**Conceptualizing and Measuring Risk Perceptions 4/6/2003**

Neil D. Weinstein

Rutgers University

The volume of research on the determinants of health behavior is
enormous, but that does not mean that the research is sophisticated
about the constructs involved. In nearly all of this literature, the
complex topic of how people think about risk is reduced to only two
variables: a rating of probability and a rating of severity. A major
reason for convening this workshop is to question whether these are the
only features of hazards to which people attend and, if we agree that
they are not, to ask what other features researchers ought to consider.

Table 1 contains a list of questions about risk perception that I would
like to raise in this meeting. First, how do people think about
probability? Having to take into account the likelihood of a particular
event happening to us is such a central task of daily experience that we
must have some way of analyzing, thinking about, or remembering this
issue, but *how* do we do it. We are not born with numerical risk
scales; I doubt very much that there is any type of numerical reference
point in our brains. But what information or expectations do we store to
summarizes our beliefs or experiences with events? Are their "natural"
categories of risk probabilities...ways that people naturally classify
the likelihood of events? Perhaps people get by with a simple,
4-category system for probability: no chance, low, high, and certain. If
we can discover the categories or cognitive structures that reflect how
people think about probability, that will give us advantages both in
predicting their actions and also in communicating risk probabilities.
If we communicate with concepts and categories that are natural to
people, it should help them understand risks better.

A second question is, "What are other hazards attribute are important?"
The severity construct has always bothered me. It seems so unrealistic
to assume that everything other than probability can be summarized by a
single dimension. It is not difficult to think of specific features of
hazards that appear to affect us: hazards that are far in the future
generate different reactions than ones that are just around the corner;
hazards may or may not cause pain or disability; some have catastrophic
potential, potentially affecting many people, but others affect only one
person at a time. Paul Slovic has done a great deal of research over the
years examining hazard attributes that influence judgments about the
acceptability of technologies and the need for government regulation
(Slovic, 2000), but parallel research on how people think about hazards
for themselves\--in particular, about their need to protect
themselves\--has never occurred. In planning whom to invite to this
workshop, I asked Paul if anyone is studying whether individuals'
personal decisions and behavior are influenced by hazard dimensions
other than severity and likelihood. We were not able to identify someone
who could speak to those issues. In fact, there is hardly any health
behavior research that studies how various hazard attributes relate to
severity judgments or whether these attributes affect judgments
independent of severity judgments.

In addition to objective features of a hazard, such as its probability,
its speed of arrival, and the nature of its harm, one can ask about
"subjective" features of hazards, ones that can only be defined in terms
of an interaction between the event and the individual. For example, a
hazard may be experienced as more or less vivid than others. A hazard
may be thought to have a simple causality, making it easy to think of
ways---"scenarios"\--in which they might happen. In contrast, for
another hazard or person, the causal mechanisms and situations that
could put us at risk are obscure. Infectious diseases seem to be a
category of hazard in which causality---through direct, physical
contact---is easy to visualize for most individuals, making people
relatively risk averse. It is highly unlikely that all the hazards
features listed in Table 1 are taken into account by a simple rating of
severity. Looking for their separate effects would be a place to start.

There will be much discussion of emotion and affect in the rest of the
workshop. It is very important to ask where these issues fit into the
hazard response equation. It is not just fear that can be important;
anxiety, anger, and depression also need to be considered. Do people
regulate and try to manage their emotions separately and differently
from the way they manage and regulate danger? Howard Leventhal initiated
and developed that idea in the domain of health behavior (1970), and Kim
Witte has continued to study these issues (Witte, 1992), but affect is
still absent in nearly all current health behavior theories. Other
speakers are going to address these issues.

There is another class of constructs\--worry, preoccupation, vigilance,
intrusive thoughts---describing our reactions to hazards that may have
strong effects on decisions and actions. Clinical psychologists refer to
worry as a cognitive variable, but cognitive psychologists think of
worry as an emotion. Neither group knows quite what to do with it.

When I mention worry and the other questions in Table 1, I'm not just
brainstorming about possibilities. There is research---though not a
great deal---demonstrating that these issues make a difference. How do
we weave them together into a more complete notion of how people
appraise hazards?

In addition to focusing on what people tell you about their beliefs on
questionnaires or in interviews, we should also be asking about the
differences between beliefs that are firmly established and ones that
are tentative and easily changed. For example, judgments about hazards
that are based on personal experiences are likely to be very different
from judgments made about a risk that the respondent had never even
considered until faced by a researcher's questions. In the study of risk
perceptions, is there a difference between *judging oneself as being
vulnerable* (possibly a spur-of-the-moment rating unlinked to past or
future action) and *feeling vulnerable* (possibly a consequence of past
victimization and personal experience). In hearing about studies of
adolescents' risk perceptions, I often imagine them responding, "yeah,
that *might* happen" without the risk seeming either real to them or
worth serious attention. But what does it mean to say that a risk "seems
real"? This distinction is clearly related to Epstein's distinction
(1994) between the rational and the experiential systems.

