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Quality & Quantity 34: 407–418, 2000.© 2000 Kluwer Academic Publishers. Printed in the Netherlands.

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The Methodology of Risk Perception Research

LENNART SJÖBERGCenter for Risk Research, Stockholm School of Economics, Box 6501, 113 83 Stockholm, Sweden

Abstract. Risk perception is not strictly a matter of sensory perception, but of attitudes and expect-ations. As such, it can be studied by reasonably well developed methods of attitude measurementand psychological scaling. Such measurement needs to be applied in a pragmatic fashion, however,

since the discussions of fundamental measurement and requirements of scale levels appropriate forvarious types of statistical analysis has failed in establishing a useful basis for empirical research.The paper also discuses sampling procedures and the response rate problem. In risk perception work,there is usually a bias involving too many respondents with an above average level of education, butthat variable tends to be weakly related to risk perception variables. Finally, post-modern claims andtheir rejection of quantitative methods are critically discussed.

Key words: risk perception, research methods, measurement, attitudes.

1. Introduction

Risk perception is frequently held to be crucial in the understanding and manage-ment of risk in policy contexts (Sjöberg, 1987b). Conflicting views about risksconstitute a social and political problem of considerable magnitude in many con-texts (Sjöberg, 1980, 1998a). Furthermore, implied life values in various policy andregulatory decisions have been found to vary enormously (Morrall, 1986; Rams-berg & Sjöberg, 1997), and although the reasons behind such variation are onlypartly understood, risk perception does appear to be one important factor (Rams-berg & Sjöberg, 1998). Perceived risk, in turn, is surely not merely a function of probability of harm but many other factors, such as attitudes, enter (Sjöberg, 1996,2000).

The present paper takes as a starting point the notion that risk perception, of the public, of experts and other special groups, is important and hence the question

arises how it should be investigated. We have here a question which may seem

This is a study within CEC project RISKPERCOM (Contract FI4PCT950016), supported alsoby the Swedish Council for Planning and Coordination of Research (FRN), the Swedish Council forHumanistic and Social Science Research (HSFR), the Swedish Nuclear Power Inspectorate (SKI),and the Swedish Radiation Protection Institute (SSI)



408 LENNART SJÖBERG

simple and innocent at the surface, but it calls for opening a can of worms, or evenseveral such cans . . .

2. Is There Such a Thing as “Perceived Risk” – And If So, What Is It?

First, can risk at all be “perceived”? It may be argued that it cannot, since there isnothing “out there” which can be called “risk” and which can be sensed. Hence,there is no risk perception, cp. (Brehmer, 1987)!

This argument would seem to be the beginning and the end of the debate, butthings are not that simple. True, risk cannot be sensed, only dangers and threats.Risk is about a future event, and future events can be imagined or construed, notsensed, unless you are a psychic or a new Nostradamus. Furthermore, risk is aboutboth the likelihood, or probability if you prefer, of harm and the size and quality of the harmful consequences, should they occur (Drottz-Sjöberg, 1991). Hence, riskis something quite different from perception in the technical sense of the word asused by students of the psychology of perception and sensation.

Yet, the term caught on in the 70’s, and seems to be here to stay, in spite of itsbasically confusing meaning. Perhaps there is no more handy word in the Englishlanguage, as there is in, say, Swedish or German, and perhaps the term is attractivebecause it leads the thoughts to “perception mechanisms”; a simplistic view of riskperception as being stimulus driven. Nothing could be further from the truth, of course – since there is not even a stimulus around! Risk perception is all aboutthoughts, beliefs and constructs (Sjöberg, 1979).

The point can indeed be made that risk perception is not, at least not onlyor mainly, a question of cognition. Now, cognition is a term just as confusing

as perception. It refers to “higher” mental processes such as thought, memory, judgments and decision making and is supposed to be more flexible, less boundby the environmental contingencies, than perception (Brunswik, 1956; Sjöberg,1971a). Maybe risk perception is a question of subjective probability, which in turnpossibly is to be understood as a function of “heuristics” (Tversky & Kahneman,1974)? Many researchers seem to have believed this in the 70’s, on the basis of theelegant work by Tversky and Kahneman on subjective probability. However, twofatal mistakes were made. First, risk is not only a question of probability even if probability is quite important in accounting for risk. Second, and more important,the heuristics work took its basis in probability calculus problems and was basedon counter-intuitive solutions to some problems of that kind. The generalizability

of this work to “real world” problems of risk perception is highly tenuous and spec-ulative, although there are a few cases supporting it to some extent (e.g., McNeilet al., 1982). Risk is very seldom connected with well specified calculus problems– other factors enter and mathematical analysis of perceived risk is usually intract-able or even irrelevant. The heuristics work attempted to establish risk perceptionas a cognitive phenomenon governed by certain biasing factors that could in turn



THE METHODOLOGY OF RISK PERCEPTION RESEARCH 409

be explained as necessary for dealing with problems of cognitive constraints andcognitive delusions or simply lack of education about probability and its laws.

