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Risk Communication in Health

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Book cover Handbook of Risk Theory

Abstract

Policy makers, health professionals, and patients have to understand health statistics to make informed medical decisions. However, health messages often follow a persuasive rather than an informative approach and undermine the idea of informed decision making. The current practice of health risk communication is often biased: Risks are communicated one sided and in nontransparent formats. Thereby, patients are misinformed and misled. Despite the fact that the public is often described as lacking basic statistical literacy skills, statistics can be presented in a way that facilitates understanding. In this chapter, we discuss how transparent risk communication can contribute to informed patients and how transparency can be achieved. Transparency requires formats that are easy to understand and present the facts objectively. For instance, using statistical evidence instead of narrative evidence helps patients to better assess and evaluate risks. Similarly, verbal probability estimates (e.g., “probable,” “rare”) usually result in incorrect interpretations of the underlying risk in contrast to numerical probability estimates (e.g., “20%,” “0.1”). Furthermore, we will explain and discuss four formats – relative risks, conditional probabilities, 5-year survival rates, and single-event probabilities – that often confuse people, and propose alternative formats – absolute risks, natural frequencies, annual mortality rates, and frequency statements – that increase transparency. Although research about graphs is still in its infancy, we discuss graphical visualizations as a promising tool to overcome low statistical literacy. A further challenge in risk communication is the communication of uncertainty. Evidence about medical treatments is often limited and conflicting, and the question arises how health professionals and laypeople deal with uncertainty. Finally, we propose further research to implement the concepts of transparency in risk communication.

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References

  • Allen M, Preiss R (1997) Comparing the persuasiveness of narrative and statistical evidence using meta-analysis. Commun Res Rep 14:125–131

    Article  Google Scholar 

  • Ancker JS, Kaufman D (2007) Rethinking health numeracy: a multidisciplinary literature review. J Am Med Inform Assoc 14:713–721

    Article  Google Scholar 

  • 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 3:608–618

    Article  Google Scholar 

  • Baesler JE (1997) Persuasive effects of story and statistical evidence. Argument Advocacy 33:170–175

    Google Scholar 

  • Baesler JE, Burgoon JK (1994) The temporal effects of story and statistical evidence on belief change. Commun Res 21:582–602

    Article  Google Scholar 

  • Barbey AK, Sloman SA (2007) Base-rate respect: from ecological rationality to dual processes. Behav Brain Sci 30:241–297

    Google Scholar 

  • Barton A, Mousavi S, Stevens JR (2007) A statistical taxonomy and another “chance” for natural frequencies. Behav Brain Sci 30:255–256

    Article  Google Scholar 

  • Berry D, Raynor T, Knapp P, Bersellini E (2004) Over the counter medicines and the need for immediate action: a further evaluation of European commission recommended wordings for communicating risk. Patient Educ Couns 53:129–134

    Article  Google Scholar 

  • Betsch C, Renkewitz F, Betsch T, Ulshöfer C (2010) The influence of vaccine-critical Internet pages on perception of vaccination risks. J Health Psychol 15:446–455

    Article  Google Scholar 

  • Bodemer N, Müller SM, Okan Y, Garcia-Retamero R, Neumeyer-Gromen A (2011) Do the media provide transparent health information? A cross-cultural comparison of public information about the HPV vaccine (Submitted)

    Google Scholar 

  • Brase GL (2009) Pictorial representations in statistical reasoning. Appl Cogn Psychol 23:369–381

    Article  Google Scholar 

  • Brun W, Teigen KH (1988) Verbal probabilities: ambiguous, context-dependent, or both? Organ Behav Hum Decis Process 41:390–404

    Article  Google Scholar 

  • Bucher HC, Weinbacher M, Gyr K (1994) Influence of method of reporting study results on decision of physicians to prescribe drugs to lower cholesterol concentration. Br Med J 309:761–764

    Article  Google Scholar 

  • Budescu DV, Wallsten TS (1985) Consistency in interpretation of probabilistic phrases. Organ Behav Hum Decis Process 36:391–405

