Erika A. Waters

Taking Stock of Unrealistic Optimism

Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from 3 decades of research, we discuss critically how researchers define unrealistic optimism, and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group levels and unrealistic comparative optimism at the individual and group levels. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type: the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic as they might seem, even for unrealistic comparative optimism. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention.

Formats for Improving Risk Communication in Medical Tradeoff Decisions

ABSTRACT To make treatment decisions, patients should consider not only a treatment options potential consequences but also the probability of those consequences. Many laypeople, however, have difficulty using probability information. This Internet-based study (2,601 participants) examined a hypothetical medical tradeoff situation in which a treatment would decrease one risk but increase another. Accuracy was assessed in terms of the ability to determine correctly whether the treatment would increase or decrease the total risk. For these tradeoff problems, accuracy was greater when the following occurred: (1) the amount of cognitive effort required to evaluate the tradeoff was reduced; (2) probability information was presented as a graphical display rather than as text only; and (3) information was presented as percentages rather than as frequencies (n in 100). These findings provide suggestions of ways to present risk probabilities that may help patients understand their treatment options.

Prevalence of Tamoxifen Use for Breast Cancer Chemoprevention Among U.S. Women

Background: Tamoxifen can reduce the risk of developing invasive estrogen receptor–positive breast cancer by 49%, but it is unknown how many women in the United States are taking tamoxifen for primary prevention of breast cancer. Methods: Data from the years 2000 and 2005 National Health Interview Surveys were analyzed to estimate the prevalence of tamoxifen use among U.S. women for primary chemoprevention of breast cancer. Results: In 2000, ∼0.2% of U.S. women ages 40 to 79 years without a personal history of breast cancer took tamoxifen for chemoprevention (95% confidence interval, 0.13-0.31). In 2005, the prevalence was ∼0.08% (95% confidence interval, 0.03-0.17). Conclusion: The prevalence of tamoxifen use for primary prevention of breast cancer was very low in the years 2000 and 2005. Possible explanations for the low uptake are explored. Cancer Epidemiol Biomarkers Prev; 19(2); 443–6

Reducing Aversion to Side Effects in Preventive Medical Treatment Decisions.

Laypeople tend to be overly sensitive to side effects of treatments that prevent illness, possibly leading them to refuse beneficial therapies. This Internet-based study attempted to reduce such side effect aversion by adding graphic displays to the numerical risk probabilities. It also explored whether graphics reduce side effect aversion by making it easier for respondents to determine how the treatment might change their net cancer risk. Participants (N=4,248) were presented with a hypothetical preventive treatment situation that was or was not accompanied by a small side effect. In both conditions, the net absolute risk reduction was 12%. Adding an array of stick figures to risk probabilities reduced side effect aversion substantially, but adding a bar graph was not beneficial. The ability of arrays to reduce side effect aversion was not attributable to greater accuracy in evaluating the treatments net benefit.

Public understanding of the illnesses caused by cigarette smoking

A nationwide survey of 776 U.S. residents, divided approximately equally between teenagers and adults, smokers and nonsmokers, assessed public understanding of the illnesses caused by smoking. When respondents were asked what illnesses are caused by smoking, lung cancer was the only illness that could be identified by a clear majority of respondents. Roughly half mentioned emphysema. A much smaller percentage of respondents were able to mention any cardiovascular disease or any kind of cancer other than lung cancer. People also underestimated the death rate from lung cancer and overestimated survival duration. Only a minority realized that emphysema is incurable. Large portions of the sample said they knew only a little about the pain and suffering experienced by individuals with these illnesses. The results demonstrated that even though people recognize that smoking can lead to adverse health consequences, they do not have even a basic understanding of the nature and severity of these consequences.

A Primer on Unrealistic Optimism

People display unrealistic optimism in their predictions about countless events, believing that their personal future outcomes will be more desirable than can possibly be true. We summarize the vast literature on unrealistic optimism by focusing on four broad questions: What is unrealistic optimism, when does it occur, why does it occur, and what are its consequences? Unrealistic optimism can be operationalized in multiple ways; is commonplace yet has well-established boundary conditions; occurs for a variety of reasons; and has consequences for affect, decision making, and behavior.

Perceptions of cancer as a death sentence: prevalence and consequences.

Research suggests that perceiving cancer as a death sentence is a critical determinant of health care–seeking behaviors. However, there is limited information regarding the prevalence of this perception in the US population. Cross-sectional analysis of data (n = 7674 adults) from the 2007-2008 administration of the nationally representative Health Information National Trends Survey (HINTS 3) was performed. A majority (61.6%) of respondents perceived cancer as death sentence, and more than one-third (36%) of respondents reported that they avoid seeing their physicians. In the adult US population, perceiving cancer as a death sentence is common and is associated with education level and avoidance of physicians.

Don't know responses to risk perception measures: implications for underserved populations.

