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Communicating risk

from Psychology, health and illness

Published online by Cambridge University Press:  18 December 2014

David P. French
Affiliation:
University of Birmingham
Theresa M. Marteau
Affiliation:
King's College London
Susan Ayers
Affiliation:
University of Sussex
Andrew Baum
Affiliation:
University of Pittsburgh
Chris McManus
Affiliation:
St Mary's Hospital Medical School
Stanton Newman
Affiliation:
University College and Middlesex School of Medicine
Kenneth Wallston
Affiliation:
Vanderbilt University School of Nursing
John Weinman
Affiliation:
United Medical and Dental Schools of Guy's and St Thomas's
Robert West
Affiliation:
St George's Hospital Medical School, University of London
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Summary

Introduction

There is an increasing move towards communicating risk information to both patients and the wider public, fuelled by increasingly precise epidemiological estimates, technological developments allowing the use of biomarkers of risk as communication tools and the rise of interest in informed choice (see, for example, ‘Screening in healthcare’). As a consequence, concern about how best to communicate risk information and evaluate the impact of different methods of communicating risk has risen correspondingly. Communicating risk information should not be seen as an end in itself, but rather as a means to achieving one or more ultimate aims. Principally, these include communicating risk information to (a) facilitate informed choices; (b) motivate behaviour change to reduce identified risks and (c) provide reassurance while avoiding false reassurance. This chapter discusses why the current focus on communicating probabilistic information is insufficient for achieving these outcomes and describes other approaches which have shown more promise.

Risk communication as presenting probabilities

Much recent discussion of risk communication has centred on how numerical probability information should be presented (Calman & Royston, 1997; Edwards et al., 2001, 2002, 2003; Paling, 2003). At face value, presenting risk information in a probabilistic form is entirely reasonable: the information derives from epidemiological studies, which yield information about disease risks in terms of probabilities. However, there are reliable and systematic differences between estimates of actual risks, as calculated from mortality statistics and the public's perception of these (Lichtenstein et al., 1978) (see ‘Risk perception’).

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Publisher: Cambridge University Press
Print publication year: 2007