    Article  Google Scholar 

  • Casscells W, Schoenberger A, Grayboys T (1978) Interpretation by physicians of clinical laboratory results. N Engl J Med 299:999–1000

    Article  Google Scholar 

  • Consort (2009) Consolidated standards of reporting trials. www.consort-statement.org. Accessed April 2011

  • Cosmides L, Tooby J (1996) Are humans good intuitive statisticians after all? Rethinking some conclusions of the literature on judgment under uncertainty. Cognition 58:1–73

    Google Scholar 

  • Covey J (2007) A meta-analysis of the effects of presenting treatment benefits in different formats. Med Decis Making 27:638–654

    Article  Google Scholar 

  • Davids SL, Schapira MM, McAuliffe TL, Nattinger AB (2004) Predictors of pessimistic breast cancer risk perception in a primary care population. J Gen Intern Med 19:310–315

    Article  Google Scholar 

  • deWit JBF, Das E, Vet R (2008) What works best: objective statistics or a personal testimonial? An assessment of the persuasive effects of different types of message evidence on risk perception. Health Psychol 27:110–115

    Article  Google Scholar 

  • Diaz JA, Griffith RA, Ng JJ, Reinert SE, Friedmann PD, Moulton AW (2002) Patients’ use of the Internet for medical information. J Gen Intern Med 17:180–185

    Article  Google Scholar 

  • Dieckmann NF, Slovic P, Peters E (2009) The use of narrative evidence and explicit likelihood by decisionmakers varying in numeracy. Risk Anal 29:1473–1488

    Article  Google Scholar 

  • Djulbegovic M, Beyth RJ, Neuberger MM, Stoffs TL, Vieweg J, Djulbegovic B et al (2010) Screening for prostate cancer: systematic review and meta-analysis of randomised controlled trials. Br Med J 341:c4543

    Article  Google Scholar 

  • Dören M, Gerhardus A, Gerlach FM, Hornberg C, Kochen MM, Kolip P et al. (2008) Wissenschaftler/innen fordern Neubewertung der HPV-Impfung und ein Ende der irreführenden Informationen. http://www.uni-bielefeld.de/gesundhw/ag3/downloads/Stellungnahme_Wirksamkeit_HPV-Impfung.pdf. Accessed April 2011

  • Durand M-A, Stiel M, Boivin J, Elwyn G (2008) Where is the theory? Evaluating the theoretical frameworks described in decision support technologies. Patient Educ Couns 71:125–135

    Article  Google Scholar 

  • Eddy DM (1982) Probabilistic reasoning in clinical medicine: problems and opportunities. In: Kahneman D, Slovic P, Tversky A (eds) Judgment under uncertainty: heuristics and biases. Cambridge University Press, Cambridge, pp 246–267

    Google Scholar 

  • Edwards A, Elwyn G (2009) Shared decision making in health care: achieving evidence-based patient choice. Oxford University Press, Oxford

    Google Scholar 

  • Edwards A, Elwyn G, Covey J, Matthews E, Pill R (2001) Presenting risk information – A review of the effects of “framing” and other manipulations on patient outcomes. J Health Commun 6:61–82

    Article  Google Scholar 

  • Einhorn HJ, Hogarth RM (1985) Ambiguity and uncertainty in probabilistic inference. Psychol Rev 92:433–461

    Article  Google Scholar 

  • Epstein LG (1999) A definition of uncertainty aversion. Rev Econ Stud 66:579–608

    Article  Google Scholar 

  • Erev I, Cohen BL (1990) Verbal versus numerical probabilities: efficiency, biases, and the preference paradox. Organ Behav Hum Decis Process 45:1–18

    Article  Google Scholar 

  • Estrada CA, Martin-Hryniewicz M, Peek BT, Collins C, Byrd JC (2004) Literacy and numeracy skills and anticoagulation control. Am J Med Sci 328:88–93

    Article  Google Scholar 

  • European Commission (1998) A guideline on the readability of the label and package leaflet of medicinal products for human use. EC Pharmaceuticals Committee, Brussels

