1932

Abstract

This review briefly examines the vast range of techniques used to communicate risk assessments arising from statistical analysis. After discussing essential psychological and sociological issues, I focus on individual health risks and relevant research on communicating numbers, verbal expressions, graphics, and conveying deeper uncertainty. I then consider practice in a selection of diverse case studies, including gambling, the benefits and risks of pharmaceuticals, weather forecasting, natural hazards, climate change, environmental exposures, security and intelligence, industrial reliability, and catastrophic national and global risks. There are some tentative final conclusions, but the primary message is to acknowledge expert guidance, be clear about objectives, and work closely with intended audiences.

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2017-03-07
2024-11-06
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Literature Cited

  1. Akl EA, Oxman AD, Herrin J, Vist GE, Terrenato I. et al. 2011. Using alternative statistical formats for presenting risks and risk reductions. Cochrane Database Syst. Rev. 3:CD006776 [Google Scholar]
  2. Ancker JS, Senathirajah Y, Kukafka R, Starren JB. 2006. Design features of graphs in health risk communication: a systematic review. J. Am. Med. Inform. Assoc. JAMIA 13608–18 [Google Scholar]
  3. Ancker JS, Weber EU, Kukafka R. 2011. Effect of arrangement of stick figures on estimates of proportion in risk graphics. Med. Decis. Making 31143–50 [Google Scholar]
  4. ASQ (Am. Soc. for Qual.) 2004. Failure Mode Effects Analysis (FMEA) Milwaukee, WI: Am. Soc. for Qual http://asq.org/learn-about-quality/process-analysis-tools/overview/fmea.html [Google Scholar]
  5. Automot. Ind. Action Group. 2009. Failure mode and effects analysis ranking table http://elsmar.com/pdf_files/FMEA%20and%20Reliability%20Analysis/AIAG%20FMEA-Ranking-Tables.pdf [Google Scholar]
  6. Balshem H, Helfand M, Schünemann HJ, Oxman AD, Kunz R. et al. 2011. GRADE guidelines: 3. Rating the quality of evidence. J. Clin. Epidemiol. 64:401–6 [Google Scholar]
  7. Bammer G, Smithson M. 2008. Uncertainty and Risk: Multidisciplinary Perspectives London: Earthscan [Google Scholar]
  8. Beck NB, Becker RA, Erraguntla N, Farland WH, Grant RL. et al. 2016. Approaches for describing and communicating overall uncertainty in toxicity characterizations: U.S. Environmental Protection Agency's Integrated Risk Information System (IRIS) as a case study. Environ. Int. 89–90:110–28 [Google Scholar]
  9. Bell H, Tobin G. 2007. Efficient and effective? The 100-year flood in the communication and perception of flood risk. Environ. Hazards 7:302–11 [Google Scholar]
  10. Bouder F, Slavin D. 2007. The Tolerability of Risk: A New Framework for Risk Management London: Earthscan [Google Scholar]
  11. Broad K, Leiserowitz A, Weinkle J, Steketee M. 2007. Misinterpretations of the “cone of uncertainty” in Florida during the 2004 hurricane season. Bull. Am. Meteorol. Soc. 88:651–67 [Google Scholar]
  12. Budescu DV, Por H-H, Broomell SB, Smithson M. 2014. The interpretation of IPCC probabilistic statements around the world. Nat. Clim. Change 4:508–12 [Google Scholar]
  13. Cancer Research UK. 2015. Lifetime Risk of Cancer London: Cancer Research UK http://www.cancerresearchuk.org/health-professional/cancer-statistics/risk/lifetime-risk [Google Scholar]
