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Measuring Subjective Risk Estimates
Abstract
Insights from the growing risk literature unearth a range of challenges that have to be addressed in order to receive valid risk estimates and to interpret them realistically. The present chapter highlights some often-neglected influences and their consequences. These include a clear goal definition of the measurement and a thoughtful consideration of the chosen risk perspective and answer format. At the same time, the chapter aims at contributing to an integrative perspective in the field of measuring risk estimates. As a suggestion for a starting point for the development of an integrative framework, a model, the risk assessment matrix (RAM), is presented. The risk assessment matrix combines evidence-based theoretical approaches of probabilistic reasoning (singular vs. distributional) and thinking style (intuitive vs. deliberative). The chapter closes with a summary of the presented influences and some practical recommendations for researchers and practitioners.
... As stated by Lermer et al., risk-taking is related to several personal characteristics in different areas rather than being a uni-dimensional trait (14). They proposed a conceptual model based on previous studies, in which some personality traits and higher-order temperament dimensions in six domains (social, recreation, investment, gambling, health/safety, and ethics) of risk-taking were proposed (14). ...
... As stated by Lermer et al., risk-taking is related to several personal characteristics in different areas rather than being a uni-dimensional trait (14). They proposed a conceptual model based on previous studies, in which some personality traits and higher-order temperament dimensions in six domains (social, recreation, investment, gambling, health/safety, and ethics) of risk-taking were proposed (14). ...
... These questionnaires show risk-taking in general people, which might not apply to specific workplaces with a high level of risk. Another important aspect that should be considered when designing a risk-taking questionnaire is the association between risk-taking and other psychological traits, as Lermer et al. showed in a conceptual model (14). ...
Background: Risk-taking has an influential role in accident occurrence or prevention. Hence, having a valid tool to evaluate workers for risk-taking is necessary. Risk-taking has been intensely studied in the field of psychology and neuroscience, leading to the development of several questionnaires and software. Objectives: In the present study, a new questionnaire was developed and validated based on the conceptual model to assess risk-taking behavior in people working in operator control rooms in industrial settings. Methods: Questions were selected from well-known psychological scales based on a conceptual model, followed by approving its face validity and conducting exploratory factor analysis (EFA). Afterward, some models were computed with confirmatory factor analysis (CFA) and Bayesian structural equation modeling (BSEM). The questionnaire was completed by 208 males who worked in the control room of some industries in Markazi province, Iran, in 2021. Test-retest reliability was done by 42 participants at a three-month interval. Results: One factor and 12 items were suggested by EFA. The model was accepted based on the results of Operator Control Room Risk-taking Questionnaire (ORTQ) goodness of fit CFA (χ2/df = 1.89, comparative fit index (CFI) = 0.90, root mean square error of approximation (RMSEA) = 0.09, and P < 0.001). The correlation coefficient (P < 0.001) between risk-taking and impulsivity was 0.65. However, it was 0.69 between venturesomeness and risk-taking and 0.58 between impulsivity and venturesomeness. Cronbach's alpha was 0.89 for ORTQ test-retest reliability. Operator Control Room Risk-taking Questionnaire was confirmed to have a better leave-one-out cross-validation information criterion (LOOIC) based on BSEM rather than Bayesian confirmatory factor analysis (BCFA). Conclusions: Operator Control Room Risk-taking Questionnaire is a valid and reliable questionnaire that can be used as a screening tool for risk-taking traits in workers before enrolment.
... As with the reappraisal hypothesis, testing the behavior motivation hypothesis needs at least a longitudinal and at best an experimental study design. Researchers need to know exactly what they want to measure and have to adopt an appropriate method to study this effect to avoid misinterpretations (see also Lermer, Streicher, & Raue, 2018). ...
... For instance, the answer format used in a questionnaire can affect the relationship between risk perception and health behavior. To this day, there is no consensus on how to assess risk perception, especially regarding the answer format (Lermer, Streicher, Sachs, & Frey, 2013), even though it has been long known that the scale on which risk questions are to be answered has an impact on people's risk assessment (for comprehensive reviews on this topic see Lermer et al., 2013, 2016, 2018. In sum, the above-mentioned methodological issues should be kept in mind when interpreting the results of studies looking at the link between risk perception and health behavior. ...
Messages aiming to increase the public’s perception of health and safety risks, such as the spread of antibiotic-resistant pathogens, are omnipresent. In these cases, the basic assumption often is that a heightened level of risk perception should lead to more protective behaviours like proper hand hygiene in hospitals. The notion that people’s perception of health risks influences their risk-taking or safety behaviour is prevalent both in health behaviour theories and applied health communication. However, research findings on the connection between risk perception and health-related behaviour are not clear-cut. In the present chapter, we look at the different operationalisations of the term risk perception and discuss several methodological issues that are widespread in the health risk perception literature which might have led to inconclusive results. Overall, even though the effect sizes are generally moderate, the majority of research findings indicate that risk perception influences health- and safety-related behaviour. This was shown both in research looking at a variety of different health-related behaviours at the same time as well as in studies only concerned with specific activities such as hand hygiene and vaccination. Therefore, risk perception as a concept truly deserves its place in health behaviour theory and behaviour change interventions. Some implications of these findings on intervention design are discussed.
... However, there are some doubts whether this is the case for some adventure sports activities, such as rock climbing (Martha, Sanchez, and Gomà-i-Freixanet 2009). Further, Lermer et al. (2013) and Lermer, Streicher, and Raue (2018) show that this effect holds only for comparisons with an abstract third person e.g. 'a person' , and not for specific third persons (even those identified only by adding a name, like we do above). ...
We investigate differences in perceived danger and recklessness judgements by experts (experienced skiers, N=362) and laypeople (N=2080) about participation in adventure sports across the same judgemental task using a third person perspective. We investigate the relationship between danger and recklessness and the extent to which fatality frequency, as well as other contextual factors such as gender, dependants, competence, and motivations of the sports participant affect expert and laypeople judgements respectively. Experienced skiers gave lower overall danger and recklessness ratings than non-skiers. Experienced skiers’ judgements were also more sensitive than non-skiers’ to variations in the fatality rate of the activity and the competence level of the participant, yet were less sensitive to whether the event was done for external benefit such as a charity. Recklessness judgements were overall more sensitive to changes in activity descriptions than danger judgements. Our findings support the emerging picture of adventure sports participants as rational and sensitive to risk-relevant features rather than somehow pathological in their risk perception.