    Google Scholar 

  • 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 Making 25:398–405

    Article  Google Scholar 

  • Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM (2007) Measuring numeracy without a math test: development of the subjective numeracy scale. Med Decis Making 27:672–680

    Article  Google Scholar 

  • Feufel M, Antes G, Gigerenzer G (2010) Competence in dealing with uncertainty lessons to learn from the influenza pandemic (H1N1) 2009. Bundesgesundheitsblatt 53:1283–1289

    Article  Google Scholar 

  • Frewer LJ (1999) Risk perception, social trust, and public participation in strategic decision making: implications for emerging technologies. Ambio 28:569–574

    Google Scholar 

  • Frewer LJ, Hunt S, Brennan M, Kuznesof S, Ness M, Ritson C (2003) The views of scientific experts on how the public conceptualize uncertainty. J Risk Res 6:75–85

    Article  Google Scholar 

  • Frosch DL, Krueger PM, Hornik RC, Cronholm PF, Barg FK (2007) Creating demand for prescription drugs: a content analysis of television direct-to-consumer advertising. Ann Fam Med 5:6–13

    Article  Google Scholar 

  • Gaissmaier W, Straubinger N, Funder DC (2007) Ecologically structured information: the power of pictures and other effective data presentations. Behav Brain Sci 30:263–264

    Article  Google Scholar 

  • Gal I (1995) Big picture: what does “numeracy” mean? http://mathforum.org/teachers/adult.ed/articles/gal.html. Accessed April 2011

  • Galesic M, Garcia-Retamero R (2010) Statistical numeracy for health: a cross-cultural comparison with probabilistic national samples. Arch Intern Med 170:462–468

    Article  Google Scholar 

  • Galesic M, Garcia-Retamero R (2011) Graph literacy: a cross-cultural comparison. Med Decis Making 31:444–457

    Article  Google Scholar 

  • Galesic M, Garcia-Retamero R, Gigerenzer G (2009) Using icon arrays to communicate medical risks: overcoming low numeracy. Health Psychol 28:210–216

    Article  Google Scholar 

  • Garcia-Retamero R, Galesic M (2009) Communicating treatment risk reduction to people with low numeracy skills: a cross-cultural comparison. Am J Public Health 99:2196–2202

    Article  Google Scholar 

  • Garcia-Retamero R, Galesic M (2010) Who profits from visual aids: overcoming challenges in people’s understanding of risks. Soc Sci Med 70:1019–1025

    Article  Google Scholar 

  • Garcia-Retamero R, Galesic M, Gigerenzer G (2010) Do icon arrays help reduce denominator neglect? Med Decis Making 30:672–684

    Article  Google Scholar 

  • Gigerenzer G (2002) Calculated risks: how to know when numbers deceive you. Simon & Schuster, New York

    Google Scholar 

  • Gigerenzer G (2007) Gut feeling: the intelligence of the unconscious. Viking, New York

    Google Scholar 

  • Gigerenzer G, Gray M (2011) Launching the century of the patient. In: Gigerenzer G, Gray M (eds) Better doctors, better patients, better decisions: envisioning health care 2020. MIT Press, Cambridge, pp 3–28

    Google Scholar 

  • Gigerenzer G, Hoffrage U (1995) How to improve Bayesian reasoning without instruction: frequency formats. Psychol Rev 102:684–704

    Article  Google Scholar 

  • Gigerenzer G, Hoffrage U, Ebert A (1998) AIDS counselling for low-risk clients. AIDS Care 10:197–211

    Article  Google Scholar 

  • 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 25:623–629

    Article  Google Scholar 

  • Gigerenzer G, Gaissmaier W, Kurz-Milcke E, Schwartz LM, Woloshin S (2007) Helping doctors and patients to make sense of health statistics. Psychol Sci Public Interest 8:53–96

    Google Scholar 

  • Gigerenzer G, Mata J, Frank R (2009) Public knowledge of benefits of breast and prostate cancer screening in Europe. J Natl Cancer Inst 101:1216–1220

