Keywords

You, the reader, are already well aware that in this book we analyze two cognitive positive biases: the better-than-average effect and unrealistic optimism. The former seems to produce negative consequences only when it is acutely amplified, when, to use Baumeister’s (1989) language, it ceases to be an illusion and takes the form of a delusion. In such situations, the individual, convinced of their own perfection, may lose motivation to enhance their competence and skills (Brown, 2012; Moore & Healy, 2008). Research also shows that, in certain situations, it can also diminish one’s interpersonal attractiveness, especially in the long term (Bonanno et al., 2005). While certainly in some cases the belief that one is better than others can also have – as we have shown above in the context of prevention against COVID-19 – negative consequences for people’s functioning in the area of health, by far the second of the biases analyzed in this book, unrealistic optimism, seems more dangerous. In his pioneering article on this positivity bias, Neil Weinstein (1980) already draws attention to the dangers of optimism construed in this way. In doing so, he presents research showing how the magnitude of this positivity bias can be reduced. While we have also discussed a number of works in the broad context of healthcare confirming these preliminary results and presented a detailed analysis of the dangerous link between realistic optimism and the failure to employ active behaviors targeting COVID-19, the key question is “what can be done” to reduce the widespread and dangerous presence of unrealistic optimism during threats such as the coronavirus pandemic.

Recall that the author of the concept of unrealistic optimum, Weinstein, started from the premise that one of the reasons for the occurrence of unrealistic optimism may be a false image of other people. The individual may believe that, for various reasons, they are very likely to be victims of various undesirable events and, on the other hand, lack the competence, motivation, perseverance, or other attributes to achieve desirable states. In other words, while people are aware of their own attributes and competencies, they are not aware that other people also have them. And it is precisely this discrepancy in knowledge about oneself and knowledge about other people, referred to as cognitive egocentrism, that is one of the sources of unrealistic optimism. Now let us look at how cognitive egocentrism is empirically tested for the reduction, or even elimination, of unrealistic optimism.

4.1 You Are Not Exceptional, Not at All!

In Weinstein’s (1980) pioneering experiment, 120 female students of Rutgers University took part. They were asked to estimate from what percentage of female students at that university they were more likely to experience various negative events and from what percentage of female students they were more likely to have various positive experiences. The respondents were then asked to write down the various factors that lead them to make such judgments. So they were to write down what actually makes them more likely than others to have positive things happen in their lives and what makes them relatively (i.e., compared to other people) less likely to experience various traumatic events. After doing so, they were handed a folder with pages that had been written by five other female participants who had been surveyed earlier in the experiment. They were asked to read these notes carefully. By this procedure, the students were able to see that other people gave a whole host of different reasons why they would be highly likely to experience desirable states and avoid undesirable ones. Finally, respondents again filled out a questionnaire allowing them to estimate their level of unrealistic optimism. It turned out that this procedure led to a significant decrease in the level of bias analyzed here.

In subsequent studies, Weinstein (1983) used a slightly different procedure, although the idea of reducing unrealistic optimism itself remained the same. This time, both men and women were studied, and participants were randomly assigned to one of three experimental conditions. In the first condition (control), they simply estimated their chances of experiencing various negative states of affairs, comparing them to the chances of the average university student of their own sex. In the second condition (own risk), the participants were asked to think about whether, in their case, the possibility of avoiding undesirable events might be influenced by the various factors presented to them, and only then did they measure their level of unrealistic optimism about various negative events. In the third group (information), participants were shown the same list of factors, but at the same time, with each question they were told what percentage of previously surveyed students at that university considered the factor to be important in their own case. The reduction or increase in the level of unrealistic optimism can be described in this experiment by comparing the estimates made by participants in the last two groups with those made by participants in the control condition, that is, those who were simply asked to provide risk assessments.

Weinstein asked participants to estimate their own chances of avoiding negative events compared to those of the average student for ten different events. He chose five for which very strong unrealistic optimism had been recorded in earlier studies (diabetes, heart attack, drinking problem, suicide, lung cancer) and five for which unrealistic optimism was weak or not reported at all (other form of cancer, ulcer, tooth decay, high blood pressure, auto accident injury, mugging).