Background: Risk perceptions are legitimate targets for behavioral interventions because they can motivate medical decisions and health behaviors. However, some survey respondents may not know (or may not indicate) their risk perceptions. The scope of “don’t know” (DK) responding is unknown. Objective: Examine the prevalence and correlates of responding DK to items assessing perceived risk of colorectal cancer. Methods: Two nationally representative, population-based, cross-sectional surveys (2005 National Health Interview Survey [NHIS]; 2005 Health Information National Trends Survey [HINTS]), and one primary care clinic-based survey comprised of individuals from low-income communities. Analyses included 31,202 (NHIS), 1,937 (HINTS), and 769 (clinic) individuals. Measures: Five items assessed perceived risk of colorectal cancer. Four of the items differed in format and/or response scale: comparative risk (NHIS, HINTS); absolute risk (HINTS, clinic), and “likelihood” and “chance” response scales (clinic). Only the clinic-based survey included an explicit DK response option. Results: “Don’t know” responding was 6.9% (NHIS), 7.5% (HINTS-comparative), and 8.7% (HINTS-absolute). “Don’t know” responding was 49.1% and 69.3% for the “chance” and “likely” response options (clinic). Correlates of DK responding were characteristics generally associated with disparities (e.g., low education), but the pattern of results varied among samples, question formats, and response scales. Limitations: The surveys were developed independently and employed different methodologies and items. Consequently, the results were not directly comparable. There may be multiple explanations for differences in the magnitude and characteristics of DK responding. Conclusions: “Don’t know” responding is more prevalent in populations affected by health disparities. Either not assessing or not analyzing DK responses could further disenfranchise these populations and negatively affect the validity of research and the efficacy of interventions seeking to eliminate health disparities.

What Is My Cancer Risk? How Internet-Based Cancer Risk Assessment Tools Communicate Individualized Risk Estimates to the Public: Content Analysis

Background Internet-based cancer risk assessment tools have the potential to inform the public about cancer risk and promote risk-reducing behaviors. However, poorly communicated information on these websites may result in unintended adverse health outcomes. Objective This study examined whether: (1) Internet-based cancer risk assessment tools use risk communication formats that facilitate comprehension and reduce bias (as identified by the empirical literature); (2) the use of these formats varies by website affiliation; and (3) the websites provided information necessary to evaluate the quality of the risk estimate. Methods A content analysis of Internet-based cancer risk assessment tools was conducted. The terms calculate cancer risk, cancer risk calculator, estimate cancer risk, assess cancer risk, and cancer risk assessment were searched using three search engines. We identified 47 risk assessment tools and coded each according to standardized criteria. We calculated simple frequencies on all coding categories and performed crosstabulations but did not conduct formal statistical analysis due to small cell sizes. Results Use of risk communication formats that facilitate comprehension and reduce bias varied widely (eg, 30% of websites [14/47] provided absolute and comparative risk information but 83% [39/47] provided safety messages). Use of formats that facilitate comprehension varied by website affiliation and communication strategy (eg, only 8.3% [1/12] websites affiliated with the health care industry provided absolute and comparative risk information, but 83% [5/6] of websites affiliated with a governmental organization did so). Only 53% (25/47) of websites provided information about the statistical model or the peer-reviewed literature that was used to calculate the risk estimate. Conclusion Internet-based cancer risk assessment tools varied in their use of risk communication formats that facilitate comprehension and reduce bias. Formats that are difficult to understand may cause people to misperceive their cancer risk and consequently take inappropriate action.

Aversion to side effects in preventive medical treatment decisions.

OBJECTIVES Individuals may be overly sensitive to the side effects of treatments aimed at preventing illness, in part because they have difficulty in evaluating situations with several possible outcomes that differ in probability. This study tested willingness to undergo a hypothetical preventive treatment and accuracy in determining the probability of harm from the treatment as a function of the presence of a side effect, the initial probability of harm, the format in which probabilities were presented (percentages or frequencies), and the presence or absence of a graphic. DESIGN The study was a factorial experiment involving 5,251 participants. METHODS Participants recruited from a health-oriented internet site read about a hypothetical cancer prevention treatment situation and were asked to indicate their willingness to accept this treatment and whether it would increase or decrease their overall risk of cancer. The net benefit of the treatment was the same in all conditions, whether or not it was associated with a small side effect. RESULTS The presence of information about a side effect dramatically decreased willingness to undergo preventive treatment and accuracy in evaluating the treatments effects. Willingness and accuracy were not influenced by the initial probability of harm, whether the risk probability information was presented as frequencies (N in 100) or as percentages, or whether the initial risk was presented with a bar graph or an array of asterisks or stick figures. CONCLUSIONS Individuals are highly averse to preventive treatments with even small side effects and have difficulty combining the likelihood of positive and negative outcomes to determine the treatments overall benefits.