    Article  Google Scholar 

  • Gigerenzer G, Wegwarth O, Feufel M (2010) Misleading communication of risk: editors should enforce transparent reporting in abstracts. Br Med J 341:c4830

    Article  Google Scholar 

  • Golbeck AL, Ahlers-Schmidt CR, Paschal AM, Dismuke S (2005) A definition and operational framework for health numeracy. Am J Prev Med 29:375–376

    Article  Google Scholar 

  • Grigg W, Donahue P, Dion G (2007) The nation’s report card:12th-grade reading and mathematics 2005 (NCES Report No. 2007–468). U.S. Department of Education, National Center for Education Statistics, Washington, DC

    Google Scholar 

  • Grilli R, Ramsey C, Minozzi S (2009) Mass media interventions: effects on health care utilization. Cochrane Database Syst Rev 1:CD000389

    Google Scholar 

  • Gurmankin AD, Baron J, Armstrong K (2004) The effect of numerical statements of risk on trust and comfort with hypothetical physician risk communication. Med Decis Making 24:265–271

    Article  Google Scholar 

  • Hacking I (1975) The emergence of probability. Cambridge University Press, Cambridge

    Google Scholar 

  • Hargittai E (2005) Survey measures of web-oriented digital literacy. Soc Sci Comput Rev 23:371–379

    Article  Google Scholar 

  • Hargittai E (2009) An update on survey measures of web-oriented digital literacy. Soc Sci Comput Rev 27:130–137

    Article  Google Scholar 

  • Hargittai E, Fullerton F, Menchen-Trevino E, Thomas K (2010) Trust online: young adults’ evaluation of web content. Int J Commun 4:468–494

    Google Scholar 

  • Heesen C, Köpke S, Kasper J, Richter T, Beier M, Mühlhauser I (2008) Immuntherapien der Multiplen Sklerose. http://www.zmnh.uni-hamburg.de/martin/dl/pinfo/immuntherapien_ms_inims_hamburg.pdf. Accessed April 2011

  • Heesen C, Kleiter I, Nguyen F, Schäffler N, Kasper J, Köpke S et al (2010) Risk perceptions in natalizumab-treated multiple sclerosis patients and their neurologists. Mult Scler 16:1507–1512

    Article  Google Scholar 

  • Hembroff LA, Holmes-Rovner M, Wills CE (2004) Treatment decision-making and the form of risk communication: results of a factorial survey. BMC Med Inform Decis Mak 4:1184–1120

    Article  Google Scholar 

  • Hoffrage U, Gigerenzer G, Krauss S, Martignon L (2002) Representation facilitates reasoning: what natural frequencies are and what they are not. Cognition 84:343–352

    Article  Google Scholar 

  • Holmes BJ, Henrich N, Hancock S, Lestou V (2009) Communicating with the public during health crises: experts’ experiences and opinions. J Risk Res 12:793–807

    Article  Google Scholar 

  • Ibrekk H, Morgan MG (1987) Graphical communication of uncertain quantities to nontechnical people. Risk Anal 7:519–529

    Article  Google Scholar 

  • Johnson BB, Slovic P (1995) Presenting uncertainty in health risk assessment: initial studies of its effects on risk perception and trust. Risk Anal 15:485–494

    Article  Google Scholar 

  • Kahneman D, Tversky A (1972) Subjective probability: a judgment of representativeness. Cognit Psychol 3:430–454

    Article  Google Scholar 

  • Kirsch IS, Jungeblut A, Jenkins L, Kolstad A (2007) Adult literacy in America: a first look at the findings of the National Adult Literacy Survey (NCES Report No. 1993–275; 3rd edn, U.S. Department of Education, National Center for Education Statistics. Washington, DC

    Google Scholar 

  • Knapp P, Raynor DK, Berry DC (2004) Comparison of two methods of presenting risk information to patients about the side effects of medicines. Qual Saf Health Care 13:176–180

    Article  Google Scholar 

  • Knight FH (1921) Risk, uncertainty and profit. Harper, New York

    Google Scholar 

  • Kotler P, Lee NR (2007) Social marketing: influencing behaviors for good. Sage, London

