In our daily life, we constantly evaluate the likelihood of possible future events in order to take decisions under uncertainty. However, we do not process the obtainable evidence in an objective and strictly realistic manner. Indeed, our reasoning is inherently subjective and contains systematic biases. The optimism bias constitutes one of the most widespread and consistent cognitive biases. People believe to be less at risk of experiencing negative events, while on the other hand overestimating their likelihood to experience positive events (Shepperd, Waters, Weinstein, & Klein, 2015).
About 80 % of the population regardless of age, sex, education and occupation are unrealistically optimistic. / display optimistic errors (Sharot et al., 2011). Furthermore, the bias is widespread in an extensive range of fields including workspace, finances, well-being, personal relationships or self-evaluation (Dunning, Meyerowitz, & Holzber, 1989). In the western world, two out of 5 marriages will end up in a divorce (Sharot, 2011). Nevertheless, those about to marry consistently underestimate the longevity of their own marriages (Baker & Emery, 1993).
One could argue that they are too naive, having no experience and knowledge about marriages. However, even experts display concerning degrees of optimism bias. Family lawyers underestimate the negative consequences of a divorce even though they are confronted with clients’ divorces on a daily basis (Sharot, Korn, & Dolan, 2011). Moreover, medical practitioners overestimate the success of their therapy and financial specialists predict unusually high profits (Calderon, 1993) to the point that economists have proposed the optimism bias as a root cause for the financial meltdown/crisis of 2008 (Shefrin, 2009).
It has been proposed that cognitive and motivational factors underlie these unrealistic perceptions. From the cognitive perspective, optimistic beliefs may be a natural outgrowth of the process of setting goals. By thinking about ways of achieving a goal, the belief that one will accomplish it is strengthened. Complementary, imagining approaches how to avoid negative events improves the perception that one will be capable of doing so. Additionally, we are highly motivated to be optimistic. By believing that our probability of success is higher than that of failure, a positive sense of oneself, including one’s skills, capabilities, resources and outcomes can be preserved. Moreover, gender seems to influence optimistic perceptions. Lin & Raghubir (2005) show that men display greater optimism bias than women regarding expectations of their marriage. However, the underlying mechanisms are thus far not established.
An important question stemming from these observations is whether costs of irrational and overoptimistic beliefs outweigh potential benefits. On the one hand, constantly expecting positive outcomes can encourage goal persistence, motivation, positive affect and hope (Armor & Taylor, 1998). Furthermore, Taylor and Brown (1988) propose that healthy individuals view their future overly optimistic and that being accurate about one’s personal risk may have negative consequences on mental health. Specifically, it is suggested that depression is associated with to an absence of optimistic beliefs about future life events (Korn, Sharot, Walter, Heekeren & Dolan, 2014).
Hence, it is claimed that being unrealistically optimistic about one’s future is natural and beneficial for mental health. At the same time, increasing evidence suggest that underestimating one’s risk is problematic as it can prevent people from taking adequate precautions. Indeed, looking at most health behavior models, a necessary requirement to take precautionary action is to perceive oneself as personally vulnerable to a negative event beforehand. Consistent with this line of reasoning, Kim and Niederdeppe (2013) have found that people who were unrealistically optimistic about evading the H1N1 virus stated lower intentions to wash their hands and use hand sanitizers.
Although the existence of unrealistic optimism has been extensively studied, the bias appears to be remarkably resistant to a variety of manipulations designed to reduce it. Learning theories suggest that people usually adjust their beliefs when confronted with contradicting information (Pearce & Hall, 1980, Sutton & Burton, 1998). Nevertheless, Sharot, Korn & Dolan (2011) have found that when asked to estimate the likelihood of experiencing an aversive life event after receiving the average probability of experiencing those events, participants only changed their estimates significantly when the average frequency was better than their own estimate, but did not so, when it was worse. This belief update method introduced a new way of assessing the optimism bias and suggests that providing people with the actual risk estimates is surprisingly unsuccessful at adjusting individual’s perception of their own vulnerability.
