Risk Communication Challenges for Nanomaterials:

A Taxonomy (Typology)within a Risk Analysis Framework

Prof. Jennifer Kuzma, co-PI

Associate Professor, U of MNNIRT ITox Meeting

August 28, 2008

Outline

• Challenges in risk communication from a risk analysis standpoint

• Context and framing possibilities

• Discussion of integrating concepts across disciplines--risk analysis, risk communication, science, public policy, and public engagement

• Ties to NSF-funded research

Risk Communication goals

• Risk communication is an exchangeexchange of information about risk amongamong decision makers, stakeholders, and the public which is intended to supply people with the information they need to make informedinformed and independent independent judgments about risk

– Morgan, G. et al. 2002. Risk Communication: A Mental Models Approach. Cambridge, MA: Cambridge University Press. (p. 4)

• Not a “deficit model”, but Enabling model

• Advice and answers• Number • Context and Framing

A Risk Analysis Framework

Risk Assessment

Risk Management(including mitigation

Risk Communication

Risk Assessment

Risk Management(including mitigation

Risk Communication

Risk perception Decision making

Public Engagement

Risk Policy

Hazard identificationExposure Assessment

Dose-Response AssessmentRisk Characterization

Risk communication should be the hub of policy

Powell and Leiss 1997Mad Cows and Mother’s Milk: The Perils of Poor Risk Communication

A Risk Policy Problem

Powell and Leiss 1997

Risk Communication Challenges

Powell and Leiss 1997

An (outdated)model of risk communication

Knuth, B.A. (1990). North American Journal of Fisheries Management. 10(4):374-381.

Message modulators•Credibility of messenger•Cultural, social, and •operational factors•Channels of communication

Can cause distortion and unintended messages

Filters

IRGC report • Where do nanomaterials fit?

• Depends on type of nanomaterial—product dependency?

• High ambiguity—more need for deliberation (context and framing approach to risk communication)

IRGC 2006Advice and answers, numbers, context/framing?

Problem Formulation and Deliberative Analytical ProcessInput from Experts, Stakeholders, and the Public (Interested and Affected Parties)

Ongoing and Iterative

Sources of nanomaterials

Material-related characteristics

Transport and fate; geochemical processes

Biological uptake mechanisms

Toxic effects on individual species

Interactions between species and geochemical processes

Human or Ecological risks with different population of species end points

Exposure Assessment

Characterization of Human orEcological Effects

Including Dose or Stressor-Response Assessment

Risk Characterization

Hazard Identification

Problem Formulation and Deliberative Analytical ProcessInput from Experts, Stakeholders, and the Public (Interested and Affected Parties)

Ongoing and Iterative

Sources of nanomaterials

Material-related characteristics

Transport and fate; geochemical processes

Biological uptake mechanisms

Toxic effects on individual species

Interactions between species and geochemical processes

Human or Ecological risks with different population of species end points

Exposure Assessment

Characterization of Human orEcological Effects

Including Dose or Stressor-Response Assessment

Risk Characterization

Hazard Identification

Environmental Risk Assessment for Nanomaterials

Monitoring, Adaptive, Feedback, Guiding Force for Risk Research

Steps to risk communication or deliberation (Morgan et al 2002)

• Create expert model (influence diagram)– Diagram allows representation of knowledge of experts from diverse disciplines– “The influence diagram allows a quick, visual check of the factors that must be covered when

evaluating audience information needs” • Caseman and Morgan (2008)

• Conduct open-ended (mental-model) interviews– People’s beliefs about hazard and risk in their own terms– How well do mental models correspond to expert model in influence diagram– Identify issues

• Conduct structured initial interviews– Explore issues– Larger groups

• Draft risk communication or deliberation method– Neutral voice– Which knowledge gaps need filling

• Evaluate communication or deliberation method with individuals selected from target population

– “Lay evaluation”

Expert Model of risk--puzzle• Morgan 2005 Risk Analysis 25(4): 1621-1635

Toxic Effects Magnified

Equity in risk discussions

• Expert vs. Not Expert

• Barriers, filters, gaps, and different mental models

• Can we level the playing field so that we get to true differences in attitudes rather than differences in reception and understanding of information?

Gaps in Information

• Even Experts do not have the information

• Any individual study about risk does not put the puzzle together

• How to communicate with stakeholders and laypersons about risk based on one or just a few pieces of the puzzle?