... Because the effects of safety measures on risk behavior can rarely be studied in controlled experimental conditions, accurately capturing the multidimensionality of risk is difficult and may impede conclusive results on risk compensation (Adams, 1995;Evans, 1985;Hedlund, 2000). Various methodologies and forms of risk measurements, including self-reports, crash data, field, and laboratory studies may also explain conflicting results of studies on risk compensation (see Lermer et al., 2018 for a discussion on measuring subjective risk estimates). ...
Risk is the probability of harm, such as the probability of getting into an accident when driving a car. Perceived risks are based on subjective assessments and often deviate from actual probabilities of harm. Both cognitive analysis and feelings inform people's risk perceptions. Laypeople are especially susceptible to emotional factors when judging risks and often focus more on the severity of the outcome than the probability of a risk. When driving, reliance on feelings and intuition is a useful strategy to react quickly to complex situations, but feelings can also distort judgments. Risks that are perceived as dreadful or new are often overestimated, while risks that are perceived as familiar and controllable—such as driving a car—are often underestimated. Repeated exposure to risks without negative consequences can also decrease risk perceptions. Relevant phenomena in this context are speeding and the use of mobile phones while driving; effective risk communication is essential to combat such risky behavior.
... • Identification as risk group and personal risk perception • Perceptions and beliefs (i.e., trivialising beliefs, social trust, personal fears) • Loneliness as a measure of psychological well-being • Acceptance of measures and protective behaviour (i.e., hygiene, social distancing) • Socio-demographics (age > 75) and pre-existing conditions Most measures presented subsequently were developed by the authors, and based on methodological recommendations for measuring public risk responses (Lermer et al., 2018), prior literature on public responses to pandemics (Cho et al., 2013;Prati et al., 2011b;Reintjes et al., 2016), the public discourse in Switzerland, and the measures in place (Federal Council, 2020; Federal Office of Public Health, 2020). ...
Rationale
An important public health strategy during the COVID-19 pandemic was the protection of people at risk of severe progressions of an infection; namely, older people and people with pre-existing conditions.
Objective
To improve public health communication, it is vital to understand, which sociodemographic and psychological factors drive older people’s acceptance of and compliance with public health measures.
Method
This goal was pursued in this three-wave longitudinal online study with older adults, collected between March and June during the COVID-19 pandemic in 2020 (N = 327; first and second wave during the national lockdown; third wave: after the lifting of most lockdown measures).
Results
The results show that overall acceptance of and adherence to the public health measures were high among older adults and even more so for people with pre-existing conditions (e.g., cancer, type II diabetes). However, some infringements of the measures were observed, and the longitudinal analyses suggest that increases in social trust positively influenced acceptance of measures over time, while trivialising beliefs and health fears impacted older adults’ compliance with protective measures over time.
Conclusions
This study offers insights into the behavioural responses of older adults to an ongoing threat and the associated uncertainty that is part of public communication about the pandemic and protective measures.
... Because the effects of safety measures on risk behavior can rarely be studied in controlled experimental conditions, accurately capturing the multidimensionality of risk is difficult and may impede conclusive results on risk compensation (Adams, 1995;Evans, 1985;Hedlund, 2000). Various methodologies and forms of risk measurements, including self-reports, crash data, field and laboratory studies may also explain conflicting results of studies on risk compensation (see Lermer, Streicher, & Raue, 2018 for a discussion on measuring subjective risk estimates). ...
International Encyclopedia of Transportation (Editor: R. Vickerman)
Section: Transport Safety and Security (Section Editor: Per Garder)
Risk is the probability of harm, such as the probability of getting into an accident when driving a car. Perceived risks are based on subjective assessments and often deviate from actual probabilities of harm. Both cognitive analysis and feelings inform people’s risk perceptions. Laypeople are especially susceptible to emotional factors when judging risks and often focus more on the severity of the outcome than the probability of a risk. When driving, reliance on feelings and intuition is a useful strategy to react quickly to complex situations, but feelings can also distort judgments. Risks that are perceived as dreadful or new are often overestimated, while risks that are perceived as familiar and controllable – such as driving a car – are often underestimated. Repeated exposure to risks without negative consequences can also decrease risk perceptions. Relevant phenomena in this context are speeding and the use of mobile phones while driving; effective risk communication is essential to combat such risky behavior.
High-stakes debates often pivot on clashing estimates of outcomes that one side sees as so improbable as not to deserve policy prioritization. These debates are especially intractable when they focus on rare events ranging from disasters (e.g., existential risks from Artificial Intelligence, nuclear war, or bioengineered pandemics) to surprising successes (e.g., once inconceivable scientific discoveries). The research literature offers grounds for suspecting that the micro-probability judgments flowing into such debates are both unreliable and biased.This article covers experimental manipulations that achieve improvements in accuracy for low-probability judgments by shifting from the standard linear elicitation scale and Brier scoring rule to nonlinear (logarithmic) elicitation scales and logarithmic scoring rules. These methodological changes produced accuracy improvements of approximately d = 0.2 to 0.5 for individual accuracy scores. Improvements in aggregate accuracy varied more widely by aggregation function (mean vs. median) and accuracy scoring rule, between parity (d = 0) and a large advantage for non-linear over linear scales (d = 0.68). Judgments obtained via the linear scale and text box elicitations systematically overestimated the true values. Newscales allowed forecasters to provide precise judgments at the low end of the probability scale and logarithmic scoring rules penalize large errors harshly, incentivising judges to avoid 0% and provide precise non-zero probabilities. An indirect elicitation protocol we developed,successive menus, yielded mixed results, such as improving aggregate accuracy and individual calibration at the cost of increasing outlier judgments and reducing retention. Base rate anchors provided context but no measurable accuracy benefits. These results point to next steps for improving probability judgments of rare events. The most promising next steps include a) using subject-specific Base-Rate Anchors, b) developing training programs specific to low-probability events, c) developing more robust and usable indirect elicitation protocols,and d) assessing all of these methods in longitudinal forecasting tournament featuring many forecasting questions focused on rare events.