  14. Carlyle T. 1871. Oliver Cromwell's Letters and Speeches: With Elucidations New York: Scribner, Welford and Co. [Google Scholar]
  15. Channel 4 2011. Bin Laden: shoot to kill Channel 4 Television Documentary, first aired Sept. 7 [Google Scholar]
  16. COMEAP (Comm. Med. Eff. Air Pollut.). 2009. Long-term exposure to air pollution: effect on mortality Rep., Comm. Med. Eff. Air Pollut., UK Health Prot. Agency. https://www.gov.uk/government/publications/comeap-long-term-exposure-to-air-pollution-effect-on-mortality [Google Scholar]
  17. Covey J. 2007. A meta-analysis of the effects of presenting treatment benefits in different formats. Med. Decis. Mak. Int. J. Soc. Med. Decis. Mak 27638–54 [Google Scholar]
  18. Cvetkovich G, Lofstedt RE. 2013. Social Trust and the Management of Risk London: Routledge [Google Scholar]
  19. Demuth JL, Morss RE, Morrow BH, Lazo JK. 2012. Creation and communication of hurricane risk information. Bull. Am. Meteorol. Soc. 93:1133–45 [Google Scholar]
  20. Dep. Homel. Secur. 2011. The Strategic National Risk Assessment in Support of PPD 8: A Comprehensive Risk-Based Approach Toward a Secure and Resilient Nation https://www.dhs.gov/xlibrary/assets/rma-strategic-national-risk-assessment-ppd8.pdf [Google Scholar]
  21. Diebold FX, Doherty NA, Herring RJ. 2010. The Known, the Unknown, and the Unknowable in Financial Risk Management: Measurement and Theory Advancing Practice Princeton, NJ: Princeton Univ. Press [Google Scholar]
  22. Dieckmann NF, Peters E, Gregory R. 2015. At home on the range? Lay interpretations of numerical uncertainty ranges. Risk Anal 35:1281–95 [Google Scholar]
  23. Douglas M, Wildavsky A. 1983. Risk and Culture: An Essay on the Selection of Technological and Environmental Dangers Oakland: Univ. Calif. Press [Google Scholar]
  24. Ellsberg D. 1961. Risk, ambiguity and the Savage axioms. Q. J. Econ. 75:643–69 [Google Scholar]
  25. EFSA (Eur. Food Saf. Auth.). 2016. Guidance on Uncertainty in EFSA Scientific Assessment https://www.efsa.europa.eu/sites/default/files/160321DraftGDUncertaintyInScientificAssessment.pdf [Google Scholar]
  26. EFSA Panel on Food CEF (Eur. Food Saf. Auth. Panel on Food Contact Mater., Enzym., Flavour. and Process. Aids). 2015. Scientific opinion on the risks to public health related to the presence of bisphenol A (BPA) in foodstuffs. EFSA J. 13:3978 [Google Scholar]
  27. EMA (Eur. Med. Agency). 2014. Benefit-Risk Methodology Project. Update on Work Package 5: Effects Table Pilot (Phase I) Eur. Med. Agency, London. http://www.ema.europa.eu/docs/en_GB/document_library/Report/2014/02/WC500162036.pdf [Google Scholar]
  28. EMA (Eur. Med. Agency). 2016. Section 4.8: Undesirable Effects Eur. Med. Agency, London. http://www.ema.europa.eu/docs/en_GB/document_library/Presentation/2013/01/WC500137021.pdf [Google Scholar]
  29. EPA (U.S. Environ. Prot. Agency). 2011. Vocabulary catalog: Integrated Risk Information System (IRIS) glossary https://ofmpub.epa.gov/sor_internet/registry/termreg/searchandretrieve/glossariesandkeywordlists/search.do?details=&glossaryName=IRIS%20Glossary#formTop [Google Scholar]
  30. Fagerlin A, Wang C, Ubel PA. 2005. Reducing the influence of anecdotal reasoning on people's health care decisions: is a picture worth a thousand statistics?. Med. Decis. Mak. Int. J. Soc. Med. Decis. Mak 25398–405 [Google Scholar]
