Measuring Cigarette Smoking Risk Perceptions.

Risk perception is an important construct in many health behavior theories. Smoking risk perceptions are thoughts and feelings about the harms associated with cigarette smoking. Wide variation in the terminology, definition, and assessment of this construct makes it difficult to draw conclusions about the associations of risk perceptions with smoking behaviors. To understand optimal methods of assessing adults' cigarette smoking risk perceptions (among both smokers and nonsmokers), we reviewed best practices from the tobacco control literature, and where gaps were identified, we looked more broadly to the research on risk perceptions in other health domains. Based on this review, we suggest assessments of risk perceptions (1) about multiple smoking-related health harms, (2) about harms over a specific timeframe, and (3) for the person affected by the harm. For the measurement of perceived likelihood in particular (ie, the perceived chance of harm from smoking based largely on deliberative thought), we suggest including (4) unconditional and conditional items (stipulating smoking behavior) and (5) absolute and comparative items and including (6) comparisons to specific populations through (7) direct and indirect assessments. We also suggest including (8) experiential (ostensibly automatic, somatic perceptions of vulnerability to a harm) and affective (emotional reactions to a potential harm) risk perception items. We also offer suggestions for (9) response options and (10) the assessment of risk perception at multiple time points. Researchers can use this resource to inform the selection, use, and future development of smoking risk perception measures. IMPLICATIONS: Incorporating the measurement suggestions for cigarette smoking risk perceptions that are presented will help researchers select items most appropriate for their research questions and will contribute to greater consistency in the assessment of smoking risk perceptions among adults.

Perceptions of control and unrealistic optimism in early-phase cancer trials.

PURPOSE: Recent research has found unrealistic optimism (UO) among patient-subjects in early-phase oncology trials. Our aim was to investigate the cognitive and motivational factors that evoke this bias in this context. We expected perceptions of control to be a strong correlate of unrealistic optimism. METHODS: A study of patient-subjects enrolled in early-phase oncology trials was conducted at two sites in the USA. Respondents completed questionnaires designed to assess unrealistic optimism and several risk attribute variables that have been found to evoke the bias in other contexts. RESULTS: One hundred and seventy-one patient-subjects agreed to be interviewed for our study. Significant levels of perceived controllability were found with respect to all nine research-related questions. Perceptions of control were found to predict unrealistic optimism. Two other risk attribute variables, awareness of indicators (p=0.024) and mental image (p=0.022), were correlated with unrealistic optimism. However, in multivariate regression analysis, awareness and mental image dropped out of the model and perceived controllability was the only factor independently associated with unrealistic optimism (p<0.0001). CONCLUSION: Patient-subjects reported that they can, at least partially, control the benefits they receive from participating in an early-phase oncology trial. This sense of control may underlie unrealistic optimism about benefiting personally from trial participation. Effective interventions to counteract unrealistic optimism may need to address the psychological factors that give rise to distorted risk/benefit processing.

Variations in Unrealistic Optimism Between Acceptors and Decliners of Early Phase Cancer Trials.

Research has found that patient-subjects in early phase cancer trials exhibit unrealistic optimism regarding the risks and possible benefits of trial participation. Unrealistic optimism is associated with therapeutic misconception and failures to appreciate research-related information. This is the first study to assess whether those who decline to participate in these trials also exhibit unrealistic optimism. It is also the first study to assess whether there are significant differences in appreciation of research-related risks/benefits and therapeutic misconception between these two groups. We approached 261 patients at two academic medical centers who were offered enrollment in a Phase I, II, or I/II cancer trial (between 2012 and 2016). Two hundred thirty-three patients agreed to enroll in an early phase cancer trial, 171 of whom agreed to be interviewed for the study. Twenty-eight patients declined the offer to enroll, 15 of whom agreed to be interviewed for the study. Subjects participated in a structured face-to-face interview with a research associate trained to administer the study questionnaires. Acceptors demonstrated a significantly higher level of unrealistic optimism than decliners ( p < .05). Decliners had significantly less therapeutic misconception than acceptors (3.37 [ SD = 0.85] vs. 3.79 [ SD = 0.77], p = .042). There was a significant difference on one of the appreciation questions between acceptors and decliners ( p = .009). Comparative assessment of acceptors and decliners to early phase cancer trials casts light on whether unrealistic optimism is consequential for the decision to participate in these trials. The different levels of unrealistic optimism exhibited by these groups suggest that it may be a factor that affects the decision to participate.

Dispositional optimism and therapeutic expectations in early-phase oncology trials.