    Google Scholar 

  • Kuhn KM (2000) Message format and audience values: interactive effects of uncertainty information and environmental attitudes on perceived risk. J Environ Psychol 20:41–51

    Article  Google Scholar 

  • Kurzenhäuser S (2003) Welche Informationen vermitteln deutsche Gesundheitsbroschüren über die Screening-Mammographie? Z Arztl Fortbild Qualitatssich 97:53–57

    Google Scholar 

  • Kurz-Milcke E, Martignon L (2007) Stochastische Urnen und Modelle in der Grundschule (Stochastic urns and models in elementary school). In: Kaiser G (ed) Tagungsband der Jahrestagung der Gesellschaft für Didaktik der Mathematik. Verlag Franzbecker, Berlin

    Google Scholar 

  • Kurz-Milcke E, Gigerenzer G, Martignon L (2008) Transparency in risk communication: graphical and analog tools. In: Tucker WT, Ferson S, Finkel A, Long TF, Slavin D, Wright P (eds) Strategies for risk communication: evolution, evidence, experience, vol 1128, Annals of the New York Academy of Sciences. Blackwell, New York, pp 18–28

    Google Scholar 

  • Kutner M, Greenberg E, Jin Y, Paulsen C (2006) The health literacy of America’s adults: results from the 2003 national assessment of adult literacy (NCES Report No. 2006–483). Government Printing Office, Washington, DC

    Google Scholar 

  • Lafata JE, Simpkins J, Lamerato L, Poisson L, Divine G, Johnson CC (2004) The economic impact of false-positive cancer screens. Cancer Epidemiol Biomarkers Prev 13:2126–2132

    Google Scholar 

  • Lewis C, Keren G (1999) On the difficulties underlying Bayesian reasoning: comment on Gigerenzer and Hoffrage. Psychol Rev 106:411–416

    Article  Google Scholar 

  • Lipkus IM (2007) Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations. Med Decis Making 27:696–713

    Article  Google Scholar 

  • Lipkus IM, Hollands JG (1999) The visual communication of risks. J Natl Cancer Inst Monogr 25:149–162

    Google Scholar 

  • Lipkus IM, Peters E (2009) Understanding the role of numeracy in health: proposed theoretical framework and practical insight. Health Educ Behav 36:1065–1081

    Article  Google Scholar 

  • Lipkus IM, Samsa G, Rimer BK (2001) General performance on a numeracy scale among highly educated samples. Med Decis Making 21:37–44

    Article  Google Scholar 

  • Macchi L, Mosconi G (1998) Computational features vs frequentist phrasing in the base-rate fallacy. Swiss J Psychol 57:79–85

    Google Scholar 

  • Malenka DJ, Baron JA, Johansen S, Wahrenberger JW, Ross JM (1993) The framing effect of relative versus absolute risk. J Gen Intern Med 8:543–548

    Article  Google Scholar 

  • Marcus PM, Bergstrahl EJ, Zweig MH, Harris A, Offord KP, Fontana RS (2006) Extended lung cancer incidence follow-up in the Mayo lung project and overdiagnosis. J Natl Cancer Inst 98:748–756

    Article  Google Scholar 

  • Marteau TM, Saidi G, Goodburn S, Lawton J, Michie S, Bobrow M (2000) Numbers or words? A randomized controlled trial of presenting screen negative results to pregnant women. Prenat Diagn 20:714–718

    Article  Google Scholar 

  • Mathematics and medicine (1937, January 2). Lancet i:31

    Google Scholar 

  • Mazur DJ, Hickham DH, Mazur MD (1999) How patients’ preferences for risk communication influence treatment choice in a case of high risk and high therapeutic uncertainty: asymptotic localized prostate cancer. Med Decis Making 19:394–398

    Article  Google Scholar 

  • McMullan M (2006) Patients using the Internet to obtain health information: how this affects the patient–health professional relationship. Patient Educ Couns 63:24–28