  31. Fagerlin A, Zikmund-Fisher BJ, Ubel PA. 2011. Helping Patients Decide: Ten Steps to Better Risk Communication. JNCI J. Natl. Cancer Inst. 103:1436–43 [Google Scholar]
  32. Feldman-Stewart D, Brundage MD, Zotov V. 2007. Further insight into the perception of quantitative information: judgments of gist in treatment decisions. Med. Decis. Mak. Int. J. Soc. Med. Decis. Mak 2734–43 [Google Scholar]
  33. Few S. 2016. Expressing proportions. Vis. Bus. Intell. Newsl. April/May/June. http://www.perceptualedge.com/articles/visual_business_intelligence/expressing_proportions.pdf [Google Scholar]
  34. Fischhoff B. 1995. Risk perception and communication unplugged: twenty years of Process1. Risk Anal 15:137–45 [Google Scholar]
  35. Fischhoff B. 2006. The science and practice of risk ranking. Horizons 10:3 https://www.cmu.edu/dietrich/sds/docs/fischhoff/SciencePracticeRiskRanking.pdf [Google Scholar]
  36. Fischhoff B, Brewer NT, Downs JS. 2011. Communicating Risks and Benefits: An Evidence-Based User's Guide Silver Spring, MD: US Dep. Health Hum. Serv. [Google Scholar]
  37. Fischhoff B, Davis AL. 2014. Communicating scientific uncertainty. PNAS 111:13664–71 [Google Scholar]
  38. Friedman JA, Zeckhauser R. 2015. Handling and mishandling estimative probability: likelihood, confidence, and the search for Bin Laden. Intell. Natl. Secur. 30:1–23 [Google Scholar]
  39. Gaissmaier W, Wegwarth O, Skopec D, Müller A-S, Broschinski S, Politi MC. 2012. Numbers can be worth a thousand pictures: individual differences in understanding graphical and numerical representations of health-related information. Health Psychol 31:286–96 [Google Scholar]
  40. Galesic M, Garcia-Retamero R. 2010. Statistical numeracy for health: A cross-cultural comparison with probabilistic national samples. Arch. Intern. Med. 170:462–68 [Google Scholar]
  41. Galesic M, Garcia-Retamero R, Gigerenzer G. 2009. Using icon arrays to communicate medical risks: overcoming low numeracy. Health Psychol. Off. J. Div. Health Psychol. Am. Psychol. Assoc. 28:210–16 [Google Scholar]
  42. Galesic M, Kause A, Gaissmaier W. 2016. A Sampling Framework for Uncertainty in Individual Environmental Decisions. Top. Cogn. Sci. 8:242–58 [Google Scholar]
  43. Garcia-Retamero R, Galesic M, Gigerenzer G. 2010. Do icon arrays help reduce denominator neglect?. Med. Decis. Mak 30672–84 [Google Scholar]
  44. Geosci. Aust. 2014. What is Risk? Geosci. Aust., Symonston, Aust. http://www.ga.gov.au/scientific-topics/hazards/risk-impact/risk [Google Scholar]
  45. Gigerenzer G. 2014. Should patients listen to how doctors frame messages. BMJ 349:g7091 [Google Scholar]
  46. Gigerenzer G, Galesic M. 2012. Why do single event probabilities confuse patients?. BMJ 344:e245 [Google Scholar]
  47. Gigerenzer G, Hertwig R, van den Broek E, Fasolo B, Katsikopoulos KV. 2005. “A 30% chance of rain tomorrow”: How does the public understand probabilistic weather forecasts?. Risk Anal 25:623–29 [Google Scholar]
  48. Global Chall. Found. 2016. Global Catastrophic Risks Global Chall. Found., Stockholm. http://globalchallenges.org/annual-report-on-global-risks [Google Scholar]
  49. Goldin R. 2015. Death by bacon: Did the news get to the meat of the matter. STATS Nov. 11. http://www.stats.org/death-by-bacon-did-the-news-get-to-the-meat-of-the-matter/ [Google Scholar]
  50. Hall SS. 2011. Scientists on trial: at fault?. Nat. News 477:264–69 [Google Scholar]
