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Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering & Public Policy Adapted for the SuperCourse from a talk to International Society for Pharmacoepidemiology” April 19-20, 2004

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Page 1: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Risk Communication:An Introduction

Baruch FischhoffUniversity Professor

Carnegie MellonDepartment of Social & Decision SciencesDepartment of Engineering & Public Policy

Adapted for the SuperCourse from a talk to

International Society for Pharmacoepidemiology”April 19-20, 2004

Page 2: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Overview

Communication research strategiesTwo case studies

medical informed consentpublic health information management

Six brief examplesCommunication research management

Page 3: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Pressure for Lay Participationin Decisions Involving Risks

healthfinanceenvironmentnational security…

Page 4: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Poor Execution Can…

undermine effective lay decision making create feelings of helplessness erode public faith in authorities erode authorities’ faith in the public erode the social coordination produced by sharing trusted information sources

Page 5: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Research Strategy Choices

Begin with formal analysis?Persuasive or non-persuasive?Optimality or mastery?Which individual differences?

Page 6: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Research Strategy Choices

Begin with formal analysis?Persuasive or non-persuasive?Optimality or mastery?Which individual differences?

Also: Do you consider affect? social context? resources? …(potentially important, but outside present talk)

Page 7: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Behavioral Decision Research

Normative analysis of decision situationDescriptive behavioral research, in terms

comparable to normative analysisPrescriptive interventions, closing gaps

between normative ideal anddescriptive reality

Page 8: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Behavioral Decision Research Strategy Choices

Begin with formal analysis? yesPersuasive or non-persuasive? Non (default)Optimality or mastery? eitherWhich individual differences? circumstances, values, competence

Page 9: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Three Classes of Information

QuantitativeHow big are the risks - and benefits?

QualitativeWhat determines risks - and benefits?

Communication processWhat is social context of message?

Page 10: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

calculating expected utilityassessing the value of new information setting prioritiesapplying a threshold for concern

Uses of Quantitative Information

Page 11: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

making quantitative information credible

reconciling competing claims

generating options

monitoring environment for changes

feeling realistically empowered

Uses of Qualitative Information

Page 12: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

establishing source credibility(competence, honesty)

assessing source expectations(audience competence, locus of

control)identifying conversational context

(interpretation, reading between the lines)

Uses of Process Information

Page 13: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Surgery can extend life, but lots can go wrong.

Patients face flood of information at a stressful time.

Physicians face duty to inform.

(with Jon Merz, Paul Fischbeck, Dennis Mazur)

A Quantitative Information Example:

Carotid Endarterechtomy

Page 14: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Normative Analysis

Value-of-information analysis, using risk analyses of patient - relevant outcomes, formalizing the materiality standard

Page 15: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

deathstrokefacial paralysismyocardial infarctionlung damageheadache resurgerytracheostomygastrointestinal upsetbroken teeth…….

Many Possible Side Effects

Page 16: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

death 15.0%stroke 5.0facial paralysis 3.0myocardial infarction 1.1lung damage 0.9headache 0.8resurgery 0.4tracheostomy 0.2gastrointestinal upset 0.09broken teeth 0.01

(% that would decline, if they knew of each risk)

But knowledge of only a few would affect many patients’ choices

Page 17: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Descriptive Research (anticipated)

Patients don’t know probabilities of top risks: death, stroke, facial nerve paralysis

Patients don’t know event meaning forfacial paralysis

Page 18: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

verbal quantifiers (e.g., “likely” threat)experientially unfamiliar eventsvalue uncertainty (what do I really want?)

but not

very low probabilitiescumulative risk (from repeated exposure)

Prescriptive Design Issues (1)Identify Communication Challenges

Page 19: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

knowledgeinferential abilityappropriateness of confidenceappropriateness of self-efficacypersonally rational choicessatisfaction (?)