Considering these findings, perceived vulnerability may need to be defined differently by decomposing it into both absolute and comparative terms. The former is linked to the absolute optimism bias, which refers to people’s risk estimates as overly optimistic as pointed out by to a quantitative, objective standard. For example, someone may belief that his risk of getting cancer, is below 10%, while in fact his family background and unhealthy lifestyle cause his risk to be over 50%. The latter is linked to the comparative optimism bias, which states that people evaluate their personal outcomes as more favorable than the outcomes of another specific reference group.
In several experiments, it has been demonstrated that comparative and absolute risk perception influence behavioral intentions. Klein (1997) even postulates that comparative risk perceptions have a stronger effect than the comparison to an objective standard. Especially for self-evaluations, objective criteria are often redundant, demanding the use of social comparison information. It is virtually impossible to evaluate one’s attractiveness, intelligence or achievements without looking at how other perform on these aspects. Accordingly, in many situations, people apply social comparison information as a gauge for judgment, which in most cases, gives rise to a favorable self-assessment (Aspinwall & Taylor, 1993). Indeed, breast cancer patients compare themselves with others in still worse conditions in order to effectively cope with their situation (Wood, Taylor & Lichtman, 1985).
The underlying mechanism which operates to purposely elect inferior target has been appointed to downward comparison. In a study by Perloff & Fetzer (1986) participants rated their own risk of experiencing several negative events and provided ratings for the average student, their closest friend, or “one of your friends“. Participants exhibited less optimism bias when comparing themselves with a best friend than with “one of your friends“, or the average person. These findings indicate that vague targets encourage downward comparisons, while specific targets make this kind of comparison more difficult (Perloff & Fetzer, 1986).
Several researchers have offered motivational and cognitive mechanisms as an explanatory basis for this phenomenon. Weinstein (1980) explains/ claims that a basic cognitive short-cut can be attributed to the main cause of comparative optimism. The representativeness heurististic describes the tendency to base one’s risk estimation merely with regard to how closely an event corresponds to a person’s prototype (Tversky, 1977). Thus, a vague and general comparison target may facilitate the selection of a general prototype of the risk category. This leads to lower risk judgements to the extent that people feel they are dissimilar to the prototypical target.
Others argue that similarity to the comparison target is associated with less comparative optimism bias. It was found that optimism bias for smoking related health problems was greatest among those smokers who considered themselves least similar to the typical smoker (McCoy, Gibbons, Reis, Gerrard & Sufka, 1992). Furthermore, in a number of studies, Alicke, Klotz, Breitenbecher, Yurak & Vredenburg (1995) enhanced individuation of the comparison target by having participants look at a videotape or photo of the person with whom they were comparing themselves. Participants showed less optimism bias than a control group that compared itself with the average person. According to the person-positivity bias, vague and generalized targets are seen as less human and thus less favorable (Sears, 1983).
An interesting question stemming from these observations is whether the type of comparison standard differentially affects optimistic belief updating. Therefore, the current study was set up. Although optimism bias is characterized both as the overestimation of positive future events and the underestimation of future negative events, we concentrated on the latter, as this is strongly associated to a concern that people do not take precautionary action to protect themselves against hazards.
In order to provide additional confirmatory data on the phenomenon of comparative optimism bias we examine how the comparison standard affects participant’s optimism bias. Half of the participants were asked to estimate their likelihood of experiencing various adverse life events by comparing themselves to a fellow peer (vague target). The other half was instructed to compare themselves to their closest friend (specific target). It is hypothesized that participants who compare themselves to a specific target will show less optimism bias than participants who compare themselves to a vague target.
Thereafter, using a belief update task (Sharot et al., 2011), participants were asked to reevaluate their likelihood compared to either a fellow peer or their closest friend, while being presented to the actual population risk estimates. Of critical importance and contrary to the disappointing results of using the belief update task alone (Sharot et al., 2011), we expect that participants who compare themselves to a specific target will show less optimism bias at the second evaluation and update their beliefs more in the direction of the population risk estimates than participants who compare themselves to a vague target.
Replicating past studies and combining differential levels of comparison target with the belief update method could shed light on new methods to reduce the optimism bias. The optimism bias has large societal implications since it has strong effect on decision-making. Therefore, knowing about ways to diminish the bias