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Abstract

Research conducted at the outset of the pandemic shows that people are vulnerable to unrealistic optimism (UO). However, the Weinstein model suggests that this tendency may not persist as the pandemic progresses. Our research aimed at verifying whether UO persists during the second (Study 1) and the third wave (Study 2) of the pandemic in Poland, whether it concerns the assessment of the chances of COVID-19 infection (Study 1 and Study 2), the chances of severe course of the disease and adverse vaccine reactions (Study 2). We show that UO toward contracting COVID-19 persists throughout the pandemic. However, in situations where people have little influence on the occurrence of the event (chances of severe course of the disease and adverse vaccine reactions), the participants do not show UO. The exceptions are those who have personally known someone who has died from a coronavirus infection. These results are discussed in terms of self-esteem protection and the psychological threat reduction mechanism.

Plain language summary

Recent reports suggest that unrealistic optimism (tendency to assess personal risk as lower than the others) may adversely affect compliance with the restrictions that allow containing the pandemic. Therefore in a series of two studies, we focus on verifying whether the effect of unrealistic optimism concerning one’s chances of contracting coronavirus persists with the development of the pandemic. In addition, in the second study, we extend the research to other health-related aspects relevant to the progressing pandemic. We aim to clarify whether the positive bias is present only when assessing the chance of contracting the disease or is also extended to assessing the possibility of developing a severe course of the disease and the chances of developing a severe post-vaccination reaction. Our results confirm the effect of unrealistic optimism concerning the risk of COVID-19 infection during the second and third waves of coronavirus in Poland. Moreover, we found there was no such effect for assessing the possibility of developing a severe course of the disease and the chances of developing severe post-vaccination reaction, with the interesting exception of those individuals who personally knew someone who died due to coronavirus infection. Therefore our paper expands on prior research concerning the positive bias related to chances of contracting coronavirus, which were conducted at the beginning of the pandemic, and sheds light on aspects influencing the emergence of unrealistic optimism during the COVID-19 pandemic.

Keywords

unrealistic optimism positive bias positive illusions contracting COVID-19 severe consequences of COVID-19

It is common for people to make predictions about their future. While pessimists tend to contemplate the worst-case scenario, optimists believe that good things will happen to them (Dolinski et al., 2020). According to recent meta-analyses, optimism is believed to be associated with benefits of various types, including health and well-being (Nes & Segerstrom, 2006; Rozanski et al., 2019). For example, optimism is associated with a lower risk of cardiovascular events and all-cause mortality (Rozanski et al., 2019). Some authors (Rozanski et al., 2019; Taylor & Brown, 1988) suggest that future studies should be focused on evaluating the benefits of interventions that are aimed at reducing pessimism and promoting optimism. However, not all aspects of optimism are desirable nor beneficial.

Dispositional optimism “is defined as the generalized positive expectancy that one will experience good outcomes” (Radcliffe & Klein, 2002, p. 837) and is mostly responsible for the above-mentioned benefits. Its dark side variant is so-called unrealistic optimism (UO), a cognitive bias that makes people think that negative events are more likely to happen to others, and positive events are more likely to happen to them (Clarke et al., 2000; Weinstein, 1980). Although some researchers (Taylor & Brown, 1988) posit that UO functions as a positive illusion that helps people to cope with potentially threatening experiences by reducing anxiety, others (Burger & Burns, 1988; Clarke et al., 2000; Dillard et al., 2009; McKenna & Albery, 2001) point to the maladaptive aspects of UO. For example, UO may be related to developing some dire conditions such as coronary disease (Radcliffe & Klein, 2002), alcoholism (Dillard et al., 2009), breast cancer in women, and prostate cancer in men (Clarke et al., 2000) as people have the tendency to underestimate own risk of developing serious health problems. UO is also correlated with risky and hazardous behaviors. People who perceive themselves as better drivers than others admit to violating speed limits (McKenna & Albery, 2001), and young women who presume they are less likely than others to get pregnant are also less likely to use effective contraception methods (Burger & Burns, 1988).

Unrealistic Optimism During the COVID-19 Pandemic

The issue of UO has grown in importance in light of recent research on the perceived risk of infection during the COVID-19 pandemic (Asimakopoulou et al., 2020; Dolinski et al., 2020). Dolinski et al. (2020) showed that UO emerged in Poland in the face of the beginning of the COVID-19 pandemic. Similar results were obtained in other European countries (France, Great Britain, Switzerland, and Italy) in February 2020 before the collapse of the healthcare system in Italy (Raude et al., 2020). People who were asked about their chances of getting infected were generally optimistic and assessed the personal risk of contracting coronavirus as lower than others. Recent study conducted by Izydorczak et al. (2022) suggests that UO may persist during pandemic. Interestingly UO appeared not only when assessing individual risk of infection. In a study conducted by Szuster et al. (2022) at various stages of the pandemic respondents had consistently rated the pandemic situation in their country (Poland) as less threatening than in other European countries and the world despite the lack of objective reasons for such assessment.