It turned out that among the participants subjected to the “information” type of intervention (reduction of cognitive egocentrism, orientation to others), there was a marked reduction in the level of unrealistic optimism with regard to events where the research usually recorded high levels of this bias, and except for one case (auto accident injury), there was no change in their belief about the chances of avoiding undesirable conditions with regard to events where the bias was generally weak. In contrast, there was an increase in the level of unrealistic optimism among participants who reflected only on their own situation (own risk group, where self-centeredness boosts egocentrism). Interestingly, this effect appeared both for events in which unrealistic optimism is usually noted and for events in which it usually does not appear or is weak.

We can therefore see that one way to reduce unrealistic optimism may be to make people aware that they are not unique with regard to certain events – other people also have various attributes or competencies that may, in their individual case, favor the avoidance of undesirable states. This assumption is consonant with the findings of Weinstein and Lachendro’s (1982) experiment, in which it was shown that even just getting people to think about various factors that can reduce the risk of others experiencing negative events may to some degree reduce the level of positive illusion discussed here.

A number of years later, Rothman et al. (1996) took a more systematic look at this regularity. They had reliable statistics at their disposal on the probability of various negative states of affairs for the American population. Thus, for example, the probability of at least one divorce in a lifetime was 38% at the time the experiment was conducted, for pneumonia ending in death 2.2% for women and 1.9% for men, and for alcohol dependence or problems resulting from excessive drinking 4.5% for women and as high as 19.5% for men.

The experiment reported here involved female students who were randomly divided into three groups. In the first group, real statistics were presented on the probabilities of various negative events occurring in an American woman’s life (such as divorce, alcoholism, chlamydia, depression requiring treatment, or reaching a weight 20% above the norm). In the second group, these statistics were fabricated by giving the participants twice the actual values. In the third group, the respondents were also given false data, but the figures were 150% of the actual values. They were asked to indicate the probabilities that various negative states of affairs would happen to them.

The results were unequivocal. When the respondents were presented with real statistics, they exhibited unrealistic optimism. This illusion was amplified when they were given fabricated statistics suggesting that the risk to the population was lower than it actually was. If, on the other hand, they were provided with false statistics that overstated the risk, they also made higher estimates of the probability that negative events might be their lot. Note, however, that while this is clear evidence that, in estimating risks to themselves, people take into account the probability that such an event could befall the average person in their population, this does not necessarily lead directly to the phenomenon of unrealistic optimism. In other words, the question is whether people demonstrate a belief that they are less likely to experience various negative states of affairs from the statistical values they are provided.

It turned out that in circumstances when they were given falsified statistics suggesting that the risk was higher than it actually was, this was the case. Under such conditions, the women in the study believed that they were clearly less likely to experience such events than the average American woman. However, if the participants were given statistics falsely suggesting that the probability of experiencing various negative events was lower than the actual probability, not only did they not manifest unrealistic optimism but actually considered themselves slightly more likely to experience undesirable conditions than the average American woman. In summary, there is a very interesting interrelation here. If we mislead someone by suggesting that the objective (statistical) probability of some negative event occurring in the life of a person from the group to which they belong is lower than it really is, then, while they will incorrectly assume that the probability of them experiencing it is low (i.e., they will think it is lower than objective statistics suggest), they will not, at the same time, manifest unrealistic optimism. They will not believe that they are less vulnerable than most other people (and may even believe that they are slightly more vulnerable than they are). If, on the other hand, we present them with falsified statistics, from which it will appear that the threat, statistically speaking, is high (more accurately, higher than it would appear from objective data), then they will overestimate the threat to themselves, while at the same time demonstrating heightened unrealistic optimism. Thus, we can conclude that misleading people about such statistics is a double-edged sword and therefore counterproductive. We also cannot overlook the ethical aspect here. After all, lying to patients or clients of a doctor or psychotherapist must not be condoned. Thus, although the experiment presented here, aimed at identifying the mechanism responsible for reducing unrealistic optimism, is cognitively meritorious, we cannot recommend the described interaction as a way of reducing this bias.

