Judgment and Decision Making, Vol. 1, No. 1, July 2006, pp. 48–63 Gender Differences in Risk Assessment: Why do Women Take Christine R. Harris, Michael Jenkins Across many real-world domains, men engage in more risky behaviors than do women. To examine some of the beliefs and preferences that underlie this difference, 657 participants assessed their likelihood of engaging in variousrisky activities relating to four different domains (gambling, health, recreation, and social), and reported their perceptionsof (1) probability of negative outcomes, (2) severity of potential negative outcomes, and (3) enjoyment expected fromthe risky activities. Women’s greater perceived likelihood of negative outcomes and lesser expectation of enjoymentpartially mediated their lower propensity toward risky choices in gambling, recreation, and health domains. Perceptionsof severity of potential outcomes was a partial mediator in the gambling and health domains. The genders did not differin their propensity towards taking social risks. A fifth domain of activities associated with high potential payoffs andfixed minor costs was also assessed. In contrast to other domains, women reported being more likely to engage inbehaviors in this domain. This gender difference was partially mediated by women’s more optimistic judgments of theprobability of good outcomes and of outcomes being more intensely positive.
Keywords: sex differences, gender differences, risk perception drowning or accidental poisoning throughout the West-ern world (Waldron, et al., 2005). Thus, there seems little Accidents are a very frequent cause of death, particularly doubt that men must be engaging in more risky behaviors among young adults and teenagers (U.S. Center for Dis- ease Control [CDC], 2004), and men are more often the Despite its obvious practical importance, some key as- victims of accidents than are women (CDC, 2004; Wal- pects of the psychological underpinnings of gender dif- dron, McCloskey, & Earle, 2005). For example, for ev- ferences in risk taking have not been examined. The ery 100,000 US drivers, men are three times as likely as present article seeks to shed new light on these under- women to be involved in fatal car accidents (U.S. De- pinnings, by asking a substantial sample of college men partment of Transportation, 2004). While some of this and women to report various perceptions and preferences well-known difference in automobile death rates prob- related to a wide range of risk-taking scenarios.
ably reflects differences in the average amount of timemen and women spend driving, it seems likely that an- 1.1 Gender differences in risk taking and other important cause is that males voluntarily engage in risky behaviors more often than do females. For exam-ple, US women report usually using seat belts substan- The existence of gender differences in propensity to take tially more often than men (Waldron, et al., 2005), and risks has been documented in a large number of ques- men have been shown to run yellow lights more often tionnaire and experimental studies. For example, a meta- than women (Konecni, Ebbesen, & Konecni, 1976). Fur- analysis by Byrnes, Miller, and Schafer (1999) reviewed thermore, similar differences are seen in a wide variety of over 150 papers on gender differences in risk perception.
other forms of accident statistics. Male pedestrians in the They concluded that the literature “clearly” indicated that UK are involved in accidents about 80% more often than “male participants are more likely to take risks than fe- female pedestrians, and men die much more often from Recent work has begun to examine the generality and Correspondence concerning this article should be addressed to cognitive underpinnings of these differences in greater Christine R. Harris, Department of Psychology, University of Califor-nia San Diego, 9500 Gilman Drive #0109, La Jolla, CA 92093–0109.
detail (Slovic, 1997). In one important study that pro- vides a backdrop for the present investigation, Weber, Judgment and Decision Making, Vol. 1, No. 1, July 2006 Blais, and Betz (2002) assessed the risks that men and Note that in the field of finance, where distribution of women perceived in behaviors spanning five different potential outcomes is obviously continuous, risk is often content domains (financial, health/safety, recreational, conceptualized as the variability of the returns offered ethical, and social decisions). Gender differences were by a choice. Following that approach, some theorists found in four of the five domains — social decision- have found it useful to conceive of people’s generalized making being the exception — with males perceiving risk preferences in terms of how this variability affects less risk and indicating a greater likelihood of engag- an individual’s disposition to choose an option (see We- ing in risky behaviors. Similar gender differences have ber, 1999, for a discussion). While this seems quite rea- been found in these domains in a large German sample sonable, in many real world risky choice scenarios (e.g., (Johnson, Wilke, & Weber, 2004). Across studies, the so- riding motorcycle without helmet; not using sunscreen; cial domain is unique in that either no gender differences etc.), it would seem to be a reasonable simplification to are found or when they are found, it is women who re- view the potential negative outcomes as a unitary event, port greater propensity to engage in risky behaviors and having a probability and some degree of (un-)desirability.
perceive overall greater benefit and less risk in doing so This approach will be followed here, although in the Gen- (Johnson et al., 2004; Weber et al., 2002). Of interest, eral Discussion we will point out the potential for follow- these authors also found great variability in an individ- up work that would consider risks involving more than a ual’s willingness to engage in risk across domains, sug- gesting that risk taking is not simply the product of some Remarkably, the literature with adults does not seem general personality trait that promotes risk seeking. In- to contain any studies that seek to decompose the per- stead, individual and group differences are substantially ceptions of risk involved in real-world risky behaviors, due to differing perceptions of risk in different domains.