    Article  Google Scholar 

  • Moxey A, O’Connell D, McGettigan P, Henry D (2003) Describing treatment effects to patients: how they are expressed makes a difference. J Gen Intern Med 18:948–959

    Article  Google Scholar 

  • Moynihan R, Bero L, Ross-Degnan D, Henry D, Lee K, Watkins J et al (2000) Coverage by the news media of the benefits and risks of medications. New Engl J Med 342:1645–1650

    Article  Google Scholar 

  • Mühlhauser I, Kasper J, Meyer G (2006) FEND: understanding of diabetes prevention studies: questionnaire survey of professionals in diabetes care. Diabetologia 49:1742–1746

    Article  Google Scholar 

  • Nadav-Greenberg L, Joslyn S (2009) Uncertainty forecasts improve decision making among nonexperts. J Cogn Eng Decis Making 3:209–227

    Article  Google Scholar 

  • Naylor CD, Chen E, Strauss B (1992) Measured enthusiasm: does the method of reporting trial results alter perceptions of therapeutic effectiveness? Ann Intern Med 171:916–921

    Google Scholar 

  • Neumeyer-Gromen A, Bodemer N, Müller SM, Gigerenzer G (in press) Ermöglichen Medienberichte und Informationsbroschüren zur Gebärmutterhalskrebsprävention informierte Entscheidungen? Eine Medienanalyse in Deutschland (Submitted)

    Google Scholar 

  • Nielsen Company (2009) U.S. ad spending fell 2.6% in 2008, Nielson reports. Nielson Company, New York

    Google Scholar 

  • Nisbett RE, Ross LD (1980) Human inference: strategies and shortcomings of social judgment. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Paulos JA (1988) Innumeracy: mathematical illiteracy and its consequences. Hill & Wang, New York

    Google Scholar 

  • Pepper S, Prytulak LS (1974) Sometimes frequently means seldom: context effects in the interpretation of quantitative expressions. J Res Pers 8:95–101

    Article  Google Scholar 

  • Peters E, Västfjäll D, Slovic P, Mertz CK, Mazzocco K, Dickert S (2006) Numeracy and decision making. Psychol Sci Public Interest 17:407–413

    Google Scholar 

  • Politi MC, Han PKJ, Col NF (2007) Communicating the uncertainty of harms and benefits of medical interventions. Med Decis Making 27:681–695

    Article  Google Scholar 

  • Politi MC, Clark MA, Ombao H, Dizon D, Elwyn G (2010) Communicating uncertainty can lead to less decision satisfaction: a necessary cost of involving patients in shared decision making? Health Expect 14:1–8

    Google Scholar 

  • Reinard JC (1988) The empirical study of the persuasive effects of evidence: the status after fifty years of research. Hum Commun Res 15:3–59

    Article  Google Scholar 

  • Reyna V, Nelson WL, Han PK, Dieckmann NF (2009) How numeracy influences risk comprehension and medical decision making. Psychol Bull 135:943–973

    Article  Google Scholar 

  • Rothman RL, Housam R, Weiss H, Davis D, Gregory R, Gebretsadik T, Shintani A, Elasy TA (2006) Patient understanding of food labels: the role of literacy and numeracy. Am J Prev Med 31:391–398

    Article  Google Scholar 

  • Sandblom G, Varenhorst E, Rosell J, Löfman O, Carlsson P (2011) Randomised prostate cancer screening trial: 20 year follow-up. Br Med J 342:d1539

    Article  Google Scholar 

  • Sarfati D, Howden-Chapman P, Woodward A, Salmond C (1998) Does the frame affect the picture? A study into how attitudes to screening for cancer are affected by the way benefits are expressed. J Med Screen 5:137–140

    Google Scholar 

  • Schapira MM, Nattinger AB, McHorney CA (2001) Frequency or probability? A qualitative study of risk communication formats used in health care. Med Decis Making 21:459–467

    Google Scholar 

  • Schröder FH, Hugosson J, Roobol MJ et al (2009) Screening and prostate-cancer mortality in a randomized European study. N Engl J Med 360:1320–1328