4.2 Don’t Look Away: Think About the Danger!

You may recall that unrealistic optimism helps reduce fear and anxiety. Thus, it can be assumed that it allows us to disregard that which threatens us. Anxiety, after all, concentrates our attention on the factor that causes it. So let us look at another possibility, consistent with this assumption, for reducing such positive illusions, which comes from research published by Frank McKenna and Ian Albery (2001).

In contrast to the researchers whose experiments we have discussed above (where the effect of reducing egocentrism on lowering unrealistic optimism was tested), McKenna and Albery assumed that a decrease in unrealistic optimism could be achieved by directing one’s attention to oneself, rather than to other people. However, this is not a matter of focusing on various real or hypothetical competencies or mental dispositions that can help a person avoid a threat but on the negative event itself as such. A situation in which the individual can imagine being a participant in, or actually a victim of, such accidents can increase their subjective belief that this is possible (it is difficult to fear something we don’t know about and don’t pay attention to, such as Ebola for Europeans). In turn, this is easiest to imagine if one has already experienced such a situation.

McKenna and Albery (2001) explored this possibility in a simple fashion and ensured that their study included drivers with a variety of driving experiences: those who, according to police records, had never been in an accident, those who had caused a minor accident that did not injure its participants, those who had caused a serious accident in which someone else was injured, and those who had caused an equally serious accident in which they themselves were victims. Participants were asked to estimate how skilled they were at driving compared to the average driver and how safe they drive, as well as how likely they were (also, of course, compared to the average driver) to cause a traffic accident in the future. Thus, we see that we are dealing here with both questions pertaining to the realm of better than average (the first two questions) and to that of unrealistic optimism (question three).

It turned out that, with regard to the first two questions, two groups proved distinct from the other two. Common sense would dictate that drivers who had never caused an accident considered themselves more skilled and safer drivers than those in the other groups. After all, it is difficult to assume that one is an unsafe driver if one has never caused an accident. Drivers who themselves suffered in an accident they caused considered themselves, in turn, to be the least capable and the least safe of the four groups surveyed. This, too, is perfectly understandable: having accidents = not driving safely.

However, it turned out that when estimating the likelihood of causing an accident in the future, no differences were noted between the four groups of drivers. For the sake of clarity, we should add that strong unrealistic optimism was recorded in all four groups. Thus, summarizing these results, it can be said that personal experiences can change unrealistic beliefs about one’s own above-average abilities but do not reduce the level of unrealistic optimism and perception of the future. This may yield serious lessons for pandemic management and the feeling of unrealistic optimism: regardless of whether we have been affected by the virus, we unrealistically assume that it will not affect us (anymore), but it will affect others!

As part of our own empirical research program on the positive illusions experienced by people during a pandemic, we also faced failure in developing a technique to reduce the level of unrealistic optimism. Our idea was inspired by the so-called cognitive accessibility heuristic (Tversky & Kahneman, 1973). A good example of this phenomenon is a study whose participants read a list of names. In one case, it consisted of the names of 19 famous men and 20 rather unknown women, and in the other case, it consisted of the names of 19 famous women and 20 little-known men. When the participants were then asked whether there were more women or men on the list, those reading the first list mistakenly thought there were more men, while those reading the second list thought there were more women. The explanation for these mistakes is that familiar names were cognitively easier to remember and recall (because they were familiar) when it came to answering the question of whether men or women dominated the list in terms of numbers.

Building on the concept of the accessibility heuristic, Norbert Schwarz and colleagues concluded that in certain situations, people can base inferences about their own characteristics on the extent to which certain information is accessible to their cognitive processes (Schwarz et al., 1991). Some participants in the experiment were asked to recall 6 episodes from their own lives when they behaved assertively, while others were asked to recall 12 such episodes. Subsequently, they completed a self-assessment and were asked to evaluate, among other things, their own assertiveness (understood as a personality trait).