  51. Hallgreen CE, Mt-Isa S, Lieftucht A, Phillips LD, Hughes D. et al. 2016. Literature review of visual representation of the results of benefit–risk assessments of medicinal products. Pharmacoepidemiol. Drug Saf. 25:238–50 [Google Scholar]
  52. Han PKJ, Klein WMP, Lehman T, Killam B, Massett H, Freedman AN. 2011. Communication of uncertainty regarding individualized cancer risk estimates. Med. Decis. Mak 31354–66 [Google Scholar]
  53. Harmsen CG, Kristiansen IS, Larsen PV, Nexoe J, Stovring H. et al. 2014. Communicating risk using absolute risk reduction or prolongation of life formats: cluster-randomised trial in general practice. Br. J. Gen. Pract. 64:e199–207 [Google Scholar]
  54. Health Saf. Executive. 2016. HID's Approach to ALARP Decisions—SPC/Permissioning/39 Health Saf. Executive Bootle, UK: http://www.hse.gov.uk/foi/internalops/hid_circs/permissioning/spc_perm_39.htm [Google Scholar]
  55. Hildon Z, Allwood D, Black N. 2012. Impact of format and content of visual display of data on comprehension, choice and preference: a systematic review. Int. J. Qual. Health Care 24:55–64 [Google Scholar]
  56. Hughes D, Waddingham E, Mt-Isa S, Goginsky A, Chan E. et al. 2016. Recommendations for benefit-risk assessment methodologies and visual representations. Pharmacoepidemiol. Drug Saf. 25:251–62 [Google Scholar]
  57. IPCC (Intergov. Panel Clim. Change). 2013. Summary for policymakers. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge, UK: Cambridge Univ. Press https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_SPM_FINAL.pdf [Google Scholar]
  58. IPCC (Intergov. Panel Clim. Change) Cross-Working Group Meeting on Consistent Treatment of Uncertainties. 2010. Guidance note for lead authors of the IPCC fifth assessment report on consistent treatment of uncertainties. IPCC Cross-Work. Group Meet. Consistent Treat. Uncertain., Jasper Ridge, CA, USA, 6–7 July. [Google Scholar]
  59. ISO (Int. Stan. Organ.) 2009. ISO 31000—Risk Management Geneva: ISO http://www.iso.org/iso/home/standards/iso31000.htm [Google Scholar]
  60. Johansen IL, Rausand M. 2012. Risk metrics: Interpretation and choice. IEEE Int. Conf. Ind. Eng. Eng. Manag.1914–18 Piscataway, NJ: IEEE [Google Scholar]
  61. Jonkman SN, van Gelder PHAJM, Vrijling JK. 2003. An overview of quantitative risk measures for loss of life and economic damage. J. Hazard. Mater. 99:1–30 [Google Scholar]
  62. Joslyn SL, Nichols RM. 2009. Probability or frequency? Expressing forecast uncertainty in public weather forecasts. Meteorol. Appl 16:309–14 [Google Scholar]
  63. Kahan DM. 2015. What is the “science of science communication”?. J. Sci. Comm 14:1–10 [Google Scholar]
  64. Kahneman D, Slovic P, Tversky A. 2006. Judgment under Uncertainty: Heuristics and Biases Cambridge, UK: Cambridge Univ. Press [Google Scholar]
  65. Kellens W, Terpstra T, De Maeyer P. 2013. Perception and communication of flood risks: a systematic review of empirical research. Risk Anal 33:24–49 [Google Scholar]
  66. Keller C, Siegrist M, Visschers V. 2009. Effect of risk ladder format on risk perception in high- and low-numerate individuals. Risk Anal 29:1255–64 [Google Scholar]
  67. Kemp R. 2016. Why are only 1 in 100 men taking up shared parental leave?. The Telegraph Apr. 5. http://www.telegraph.co.uk/men/the-filter/why-are-only-1-in-100-men-taking-up-shared-parental-leave/ [Google Scholar]