Prescriptive Design Issues (2)Choose Performance Measures

Page 20: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Conclusions

Systematically using clinical trial results can: drastically simplify task

(for patient & physician)formalize materiality standardset research priorities

The adequacy of non-persuasive communication

is plausible, but not proven

Page 21: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Research Strategy

Begin with formal analysis? yesPersuasive or non-persuasive? nonOptimality or mastery? ptimalityWhich individual differences?

health status, values(assume competence)

Page 22: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

A Qualitative Information (and Communication Process)

Example: Emergency Notification for Waterborne Pathogens

Cryptosporidium intrusion in domestic water supplies. Special vulnerabilityfor immunocompromised individuals.

(Liz Casman, Felicia Wu, Claire Palmgren, Mitch Small, Joan Rose, Hadi Dowlatabadi)

Page 23: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Normative Analysis

Behaviorally realistic model of system performance, including detection, organizational coordination, and consumer response

Page 24: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering
Page 25: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Units: Averting_behavior

Definition:  if consumer_awareness =0 then 0 else if consumer_awareness =1 then 1 else if info_sources > 0 then 2 else 2

Inputs:  Consumer_a…Consumer Awareness for Public Systems

Info_sources Info Sources

Outputs:  Consumptio…Consumption of Treated Water

Decision

Title:  Averting Behavior for Public Systems

Description:  Do consumers do something to avoid any possible risk of cryptosporidial infection? Correct averting behavior includes boiling drinking water and switching to safe water sources. Washing dishes, tooth brushing, and rinsing vegetables are not presently considered high risk behaviors for immunocompetent people in developed countries. Showering is not risky. Only filters with an absolute (not nominal) pore size Š 1 micron can effectively remove oocysts. (MMWR, 1995) Use of other types of filters do not constitute correct averting behavior. reference: MMWR 1995. Assessing the public health threat associated with waterborne cryptosporidiosis: report of a workshop. Rep. 44(RR-6):1-19. 0 = no action or inappropriate action (eg charcoal filter) 1 = avoid most tap water 2 = boil drinking water or use clean bottled water

Page 26: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Descriptive Research

“Mental models” interviews (open-ended, structured by model)

with:

HIV+ individuals:knew a lot, could do little

residents of communities with past intrusions:

knew little, mildly curious

Page 27: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Conclusions

Abandon emergency communication for crypto (perhaps OK for other contaminants, E. coli, bioterror)Provide bottled water to those at riskReevaluate communications for other immunocompromised individuals

Page 28: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Research Strategy

Begin with formal analysis? yesPersuasive or non-persuasive? persuasiveOptimality or mastery? masteryWhich individual differences?

health status, values, competence

Page 29: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Six Brief Examples

Sexual assault prevention adviceTeen STI riskVaccines (anthrax, MMR)Dietary supplementsHazardous chemicalsHomeland security

Page 30: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Problem: confident, universal, contradictory advice fosters confusion and guilt

Normative: inventory of strategies, meta-analysis of effectiveness studies, identification of valuesDescriptive: nuanced belief structure, exaggerated effectivenessPrescriptive: create realistic expectations, promote research evaluating effectiveness

Sexual Assault

Page 31: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Problem: flood of repetitious information creates illusion of understanding.

Normative: influence diagram summarizing decision-relevant scienceDescriptive: broad knowledge of HIV/AIDS, with critical “bugs”; little knowledge of other STIs, limited feeling of controlPrescriptive: targeted HIV/AIDS messages; DVD on sexual decision making

STIs (teens)

Page 32: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Problem: mistrust of officials affects trust in medicine

Normative: comprehensive model of factors determining health, trustDescriptive: critical issues outside official problem space, terminological confusionPrescriptive: provide context, including “irrelevant concerns”; research as communication

Vaccination (anthrax, MMR)

Page 33: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Problem: commercial-freedom-of-speech policies expanding direct-to-consumer communication

Normative analysis: model sensitive to burden of responsibility for consumer/market failureDescriptive analysis: court-mandated labels may erode consumer rationalityPrescriptive analysis: standardized, validated labels; legal standard for adequacy

Dietary supplements

Page 34: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Problem: Can voluntary controls substitute for regulatory controls?