Further research results also point to the implications of UO for health-related behaviors (Gassen et al., 2021; Salgado & Berntsen, 2021). According to Oljača et al. (2020), UO may indeed influence attitudes towards compliance with restrictions. In a study conducted in Serbia (Oljača et al., 2020), the participants who scored higher on the UOS–NLE subscale (measuring UO towards negative life events) assessed the risk connected with COVID-19 infection as lower and declared lower compliance with the pandemic restrictions. Similarly, Gordeeva et al. (2020) found a positive link between UO and failure to comply with the stay-at-home rule in their study conducted in Russia in March and April 2020. A study by Wielgopolan et al. (2022) found a negative correlation between UO and the declared number of preventive behaviors during the pandemic. It is worth noting that the most common aspect of UO examined during the COVID-19 pandemic was the assessment of the risk of virus infection. Little is known about other aspects of assessing the risk of a pandemic, i.e. assessing the probability of a severe course of the disease or the risk of post-vaccination complications. We will take a closer look at these issues, basing our predictions on the theoretical model of UO by Weinstein (1980).

Predictors of Unrealistic Optimism in the Context of the COVID-19 Pandemic

So far, the most elaborated theoretical model of UO has been formulated by Weinstein (1980) who refers to the five moderators that, may significantly impact UO during the pandemic. These moderators are: (a) the perceived probability of the event, (b) the ease of recalling a stereotypical victim of a given situation, (c) the controllability of the situation, (d) the degree of desirability, and (e) the personal experience. As the pandemic continues to evolve, it remains uncertain how the moderators identified by Weinstein’s (1980) model will impact people’s tendency toward UO. This could either increase or weaken depending on how individuals assess specific factors related to the pandemic, such as the likelihood of contracting the virus, the severity of the illness, or the chances of experiencing adverse reactions after vaccination (see Table 1). In the following paragraphs, we will discuss how these moderators may affect people’s tendency toward UO as the pandemic progresses.

Table 1.

Moderators of UO According to Weinstein’s (1980) Model and Predictions Regarding Three Specific Aspects of UO: COVID-19 Infection, Severe Course of COVID-19, and Adverse Post-Vaccination Reactions in Studies 1 and 2.

		Moderators of UO in the pandemic context	Predictions based on the assumed influence of moderators on various aspects of UO in the context of the development of the COVID-19 pandemic
			Contracting COVID-19		Severe course of COVID-19	Adverse vaccine reactions
Moderators of UO according to the Weinstein’s (1980) model			Study 1	Study 2	Study 2	Study 2
(a)	Perceived probability of the event	The higher perceived probability of the risk should affect one’s higher judgment of the personal risk of the infection relative to the risk of infection of other people in the population (Harris et al., 2008)	−		−	−
(b)	Ease of recalling a stereotypical victim	As the pandemic spreads, the diversity of pandemic victims increases, hence it is increasingly difficult to create a stereotypical image of the person most exposed to contact with the coronavirus (Kahneman & Tversky, 1972)	−		−	−
(c)	Controllability of the situation	People at risk during a pandemic may be vulnerable to the illusion of control through the availability of preventive measures: wearing a mask, keeping their distance, and disinfecting hands. Thus, they could easily create the illusion of greater control of the situation and less chance of contracting the virus. Note that these preventive actions should primarily influence the assessment of the chances of contracting the virus but not necessarily should increase the assessment of UO in other aspects: such as susceptibility to severe COVID-19 or adverse post-vaccination reactions	+		−	−
(d)	Degree of desirability	As the pandemic spreads, people experience more negative effect which leads to defensive strategies for protecting oneself and also results in higher UO. Higher UO helps to change perception of a situation from threatening to less threatening (Harris et al., 2008).	+		+	+
(e)	Personal experience	Personal experience is based on the availability heuristic (Tversky & Kahneman, 1973). Personal experience can change a person’s perception of risk in two possible directions: the shift in the perception of the situation to be more threatening and even leads to the opposite of UO: unrealistic pessimism phenomenon (Dolinski et al., 1987) or at least to lower level of UO (McKenna & Albery, 2001). Alternatively, personal experience may, in some cases, result in enhanced self-protective motivation and underestimation of the personal risk which may as a consequence lead to increase the tendency to UO (Dillard et al., 2009).	+/−		+/−	+/−

Note. The symbols “+” and “−” in Table 1 indicate whether moderators increase or decrease the tendency to UO, “+/−” indicates ambiguous premises.