  68. Kirby J. 2015. Bacon, ham and sausages have the same cancer risk as cigarettes warn experts. Daily Record Oct. 23. http://www.dailyrecord.co.uk/news/health/bacon-ham-sausages-same-cancer-6689230#ebyBMgxErTb9Jf7i.97 [Google Scholar]
  69. Knapp P. 2004. Comparison of two methods of presenting risk information to patients about the side effects of medicines. Qual. Saf. Health Care 13:176–80 [Google Scholar]
  70. Knapp P, Gardner PH, Woolf E. 2016. Combined verbal and numerical expressions increase perceived risk of medicine side‐effects: a randomized controlled trial of EMA recommendations. Health Expect 19:264–74 [Google Scholar]
  71. Knight F. 1921. Risk, Uncertainty and Profit Boston: Hart, Schaffner & Marx [Google Scholar]
  72. Kreuzmair C, Siegrist M, Keller C. 2016. High numerates count icons and low numerates process large areas in pictographs: results of an eye-tracking study. Risk Anal 36:1599–614 [Google Scholar]
  73. Lachlan K, Spence PR. 2010. Communicating risks: examining hazard and outrage in multiple contexts. Risk Anal 30:1872–86 [Google Scholar]
  74. Langendam MW, Akl EA, Dahm P, Glasziou P, Guyatt G, Schünemann HJ. 2013. Assessing and presenting summaries of evidence in Cochrane Reviews. Syst. Rev. 2:81 [Google Scholar]
  75. Leiss W. 1996. Three phases in the evolution of risk communication practice. Ann. Am. Acad. Pol. Soc. Sci. 545:85–94 [Google Scholar]
  76. Lempert RJ, Collins MT. 2007. Managing the risk of uncertain threshold responses: comparison of robust, optimum, and precautionary approaches. Risk Anal 27:1009–26 [Google Scholar]
  77. Lofstedt R. 2013. Communicating food risks in an era of growing public distrust: three case studies: perspective. Risk Anal 33:192–202 [Google Scholar]
  78. Lopez-Gonzalez AA, Aguilo A, Frontera M, Bennasar-Veny M, Campos I. et al. 2015. Effectiveness of the Heart Age tool for improving modifiable cardiovascular risk factors in a Southern European population: a randomized trial. Eur. J. Prev. Cardiol. 22:389–96 [Google Scholar]
  79. Marchio J. 2014. “If the weatherman can...”: the intelligence community's struggle to express analytic uncertainty in the 1970s. Stud. Intell. 58:31–42 [Google Scholar]
  80. Melnick EL, Everitt BS. 2008. Encyclopedia of Quantitative Risk Analysis and Assessment New York: John Wiley & Sons [Google Scholar]
  81. MI5. 2010. MI5 Terrorism Threat Level https://www.mi5.gov.uk/threat-levels [Google Scholar]
  82. Moore RA, Wiffen PJ, Derry S, Toelle T, Rice ASC. 2014. Gabapentin for chronic neuropathic pain and fibromyalgia in adults. Cochrane Database Syst. Rev. 3:CD007938 [Google Scholar]
  83. Morgan G, Dowlatabadi H, Henrion M, Keith D, Lempert R. et al. 2009. Best Practice Approaches for Characterizing, Communicating, and Incorporating Scientific Uncertainty in Climate Decision Making Silver Spring, MD: Natl. Ocean. Atmos. Organ. [Google Scholar]
  84. Morgan MG, Fischhoff B, Bostrom A, Atman CJ. 2001. Risk Communication: A Mental Models Approach Cambridge, UK: Cambridge Univ. Press, 1st ed.. [Google Scholar]
  85. Morgan RL, Thayer KA, Bero L, Bruce N, Falck-Ytter Y. et al. 2016. GRADE: assessing the quality of evidence in environmental and occupational health. Environ. Int. 92–93:611–16 [Google Scholar]
  86. Morss R, Demuth J, Lazo J. 2008. Communicating uncertainty in weather forecasts: a survey of the U.S. public. Weather Forecast 23:974–91 [Google Scholar]
