Journal of the National Cancer Institute Advance Access originally published online on June 10, 2008
JNCI Journal of the National Cancer Institute 2008 100(12):830-831; doi:10.1093/jnci/djn179
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
© The Author 2008. Published by Oxford University Press.
EDITORIALS |
Risky Business: Tools to Improve Risk Communication in a Doctor's Office
Affiliations of authors: Department of Epidemiology (MJT, LMH) and Surveillance Research and Behavioral Research Center (MS), American Cancer Society, Atlanta, GA
Correspondence to: Michael J. Thun, MD, Department of Epidemiology and Surveillance Research, American Cancer Society, 250 Williams St, Northwest, Atlanta, GA 30303-1002 (e-mail: michael.thun{at}cancer.org).
Imagine if the waiting room of every doctor's office had an inexpensive device that allowed patients to understand their true health risks and the benefits to be gained from modifying various behaviors. Ideally, this device would be simple, readily accessible, have high visual impact, and generate feedback that is personalized to the individual. The paper by Woloshin et al. (1) in this issue of the Journal is a step in that direction. It presents simple risk charts that could be taped to the wall of a doctor's office to indicate the average probability of dying from various conditions over the next 10 years for a man or woman of specified age and smoking status. These charts put the risk from different conditions into context, suggest where risk reduction efforts should be focused, and highlight the harms from cigarette smoking.
These charts improve on an earlier version by the same authors (2) in that they use updated mortality data and, in response to comments on the earlier paper (3), a different statistical approach that separates former smokers from never smokers. Both versions provide a broader perspective on risk than various interactive risk calculators on the Internet (4) in that they allow comparisons across a variety of conditions instead of considering single illnesses. This better communicates the extent of the benefits from a behavioral change such as stopping smoking. Both papers (1,2) also incorporate insights from research on risk communication (5). They avoid the use of decimals (6), express risk in absolute rather than relative terms (7), explicitly specify the time period (10 years) to which this risk applies, and present frequencies using a constant denominator to facilitate comparisons (eg, x cases per 1000 people). The latter avoids the erroneous perception that a disease affecting 10 in 100 people is more risky than one that affects 1 in 10 people (8) or that a condition that kills "1286 of 10 000 people" (ie, about 13%) is worse than a disease that kills "24.14 of 100 people" (ie, about 24%) (9).
The paper tackles an issue that is both important and difficult. Risk communication is challenging for several reasons. Americans in general have poor numeracy skills (10,11), find it difficult to recall and interpret probabilities (12), and have limited knowledge about the modifiable causes of cancer (13) or the full risks of cigarette smoking (14). Individuals with the least education who have the most risk factors and the highest risk of developing and dying from chronic diseases are the least aware of modifiable risk factors (15).
Health messages delivered by a physician or other health professional are especially powerful in motivating behavioral changes and have been shown to increase the rate of quitting smoking (16) and abstinence after smoking cessation (17). However, physicians do not fully capitalize on this unique opportunity. Only about half of adult current smokers who visited a doctor during the previous year reported receiving advice to quit smoking (18,19). One reason is that doctors have insufficient time and training to provide detailed behavioral counseling. Institutional changes in clinical practice (17) and educational tools that facilitate such counseling are needed to take full advantage of this high-yield and cost-effective intervention (20).
The approach proposed by Woloshin et al. (1) could be further improved by combining the numerical estimates with graphical imagery, preferably in an interactive format. Numerical data alone are not sufficient in communicating risk because people vary widely in their affective response to the same probability estimates (7,12). Perceptions of personal risk are influenced by whether the exposure is considered voluntary, controllable, and socially desirable. The salience of health messages can be improved by individualizing communications beyond the broad attributes of age, sex, and smoking status, and by comparing risk under different scenarios. Tailored communications are considered one of the most promising approaches to smoking cessation interventions (21). These are particularly effective when individuals can compare their predicted risk in the presence or absence of various behavioral changes because most of us can more easily judge comparative risks than single probabilities.
The key issue is whether people will actually pay attention to these risk charts if they are posted in the waiting room or on the wall of a doctor's office. Our sense is that these could be used by a doctor for a visual illustration of the benefits of quitting smoking but that they would have broader use and greater impact if provided as an interactive program that patients could be encouraged to use in the waiting room. The risk estimates provided by Woloshin et al. (1) bring us a step closer to the goal of communicating effectively about risk in the context of routine medical care. The next steps could involve collaboration with other risk communication researchers to personalize this information and deliver it in ways that maximize its impact on health behaviors.
