Dispositional, Unrealistic, and Comparative Optimism

Dispositional, Unrealistic, and Comparative Optimism: Differential Relations With the Knowledge and Processing of Risk Information and Beliefs About Personal Risk Nathan M. Radcliffe Temple University School of Medicine William M. P. Klein Colby College

This study examined the relationship of dispositrona4 unrealis

tic, and comparative optimism to each otherand to persouai risk beliefs, actual risk, and the knowledge and processing of risk information. The study included 146 middle-age adults who reported heart attack—related knowledge, beliefs, and behaviors and read an esauy about heart a/tack risk Jizctors. Driposilional op/imdm was correlated with comparative optimism (perception of lozo risk relative to peers) but not with a variable assessing accuracy ofparticipants ‘comparative risk estimates (unrealistic optimism). In divid na/s ii igh in dispositional optimism curd comparative optimism possessed an. adaptive risk and helifpro file and knew mow ahosit heart attacks, whereas an realistically optinri.stic in di-oiduals exhibited the opposite /.rattern a red also learned relalively less of the risay material. Evidently, percep lions of low corn par (SteVe risk are relatively accir rate, (lr’sposrtional op/into in is associated in. an adaptive tr’a roil/i irrji.rrrnatiorr processing, arid ten realistic optinusru may be cissoci— ated err ith processing defter ts and deferrsiverr ess, as well as ii igher

risk.

Is

it adaptive to be optimist1c The answer to this ques don is more complicated than one would expect. Much evidence supports (he tiitUitive and lay accepted nOtiOn that having a positive outlook is associated with (aisci max even cause) favorable attitudes and health outcomes (e.g.,Arinor & Taylor, 1998; Sciraier & Carver, l99; Taxlos- $c Brown, 1988). 1 Iowcver, some r-cscarchcrs castilorl that opt imisin nsav prevent individuals from taking pro active measures to affect tire otitconses aborrtwhrcii they are optimistic (e.g., Weinstern, 1989), a caution snider— lined by models linking risk I CCCL1Oi55 with behavior

(e.g.,Janz & Becker, 1984). Understanding the costs and benefits of optimism, however, necessitates a careful examination of how optimism is defined. In this investi— gatsoir, we explored three conceptualizations of opti mism: dispositional optimism, unrealistic optimism, and comparative optimism. We considered how each is related to actual risk and how they are related to each other. Moreover, we investigated how each may be related to knowledge and beliefs about Personal risk and risk factors and to the ability and willingness to learn new information about how one might reduce personal risk.

Definr rig arid Measuring Optimism Dispositional optimism (Scheier & Carver. 1985) cap tures optimism in tire most conventional sense of the Authors’ Note: This investigation was supported 6 y Colby College So cial Science Granrs 01-2203 and 0 1-2200 and a grain From I he Colby College Dean”, Fund for Students’ Special Projects (02-2620-65126827). The snrrh’ was cotrilmtcte(l as the first author’s horrors rlresis mitt dee tire di mcclii) i of fire secon ci suit i or trim d was pm eserr ted at the 1999 meetings of the European Health Psychology Socieo’ in Florence, It_sit’. We arc grateful to Er-jim CuIc-Karagumy lorscrvinmg as an experimenter; Melanie Thompson br her medical expertise: Dorothy Evertsen, Jennifer Freese, and Jacqtreline Ogrrrha for assisusure with schedtmling; tire Colby Health Center for iii cii assistance with supplies and ntredrcal procedures; Edward Hrrmcluns for helpful advice on rise of the Health Risk uppt aisal (I IR) tire Star ne DartrnouLlt Fanrrilv Practice lbr their hmelpwith mecruitmemmm: aricljen iv Suis and two anonymous evmcwems for helpful smrggr’srious on ant earlier version of rite armiclc. Curvc’spun— mience cotlcerninrg this to fiche rosy he addressed to tire secortcl arttlmor at Dc’parrnmeni of Psvchoiogy, Colhv College, Waterville, StE 04901; nail: wmnttlcitrtr)coiby.cdu. J’SPJI, Vol. 23 No 6, Jrme 2002 836-846 © 2002 by the Society for Personality and Social Psychology. Jut.