At least two moderators should inhibit the tendency to the UO among people at pandemic risk: (a) the perceived probability of the event and (b) the ease of recalling a stereotypical victim of a given situation. The first one is inherently connected with the pandemic’s growth and increasing numbers of people contracting coronavirus. According to the results of a meta-analysis conducted by Harris et al. (2008), higher perceived frequency (i.e., probability) in the general population should affect the personal judgment of the risk but not necessarily others’ judgement. Thus, when the event is more frequent, the UO may be weakened by a higher own risk rating.

The second predictor that works in a similar direction means that the assumption regarding stereotype salience is based on the representativeness heuristic (Kahneman & Tversky, 1972). Weinstein (1980) assumes that the harder it is to imagine a typical victim of a specific event, the weaker UO will be. Although there were mixed results across the studies the Harris et al. (2008) meta-analysis supports salience hypothesis. As the pandemic spreads, individuals should be more aware that the severe consequences of COVID-19 affect not only the elderly with significant health problems but also younger, healthy people. With the increase in diversity and the number of victims of the pandemic, it would be more difficult to create a stereotypical image of the person most exposed to coronavirus, which should reduce the tendency to create UO. As the pandemic evolves and the number of cases increases, both (a) and (b) are expected to equally hinder the tendency towards UO across all three assessment aspects: the likelihood of infection, the severity of the illness, and the risk of the adverse vaccine reactions. However, there are two other predictors that in our opinion would work in opposite directions to enhance UO: (c) controllability of the situation, (d) the degree of desirability, and (e) the personal experience which the last one can work both ways. Controllability of the situation refers to a human’s sense that a situation’s outcome is dependent on their own actions. Therefore, people tend to overestimate their chances in positive events and underestimate their risks in negative events. Previous research on UO strongly supports this assumption (Harris et al., 2008; C. T. F. Klein & Helweg-Larsen, 2002; W. M. Klein & Kunda, 1993). In our opinion, people at risk during a pandemic may be vulnerable to the illusion of control through the availability of preventive measures: wearing a mask, keeping their distance, disinfecting hands. Thus, they could create the illusion of greater control of the situation and less chance of contracting the virus. In our opinion, a sense of control could foster UO when asking individuals about the chances of contracting coronavirus. In this aspect, people seem more susceptible to the illusion of their own preventive actions but not necessarily to other aspects such as vulnerability to a severe course of COVID-19 or adverse vaccine reactions.

The degree of desirability refers to the severity of the consequences. It is assumed that the more desirable a situation’s outcome, the greater UO. However, negative events induce a more negative effect which leads to defensive strategies for protecting oneself and also results in higher UO. People desire positive outcomes, and when they are faced with the risk of losing their health or even their life, they may be prone to reducing anxiety and protecting their self-esteem. One such strategy may be by creating positive illusions, which allows individuals to change their perception of a situation from threatening to less threatening. To date, there are mixed findings in the literature related to this aspect of UO (Harris et al., 2008).

The last moderator mentioned by Weinstein (1980) is the assumption on personal experience which is based on the availability heuristic (Tversky & Kahneman, 1973). Previous experience with an event increases the belief in its reoccurrence. Personal experience may, in a similar vein, change the personal perception of the risk faced by an individual. However, two alternatives of these changes in the perception of the risk may be taken into account according to the existing literature (McKenna & Albery, 2001). The first one is the shift in the perception of the situation to be more threatening and even leads to the opposite of UO: unrealistic pessimism phenomenon (Dolinski et al., 1987) or at least to lower level of UO (McKenna & Albery, 2001). Alternatively, personal experience may, in some cases, result in enhanced self-protective motivation and may lead to an underestimation of the personal risk in relation to others which may as a consequence increase the tendency to UO (Dillard et al., 2009).

Aim of the Studies

We decided to explore the susceptibility to UO during the second (Study 1) and the third wave of the pandemic in Poland (Study 2), when the number of infections increased dramatically. If the tendency to UO persisted in the further stages of the pandemic, we expected to replicate the tendency to underestimate one’s own chance of contracting coronavirus despite the growth in the number of infections in the population both during the second (Study 1) and third (Study 2) waves of the pandemic in Poland. In addition, in Study 2, we decided to broaden the spectrum of assessing the tendency to UO with two issues that seem to be of particular importance as the pandemic develops: the severity of a potential COVID-19 infection and adverse vaccine reactions. To our best knowledge, there is scarce evidence whether UO is limited only to the prediction of the chance of contracting COVID-19 or is related to other important health-related topics. UO toward getting infected with the coronavirus does not need to imply increased subjective assessment of risk of serious complications, permanent health impairment, or death. On the contrary, since biased individuals perceive themselves as resistant in some way, it can be assumed that UO may protect them from deliberating the ramifications of contracting COVID-19. Thus, the presence of the UO towards contracting COVID-19 does not necessarily mean that people are positively biased towards assessment of the chances of a severe course of the disease or adverse vaccine reactions. As we analyzed the effect of different moderators during the ongoing pandemic, following the Weinstein model, we anticipate that individuals may be more inclined towards UO when evaluating the likelihood of contracting the virus. However, we also predict that they may be less likely to exhibit UO towards the severity of COVID-19 and negative post-vaccine reactions.