High-stakes debates often pivot on clashing estimates of outcomes that one side sees as so improbable as not to deserve policy prioritization. These debates are especially intractable when they focus on rare events ranging from disasters (e.g., existential risks from Artificial Intelligence, nuclear war, or bioengineered pandemics) to surprising successes (e.g., once inconceivable scientific discoveries). The research literature offers grounds for suspecting that the micro-probability judgments flowing into such debates are both unreliable and biased. This article covers experimental manipulations that achieve improvements in accuracy for low-probability judgments by shifting from the standard linear elicitation scale and Brier scoring rule to nonlinear (logarithmic) elicitation scales and logarithmic scoring rules. These methodological changes produced accuracy improvements of approximately d = 0.2 to 0.5 for individual accuracy scores. Improvements in aggregate accuracy varied more widely by aggregation function (mean vs. median) and accuracy scoring rule, between parity (d = 0) and a large advantage for non-linear over linear scales (d = 0.68). Judgments obtained via the linear scale and text box elicitations systematically overestimated the true values. New scales allowed forecasters to provide precise judgments at the low end of the probability scale and logarithmic scoring rules penalize large errors harshly, incentivising judges to avoid 0%and provide precise non-zero probabilities. An indirect elicitation protocol we developed, successive menus, yielded mixed results, such as improving aggregate accuracy and individual calibration at the cost of increasing outlier judgments and reducing retention. Base rate anchors provided context but no measurable accuracy benefits. These results point to next steps for improving probability judgments of rare events. The most promising next steps include a) using subject-specific Base-Rate Anchors, b) developing training programs specific to low-probability events, c) developing more robust and usable indirect elicitation protocols, and d) assessing all of these methods in longitudinal forecasting tournament featuring many forecasting questions focused on rare events.
Ob Covid-19-Pandemie, Fake Stories oder politische Erdbeben: Der Umgang mit Unsicherheit ist eine wesentliche Herausforderung im menschlichen Alltag. Obwohl viele beunruhigende Ereignisse der Vergangenheit (z. B. Sonnenfinsternis) erklärt werden konnten, verharren wir bei neuen Unsicherheitslagen in unseren alten Denk- und Verhaltensmustern. Diese sind geprägt durch Phänomene wie verzerrte Wahrnehmung oder (Selbst-)Überschätzung. Dieses Buch leistet einen Beitrag zum kompetenten Umgang mit Unsicherheit. Mithilfe von psychologischem Wissen werden Denkprozesse und Interaktionen besser verständlich gemacht, um künftig reflektierter (re-)agieren zu können. Das Buch ist ein Plädoyer für eine neue Aufklärung mit einem Appell an die individuelle Verantwortlichkeit, sich seines Verstandes zu bedienen.
This book offers a multidisciplinary perspective on perceived safety. It discusses the concept of safety from engineering, philosophy, and psychology angles, and considers various definitions of safety and its relationship to risk. Examining the categorization of safety and the measurement of risk, risk cultures, basic human needs and decision-making under uncertainty, the contributions demonstrate the practical implications and applications in areas such as health behavior, aviation and sports.
Topics covered include:
What is “safety” and is there “optimal safety” in engineering?
Philosophical perspectives on safety and risk
Psychological perspectives on perceived safety: social factors of feeling safe
Psychological perspectives on perceived safety: zero-risk bias, feelings & learned carelessness
Perception of aviation safety
Intended for both practitioners and academic researchers, this book appeals to anyone interested in decision-making and the perception and establishment of safety.
In this section a definition of the term “safety” based on freedom of resources is introduced. Such freedom of resources can also be used for the definition of the terms “danger” and “disaster”. Additionally, the terms “safety”, “danger” and “disaster” can be correlated to time horizons of planning. The introduced relationships will then be used for the discussion whether “optimal safety” is achievable or not. Currently, “optimal safety” is being intensively discussed in many disciplines such as the field of structural safety. Considering the definition of “safety”, this paper will show that “optimal safety” is rather a theoretical issue and cannot be achieved under real world conditions. This statement fits very well not only to considerations in the field of system theory, but also to empirical observations. It is suggested that the term “optimal safety” is introduced as an assurance measure for engineers rather than for the public. As a solution the concept of integral risk management is introduced. One of the properties of this concept is the possibility of continuous improvement and therefore no optimal solution is claimed.
Risks can be categorized and ranked based on different characteristics. Such characteristics can be causes of damages or consequences or magnitudes of risks. Categorizations may improve the understanding of risks and, even more importantly, may help decision-makers to deal properly with risks in terms of risk-informed decisions. However, it has often been shown that the categorization of risks cannot be completed because the definition of risks is challenging and the size of the risks depends strongly on the choice of risk parameter and context. For example, many statistical investigations have shown that health risks are of utmost importance for human lives since 95% of all deaths in developed countries are related to health problems. Other risk studies reveal that the greatest risks to humans are social failures such as war or unemployment since many health issues are related to social failures. Such categorizations are even more difficult for emerging risks related to new technologies or current changes in social systems. For such systems, experience and therefore statistical data is still missing. Additionally, some of these systems belong to the class of complex systems with unknown causal chains.
Risk is a very complex construct and, as such, can be studied from various perspectives. In the present chapter we discuss the influences of answer format on risk assessment, the chosen perspective from which a risk is assessed and describe two systems of probabilistic reasoning. Although many different measurements exist today, there is no clear methodological advice as to which kind of instrument is appropriate in a given context. As a suggestion, we present the risk assessment matrix (RAM), a model developed to explore the impact of both answer format and risk perspective on risk assessment. The RAM combines both factors and addresses the question of how the measurement of subjective perceived risk is influenced by psychological factors triggered by methodological aspects.
Cognitive–experiential self-theory integrates the cognitive and the psychodynamic unconscious by assuming the existence of two parallel, interacting modes of information processing: a rational system and an emotionally driven experiential system. Support for the theory is provided by the convergence of a wide variety of theoretical positions on two similar processing modes; by real-life phenomena—such as conflicts between the heart and the head; the appeal of concrete, imagistic, and narrative representations; superstitious thinking; and the ubiquity of religion throughout recorded history—and by laboratory research, including the prediction of new phenomena in heuristic reasoning.