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References

Axworthy, D., Brock, D.J., Bobrow, M. & Marteau, T.M. (1996). Psychological impact of population-based carrier testing for cystic fibrosis: 3-year follow-up. Lancet, 347, 1443–6.Google Scholar
Bekker, H., Thornton, J.G., Airey, C.M.et al. (1999). Informed decision making: an annotated bibliography and systematic review. Health Technology Assessment, 3(1).Google Scholar
Bishop, G.D. (1991). Understanding the understanding of illness. In Skelton, J.A. & Croyle, R.T. (Eds.). Mental representation in health and illness (pp. 32–59). New York: Springer-Verlag.
Bostrom, A., Fischhoff, B. & Morgan, M.G. (1992). Characterizing mental models of hazardous processes: a methodology and an application to radon. Journal of Social Issues, 48, 85–100.Google Scholar
Calman, K. & Royston, G. (1997). Risk language and dialects. British Medical Journal, 315, 939–42.Google Scholar
Christensen, A.J., Moran, P.J., Ehlers, S.L.et al. (1999). Smoking and drinking behavior in patients with head and neck cancer: effects of behavioral self-blame and perceived control. Journal of Behavioral Medicine, 22, 407–18.Google Scholar
Crawford, D. (2002). Population strategies to prevent obesity. British Medical Journal, 325, 728–9.Google Scholar
Dijkstra, A. & deVries, H. (2000). Self-efficacy expectations with regard to different tasks in smoking cessation. Psychology and Health, 15, 501–11.Google Scholar
Edwards, A.G.K., Elwyn, G.J., Mathews, E. & Pill, R. (2001). Presenting risk information – a review of the effects of “framing” and other manipulations on patient outcomes. Journal of Health Communication, 6, 61–2.Google Scholar
Edwards, A., Elwyn, G. & Mulley, A. (2002). Explaining risks: turning numerical data into meaningful pictures. British Medical Journal, 324, 827–30.Google Scholar
Edwards, A., Unigwe, S., Elwyn, G. & Hood, K. (2003). Effects of communicating individual risks in screening programmes: Cochrane systematic review. British Medical Journal, 327, 703–9.Google Scholar
Farmer, A., Levy, J.C. & Turner, R.C. (1999). Knowledge of risk of developing diabetes mellitus among siblings of Type 2 diabetic patients. Diabetic Medicine, 16, 233–7.Google Scholar
Floyd, D.L., Prentice-Dunn, S. & Rogers, R.W. (2000). A meta-analysis of research on protection motivation theory. Journal of Applied Social Psychology, 30, 407–29.Google Scholar
Hall, S., Bobrow, M. & Marteau, T.M. (2000). Psychological consequences for parents of false negative results on prenatal screening for Down's syndrome: retrospective interview study. British Medical Journal, 320, 407–12.Google Scholar
Hall, S., Weinman, J. & Marteau, T.M. (2004). The motivating impact of informing women smokers of a link between smoking and cervical cancer: the role of coherence. Health Psychology, 23, 419–24.Google Scholar
Hendrickx, L., Vlek, C. & Oppewal, H. (1989). Relative importance of scenario information and frequency information in the judgment of risk. Acta Psychologica, 72, 41–63.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, 343–52.Google Scholar
Hoffrage, U., Lindsey, S., Hertwig, R. & Gigerenzer, G. (2000). Communicating statistical information. Science, 290, 2261–2.Google Scholar
Klein, W.M. (1997). Objective standards are not enough: affective, self-evaluative, and behavioral responses to social cognition information. Journal of Personality and Social Psychology, 72, 763–74.Google Scholar
Lawson, K.L. (2001). Contemplating selective reproduction: the subjective appraisal of parenting a child with a disability. Journal of Reproductive and Infant Psychology, 19, 73–82.Google Scholar
Leventhal, H. (1970). Findings and theory in the study of fear communications. Advances in Experimental Social Psychology, 5, 119–86.Google Scholar
Leventhal, H., Benyamini, Y., Brownlee, S. et al. (1997). Illness representations: theoretical foundations. In Petrie, K.J. & Weinman, J.A. (Eds.). Perceptions of health and illness: current research and applications (pp. 19–45). Amsterdam: Harwood Academic.
Lichtenstein, S., Slovic, P., Fischhoff, B., Layman, M. & Combs, B. (1978). Judged frequency of lethal events. Journal of Experimental Psychology: Human Learning and Memory, 4, 551–78.Google Scholar
Lipkus, I.M., Samsa, G. & Rimer, B.K. (2001). General performance on a numeracy scale among highly education samples. Medical Decision Making, 21, 37–44.Google Scholar
Lippman-Hand, A. & Fraser, F.C. (1979). Genetic counseling: provision and reception of information. American Journal of Medical Genetics, 3, 113–27.Google Scholar