BACKGROUND: Prior research has identified unrealistic optimism as a bias that might impair informed consent among patient-subjects in early-phase oncology trials. However, optimism is not a unitary construct; it also can be defined as a general disposition, or what is called dispositional optimism. The authors assessed whether dispositional optimism would be related to high expectations for personal therapeutic benefit reported by patient-subjects in these trials but not to the therapeutic misconception. The authors also assessed how dispositional optimism related to unrealistic optimism. METHODS: Patient-subjects completed questionnaires designed to measure expectations for therapeutic benefit, dispositional optimism, unrealistic optimism, and the therapeutic misconception. RESULTS: Dispositional optimism was found to be significantly associated with higher expectations for personal therapeutic benefit (Spearman rank correlation coefficient [r], 0.333; P<.0001), but was not associated with the therapeutic misconception (Spearman r, -0.075; P = .329). Dispositional optimism was found to be weakly associated with unrealistic optimism (Spearman r, 0.215; P = .005). On multivariate analysis, both dispositional optimism (P = .02) and unrealistic optimism (P<.0001) were found to be independently associated with high expectations for personal therapeutic benefit. Unrealistic optimism (P = .0001), but not dispositional optimism, was found to be independently associated with the therapeutic misconception. CONCLUSIONS: High expectations for therapeutic benefit among patient-subjects in early-phase oncology trials should not be assumed to result from misunderstanding of specific information regarding the trials. The data from the current study indicate that these expectations are associated with either a dispositionally positive outlook on life or biased expectations concerning specific aspects of trial participation. Not all manifestations of optimism are the same, and different types of optimism likely have different consequences for informed consent in early-phase oncology research.

A Primer on Unrealistic Optimism.

People display unrealistic optimism in their predictions for 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.

Examining intuitive risk perceptions for cancer in diverse populations.

In this article we examine intuitive dimensions of personal cancer risk likelihood, which theory and empirical evidence indicate may be important elements in the risk perception process. We draw on data from a study of risk perceptions in three social groups, university students, men living in the community, and primary care patients living in urban area. The study took place in 2007-2011, in New York State (Garden City and New York City) and Boston, Massachusetts. This study used items developed from categories identified in prior qualitative research specifying emotions and attitudes activated in cancer risk determination to examine perception of cancer risks. Across three samples - university students (N=568), community men (N=182), and diverse, urban primary care patients (N=127) - we conducted exploratory factor and construct analyses. We found that the most reliable two factors within the five-factor solution were Cognitive Causation, tapping beliefs that risk thoughts may encourage cancer development, and Negative Affect in Risk, assessing negative feelings generated during the risk perception process. For these factors, there were high levels of item endorsement, especially in minority groups, and only modest associations with established cancer risk perception and worry assessments, indicating novel content. These items may prove useful in measuring and comparing intuitive cancer risk perceptions across diverse population subgroups.

Perceived risk for sexually transmitted infections aligns with sexual risk behavior with the exception of condom nonuse: data from a nonclinical sample of sexually active young adult women.

BACKGROUND: Research on the relationship between sexual risk behavior and perceived risk for contracting a sexually transmitted infection (STI) has yielded mixed results. The objective of this study is to investigate the extent to which 3 measures of perceived risk accurately reflect 5 sexual risk behaviors in a sample of healthy, sexually active young adult women. A positive monotonic relationship between sexual risk behavior and perceived risk for STIs is hypothesized. METHODS: A sample of 1192 female U.S. Marine Corps on their first duty assignment 10 to 11 months (on average) after graduation from recruit training answered a self-administered paper-and-pencil questionnaire as part of a larger study evaluating an intervention to prevent STIs and unintended pregnancy that was administered during recruit training. RESULTS: All but 1 of the 15 bivariate associations between sexual risk behavior and perceived risk for STIs was statistically significant. The expected positive monotonic relationship was observed except for condom use. Women who never used condoms during intercourse reported lower levels of perceived risk than occasional users and, in some subgroups, consistent condom users. Multivariate analyses further explored the relationship between condom use and perceived risk. CONCLUSIONS: The results suggest that interventions directed at raising awareness of susceptibility to STIs should emphasize how the individual's own behavior puts them at risk, regardless of situation or context.

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 three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. 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 even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention.

Explanations for side effect aversion in preventive medical treatment decisions.

OBJECTIVE: Many laypeople demonstrate excessive sensitivity to negative side effects of medical treatments, which may lead them to refuse beneficial therapies. This Internet-based experiment investigated three possible explanations for such "side effect aversion." One was derived from mental accounting, one examined the mere presence of a side effect, and one focused on computational difficulties. DESIGN: Participants (N = 5,379) were presented with a hypothetical cancer preventive treatment situation that was or was not accompanied by one or two small side effects. The side effects were either beneficial or harmful. In all conditions, the net absolute risk reduction associated with the treatment was 15%. MAIN OUTCOME MEASURES: Participants indicated their willingness to accept treatment and their perceptions of the treatment's effects on their overall cancer risk. RESULTS: Data were consistent only with the "mere presence" explanation of side effect aversion, the idea that side effects act as a strong negative cue that directly affects treatment appraisal. The number of negative side effects did not influence treatment willingness. CONCLUSION: Side effect aversion is a challenge to informed decision making. Specific mechanisms that produce side effect aversion should be identified.

A test of numeric formats for communicating risk probabilities.