The authors argue that alternatives to the traditional numeric methods of measuring people's uncertainty may prove to hold important advantages under some conditions. In 3 experiments, the authors compared verbal measures involving responses such as very likely, and numeric measures involving responses such as 80% chance. The verbal measures were found to show more sensitivity to various manipulations affecting psychological uncertainty (Experiment 1), to be better predictors of individual preferences among options with unknown outcomes (Experiment 2), and to be better predictors of behavioral intentions (Experiment 3). Results suggest that numeric measures tend to elicit deliberate and rule-based reasoning from respondents, whereas verbal measures allow for more associative and intuitive thinking. Given that there may be many types of situations in which human decisions and behaviors are not based on deliberate and rule-based thinking, numeric measures may misrepresent how individuals think about uncertainty in those situations. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The present research examined the influence of different risk perspectives by the use of four different target persons (who could be affected: abstract person, self, specific person, and specific others) and of four different questionnaire answer formats (rating, open percentage, open, and closed frequency) on risk assess-ments. It was assumed that subjects use two different systems in terms of proba-bilistic reasoning: a distributional approach for abstract targets leading to higher risk estimates and a singular approach for specific targets leading to lower risk assessments. According to unrealistic optimism (UO) research (showing higher risk assessments for an abstract person than for self), the assumption was that risk assessments for a specific (named) target lead to lower risk assessments compared to an abstract target. Further, common quantitative answer formats for assessing risk were compared to explore differences in risk estimates. The hypotheses were tested using data of a sample of 512 students from a Bavarian university. The frequently confirmed finding of UO could be replicated with both rating scale and open frequency scale, which appeared to be more sensitive compared to the other used scales. However, UO disappeared when the compari-son target was specific. Further, risk assessments for an abstract target were highest within every answer format and lowest for specific targets. Furthermore, results revealed that the type of answer format has a moderating effect on the extent of the influence of risk perspective on risk assessments. Overall, this study gives evidence that both the chosen scale and the risk perspective strongly influence risk assessments. Results aim to contribute to the research fields of quantitative assessment of perceived risk. They suggest that probabilistic reason-ing in regard to risk not only underlies motivational or cognitive ego-defensive mechanisms but is rather presumably caused by the use of different systems of inferential strategies.
Life is full of risky decisions, from the mundane to matters of life or death. Individuals differ in the risks they accept (or even deliberately embrace). However, risk taking is not a single trait but is a behavior influenced by characteristics of the situation (what the decision is about and to what extent it engages affect vs. deliberation), the decision maker (age and gender), and interactions between situation and decision maker. Understanding the mechanisms behind risk taking—or who takes risks when and why—is particularly important when the goal is to influence and modify the behavior.
Self-reports of behaviors and attitudes are strongly influenced by features of the research instrument, including question wording, format, and context. Recent research has addressed the underlying cognitive and communicative processes, which are systematic and increasingly well- understood. I review what has been learned, focusing on issues of question comprehension, behavioral frequency reports, and the emergence of context effects in attitude measurement. The accumulating knowledge about the processes underlying self-reports promises to improve questionnaire design and data quality.
Previous studies have shown that people who have not been victimized by negative life events tend to perceive themselves as less vulnerable than others to victimization. The present 2 studies examined the conditions under which Ss' judgments of others' vulnerability would differ from judgments of their own vulnerability. In Study 1, 101 undergraduates saw vague comparison targets (either the average person or the average college student) as more vulnerable than themselves to 10 negative events. In contrast, Ss perceived a specific target (their closest friend, sibling, or same-sex parent) as equally invulnerable as themselves. In Study 2, 190 Ss who were instructed to consider a vague, abstract target (either the average college student or one of their friends) made downward comparisons, choosing a real or hypothetical other who was especially vulnerable to a particular event. Ss who were instructed to consider a specific, concrete target (their closest friend) perceived no self–other differences in risk status. It is concluded that when given the opportunity, Ss actively engage in downward comparisons, thereby seeing themselves as relatively invulnerable. Whereas vague targets facilitate downward comparisons, specific targets make such comparisons more difficult. Both cognitive and motivational mechanisms underlying such downward comparisons are discussed. (29 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
In Study 1, over 200 college students estimated how much their own chance of experiencing 42 events differed from the chances of their classmates. Overall, Ss rated their own chances to be significantly above average for positive events and below average for negative events. Cognitive and motivational considerations led to predictions that degree of desirability, perceived probability, personal experience, perceived controllability, and stereotype salience would influence the amount of optimistic bias evoked by different events. All predictions were supported, although the pattern of effects differed for positive and negative events. Study 2 with 120 female undergraduates from Study 1 tested the idea that people are unrealistically optimistic because they focus on factors that improve their own chances of achieving desirable outcomes and fail to realize that others may have just as many factors in their favor. Ss listed the factors that they thought influenced their own chances of experiencing 8 future events. When such lists were read by a 2nd group of Ss, the amount of unrealistic optimism shown by this 2nd group for the same 8 events decreased significantly, although it was not eliminated. (22 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The theory of downward comparison posits that persons experiencing negative affect can enhance their subjective well-being through comparison with a less fortunate other, the process occurring on either a passive or active basis. The present author discusses the basic principle of downward comparison and its corollaries and suggests that these represent the motivational process for phenomena observed in several areas of social psychology. Evidence is considered from studies of the fear-affiliation effect, choice of others for social comparison, scapegoating, projection, aversive environmental events and attraction toward others, social prejudice, hostile aggression, and humor. It is shown that downward comparison principles encompass empirical evidence from these areas, account for nonreplications as well as confirmatory findings, and provide a theoretical basis for the relation among the various phenomena. (111 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Four experiments examined differences in probabilistic reasoning as a function of whether problems were presented in a frequentist or case-specific form. The experiments demonstrated that these different forms influence the likelihood of Ss committing the conjunction and disjunction fallacies. The authors contend that these 2 forms elicit different approaches to probability. Frequency problems, it is argued, elicit a distributional approach in which probabilities are equated with relative frequencies, whereas case-specific problems elicit a singular approach in which probabilities are equated with the propensities or causal forces operating in an individual case. According to this account, distributional and singular approaches evoke different kinds of inferential rules and heuristic procedures, some of which are more closely aligned with extensional principles than others. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
We conducted three studies to investigate how well pictographs communicate medical screening information to persons with higher and lower numeracy skills. In Study 1, we conducted a 2 (probability level: higher vs. lower) x 2 (reference information: yes vs. no) x 2 (subjective numeracy: higher vs. lower) between-subjects design. Persons with higher numeracy skills were influenced by probability level but not by reference information. Persons with lower numeracy tended to differentiate between a higher and a lower probability when there was no reference information. Study 2 consisted of interviews about the mental processing of pictographs. Higher numeracy was associated with counting the icons and relying on numbers depicted in the graph. Study 3 was an experiment with the same design as in Study 1, but, rather than using reference information, we varied the sequence of task type (counting first vs. non-counting first) to explore the role of the focus on numerical information. Persons with lower numeracy differentiated between higher and lower risk only when they were in the non-counting first condition. Task sequence did not influence the risk perceptions of persons with higher numeracy. In sum, our results suggest that pictographs may be useful for persons with higher and lower numeracy. However, these groups seem to process the graph differently. Persons with higher numeracy rely more on the numerical information depicted in the graph, whereas persons with lower numeracy seem to be confused when they are guided towards these numbers.