REFERENCES
1. Woloshin S, Schwartz LM, Welch HG. The risk of death by age, sex, and smoking status in the United States: putting health risks in context. J Natl Cancer Inst (2008) 100(11):1–10.
2. Woloshin S, Schwartz LM, Welch HG. Risk charts: putting cancer in context. J Natl Cancer Inst (2002) 94(11):799–804.
3. Bach PB, Schrag D. Risk charts: putting cancer in context. J Natl Cancer Inst (2002) 94(20):1584–1585. author reply 1585–1586.
4. Levy AG, Sonnad SS, Kurichi JE, Sherman M, Armstrong K. Making sense of cancer risk calculators on the web. J Gen Intern Med (2008) 23(3):229–235.[CrossRef][ISI][Medline]
5. Klein WM, Stefanek ME. Cancer risk elicitation and communication: lessons from the psychology of risk perception. CA Cancer J Clin (2007) 57(3):147–167.
6. Lipkus IM. Numeric, verbal, visual formats of conveying health risks: suggested best practices and future recommendations. Med Decis Making (2007) 27(5):696–713.
7. O’Doherty K, Suthers GK. Risky communication: pitfalls in counseling about risk, and how to avoid them. J Genet Couns (2007) 16(4):409–417.[CrossRef][Medline]
8. Alonso D, Fernandez-Berrocal P. Irrational decisions: attending to numbers rather than ratios. Pers Individ Dif (2003) 35(7):1537–1547.[CrossRef][ISI]
9 Yamagishi K. When a 12.86% mortality is more dangerous than 24.14%: implications for risk communication. Appl Cogn Psychol (1997) 11(6):495–506.[CrossRef][ISI]
10. Fagerlin A, Ubel PA, Smith DM, Zikmund-Fisher BJ. Making numbers matter: present and future research in risk communication. Am J Health Behav (2007) 31(suppl_1):S47–S56.[ISI][Medline]
11. Burkell J. What are the chances? Evaluating risk and benefit information in consumer health materials. J Med Libr Assoc (2004) 92(2):200–208.[ISI][Medline]
12. Rothman AJ, Kiviniemi MT. Treating people with information: an analysis and review of approaches to communicating health risk information. J Natl Cancer Inst Monogr (1999) 25:44–51.
13. Breslow RA, Sorkin JD, Frey CM, Kessler LG. Americans’ knowledge of cancer risk and survival. Prev Med (1997) 26(2):170–177.[CrossRef][ISI][Medline]
14. Weinstein ND, Marcus SE, Moser RP. Smokers’ unrealistic optimism about their risk. Tob Control (2005) 14(1):55–59.
15. National Center for Health Statistics. Health, United States, 2007 with Chartbook on Trends in the Health of Americans (2007) Hyattsville, MD: Public Health Service.
16. Stead L, Bergson G, Lancaster T. Physician advice for smoking cessation. Cochrane Database Syst Rev (2008) 2. CD000165.
17. Fiore M, Jaen C. A clinical blueprint to accelerate the elimination of tobacco use. JAMA (2008) 299(17):2083–2085.
18. Lopez-Quintero C, Crum RM, Neumark YD. Racial/ethnic disparities in report of physician-provided smoking cessation advice: analysis of the 2000 National Health Interview Survey. Am J Public Health (2006) 96(12):2235–2239.
19. Lee DJ, Fleming LE, McCollister KE, et al. Healthcare provider smoking cessation advice among US worker groups. Tob Control (2007) 16(5):325–328.
20. Centers for Disease Control and Prevention. Best Practices for Comprehensive Tobacco Control Programs (2007) Atlanta, GA: Office of Smoking and Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, US Department of Health and Human Services.
21. Velicer WF, Prochaska JO, Redding CA. Tailored communications for smoking cessation: past successes and future directions. Drug Alcohol Rev (2006) 25(1):49–57.[CrossRef][ISI][Medline]
Related Articles in JNCI
CiteULike 
Connotea 
Del.icio.us What's this?
J Natl Cancer Inst 2008 100: 845-853.
J Natl Cancer Inst 2008 100: 829.
J Natl Cancer Inst 2008 100: 829.
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||