  87. NRC (Natl. Res. Counc.) 1989. Improving Risk Communication. Washington, D.C.: Natl. Acad. Press [Google Scholar]
  88. Paling J. 2003. Strategies to help patients understand risks. BMJ 327:745–48 [Google Scholar]
  89. Pappenberger F, Stephens E, Thielen J, Salamon P, Demeritt D. et al. 2013. Visualizing probabilistic flood forecast information: expert preferences and perceptions of best practice in uncertainty communication. Hydrol. Process. 27:132–46 [Google Scholar]
  90. Peters E. 2008. Numeracy and the Perception and Communication of Risk. Ann. N. Y. Acad. Sci. 1128:1–7 [Google Scholar]
  91. Peters E, Dieckmann NF, Västfjäll D, K C, Slovic P, Hibbard JH. 2009. Bringing meaning to numbers: The impact of evaluative categories on decisions. J. Exp. Psychol. Appl. 15:213–27 [Google Scholar]
  92. Peters E, Hart PS, Fraenkel L. 2011. Informing patients: the influence of numeracy, framing, and format of side effect information on risk perceptions. Med. Decis. Mak 31432–36 [Google Scholar]
  93. Pidgeon N, Fischhoff B. 2011. The role of social and decision sciences in communicating uncertain climate risks. Nat. Clim. Change 1:35–41 [Google Scholar]
  94. Pighin S, Savadori L, Barilli E, Galbiati S, Smid M. et al. 2015. Communicating Down syndrome risk according to maternal age: “1-in-X” effect on perceived risk. Prenat. Diagn. 35:777–82 [Google Scholar]
  95. Radawski C, Morrato E, Hornbuckle K, Bahri P, Smith M. et al. 2015. Benefit-risk assessment, communication, and evaluation (BRACE) throughout the life cycle of therapeutic products: overall perspective and role of the pharmacoepidemiologist. Pharmacoepidemiol. Drug Saf. 24:1233–40 [Google Scholar]
  96. Rakow T, Wright RJ, Bull C, Spiegelhalter DJ. 2012. Simple and multistate survival curves: Can people learn to use them. Med. Decis. Mak 32792–804 [Google Scholar]
  97. Rakow T, Wright RJ, Spiegelhalter DJ, Bull C. 2015. The pros and cons of funnel plots as an aid to risk communication and patient decision making. Br. J. Psychol. 106:327–48 [Google Scholar]
  98. Reinhardt JC, Chen X, Liu W, Manchev P, Paté-Cornell ME. 2016. Asteroid risk assessment: a probabilistic approach. Risk Anal 36:244–61 [Google Scholar]
  99. Risk Management Solutions. 2012. Model use and uncertainty http://www.casact.org/community/affiliates/camar/1012/uncertainty.pdf [Google Scholar]
  100. Ropeik D. 2010. How Risky Is It, Really? Why Our Fears Don't Always Match the Facts New York: McGraw-Hill [Google Scholar]
  101. Rumsfeld D. 2002. Defense.gov News Transcript. http://archive.defense.gov/Transcripts/Transcript.aspx?TranscriptID=2636 [Google Scholar]
  102. Sandberg A, Bostrom N. 2008. Global catastrophic risks survey Tech. Rep. 2008–1, Future Humanity Inst., Univ. Oxford [Google Scholar]
  103. Sandman PM, Miller PM, Johnson BB, Weinstein ND. 1993. Agency communication, community outrage, and perception of risk: three simulation experiments. Risk Anal 13:585–98 [Google Scholar]
  104. Sandman PM, Weinstein ND, Miller P. 1994. High risk or low: how location on a “risk ladder” affects perceived risk. Risk Anal 14:35–45 [Google Scholar]
  105. Savage LJ. 1951. The Theory of Statistical Decision. J. Am. Stat. Assoc. 46:55–67 [Google Scholar]
  106. Savage LJ. 1972. The Foundations of Statistics New York: Dover [Google Scholar]