But risk perception, again, is a question of beliefs about risk, and as such itis akin to many other phenomena which have been investigated by social psy-chologists under the heading of attitude, see Eagley and Chaiken (1993) for anextensive review. Attitude has many determinants and ramifications – cognitivelimitations play a minor role here. Risk perception should hence be more closelyrelated to social than to cognitive psychology and cannot be understood by thedemonstration of faulty intuitions in probability calculus, however elegantly theyare demonstrated.

3. How Can You Investigate Such a Seemingly Elusive Phenomenon as

People’s “Perception” of Risk?

The first answer to the question of the subheading is that you can investigate it inthe same way as other beliefs and attitudes. There is a wealth of research whichhas shown, since the first attempts were made by Thurstone in the 20’s (Thurstone,1928), that attitudes can be measured. I even venture to assert that it is not thatdifficult to measure beliefs and attitudes. People can be asked to make ratings of size of perceived risk on a scale, say, from 0 (no risk) through a number of definedcategories to a maximum risk, perhaps defined as “an extremely large risk”. Suchratings have been found to be quite useful. Other, more complicated, ways of ratingsubjective intensities have been suggested and used in psychophysics and relatedwork in perception, and also with regard to constructs and beliefs (Ekman, 1961;Ekman & Bratfisch, 1965; Ekman & Sjöberg, 1965, 1971b; Stevens, 1957). How-ever, these so-called ratio scaling methods have not turned out to give more useful

data than the simpler category ratings and they do provoke protests from subjectswho feel that they cannot give such precise estimates of their belief strengths ascalled for in the instructions.

The discussion of scale levels must be mentioned here, since it still is brought upin discussions of appropriate data analysis, especially by statisticians. The debatestarted a long time ago, in the 40’s, and was carried over into psychology by S.S. Stevens who argued against category scales. These scales, according to him,were biased in a nonlinear manner and should be replaced by some variation of magnitude estimation or ratio ratings, which were supposed to yield ratio scales.However, as mentioned above, the ratio rating methods gave rise to a host of dif-ficult methodological problems (Sjöberg, 1971b) (mostly just ignored in the ratio

scale tradition), while Anderson managed to show, in a very extensive research pro-gram, that category scales had many desirable quantitative properties (Anderson,1996).

The measurement tradition later led to attempts at devising methods for repres-entational measurement. Although some valuable conceptual insights came out of this work, it has resulted in few practically useful methods (Cliff, 1992; Dawes,




1994b), and the psychometric tradition, based on classical test theory (Gulliksen,1950) prevails (Judd & McClelland, 1998).

Logically speaking, category rating scales could be extremely misleading. Sup-pose one category interval is subjectively 1000 times larger than the others. Insuch a case, analyses that assume all intervals to be equal could be quite invalid.However, nothing suggests that such extreme deviations actually occur. And even if there are some mild deviations from strict linearity, they probably play only a minorrole and can be safely disregarded. As a check, some simple forms of statisticalanalysis can always be carried out with ordinal statistics. When this is done, resultstypically coincide, more or less, with those based on conventional metric analyses.

It is plausible that category rating scales carry more information than the simpleordinal one, in particular also some valid information about the order of the inter-vals. If this is true, they yield ordered metric scales and it has been shown thatsuch scales are close approximations to interval measurement (Lehner & Noma,1980). It can be concluded that psychological rating scales give close enough ap-

proximations to interval scales; restrictions on numerical assignment, posed by thescaling methods, are large enough to rule out widely divergent numerical repres-entations. Hence, the data analyses will be robust with relation to the finer detailsof measurement.

However, this argument is not widely known or tends to be buried in a wealthof more or less sophisticated measurement discussions. There is frequent criticismof quantitative approaches, ranging from the naive “a 4 could just as well be a5” to more elaborate arguments built on the logic of measurement rather thanthe psychology of measurement. The result of these uninformed and destructivestandpoints is a flight from quantitative methods altogether.

Thus, it is commonly argued that risk perception should be studied by “soft”

methods such as “depth interviews”, and that surveys are unnecessary or evenmisleading. It suffices, apparently, to interview in an unstructured way a handful of persons to get an idea about risk perception in a population! Social scientists know,however, that this is indeed a very dangerous route to travel.