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Radclilfr, Klein

term and is clef ned as the generalized positive expec tancy that one will experience good outcomes. It is typi call) measured using the Life Orientation Test (LOT) (Scbeier, Carver, & Bridges, 1994), which includes state ments such as “Tin a believer in the idea that ‘every cloud has a silver lining.’ We might also define optimism in terms of expectan cies about specific events (Armor & Taylor, 1998) One relevant literature is that on “unrealistic optimism” (or “optimistic bias”). In a typical study, participants rate their chances of experiencIng a health or safe iv problem on a scale ranging from much below average to much above aver age, with a nddpoin t. of asooge. In many investiga tions (riiore than 300 in a bibliography prepared by deinsteiu. 1998), [lie observed sample mean is below the midpoint, represeuti ig a self—serving bias about the chances of experiencing his event (assuming risk is dis tributed normally). Such a bias emerges for a variety of health and safety issues (for review, see Heiweg-Larsen & Shepperd, 2001). Of importance, because participants in these studies rate their risk relative to that of the average peer, their judgments are social comparisons rather than absolute judgments. The comparative nature of these risk jtidg ments is exactly why unrealistic optimism is easy to mea sure at the group level; one does not need to know each persons actuarial risk to infer bias because whatever the average risk, it is unlikely that a majority of the sample can be below it. Compai-ative risk may not be only meth odologically useful but also psychologically important. First, people’s understanditig of objective risk is limited and subject to much bias. They tend to uiiderestiinate large risks and overestimate sniall risks (e.g., Slovic. 1987) and have trouble thinking about us k in terms of acids and percentages (Diefenbach, Weinstein, & O’Reilly, 1993). it is simply easier tojudge how one’s risk compares with that of other people, regardless of the absolute risk levels. Second, there is emerging evidence that social comparisons are central to the estimation of personal risk. Indeed, people engage ifl several strate gies to protect their favorable comparative risk assess ments (Klein & Weinstein, 1997), an iniportant point given the possibility that such ratiugs are simply proxies for absolute risk perceptions (Wood. 1996). Unrealistic optimism differs from dispositional opti— nusin not only in terms of speciticity and social compari son but also because of the accuracy component. Dispositional optunisni is siniplv an orientation that can not be said to be accurate or inaccurate, whereas unreal istic optimism is a bias. ( onsequentlv, in this invi:stig:i— ion, we also consider a third type of optimism: comparative optimism, or the belief that one’s risk is below average without regard to whether this beliet is correct). Caiiparauve optimism and tusreahisuc: opti

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OPTIMISM AND RISK

837

mum are alien conilaterl in research on risk (e.g., lPewherrv, Ing, James, Nixon, & Richardson, 1989). Whereas the standard method of measuring unrealistic optimism can establish bias at the group level, there is no way to know which members of the sample are biased. Some individuals who rate their risk as below average may have a risk factor profile that puts them at below average risk, so it would be inappropriate to label them as unrealisttc (Weinstein & Klein, 1996). Also. indtvidu als ansm’here on the scale can be optimistically biased: for example. a person may consider his or her risk to be only moderately above average (an apparently pessuuis tic stance) when in fact this persons risk is well above average (making the judgment unrealistically optimis tic). Consequently, ordinal position on the scale does Hot necessarily reveal anytlung about bias. As Colvin and Block (1994) note, “the absence of an niclepetident, external, subsequent life criterion against which an mdi— virlual’s current optimism univ be judged as realistic or mirealistic renders suspect and perhaps erroneous all attributions of accuracy or error” (p. 12). Iii tact, people’s comparative ratings may be ordinallv accurate. Indeed, nonsmokers give lower personal risk ratings for smoking-relitteci diseases than do smokers (McKenna, Warhtirton, & Winwood, 1993), people with a family history of breast. cancer give higher ratings of personal risk for hi-east cancer (e.g., Lipkus, Rimer, & Strigo, 1996), and prostitutes give higher personal risk estimates for HIV (van cler Velcie, ian der Pligt, & Hooykaas, 1994). In most cases, high-risk individuals underestimate their risk (Strecher, Kreuier, & Kobrmn, 1995), yet they still rate themselves more lnglilv than do low-risk individuals. When assessing time difference between unrealistic and comparative optimism, clearly one must measure the accuracy of the comparative risk perception. The i-Tealth Risk Appraisal (HPA), designed by Lewis Robbins, is one instrumen tthat can do so. Tins instrument uses epiclennological data (mcli as those collected in the Framingham study) in commjmiction with participant data (including physiological nieasures) national muortahits’ norms, and regression tornmulas. If used properly, HRs can predict 1 (i—year iriortahty risk with :ni impressive degree of accuracy (G:izmnararian, Foxnian, Yen Morgenstermi, & Ldingtoit, 1001; Peterson. 1906). cotnpanimg iii individuals I IRA—calcimlaterl risks with the population average for that person’s age and sex, one can determine an individual’s comparative nsk for a spe cific health problem. HRAs are more accurate at predict ing comparative risk than they are at predicting absolute risk (Sclioenbach, 1987’), which is convenient given the emphasis on comparative risk here. One can then com pare an individual’s actual comparative risk with his or (icr estimauon of that risk to determine if that individual ,