Normative: diffusion/uptake model, including effects of behaviorDescriptive: ineffective measures intuitively appealing (e.g., gloves, in-room breaks)Prescriptive: standardized, validated labels; legal standard for adequacy

Hazardous Chemicals

Page 35: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Problem: Plans without behavioral input

Normative: Behaviorally realistic emergency response modelDescriptive: Simple facts not transmitted; unfounded belief in panic; specific fears decline, general anxiety stablePrescriptive: Communication to experts, interdisciplinary teams, preemptive messages

Homeland Security

Page 36: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Also…

BSESARSHRTGMOsXenotransplantationsmallpox (vaccination)…

Page 37: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

General Conclusions

Effective risk communication requires continuing collaboration among domain specialists, risk analysts, risk communicators, practitioners, andpatients (or their representatives) -- with each willing to have its assumptions challenged.

Page 38: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Why doesn’t everyone adoptbehavioral decision research?

Page 39: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Possible Professional Reasons

need for specializationseparation of research worldsisolation of researchers from practitionerspredisposition to persuasionpredisposition to sweeping generalizations…

Page 40: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Possible Management Reasons

focus on single outcomenarrow reviewing of proposals and productsfavor method application over developmentmandate to persuadedifficulty of evaluating non-persuasive communications

Page 41: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Persuasive communication can inappropriately

undermine credibility of public and experts

alienate audienceoverlook critical audience goals &

constraintsimpose bureaucratic priorities

Page 42: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Non-persuasive communication can inappropriately

assume nonexistent abilitiesdeny people needed protectionsmuddle value issuesleave wrong priorities unchallenged

Page 43: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Non-persuasive communicationis needed when:

No single, clear optimal choicemultiple values, situationslarge uncertainties

No clear advisory roleexperts distrustedshared decision-making

option desired

Page 44: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

The Empirical Question

How competent are lay people to participate?

Page 45: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Many Strong Opinions, Drawn from

assertionselected research evidenceanecdotal observation

small, unrepresentative samplesspeculative interpretationambiguity regarding decision frame

Page 46: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

technocratic control

paternalistic regulation

irrational public

free marketspopular democracy

hyper-rational public

“conservative”“liberal” Political predisposition:

Behavioral assumption:

Common Rhetorical Answers

Page 47: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

The Empirical Question(reformulated)

How competent are lay people to participate?

-- when facing specific decisions

-- and given half a chance

Page 48: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

A (Complex) Working Hypothesis

People often do sensible things if:

They get relevant information in a concise, credible form with adequate context, and without distractions

They have control over their environment and are judged by their own goals

They have some minimal decision-making competence

Page 49: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Lita Furby, Marcia Morgan, Julie Downs, Wändi Bruine de Bruin, Sara Eggers, Matt Dombroski, Donna Riley, Mitch Small, Steve Risotto, Dan Kovacs, Paul Fischbeck, Claire Palmgren, Robyn Dawes, Rebecca Parkin, Gordon Butte, Sarah Thorne, Martha Embrey, Jenn Lerner, Roxana Gonzalez, Deb Small, Gabriel Silverman, Lisa Schwartz, Steve Woloshin…

Collaborators

Page 50: Risk Communication: An Introduction Baruch Fischhoff University Professor Carnegie Mellon Department of Social & Decision Sciences Department of Engineering

Eggers, S.L., & Fischhoff, B. (in press). A defensible claim? Behaviorally realistic evaluation standards. Journal of Public Policy and Marketing.

Fischhoff, B. (1992). Giving advice: Decision theory perspectives on sexual assault. American Psychologist, 47, 577-588.

Fischhoff, B. (1994). What forecasts (seem to) mean. Intl Journal of Forecasting, 10, 387-403.

Fischhoff, B. (1995). Risk perception and communication unplugged: Twenty years of process. Risk Analysis, 15, 137-145.

Fischhoff, B. (1999). Why (cancer) risk communication can be hard. Journal of the National Cancer Institute Monographs, 25, 7-13.

Fischhoff, B. (2000). Scientific management of science? Policy Sciences, 33, 73-87.

Sources