Communicating Food Benefits and Risks Baruch Fischhoff Carnegie Mellon University

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1 Communicating Food Benefits and Risks Baruch Fischhoff Carnegie Mellon University Food: Balancing Risk and Benefit Challenges and Limitations for Risk Management January 21, 2013

2 Disclosure I have no known conflicts of interest.

3 Decision Science Normative analysis (how people should make decisions) Descriptive research (how people do make decisions) Prescriptive interventions (how people could make decisions) (Edwards, 1954)

4 Some Basic Sources Normative Descriptive Prescriptive

5 Good Communication Is Vital listening for: fears, desires, opportunities for conveying benefits, risks, respect for audience

6 Poor Communications Undermine lay decision making by missing opportunities to help people make sound choices to learn about their concerns to design better options to get full value from our science and technology

7 Poor Communications Erode the commons of goodwill by -- undermining lay confidence in experts -- undermining expert confidence in the public

8 Challenges Normative analysis how to measure risks and benefits Descriptive research how to measure beliefs and values Prescriptive interventions how to make risks and benefits clear

9 Challenges Normative analysis how to measure risks and benefits Descriptive research how to measure beliefs and values Prescriptive interventions how to make risks and benefits clear

10 Common Constraints (Evidence) Multiple, heterogeneous endpoints Complex, uncertain direct data Rich, nuanced background science

11 Common Constraints (Stakeholders) Limited cognitive capacity (need data reduction) Different values (not captured by any single representation) Labile values (may be unstable with unfamiliar representations) Different backgrounds (may not read between the lines similarly)

12 Common Metrics: Potential Benefits Reduced cognitive load by summarizing data Transparency with explicit measures Comparability with common measure

13 Common Metrics: Potential Risks Increased cognitive load from decoding obscure measures Reduced transparency with embedded values Non-comparability due to lost data properties

14 Two Analytical Challenges Embedded values Lost data properties

15 Embedded Values The terms of all analyses embody values that favor some interests. When transparent, those assumptions are controversial.

16 Defining Risk of Death probability of premature death vs. expected life-year lost

17 Defining Risk of Death probability of premature death vs. expected life-year lost The choice of measure depends on whether a death is a death or one values deaths of young people more.

18 Other Possible Bases for Distinguishing among Deaths Are the risks distributed equitably? assumed voluntarily? catastrophic? well understood? controllable? dread? borne by future generations?

19 Fischhoff, B., & Kadvany, J. (2011). Risk: A Very Short Introduction. Oxford: Oxford University Press.

20 Discounting Future Outcomes Reasons to value future outcomes less -- valuing them less deliberately unthinkingly (hyperbolic discounting) -- opportunity costs -- not expecting to have them provided -- not expecting to be there to get them -- dreading the wait -- wanting to live with the experience (Frederick, Loewenstein, O Donoghue, 2002)

21 Embedded Values The terms of all analyses embody values that favor some interests. When transparent, those assumptions are controversial. As a result, common metrics obscure value issues, unless adopted by a credible public process resolving those controversies.

22 Lost Data Properties Treatment of uncertainties Long, J., & Fischhoff, B. (2000). Setting risk priorities: A formal model. Risk Analysis, 20,

23 Lost Data Properties Common metrics can obscure the expert judgment involved in data interpretation. Decision makers have no way to discover that logic or know if it matters.

24 Lost Data Properties Common metrics can obscure the expert judgment involved in data interpretation. Decision makers have no way to discover that logic or know if it matters. As a result, a candid, comprehensible disclosure process is needed.

25 Challenges Normative analysis how to measure risks and benefits Descriptive research how to measure beliefs and values Prescriptive interventions how to make risks and benefits clear

26 Decision Science Finds That Decision making follows simple principles.

27 Decision Science Finds That Decision making follows simple principles. However, the set of principles is large, the contextual triggers are subtle, and the interactions are complex

28 Decision Science Finds That Decision making follows simple principles. However, the set of principles is large, the contextual triggers are subtle, and the interactions are complex As a result, decision-specific research is needed.