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PERSONALITYAND SOCLkL PSYCHOLOGY BULLETIN

is unrealistically optimistic (Kreitter & Strecher, 1995; Skinner, Kreuter, & Strecher 1994). ldaJ,tiveness of Otimisin We consider in this investigation the extent to which these three types of optimism—dispositional, unrealis tic, and comparative—might be adaptive. The term adaptive, defined here, refers not only to the relationship of optimism with lifestyle and physical health but also with beliefs, knowledge, and the processing of health

information. For example, ifawoman is optimistic about her colon cancer risk, is she more informed about the risk factors for breast cancer, able to learn more about this disease, and willing to consider information that ought challenge her optimistic stance? If so, lice opti— mismn might he said to he adaptive. Dispositional optimism. Generally, it is found that peo ple high in dispositional optimism have better overall physical health, report being bothered by fewer synip toms of illness, adjust better to important life transitions, cope better with stress, recover faster from coronary artery bypass surgery, use more problent-tocused coping strategies, handle illness more effectively, and are more likely to accept or resign in a situation that appears to be uncontrollable (e.g., Aspinwail & Taylor, 1992; Scheier & Carver, 1985; Scheier et al., 1989, 1994). There is also evi dence that dispositional optimists are attentive to rele vant health information, even if it is threatening (Aspinwahl & Brunhart, 1996). (T,,alotiC optimism. In a review of the literature, van der Pligt (1998) reported that comparative optimism was generally not associated with detrimental behavior, a finding consistent with our contention that comparative optimism uiay reflect relative accuracy in risk perception and that it should not be a cause for concern. 1-lowever, wheim coimiparative opulnisiri is unrealistic, is it equally liarimiless? Consider the dehate on the adaplivcIiess of depressive realism, exemplified by the tendency of depi-essives, relative to nondepressives, to expect ami equal balance of negative and positive future life events. Tins is used as evidence to suggest that unrealistic opti— tmsni (defined here as an milameci ratio of positive to neg ative expected cvents) is correlated with positive mental health. However, it turns out that depressivcs are just as biased as anyone else because their ide circuiiistances make theiri more susceptible to greater numbers of neg ative events (Dunning & Story, 1991), leading some to fliCSUOdl whether illusions are adaptive after all (Colvin & Block, 1994). Because of the methodological clilficulnes in ineasur— ing unrealistic optimism, an adequate archive of data has yet to be collected on its correlates (when defined at the level of the individuall Moreover. uiclies uleetitig the .

definitional criterion offer conflicting conclusions (e.g., Skinner, Kreutei Kobrin, & Streclier, 1998; Taylor et al., 1992). Tn addition, cross-sectional correlations between unrealistic optimism (or any type of risk assessment) and behavior are ambiguous because whereas they could imply a harmful effect of risk perceptions on behavior, they could also simply reflect accuracy (i.e., high-risk perceptions result from acknowledgement of past and present risky behaviors) (Wetnstemn &Nicolich, 1993) It is erucial to partial out prior standing in such studies. One approach to the adaptiveness issue is to identify specific situations in winch unrealistic optimism is aciap tive. For example, Armor and Taylor (1998) review cvi clence that unrealistic optimism sometimes leads to the optimistic reinterpretation of outcomes and to produc tive self-fulfilling prophecies, such as when people underestimate how long it will take to complete a task and then try harder to do so (Buehler. Griffin, & Ross, 1994). 1 Iowevcr, the distal and ambiguous flat nrc of’ health threats may reduce the feasibility of these advan tages. Most studies demonstrating the role of these fac tors examine short-term performance ctoniains rather than long-term health threats. The available evidence on how unrealistic optimism is associated with attitudes about risk and processing of risk information is similarly scant Avis, Smith, and MeKirilay (1989) found that optimistically biased indi viduals were resistant to changing their risk perceptions after receiving I-IRA feedback. Wiehe and Black (1997) found that unrealistic optimists were more likely to avoid exposure to information implicating their risk. Notably, individuals having realistic high-risk perceptions in this study showed high levels of interest mu viewing informa tion about contraception and freely acknowledged its relevance, supporting the idea that unrealistic optimismil and how—risk perception are not synonynioits. Davidson and Prkachin (1997) found that individuals high in both unrealistic optimism and dispositional optimism were relatively less likely to learn new information when pre sented wmthi aim essay about coronary heart disuase (although in that study, unrealistic optimism was assessed by measuring participants’ expectations of 11 future life events witliouL taking into account tIme actual likelihood of these events). Finally, people employ sev eral strategies Umat help them to sustain their unrealistic beliefs, such as downplaying the riskiness of their helmav ior (Klein, 1996). In short, one might expect unrealistic optimism to be associated with defensive processing of risk information. Are the Various T)pes

