based communication methods. Five studies increase understanding of psychological mechanisms underlying health decisions involving numeric information. Novel tests of formats to communicate numeric health risks are designed to alter psychological mechanisms through affective meaning (i.e., feelings of goodness or badness about risk numbers); 2) focusing attention; or 3) changing cognitive effort. Systematically varying risk formats allows for tests of dual-process theories and development of a theory-based taxonomy of risk formats in low- and high-affect settings. Good decisions are identified primarily through increased risk comprehension and sensitivity to risk numbers where sensitivity is defined either as distinguishing sensibly between numeric levels—e.g., perceiving more risk from a 22% than 7% chance—or weighting statistics more in the presence of narrative content. Findings illuminate how people integrate affect to health outcomes and to risk statistics. The research has theoretical and pragmatic implications in medical decisions and science communication. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.