The notions of soft methodology have been historically closely connected withsome schools of clinical psychology and psychiatry, most notably the so-calledpsychodynamic schools. These are based on the work by Freud and Jung a centuryago and use many variations of their basic conceptual contributions. In risk per-ception work, we have seen the launching of ideas about “radiation phobia”, see(Drottz-Sjöberg & Persson, 1993) for a critical discussion. Jungian ideas appearto be attractive to some investigators of risk perception (Fritzsche, 1995, 1996).Yet, current discussions of the psychodynamic schools leave little doubt about the

frailty of these theories and their accompanying methods (Crews, 1996; Macmillan,1991; Noll, 1994).

In addition to these critical comments on soft methodology, it should be stressedthat people can make (approximately) valid ratings of intensity of their beliefs,while interviews are likely to be subjected to many interviewer biases. The latter is




true also of telephone interviews, which are becoming increasingly popular. Fur-thermore, people can be prompted, in interviews, to construct negative scenarioswhich have little or nothing to do with their spontaneous risk perception as revealedin responses to a questionnaire eliciting risk perception ratings. Especially sensit-ive questions, and risks are indeed sensitive matters, are best studied by mailedsurveys which can be answered anonymously (Wentland & Smith, 1993). The factthat mailed surveys are much cheaper than other methods speaks in their favorwhenever the other methods have not been found to be clearly superior. The oftenclaimed low response rate of mailed surveys can be greatly improved (Dillman,1991).

It is sometimes argued that interviewers can monitor and guide the processand correct any misunderstandings etc., and that this is an important advantage of interviews over mailed surveys (Suchman & Jordan, 1990); see Schlegloff (1990)for a critical comment. The questions themselves appear to be a major factor in ac-counting for answers to a survey, whether it be administered face-to-face or by mail

(Schwarz et al., 1998), while interviewer variability, in standardized interviews, is arelatively minor factor (Groves, 1989). Yet, in highly unstandardized interviews of the “depth” interview variety there is every reason to believe that interviewers varythe questions in an uncontrolled manner and there is no guarantee that interviewersdo not affect the results they get.

On the other hand, quantitative rating scales are quite well behaved. In a meth-odological study, I investigated the properties of various response formats usedfor studying risk perception (Sjöberg, 1994). It was found that all formats gaveessentially linearly related results, but that some of them gave data which weremore efficient to discriminate among hazards. Category scales with a limited num-ber of response categories, say 5 or 7, appear to be preferable. The scale used

in the psychometric paradigm (see Englander et al. (1986) for an example), with21 categories, turned out to be inferior. Graphical rating scales also appear to beinferior. Too many categories may be confusing to people.

So far the present discussion dealt only with risk perception explicitly, i.e., withinstructions where people are asked to judge perceived risk. Other terms are com-mon, such as concern, worry and safety. It would be interesting to know what arethe most common ways of operationalizing “risk perception" in applied work, andwhat the basis is for choosing one approach or another. One example is providedby work on industrial accidents where workers were asked to judge if they felt safeduring the execution of various tasks (Rundmo & Sjöberg, 1998).

Still other possibilities exist. Some current work is focused on worry and con-cern rather than risk. E.g., ratings of worry and worry characteristics were obtained

by MacGregor (1991) but they were not related to perceived risk. A study of con-cern and a number of other risk dimensions also excluded perceived risk level(Fischer et al., 1991). It is not obvious that worry and concern judgments canreplace judgments of risk level, consequences or other related dimensions. Ratingsof worry have been found to be only weakly related to perceived risk, however




(Drottz-Sjöberg & Sjöberg, 1990; Sjöberg, 1998d). I found this to be equally trueof general and specific worry measures. It is therefore unclear what policy implic-ations such data have. It can also be noted that a word such as “concern” is hardto translate to other languages without losing some of its essential meaning, orwithout adding some new meanings. “Risk”, by way of contrast, is a word whichappears in many languages and is clearly to be translated by its closely correspond-ing expressions (“risque”, “risiko”, “riski” etc). International understanding andcomparability are therefore probably improved when “risk” is used, as comparedwith studies using such terms as “concern”. This does not deny the need for a closerscrutiny of probabilities and consequences, of course, or for attention being paid tothe risk definitions that people use spontaneously (Drottz-Sjöberg, 1991).