gf Optintism Related T

As noted earlier, unrealistic optimism could occur at any level of comparative risk, nmeantng they ai-e not nec—

Radcliffe, Klein

essarily correlated. Comparative risk would seem more likely to be correlated with dispositional optimism, although several studies report a small or nonexistent relationship between global optimism and optimism about specific events (e.g., Davidson & Prkachin, 1997; Fontaine, 1994; Goodman, Chesney, & Tipton, 1995; Taylor etal., 1992). Could dispositional optimism be related to unrealis tic optnrusrn? Perhaps dispositional optirrusts might be less likely to be biased because they are more attentive to health info rmauon and therefore more informed (Aspinwall & Brunliart, 1996). On the other hand, dispositional optimists may engage in mild distortion as part of their opunustic strategy, making them more likely to reveal unrealistic optimism. Perhaps the safest predic tion, however, is that the two are unrelated, given that there is little theoretical backing to expect that people with positive orientations toward the future will neeessar— ’ have biased comparative beliefs about specific events. 1 i1 Clearly, data on the relationships among these different types of optimism are necessary. Current Study Our principal prechetion was that individuals high in dispositional optinsismn, high in comparative optimism, and low in unrealistic optinmisrmi would reveal the most favorable profic. We expected that these individuals would (a) exhibit the best health status and stanhing on risk factors such as cholesterol and exercise, (b) have the lowest risk for having a fatal heart attack and the least worry about this risk, (c) know the most at baseline about heart attacks arid their risk factors, (d) reveal more accu rate beliefs about how their own standing on risk factors for heart attack was related to their risk of experiencing tins problem, (e) choose to read inforniation about risk factors more carefully and less defensively, and (I) retain more information from an essay we had them read. Finally, we expected that whereas dispositional optimism would be correlated with comparative optnnism, it would not be correlated with unrealistic optimism. METT TOD

Partici/iai its The sample consisted of 146 individuals between the ages of 40 and 60 (M= 49.07, SD= 5.86). We recruited participants front a fannly practice arid a factory in een— ml Maine, the Colby College campus, and via advertise ments in a local newspaper. The sample was 95% White and 69% women; 2.8% did not have a high school degree, 24% had only a high school degree, 21.9% had only some college, 24.7% had only a college degree. and 26.7% had a graduate or professional degree. Paruci

/ OPTIMISM AND RISK

839

pants completed the study individually and were monetaril compensated for their time. They completed several additional measures as part of a larger study; only those measures pertinent to the current article are reported here. Materiafc and Proceducs Most of the study was conducted via computer. After receiving a brief tutorial on how to operate the coin puter, participants read the American Heart Associa tion’s definition of a heart attack and proceeded to cons plete the dependent measures as follows.

