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      Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers

      review-article
      1 , , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14
      BMC Medical Informatics and Decision Making
      BioMed Central
      The International Patient Decision Aid Standards (IPDAS) Collaboration's Quality Dimensions: Theoretical Rationales, Current Evidence, and Emerging Issues
      1392012

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          Abstract

          Background

          Making evidence-based decisions often requires comparison of two or more options. Research-based evidence may exist which quantifies how likely the outcomes are for each option. Understanding these numeric estimates improves patients’ risk perception and leads to better informed decision making. This paper summarises current “best practices” in communication of evidence-based numeric outcomes for developers of patient decision aids (PtDAs) and other health communication tools.

          Method

          An expert consensus group of fourteen researchers from North America, Europe, and Australasia identified eleven main issues in risk communication. Two experts for each issue wrote a “state of the art” summary of best evidence, drawing on the PtDA, health, psychological, and broader scientific literature. In addition, commonly used terms were defined and a set of guiding principles and key messages derived from the results.

          Results

          The eleven key components of risk communication were: 1) Presenting the chance an event will occur; 2) Presenting changes in numeric outcomes; 3) Outcome estimates for test and screening decisions; 4) Numeric estimates in context and with evaluative labels; 5) Conveying uncertainty; 6) Visual formats; 7) Tailoring estimates; 8) Formats for understanding outcomes over time; 9) Narrative methods for conveying the chance of an event; 10) Important skills for understanding numerical estimates; and 11) Interactive web-based formats. Guiding principles from the evidence summaries advise that risk communication formats should reflect the task required of the user, should always define a relevant reference class (i.e., denominator) over time, should aim to use a consistent format throughout documents, should avoid “1 in x” formats and variable denominators, consider the magnitude of numbers used and the possibility of format bias, and should take into account the numeracy and graph literacy of the audience.

          Conclusion

          A substantial and rapidly expanding evidence base exists for risk communication. Developers of tools to facilitate evidence-based decision making should apply these principles to improve the quality of risk communication in practice.

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          Most cited references131

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          Risk, Ambiguity, and the Savage Axioms

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            The framing of decisions and the psychology of choice.

            The psychological principles that govern the perception of decision problems and the evaluation of probabilities and outcomes produce predictable shifts of preference when the same problem is framed in different ways. Reversals of preference are demonstrated in choices regarding monetary outcomes, both hypothetical and real, and in questions pertaining to the loss of human lives. The effects of frames on preferences are compared to the effects of perspectives on perceptual appearance. The dependence of preferences on the formulation of decision problems is a significant concern for the theory of rational choice.
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              General Performance on a Numeracy Scale among Highly Educated Samples

              Numeracy, how facile people are with basic probability and mathematical concepts, is associated with how people perceive health risks. Performance on simple numeracy problems has been poor among populations with little as well as more formal education. Here, we examine how highly educated participants performed on a general and an expanded numeracy scale. The latter was designed within the context of health risks.
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                Author and article information

                Contributors
                Conference
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central
                1472-6947
                2013
                29 November 2013
                : 13
                : Suppl 2
                : S7
                Affiliations
                [1 ]Primary Health Care, School of Public Health, Room 321b, Edward Ford Building (A27), University of Sydney, NSW 2006, Australia
                [2 ]Department of Health Behavior & Health Education, School of Public Health, Department of Internal Medicine, School of Medicine, and Center for Bioethics and Social Sciences in Medicine, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, USA
                [3 ]Cochrane Institute of Primary Care and Public Health, School of Medicine, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff CF14 4YS, UK
                [4 ]Harding Center for Risk Literacy, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
                [5 ]Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
                [6 ]Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, 509 Forest Avenue, Portland, ME 04101, USA
                [7 ]Department of Family Medicine, University of Vermont College of Medicine, 235 Rowell, 106 Carrigan Drive, University of Vermont, Burlington, Vermont 05405, USA
                [8 ]Department of Pediatrics, Children’s Hospital of Eastern Ontario, University of Ottawa, 401 Smyth Road, Ottawa, Ontario, K1H 8L1, Canada
                [9 ]Department of General Internal Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA
                [10 ]Duke University School of Nursing, 307 Trent Drive, Durham, NC 27710, USA
                [11 ]Department of Surgery and Institute for Health Policy Studies, University of California, San Francisco, 3333 California St. Suite 265, San Francisco, CA 94143-0936, USA
                [12 ]Department of Psychology, Ohio State University, 235 Psychology Building, 1835 Neil Avenue, Columbus, OH 43210, USA
                [13 ]Department of Public and Occupational Health, EMGO Institute for Health and Care Research, VU University Medical Center, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
                [14 ]Departments of Medicine and of Community & Family Medicine and The Dartmouth Institute for Health Policy & Clinical Practice at the Geisel School of Medicine at Dartmouth and the VA Outcomes Group, VA Medical Center, 215 North Main Street, White River Junction, VT 05009-0001, USA
                Article
                1472-6947-13-S2-S7
                10.1186/1472-6947-13-S2-S7
                4045391
                24625237
                6165d523-0be2-4c0b-bf05-20aa5b900297
                Copyright © 2013 Trevena et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                The International Patient Decision Aid Standards (IPDAS) Collaboration's Quality Dimensions: Theoretical Rationales, Current Evidence, and Emerging Issues
                Rockville, MD, USA
                1392012
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                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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