Perceived risk is, by itself, not a very good indicator of demand for risk reduc-tion, which may be a more directly relevant dimension (Sjöberg, 1998b, 1999a).Such demand is more closely related to expected severity of consequences, shouldharm be inflicted by a stated hazard. This finding may seem to be counter intuitive,

but it still has been found to hold in many studies, and whether the hazard is definedas a consequence or as a risk generating activity (Sjöberg, 1999c).

4. The Accumulation of Knowledge

Any scientific field aims at the improvement of knowledge, provided that it isaccepted that there can be such a thing. Of course, Tolstoy was not a better writerthan Homer – but literature is not the same as science – or is it? I will here notaccept the “post-modern” claim that all knowledge is arbitrary and simply a matterof social construction, but I presume that "there is something out there" and thatsome statements about that something are better than others. It is our job to improve

on statements about risk perception. How can this be done? Psychological researchis full of traps (Sjöberg, 1981, 1983, 1987a, 1998c).

A common procedure is that of hypothesis testing. A model or theory of somekind implies hypotheses, almost always of the kind “X and Y are related” or “A isdifferent from B”. Straw men in the form of null hypotheses are then set up andstatistical analysis is used to derive a measure of how likely the actual data wouldbe, given that the null hypothesis is true. If this probability is low, it is concludedthat the proposed hypothesized relationship “probably” exists.

There are many problems with this so far dominating approach to the accumula-tion of knowledge in the behavioral sciences. One is a very basic logical one; evenif the null hypothesis is unlikely one cannot logically deduce that the alternative

hypothesis is likely (Falk & Greenbaum, 1995). In an attempt to defend the tradi-tional approach to hypothesis testing, Hagen argued that deductions need not at allbe logically correct, or that bizarre conclusions can be drawn in a logically correctmanner (given a bizarre premise) (Hagen, 1997b). Clearly, the apparent necessityto use such obviously invalid or irrelevant arguments suggests that there is no reallygood way to defend the received wisdom of hypothesis testing . . . .




Another problem is that statistical significance is so easy to obtain. Perhapsthat is a major reason for its popularity. All it takes, even with very minusculeeffects and correlations, is a moderately sized sample. Researchers typically huntfor significance, and journal editors, the gate keepers of Academia, rarely ask foranything more by way of quantitative results. Any hunch can typically gain some

small effect in data, and scientific divergence rather than convergence is the result.Research becomes something of a random walk, because minuscule effects canalways be found, and can have any of a large number of explanations. (Textbookwriters, in the next stage, seldom take up the issue of strength of relationship at all,but limit themselves to writing about “systematic” or “significant” effects.)

For example, background data are seldom thoroughly checked in connectionwith ideas about new dimensions in any field. Take cultural theory of risk percep-tion as an example. We have here minuscule effects of about 5% explained variance(Sjöberg, 1997). At the same time it is quite plausible that some or all of these smalleffects are due to gender variation, but that possibility is typically not checked out.

Researchers have been contended with the demonstration of statistical significance.It is not strange at all that the reliance on hypothesis and significance testing

brings about an explosion of complexity and that any reading of the research literat-ure which does not consider the size of effects leaves an impression of bewilderingand overwhelming multiplication of new concepts.

5. Samples

Any study of risk perception requires a sampling of respondents. The question ishow to do it and what should be required of the sampling procedure.

Many investigators have been content with a convenience sample of people that

for some reason were available and willing to participate. They then try to drawconclusions about a population. A striking example is a French study where gradu-ate students were respondents and the authors draw conclusions about the Frenchpublic at large (Karpowicz-Lazreg & Mullet, 1993). The paper was published in aprestigious journal in the field of risk research, so apparently the editor and the re-viewers were not worried about the use of a highly specialized convenience sample.Other examples are easy to find. Most of the cross-country comparison of riskperception performed in the psychometric paradigm used academic conveniencesamples and went on to comparisons of nations on this basis, see Boholm (1998)for a review. Others have used a canvassing strategy: widely different conveniencesamples have been used in order to get a notion about the range of risk perceptions

in a country (Nyland, 1993; Sjöberg et al., in press). In the latter work, there is atleast some possibility to get an impression of the within-country variation amonggroups.