Possible approaches to test

• Map expert model onto layperson model– Follow standard Morgan et al. approach

• Map expert studies into expert models:– Forgo “advice, answers,” and “numbers” for

“context and framing”– Use expert framing of risk for nanomaterials to

type individual pieces of information– Visual and contextual translation for not-expert

audience

Possibilities to Explore for Better Risk Communication

• Objective risk– Database of studies mapped into risk assessment (and risk

analysis) framework• Levels to database based on user• (part of U of MN NSF CEIN proposal)

– For starters, use what, when, who, why, where questions to enhance communications about risk (and toxicology or dose-response)

• Subjective risk– Listen and learn– Incorporate concerns and values into risk analysis framing

of problems– Deliberative democracy. Public engagement approaches

Puzzling together risk

Study a

Study b

Study d Study c

Context and Framing: Information comes in bits and piecesHow can we enhance risk communication for individual studies?

U of MN CEIN grant proposal 2007

Clearinghouse of EHS and Risk Studies

• Taxonomy of EHS information in Risk Analysis framework– Level 1: Public, Educators, Stakeholders– Level 2: EHS and other interested experts– Level 3: Nanomaterial manufacturers– Level 4: Nanoinformatics

• A possible communication tool? – Web-based information and framing tool for other printed or verbal materials

Research

Risk AssessmentRisk Analysis

Context and Framing

Typology of questions about riskQuestion Examples Why do we care about the risk? Subjective risk dominates, although objective plays a role.

Social concern about hazard Previously demonstrated harm Societal value placed on endpoints of harm Hazard with parallels to those with known significant risk Political interest

What is causing the harm? Hazard identification step primarily, although overlap with exposure assessment. Subjective and objective risk.

Biological based nanomaterial (e.g. nanoparticle made of protein or DNA, viral b io-nanotechnology)

Chemically manufactured or engineered nanomaterial Modified, natural nanomaterial Free-floating nanoparticle in air, soil, water, etc. Bound nanomaterials Modified state of nanomaterial from environmental travel Mixtures of nanomaterials and other chemicals

Who (or what) is potentially harmed? Endpoints of concern for exposure assessment and hazard identification. Subjects of dose-response studies and ultimately risk characterization. Subjective and objective risk.

Human populations generally Higher organis ms Ecosystems generally Microbes in water or soil Susceptible populations of humans (e.g. children, elderly ) Particular populations of humans (e.g. immigrants, disadvantaged

groups, indigenous peoples) How might the harm occur? Hazard origins and exposure routes. Objective risk dominates, but subjective risk plays a role.

Intentional release (e.g. pesticides, environmental remediat ion) Non-compliance with material d isposal Unintentional leakage or leaching Accidental Through air, water, soil, products, or food By inhalation, dermal, or ingestion routes

Where does the harm take place? Endpoint and exposure environments. Subjective and objective risk.

Workplace Human natural environment Human built environment Ecosystems (wet lands, agroecosystems, etc.) Homes (e.g. from consumer products)

When does the risk occur? Exposure timing and hazard identification. Objective risk dominates, although subjective risk plays a role

Seasonal Acute Chronic Dependent on temporal compliance with oversight Dependent on environmental conditions

Trust-credibility• Address subjective risk component (deliberation, engagement)

• But recognize that subjective (social?) and objective (epistemic?)dimensions of risk are not that distinct– Fischhoff, B., S.R. Watson, and C. Hope. 1984. Defining risk.

Policy Sciences 17: 123-139.– Kuzma and Besley 2008. Ethics of Risk Analysis and Regulatory

Review: From Bio to Nano. Nanoethics in press, online.

• Prevent biased (and exaggerated) communication of individual study results– E.g. GE Corn and Monarch butterfly story, Losey article and first

round of field trials (see Pew Initiative on Food and Biotechnology report, 2002)

• “Neutral” communication bodies for objective information and subjective risk discussions

Ethics of Risk Analysis and Regulatory Review: From Bio to Nano

Kuzma and Besley 2008, Nanoethics

Factors in Risk Comparisons & Perception

• “Risk” not necessarily equal to the # of fatalities

• Experts perceive differently

• Laypersons – Benefits, Trust, Affect

Important – Product dependent for

nanofood– Siegrist 2007, 2008

“Thus, disagreements about risk should not be expected to evaporate in the presence of evidence” (Slovic et al 1990)

• “Risk Perception Factors”– Natural/Man-Made– Ordinary/catastrophic– Voluntary/Involuntary– Delayed/Immediate– Controlled/Uncontrolled– Old/New– Necessary/Luxury– Regular/Occasional

Rasmussen, Slovic, Fischhoff, et al. 1990, in Readings in Risk

Stages of Risk Communication

•Given “fuzziness” of risk and risk analysis itself, trust, and perception factors •(S. Priest)

•Need to move beyond stages, separation of objective/subjective• To Integration, Enabling, Contextual, Analytical-Deliberative process (NRC 1996)

Morgan et al. 2002

NSF-NIRT Grant

1. What factors are most significant in affecting public perception of the risks of applied nanosciences?

2. What, if any, relationship exists between the modes of public deliberation, sources of information (e.g., use of new media), and the effects of new information on perceptions of the risks of applied nanosciences?