A robust finding in social psychology is that people judge negative events as less likely to happen to themselves than to the average person, a behavior interpreted as showing that people are “unrealistically optimistic” in their judgments of risk concerning future life events. However, we demonstrate how unbiased responses can result in data patterns commonly interpreted as indicative of optimism for purely statistical reasons. Specifically, we show how extant data from unrealistic optimism studies investigating people's comparative risk judgments are plagued by the statistical consequences of sampling constraints and the response scales used, in combination with the comparative rarity of truly negative events. We conclude that the presence of such statistical artifacts raises questions over the very existence of an optimistic bias about risk and implies that to the extent that such a bias exists, we know considerably less about its magnitude, mechanisms, and moderators than previously assumed.
We review the growing literature on health numeracy, the ability to understand and use numerical information, and its relation to cognition, health behaviors, and medical outcomes. Despite the surfeit of health information from commercial and noncommercial sources, national and international surveys show that many people lack basic numerical skills that are essential to maintain their health and make informed medical decisions. Low numeracy distorts perceptions of risks and benefits of screening, reduces medication compliance, impedes access to treatments, impairs risk communication (limiting prevention efforts among the most vulnerable), and, based on the scant research conducted on outcomes, appears to adversely affect medical outcomes. Low numeracy is also associated with greater susceptibility to extraneous factors (i.e., factors that do not change the objective numerical information). That is, low numeracy increases susceptibility to effects of mood or how information is presented (e.g., as frequencies vs. percentages) and to biases in judgment and decision making (e.g., framing and ratio bias effects). Much of this research is not grounded in empirically supported theories of numeracy or mathematical cognition, which are crucial for designing evidence-based policies and interventions that are effective in reducing risk and improving medical decision making. To address this gap, we outline four theoretical approaches (psychophysical, computational, standard dual-process, and fuzzy trace theory), review their implications for numeracy, and point to avenues for future research.
Four studies were conducted with college student subjects to examine: (1) perceptions of susceptibility to health and safety risks; (2) factors that subjects see as important in determining their susceptibility; and (3) subjects' actual standing on objective risk factors. Subjects were generally unbiased about hereditary risk factors and were even somewhat pessimistic about environmental risk factors. Their views of their own actions and psychological attributes, however, were excessively optimistic. Few acknowledged actions or psychological attributes that increased their risk. This pattern of findings helps to explain why risks thought to be controllable (i.e., preventable by personal action) are likely to evoke unrealistic optimism about susceptibility. Family histories of health problems were incorporated into judgments of susceptibility, but, except for smoking, correlations between behavioral risk factors and judgments of susceptibility were surprisingly weak. Self-esteem enhancement is suggested as a motive that could explain many of the present findings. Several recommendations are offered for health campaigns that seek to produce more realistic perceptions of susceptibility to health and safety problems.
Using a self-administered questionnaire, 149 respondents rated service elements associated with a recently visited store or restaurant on scales that differed only in the number of response categories (ranging from 2 to 11) and on a 101-point scale presented in a different format. On several indices of reliability, validity, and discriminating power, the two-point, three-point, and four-point scales performed relatively poorly, and indices were significantly higher for scales with more response categories, up to about 7. Internal consistency did not differ significantly between scales, but test-retest reliability tended to decrease for scales with more than 10 response categories. Respondent preferences were highest for the 10-point scale, closely followed by the seven-point and nine-point scales. Implications for research and practice are discussed.
Most people, experts included, have difficulties understanding and combining statistical information effectively. Hoffrage et al. demonstrate that these difficulties can be considerably reduced by communicating the information in terms of natural frequencies rather than in terms of probabilities. Several applications in medicine, legal decision-making, and education are discussed.
Numeracy, how facile people are with basic probability and mathematical concepts, is associated with how people perceive health risks. Performance on simple numeracy problems has been poor among populations with little as well as more formal education. Here, we examine how highly educated participants performed on a general and an expanded numeracy scale. The latter was designed within the context of health risks.
A total of 463 men and women aged 40 and older completed a 3-item general and an expanded 7-item numeracy scale. The expanded scale assessed how well people 1) differentiate and perform simple mathematical operations on risk magnitudes using percentages and proportions, 2) convert percentages to proportions, 3) convert proportions to percentages, and 4) convert probabilities to proportions.
On average, 18% and 32% of participants correctly answered all of the general and expanded numeracy scale items, respectively. Approximately 16% to 20% incorrectly answered the most straightforward questions pertaining to risk magnitudes (e.g., Which represents the larger risk: 1%, 5%, or 10%?). A factor analysis revealed that the general and expanded risk numeracy items tapped the construct of global numeracy.
These results suggest that even highly educated participants have difficulty with relatively simple numeracy questions, thus replicating in part earlier studies. The implication is that usual strategies for communicating numerical risk may be flawed. Methods and consequences of communicating health risk information tailored to a person's level of numeracy should be explored further.
Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational limitations, (3) the wrong norm being applied by the experimenter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the model response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implications of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance errors are a minor factor in the gap; computational limitations underlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Unexpected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.
Early studies of intuitive judgment and decision making conducted with the late Amos Tversky are reviewed in the context of two related concepts: an analysis of accessibility, the ease with which thoughts come to mind; a distinction between effortless intuition and deliberate reasoning. Intuitive thoughts, like percepts, are highly accessible. Determinants and consequences of accessibility help explain the central results of prospect theory, framing effects, the heuristic process of attribute substitution, and the characteristic biases that result from the substitution of nonextensional for extensional attributes. Variations in the accessibility of rules explain the occasional corrections of intuitive judgments. The study of biases is compatible with a view of intuitive thinking and decision making as generally skilled and successful.
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.
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.
Self-reported influenza vaccination.
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.
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.
Five studies showed that people assess vulnerability to future controllable negative life events differently depending on whether it concerns: (a) generalized targets (e.g., the average peer), or (b) concrete and familiar targets (self or nonself). In the former case, adistributionalframework is applied which focuses on available statistical information such as groups’ base-rates. In the latter case, people apply asingularjudgmental perspective and focus on available individuating information such as personal dispositions and preventive actions. This perspective would typically lead to an optimistic bias in favor of concrete and familiar rather than generalized targets. Participants in Study 1 evaluated both self's and a spontaneously selected (non-intimate) peer's risk prospects as lower than those of their average peer in controllable but not uncontrollable future events or controllable and uncontrollable everyday negative events. Study 2 replicated the main findings in direct comparative judgments. In Study 3, verbal accounts and a measure of interest in the base-rate supported the singular-distributional analysis. In Studies 4 and 5, an optimistic bias was found in favor of a randomly assigned member of their small group to whom participants were yoked. These findings suggest that in addition to the classic “illusion of unique invulnerability” (e.g., Perloff & Fetzer, 1986), whereby participants judge themselves to be less vulnerable than the average group-member, there is an “illusion ofnonuniqueinvulnerability,” whereby participants judge also their singular group-members to be less vulnerable than the average group-member. Finally we discuss conditions in which apessimisticrather than the standard optimistic bias might occur in comparative risk comparisons.
Many descriptions of states of affairs or beliefs are quantified. Quantification in its most general sense involves the use of numbers and proportions (e.g., 3,2%) and more typically a whole host of natural language expressions, including quantifiers (a few, some, most), quantifying frequency adverbs (sometimes, often, usually), and probability expressions (possibly, likely), among others. It may be the case that when they are used, such expressions play the role of numerical descriptions without requiring the exactness of numbers. Sometimes this is true, and such an approach has led to research on how the mapping between verbal descriptions and decisions under risk, particularly using probability or likelihood expressions (e.g., Budescu, Weinberg, & Wallsten, 1988; Rapoport, Wallsten, Erev, & Cohen, in press). The results of these studies show that numerical information is more accurate than that information conveyed by a verbal expression and is consistent with the view that quantifiers do not denote single values but instead specify ranges, which are describable as membership functions on probability or frequency continua. Obviously, the same argument can be made for the importance of ranges with quantifying determiners (see Moxey, 1986): A word such as “many” can be thought of as denoting a range that the user has in mind, for instance.
Recent findings on construal level theory (CLT) suggest that abstract thinking leads to a lower estimated probability of an event occurring compared to concrete thinking. We applied this idea to the risk context and explored the influence of construal level (CL) on the overestimation of small and underestimation of large probabilities for risk estimates concerning a vague target person (Study 1 and Study 3) and personal risk estimates (Study 2). We were specifically interested in whether the often-found overestimation of small probabilities could be reduced with abstract thinking, and the often-found underestimation of large probabilities was reduced with concrete thinking. The results showed that CL influenced risk estimates. In particular, a concrete mindset led to higher risk estimates compared to an abstract mindset for several adverse events, including events with small and large probabilities. This suggests that CL manipulation can indeed be used for improving the accuracy of lay people's estimates of small and large probabilities. Moreover, the results suggest that professional risk managers' risk estimates of common events (thus with a relatively high probability) could be improved by adopting a concrete mindset. However, the abstract manipulation did not lead managers to estimate extremely unlikely events more accurately. Potential reasons for different CL manipulation effects on risk estimates' accuracy between lay people and risk managers are discussed.
© 2015 Society for Risk Analysis.
The Feeling of Risk brings together the work of Paul Slovic, one of the world's leading analysts of risk, to describe the extension of risk perception research into the first decade of this new century. In this collection of important works, Paul Slovic explores the conception of 'risk as feelings' and examines the interaction of feeling and cognition in the perception of risk. He also examines the elements of knowledge, cognitive skill, and communication necessary for good decisions in the face of risk. The first section of the book looks at the difficulty of understanding risk without an emotional component, for example that disaster statistics lack emotion and thus fail to convey the true meaning of disasters and fail to motivate proper action to prevent them. The book also highlights other important perspectives on risk arising from cultural worldviews and concerns about specific hazards pertaining to blood transfusion, biotechnology, prescription drugs, smoking, terrorism, and nanotechnology. Following on from The Perception of Risk (2000), this book presents some of the most significant research on risk perception in recent years, providing essential lessons for all those involved in risk perception and communication.
Many health and safety problems, including war and terrorism, are by-products of how people reason about risk. I describe a new approach to reasoning about risk that implements a modern dual-process model of memory called fuzzy-trace theory. This approach posits encoding of both verbatim and gist representations, with reliance on the latter whenever possible; dependence of reasoning on retrieval cues that access stored values and principles; and vulnerability of reasoning to processing interference from overlapping classes of events, which causes denominator neglect in risk or probability judgments. These simple principles explain classic and new findings, for example, the finding that people overestimate small risks but ignore very small risks. Fuzzy-trace theory differs from other dual-process approaches to reasoning in that it places intuition at the apex of development, considering fuzzy intuitive processing more advanced than precise computational processing (e.g., trading off risks and rewards). The theory supplies a conception of rationality that distinguishes degrees of severity of errors in reasoning. It also includes a mechanism for achieving consistency in reasoning, a hallmark of rationality, by explaining how a person can treat superficially different reasoning problems in the same way if the problems share an underlying gist.