It turned out that those who were previously tasked with recalling 6 episodes were considered more assertive than those who recalled 12 such events. Why? Recalling six episodes of one’s own assertive behavior is quite easy, and probably each of us can perform this task. By then answering the question “how assertive are you?,” the participants have a solid basis for thinking of themselves as people endowed with such a trait: “Since I can easily recall situations in which I reacted assertively, it means that I am assertive.” However, recalling 12 such episodes is difficult or even very difficult for most people (for us, the authors of this book, it is very difficult). Thus, if the participants of the study are asked how assertive they are, their inference proceeds as follows: “Since I had so much difficulty recalling real situations from my own life in which I reacted assertively, it means that I’m probably not very assertive.”

Seeking to apply the above results to the pandemic context, we hypothesized that the same might be true of unrealistic optimism and the assumption that one is less likely to contract COVID-19 than other, similar people (we discussed this research in Sect. 3.3). In designing our study, we assumed that if we asked people to give a small number of reasons for believing that they were less likely to experience a negative event (contracting COVID-19) than the average person, it would be an easy task for them. However, if we ask them to give a large number of such reasons, the task becomes difficult. Consequently, in the first of these cases, people should demonstrate heightened unrealistic optimism (“My risk of contracting COVID-19 is lower than that of other, similar people”), but in the second, the degree of this positive illusion should decrease (“it’s hard for me to give reasons why I’m actually at less risk so I suppose I’m in the same danger as other, similar people”).

In our experiment (Kulesza et al., 2023c), we conducted an online survey of a large group of subscribers to an online university portal for the dissemination of scientific knowledge. We randomly divided the participants into four groups. In the first (control) group, they simply estimated the probability that they themselves would become ill with COVID-19 and estimated the probability that an average subscriber of that portal of their sex would become ill. In the other groups, before making such an estimate, they were asked to list (3, 6, or 9, respectively) factors that should prevent them from becoming ill with COVID-19 themselves, and only after doing so did they answer the same two questions we asked in the control condition.

While we had presumed that an individual’s generating six and certainly nine reasons why they were at low risk of getting sick would diminish their unrealistic optimism, nothing of the sort occurred. In addition, we found that the more reasons people gave for remaining healthy in a pandemic, the higher their level of unrealistic optimism was.

So, as we can see, we failed to confirm our assumptions. Perhaps this was because generating even nine reasons to justify one’s own optimism was not difficult enough for our participants. (Unfortunately, we did not control for this in our experiment.) It is also possible that our proposed method of reducing unrealistic optimism, while ineffective for contracting a virus during a pandemic, would be effective in other situations. Only future research can answer these questions.

Further research is also undoubtedly needed on the suggestion for reducing unrealistic optimism presented by Hye Kyung Kim and Jeff Niederdeppe (2016). They addressed the problem of risky drinking by college students. They noted that “dry” information about the harms of alcohol and behaviors that can lead to alcoholism or other problems associated with excessive drinking is not very impressive to students, who prefer to party hard with huge amounts of beer or whiskey. They also noted that the level of unrealistic optimism they measured in the student population is clearly related to such alcohol-fueled, leisure activities presenting health risks.

How did the study work? The unrealistic optimists were provided with either dry descriptions saying that drinking large amounts of alcohol was very harmful, or they were introduced to narratives from a student who related that heavy partying based mainly on getting drunk had led him to considerable health problems and an inability to concentrate on his studies (e.g., increasing difficulty in completing homework assignments) during the experiment. The hard-partying student also added that he by no means realized that drinking alcohol could lead to such a predicament. In the control conditions of this experiment, the students were not given any information about the consequences of alcohol use or abuse. All of the participants were asked, in turn, what they thought the likelihood was that they themselves would experience negative consequences of alcohol use during the current semester.

It turned out – contrary to the expectations of the study’s authors – that the aforementioned perceived threat was the same in all three experimental conditions (i.e., the “dry” information, narrative, and control conditions). Note, however, that Kim and Niederdeppe examined the level of unrealistic optimism only at the beginning of their study, and after the experimental manipulation, they asked the participants only about the threat they perceived in relation to themselves. The lack of measurement of an analogous threat to the “average other,” therefore, makes it impossible to judge whether the narratives bear any relation to unrealistic optimism per se. This issue therefore requires further empirical exploration, as we have already noted.