Risk perceptions and worry. After being provided with a few numerical examples, participants compared their risk of having a fatal heart attack in the next 10 years to that of tire average same-age, same-sex person on a slid ing horizontal scroll bar (ranging from 0.1% to 1000% of the average person’s risk). After the participant set the computer’s horizontal scroll bar to a spccitic percentage, the computer would give the numerical value as well as a verbal value. For example, a participant who selected 25% would read, “I believe my risk to be 25% of the aver age person’s risk. My risk is one quarter of the average person’s risk.” This scale emphasized the plausibility of small estimates (e.g., .3%) even though much higher estimates were possible (see Rothmnan, Klein, & Weinstein, 1996). Participants also estimated their com parative risk on a 5—point scale ranging front much lower than average (1) to much higher f/san average (5) with aver age (3) as a midpoint. Because these two measures were highly correlated, r(144) = .56, p< .001, all reported anal yses used the first, more sensitive measure. Participants estimated how likely they were to have a fatal heart attack within the next 10 years on a 9-point scale (I = extremely unlikely, 9 = extremely likely) asa incasure of perceived absolute risk. They also macic this esti mate, on the same scale, for the average person of their same age and sex. Finally, participants indicated how worried they were about their risk on a 5-point scale ranging from 1 (riot at all worriea’) to 5 (extrenici worried). ,

,

Prior knowledge and beiiejs. The next set of measures concerned participants’ knowledge anti beliefs about six heart attack—related risk factors (alcohol consumption, fat consumption, nutrition, smoking, exercise, and stress). First, to assess prior knowledge, participants were asked 12 multiple—choice questions including one about each of the risk factors arid six about heart attacks in gent— eral. The questions were pretested (and revised accord ingly) to assure comprehensibility and adequate diffi culty. A typical question was, What percentage of your caloric intake shotilci conic from fat, according to the American Heart Association?” Second. items were included to assess participants’ beliefs about how related

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PERSONALITY AND SOCL\L PSYCI-IOLOGY BULLETIN

each risk factor was to the risk of having a heart attack (1 not at all related, a = extieine5’ related). Third, participants indicated how their standing on each of the six risk fac tors affected their personal risk of having a heart attack (1 = greatly decreases my chances, 5 = greatly increases my chances). Fourth, participants estimated how much they knew geiicrallv about the causes of heart attacks ott aSpoint scale (1 = nothing at all. 5 = a great deal)

RESULTS

=

Health Risk Appraisal. Next, participants completed a computenzed version of The Healthier People Net work’s Health Risk Appraisal (HRV, Version 6.0. The TIRA Contains 43 questions about. daily habits (e.g., level of physical acuvin) life satisfaction, family history, and demographics. The HR-\ protocol also uiclucles physio logical information (height, weight, systolic and dia stolic blood pressrue, and serum cholesterol) 2 ,

Dispositional optimism. After completing the HRA, par ticipants were moved to a different rooni where they completed (on paper) the Life Orientation Test (Scheier et al., 1994) in addition to other measures not related to this investigation. In the meantime, the exper imenter had the computer calculate the particIpant’s I-IRA risk. Risk factor essay. After returning to the conlputei par ticipants were asked to choose one topic they would most like to learn more about from a list of the six risk factors. After participants indicated a preference, the computer explained that participants would now have a chance to learn aboutall of the nskfactors listed, including the one they chose. Participants then read an essay (including material taken mostly from the American Heart Associa tion Web page) that briefly discussed the effects on coro— nary heart disease of the six risk factors. 5 Learning oJ risk IoJormalion. Finally, participants com pleted a 32—i teni papei’—nd—petici1 test of material iii the essay. The first 8 questions concerned general attention to the essay (such as the order in which the topics appeared) The next 24 questions included four ques tions for each of the six risk factors. The questions per tained only to information ni thin essay, and ui a pretest, no more than 70% of respondents correctly answered any particular dluestion. During the protocol (after reading the risk factor essay), we also had participants reach an essay that explained important facts about the HRA. At the end of the study, parneipants answered 10 true/false questions about this essay to attain a measure of baseline reading coniprehsension. Finally, participants were given their complete HRA results along ;unh detailed instructions on how to nterpret them and were debriefed and compensated, .