  107. Scheer D, Benighaus C, Benighaus L, Renn O, Gold S. et al. 2014. The distinction between risk and hazard: understanding and use in stakeholder communication. Risk Anal 34:1270–85 [Google Scholar]
  108. Schwartz LM, Woloshin S. 2013. The drug facts box: improving the communication of prescription drug information. PNAS 110:14069–74 [Google Scholar]
  109. Sirota M, Juanchich M, Kostopoulou O, Hanak R. 2014. Decisive evidence on a smaller-than-you-think phenomenon: revisiting the “1-in-x” effect on subjective medical probabilities. Med. Decis. Mak 34419–29 [Google Scholar]
  110. Skarlatidou A, Cheng T, Haklay M. 2012. What do lay people want to know about the disposal of nuclear waste? A mental model approach to the design and development of an online risk communication. Risk Anal 32:1496–511 [Google Scholar]
  111. Slovic P. 1987. Perception of risk. Science 236:280–85 [Google Scholar]
  112. Slovic P. 2000. The Perception of Risk England: Earthscan [Google Scholar]
  113. Slovic P, Peters E. 2006. Risk perception and affect. Curr. Dir. Psychol. Sci. 15:322–25 [Google Scholar]
  114. Society of Thoracic Surgeons 2015. Adult cardiac surgery database executive summary. Chicago: Soc. Thorac. Surg http://www.sts.org/sites/default/files/documents/2015Harvest4_ExecutiveSummary.pdf
  115. Sorensen L, Gyrd-Hansen D, Kristiansen IS, Nexøe J, Nielsen JB. 2008. Laypersons’ understanding of relative risk reductions: Randomised cross-sectional study. BMC Med. Inform. Decis. Mak 831 [Google Scholar]
  116. Spiegelhalter DJ. 2002. Mortality and volume of cases in paediatric cardiac surgery: retrospective study based on routinely collected data. BMJ 324:261–61 [Google Scholar]
  117. Spiegelhalter DJ. 2012. Using speed of ageing and “microlives” to communicate the effects of lifetime habits and environment. BMJ 345:e8223 [Google Scholar]
  118. Spiegelhalter DJ. 2014. The power of the MicroMort. BJOG Int. J. Obstet. Gynaecol. 121:662–63 [Google Scholar]
  119. Spiegelhalter DJ, Pearson M, Short I. 2011. Visualizing uncertainty about the future. Science 333:1393–400 [Google Scholar]
  120. Spiegelhalter DJ, Riesch H. 2011. Don't know, can't know: embracing deeper uncertainties when analysing risks. Philos. Trans. R. Soc. A 369:4730–50 [Google Scholar]
  121. Stephens EM, Edwards TL, Demeritt D. 2012. Communicating probabilistic information from climate model ensembles—lessons from numerical weather prediction. Wiley Interdiscip. Rev. Clim. Change 3:409–26 [Google Scholar]
  122. Stirling A. 2007. Risk, precaution and science: towards a more constructive policy debate. Talking point on the precautionary principle. EMBO Rep 8:309–15 [Google Scholar]
  123. Stone ER, Sieck WR, Bull BE, Yates JF, Parks SC, Rush CJ. 2003. Foreground:background salience: explaining the effects of graphical displays on risk avoidance. Organ. Behav. Hum. Decis. Process. 90:19–36 [Google Scholar]
  124. Tait AR, Voepel-Lewis T, Zikmund-Fisher BJ, Fagerlin A. 2010. Presenting research risks and benefits to parents: Does format matter?. Anesth. Analg. 111:718–23 [Google Scholar]
  125. Taleb N. 2007. The Black Swan: the Impact of the Highly Improbable New York: Random House, 1st ed.. [Google Scholar]
  126. Trevena LJ, Barratt A, Butow P, Caldwell P. 2006. A systematic review on communicating with patients about evidence. J. Eval. Clin. Pract. 12:13–23 [Google Scholar]