The short-term goals of this workshop are (Table 2) to examine the
meaning of perceived risk from a variety of research perspectives, and,
by doing so, to arrive at a more sophisticated and more comprehensive
conceptualization of perceived risk and at better ways to measure
perceived risk. In the long run, I hope that careful study of perceived
risk will improve the ability of theories to predict health behavior. An
improved understanding of risk perceptions should help us to identify
risk issues and dimensions that could make interventions more effective.
Such an understanding could also help applied researchers find better
ways to assess whether their interventions have succeeded in changing
the way the hazards are perceived.

Next, I would like to offer a personal anecdote. Some years back, I
returned home with my family after dinner at a neighbor's house at
around 9 o'clock in the evening. All the lights were on in our house,
and we knew immediately that something was wrong. We had not left the
lights on. When we entered the house, we realized that a burglar had
just left. Jewelry, a camera, and a few other items had been stolen. It
was upsetting, but it was not a traumatic experience. The house was not
torn apart; the camera was found in the back yard; and the jewelry was
replaceable. But from then on, we always took extra care to lock the
door and to leave lights on whenever we went out.

I've asked myself many times what it was in that experience that changed
my behavior. It seems a wholly insufficient explanation to say that my
beliefs about the probability or severity of victimization had changed.
If I had to make an estimate of the likelihood of burglary, I suppose
that my estimate might have gone up slightly, but I don't think that's
it. What stood out in my response was the enormous change in the
*availability* of thoughts about burglary. For years after, every time
we drove home in the evening, I found myself watching to see if the
lights were those that we had left on. Maybe the frequency of thoughts
about a risk---whether produced from internal or external sources\--are
as important as the content of those thoughts in motivating action. Here
are some data that touch on this issue.

The data in Table 3 come from a study of three communities after they
had been struck by very serious tornadoes (Weinstein, Lyon, Rothman, &
Cuite, 2000). Our aim was to predict which community residents would
take recommended actions to make themselves better prepared for the next
tornado. Who would put aside water and a transistor radio, designate an
area in their home as the safest place to go, or create a plan with the
family for what they would do when the next warning occurred? In
interviews immediately after the damaging tornado, we assessed
residents' views about the absolute likelihood of future tornadoes and
about relative likelihood (comparing their town and their home to other
towns and other homes in the same state). We assessed how anxious they
were when thinking about tornados. And we posed questions about
vigilance (how easily tornadoes come to mind in various situations, such
as when you see a dark cloud overhead), frequency of thoughts, and
intrusive thoughts. We gathered these latter questions together into a
composite variable we called preoccupation.

If we look at the column in Table 3 referring to initial actions, we see
that high anxiety actually impeded protective action, but preoccupation
was strongly and positively associated with taking more precautions. But
these are only cross sectional data, based on interviews conducted two
weeks after the tornados. Fifteen months later, we interviewed people
again to learn about the actions that they had taken in the subsequent
time period. The data in the right hand column of

Column of Table 3 refer to actions at one year, controlling for initial
action. Likelihood judgments, whether absolute or relative, did not
predict who would take more action, whereas preoccupation remained a
strong predictor. Thus, frequency and availability of thoughts about
hazards seems to have predictive power beyond that of judgments about
risk likelihood.

In a different study currently underway, we have been looking to see who
would get vaccinated for Lyme disease. We first interviewed people
before the Lyme vaccine was available; it had been approved by the FDA
only a month or two earlier. The interviews covered a range of topics,
including intentions to get vaccinated. Among other factors, we looked
at perceptions of absolute likelihood, worry about getting Lyme disease,
and frequency of thoughts about Lyme disease. We then came back a year
later and reinterviewed 745 people to find out who had actually received
the vaccine. This study has a nice simple behavioral outcome: you get a
shot of the vaccine or you don't. The left hand column of Table 4 shows
the cross sectional predictors of vaccination intentions. You can see
that worry was the best predictor of intentions. When we look at actual
vaccination 15 months later, worry was still the best predictor although
perceived likelihood of getting Lyme disease if not vaccinated, and
frequency of thoughts about Lyme disease were also good predictors of
action.