in order to determine whether the genders differ in their For the most part, previous research has relied on a evaluations of the likelihoods and costs of negative out- unitary and subject-defined notion of “risk” (e.g., “how comes. A number of plausible hypotheses immediately risky is the behavior or situation?”). A number of re- present themselves. One such hypothesis is that women searchers have examined the role of various affect di- do not evaluate the probability of negative outcomes dif- mensions in determining overall perceptions of riskiness.
ferently than men; they simply assume (perhaps rightly; Slovic (1997) proposes that several psychological risk di- perhaps not) that they would be more emotionally upset mensions (including dread, control, and knowledge) con- or harmed by negative outcomes, should these occur. Al- tribute to perceived riskiness. Follow-up research has ternatively, one may hypothesize that women assess as shown the material as well as emotional factors also im- greater the probability of unfavorable outcomes, without pact overall risk judgments (Holtgrave & Weber, 1993).
projecting any stronger negative reactions to these out- Any global assessment of perceived risk combines el- ements of a belief (“how likely is it that something bad While studies of gender effects in adult risk prefer- will happen?”) and a subjective valuation of that outcome ences — with the exception of Gurmankin Levy and (“how bad would that be?”). Thus, in common parlance Baron (2005) — have not addressed this issue, there is a given behavior might be said to be riskier than another one study within the developmental literature that ex- behavior if the former has more severe potential conse- plored this question. Hillier and Morrongiello (1998) quences, or if it has a higher risk of potential negative examined gender differences in perceptions involved in consequences, or both. For example, leaving one’s bike physical risk taking in children. Using pictorial descrip- unattended for a day in a busy city, and bungie jumping tions (e.g., riding bicycle with no helmet in street) and an could both be described as risky behaviors, and yet the interview to determine how children assessed risks, they probabilities and potential bad outcomes are enormously found that girls appraised more general risk (i.e., judged different in the two cases. Past research shows that de- the situations as more unsafe) than boys. The genders composing these elements can shed important light on also differed in the factors that contributed to their over- individual and group differences in responses to risky sit- all risk judgments. Boys’ risk judgments were signifi- uations. Gurmankin Levy and Baron (2005) had subjects cantly predicted by their ratings of injury severity while assess badness of unfortunate medical outcomes associ- girls’ risk judgments were better predicted by their rat- ated with a defined probability (e.g., 32% chance of loss ings of vulnerability to any type of injury. This suggests of a big toe). Different groups (men vs. women; physi- that girls may avoid risky situations with any likelihood cians vs. non-physicians) were differentially sensitive to of perceived injury and boys may avoid risky situations probability as against severity. The present article pur- only if the possible perceived injuries are judged as being sues a similar approach to explore the determinants of men’s and women’s willingness to engage in different As noted above, the literature with adults has not exam- ined whether the genders differ in their evaluations of (1) Judgment and Decision Making, Vol. 1, No. 1, July 2006 the likelihood of potential negative outcomes and (2) their low-frequency outcomes (whether good or bad) as more appraisals of the severity of these potential outcomes. In likely to occur, in which cases they should show greater adults, either or both of these aspects of risk may mediate attraction to choices in the positive domain.
gender differences in engaging in “risky” behaviors. Athird factor may also be responsible for the gender differ-ences in propensity to engage in risky behaviors: the gen- ders may differ in their estimates of the enjoyment offeredby the activity, assuming that negative outcomes do nottake place. This last possibility finds some support from Weber et al. (2002) and Johnson et al. (2004), who found A sample of 657 subjects (389 female and 268 male) from that relative to women, men judged they would obtain undergraduate psychology classes at the University of greater benefits from engaging in risky behaviors in all California, San Diego participated in the study for course domains except social.1 Using a risk-return framework, credit. Their average age was 18.5 years. Three addi- Weber and colleagues have suggested that risky decision tional subjects participated but were excluded because making can be seen as a trade-off between fear (risk) and The present study had two major goals. The first was to Sixteen of the risk behavior scenarios consisted of a sub- separately assess gender differences in the three kinds of set of those used by Weber et al. (2002). These fell into assessments just mentioned. To put it in simple terms, 4 domains: gambling (e.g., betting at a race track), health the present study asks: do women tend, for example, to (e.g., deciding whether or not to use sunscreen), recre- engage in dangerous recreational activities less often be- ational (e.g., engaging in an extreme sport such as moun- cause (a) they think the likelihood of injury is greater, tain climbing), and social decisions (e.g., discussing op- (b) they think the severity of an injury, were it to occur, posing viewpoints with a friend). For each domain, we would be greater, and/or (c) because they simply do not chose the four items that had the highest risk perception find the positive aspects of such activities as attractive as factor loadings in Weber et al. (2002). Given the mixed men do? In addition, we examined whether such assess- results regarding gender differences in the social domain ments vary depending upon the domain of behavior and reported by Weber et al. (2002) and Johnson et al. (2004), compared patterns of risk perception with individuals’ re- two additional social domain scenarios were created for ports of engaging in risky behaviors in the past.
the current work to further examine potential gender dif- A second aim was to explore an important category of ferences in this domain. These items were designed to choices (popularly referred to as “taking a chance”) that include behaviors that while having potential social risk have not, to our knowledge, been examined in previous also had potential social benefit. For each scenario (listed studies of individual differences in risk: decisions to en- in Appendix A), subjects rated (1) their likelihood of en- gage or not engage in behaviors that offer a small proba- gaging in the activity, (2) the probability of a risky be- bility of a large positive reward in return for some small havior incurring negative consequences, (3) the severity but certain cost. An example is trying to be the 12th caller of these potential consequences, should they occur, and to a radio station in order to win a large sum of money.