4.3 Chameleon? Failed!

As part of our research program, we considered whether, for example, doctors – when visiting and talking to patients – or others directly interacting for health purposes with people affected by the COVID-19 pandemic should employ the common method of mimicry, an imitation also called the “chameleon effect” in the literature. There were several justifications for choosing this technique to change views of comparative biases. First, mimicry has been shown to reduce egocentrism: a mechanism we discussed in the first chapter that is a key factor in the constitution of comparative biases. In numerous studies it was shown that mimicry changes the social focus from “me” toward “others” (Lakin et al., 2008; Van Baaren et al., 2004) and changes in social orientation from “me” to “you” create greater tendency to perform mimicry (Castelli et al., 2009; Leighton et al., 2010; Van Swol & Drury-Grogan, 2017).

Participants of our experiment (Kulesza et al., 2022a) for 10 min interacted online with the confederate. The study took place under strict lockdown, so exposure to the COVID-19 threat was imminent, making this experiment especially relevant: participants were not asked to “imagine” being in a pandemic (see also Dolinski, 2018). To stress the focus of the ongoing coronavirus pandemic, the topic of the interview concerned opinions on the ongoing COVID-19 pandemic. In the mimicry condition, the confederate repeated some verbal statements expressed by participant, while in the control condition the confederate only assessed understanding of the statements (“yes,” “I understand”; see details for this manipulation, Kulesza et al., 2014).

Contrary to our expectations – backfired – it fueled the unrealistic optimism bias in estimation of risk of COVID-19 infection. Importantly, it is probably the first experiment in the body of research on comparative biases showing that a specific manipulation may fuel this phenomena, indicating that future studies should also research this area.

Our next empirical program, on the possibility of using mass media for this purpose, turned out to be more conclusive in terms of finding a way to reduce levels of unrealistic optimism (Dolinski et al., 2022).

4.4 Media Intervention Program

As we already know, the mechanism of cognitive egocentrism leads the individual to focus on their own behavior, while being less aware of other people’s actions. This makes them think they have a better chance than others to avoid various negative events. Part of the techniques described above for lowering the intensity of unrealistic optimism are thus focused on making one realize that other people also take various actions that are motivated by their desire to reduce risk (Weinstein, 1980, 1983; Weinstein & Lachendro, 1982; Rothman et al., 1996). Note, however, when people estimate the risk of contracting an easily spread virus during a pandemic, the situation is much more complex than with regard to diseases and disorders such as alcoholism or obesity. In cases of alcoholism or the possibility of obesity, the actions and behaviors of others have a very limited impact on the individual’s situation. One may or may not become an alcoholic and may or may not become obese regardless of what other people (especially those outside their circle of acquaintances) do.

In the case of infectious diseases, however, the situation is quite different. The behavior of other people who can transmit viruses remains in close relation to the situation of the individual, who, willingly or unwillingly, must come into contact with such people, at least from time to time. This creates, from the perspective of factors that can affect the level of unrealistic optimism, a unique situation. On the one hand, making the individual aware that others also frequently wash their hands, keep physical distance, disinfect surfaces in the places they are in, or wear masks should make us realize that we are not unique in these respects and, consequently, reduce our level of unrealistic optimism. On the other hand, however, the conviction that many others are acting unwisely and not following medical advice should make us realize that this increases the likelihood that we ourselves will get infected (from such people) and become ill. Nevertheless, in the case of the COVID-19 pandemic, many of us have contracted this dangerous disease at least once, and certainly we all know people affected by the virus. Moreover, unfortunately, some of us have suffered the death of a loved one from COVID-19. Consequently, influenced by just such information, we should also experience a reduction in unrealistic optimism.