+------------------------------+------------------+-------------------+
| **Table 4: Lyme Disease      |                  |                   |
| Vaccination Predictions (N = |                  |                   |
| 745)**                       |                  |                   |
+------------------------------+------------------+-------------------+
|                              | Intentions to    | Vaccination 15    |
|                              | get vaccine      | months later      |
|                              |                  | (odds ratio)      |
|                              | (Pearson's r)    |                   |
+------------------------------+------------------+-------------------+
| ***Absolute likelihood***    | .27\*\*\*\*      | 1.60\*\*\*\*      |
|                              |                  |                   |
| (6-point numerical scale;    |                  |                   |
|                              |                  |                   |
| 0%\--100%)                   |                  |                   |
+------------------------------+------------------+-------------------+
| ***Worry about getting Lyme  | .36\*\*\*\*      | 1.78\*\*\*\*      |
| disease in the future***     |                  |                   |
|                              |                  |                   |
| (4-pt scale; not at all -- a |                  |                   |
| lot)                         |                  |                   |
+------------------------------+------------------+-------------------+
| ***Frequency of thoughts     | .30\*\*\*\*      | 1.36\*\*\*\*      |
| about Lyme disease***        |                  |                   |
|                              |                  |                   |
| (3 questions; a=.69)         |                  |                   |
+------------------------------+------------------+-------------------+

However, there are many ways to assess perceived likelihood, and, as I
suggested earlier, perhaps there are natural categories of likelihood.
If we can identify such categories we should get better predictions.
Consequently, this study had actually included several different
likelihood scales. We had a 6-point percentage scale, a 5-point verbal
scale, and a simple, little 2-point scale, "Is it unlikely or likely
that you will get Lyme disease if you don't get vaccinated?" All of
these scales significantly predicted who would get vaccinated. However,
the 2-point scale was clearly the best predictor. In fact, once we put
the 2-point verbal scale into the prediction equation, none of the other
scales, including the worry scale, added anything new. Those people who
said that they were likely to get Lyme disease if not vaccinated were
about five times more likely to get the vaccine than those who thought
they were unlikely to get the disease. That is a very large difference.

+---+-------------------------------------------+------------------------+
|   | ## Table 5: Risk Question Wording         |                        |
|   |  and Lyme Disease Vaccination Predictions |                        |
+---+-------------------------------------------+------------------------+
|   |                                           | Vaccination 15 months  |
|   |                                           | later (odds ratio^1^)  |
+---+-------------------------------------------+------------------------+
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+---+-------------------------------------------+------------------------+
|   | ***6-point percentage scale***            | 1.60\*\*\*\*           |
|   |                                           |                        |
|   | 0-1%, 10%, 25%, 50%, 75%,100%             |                        |
+---+-------------------------------------------+------------------------+
|   | ***5-point verbal scale***                | 1.72\*\*\*\*           |
|   |                                           |                        |
|   | definitely will not, probably will not,   |                        |
|   | equal chance, probably will, definitely   |                        |
|   | will                                      |                        |
+---+-------------------------------------------+------------------------+
|   | ***2-point verbal scale***                | 2.49\*\*\*\*           |
|   |                                           |                        |
|   | unlikely, likely                          |                        |
+---+-------------------------------------------+------------------------+
| * |                                           | 1.76\*\*\*\*           |
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+---+-------------------------------------------+------------------------+

Whether scales are treated as linear variables (1 df) or categorical
variables (3-5 df), none improves the prediction of the 2-point scale.

^1^ Based on normalized prediction variables.

The data I have just presented concern a construct, "preoccupation,"
that is not a standard measure of perceived risk and not a variable in
any of the most widely-used theories of health behavior and another
construct, "worry," that is also not a standard measure or theory
ingredient. The data also demonstrate how conclusions can differ as a
function of different likelihood measures.

I have tried to point out issues that take us far beyond the way risk
perception is normally considered in health behavior research. My data
suggest that these issues make a difference, that the standard
interpretation of risk perceptions as reducible to ratings of likelihood
and severity fails to address essential questions about the meaning of
perceived risk and provides a misleading impression about the strength
of links between perceptions and action. The remaining speakers in this
workshop will raise additional questions about the conceptualization and
assessment of risk perceptions.

##### **References**

Epstein, S. (1994). Integration of the cognitive and the psychodynamic
unconscious. *American Psychologist, 49*, 709-724.

Leventhal, H. (1970). Findings and theory in the study of fear
communications. In L. Berkowitz (Ed.), *Advances in Experimental Social
Psychology*, pp. 119-186. New York: Academic Press.

Slovic,P. (2000). *The perception of risk*. Sterling, VA: Earthscan
Publications.

Weinstein, N. D., Lyon, J. E., Rothman, A. J., & Cuite, C. L. (2000).
Preoccupation and affect as predictors of self-protective behavior
following natural disaster. *British Journal of Health Psychology, 5*,
351-363.

Witte, K. (1992). Putting the fear back into fear appeals: the extended
parallel process model. *Communication Monographs, 59*, 329-349.