    Article  Google Scholar 

  • Schwartz LM, Woloshin S, Black WC, Welch HG (1997) The role of numeracy in understanding the benefit of screening mammography. Ann Intern Med 127:966–972

    Google Scholar 

  • Schwartz LM, Woloshin S, Dvorin EL, Welch HG (2006) Ratio measures in leading medical journals: structured review of accessibility of underlying absolute risks. Br Med J 333:1248–1252

    Article  Google Scholar 

  • Schwartz LM, Woloshin S, Welch HG (2007) Using a drug facts box to communicate drug benefits and harms. Ann Intern Med 150:516–527

    Google Scholar 

  • Sedrakyan A, Shih C (2007) Improving depiction of benefits and harms: analyses of studies of well-known therapeutics and review of high-impact medical journals. Med Care 45:523–528

    Article  Google Scholar 

  • Shaw NJ, Dear PRF (1990) How do parents of babies interpret qualitative expressions of probability. Arch Dis Child 65:520–523

    Article  Google Scholar 

  • Sheridan S, Pignone MP, Lewis CL (2003) A randomized comparison of patients’ understanding of number needed to treat and other common risk reduction formats. J Gen Intern Med 18:884–892

    Article  Google Scholar 

  • Smeeth L, Haines A, Ebrahim S (1999) Numbers needed to treat derived from meta-analyses – sometimes informative, usually misleading. Br Med J 318:1548–1551

    Article  Google Scholar 

  • Steckelberg A, Balgenorth A, Mühlhauser I (2001) Analyse von deutschsprachigen Verbraucher-Informationsbroschüren zum Screening auf kolorektales Karzinom. Z Arztl Fortbild Qualitatssich 95:535–538

    Google Scholar 

  • Steckelberg A, Berger B, Köpke S, Heesen C, Mühlhauser I (2005) Criteria for evidence-based patient information. Z Arztl Fortbild Qualitatssich 99:343–351

    Google Scholar 

  • Steurer J, Held U, Schmidt M, Gigerenzer G, Tag B, Bachmann L (2009) Legal concerns trigger prostate-specific antigen testing. J Eval Clin Pract 15:390–392

    Article  Google Scholar 

  • Stone ER, Yates JF, Parker AM (1997) Effects of numerical and graphical displays on professed risk-taking behavior. J Exp Psychol Appl 3:243–256

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Strobe-Statement (2007) Strengthening the reporting of observational studies in epidemiology. http://www.strobe-statement.org/. Accessed April 2011

  • Taylor SE, Thompson SC (1982) Stalking the elusive “vividness” effect. Psychol Rev 89:155–181

    Article  Google Scholar 

  • Thompson KM (2002) Variability and uncertainty meet risk management and risk communication. Risk Anal 22:647–654

    Article  Google Scholar 

  • Ubel PA, Jepson C, Baron J (2001) The inclusion of patient testimonials in decision aids: effects on treatment choices. Med Decis Making 21:60–68

    Article  Google Scholar 

  • van Dijk H, Houghton J, van Kleef E, van der Lans I, Rowe G, Frewer LJ (2008) Consumer responses to communication about food risk management. Appetite 50:340–352

    Article  Google Scholar 

  • Viscusi WK, Magat WA, Huber J (1991) Communication of ambiguous risk information. Theory Decis 31:159–173

    Article  Google Scholar 

  • Wager E, Mhaskar R, Warburton S, Djulbegovic B (2010) JAMA published fewer industry-funded studies after introducing a requirement for independent statistical analysis. PLoS One 5:e13591

    Article  Google Scholar 

  • Wainer H (1984) How to display data badly. Am Stat 38:137–147

    Article  Google Scholar 

  • Wallsten TS, Fillenbaum S, Cox JA (1986) Base rate effects on the interpretation of probability and frequency expressions. J Mem Lang 25:571–587

    Article  Google Scholar 

  • Wallsten TS, Budescu DV, Zwick R, Kemp SM (1993) Preferences and reasons for communicating probabilistic information in verbal or numerical terms. Bull Psychon Soc 31:135–138