(4) how positive or enjoyable the given activity would be, This type of scenario will be referred to as the “positive if there were no bad outcomes. Following Weber et al.
domain”. One possible explanation for why women en- (2002), subjects responded to the likelihood of engag- gage in fewer risky activities is that they are relatively ing question with a 5-pt. scale (1 = very unlikely; 5 = pessimistic and feel themselves relatively “unlucky” (i.e., very likely). The three additional questions were also an- prone to experience the least desirable possible outcome swered on a 5-pt. scale (1 = not at all; 5 = extremely).
more often than would be expected based on overall fre- An additional set of questions assessed possible gen- quencies). If this is so, then women should also show less der differences in relation to choices associated with high interest than men in options offering a low probability of potential payoffs and relatively minor but certain costs, positive reward. Another possibility is that women see referred to as the “positive domain”. An example would 1It should be noted that Weber et al. (2002) did not ask subjects to be calling a radio station to win money. For each scenario assess the benefits of risky behaviors conditionalized on the absence of (see Appendix B), subjects rated (1) their likelihood of any negative outcomes; hence, it is possible that in giving their judg- engaging in the activity, (2) the likelihood of the behavior ments about positive benefits, respondents were “folding in” the risks,thus potentially explaining why females might have given lower scores incurring positive outcomes, (3) the intensity of these po- tential positive consequences, should they occur, and (4) Judgment and Decision Making, Vol. 1, No. 1, July 2006 the degree of unpleasantness of the activity, if there were Relative to women, men reported a greater overall like- lihood of engaging in risky behaviors in the gambling, Finally, additional questions dealing with risky past health, and recreational domains. In all three domains, behaviors were created for the present study, including women judged potential negative consequences as more some that were adapted from Gibbons and Gerrard (1995) likely to occur and they judged the potential negative con- (see Appendix C). Subjects were asked how frequently sequences as significantly more severe in two of these they had actually engaged in behaviors that correspond to domains (gambling and health). The genders also signifi- the four negative domains of gambling, recreation, health, cantly differed in their ratings of the enjoyment of engag- ing in risky behaviors (assuming no negative outcome) inall three domains, with men rating the scenarios as moreenjoyable.
The social domain showed a very different pattern of Subjects were recruited from the UCSD psychology sub- responses than the three domains just described. There ject pool and completed questionnaires through a spe- was no overall gender difference in reports of likelihood cially created web program that was generated using PHP.
of engaging in behaviors carrying social risks. An ex- The scenarios listed in Appendix A were presented in a amination of individual items suggested that the gender random order and subjects assessed their likelihood of en- differences were not consistent in direction. For exam- gaging in each described behavior. These scenarios were ple, women reported significantly greater propensity for then presented a second time in a random order and sub- taking risks on two scenarios (admitting tastes are dif- jects answered the three additional risk questions (prob- ferent than friends’; disagreeing with parent on a major ability of negative outcomes, severity of negative out- issue) while men reported significantly greater propen- comes, and enjoyment). Two practice scenarios appeared sity on two different scenarios (defending unpopular is- before the actual stimuli to familiarize the subjects with sue; asking someone on a date) as well as a significant the types of scenarios and the response scales. The pos- trend (p = .06) on a third scenario (arguing with a friend).
itive domain scenarios were presented next and followed There were also no gender differences in overall ratings the same procedures as the negative domain (e.g., like- of likelihood of negative consequences or enjoyment of lihood of engaging in the activity was first assessed and the behaviors. However, women did rate the severity of then the scenarios were presented a second time with the possible negative consequences as greater than men for three additional questions about outcomes). Lastly, sub- jects answered questions regarding past risky behavior.
The positive domain — behavioral choices offering a chance of substantial gain and imposing a relatively smallbut certain cost — is one that has not to our knowledge been examined in any previous studies of gender dif-ferences and risk. In contrast to the findings from the domains described above, women reported being morelikely to engage in these behaviors. They also gave sig- For each type of question (willingness to engage in be- nificantly higher probability estimates for positive conse- havior, perceived benefits, etc.), an individual’s responses quences occurring and showed a trend towards reporting to the scenarios composing each domain were averaged that the potential favorable consequences would be more together to form a composite score for that domain. As positive. The genders did not significantly differ in their noted above, the categorization followed Weber et al.
assessments of degree of unpleasantness associated with (2002). All the analyses described below were performed the costs incurred by these behaviors.
on these mean responses. For each negative risk domain(gambling, health, recreation, and social), four separate t-tests were performed to determine the existence of genderdifferences in perceptions of (1) likelihood of engaging; 3.2 Gender differences in reports of past (2) probability of negative consequences due to engag- ing; (3) severity of potential negative consequences; and(4) enjoyment. The overall mean responses for each type The frequency of reporting engaging in specific risky be- of question in each domain by gender are shown in Table haviors as a function of gender is shown in Table 2. Every 1. T-tests were also performed on the positive domain foreach question type and are shown in Table 1.