  127. Trevena LJ, Zikmund-Fisher BJ, Edwards A, Gaissmaier W, Galesic M. et al. 2013. Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers. BMC Med. Inform. Decis. Mak 13Suppl 2S7 [Google Scholar]
  128. UK Cabinet Off. 2010. Fact Sheet2: National Security Risk Assessment London: Cabinet Off https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/62484/Factsheet2-National-Security-Risk-Assessment.pdf [Google Scholar]
  129. UK Cabinet Off. 2011. Communicating Risk Guidance London: Cabinet Off https://www.gov.uk/government/publications/communicating-risk-guidance [Google Scholar]
  130. UK Cabinet Off. 2012. National Risk Register for Civil Emergencies—2012 Update London: Cabinet Off https://www.gov.uk/government/publications/national-risk-register-for-civil-emergencies-2012-update [Google Scholar]
  131. UK Cabinet Off. 2015. National Risk Register for Civil Emergencies—2015 Edition London: Cabinet Off https://www.gov.uk/government/publications/national-risk-register-for-civil-emergencies-2015-edition [Google Scholar]
  132. van der Linden S. 2016. A conceptual critique of the cultural cognition thesis. Sci. Commun. 38:128–38 [Google Scholar]
  133. van Dyk DA. 2014. The role of statistics in the discovery of a Higgs boson. Annu. Rev. Stat. Appl. 1:41–59 [Google Scholar]
  134. Visschers VHM, Meertens RM, Passchier WWF, de Vries NNK. 2009. Probability information in risk communication: a review of the research literature. Risk Anal 29:267–87 [Google Scholar]
  135. WHO (World Health Organ.) 2016. WHO global urban ambient air pollution database World Health Organ., updated 2016, retrieved May 24, 2016. http://www.who.int/phe/health_topics/outdoorair/databases/cities/en/ [Google Scholar]
  136. Woo G, Marzocchi W. 2014. Operational earthquake forecasting and decision-making. Early Warning for Geological Disasters F Wenzel, J Zschau 353–67 Berlin: Springer [Google Scholar]
  137. World Econ. Forum. 2016. The Global Risks Report 2016, 11th Edition Geneva: World Econ. Forum https://www.weforum.org/reports/the-global-risks-report-2016/ [Google Scholar]
  138. Wynne B. 1991. Knowledges in Context. Sci. Technol. Hum. 16:111–21 [Google Scholar]
  139. Yamagishi K. 1997. When a 12.86% mortality is more dangerous than 24.14%: implications for risk communication. Appl. Cogn. Psychol. 11:495–506 [Google Scholar]
  140. Zikmund-Fisher BJ. 2014. Continued use of 1-in-x risk communications is a systemic problem. Med. Decis. Making 34412–13 [Google Scholar]
  141. Zikmund-Fisher BJ, Dickson M, Witteman HO. 2011. Cool but counterproductive: interactive, web-based risk communications can backfire. J. Med. Internet Res 13e60 [Google Scholar]
  142. Zikmund-Fisher BJ, Fagerlin A, Ubel PA. 2010. A demonstration of “‘less can be more’” in risk graphics. Med. Decis. Mak 30661–71 [Google Scholar]
  143. Zikmund-Fisher BJ, Ubel PA, Smith DM, Derry HA, McClure JB. et al. 2008. Communicating side effect risks in a tamoxifen prophylaxis decision aid: the debiasing influence of pictographs. Patient Educ. Couns. 73:209–14 [Google Scholar]
  144. Zikmund-Fisher BJ, Witteman HO, Fuhrel-Forbis A, Exe NL, Kahn VC, Dickson M. 2012. Animated graphics for comparing two risks: a cautionary tale. J. Med. Internet Res 14e106 [Google Scholar]
  145. Zipkin DA, Umscheid CA, Keating NL, Allen E, Aung K. et al. 2014. Evidence-based risk communication: a systematic review. Ann. Intern. Med. 161:270–80 [Google Scholar]
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