I The Mental Modeling Approach

Mental Modeling Research Technical Approach

Sarah Thorne, Gordon Butte, Daniel Kovacs, and Matthew D. Wood

Introduction

The Mental Modeling research approach discussed in the following chapters is built on the foundational work in risk perception and risk communications at Carnegie Mellon University led by Dr. Baruch Fischhoff[1] [2] and is well established in the fields of risk analysis and decision sciences (Atman et al. 1994; Bostrom et al. 1992; Fischhoff et al. 2011; Morgan et al. 2002). Mental Modeling is particularly well suited for generating the in-depth, evidence-based understanding of factors influencing decision making and behavior required to develop strategies, plans, and communications to effectively address people’s thinking on complex issues. The process is science-informed, based on social science methodology, and evidence- based in that it facilitates the use of information systematically gathered from stakeholders themselves. Its purpose is to help decision-makers and communicators make informed decisions about how best to communicate risks, design policy, or develop behavioral interventions with the needs, priorities, and interests of the focal stakeholders in mind.

The central idea behind Mental Modeling is that people’s judgments, decision making, and behavior about whether and how to adopt a new innovation, accept a medical procedure, or support a power plant or natural gas transmission line, are influenced by their mental models (Morgan et al. 2002).

Mental models are the tacit webs of beliefs that individuals draw upon to interpret and make inferences about issues that come to their attention. They develop over time based on a person’s values, priorities, experiences and observations, formal education, and communications of all kinds. Where persons have no experience upon which to draw, they will draw inferences from existing mental models that seem relevant to them (Fischhoff et al. 2002). Information perceived as consistent with existing beliefs is readily incorporated into a person’s mental model; information at odds with existing beliefs is not, and may even be rejected.

  • [1] This Guideline (subsequently revised in 2009 as Q850-87 (R2009) Risk Management: Guidelinefor Decision Makers) is also aligned with the US Presidential/Congressional Commission on RiskAssessment and Risk Management Process and the Australian/New Zealand Risk ManagementStandard. In addition, our work in strategic risk communications is aligned with the InternationalOrganization for Standardization’s (ISO) 31000 Guidelines on Risk Management (2009), to whichwe provided input.
  • [2] Dr. Fischhoff is Decision Partners’ Chief Scientist responsible for strategic research design,implementation, and analysis. He is also the Howard Heinz University Professor of the Departmentsof Social and Decision Science, and Engineering and Public Policy at Carnegie Mellon University. S. Thorne , M.A. Decision Partners, 1084 Queen Street West, #32B, Mississauga, ON, Canada L5H 4K4e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it G. Butte (*) Decision Partners LLC , Suite 200, 313 East Carson Street , Pittsburgh , PA 15217 , USAe-mail: This email address is being protected from spam bots, you need Javascript enabled to view it D. Kovacs , Ph.D. Decision Partners, 1458 Jersey Street, Lake Milton, OH 44429, USAe-mail: This email address is being protected from spam bots, you need Javascript enabled to view it M.D. Wood , Ph.D. U.S. Army Corps of Engineers, Engineer Research and Development Center (ERDC) andCarnegie Mellon University, 696 Virginia Road, Concord, MA 01742, USAe-mail: This email address is being protected from spam bots, you need Javascript enabled to view it © Springer Science+Business Media, LLC 2017 M.D. Wood et al., Mental Modeling Approach, Risk, Systems and Decisions,DOI 10.1007/978-1-4939-6616-5_2
 
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