3Results from analyses using just the four original items from We- ber et al. revealed the same pattern of results with the exception that 2 Subjects also completed additional questions on other topics not the gender difference in predictions of severity of outcome no longer Judgment and Decision Making, Vol. 1, No. 1, July 2006 Table 1: Means (SD) of gender differences in risk perceptions by domain and question type.
GamblingLikelihood of engaging in risky behavior Severity of potential negative consequences HealthLikelihood of engaging in risky behavior Severity of potential negative consequences RecreationLikelihood of engaging in risky behavior Severity of potential negative consequences SocialLikelihood of engaging in risky behavior Severity of potential negative consequences PositiveLikelihood of engaging in behavior Intensity of potential positive consequences †p < .10, *p < .05, **p < .01, ***p < .001 Judgment and Decision Making, Vol. 1, No. 1, July 2006 Table 2: Gender differences in reports of actual past risky behaviors.
you typically drink in a week?How often have you had too much to drink or gotten drunk?How often do you drive over the speed limit?How often do you “bend” or break recreational activities?How often do you get into argu- ments with friends or family?How often do you raise your hand to *p < .05, **p < .01.
Note. Some n’s may be slightly reduced for some individual analyses due to missing data points.
category of behavior showed a significant gender differ- ence with the exception of one question associated with How are perceptions of the likelihood of and the severityof negative outcomes related? This can be addressed by examining a correlation computed across subjects, ask- ing “do people who rate a behavior as risking a severeoutcome rate this outcome as more — or less — likely How are subjects’ assessments of likelihood of engaging to occur?” As shown in Table 4, those rating the bad in risky behaviors in a given domain related to the fre- outcomes as severe also rated them as more probable.
quency with which they have actually engaged in risky Across different domain scales, all 18 correlations were behaviors in that domain? Judgments of the likelihood positive (all but one being statistically significant), with of engaging in risky behaviors in the recreational domain an average correlation of .40. These positive correlations were significantly related to the responses on an actual were present both in the sample as a whole, and within risk behavior question in the same domain, r(656) = .588, the male and female subsets of the population considered p < .001, as were responses regarding likelihood of en- separately. We also examined the relationship between gage in risky gambling behavior and reports of past gam- evaluations of the enjoyment associated with an activity bling risk behavior, r(654) = 0.582, p < .001. Signifi- and the probability and the severity of potential nega- cant associations between predicted and actual behavior tive outcomes. There was a weak negative relationship also were found in the health domain, as shown in Table between enjoyment and probability (across items, corre- 3. Reports of likelihood of engaging in risky behavior in lations ranged between -.23 and .02, averaging -.10; of the social domain were significantly associated with past these, 10 were significant, all in a negative direction).
socially risky behaviors: r(656) = .41, p < .001 for the There was no discernible consistent relationship between question regarding raising ones hand in class and r(656) pleasure and severity (across items, correlations ranged = .25, p < .001 for the question regarding getting into from -.21 and .12, averaging 0; of these, 6 were sig- nificant, 4 in a positive direction, 2 in a negative direc- Judgment and Decision Making, Vol. 1, No. 1, July 2006 Table 3: Health domain: correlation between reports of actual past risk behavior and likelihood of engaging in riskybehavior How many alcoholic beverages do you typically drink in a week? How often have you had too much to drink or gotten drunk? How often do you drive over the speed limit? How often do you bend or break traffic laws? * p < 0.01, ** p < 0.001.
tion). In summary, people who evaluate potential harms the independent variable and the mediator variable are in- as likely also have a marked tendency to also evaluate cluded as predictors of the outcome variable. Evidence of them as being severe; however, assessing the activities as mediation exists, if the effect of the independent variable enjoyable says little or nothing about whether a person is reduced in this third equation, a reduction that can be will view the potential negative outcomes as likely or se- tested by Sobel’s test. We applied this strategy to each of the domains described here for each of the potential me- Similar questions can be posed in the positive domain.
diators separately. For simplicity sake, we only present First, do those viewing the positive rewards as greater the Sobel test statistic for these analyses as well as corre- also think them more probable? Here, the answer varied lations and partial correlations between likelihood in en- (see Table 5), with the correlations between judgments gaging in risky behavior, gender, and mediators for each of probability of good outcomes and intensity ranging from -.07 to .47, averaging .20. Ratings of the antic-ipated unpleasantness (costs) were not correlated with For both the gambling and health domains, separate probability of positive outcomes (average correlation = analyses of each mediator revealed that perceptions of .02, none significant). Anticipated unpleasantness was probability of negative consequences, severity of poten- significantly negatively correlated with intensity of posi- tial negative consequences, and enjoyment each partially tive consequences for only one of the four scenarios, and mediated the gender effect in risky gambling behavior. In the average correlation for the four scenarios was -.05.
the recreational domain, the gender difference in risk tak-ing was partially mediated by perceptions of likelihood of negative consequences and partially mediated by per-ceptions of enjoyment from engaging in such behaviors.