Marteau, T.M., Dormandy, E. & Michie, S. (2001a). A measure of informed choice. Health Expectations, 4, 99–108.Google Scholar
Marteau, T.M. & Kinmonth, A.L. (2002). Screening for cardiovascular risk: public health imperative or matter for individual informed choice?British Medical Journal, 325, 78–80.Google Scholar
Marteau, T.M., Rana, S. & Kubba, A. (2002). Smoking and cervical cancer: a qualitative study of the explanatory models of smokers with cervical abnormalities. Psychology, Health and Medicine, 7, 107–9.Google Scholar
Marteau, T.M., Saidi, G., Goodburn, S.et al. (2000). Numbers or words? A randomised controlled trial of presenting screen negative results to pregnant women. Prenatal Diagnosis, 20, 714–18.Google Scholar
Marteau, T.M., Senior, V. & Sasieni, P. (2001b). Women's understanding of a “normal smear test result”: experimental questionnaire based study. British Medical Journal, 322, 526–8.Google Scholar
McBride, C.M., Scholes, D., Grothaus, L.C.et al. (1999). Evaluation of a minimal self-help smoking cessation intervention following cervical cancer screening. Preventive Medicine, 20, 133–8.Google Scholar
Milne, S., Sheeran, P. & Orbell, S. (2000). Prediction and intervention in health-related behavior: a meta-analytic review of protection motivation theory. Journal of Applied Social Psychology, 30, 106–43.Google Scholar
Nexoe, J., Gyrd-Hansen, D., Kragstrup, J., Kristiansen, I.S. & Nielsen, J.B. (2002). Danish GPs' perception of disease risk and benefit of prevention. Family Practice, 19, 3–6.Google Scholar
O'Connor, A.M., Legare, F. & Stacey, D. (2003). Risk communication in practice: the contribution of decision aids. British Medical Journal, 327, 736–40.Google Scholar
Paling, J. (2003). Strategies to help patients understand risks. British Medical Journal, 327, 745–8.Google Scholar
Petticrew, M.P., Sowden, A.J., Lister-Sharp, D. & Wright, K. (2000). False-negative results in screening programmes: systematic review of impact and implications. Health Technology Assessment, 4(5).Google Scholar
Reyna, V.F. & Brainerd, C.J. (1991). Fuzzy-trace theory and framing effects in choice: gist extraction, truncation, and conversion. Journal of Behavioral Decision Making, 4, 249–62.Google Scholar
Roth, E., Morgan, M.G., Fischhoff, B., Lave, L. & Bostrom, A. (1990). What do we know about making risk comparisons?Risk Analysis, 10, 375–80.Google Scholar
Rothman, A.J. & Kiviniemi, M.T. (1999). Treating people with information: an analysis and review of approaches to communicating health risk information. Journal of the National Cancer Institute Monographs, 25, 44–51.Google Scholar
Schwartz, L.M., Woloshin, S., Black, W.C. & Welch, G.H. (1997). The role of numeracy in understanding the benefit of screening mammography. Annals of Internal Medicine, 127, 966–71.Google Scholar
Schwarz, N. & Vaughn, L.A. (2002). The availability heuristic revisited: ease of recall and content of recall as distinct sources of information. In Gilovich, T., Griffin, D. & Kahneman, D. (Eds.). Heuristics and biases: the psychology of intuitive judgment (pp. 103–19). Cambridge: Cambridge University Press.
Sheeran, P. (2002). Intention–behaviour relations: a conceptual and empirical review. European Review of Social Psychology, 12, 1–36.Google Scholar
Slaytor, E.K. & Ward, J.E. (1998). How risks of breast cancer and benefits of screening are communicated to women: analysis of 58 pamphlets. British Medical Journal, 317, 263–4.Google Scholar
Tymstra, T. & Bieleman, B. (1987). The psychosocial impact of mass-screening for cardiovascular risk-factors. Family Practice, 4, 287–90.Google Scholar
Weinstein, N.D. (1998). Accuracy of smokers' risk perceptions. Annals of Behavioral Medicine, 20, 135–40.Google Scholar
Weinstein, N.D. (1999). What does it mean to understand a risk? Evaluating risk communication. Journal of the National Cancer Institute Monographs, 25, 15–20.Google Scholar
Weinstein, N.D., Slovic, P., Waters, E. & Gibson, G. (2004). Public understanding of the illnesses caused by cigarette smoking. Nicotine and Tobacco Research, 6, 349–55.Google Scholar
Witte, K. & Allen, M. (2000). A meta-analysis of fear appeals: implications for effective public health campaigns. Health Education and Behavior, 27, 591–615.Google Scholar
Wright, P. (1999). Designing healthcare advice for the public. In Durso, F.T., Nickerson, R.S., et al. (Eds.). Handbook of applied cognition (pp. 695–723). New York: John Wiley & Sons.

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