Independent Variables Dispositional optimism served as the first independ ent variable, as measured by the Life Orientation Test. Scores on this test were found to be reliable (a = .88). To deteri’nine whether each participant was unrealistically opunsistie, we began by calculating the ratio of the per sons actual HR/c-determined, fatal heart attack risk to that of the average same-age. same-sex other (also pro vided in HR/c output) We then compared this ratio with participants’ relative risk estimate on the sliding scale (from 0.1% to 1000% of the average pet-son’s risk). Those providing a risk ratio more than 10% lower than their HR/c-computed risk ratio were defined as unrealis tically optimistic (Kreuter & Strcclier, 1995). For exam ple, if the participant considered los or her risk to be 50% of the average person’s risk and in fact it was 65%, then that participant would be considered unrealisti cally optimistic. Likewise, individuals who considered themselves to be at higher relative risk than their risk ratio (by more than 10%) were considered unreahisti callypessimistic. Individuals whose relative risk estimates were within 10% of their actual risk ratios were consid ered accurate. Usnig this definition, 56% of participants were defined as unreal stically optilinstie, 19% accurate, and 25% unrealistically pessimistic. We chose this categorical rather than continuous defi nition of unrealistic optimism becatise we did not feel there was any basis for predicting a linear relationship between people’s standing on this metric antI the oilier measures we report. For example, processing deficits could very well be associated with both oprimisismn and pessimism but not accuracy, yielding a curvilinear rela tionship. In fact, as itturnecl omit, individuals in the pessi misin anti accurate categories did not differ in most anal yses, leading its to collapse these uvo groups in the reported results. Thus, we believed that the categorical metric was more appropriate. Although the 10% mliargin of error is consistent with the approach taken by others who have compared actual and perceived risk (e.g., Kreuter & Streclier, 1995). natu rally we were concerned that it could he too small. Ilow— ever, when we redefined unrealistic optnTnsin based on a 20% arid then a 40% margin of error, die results reported in thisar tide were generally simmnlar to those reported (although significance levels checreasetl as the margin of error increased) Participants’ comparative risk percept ons (prior to being compared with actual risk ratios) were used as the measure of comparative opumisin. Given the obvious dependency beiween comparative risk perceptions and unrealistic optmmism. these variables were always aria— lvzecl separately. .

Radclilfr, Klein

As predicted, dispositional optimism and unrealistic optimism were not correlated, r(142) = .01, p> .10. Indi viduals who were comparatively optimistic (i.e., had lower risk ratings) however, were higher in dispositional optimism, r(142) = —.31, p < .001. Thus, dispositional optimists possessed more optimistic risk perceptions hut not more optimistically biased risk perceptions. Evi dently, inaccuracy in one’s perceptions of the risk of hav ing a heart attack is not related to one’s general state of optimism or pessimism. Unrealistic optimists also pos sessed lower comparative risk perceptions, r(142) = —.30, p < .001, although the meaning of tins correlation is unclear given that comparative risk perceptions were used to define whether individuals were biased.

TABLE 1:

/ OPTIMISM AND RISK

Correlations of Different Types of Optimism With Princi pal Dependent Variables Contjs’iiatii’e tTnreatisiic O/)/lWtcut O/ilimi.csi

,

Detnograbhic

and 1—[a it/c Correlates

In the correlational analyses that follow, the degrees of Ireedom vary due to missing valises on sonic items. Dispositional optimism was positively correlated with highest educational level attained, r(142) = .27, p= .001, hut not sex, age, or serum cholesterol (—.09< is < .13, ns). In clividuals higher in dispositional optimism had lower systolic and diastolic blood pressure and lower overall heart attackrisk, ts(142) .28, pa < .001. Dispositional optimists therefore seem warranted in having lower coniparative risk perceptions. We also looked at the point-iiserial correlations between unrealistic optimism and these measures, although interpretation of the correlations must he approached with caution because the measures them selves were used to compute actual risk (and thus, us turn, unrealistic optimism). There were no correlations between unrealistic optimism and sex, age, or educa tional level, ,s(144) < .03, s > .10, consistent with Weinstein’s (1987) finding that uni-ealistic optimism pervades many demographic subgroups. Unrealistically optimistic individuals did have higher systolic blood pressure and serum cholesterol, ;s(l 37) > .18, pa < .001, aHd a higher overall risk of havnig a heart au.ac:k, i(143) = .29, p < .001. (Recall that unrealistic optinusts believed they possessed significantly lower risk.) Unrealistic opti mism was uncorrelated with diastolic blood pressure, physical activity, and life satisfaction, ts(138) < .12, us. The latter finding is interesting in light of the fact that unrealistic optimism is thought to be related to content ment over and above its association with behavior (Tay lor & Brown, 1088). People giving lower comparative risk perceptions (irrespective of accuracy) did not differ by sex or age, —.14 < is(143) < 0, s > .10, and were more educated, i(143) =—.32, p< .0001. They also had lower systolic and diastolic blood pressure and heart attack risk, ts(l 3(1) > .20. ps .01, and higher life satisfdction and levels of

841

Perceived own absolute rtsk Perceived average absolute risk Worrs about risk’ Actual prior knowledge Estimated priot knowledge” Ccnetal effect of risk lkcto,s Personal effect of risk factors Reading topic choice’ Essay retention”

.515*5 .225*

.03

—.06 .05 .22** 35*5*

—.20 .01 —.03

.10 .21

—.l6t

DLsposiliortai ()t?tlnsoin.