The analyses reported above show that in regard to gam- Perceptions of severity of negative consequences were bling, health, and recreational domains — but not so- not analyzed since they were not significantly correlated cial domains — women tend to judge negative outcomes with gender. The genders did not significantly differ in associated with risky behaviors as both more likely and their average willingness to engage in social risk, there- more severe; they also indicate a lower likelihood of en- fore mediational analyses were not performed in this do- gaging in these risky behaviors and judge the activities as less enjoyable than do men (assuming that the negativeoutcomes do not occur). Do these perceptions mediatethe gender differences in reported likelihood of engaging Next we examined mediation in the positive domain, where potential payoffs were high but uncertain, and To test for mediational effects, we began with the costs were low. Unlike the most of the negative do- commonly used approach laid out by Baron and Kenny mains, women reported being more likely to engage in (1986). Each mediational analysis requires three regres- these types of behaviors. This difference was partially sion equations. The first tests for a significant relation- mediated by perceptions of probability of positive con- ship between the independent variable and the mediator.
sequences. Intensity of positive consequences was also The second looks at the relationship between the media- a partial mediator, although only marginally so. Per- tor and the outcome variable. If both of these correlations ceptions of unpleasantness were not analyzed since they are significant, a third equation is computed in which both were not significantly correlated with gender.
Judgment and Decision Making, Vol. 1, No. 1, July 2006 Table 4: Correlations of judgments of probability of negative consequences, severity of negative consequences, andenjoyment of activity for each item within each risky domain.
† p < .10, *p < .05, **p < .01, ***p < .001 Table 5: Correlations of judgments of probability of good outcomes, intensity of good outcomes, and unpleasantnessof activity for each item within the positive domain.
Probability of Good Outcomes Intensity of Good Outcomes † p < .10, ***p < .001.
Judgment and Decision Making, Vol. 1, No. 1, July 2006 Table 6: Analyses of mediators of risk taking for each domain, with zero-order and partial correlations.
† p < .10, *p < .05, **p < .01, ***p < .001., −− criteria for mediational analyses not met, for gender M = 1 F = 2.
Judgment and Decision Making, Vol. 1, No. 1, July 2006 of engaging in risky behaviors. Judged severity of po-tential negative consequences was an additional partial As a further check on the conclusions just described re- mediator of the gender differences in engaging in risky garding mediation, we utilized a path analysis (SEM us- behaviors in the health and gambling domains.
ing LISREL 8.54) to test a model in which perceptions The social domain showed more mixed results, as was of probability of negative outcomes, severity of nega- the case in the data of Weber et al. (2002). In one study, tive outcomes, and perceived enjoyment are assessed as they found that women reported greater propensity to- potential mediators of gender differences in risk taking wards taking social risks but in a second study this dif- for each of the four different content domains. This ference was not significant. In a German sample, John- framework assumes that the variables combine additively son et al. (2004) also did not find a sex difference in so- with each other to determine the target variables. How- cial risk taking, although women did perceive such ac- ever, there is no decision-theoretic model that we are tivities as providing greater benefits. It is interesting that aware of that would predict that probability would com- the genders do not show consistent differences with re- bine additively with severity to determine an individual’s spect to social risks, as they do in the other domains.
propensity to engage in a behavior.4 Thus, a path an- Looking over the individual items, it appeared that men alytic approach is perhaps best viewed as exploratory tended more often to describe themselves as likely to en- (Raykov & Marcoulides, 2000). Nonetheless, the results gage in behaviors that could be perceived as ‘defending’ mirrored the individual Sobel mediation tests described ideas (e.g., “Defending an unpopular issue that you be- lieve in at a social occasion”) whereas women appearedto respond more positively than men to behaviors that in- volved social risks, but which were not phrased in thisway (e.g., “Admitting that your tastes are different from The final analyses focused on full regression models those of your friends”). Indeed, men scored significantly where likelihood in engaging in risky behaviors was re- higher on the former while women scored significantly gressed on gender, probability, severity and enjoyment higher on the latter question in the social domain. This for each domain. These results are presented in Table 7.
suggestion is obviously tentative, however; a more fine- When included together, all four variables significantly grained analysis of the particular risks and benefits at is- predicted risk taking in the gambling and recreational do- sue in “risky” social decisions is plainly needed in order mains. In the health domain, all variables except severity to better characterize gender differences. What is clear were significant predictors of risk taking. Social risk tak- is that the social domain, as assessed here, did not show ing was only significantly predicted by severity and en- homogenous gender effects, which is quite different from joyment. Finally, all variables except unpleasantness sig- the other domains of risky behavior.
nificantly predicted behavioral inclinations in the positive One category of risky choice examined in the present data set that apparently has not been previously investi-gated is what was termed the “positive domain”: behav-ioral choices affording a small chance of a large bene- fit for a fixed small cost. Interestingly, women reportedgreater willingness to engage in the behaviors surveyed.