29 Some Sources

30 Some Applications plague perchloroethylene LNG climate change detergent breast cancer nuclear explosions herpes (stigma) xenotransplantation smart meters domestic radon methylene chloride EMF UXO violent radicalization breast implants nuclear power in space Plan B (morning after pill) neonates vaccines (anthrax, MMR)

31 Challenges Normative analysis how to measure risks and benefits Descriptive research how to measure beliefs and values Prescriptive interventions how to make risks and benefits clear

32 Three Examples Risk ranking (US EPA; HM Treasury) Benefit-risk framework (US FDA CDER) Drug fact boxes (US NCI, US FDA?)

33 Risk Ranking US EPA attempt to involve public in resetting its priorities. Solution pursued by many national bodies.

34 Florig, H.K., Morgan, M.G., Morgan, K.M., Jenni, K.E., Fischhoff, B., Fischbeck, P.S., & DeKay, M. (2001). A deliberative method for ranking risks (1): Overview and test beddevelopment. Risk Analysis, 21,

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36 Decisions on managing risks to the public CBA, including Societal Concerns Deaths Harm Concern factors 1 Familiarity Expert views Public views 2 Understanding 3 Equity 4 Dread Baseline WTP 5 Control 6 Trust Decision making HM Treasury. (2005). Managing risks to the public. London: Author.

37 FDA CDER Benefit-Risk Framework Capture rationale of FDA evaluation of evidence and decision making. Clear to producers and consumers. In PDUFA V. Fischhoff, B. (2012). Good decisions require good communication. Drug Safety, 35,

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39 Drug Fact Boxes Patterned on nutrition fact boxes. Decision-specific risks and benefits. Empirically evaluated to publication standard. Schwartz L, Woloshin, S, & Welch, H. (2007). The drug facts box: Providing consumers with simple tabular data on drug benefit and harm. Medical Decision Making, 27,

40 40

41 See Woloshin, S., Schwartz, L.M., Black, W.C., & Kramer, B.S. (2012). Cancer screening campaigns Getting past uninformative persuasion. NEJM, 367, DOI: /NEJMp

42 Effective Communication Requires Normative analysis which risks and benefits matter Descriptive research into what people believe and want Prescriptive interventions tested for creating the beliefs needed to make decisions addressing wants

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44 Books Fischhoff, B., Brewer, N., & Downs, J.S. (eds.). (2011). Communicating risks and benefits: An evidence-based user s guide. Washington, DC: Food and Drug Administration. Fischhoff, B., & Chauvin, C. (eds.). (2011). Intelligence analysis: Behavioral and social science foundations. Washington, DC: National Academy Presshttp:// Fischhoff, B., & Kadvany, J. (2011). Risk: A very short introduction. Oxford: Oxford University Press. Fischhoff, B., Lichtenstein, S., Slovic, P., Derby, S. L. & Keeney, R. L. (1981). Acceptable risk. New York: Cambridge University Press. (NUREG/CR-1614). Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar Giroux & Strauss. Morgan, M.G., Henrion, M. (1990). Uncertainty. New York: Cambridge University Press. Slovic, P. (ed.) (2000). Perception of risk. London: Earthscan. Research Articles Bruine de Bruin, W., Parker, A., & Fischhoff, B. (2007) Individual differences in adult decision-making competence (A-DMC). Journal of Personality and Social Psychology. 92, Fischhoff, B. (1992). Giving advice: Decision theory perspectives on sexual assault. American Psychologist, 47, Fischhoff, B. (2011). Communicating the risks of terrorism (and anything else). American Psychologist, 66, Fischhoff, B. (2012, Summer). Communicating uncertainty: Fulfilling the duty to inform. Issues in Science and Technology, 29, 63-70, Fischhoff, B., Bruine de Bruin, W., Guvenc, U., Caruso, D., & Brilliant, L. (2006). Analyzing disaster risks and plans: An avian flu example. Journal of Risk and Uncertainty, 33, Carnegie Mellon Electricity Center: Center for Climate and Environmental Decision Making: Center for Risk Perception and Communication: Center for Human Rights Science: