# Conceptualizing and Measuring Risk Perceptions Workshop

## February 13-14, 2003

**Embassy Suites at the Chevy Chase Pavilion, Washington, DC**

**Summary of Discussion Sessions**

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# Conceptualizing and Measuring Risk Perceptions: Looking More Deeply Into the Influences of Risk Perceptions on Health Decisions and Behaviors

*Neil Weinstein, Ph.D.*

*Professor, Department of Human Ecology, Rutgers University*

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# Discussion

# 

# Dr. Greenwald noted that there likely are individual differences among subjects in terms of objective likelihood because they were outdoors more or were in settings where they might get bitten by a tick. However, it also may be that there is a subjective factor that is totally independent of any objective likelihood. Dr. Weinstein replied that study subjects live in high-risk counties and are homeowners rather than apartment dwellers. Nevertheless, there are individuals who garden/do not garden, take walks/do not take walks, etc., so there are differences in objective risk. Dr. Weinstein and colleagues have a series of questions on these issues, but have not yet tried to relate them to vaccination behavior.

# 

# Dr. Millstein reported that she often refers to the "50-50 blip" when subjects give an excess of responses. The 2-point verbal scale appears to be a natural way that people think about risk because they tend not to think on a population basis. Individuals generally think to themselves "the risk is going to happen," or "the risk is not going to happen," partly leading to the "50-50 blip," and this phenomenon may be closer to the type of natural measure seen in the study by Dr. Weinstein and colleagues. Dr. Weinstein indicated that more data are needed, and that in these types of studies, what subjects tell researchers about what they think is not necessarily all that they can think, and there may be some difficulty related to subjects expressing their thoughts. 

# 

# Dr. Slovic asked about the perception of benefit from an activity, noting that there is evidence that risk and benefit sometimes are confounded in people's minds. Dr. Weinstein explained that this is an empirical question dealing with how people conceptualize risk and what they combine and keep separate. His goal for this area of research is to more accurately understand how people think about hazards so that interventions can be identified or developed to help them avoid suffering from a hazard. If the benefits cannot be split from the risks in terms of people's conceptualization, then they should not be removed from consideration. 

# There are risk perception differences between the kind of behaviors people enjoy doing (e.g., smoking) and issues where there are avoidance motivations (e.g., getting Lyme disease), Dr. Cameron explained. When examining risk, researchers should consider whether they are assessing the risk of an illness or hazard versus the riskiness of a type of behavior in which individuals might want to participate. It appears that these situations have different variables, such as benefits, that are operational.

# 

# Dr. Rimer asked whether providing study subjects with statistics distracts them in some fundamental way from thinking about what those numbers mean. A recent review on informed decisionmaking found that people were less influenced when they were given specific risk numbers, such as the Gail model score for breast cancer. Individuals may react more on a "gut" level when they are in "likely/unlikely" scenarios and are not presented with statistical information. Subjects may become distracted by numbers, and as a result may consider factors not related to their behavior. This area requires a greater level of understanding. Dr. Weinstein added that there also may be a significant difference between how people think and how the research community can communicate to them. There may be instances where researchers are not able to communicate a depth of information in a useful way.

# 

# From a psychometric standpoint, one consideration is that when giving study subjects a 7-point scale, it may only function as a 2-point scale based on subjects' cognitive abilities (e.g., perhaps the anchors are not clear, perhaps subjects clearly think the issue is a yes/no issue), Dr. Masse explained. When study populations do not function at the level of measurement scales, it adds measurement error into analyses. 

# Dr. Cappella asked whether researchers constrain themselves if they start to think about risk only as a single measure (e.g., as a scale, regardless of its complexity or simplicity, that is going to predict an outcome), versus considering risk in a more complex way that involves aspects of risk behind a judgment that are activated from time to time and from circumstance to circumstance. Risk may be a fairly temporary and transient type of measure at a point in time that gets activated based on components of the cognitive map associated with risk that a person has at a given juncture in terms of consequences and other factors. Should researchers tie themselves to a notion of a single scale that would be most efficient and allow them to predict subsequent behavior easily and readily, but at the same time possibly create a significant mismatch between the way people think about risk and how they actually process risk at a given point in time? Dr. Weinstein noted that the population in the study on Lyme disease vaccination was well aware of the risk because they live in an area where it is always present. He cautioned that researchers must be careful about conflating probability judgments with all of the other dimensions associated with risk.

Dr. Croyle commented that an interesting empirical study would be to
examine the parallel between these data, where subjects appear to
dichotomize into likely/unlikely scenarios. One hypothesis is that
people's lumping of their risk construct maps onto how much they can
lump the phenomenon that they are trying to perceive. Subjects might use
the most parsimonious mental risk model that matches the phenomenon. In
this case, people are lumping into a dichotomous mental construct
because the phenomenon is dichotomous (i.e., Lyme disease/no Lyme
disease; vaccinated, not vaccinated). However, if the study was asking
about the progression over time for a chronic disease like diabetes,
there is not a dichotomous frame with the phenomenon or the problem (it
is not a yes/no, have it/do not have it type of scenario), and therefore
subjects will be less likely to dichotomize. They will use the most
parsimonious mental model of risk that still allows them to map onto the
phenomena. Dr. Croyle added that as the phenomena in question becomes
more complex, individuals are less likely to say that the scenario will
or will not happen. Rather, they will construct something more complex,
but it always is going to be the most minimally complex mental model
that will work in that situation.

# Applied Science: Population-Level Health Promotion Programs

*Brian Flynn, Sc.D.*

*Associate Director, Office of Health Promotion Research, University of
Vermont*

# Discussion

Dr. Weinstein asked if the people who are left performing the risky
behavior when Dr. Flynn and colleagues enter the field are tolerant of
the risk or have very strong denial mechanisms. Individuals who are
responsive to the risk already have changed their behavior, leaving
those on the resistive end of the distribution. An incorrect
conclusion---that the risk is never important---could be formed in this
instance (however, the risk might be very important at a different
time). Dr. Flynn agreed, noting that by the time he and his associates
get into the field, those individuals who are continuing to smoke
cigarettes have survived a great deal of risk information; they have
been bombarded through multiple media outlets with information about the
risks of smoking. Those individuals who are ready to change once they
are able to get adequate information and process it rationally (and who
have the discipline to make the change) already have done so.

Dr. Vishwanath asked whether Dr. Flynn and colleagues had looked at the
proportion of people who agree that smoking is a problem, or whether
they examined media coverage, noting that they are not the same. Dr.
Flynn responded that they had examined media coverage, and that it
clearly is linked to the proportion of people who agree that smoking is
a problem, resulting in an overabundance of health information via the
media. One example is that the rise in the prevalence of smoking stopped
shortly after the release of the *Surgeon General's Report on Smoking*
in 1964, due to people absorbing the information and making behavior
changes---a combination of the media and then the level of acceptance
within the community.

Dr. Slovic noted that an obvious hypothesis is that smoking is related
to nicotine addiction, and that these individuals are having more
trouble getting out of the addictive state. This could be because
something physiological is going on inside them, or it may be
psychological. He asked whether Dr. Flynn and colleagues examine this
aspect of smoking in their community intervention, and whether they try
to individualize or target different treatment approaches to different
people in this way. Dr. Flynn responded that he was not sure how to
conduct this sort of intervention, and that it is a struggle from a
public health perspective. Dr. Flynn sits on the Board of a statewide
program in Vermont that provides free nicotine replacement prescriptions
to low-income people on Medicaid. Currently, the program is in
negotiations with insurance companies and is conducting a pilot study on
coverage for nicotine replacement therapy.

Dr. Cameron described a study she and her colleagues are conducting in
which they are trying to help women quit smoking. In one of the
conditions, women are provided with a health education group. In Dr.
Cameron's experience, the usual risk information does not have a
significant impact on them because they are well aware of the risks.
These women ask for powerful graphic risk information that will give
them a high level of motivation. Specifically, they want to see a
diseased lung that is blackened with cancer. Perhaps smokers can still
respond to risk information, but it may have to be of a different sort,
possibly using graphic and scary images. Dr. Flynn noted that there is a
similar study underway that has graphic images of diseased lungs on
packages of cigarettes in Canada but not in the United States. The study
is comparing similar populations in the two countries.

Dr. Abrams explained that researchers should look at individual
differences in a number of categories, and perhaps even use these as
natural experiments to see how different risk schema map to these key
individual differences. They also should examine nested contextual
factors interacting with those individual differences, which will lay
out a whole matrix of changes in key parameters that could bring out
some important components of how risk perceptions differ. In other
words, looking at those parameters as covariates results in completely
different ways of exploring these interactions, and this type of
analysis has not been conducted very often. Researchers tend to focus on
individuals over time or on the macroenvironment and populations; they
do not bring the two together as often as they should.

Dr. Slovic noted that Dr. Cameron's comment about the blackened lung
relates to Dr. Weinstein focusing the group on the issue of severity. It
is one thing to be informed about a consequence and to know a
consequence as a name or a concept, and another to experience the
consequence in a more real way. Looking at a blackened lung is one way
to get beyond the name of a consequence. Another approach would be to
meet with or get to know someone who is dying from lung cancer and learn
about their experience with the disease. The difference between knowing
the consequence in an abstract sense and knowing the experience of the
consequence is lacking in many cases. Dr. Flynn briefly described a
series of television messages in Massachusetts that focused on an
individual who died of lung disease. Although it was not a controlled
study, the messages appeared to have an impact.

Dr. Rimer described a number of studies that have tried to focus on
testimonials and stories of tragic cases of people dying of lung cancer.
Part of the effect is to make the risk more vivid, and more work is
needed on making the risk more real to individuals. There also are some
interesting cultural differences. Making risk more real to people is
important, and the level of information diffusion for these types of
issues is important, because familiarity with the risk may cause people
to be turned off from more messages. It may be that early on, the risk
information is important and persuasive, but affect, emotion, and other
factors may become more important and may get in the way of hearing the
risk message or personalizing the risk message.

Dr. Cappella asked how one activates, in a vivid way, the risk that
might be associated with changing behavior. When does the activation of
risk to such a degree raise negative consequences and assessments of
risk versus producing the kind of anxiety and fear response that leads
to withdrawal? In creating and using vivid messages, emotions are
activated that can produce withdrawal (a boomerang effect). When do the
cognitive consequences and the emotional consequences agree, and when do
they start to depart from one another? Dr. Croyle explained that
previous studies of two dimensions of perceived risk or perceived threat
and perceived control have found that as long as the perception of
control accompanies the greater threat, a behavior change will result. A
key element is to what degree researchers separate out these component
dimensions such as probability and severity.

Dr. Flynn asked participants to keep "the bigger picture" in mind. His
case study did not address risk perceptions, but it did include other
factors smokers consider, such as access to resources, direct support,
modeling, and community support for their efforts to quit. Once an
individual is on the road to trying to quit, they are going to need
these, so they should not be left out of the picture when smokers' risk
perceptions are analyzed.

# Risk and Discrete Emotions: Anticipated Emotion as Risk and Benefit

*Joseph N. Cappella, Ph.D.*

*Professor and Gerald R. Miller Chair, Annenberg School for
Communication, University\
of Pennsylvania*

# Discussion

Dr. Greenwald asked whether an analysis was conducted in which emotion
(e.g., "proud") was taken as the dependent measure and predicted in the
same hierarchical regression, using intention as a predictor of emotion.
In other words, is asking a person if they are proud of their intention
another approach to asking them what is their intention? Dr. Cappella
responded that such an analysis has not been carried out. The study does
include following up with subjects (97% of subjects agreed to
participate in a followup telephone interview) starting in April or May
of this year. It is hoped that the evidence using emotion specifically,
as well as the other predictors, accounts for some of the quit attempts,
the length of quit attempts, and some successful quit attempts.

Dr. Rimer asked whether there is a role for risk in informed
decisionmaking, as opposed to only behavior and intention, in terms of
early detection behaviors. Dr. Cappella noted that the answer to this
question is unclear; however, a decision to undergo a test can be
considered a behavior that an individual intends to carry out. He noted
that the social cognition and communication literature is similar to the
decisionmaking literature in many regards, particularly with how
individuals work with information in a psychological sense. As a result,
the decisionmaking literature can be tied into behavioral intention
types of theories. It is difficult to distinguish between an
individual's intention to undergo a test for the early detection of
breast cancer and an individual's cognitive decision to have that test.
If risk is valuable in the decisionmaking context, and if it can be
shown that a single, simple, summary measure of risk will work in this
context, then it will work in the behavioral intention context.

Dr. Millstein noted with interest that the most predictive items in the
study were "hopeful" and "proud." She asked whether there were any data
on the degree to which individuals who could anticipate emotions such as
"proud" and "hopeful" may serve as a proxy for or reflect some degree of
self efficacy. Dr. Cappella explained that a widely accepted, effective
measure of self efficacy specific to smoking was included in the study
as a control variable. Dr. Millstein also asked whether it was possible
to measure the degree to which subjects were or were not able to
anticipate/imagine what might happen, how they might feel, and whether
there was a measurable difference between those who were not able to
imagine what might happen and those who were able to do so. Dr. Cappella
indicated that he was not sure if this difference could be measured. It
is hoped to examine family smoking history as an interaction variable to
determine whether there are different effects with subjects who have a
stronger family smoking history. The study did not examine family
smoking history to determine whether the subgroups may have had a
genetic predisposition or whether individuals felt they had no chance of
quitting because they have identified themselves as habitual smokers.

Dr. Croyle asked whether Dr. Cappella had considered tying this study to
the body of literature in social cognition, demonstrating that when
individuals are persuaded to imagine an event, they see it as more
probable (e.g., examining the link between how easily an event is
imagined and the event's perceived probability). If individuals are more
able to imagine themselves as nonsmokers or as quitting, it would
correlate with intention, and intention is, in a sense, a probability
(e.g., "I can imagine myself quitting," "I am intending to quit," "I can
visualize myself quitting"). This ties into the perceived probability of
quitting and the link between the ability to imagine an event and the
probability of the event, as does emotion (e.g., the degree to which an
individual can imagine him or herself feeling "proud" or "hopeful"). Dr.
Croyle added that these concepts also are found in the rumination
literature in terms of how people ruminate about events that they dread
and can imagine occurring. Dr. Cappella replied that he had not yet tied
his study to these bodies of literature. He noted that the study does
include two different measures of intention (i.e., "will quit," and "try
to quit"). The predictability for "will quit" is, not surprisingly,
lower, but substantial increments to behavioral intention are observed
with "will quit."

Dr. Weinstein noted that if risk is viewed as being equivalent to
consequences, then there may be no difference between health behavior
and any other type of behavior or decision, whether it is buying a car
or choosing a career. Health behaviors may be part of the same domain of
intended behavior. One problem with this scenario is that there may be
features of risks or hazards that can be studied by focusing on the
properties of hazards (e.g., time, imminence, catastrophic potential).
There are processes that are somewhat unique to health behaviors (e.g.,
risk resistance to personal vulnerability is not as much of an issue in
other areas as it is in health behaviors), and if health behaviors and
vulnerability are considered as just another behavior, these processes
and features may be overlooked. Dr. Cappella asked whether this could be
avoided if questions regarding consequences are asked in terms of a
negative consequence or need, and if subjects' personal vulnerability is
made more prominent, could more emotional behavior be measured. Dr.
Weinstein responded that although this may represent a measure of
emotional behavior, it does not address the fact that in this domain,
there often is a significant gap between what subjects hear about risk
and what they believe. This area requires further study. Dr. Cappella
clarified that the measures used in his study are not intended to
address this gap; rather, they are addressing individuals' beliefs. He
acknowledged that there is a gap, and that part of the intervention
development and implementation process is creating interventions to
close this gap. If researchers are going to focus on consequences in
both an objective and subjective sense, and if vulnerability is where
the research community believes there are levers for moving cognition
(and hopefully intention, and ultimately, behavior), then there should
be a focus on personal consequences to close the gap between personal
consequences and actual causality.

Dr. Weinstein noted that the study includes measures of probability in
its attitude measures. This is one approach to conceptualizing perceived
likelihood, one that is different from approaches discussed earlier in
the workshop. This approach measures subjects' being sure of an event
occurring as opposed to measuring the magnitude of the event occurring.
Dr. Cappella remarked that this approach asks subjects about their
perceptions of consequences to themselves that are relatively immediate.
Even if these consequences are "made up" in the sense that individuals
are simply guessing or using lay theory or public knowledge of the
consequences of a particular action, and if these perceived consequences
are grossly in error, then it suggests an area at which an intervention
needs to take place to communicate factually correct and accurate
information. As an example, Dr. Cappella explained that a great deal of
the work in the antidrug area focusing on beliefs has found that many of
the antimarijuana messages boomerang with young people. One class of
antimarijana messages that does not boomerang are messages that focus on
what using marijuana regularly does to adolescents' parents and how
their parents feel about it. Not surprisingly, low-risk adolescents
report believing that their parents will be very upset. However,
high-risk adolescents also report believing that their parents will be
upset. A number of advertisements using the impact of marijuana smoking
on adolescents' parents have been rated as highly effective, even by
high-risk teens.

Dr. Greenwald asked about the validity of the "try to quit" or "will
quit" intention measures on actually quitting smoking. Smoking might be
an area in which behavioral intention measures are not very predictive.
Dr. Cappella noted that there are few prospective studies in this area
that examine subsequent behavioral activity. There are, however, some
differences depending on the populations being examined. Not
surprisingly, the behavioral intention measures are more effective in
predicting smoking when the population includes both smokers and
nonsmokers. With regard to quitting, the behavioral intention measure
generally is not as effective of a predictor. It is slightly more
effective in populations of both smokers and nonsmokers (e.g.,
predicting the likelihood of taking up smoking and the likelihood of
quitting smoking). Among populations of smokers only, the predictions
are not as accurate, which is part of the reason the current study is
being conducted. Overall, findings in the literature on behavioral
intentions predicting smoking cessation are inconsistent.

Dr. Weber noted that in conducting the study's followup, it may be
useful to assess emotions at the time of decisionmaking to try to make
the distinction between concepts such as "anticipated" and
"anticipatory." There clearly is an overlap between the two as
individuals anticipate how they are going to feel in 1 year, for
example. Dr. Weber explained that this anticipation also elicits a
certain amount of affect at the moment of the decision, and in a way,
the effect of the emotion at the time of the decision drives the
behavior and could be considered as a second pathway. Dr. Cappella added
that such a secondary pathway may produce emotional responses that
counter rational responses, and that there may in fact be two pathways
pushing in opposite directions in some cases. Part of the reason the
emotional component was added to the study on quitting was to try to
improve the predictability of this measure. He noted that clarifying and
characterizing the relationship between intention and behavior is a
difficult undertaking.

# Use of the Implicit Association Test in Risk Assessment

*Anthony G. Greenwald, Ph.D.*

### Professor, Department of Psychology, University of Washington

**Discussion**

Dr. Slovic explained that Dr. Greenwald's results fit with data he and
his colleagues collected when they asked smokers if they would start
smoking again. They received tremendously negative responses, and the
negativity increased the longer the person had been smoking. It would be
interesting to use this information with samples of smokers to see if
the effect size Dr. Greenwald and colleagues found increased with the
amount of current smoking, length of smoking, sense of being addicted,
etc. Dr. Slovic asked how Dr. Greenwald and colleagues would compare
their results with what one might get with a Fazio-type measure that
would be a straight reaction time between association of smoking with
other qualities. Dr. Greenwald noted that this question has, in other
research contexts, been a cause for concern. The sequential priming
measure is believed or interpreted to measure associations involving the
specific stimuli that are presented. If climbing, hiking, and running
are used to represent the concept of exercise, Fazio would indicate that
a priming measure examines the association of positive valences with the
individual terms climbing, hiking, and running. It is clear that with
the Implicit Association Test (IAT), it is more the category at which
the researcher is examining the associations. Another difference, which
is important psychometrically, is that priming measures are notoriously
low in internal consistency and test/retest reliability, which is true
of almost all latency-based measures. Dr. Greenwald further explained
that the IAT, although also a latency-based measure, has quite high
internal consistency, usually in the .80s, and the test/retest
reliability is on the order of 0.6 and sometimes higher. For practical
purposes, this turns out to be an important difference from the priming
measure.

Dr. Abrams asked about the evolution or the progression of these
associations over time, specifically whether Dr. Greenwald and
colleagues studied, for example, groups such as children who are not yet
smoking but clearly have some cognitions about smoking because of
advertising. It would be interesting when they take their first puff to
see what happens to that cognitive schema of expectations against the
stark reality of the first experience, and then how that influences
sequential experiences. Dr. Greenwald replied that although these data
could be interesting and useful, this particular IAT smoking study did
not address this type of longitudinal question. Dr. Abrams added that
little is understood about the early decisions children make. For
example, approximately 70 percent of children try a cigarette, but only
about 36 percent progress to regular smoking, and they stop smoking at
various stages. It would be interesting to examine the emergence of what
differentiates those children, all things being equal in the first three
cigarettes, who decide this is not how they want to see themselves
versus a child or teen who feels that smoking might fit with their
emerging self image and then becomes addicted.

Dr. Greenwald noted that it would be interesting and useful to
administer an IAT before and after the first cigarette. He and his
colleagues considered trying to represent the aspects of self, such as
ideal self or actual self, in the IAT, but the test requires that
subjects are knowledgeable about the concepts being used, and it is
difficult to portray concepts such as ideal self and actual self on the
IAT. Furthermore, his research group believes that the concept of actual
self does not exist for this population. Subjects have an easier time
associating self with the ideal characteristics than with actual
characteristics when asked to associate self with trait adjectives
representing ideal characteristics versus actual characteristics.

Dr. Windschitl asked whether the finding that smokers associate smoking
with negative valence more than positive valence would depend on what
particular valence words were used. Dr. Greenwald replied that it does
not depend on which particular words are used, by only on whether the
words used are positive or negative. The characteristics of the words
used are easily classified by the subjects, so the valence is fairly
consensual and unambiguous. Dr. Windschitl noted that Dr. Greenwald and
colleagues' study used positive valence words that anyone would
recognize as positive, but if the words were switched to words such as
"relief" and "relaxation," while more narrowly focusing on some of the
consequences of smoking a cigarette, smokers might show a positive
response. Dr. Greenwald agreed, explaining that these words were
selected to represent "relaxation" and "enjoy" for the purpose of using
concepts that are smoking related and more narrowly defined than the
general concepts of positive and negative valence. When using the more
narrowly defined items, the category labels should also be changed to
indicate the more specific categories.

Dr. Greenwald added that the IAT can be used to study anything in the
health domain that can be represented in terms of concepts that already
exist in people's minds. Most IATs take only minutes to create,
according to Dr. Greenwald, who has streamlined the IAT creation
process. When asked about creating an IAT to study how hard people think
it is to quit smoking, Dr. Greenwald replied that this type of study
might be beyond the scope of the IAT because it is propositional
knowledge that is difficult to reduce to representation as a single
association between two concepts (it involves self, smoking, and
quitting, so there are at least three components). An IAT might be used
to examine the association of quitting smoking with emotions, however.
Dr. Weinstein asked about using an IAT to study the association between
"quitting is easy" and "quitting is hard." Dr. Greenwald responded that
he would be worried about confounds because "quit" is negative, "easy"
is positive, and "hard" is negative, so it may result in an association
between "quitting" and "hard" that was due to their shared valence. This
type of unintended confounding presents a significant problem in
designing IATs.

Dr. Cappella asked, in terms of social smokers, how Dr. Greenwald would
include stimulus words in an IAT that are not simply shared in terms of
their overall meaning, but actually represent the strongest negative and
strongest positive so that there is a balance of what is perceived to be
the most negative and the most positive, rather than just positive ones
and negative ones that happen to be shared. According to Dr. Greenwald,
this question confronts some of the challenges in designing IATs. There
are some IATs that can be designed in just a few minutes, but when there
are worries about possible confounds between the categories, it can be
challenging.

Dr. Cameron noted that there is the potential for IATs to be used in
many interesting ways in terms of examining health behaviors and risk.
One of the most useful ways may be dealing with concepts for which there
are a high level of desirability. In her research on exercise, she has
found that there is a good deal of social desirability concerning self
efficacy; everyone likes to think they can exercise, and she and her
colleagues have been trying to find ways to examine the implicit
associations between "can I" and "exercise" to try to avoid the
self-report biases that are seen when individuals are asked whether they
can exercise, and they say "of course." She asked whether this type of
concept could be used with an IAT. Dr. Greenwald responded that an IAT
could be developed that involves self and exercise, and then contrasts
exercise with some other positive, such as representing the idea of
relaxing, sleeping, or napping---positives that are the antithesis of
exercise---which could result in a determination of whether the person
associates self more with the concept of exercise than with some
antithetical, but positive, concept. Including the concept of self
efficacy in an IAT as a propositional representation rather than an
association is a difficult, but not impossible, undertaking.

Dr. Croyle noted that there are many behavior change domains in the
health context, where researchers have been frustrated at not being able
to obtain effective mediational measures in terms of affects. In many
cases, the proposed mediator is an experiential process at that
associative mechanism, as opposed to a rational one. It would be
interesting to pit IAT against some of the classical behavior change
mediators, in response to health communication interventions, for
example, to determine which pathway is better and distinguish the
associative and experiential pathways. Dr. Greenwald added that research
has been conducted, mostly in Germany, in which subjects were asked to
try to fake answers on the IAT. This resulted in a minimal effect on the
overall IAT results. He also noted that the IAT usually is conducted via
computer on a desktop machine, but it also works on hand-held devices,
and can be Web-based.

Dr. Cappella asked about how to address the error rates when individuals
are faced with the combined categories on an IAT with a possible social
desirability response (e.g., they do not want the test to reveal that
they operate out of a gender stereotype). This is a common problem for
all reaction-type studies. Dr. Greenwald noted that results of a study
using Web-based IAT data indicate that even when errors are left in the
data set, the IAT can tolerate fairly high error rates.

Dr. Windschitl explained that one of the self report measures that has a
strong social desirability component to it for smoking-related questions
is how "cool" individuals think they look when smoking. Many people may
think that they look "cool" when they smoke, but they would not want to
report that in a self report measure. He asked if an IAT could be
created that involved "cool" images of smoking and "ugly" images of
smoking, and correlate that or pair that up with "self" and "other." Dr.
Greenwald replied that this would be a relatively easy IAT to construct.

**Measuring and Conceptualizing Perceptions of
Vulnerability/Likelihood**

*Paul D. Windschitl, Ph.D.*

*Assistant Professor, Department of Psychology, University of Iowa*

**Discussion**

Dr. Croyle asked Dr. Windschitl to discuss individual differences in
more detail, asking whether there are differences in people's
preferences for the intuitive versus the objective way of thinking about
risk and probability. In survey methodology literature, use of the
cognitive interview method of developing survey items often results in
survey developers dropping the objective form because the majority of
people interviewed and asked to think out loud about how they are
interpreting a question item will give an intuitive response. This leads
survey developers to change the item to the intuitive form. In terms of
individual differences, he asked whether Dr. Windschitl and colleagues
considered connecting this work to numeracy and scientific literacy,
because the study population may have a significant effect on the
pattern of data. Dr. Windschitl's point about the frequency of thought
measure appears to be very similar to measuring worry, so there is a
concern that study subjects may not differentiate between "think about"
and "worry about."

Dr. Windschitl agreed that the worry questions may tap into the
frequency of thought notion, and that many of these ideas are more
appropriate for certain populations than others. With regard to asking
about frequency questions, Dr. Windschitl and colleagues were attempting
to determine how often subjects actually make a decision when they
engage in a behavior, considering in a very consequentialistic fashion
the pros and cons, the risks, and the likelihood before making a
decision, versus occasions when they engage in the behavior without
making a decision for that particular behavior. Dr. Croyle also noted
that in terms of the validity of self reports about the frequency of
thoughts, the ecological momentary assessment literature indicates that
when data are collected on a daily basis, there tends to be a low
correlation between daily reporting versus weekly or retrospective self
reporting and frequency of symptoms, behaviors, thoughts, etc. Dr.
Windschitl admitted that this could be a limitation, and it could be the
case that one type of subjective report of how much subjects think they
have been worrying about something actually provides more information
about how salient that worry is for them, more so than their objectively
reporting how often they worry about it. Two people can report worrying
about the same thing for 5 days, and this may mean a great deal of worry
for one of the individuals while not being nearly as significant for the
other individual. Dr. Cappella noted that one way to avoid the problems
associated with constant daily reminders or daily inventories is to use
a random sample approach whereby subjects carry pagers and are paged
during the study at various times.

Dr. Slovic explained that in terms of distinguishing between objective
probability and a subject's feelings, one experiment would be to put
subjects under time pressure, which would make it more likely that they
would rely on the vulnerability feeling-based system because they do not
have time to be more analytical. He also noted that worry might confound
with severity and with sense of control. For example, individuals tend
to worry more about things that they think they can do something about
(e.g., some people may not worry as much about a terrorist attack
because they feel they cannot do anything about it).

Dr. Windschitl proposed that worry is on one end of a spectrum, beliefs
about the objective probability of an event happening are on the other
end of the spectrum, and more intuitive perceptions of the likelihood of
the event happening are in the middle. Each of these three factors is
distinct, and should be treated separately. Dr. Windschitl and
colleagues focus a large part of their research on demonstrations in
which subjects intuitively feel one way, but when asked for a numerical
response, they respond quite differently from their intuitive feelings.
He explained that he views beliefs about objective probability and
intuitive perceptions as cognitive, almost consequentialistic, notions
that are separate from the more affective emotional components.

Dr. Weinstein asked if intuitive feelings are better predictors of
behavior than beliefs. Dr. Windschitl replied that this is the case in
the majority of instances, but there likely are some cases in which
objective beliefs determine whether a person engages in a behavior.
However, for most of the behaviors studied by experts, intuitive
perceptions drive behavior. Dr. Weinstein then asked if, when subjects
are asked for a probability or frequency estimation on a rating scale,
this still taps into a concern orientation, or would this be an approach
to getting at the more objective belief components. Dr. Windschitl
replied that a number of researchers have pointed out differences
between numeric probabilities and numeric frequencies. For purposes of
this workshop, numeric frequencies and numeric probabilities are likely
to show a good deal of overlap.

Dr. Greenwald noted that the pairs of measures suggested by Dr.
Windschitl capitalize on the implicit conversational pragmatics in which
researchers are implicitly requesting subjects to tell them something
that is different from what they told the researchers in their answers
to a previous question. It also would be interesting to reverse the
order, and ask subjects the vulnerability question first and then follow
it with the objective probability question. Dr. Windschitl agreed that
this would be an interesting experiment, and that for purposes of
measurement (e.g., on a survey), these questions would work best if they
ask about a variety of risks, and when the first two questions are
basically "filler" items to get subjects used to always being asked two
questions. This also raises their awareness of the need to separate out
intuitive feelings from objective beliefs.

Dr. Flynn expressed concern about the difficulty associated with asking
subjects for their assessment of objective probability followed by a
second question that seems to say "now tell me what your real answer
is," so a different time frame might be needed for the two questions to
measure different constructs. One possible frame for that objective
probability would be to ask about "people like you" instead of asking
for subjects' personal susceptibility or vulnerability. Dr. Windschitl
explained his belief that in many circumstances, there are cases where
subjects do have different responses on the two measures, and that
having the filler items in front and getting subjects used to that may
help them to separate out their two types of responses.

Dr. Rimer noted that individual differences are ignored in many
large-scale population surveys. One interesting finding is that in
studies of genetic testing and mammography behavior, women who were
depressed were more likely to give accurate assessments than
non-depressed women. As experts are better able to give individuals
realistic numerical probabilities of disease risks, how will this affect
subjects' perceptions as well as the measurements? Dr. Windschitl
explained that when subjects are given a numeric piece of information
embedded within various non-numeric forms of information on an objective
likelihood measure, they generally focus on the numeric information to
provide their response, and they might actually believe that that
numeric information is quite valid and appropriate for providing their
response on the objective likelihood scale. On the intuitive feelings
scale, however, the non-numeric information will lead subjects to depart
from what they responded for the numeric measure. In other research, Dr.
Windschitl and associates have shown that if one piece of numeric
information is provided and subjects are given a way to evaluate that
information relative to some other piece of numeric information, there
also is a "risk ladder" concept, in which the comparison of numerical
risk for one disease versus another could drive subjects' feelings. If
subjects are given only one number, it often is meaningless unless they
are provided with a comparison point against which they can evaluate the
number.

Dr. Weinstein noted that there are data suggesting that when subjects
are given personalized numerical information and they say they
understand it and they think it is credible, they still give different
answers when asked about their personal risk. Even when asking for an
objective probability, it is possible that subjects' vulnerability
feelings are overcoming what they are being told. Dr. Millstein
described an infertility study in which participants were asked to tell
researchers what their doctors told them about their chances of
conceiving. Participants then were asked about what they thought their
chances were, and the results (anecdotal evidence) indicated that
participants tended to report believing their chances of conception were
higher than the chances given to them by their doctors. She asked Dr.
Windschitl to discuss the stability of these measures and, in
particular, the stability or instability of the intuitive assessments or
perceptions. Although there are no data, Dr. Windschitl noted that the
intuitive perceptions are likely to vary, even from hour to hour, if the
right kind of information is given to subjects. For example, an
individual's sense of the objective risk of being a victim of terrorism
may be constant, but depending on what news they are watching, their
intuitive perceptions may vary dramatically. Dr. Millstein also asked to
what extent intuitive perceptions are fueled by emotion. Emotions vary
second by second, and emotional states may vary by minutes. How can
these be measured?

Dr. Slovic said that with regard to the stability and reliability of
these numbers, feelings and emotions clearly bounce around and are very
labile. On the other hand, attitudes have an important emotional or
feeling base to them and can be remarkably stable, so an attitude
towards some hazard can be unvarying over years despite new information.
Therefore, it is a complex system. In terms of eliciting numerical
probabilities, Dr. Windschitl's work demonstrates how sensitive the
system is to the context of the question. Other research has shown that
both empirically and theoretically, the judgment of a probability of an
event depends not on the event, but on the description of the event.
There can be equivalent descriptions of the same event that can elicit
vastly different probabilities (e.g., what is the probability that you
will get cancer from smoking?). This shows that the likelihood is not
represented numerically for the most part, and that individuals tend to
construct a likelihood in response to the way that the question is
presented. Dr. Windschitl explained that there is an internal
representation of beliefs and an internal representation of intuitive
feelings. The reports of beliefs---even objective beliefs---can vary
dramatically depending on the context. Both the internal representation
of beliefs and the internal representation of intuitive feelings can
move up or down when subjects are asked to report them. Belief and
objective probability likely tend to be more stable, and generally are
not well represented in a numeric fashion.

Dr. Hay asked if the intuitive, "gut" reaction might come through more
on the visual scales if a series of faces with different expressions or
a matrix of a large number of characters for subjects to choose from was
used. It appears that intuitive feelings come out much more quickly when
subjects are given something visual, as opposed to numerical or verbally
anchored scales. Dr. Windschitl agreed that these kinds of measures are
more sensitive to intuitive reactions, and noted that for any given
scale, researchers should question whether subjects are considering the
objective probability, or whether it is a strictly intuitive perception.

Dr. Cappella commented that it would be interesting to study the extent
to which an optimism bias that might take place for some subset of
individuals is associated with certain ways of thinking about a problem,
compared to a pessimism bias where they react in the opposite direction.
Dr. Croyle noted that the time frame is critically important. Research
on anticipatory pessimism shows that as individuals approach an event of
uncertain outcome, they often become more pessimistic as the event draws
closer. As an anticipatory coping strategy, people often assume the
worst before they get the news (under medical testing circumstances) to
brace themselves, so they are adjusting their objective probability to
regulate their affect and the anticipation of how to cope with a
potential negative outcome.

# Risk Perceptions: A Self-Regulatory Perspective

*Linda D. Cameron, Ph.D.*

*Senior Lecturer, Department of Psychology, University of Auckland*

**Discussion**

Dr. Cappella commented that if it is true that risk and worry accounted
for behavior completely with some simple measures (from the point of
view of intervention), then the same levels of risk or the same levels
of worry might be produced by very different kinds of representational
systems. If the interventions depend on the way in which individuals
represent risk and worry to themselves, then researchers need to know
the risk and worry. He asked whether Dr. Cameron and colleagues had been
able to study subgroups in their populations of interest to establish
not just different levels of risk and worry, but also different
representational systems behind those levels of risk and worry. Dr.
Cameron agreed that for the sake of interventions, researchers do need
to be able to address representational beliefs. Even if investigators
can predict behavior based on risk and worry, for intervention's sake
they have to look at the illness representations. She reported hoping to
conduct future research on a data set that includes subjects' risk
judgments and worries and assesses illness risk dimensions to determine
their relative contributions. There is an extensive body of literature
that examines how illness representations predict behavior. However,
this research has not examined how those representations link to risk
perceptions and worry, and how that in turn links to behaviors.

Dr. Croyle asked about the order of the causal pathway, because
representations and risk perceptions often are determined by behavior.
Behavior usually comes first, and then people keep moving their risk
perceptions and representations to conform to their prior behavior.
Often, the effect size of behavior on the cognition is significantly
larger than the effect size of the risk perception on behavior. In other
words, it is easier to show a strong effect of behavior or consequence
on cognition than if cognition is used as a predictor. He also asked,
within the context of the self regulation model, about the mental models
as adapting or changing as a consequence of behaviors, because some
people view that as a motivational process, but new behaviors are also
new information, so it could be viewed as a defense bias or ego
motivation (each time an individual engages in a new behavior, he or she
also is adding to the information they can incorporate into their mental
model).

Dr. Cameron noted that future behavior is conditional upon having the
opportunities, other situational constraints, etc. Another important
issue with this model is that although it demonstrates how illness
representations are promoting behavior, the behaviors that are being
promoted often are not the ones that researchers are interested in
(e.g., individuals at high risk for heart disease may decide to cope
with that by increasing their vitamin E intake because they somehow
believe that taking vitamin E will reduce their risk, while researchers
would be interested in whether these individuals are changing their fat
intake or exercising). It also is important to consider the "if...then"
beliefs that people have and how representations depend on the manner in
which individuals evaluate their past behaviors.

Dr. Rimer reminded participants of the need to measure worry more
comprehensively. In studies of breast cancer, researchers ask about
worry and find a very small proportion of women who say they are
worried, primarily because breast cancer does not appear to be
"believable" to them. This may be a response problem, because women
generally say they are "concerned," not "worried" about breast cancer.
There is a need to find ways to measure worry. She asked whether
different kinds of interventions would be needed for people with trait
anxiety. Dr. Cameron stated that it will be important to tailor
interventions so that they target the needs of highly anxious women.
Highly anxious women may need more attention to emotion regulation
processes and how they process those emotions in ways that will lead to
protective behavior compared with low-anxious women.

Dr. Hay noted that Dr. Cameron's model appears to show that illness
worry and risk perceptions are partially overlapping and are promoters
of behavior. She asked how the model relates to the Curvilinear
Hypothesis with regard to perceived risk. Researchers generally do not
consider very high levels of risk as being inhibitors, but with cancer
or illness worry there is a hypothesis in the literature that very high
levels of cancer worry inhibit behavior change in some individuals. Dr.
Cameron described some conflicting findings in the literature regarding
the curvilinear relationship. Some researchers have demonstrated that
there is more of a linear relationship, which could be due to an
examination of behaviors that are somewhat put off in time and do not
require immediate action (e.g., women have time to prepare themselves
emotionally for a mammogram). Researchers also have found that extreme
worry can lead to an avoidance response, at least in the short term, and
this likely is a timing issue.

Dr. Croyle explained that an ongoing methodologic and theoretical
controversy in the health domain is the generality of processes and
principles of health cognition across disease domains. Many of the
applications of psychology to the health domain do not incorporate a
consideration of the specific features and characteristics of a
particular illness context, and therefore are not effective (e.g., they
do not measure people's beliefs and representations about other features
and signs of the illness). He asked Dr. Cameron, within the context of
risk perception and measuring perceived risk, about the most critical
features of her model that will vary across diseases and that need to be
measured to have a better measure of perceived risk. Dr. Cameron noted
that it is important to identify that there will be domain specificity
across the diseases, so that the important representational attributes
for breast cancer may be very different than the important
representational aspects for lung cancer. For lung cancer, the causal
belief that smoking causes lung cancer is going to be critical, possibly
even the sole predictor of risk perceptions and behavior. For breast
cancer, the causal beliefs cannot be controlled and it therefore is more
important to focus on controllability in terms of early detection and
surgery. Dr. Croyle added that the weight of the different dimensions of
the representation may vary across the diseases.

Dr. Millstein commented that it is not just the situations in which one
pathway versus another pathway might be dominant. Individual
differences, particularly developmental differences, may be important.
Dr. Abrams explained that when researchers induce a condition
artificially in the laboratory, it relates to this dimension of ecologic
validity, and it is not surprising that some type of internal reduction
in a natural real world would be quite different from an artificial
induction in a laboratory. In his own research, he has found that when
smokers are given the sight and smell of their favorite cigarette in a
high-risk situation, it makes a tremendous difference whether the
subjects are in treatment for quitting or whether they have no interest
in quitting at all. Situational dimensions dramatically modify
experimental outcomes, he added.

# Origins and Functions of Perceptions of Risk

*Elke U. Weber, Ph.D.*

*Professor, Department of Psychology, School of Business, Columbia
University*

# Discussion

Dr. Weinstein asked for some examples of measures used by Dr. Weber and
colleagues to assess affect, feeling, or other similar constructs. Dr.
Weber explained that there are a variety of approaches, and she provided
an example from research on individuals' financial investment decisions.
Subjects may be asked to rate on a scale from 0 to 100 how worried they
are between the date of buying a stock and finding out what the outcome
will be. Subjects typically are given anchors for the upper and lower
bounds (they are shown the most risky and least risky options in terms
of variance). Dr. Windschitl asked whether Dr. Weber and colleagues
conducted an analysis of individuals who recently selected a bad card
from the deck, asking them questions about how they felt or studying how
they reacted differently from people who selected a bad card further in
the past. Dr. Weber replied that they did not ask these individuals for
their emotional reactions in the initial study. However, she and her
colleagues currently are analyzing the group reactions (e.g., how many
people picked the "sure thing" as a function of the probabilities and
the outcomes). When people learn outcomes by experience, on average they
will underestimate the probability of rare events, partly because of the
updating process and partly because some of the time there is an
asymmetry in the occurrence of key events (e.g., by chance alone, a few
individuals will see a rare event quite often).

Dr. Slovic noted that Dr. Weber's work is a vivid demonstration of the
difference between the description utility and the experience utility.
Her work could be used to predict preference as well as satisfaction
with a decision. Another key concept is that one would expect that the
insights gained about preference from the experience would be much more
lasting and useful in terms of post-decision satisfaction than the
description utility. Dr. Slovic also explained that neuroscience
research has shown that some of the brain pathways that lead to emotion
are linked to action; the motor neuron and feeling neurons somehow have
linkages, and it may be that when the feelings are aroused, the brain is
wired for one response and that satisfies the concern. Dr. Weber added
that it would be interesting and helpful to demonstrate that there is
some sort of negative feedback loop that cancels out or responds
adequately.

When asked about the experience-based effect, Dr. Weber explained that
people process information about probabilities differently. In general,
people do not pay as much attention as they should to probabilities
because they are more focused on the outcomes, which is one reason
researchers overweight rare events with descriptions. She briefly
described the following three components of experience related to a rare
event: (1) individuals do not experience a rare event, and if they do
not experience it, they do not worry about it; (2) even if an individual
experiences a rare event, they experience it less on average than
expected; and (3) if an individual experiences a rare event exactly in
proportion to its objective probability, they still tend to overweight
more recent experiences, and rare events are less likely to have been
recent experiences.

Dr. Cappella noted that it is a challenge to try to take research on
probability information acquired through learning and apply it in a
domain where in the real world, there is not an opportunity to sample a
series of events. For example, with regard to catching a cold, there are
a variety of actions individuals can take to avoid catching a cold
(e.g., washing hands, staying away from people with colds). However, for
other types of threats, individuals cannot acquire probability
information from learning (e.g., because the event is extremely rare).
How does one take these results and apply them in domains where there is
not a repetition of events or where there is a low rate of the event
occurring and individuals cannot learn from experience? Dr. Weber
explained that in these situations, people may make decisions based on
descriptions. Dr. Cappella suggested adding to Dr. Weber's experiment by
including descriptions of real people with real medical conditions on
the cards rather than having people just draw yes/no cards. This
approach may add a significant degree of reality for study subjects.

Dr. Cameron asked about the single-action bias in the health domain.
There are a number of illnesses or conditions that require multiple
behaviors, like diabetes (controlling insulin, exercising, diet, etc).
Are there any examples of single-action bias in the health domain? Dr.
Croyle offered the example of exercise, where there are many activities
one can participate in (e.g., walking, running, etc.). An individual who
thinks that he or she needs to be more physically active might join a
health club. They may never go and exercise, but they feel as though
they have taken a sufficient action because they joined the club. Dr.
Weber added that physicians generally are not very good at diagnosing
multiple diseases in a single patient---one study of radiologists found
that when they examined x-rays that showed multiple medical problems,
they tended to identify one problem---not necessarily the most obvious
problem---and not the others.

Dr. Windschitl noted that there probably is a significant egocentric
bias as well. Individuals should pay attention not only to their own
experiences, but also the information they have about their friends'
experiences, who are participating in the same behaviors as the
individual. It is likely that people vastly overweight their own
experiences. For example, if an individual has done something 10 times
and has not suffered negative consequences and their friend has the same
behavior and has suffered the negative consequence, the individual tends
to discount their friend's experience and operate from their own
experience. Although providing people with information about others'
experiences would help, it has to be made salient enough because there
will be an inequality of the impact of personal experiences versus the
experiences of others.

Dr. Greenwald explained that when people respond to the question about
the probability of their getting lung cancer, their experience of past
probability of getting lung cancer is zero, so they are not using that
for the basis for answering the question. If they think about
acquaintances who smoke, they probably know very few who have lung
cancer. Dr. Weber added that individuals are probably using a
combination of their personal experience as well as information that has
been highly publicized. The fact that individuals do not have lung
cancer when asking themselves about the risk of getting lung cancer is
likely to contribute greatly to the subjective underestimation in
certain situations.

Dr. Croyle asked where the social comparative aspect of risk fits in.
Dr. Weber explained that she would include it in the description-based
category. Dr. Croyle also asked whether Dr. Weber had examined the
actor/observer paradigm, in which the actor uses the cards while another
individual observes him or her. Dr. Weber responded that she had not,
but other researchers have found a significantly reduced impact
associated with observing other individuals.

Dr. Abrams asked whether an aspect of the underlying neurocognitive
processing can be related to a more appetitive approach reward circuitry
as opposed to the fear/inhibition circuitry. This likely is another part
of this complex interaction, partly because some of the behaviors are
motivated by appetitive reward, which also is hard-wired into survival.
Furthermore, because some of the coping responses need to be activated,
the action plans would come more from an appetitive seeking as opposed
to a void. Is there a role for the positive reward circuitry in risk
decisionmaking, and if so, what is that role? Dr. Millstein commented
that the rational decisionmaking models in the decisionmaking literature
address the risk-benefit equation, that is, the rational system. The
closest parallel in the experiential system might be some work that has
been done on conflict, the experiential version of combining risks and
benefits. Dr. Rimer added that this literature influenced a number of
researchers studying mammography to try to understand women's individual
accounting systems of risks and benefits. A number of successful
interventions were developed as a result of these efforts, but it may be
time to reexamine this work in a more sophisticated manner.

Dr. Slovic noted that the October 2002 issue of the journal *Neuron* was
devoted to the brain and decisionmaking. One of the articles raises the
question of how the human brain rapidly integrates diverse and
incommensurable inputs. The paper identifies the dopamine neurons as an
integrated mechanism. On a higher level, the affective or the feeling
system may be driven by these neurons. Dr. Abrams noted that there also
is the issue of not knowing what anxiety is, because it is an old
construct from medical models of how the brain works, based on
old-fashioned views of symptoms of an abnormal behavior. It is not
surprising that there are unexpected results when studying mood,
anxiety, depression, etc. Researchers are not mapping in accordance with
the current understanding of how the brain works, but rather are using
old categories from the 1950s to map emotions.

# Affect, Risk, and Decisionmaking

*Paul Slovic, Ph.D.*

*Decision Research*

# Discussion

Dr. Croyle noted that in terms of confounded costs and benefits, there
has been a great deal of discussion about affect, but this discussion
has presumed an old model, a bipolar unidimensional negative model, as
opposed to moderately independent dimensions of positive-negative
affect. He asked whether Dr. Slovic had considered this in the context
of his research. Dr. Slovic explained that even if, neurologically,
there are two separate channels for positive and negative affect, at
some point they have to blend, and individuals must decide whether the
positive is more appealing or the negative is more adversive. He likened
this phenomena to a bipolar scale. Dr. Croyle commented that this
explanation presumes that people do not experience chronic ambivalence
(i.e., when people are paralyzed by indecision). Dr. Slovic explained
that chronic ambivalence has not been well studied by decision analysts
and researchers.

Dr. Greenwald commented that it might not be necessary to regard the
bipolar and the orthogonal views of affect as incompatible with each
other. For example, one could hold the orthogonal positive and negative
dimensions idea and assume by an intentional mechanism that they cannot
possibly both control behavior at the same time, so if an individual is
focusing on one at the time they act rather than the other, then he or
she has reduced it to a bipolar function in order to act.

Dr. Millstein added that different emotions have different neural
pathways and different ways of operating, and that there also are mixed
states. Technically, these are brief moments of time, and what really
characterizes feeling at a given moment generally is a mixed state, not
a pure state. Therefore, the more simplistic positive/negative affect
dimensions do provide a great deal of information. For example, stress
may be a mixed state: is it fear, is it anxiety, is it both, or is it
something else? Most of the real-life situations that researchers are
able to study outside of a specialized laboratory are mixed states, and
this may cover a lot of the variance.

Dr. Croyle likened the health domain to the relationship domain, in that
ambivalence is the typical stage. Although everyone knows it is good to
be healthy, there are a variety unhealthy behaviors people undertake.
Similarly, in relationship research, experts use positives and negatives
(e.g., "I like this," "I do not like this," etc.), which is why in many
cases health behavior researchers apply the decision model to a
particular study, using it as a measure of mediators of an intervention
to change a behavior. It results in a total score that is positive or
negative, but that positive or negative number never seems to capture
the complexity of the state of ambivalence. Dr. Slovic added that when a
person does not do something, they have resolved their ambivalence and
acted on it. Dr. Croyle noted that this concept applies well to health
domains where the issue is acting or not acting (e.g., getting a
mammogram or not getting a mammogram), but it does not translate as well
to chronic daily behavioral habits that occur as an ongoing process. Dr.
Slovic replied that this involves representations of the problem and a
cumulative aspect (e.g., having a rich desert one time will not have an
adverse health effect, but having a rich dessert with every meal will).

Dr. Rimer explained that she added an item on ambivalence to some of her
studies on mammography (to measure being torn between having and not
having a mammogram). For women who were not adherent, ambivalence was a
very strong predictor, and should be considered for future studies. Dr.
Rimer asked about the value of trying to shift people's perceptions
about the time frame in which they experience the consequence. Smokers
tend to think that lung cancer will not occur until a very old age; yet
a significant proportion of lung cancers are diagnosed in middle age.
Dr. Slovic noted that time characteristics and the perception of time is
very important, although moving up to middle age may not make any
difference to a teenager who thinks they will stop smoking within a year
of starting. Most smokers are planning to quit, and when asked about
when they expect to quit, most report expecting to quit within 1 year,
so their time horizon is very short. Furthermore, they tend not to
appreciate the likelihood that they will not be quitting within 1 year.
A large body of data indicates that smokers' expectations of when they
are going to quit are vastly optimistic. Another aspect is telling
smokers that smoking, on average, will take 10 years off of their life.
But to a 16- or 17-year old, there is little appreciation for the
difference between dying at age 70 or at age 80.

Another associated problem, according to Dr. Cameron, is that
adolescents may not have a good idea of who they are going to be 10 or
20 years from now, they do not have a timeline for themselves. They
realize that cigarettes can cause lung cancer at middle age, but they
cannot imagine themselves at middle age. An impact might be made by
showing a teen-aged smoker a picture of themselves that has been aged 10
or 15 years, this may give them a concrete sense of what they will look
like and how these issues might relate to them.

Dr. Slovic commented that in many of these domains, particularly
smoking, alcohol, and with certain types of foods, there is another side
that is deliberately trying to manipulate images and perceptions. For
example, the tobacco industry knows what images appeal to young men and
women of different races, they study this, and they tune their messages
to appeal to people. They are trying to create a desirable image and
show how their product will lead people to this desirable image. It is
not just that people are stumbling into this type of behavior, they are
being manipulated into it through an industry that is very smart and has
massive resources. Dr. Rimer noted that there is a subset of people who
have many unhealthy behaviors. For example, women who do not get
mammograms are more likely to smoke, to not have other kinds of
screening tests, and to eat bad diets. These people have many risks and
presumably are not adhering to many different health-related messages.
She expressed belief that individuals do not have the ability to weigh
multiple risk messages simultaneously about very different behaviors and
risks.

Dr. Croyle noted that there is a small subgroup of people who account
for many of the risky health behaviors, and that subgroup is not
included in most studies. Furthermore, there seems to be a substantial
qualitative difference in how information is utilized in this subgroup,
and they may perceive risks in very different ways. Dr. Weinstein asked
whether the reactions discussed by Dr. Slovic are affects about
threatening issues or global value judgment evaluations, and whether
that is an important distinction. Dr. Slovic replied that it is a
general notion, it is positive and negative feeling states that often
are very faint, and they can be triggered by analysis. An individual can
analyze something and come to the conclusion that X is better than Y and
therefore have more affect, but the characteristics of X evoke almost a
conditioned response, much of which can be below the individual's
awareness. He compared these little charges of positive and negative
feeling to electrons and neutrons, noting that neuroscientists in the
future likely will be able to show that these positive and negative
feelings being demonstrated in behavioral studies can be seen to be
operating at the level of the neuron.

**Summary Discussion**

On behalf of the National Cancer Institute (NCI), Dr. Croyle thanked
participants for attending the workshop and asked for feedback and ideas
on next steps to followup the workshop. Specifically, he asked for
suggestions for future meetings, additional participants, and other
fields of expertise that should be included. He asked what the NCI could
do to facilitate work and advance research knowledge, understanding, and
synthesis in this area so that the broader research community can
benefit from the discussions at this workshop. Dr. Weinstein noted that
he will meet with Drs. Millstein and Gerrard to discuss future
directions as well.

Dr. Weber proposed inviting Jennifer Lerner at Carnegie Mellon
University and Tory Higgins at Columbia University as participants for a
future meeting or workshop. Dr. Rimer suggested adding Richard Petty
resistance to persuasion as well. He and his colleagues have been
conducting research that may help to explain people's responses to risk
information. She also noted that this field should pay more attention to
the cutting-edge persuasion literature.

Dr. Rimer described an ongoing national population survey, the Health
Information National Tends Survey (HINTS), which interviews 7,000
individuals via telephone. The survey includes individuals aged 18-75,
and oversamples minorities. There might be some opportunities to include
some multiple measures of risk, as well as some measures of worry in a
future version of HINTS. Dr. Weinstein added that this biannual survey
was designed to include modules for special purposes, including
embedding experiments within the survey. Data from the most recent HINTS
survey will be available in a few months. Dr. Weber requested that the
results be sent to workshop participants. Dr. Vishwanath agreed to send
the information out when it becomes available, and noted that the data,
questionnaire, and other materials also will be made available on the
Internet.

Dr. Millstein voiced support for another "brainstorming" workshop such
as this. There is a group of researchers who use risk perception
measures but do not know where to go for information on these measures
or how to use them most effectively. It would be helpful if workshop
participants could generate a document intended for this audience. Dr.
Weinstein agreed that it would be useful to have the group, or a subset
of volunteers from the group, develop a report for individuals who want
to examine at risk perceptions more in depth and incorporate some of
these questions into their research. Dr. Cameron suggested meeting in
another 8-12 months to allow participants to come back with significant,
new contributions.

Dr. Cappella noted that there has been a tremendous amount written on
the idea of a basic singular measure of risk and whether it has some
relationship to behaviors across a variety of target behaviors. There
also is evidence suggesting that these measures fail. He asked if any
meta-analyses exist that could clarify this situation. Dr. Weinstein
replied that there are no such existing meta-analyses. He added that
some component of this contradictory character is due to the presence of
many cross-sectional studies that incorrectly analyze the data and
therefore would not be included in meta-analyses. It is hoped to conduct
this type of study in the future. Such a study will have to start with
domains for which there is a large enough literature base to conduct the
subanalyses. Dr. Rimer added that there is a lack of consistency in this
field, and measurement problems have impeded the creation of this
literature.

In terms of future activities, Dr. Greenwald stated that it would be
helpful to list the major questions that need to be answered to follow
up the agenda that was started at this workshop. Smoking and risk of
lung cancer appears to have been chosen as a model system for
researchers in this field. Is this a good model? Can it be expected to
generalize to other areas of health risk? There is a good deal of
correlational knowledge about how measures that are being used (e.g.,
behavioral intention, risk measures, etc.) work, but there is a gap in
predicting the target behavior, so there must be some questions related
to linking up the research and the measures with the target behavior.
Furthermore, are the rule-based and associative-based, or the rational
and experiential systems, and the measures based on them enough to
predict behaviors of interest?

Dr. Cappella noted that smoking, which becomes habituated
physiologically, may have a genetic component associated with propensity
to addiction, so there should be some concern about the pathway for the
maintenance of the behavior. He added that some behaviors have a social
component to them---this has been absent from discussions at the
workshop. Specifically, there may be a social component to the
communication of worry, particularly among people who feel at risk of a
particular disease and whether they seek out family advice or spend time
talking to professionals, and more importantly, whether they talk to
other people. Other people's worries, which may be misapprehensions, are
communicated and could lead to a spiral of misperception that is
communicated. He described a study that he and his colleagues recently
completed, in which a cohort of high sensation-seeking and low
sensation-seeking adolescents viewed a series of anti-drug
advertisements. These teens then were broken out into groups and
participated in electronic "chats" with each other. The investigators
found a boomerang effect in that teens who spent time chatting with each
other developed stronger pro-drug attitudes. Teens who disliked that
advertisements tended to be the high sensation seekers and were more
expressive. By virtue of being more expressive, they communicated their
dislike of the advertisements and created more pro-drug attitudes among
the low sensation seekers. In conceptualizing risk rather than
understanding the pathways to risk, this is a potential social pathway
that is worth including.

Dr. Cameron agreed, noting that it would be an excellent topic for a
future meeting. How to directly or appropriately measure risk to predict
behavior depends on the specific illnesses, the other kinds of factors
that may be influencing behavior, the fact that peoples' risk
perceptions may be linked to completely different behaviors, and many
other factors. There are many components that researchers need to
understand about the risk-behavior link that will then feed back to
inform them on how to assess it in different kinds of contexts. Dr.
Slovic commented that one focused future direction would be for workshop
participants to come to a consensus regarding the pitfalls of working
with elicited probabilities in this domain. Additionally, to know
whether the concept of risk is useful in a particular domain, the
behaviors must be understood better, which will require more research.
There are serious problems associated with eliciting numerical
probabilities from study subjects, and alternate ways to communicate
risk probability are needed.

Dr. Millstein noted that one compelling question for future research
involves the developmental nature of risk judgment, risk perception, and
vulnerability. For example, there is a belief about adolescents having a
sense of invulnerability; whether or not it is a developmental
phenomenon is not clear, and there is conflicting evidence. If the
experiential and rational systems work in parallel and converge in
adults, does this hold true in adolescents? Is one system moving ahead
of the other in different age groups? This would have significant
implications for the development of interventions. Dr. Masse noted that
it is difficult to develop standardized scales and measures across
different age groups---the same scales do not work in adolescents and
young adults. Advanced psychometric methods potentially could be used
that involve core items that allow researchers to make comparisons while
at the same time allowing flexibility for specific items for certain
groups. This will require identifying core items and reformulating
scales. Dr. Flynn agreed, emphasizing that the adolescent situation
poses a significant challenge to the concept of risk. Researchers in
this field need to start thinking in multidimensional terms because
health risk consequences of behavior for adolescents are of minimal
importance. The social acceptance or rejection consequences of behavior
might be more important.

Dr. Weinstein asked how to measure whether a risk seems "real" to
individuals. Dr. Slovic replied that risk creates a negative feeling,
and requires a tinge of anxiety or backing away from something. The
reality is the level of this feeling. Dr. Greenwald added that one way
to establish whether a risk is "real" is to determine whether it is
associated with self. If individuals mentally associate a risk with
self, then it should be considered as real.

Dr. Windschitl noted that the workshop did not include a discussion on
the consequentialistic version of the antecedents of a behavior versus
the nonconsequentialistic (e.g., whether behaviors are preceded by
decisions that people make or whether they are preceded by something
that would not normally be considered a decision). Dr. Weinstein noted
that risky behaviors may be very different than precautionary behaviors,
which may have a larger decision component to them. Dr. Cappella
explained that there are many examples of adolescents making judged
decisions to use alcohol, drugs, etc. Data on adolescents and marijuana
use suggest that teens make very sharp distinctions between trial and
regular use. They see very clear positive consequences coming to them as
a result of drug use. The social consequences for high-risk teens are
reported to be much more positive than for the low-risk teens. Dr.
Slovic commented that if a teenager has adopted a behavior and then is
asked to explain why they have adopted this behavior, they may not
necessarily have an insight into what really was motivating that
behavior.

# In closing, Dr. Weinstein again thanked participants for attending the workshop. Before adjournment, he also asked that they forward to him any ideas for future activities to advance the discussions from the workshop.