These results suggest that when there is no risk of severenegative consequences, but rather a possibility of pre- In the health, recreational, and gambling domains, dominantly positive consequences in exchange for some women reported a lower likelihood of engaging in risky small fixed cost, women more than men will engage in behaviors. In all three domains, there were significant such behaviors. Mediational analyses suggest that the gender differences in perceptions of probabilities of neg- difference arises because women judge that these conse- ative consequences from engaging in risky behaviors, quences are more likely to occur, and to a lesser extent, with women reporting greater probabilities. In addition, because they judge the consequences as more worthwhile women expected to obtain less enjoyment from these be- than do men. The results clearly speak against the sug- haviors than did men in each of these three domains, gestion that women engage in risky behaviors less often assuming that the potential negative outcomes did not because they are pessimistic and “feel unlucky” in some occur. The mediational analyses revealed that percep- tions of negative consequences and enjoyment signifi- One category of real-world behavior that mirrors our cantly partially mediated gender differences in likelihood definition of the positive domain quite closely is the pur- 4However, it is not unprecedented to find additive models fitting data chasing of lottery tickets. One recent survey disclosed of this sort reasonably well (Mellers & Chang, 1994).
that while somewhat more men (56%) than women (43%) Judgment and Decision Making, Vol. 1, No. 1, July 2006 Table 7: Full model regression analyses of risk taking in each domain Judgment and Decision Making, Vol. 1, No. 1, July 2006 report ever having purchased a lottery ticket, the total same side of any dispute (for discussion, see Baron, 2000, spending by women as a whole ($9.89/month) was con- p. 212). On the other hand, we did not find any notable siderably greater than that of men ($8.40/month) (Gallup relationship between ratings of enjoyment and ratings of Organization, 2004). At first blush, our interpretation of either severity or probability of potential negative out- this fact and our findings in the positive domain may ap- pear at odds with our other findings that men endorsedgreater willingness to engage in gambling than women.
Interestingly, some of the strongest support for the af- However, the gambling scenarios presented to our sub- fect as feeling viewpoint has come from findings of a jects involved fairly high potential costs (i.e., the possi- negative correlation between people’s assessments of the bility of losing a full day’s or week’s worth of income).
benefits associated with an activity or investment and the Therefore, women may be more willing to pay a small risks of that activity (Alhakami & Slovic, 1994; Fin- cost for the chance of a very positive outcome but may ucane, Alhakami, Slovic & Johnson, 2000; Ganzach, be reluctant to do so when the potential cost is high. We 2001). For investments, at least, this reflects an erro- are currently conducting research to further explore the neous belief, since one of the most elementary facts un- genders’ reactions to financial gambles involving various covered in the field of finance is a positive relationship levels of potential loss and gain, which may shed further between the riskiness of an investment and its expected return — not a negative one. It should be noted, however, As described above, our results indicate that for risky that the correlations examined in the present study were choices, those subjects assigning higher probabilities to computed over individuals, whereas the papers just cited negative outcomes also assess the outcomes as more se- reported correlations across situations. It is conceivable vere. This positive correlation appears separately within that if one sampled broadly from the universe of poten- each gender as well as when participants are pooled.
tial activities that people commonly engage in, our sub- These results seem broadly congenial to the view de- jects too might have rated as more enjoyable whichever scribed as “risk as feelings” (Loewenstein, Weber, Hsee, activities they viewed as having potential bad outcomes & Welch, 2001; Slovic, Finucane, Peters & MacGre- low in severity and probability. If so, this too might be gor, 2002). According to this thesis, people tend to erroneous, since it stands to reason that just as invest- have a rather global affective representation of behavioral ments must offer a high expected return as compensation choices as more or less risky. As Slovic et al. (2002) put for risk, risky activities must, to attract participants, of- it, “if they like an activity, they are moved toward judging fer some form of pleasure and/or aesthetic experience as the risks as low and the benefits as high; if they dislike it, compensation (thus, few people seem inclined to engage they tend to judge the opposite — high risk and low ben- in night-time bungee jumping or playing catch with live efit. Under this model, affect comes prior to, and directs, judgments of risk and benefit. . . ” (p. 5), a conceptionthat also fits with evidence that sociopolitical factors play The present results also have an interesting but per- a role in gender differences in perceptions of risks associ- haps misleading resemblance to findings in the older de- ated with technologies (see Slovic, 1997, for an interest- cision making literature by Irwin (1953) and Pruitt and Hoge (1965). These investigators — and others aroundthe same time — exposed participants to events in the At a global level, at least, this seems to fit nicely with laboratory (such as lights turning on) associated by with the finding reported above that people who view an ac- various outcome values (rewards or losses for the partic- tivity as having a severe potential negative outcome also ipants) and various probabilities of occurrence. A com- tend to view the potential negative outcome as more prob- mon finding was that events associated with greater gains able. In that regard, a global judgment of negativism — (or smaller losses) were often rated as more probable.
varying across subjects and greater, on average, in women This finding differs in a number of ways from the phe- — might seem to be at work. The effect is similar to what nomenon described in the present paper. The most ob- Jervis (1976) has termed “belief overkill”, which is the vious difference is in the direction of the effect. Another tendency to believe that all good arguments rest on the difference is that, in the older literature, participants cameby their impressions of the probability and value of the 5 We should note that our mediational analyses were based on the events in question exclusively through direct experience assumption that the causal arrows run from beliefs about the risks asso- within the experiment; by contrast, in the present study, ciated with a behavior to the decision about willingness to engage in the few subjects would have any direct experience to fall back behavior. However, as with all correlational data, causal arrows operat- upon in estimating the likelihood of a bad outcome from ing in the reverse direction are not eliminated by our findings. Indeed,one way to construe the notion of “belief overkill” — discussed below activities such as motorcycle riding or piloting their own — would involve just such a reversed causal direction.