In doing so, we should note that during a pandemic the mass media can present all sorts of images and information about people’s behavior. They can – and do! – both create the impression that the vast majority of the population follows medical recommendations and publicize cases indicating that there are numerous situations in which people do not wear masks or ignore bans on mass events (such as rock concerts). As part of our empirical research program, we decided to test how the aforementioned information of various kinds (other people follow medical recommendations vs. other people don’t follow them) affects the level of unrealistic optimism that individuals demonstrate.

Our first study included 350 participants of both sexes randomly assigned to one of three experimental conditions (Dolinski et al., 2022). (The initial pool had 360 participants, but it turned out that 10 of them were infected with COVID-19, so they were excluded from analysis.) For the two experimental groups, the participants read newspaper articles we had prepared especially for them. In the first condition, they made clear that people were widely ignoring medical advice on how to function in a coronavirus pandemic. In the second condition, the thrust of the articles was completely different. They indicated that people were universally following medical guidelines. Participants in the third group (control conditions) did not read any of the newspaper articles we had prepared. They were asked questions about their own risk of getting infected and that of the “average other” (a classic measure of unrealistic optimism). We present the results of this experiment in Fig. 4.1.

Fig. 4.1
A bar chart with an error plot of the estimated risk of infection versus negative article, positive article, and control. The values of me and the peer are exhibited for each condition. Bars titled peer have a higher peak.

Unrealistic optimism effect in three experimental conditions

Source: Applied Psychology: Health and Well-Being, 14, p. 505

Copyright: Wiley

Note: Bars represent mean values, error bars represent standard error of mean

Full size image

As we can see, the pattern of results for respondents who read articles about people ignoring medical recommendations is the same as in the control condition. In both cases, people demonstrate unrealistic optimism, and estimates of risk to self and risk to the average other are also almost identical. However, the situation is different when people have read information about others behaving responsibly, and public compliance with medical recommendations is widespread. This time the unrealistic optimism vanished! For the sake of clarity, we add that this effect was achieved because people began to perceive themselves as more likely to get sick. The effect is therefore analogous to that obtained in earlier studies dealing with noncommunicable diseases and other adverse conditions (Weinstein, 1980, 1983; Weinstein & Lachendro, 1982; Rothman et al., 1996).

In our second study, we decided to see if this pattern of results would be replicated in conditions using media that employ images rather than words. This time, we presented 600 participants with videos (no words, conversations, or commentary were heard) showing the behavior of a group of people in a coffee shop. Some people saw a video in which people ignored medical recommendations (they did not disinfect their hands when entering the café despite passing a visible dispenser; they did not wear face masks; they crowded in line at the counter when choosing pastries and ordering coffee), while some were shown a video in which people behaved completely differently – they complied fully with all medical recommendations. Participants were not shown any video in the control condition.

Analysis of the results of this experiment quite unexpectedly revealed an entirely different structure to those of the experiment discussed previously. As we will see in Fig. 4.2, people observing others who behave as prescribed medically felt less at risk overall, that is, they exhibited unrealistic optimism. Compared to participants in the control condition, they believed that both they themselves and the “average other” were at less risk. At the same time, these participants demonstrated the same strong unrealistic optimism as those in the control condition. It was the “average other” who, in their view, was more likely to contract COVID-19. In contrast, we noted a decrease in unrealistic optimism among the participants who had watched the video showing people ignoring medical recommendations.

Fig. 4.2
A bar chart with an error plot of the estimated risk of infection versus negative video, positive video, and control. The values of me and the peer are exhibited for each condition. Bars titled peer have a higher peak.

Unrealistic optimism effect in positive and negative movie conditions

Source: Applied Psychology: Health and Well-Being, 14, p. 508

Copyright: Wiley

Note: Bars represent mean values, error bars represent standard error of mean

Full size image

Thus, we see that a completely different pattern of results was obtained when the participants read texts versus when they viewed images. In the first case (reading a newspaper piece), unrealistic optimism was reduced under conditions when the participants learned that other people were behaving properly and following medical recommendations, while in the second case (observing other people’s behavior in a video), the pattern was exactly the opposite – it happened only when people saw others completely ignoring medical recommendations.