Early studies of intuitive judgment and decision making conducted with the late Amos Tversky are reviewed in the context of two related concepts: an analysis of accessibil-ity, the ease with which thoughts come to mind; a distinc-tion between effortless intuition and deliberate reasoning. Intuitive thoughts, like percepts, are highly accessible. De-terminants and consequences of accessibility help explain the central results of prospect theory, framing effects, the heuristic process of attribute substitution, and the charac-teristic biases that result from the substitution of nonexten-sional for extensional attributes. Variations in the accessi-bility of rules explain the occasional corrections of intuitive judgments. The study of biases is compatible with a view of intuitive thinking and decision making as generally skilled and successful.
The risk of an event generally relates to its expected severity and the perceived probability of its occurrence. In risk research, however, there is no standard measure for subjective probability estimates. In this study, we compared five commonly used measurement formats-two rating scales, a visual analog scale, and two numeric measures-in terms of their ability to assess subjective probability judgments when objective probabilities are available. We varied the probabilities (low vs. moderate) and severity (low vs. high) of the events to be judged as well as the presentation mode of objective probabilities (sequential presentation of singular events vs. graphical presentation of aggregated information). We employed two complementary goodness-of-fit criteria: the correlation between objective and subjective probabilities (sensitivity), and the root mean square deviations of subjective probabilities from objective values (accuracy). The numeric formats generally outperformed all other measures. The severity of events had no effect on the performance. Generally, a rise in probability led to decreases in performance. This effect, however, depended on how the objective probabilities were encoded: pictographs ensured perfect information, which improved goodness of fit for all formats and diminished this negative effect on the performance. Differences in performance between scales are thus caused only in part by characteristics of the scales themselves-they also depend on the process of encoding. Consequently, researchers should take the source of probability information into account before selecting a measure.
In contrast to the research of W. K. Viscusi on the overestimation of the risks of smoking, the author presents a counterview based on cognitive psychology that demonstrates the powerful influence of experiential thinking and affect on judgment and decision making. Findings of a series of diverse studies are integrated to illustrate the operation of the affect heuristic in judgments of risk and benefit. Next, Viscusi's (1992) account of young people's overestimation of smoking risks is summarized and refuted. Evidence is presented from data collected in the second Annenberg Tobacco Survey of 14–22 yr olds and 23–95 yr olds that supports the view that smokers' short-term perspectives and underestimation of the grip of addiction indicates that experiential and affective forces are leading young people to make smoking decisions that they later regard as mistakes. These data are also used to show that Viscusi's quantitative risk estimates are unreliable, and that individuals are not acting rationally when they initiate smoking, thus repudiating the model of informed rational choice. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Investigated unrealistic optimism and illusion of control as they relate to the personal probability of encountering negative events in the area of perceived accident involvement. Whereas optimism refers to a generalized expectancy for positive outcomes independent of the source of the outcomes, the illusion of control locates the source of the expected outcome in terms of personal control. By examining conditions in which personal control was either present or absent in 2 studies with 33 university students and 127 staff, it was possible to distinguish between the 2 positions. Clear evidence was found in favor of the illusion of control with little evidence in favor of unrealistic optimism. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Over the past twenty years, risk communication researchers and practitioners have learned some lessons, often at considerable personal price. For the most part, the mistakes that they have made have been natural, even intelligent ones. As a result, the same pitfalls may tempt newcomers to the field. This essay offers a personal (even confessional) history of the field over this period. It identifies a series of developmental stages. Progress through the stages involves consolidating the skills needed to execute it and learning its limitations. Knowing about their existence might speed the learning process and alert one to how much there still is to learn.
Questionnaires using Likert-type rating scales are an important source of data in marketing research. Researchers use different rating scale formats with varying numbers of response categories and varying label formats (e.g., 7-point rating scales labeled at the endpoints, fully labeled 5-point scales, etc.) but have few guidelines when selecting a specific format. Drawing from the literature on response styles, we formulate hypotheses on the effect of the labeling of response categories and the number of response categories on the net acquiescence response style, extreme response style and misresponse to reversed items. We test the hypotheses in an online survey (N = 1207) with eight experimental conditions and a follow-up study with two experimental conditions (N = 226). We find evidence of strong effects of scale format on response distributions and misresponse to reversed items, and we formulate recommendations on the choice of a scale format.
To examine the influence of numeracy on interpreting various risk communication formats.
. A random sample of women (N = 266) completed a questionnaire assessing numeracy and risk perception of prenatal test results and results of colon cancer screening tests. The authors examined the relationships between risk level (high v. low) and format of risk presentation (ratio, pictogram, or Paling Perspective Scale) and whether these relationships differed based on the numeracy skills of the participant.
The authors identified a significant (P<0.001) 3-way interaction between format, risk level, and numeracy: high-numerate participants in the low-risk group perceived the test results as less risky compared with participants in the high-risk group (P < 0.001) with the Paling Perspective Scale but not with the other formats. For low-numerate participants, they did not observe differences between low- and high-risk scenarios for any of the 3 formats. The results were similar for the Down syndrome and colon cancer scenarios. Overall, the pictogram resulted in significantly lower risk ratings compared with the Paling Perspective Scale and the ratio with numerator 1 (P < 0.001).
Different communication formats may produce different risk perceptions, but the effect is qualified by patients' numeracy skills.
Communicating probability information about risks to the public is more difficult than might be expected. Many studies have examined this subject, so that their resulting recommendations are scattered over various publications, diverse research fields, and are about different presentation formats. An integration of empirical findings in one review would be useful therefore to describe the evidence base for communication about probability information and to present the recommendations that can be made so far. We categorized the studies in the following presentation formats: frequencies, percentages, base rates and proportions, absolute and relative risk reduction, cumulative probabilities, verbal probability information, numerical versus verbal probability information, graphs, and risk ladders. We suggest several recommendations for these formats. Based on the results of our review, we show that the effects of presentation format depend not only on the type of format, but also on the context in which the format is used. We therefore argue that the presentation format has the strongest effect when the receiver processes probability information heuristically instead of systematically. We conclude that future research and risk communication practitioners should not only concentrate on the presentation format of the probability information but also on the situation in which this message is presented, as this may predict how people process the information and how this may influence their interpretation of the risk.