BACKGROUND: Because people frequently encounter information about the probability of health risks, there is a need for research to help identify the best formats for presenting these probabilities. METHODS: Three waves of participants were recruited from visitors to a cancer-related Internet site. Participants were presented with a hypothetical scenario that required them to perform 2 mathematical operations of the types that might be encountered in discussions of risk. Each wave encountered different operations. The operations used were compare, halve, triple, add, sequence, and tradeoff. Three numeric formats for communicating risk likelihoods were tested: percentages (e.g., 12%), frequencies (e.g., 12 in 100), and 1 in n (e.g., 1 in 8), and many levels of risk magnitude were crossed with the 3 formats. RESULTS: The total sample of 16,133 individuals represented an overall participation rate of 36.1%. Although the relative performance of the formats varied by operation, aggregated across operations, the percentage and frequency formats had higher overall accuracy rates than the 1-in-n format (57% and 55% v. 45%, respectively). Participants with less education, African Americans, Hispanics, and women had more difficulty with the mathematical operations. DISCUSSION: Percentage and frequency formats facilitate performance of simple operations on risk probabilities compared with the 1-in-n format, which should usually be avoided.

Risk compensation and vaccination: can getting vaccinated cause people to engage in risky behaviors?

BACKGROUND: Some believe that vaccinating young women against human papillomavirus (HPV) will increase their risky behavior. In more formal terms, vaccination lowers risk perception, and people compensate for their lower perceived risk by reducing other preventive behaviors. PURPOSE: We test several predictions from the risk compensation hypothesis in the context of vaccination behavior. METHODS: We obtained a random sample of adults (N=705), interviewing them by phone just as the Lyme disease vaccine first became available to the public and again 18 months later. Analyses controlled for age, sex, education, and race. RESULTS: Vaccinated respondents were less likely to continue engaging in two of five protective behaviors after vaccination. The frequency of these protective behaviors did not dip below that among the unvaccinated respondents. CONCLUSIONS: We found some evidence of regression (protective behaviors dropping, after vaccination, to levels reported by the unvaccinated cohort). However, we did not find disinhibition (exceeding the risk taking of the unvaccinated cohort), the greater threat to public health. Although we will not know for several years what effect HPV vaccination has on other behaviors, if any, data on other vaccinations can offer critically important information in the interim.

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 treatment's 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 treatment's overall benefits.

Meta-analysis of the relationship between risk perception and health behavior: the example of vaccination.

BACKGROUND: Risk perceptions are central to many health behavior theories. However, the relationship between risk perceptions and behavior, muddied by instances of inappropriate assessment and analysis, often looks weak. METHOD: A meta-analysis of eligible studies assessing the bivariate association between adult vaccination and perceived likelihood, susceptibility, or severity was conducted. RESULTS: Thirty-four studies met inclusion criteria (N = 15,988). Risk likelihood (pooled r = .26), susceptibility (pooled r = .24), and severity (pooled r = .16) significantly predicted vaccination behavior. The risk perception-behavior relationship was larger for studies that were prospective, had higher quality risk measures, or had unskewed risk or behavior measures. CONCLUSIONS: The consistent relationships between risk perceptions and behavior, larger than suggested by prior meta-analyses, suggest that risk perceptions are rightly placed as core concepts in theories of health behavior.

Risk perceptions: assessment and relationship to influenza vaccination.

OBJECTIVE: Accurate measurement of beliefs about risk probability is essential to determine what role these beliefs have in health behavior. This study investigated the ability of several types of risk perception measures and of other constructs from health behavior theories to predict influenza vaccination. DESIGN: Prospective study in which students, faculty, and staff at 3 universities (N = 428) were interviewed in the fall, before influenza vaccine was available, and again early in the next calendar year. MAIN OUTCOME MEASURE: Self-reported influenza vaccination. RESULTS: Two interview questions that asked about feeling at risk and feeling vulnerable predicted subsequent behavior better (r = .44, p = .001) than 2 questions that asked for agreement or disagreement with statements about risk probability (r = .25, p = .001) or 4 questions that asked respondents to estimate the magnitude of the risk probability (r = .30, p = .001). Of the 4 perceived risk magnitude scales, a 7-point verbal scale was the best predictor of behavior. Anticipated regret was the strongest predictor of vaccination (r = .45, p = .001) of all constructs studied, including risk perceptions, worry, and perceived vaccine effectiveness. CONCLUSION: Risk perceptions predicted subsequent vaccination. However, perceived risk phrased in terms of feelings rather than as a purely cognitive probability judgment predicted better. Because neither feeling at risk nor anticipated regret is represented in the most commonly used theories of health behavior, the data suggest that these theories are missing important constructs.

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 treatment's net benefit.

Misleading tests of health behavior theories.

Most tests of cognitively oriented theories of health behavior are based on correlational data. Unfortunately, such tests are often biased, overestimating the accuracy of the theories they seek to evaluate. These biases are especially strong when studies examine health behaviors that need to be performed repeatedly, such as medication adherence, diet, exercise, and condom use. Several misleading data analysis procedures further exaggerate the theories' predictive accuracy. Because correlational designs are not adequate for deciding whether a particular construct affects behavior or for testing one theory against another, most of the literature aiming to test these theories tells us little about their validity or completeness. Neither does the existing empirical literature support decisions to use these theories to design interventions. In addition to discussing problems with correlational data, this article offers ideas for alternative testing strategies.

Formats for improving risk communication in medical tradeoff decisions.

To make treatment decisions, patients should consider not only a treatment option's 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.