How can these discrepancies be explained? We assumed that the pivotal factor is that reading articles is more effortful than watching videos, as reflected in the results of numerous studies (e.g., Dalrymple & Scheufele, 2007; Eveland et al., 2002). Thus, reading an article reduces cognitive egocentrism and prompts us to focus on the threat and assume that, because other people exhibit different health-promoting behaviors, there is no reason for us to continue believing that we are less likely than they to get sick. Watching a video, which is less effortful because it is less demanding, is not as likely to induce analytical thinking. In conditions where the participant sees people ignoring recommendations, the image acts as a danger signal: “because of people like them, I can get sick.” In other words, the key to explaining the different patterns of results in our two aforementioned experiments is found in the fact that particular forms of media lead people to process the information they receive more or less carefully.

The results of our third experiment, in which we independently manipulated the form of the message (written text vs. video footage) and information about other people’s behavior (consistent with medical recommendations vs. inconsistent with them) essentially confirmed the validity of this interpretation.

4.5 Teach and Learn?

In the first chapter of this book, we have already presented one of our studies conducted at the very beginning of the pandemic (Study #2; Kulesza et al., 2021). As a reminder, unrealistic optimism was found in three different countries, Poland, Kazakhstan, and Iran, and this comparative bias did not disappear. In that paper, we also reported a second study that may indicate some directions for another mechanism responsible for reducing unrealistic optimism, i.e., knowledge and education.

This survey was conducted in the Polish highest tertiary referral pediatric hospital with almost 1000 beds, up to 50,000 hospitalizations, and about 120,000 ambulatory clinic visits per year and thus in a frontline hospital not only in terms of fighting COVID-19 pandemic but in the volume and complexity of cases. We were interested if healthcare professionals would present unrealistic optimism or not, since both scenarios were possible: (1) to the best of our knowledge, so far there is no research showing that some work environments are free from unrealistic bias; thus we could expect that healthcare professionals would report this comparative bias as well; (2) since healthcare professionals are not only highly educated in terms of academic knowledge but first and foremost during COVID-19 pandemic were witnesses – to an extent inaccessible for the average person – to the severity of this virus, as a result, they would not report this bias. In this case, formal education and/or exposure to the severity of the pandemic both would “educate.”

More than 200 healthcare professionals (doctors/physicians, nurses, first responders/paramedics) completed the survey. Importantly, they did so during the first wave of the COVID-19 pandemic, when we assessed unrealistic optimism in Poland. They delivered surprising results: no unrealistic optimism was found! A summary of the results can be found in Tables 4.1 and 4.2.

Table 4.1 Summary of the results from the second study (dependent samples t-test)
Full size table
Table 4.2 Summary of the results from the second study (independent samples t-test)
Full size table

A very cautious practical conclusion is that we should educate (in the formal sense; academically, through coursework; “in real life,” by showcasing the effects of the pandemic). We note that this professional group possesses both qualities. While formulating the above cautious recommendation, we would like at the same time to strongly emphasize several caveats. The referenced study may suggest the previously described relationship between exposure to COVID-19 (direct, contact with patients, and indirect, knowledge of the disease), but it must be kept in mind that this was not a classic experiment! Therefore, it is possible that other factors specific to this professional group (e.g., the extreme fatigue experienced during this period) prevented it from exhibiting egotistical illusions.

In concluding this chapter, we would like to note that the search for methods to reduce unrealistic optimism is, without a doubt, of great importance in developing recommendations both for therapists conducting individual work with overly optimistic clients and for policy-makers implementing mass media information policies in the face of all sorts of crises. Our review of this subject shows that while psychologists have succeeded in making some empirical findings, further intensive research on this important problem is imperative. This is important because the effects of COVID-19 are multifaceted and long term. It would often seem that if we have “survived” COVID-19, then the worst is behind us. It turns out that there are many more long-term effects, which, from the perspective of this book, broadens the horizon of the sense of struggle to ensure that as many people as possible do not get sick in the future. We will discuss this in the next chapter.