Social scientists appear frequently to be pessimistic about getting randomlysampled persons to respond to mailed questionnaires. The competence to performsuch work is apparently not widely spread any more in the academic community,




but resides mainly in commercial firms who in turn have most of their experiencefrom market studies. This, however, is not a good place to start, because marketstudies are done under quite different auspices from studies of risk perception.People are clearly less than enthusiastic about spending some of their time doingunpaid work for what is obviously commercial interests. When they are approachedabout taking part in a study of important and interesting social and political top-ics, such as risk perception of technology, they react, quite understandably, in adifferent manner. We have done many studies with extensive questionnaires, up tosome 40 pages in A5 format, and found that some 60–70% of random samplesof the population at large are willing to participate for, in most cases, quite smallincentives. About 45 minutes to 1 hour is required for the task by each respondent.With special groups, such as experts and politicians, we have obtained some 10%higher response rates, as we also have in time periods when a hazard was particu-larly salient, such as in 1986 in the aftermath of the Chernobyl accident (Sjöberg &Drottz, 1987). In typical commercial applications in Sweden, pollsters report some

70% response in in-home or telephone interviews. In other words, the results areslightly better in this particular respect but at a cost about 20 times higher, and theyare probably worse due to the lack of anonymity and interviewer bias. Interviewerfraud is also a very real possibility in a certain number of the cases reported asinterviewed (Aaker & Day, 1990).

Possibly, conditions in Sweden favor a mailed questionnaire strategy and inother countries it might not work and other approaches may be called for. Yet,Dillman has devised methods that seem to work well enough with mailed question-naires in a U.S. setting, although probably with shorter questionnaires (Dillman,1991). A U.K. example is provided by the work of Eiser (Eiser et al., 1998). In ourexperience we get about the same response rate with a 20 page questionnaire as

with one containing 40 pages, however, so length of the questionnaire seems not tobe a crucial issue.Admittedly, with 60% response there may be some bias in the sample of re-

spondents as compared to the population, and with 70% response as well. Wetypically detect a bias only in one major respect: the respondents have, on theaverage, a higher level of education than the public at large. How important is thisfact?

Correlations have routinely been computed between level of education and corevariables of risk perception. It is then found that these correlations are quite modestin size. In other words, even if there is a bias in terms of level of education, this isapparently less important than one might have believed. The small bias that theremight be furthermore implies that levels of perceived risk are underestimated since

the correlation between educational level and size of perceived risk is negative.Another possible source of bias is self selection and interest. It is likely that

those who respond to any survey are people who have a particular interest inthe topics covered by the survey. It is not documented, however, that such a self




selection based on interest brings with it any serious bias, nor that it would bebiasing different response modes in different ways.

6. Conclusions

The “soft” methodology has face validity, but no more. It is expensive to use, oftengives confusing results and is very amenable to interviewer expectations and otherbiases. Its use is advocated by many who take a “clinical” approach to the studyof risk beliefs, but bringing in clinical psychology and psychiatry in risk percep-tion work seems less than useful, at least as long as normal people are studiedrather than pathological clinical groups (Drottz-Sjöberg & Persson, 1993). Clinicalpsychology and psychiatry per se are furthermore under heavy criticism (Dawes,1994a; Hagen, 1997a). The idea to pursue, e.g., Jungian theory in risk perceptionresearch (Fritzsche, 1995, 1996) seems to be, at the very least, futile when thebasic theory itself is shown to be incoherent and largely incomprehensible, andat least partly based on outright fraud (Noll, 1994). The entire “post-modernist”philosophy of social research is of course an ever present factor of importance indiscussions of method; see Windschuttle (1996) for a clear and illuminating exposeof the lack of scientific and logical basis for these claims. It is to be much regrettedthat critical discussions of quantitative methods seem to have provided impetus towhat is so much worse: uninhibited subjectivism.

The criticism of quantitative risk perception research is just a special case of thelarger debate about “positivism”. This is not the place to enter into that debate. Butone dimension can be mentioned, viz. that of simplicity or cognitive economics.

It is easy to produce a wealth of information about anybody’s risk perception.People can talk for hours about risks, and they can easily construct risk scenarios.

Things can go wrong in so many ways, but right only in a few. Worry is an essentialpart of the human predicament. The question is what to do with such informationand how valid it is. It is exceedingly difficult to summarize all of the details, evenwith a small number, say 30, of interviews. How important is a given respondent’sidiosyncratic notions about any given hazard?

The quantitative approach tries to do the opposite from the qualitative one.Instead of generating more and more details and new aspects, it is a way of singlingout the few dominating and most important themes. The idea is to simplify ratherthan to complicate. The simplified picture allows both the researcher and the policymaker to concentrate on what is important – knowing very well that there is muchmore to the topic for those who want completeness or to enjoy the pleasure of mul-

tiplicatory complexity. The potential value of risk perception research for policymakers has been discussed elsewhere (Sjöberg, 1999b).Science cannot proceed without simplification. It is the basic presumption of

science that simplification is both necessary and possible – and that all problemscannot be treated at the same time. The most tractable and important ones shouldcome first.




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