Judgment and Decision Making, Vol. 1, No. 1, July 2006 Suppose you were interviewing a potential babysitter for your child and learned through an interview that an ap-plicant loved dangerous sports, rarely took precautions Although the present data cannot address the question of like wearing a seatbelt, and liked to gamble large sums of why gender differences exist in risky behaviors across money, judging the risks associated with all these behav- many domains, it is perhaps of some interest to attempt iors to be slight. Would you still want to hire this person to relate our findings to some lines of speculation on this as a babysitter? An informal sample suggests that the topic. One possible interpretation, suggested by Buss near-universal reaction is an emphatic no, suggesting that (2003), extends Trivers’ (1972) Darwinian analysis of many of us tacitly assume that such attitudes would in- parental investment. For physiological reasons, the mini- deed affect the sort of risks a person would impose upon mal investment required to produce an offspring is gener- children entrusted to their care. It seems conceivable ally much greater for a female than for a male (in humans, that natural selection validated this common hunch over 9 months of gestation time vs. a few minutes). Thus, a many generations in human prehistory, and responded by male potentially can greatly increase his Darwinian fit- wiring in a very general tendency for females to perceive ness by having sex with multiple partners, whereas a fe- greater risks than do males. Of course, these kinds of male cannot. One potential consequence of this is much evolutionary/functional accounts are notoriously difficult greater variability in male reproductive success than fe- to test, and the point of the present discussion is merely to male. This difference may make it adaptive for males suggest that any possible innate biological differences in to be willing to take great risks for a chance of raising risk perception are as likely to reflect selection pressures their attractiveness to mates (Buss, 2003). For example, related to child-rearing as those related to mate-seeking.
suppose that running a 5% risk of death can move an or- A very different sort of explanation for gender dif- ganism’s fertility from the 50th percentile for their sex to ferences is suggested by work of Slovic and colleagues the 90th. For a male, this might pay a Darwinian divi- (Slovic, Fischhoff, & Lichtenstein, 2000). They found dend, whereas for females the cost would be more likely that greater familiarity with a risk was generally asso- ciated with reduced risk-perceptions. One possibility is It should be noted that this account could potentially that women have greater familiarity with social risks, thus explain risk-taking even in domains that are ostensibly they engage in them as often or more often then men.
unrelated to mate-seeking per se, if taking risks allowsa man to acquire greater resources, and thereby attract more mates. Thus, one might suppose that men are in-nately inclined to take risks in many domains due to the One interesting question raised by the present results re- large reproductive benefits available in the ancestral en- lates to the nature of the risk scale used. It would be inter- vironment for those males most successful at obtaining esting to assess whether the tendency of women to eval- access to many mates. While many of the results here uate as more likely the potential negative consequences might be consistent with this theory, our findings in the associated with risky choices examined here would hold social domain do not obviously fit. Men seemed no more up if perceptions of the likelihood of discrete and well- likely to take social risks than women, according to our defined negative outcomes (e.g., dying in a motorcycle results as well as those of Weber et al., (2002) and John- crash per 10,000 miles driven without a helmet) were as- sessed using a probability or frequency scale — rather There is another possible evolutionary explanation for than, as in the present study, assessing the likelihood of gender differences in risk that might also be worth con- negative outcomes using a Likert-type scale. It might be sidering, which we will term the “offspring risk hypothe- the case that estimating likelihood in a Likert scale, and sis”. Perhaps women have a tendency to see greater risks referring to the negative outcomes globally, promotes a than men see, not because of different selection pres- relatively associative or impressionistic mode of analy- sure relating to mate seeking, but rather because if one sis, causing the judgments of severity and likelihood to perceives more risks in the world, one will be more ef- fective at keeping safe any offspring under one’s care.
There are also several interesting approaches for po- Human infants are exceptionally helpless for an unusu- tential follow-ups which could be devised on the basis of ally long developmental period, as compared to most an- an analysis of risk attitude in terms of the negative value imals. The reader may be skeptical that the diverse kinds that people place upon outcome variability (Weber, 1999; of risk attitudes assessed in the present study — which Weber & Millman, 1997). One such approach would ask are admittedly far removed from childrearing context — subjects to specify what range of outcomes they would would have any bearing on the risks imposed on chil- anticipate as a consequence of given risky choices, and dren. But consider the following thought experiment: what probabilities they would place on these. Another ap- Judgment and Decision Making, Vol. 1, No. 1, July 2006 proach would be to compare men and women’s responses of injury risk. Journal of Pediatric Psychology, 23, to “artificial” options in which the probabilities and out- comes are both fully specified (presumably in monetary Holtgrave, D. R. & Weber, E. U. (1993). Dimensions terms). Such an investigation might help to further pin of risk perception for financial and health risks. Risk down the reason why women’s perceptions and prefer- ences seem to be shifted relative to men’s in the direction Irwin, F. W. (1953). Stated expectations as functions of of promoting less risky choices across many domains.
probability and desirability of outcomes. Journal of While the results of the present study show that men and women differ in their assessments of the likelihood and Jervis, R. (1976). Perception and misperception in in- severity of negative outcomes — both apparently con- ternational politics. Princeton: Princeton University tributing to their different propensities for engaging in such behaviors — it is possible that men and women also Johnson, J. G., Wilke, A., & Weber, E. U. (2004). Be- differ in their reactions to risk (i.e., outcome variability) yond a trait view of risk-taking: A domain- specific scale measuring risk perceptions, expected benefits,and perceived-risk attitude in German-speaking pop-ulations. Polish Psychological Bulletin, 35, 153–172.