    Google Scholar 

  • Weber EU, Hilton DJ (1990) Contextual effects in the interpretations of probability words: perceived base rate and severity of events. J Exp Psychol Hum Percept Perform 16:781–789

    Article  Google Scholar 

  • Wegwarth O, Gaissmaier W, Gigerenzer G (2011) Deceiving and informing: the risky business of risk perception. Med Decis Making 31:378–379

    Article  Google Scholar 

  • Weinfurt KP, Seils DM, Tzeng JP, Lin L, Schulman KA, Califf RM (2008) Consistency of financial interest disclosures in the biomedical literature: the case of coronary stents. PLoS One 3:e2128

    Article  Google Scholar 

  • Welch HG, Schwartz LM, Woloshin S (2000) Are increasing 5-year survival rates evidence of success against cancer? J Am Med Assoc 283:2975–2978

    Article  Google Scholar 

  • Wilde J (2009) PSA screening cuts deaths by 20%, says world’s largest prostate cancer study. ERSPC press office, carver wilde communications. http://www.erspc-media.org/release090318.php. Accessed April 2011

  • Witte K, Allen M (2000) A meta-analysis of fear appeals: implications for effective public health campaigns. Health Educ Behav 27:591–615

    Article  Google Scholar 

  • Woloshin S, Schwartz LM, Black WC, Welch HG (1999) Women’s perceptions of breast cancer risk: how you ask matters. Med Decis Making 19:221–229

    Article  Google Scholar 

  • Zhu L, Gigerenzer G (2006) Children can solve Bayesian problems: the role of representation in mental computation. Cognition 98:287–308

    Article  Google Scholar 

  • Zikmund-Fisher BJ, Smith DM, Ubel PA, Fagerlin A (2007) Validation of the subjective numeracy scale (SNS): effects of low numeracy on comprehension of risk communications and utility elicitations. Med Decis Making 27:663–671

    Article  Google Scholar 

  • Zikmund-Fisher BJ, Fagerlin A, Ubel PAU (2008a) Improving understanding of adjuvant therapy options by using simpler risk graphics. Cancer 113:3382–3390

    Article  Google Scholar 

  • Zikmund-Fisher BJ, Ubel PA, Smith DM, Derry HA, McClure JB, Stark AT et al (2008b) Communicating side effect risks in a tamoxifen prophylaxis decision aid: the debiasing influence of pictographs. Patient Educ Couns 73:209–214

    Article  Google Scholar 

  • Zimmer AC (1983) Verbal vs. numerical processing of subjective probabilities. In: Scholz RW (ed) Decision making under uncertainty. Elsevier, Amsterdam, pp 159–182

    Google Scholar 

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Authors and Affiliations

  1. Harding Center for Risk Literacy, Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany

    Nicolai Bodemer & Dr. Wolfgang Gaissmaier

Authors
  1. Nicolai Bodemer
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  2. Dr. Wolfgang Gaissmaier
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Corresponding author

Correspondence to Nicolai Bodemer .

Editor information

Editors and Affiliations

  1. Philosophy Department Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands

    Sabine Roeser

  2. Philosophy Department, University of Twente, Enschede, The Netherlands

    Sabine Roeser

  3. Human Technology Center, RWTH Aachen University, Aachen, Germany

    Rafaela Hillerbrand

  4. Department of Plant Physiology and Forest Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden

    Per Sandin

  5. Section for Philosophy and Ethics, Eindhoven University of Technology, Eindhoven, The Netherlands

    Martin Peterson

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© 2012 Springer Science+Business Media B.V.

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Bodemer, N., Gaissmaier, W. (2012). Risk Communication in Health. In: Roeser, S., Hillerbrand, R., Sandin, P., Peterson, M. (eds) Handbook of Risk Theory. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1433-5_24

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  • DOI: https://doi.org/10.1007/978-94-007-1433-5_24

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-1432-8

  • Online ISBN: 978-94-007-1433-5

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