• refine andrefine and develop key variables develop key variables and instruments (stage 1) and instruments (stage 1)

• determine the contribution of variables to perceived risk—Delphi rounds (stage 2)

– Will framing help level playing field between experts and non-experts?

• elucidate the effect of civic engagement and new media on risk perception (stage 3)

• verify key variables related to risk perception—focus groups agrifood nano (stage 4),

• outreach to the public (stage 5).

Other NIRT—Oversight Lessons for NanotechnologyEvaluation of six historical models

National Science Foundation NIRT Grant SES-0608791 (Wolf, PI; Kokkoli, Kuzma, Paradise, Ramachandran, Co-PIs).

Step 1: Develop exhaustive list of criteriaQualitative Literature Analysis, informed by Expert and Stakeholder Consensus

Step 2: Criteria RankingOf Importance for Oversight Model Evaluation

Expert and Stakeholder Elicitation , also Informed by Literature Analysis

Step 3: Application of Criteria to Each Historical Model: Expert and Stakeholder Scoring of How Well Each Model Performs on Each Criterion

Also informed by semi-structured expert and stakeholder interviews

Step 4: Evaluation of Relationships Among CriteriaExpert and stakeholder semi-structured interviews

Analysis of Criteria Scores: relationships of criteria within historical modelDevelopment of Influence Diagrams

Step 5: Comparison across historical modelsQualitative and Quantitative analysis

Comparing criteria scores across modelsComparing influence diagrams across models

Step 1: Develop exhaustive list of criteriaQualitative Literature Analysis, informed by Expert and Stakeholder Consensus

Step 2: Criteria RankingOf Importance for Oversight Model Evaluation

Expert and Stakeholder Elicitation , also Informed by Literature Analysis

Step 3: Application of Criteria to Each Historical Model: Expert and Stakeholder Scoring of How Well Each Model Performs on Each Criterion

Also informed by semi-structured expert and stakeholder interviews

Step 4: Evaluation of Relationships Among CriteriaExpert and stakeholder semi-structured interviews

Analysis of Criteria Scores: relationships of criteria within historical modelDevelopment of Influence Diagrams

Step 5: Comparison across historical modelsQualitative and Quantitative analysis

Comparing criteria scores across modelsComparing influence diagrams across models

Conclusions for Oversight: What makes an effective oversight system?Do certain ways of developing oversight frameworks lead to certain outcomes ?

Do specific attributes of oversight frameworks lead to certain outcomes ?How does development affect system attributes ?

What are apprpopriate oversight approaches for nanobiotechnology?

Criteria fall into four categoriesfor oversight:

Development, Attributes, Outcomes, and Evolution

Other NIRT—Lessons for NanotechnologyEvaluating Oversight Models for Nanobiotechnology

• Experts asked to rank how six case studies of oversight have performed on scale of 1-100 on 28 criteria

How was the oversight model developed ?

What are its attributes ?

What are its outcomes ?

How do the attributes evolve over time ?

How was the oversight model developed ?

What are its attributes ?

What are its outcomes ?

How do the attributes evolve over time ?

How was the oversight model developed ?

What are its attributes ?

What are its outcomes ?

How do the attributes evolve over time ?

National Science Foundation NIRT Grant SES-0608791 (Wolf, PI; Kokkoli, Kuzma, Paradise, Ramachandran, Co-PIs).

Ethical, policy,legal, and risk analysis

Expert and Stakeholder Interviews

Expert Elicitation Historical Literature Analysis

QuantitativeQualitativeNormative

Ethical, policy,legal, and risk analysis

Expert and Stakeholder Interviews

Expert Elicitation Historical Literature Analysis

QuantitativeQualitativeNormative

Relationships among criteriap<0.0016

Relationships:Attributes of GEOs oversight to public

confidence as an outcome

Public InputD4

Data requirements

A9

Incentives A14

Public InputA19

Public Confidence

O24

p<0.05R=approx. 0.5 for all

Hypothesis: public input is important for outcome of public confidence in oversight systems.

Messages and Synergies among NSF-NIRTs and fields of

investigation• Consider attributes of oversight as

possible factors in perception of new technologies (risk perception too)

• Finding relationships among attributes of oversight and outcomes such as public confidence, health and safety, and environmental impacts.

Thank you

• NSF NIRT grant Intuitive Toxicology and Public Engagement (#0709056)

• (PI: David M. Berube, co-PIs, Dietram A. Scheufele,Jennifer Kuzma, Kevin Elliott, Pat J. Gehrke, V. Colvin).

• Contact info, J. Kuzma– 612-625-6337, kuzma007@umn.edu