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2. Disagreeing with your father on a major issue.
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5. Asking someone you like out on a date, whose feel- 6. Raising your hand to answer a question that a For each scenario, subjects answered the following All scenarios are from Weber, Blais, and Betz (2002), ex-cept those marked “additional.” For each scenario, partic- a. Please indicate your likelihood of engaging in this ipants were asked four questions using the 5-point scales activity or behavior? [5-pt scale: 1 = very unlikely, b. If you engaged in this activity, what is the likeli- 1. Betting a day’s income on the outcome of a sporting hood (probability) that it would have negative con- event (e.g. baseball, soccer, or football).
sequences for you? [5-pt scale: 1 = not at all likely,5 = extremely likely] 2. Betting a day’s income at the horse races.
c. If you engaged in this activity, how bad would the 3. Betting a day’s income at a high stake poker game.
potential negative consequences be if they were tohappen? [5-pt scale: 1 = not at all bad, 5 = extremely 4. Gambling a week’s income at a casino.
Judgment and Decision Making, Vol. 1, No. 1, July 2006 d. Assuming that there were no bad outcomes, how en- 1. Do you smoke? [H] [5-pt scale: 1 = no, 2 = no, I joyable/positive would this experience be for you? used to but quit, 3 = yes, less than 1/2 pack a day, 4 [5-pt scale: 1 = not at all enjoyable, 5 = extremely = yes, 1/2 – 1 pack a day, 5 = yes, more than a pack 2. How many alcoholic beverages do you typically drink in a week? [H] [5-pt scale: 1 = none, 2 = 1–4,3 = 5–8, 4 = 9–12, 5 = 13 or more] Positive domain scenarios created for the present study: 3. How often in the last 6 months have you had too 1. Trying to sell a screenplay, which you have already much to drink or gotten drunk? [H] [5-pt scale: 1 = written, to a Hollywood film studio.
never, 2 = once, 3 = 2–4 times, 4 = 5–7 times, 5 = 8or more times] 2. Calling a radio station where the 12th caller will win 4. How often do you drive over the speed limit? [H] [5- pt scale: 1 = almost never, 2 = rarely, 3 = sometimes, 3. Sending out 30 applications for high paying jobs af- 5. How often do you get into arguments with friends or 4. Regularly visiting a professor in her office hours and family? [S] [5-pt scale: 1 = almost never, 2 = rarely, then asking her for a letter of recommendation.
3 = sometimes, 4 = often, 5 = almost always] For each scenario, subjects answered the following 6. How often do you gamble (e.g., betting on sports events, gambling at casinos, playing the lottery,playing games for money with friends)? [G] [5-pt a. Please indicate your likelihood of engaging in this scale: 1 = almost never, 2 = rarely, 3 = sometimes, 4 activity or behavior? [5-pt scale: 1 = very unlikely, 7. How often do you engage in risky recreational ac- b. If you engaged in this activity, what is the likeli- tivities (e.g. scuba diving, hang gliding, motorcycle hood (probability) that it would have positive con- riding)? [R] [5-pt scale: 1 = almost never, 2 = rarely, sequences for you? [5-pt scale: 1 = not at all likely, 3 = sometimes, 4 = often, 5 = almost always] 8. How often do you “bend” or break traffic laws? c. If you engaged in this activity, how good would the (e.g., jay walking, rolling through stop signs, run- potential positive consequences be if they were to ning lights that have just turned red, not wearing a happen? [5-pt scale: 1 = not at all good, 5 = ex- seatbelt)? [H] [5-pt scale: 1 = almost never, 2 = rarely, 3 = sometimes, 4 = often, 5 = almost always] d. Assuming that there were no good outcomes, how 9. How often do you raise your hand to answer or ask unpleasant/negative would this experience be for questions in class? [S] [5-pt scale: 1 = almost never, you? [5-pt scale: 1 = not at all unpleasant, 5 = very 2 = rarely, 3 = sometimes, 4 = often, 5 = almost Actual past risk behavior questions created for the presentstudy, including some adapted from Gibbons and Gerrard(1995). Each question’s association with a domain is in-dicated with the first letter of the domain.


If you own a bull terrier, you know that they will eat anything their little heart’s desire. Coins, buttons, rocks, socks, earrings, blankets, stuffed toys, and wastebasket contents (especially in the bathroom) are all treats for your bull terrier. Dental floss, dental plaquers, (mint flavor, yummy) underwear, diapers, you name it, the list is endless. So how does one know when to be concerned?

Important Information for Your Upcoming Flexible Spending Account (FSA) Enrollment As you may have heard, there is new legislation going into effect on January 1, 2011 which impacts healthcare FSAs. Here’s what’s happening. Certain over-the-counter items will require a prescription* to be considered an eligible FSA expense. The information below is important for you to know as yo

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