—.13 —.I0 .19°” .11 —.07 —.lS —10 .01

NOTE: All correlations control for sex, age, anti highest ecl,,catio,ial level attained. a. Also controls for actual Health Risk Appraisal (tiPk) sisk. b. Also controls for acmal prior knowledge. c. Also controlled for actual HRA risk and beliefs about the umncliosen risk factors. Negative correlations for catting topic choice reflect a preference for reading about, a risk factor that participants believed ic— cluceci their personal risk. d. Also controls for actual prior knowledge and baseline reading coot prehension. t/< .10. 5 p< .05. **< .01. ***/,,< .001.

physical activity, s (141) .10. These findings begin to illustrate the difference between people who believe their risk is below average and people whose risk estimates are unrealistically optimistic.

Data Analysis Strategy The analyses in the sections that follow were based on multiple regression, including dispositional optimism and unrealistic optimism and their cross-product as isidependent variables as well as any relevant coistrol variables. Dispositional optimism scores were centered prior to enny’. We always controlled for highest level of education attained because it was correlated with dispositional optinusm. Age and sex did not systemau— cally iiiodcrate or explain rise reported effects and thus are not discussed further. We also repeated the above analyses substituting unrealistic optimism with conupara— five risk ratings. Regression toef icients are reported in the text, and correlations atnong the different measures ofoptamism and the principal dependent variables (controlling for age, sex, highest level of education attained, and other variables as appropriate) appear in Table 1. Means and standard deviations for the dichotomized unrealistic optimism variable appear in Table 2.

Risk Perception and Concern Participants indicated their absolute risk of having a fatal heart attack on a 9-pointscale ranging from extientely

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PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN

TABLE 2:

Dependent Variables by Unrealistic Optimism UIiiO’il,.stC(iily O/riiniisiic? Yes M

5 Perceived owis absolute risk Perceived average absolute risk Worry abou1 risk 5 Actual prior knowledge’° Estimated prior knowledge Gencral effect of risk factors 5 Personal effect of risk factors Lisa c1cnhion**

3.71 5.04 1.99 6.64 3.46 24,55 18.05 19.05

No

SD 2.14 1.78 0.92 2.15 0.93 3.75 5.06 4.26

M

SD

4.13 4.92 2.22 7.48 3.58 24.56 19.65 22.25

2.04 1.57 1.02 1.95 0.87 3.36 5.30 3.96

NOTE: Significance levels refer to main effect of unrealistic optimism in nininpie regression analyses. 5/, < .05. “p < .01. 5*5/, < .001.

unlikely to extremely likely, and this verbal measure of abso lute risk was included in a regression that controlled for actual I-IRA risk. Although actual risk was used to deter mine whether participants were unrealistically opnmis tic, we considered it appropriate to control for this vari able given that any sharedvariatice between the variables would only reduce the chances of obtaining a significant effect of unrealistic optimism. Unrealistically optimistic individuals believed they were at lower absolute risk, as did clispositionally optimistic indivsduals, [3s .10). Thus, the belief that one’s risk is below average does not seem to he associated with less prior knowledge (unless the belief is unrealistic, as shown above). Such individuals also did not believe that they know arty more about heart attacks ([3= .05, us). Beliefs About Risk Factors No effects emerged on participants’ summed ratings of how related each of the six risk factors (alcohol con sumption, fat consumption, nutrition, smoking, exer cise, and stress; a = .78) was to licart attack risk ([3s < .17, as). I Iowcvcr, participants’ summed ratings ol’how their own risk factor standing affected their risk of having a heart attack (a = .70) showed that unrealistic optmulisum and high dispositional optimism were associated with a greater belief tl’mat one’s standing on risk factors risk ([3s 1.99, ps < .05); there was no interac tion (f3 = —.24, os). Also, participants estimating low corn parati’e risk believed their risk factor standing was more likely to reduce their risk (13 = .32, t= 3.03, p< .01). There was no effect of dispositional optionsni or an interaction (—.09