Cognitive-experiential self-theory integrates the cognitive and the psychodynamic unconscious by assuming the existence of two parallel, interacting modes of information processing: a rational system and an emotionally driven experiential system. Support for the theory is provided by the convergence of a wide variety of theoretical positions on two similar processing modes; by real-life phenomena--such as conflicts between the heart and the head; the appeal of concrete, imagistic, and narrative representations; superstitious thinking; and the ubiquity of religion throughout recorded history--and by laboratory research, including the prediction of new phenomena in heuristic reasoning.
Clinicians and researchers often wish to know how patients perceive the likelihoods of health risks. Little work has been done to develop and validate scales and formats to measure perceptions of event probabilities, particularly low probabilities (i.e., <1%).
To compare a new visual analog scale with three benchmarks in terms of validity and reliability.
Survey with retest after approximately two weeks. Respondents estimated the probabilities of six events with the new scale, which featured a "magnifying glass" to represent probabilities between 0 and 1% on a logarithmic scale. Participants estimated the same probabilities on three benchmarks: two linear visual analog scales (one labeled with words, one with numbers) and a "1 in x" scale.
100 veterans and family members and 107 university faculty and students.
For each scale, the authors assessed: 1) validity-the correlation between participants' direct rankings (i.e., numbering them from 1 to 6) and scale-derived rankings of the relative probabilities of six events; 2) test-retest reliability-the correlation of responses from test to retest two weeks later; 3) usability (missing/ incorrect responses, participant evaluation).
Both the magnifier and the two linear scales outperformed the "1 in x" scale on all criteria. The magnifier scale performed about as well as the two linear visual analog scales for validity (correlation between direct and scale-derived rankings = 0.72), reliability (test-retest correlation = 0.55), and usability (2% missing or incorrect responses, 65% rated it easy to use). 62% felt the magnifier scale was a "very good or good" indicator of their feelings about chance. The magnifier scale facilitated expression of low-probability judgments. For example, the estimated chance of parenting sextuplets was orders of magnitude lower on the magnifier scale (median perceived chance 10(-5)) than on its linear counterpart (10(-2)). Participants' assessments of high-probability events (e.g., chance of catching a cold in the next year) were not affected by the presence of the magnifier.
The "1 in x" scale performs poorly and is very difficult for people to use. The magnifier scale and the linear number scale are similar in validity, reliability, and usability. However, only the magnifier scale makes it possible to elicit perceptions in the low-probability range (<1%).
Modern theories in cognitive psychology and neuroscience indicate that there are two fundamental ways in which human beings comprehend risk. The "analytic system" uses algorithms and normative rules, such as probability calculus, formal logic, and risk assessment. It is relatively slow, effortful, and requires conscious control. The "experiential system" is intuitive, fast, mostly automatic, and not very accessible to conscious awareness. The experiential system enabled human beings to survive during their long period of evolution and remains today the most natural and most common way to respond to risk. It relies on images and associations, linked by experience to emotion and affect (a feeling that something is good or bad). This system represents risk as a feeling that tells us whether it is safe to walk down this dark street or drink this strange-smelling water. Proponents of formal risk analysis tend to view affective responses to risk as irrational. Current wisdom disputes this view. The rational and the experiential systems operate in parallel and each seems to depend on the other for guidance. Studies have demonstrated that analytic reasoning cannot be effective unless it is guided by emotion and affect. Rational decision making requires proper integration of both modes of thought. Both systems have their advantages, biases, and limitations. Now that we are beginning to understand the complex interplay between emotion and reason that is essential to rational behavior, the challenge before us is to think creatively about what this means for managing risk. On the one hand, how do we apply reason to temper the strong emotions engendered by some risk events? On the other hand, how do we infuse needed "doses of feeling" into circumstances where lack of experience may otherwise leave us too "coldly rational"? This article addresses these important questions.
The weather forecast says that there is a "30% chance of rain," and we think we understand what it means. This quantitative statement is assumed to be unambiguous and to convey more information than does a qualitative statement like "It might rain tomorrow." Because the forecast is expressed as a single-event probability, however, it does not specify the class of events it refers to. Therefore, even numerical probabilities can be interpreted by members of the public in multiple, mutually contradictory ways. To find out whether the same statement about rain probability evokes various interpretations, we randomly surveyed pedestrians in five metropolises located in countries that have had different degrees of exposure to probabilistic forecasts--Amsterdam, Athens, Berlin, Milan, and New York. They were asked what a "30% chance of rain tomorrow" means both in a multiple-choice and a free-response format. Only in New York did a majority of them supply the standard meteorological interpretation, namely, that when the weather conditions are like today, in 3 out of 10 cases there will be (at least a trace of) rain the next day. In each of the European cities, this alternative was judged as the least appropriate. The preferred interpretation in Europe was that it will rain tomorrow "30% of the time," followed by "in 30% of the area." To improve risk communication with the public, experts need to specify the reference class, that is, the class of events to which a single-event probability refers.
Results of past research suggest that affect plays an important role in risk perception. Because affect may also increase the availability of risks, affect and availability are closely related concepts. Three studies tested the hypothesis that evoking negative affect (fear), either through past experience or through experimental manipulation, results in greater perceived risk. The present research focused on perception of flooding risk. Study 1 and Study 2 showed that participants who received risk information concerning a longer time period (e.g., 30 years) perceived more danger compared with participants who received risk information for one year. Study 2 showed that the interpretation of risk information was influenced by participants' own experiences with flooding. In Study 3, affect was experimentally manipulated. After looking at photographs depicting houses in a flooded region, participants perceived greater risk compared with participants in a control group. Taken together, the results of these three studies suggest that affect is important for successful risk communication. Results of the present research are in line with the affect heuristic proposed by Slovic and colleagues.
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