Therefore, we hypothesized in Study 1 and Study 2 that:

Participants will demonstrate unrealistic optimism towards chances of contracting coronavirus. In other words, they will underestimate own risk of getting infected in comparison to others.

Additionally in Study 2 we formulated further hypotheses:

Participants will not show unrealistic optimism towards risk of severe course of coronavirus infection. They will assess the personal risk of developing severe course of coronavirus infection similar to the others.

Participants will not show unrealistic optimism towards risk of adverse vaccine reaction. They will assess the personal risk of adverse vaccine reaction similar to the others.

Both studies were approved by Research Ethics Commission.

Study 1

We decided to conduct our first study in November 2020, during the spike of the very severe second wave of the pandemic in Poland. In 2020, 70,000 more people died in Poland than in previous years, which is nearly 20% more than in 2019 (and at the same time is the highest rate of death since World War II) (Pawłowska, 2021). In November 2020 alone, 605,885 coronavirus cases were confirmed in Poland, and 11,494 people died as a result of the infection (Polish Ministry of Health, 2020). We expect to replicate the effect obtained by Dolinski et al. (2020) who conducted their study at the beginning of the pandemic in Poland when people had not yet faced the widespread traumatic experiences of the deaths of their relatives and friends due to coronavirus.

Based on the research by Dolinski et al. (2020), to determine the sample size, we expected Cohen’s d effect sizes to be from d = 0.238 to d = 0.491. For the calculations, we adopted the average value of d = 0.365; expected power of .90 and alpha = .05. The analysis of the power in G*Power (version 3.1.9.7; Faul et al., 2009) for the difference between the two dependent means and the two-tailed t-test, showed that the required power is achieved by a sample of 81 individuals. In order to meet these assumptions, we determined a sample size of at least 81 people in each of the studies.

We report all manipulations, measures, and exclusions in these studies (see supplementary materials for more details). No studies in this manuscript were preregistered. All statistical procedures were performed in IBM SPSS v.26.0 (IBM Corp., 2019)

Method

This study was part of a larger research plan concerning decision-making about resource allocation during the coronavirus pandemic. In this report, we focus on the elements of the procedure related to the measurement of UO (a full description of the procedure and other measures used in the study can be found in the supplementary materials). Detailed information on the materials and instructions for Study 1 can be found in the repository: https://zenodo.org/record/5984642.

Participants

The first study involved 111 participants (90 female and 21 male) aged 18 to 42 years (M = 22.23, SD = 3.53). All of the participants were students of the Jagiellonian University in Kraków. The participants were assigned to the study conditions on the basis of quasi-randomization. At the very beginning of the study, they were asked about their day of birth. The numbers between 1 and 31 were divided into four intervals which were used to redirect the participants to two different conditions (control and experimental) based on their answers.

Materials

Pandemic and Neutral Context

The participants were assigned to one of two conditions related to one of two contexts—pandemic versus non-pandemic—as a part of the larger research project mentioned earlier. Four separate photos were used (i.e., two for the pandemic context and two for non-pandemic). More information about the chosen photos can be found in the supplementary materials. The context was manipulated by including either neutral images or images related the pandemic. Their context was assessed in a preliminary study. We had no theoretical predictions about the impact of manipulating the context (i.e., pandemic vs. neutral), as the study was a part of a larger research project and context manipulation was only indirectly related to this particular study. The images were not part of the hypothesis, of studies described in this report. However, due to the fact that context can significantly change the perception of the social situation, especially in people who are exposed to the effects of a pandemic, we decided to take it into account in our preliminary analyses.

Unrealistic Optimism Measurement

Our main dependent variable was the measure of how the participants were unrealistically optimistic about the possibility of contracting coronavirus. To this end, we asked them two questions:

How would you rate your chances of contracting coronavirus?

How would you rate the chances that someone else like you will contract coronavirus?

The participants answered both questions by estimating the chance of becoming infected as a percentage (from 0 to 100). It is suggested by Harris et al. (2008) that such an indirect method of assessing UO (by asking two separate questions) is more beneficial and informative than the classical, direct way introduced by Weinstein (1980) which consists of only one item where participants are asked to compare themselves to an average other. Using an indirect method of measuring UO provides a better understanding of how moderators affect risk assessment and whether their influence relates to assessing one’s own risk or that of others (Helweg-Larsen & Shepperd, 2001).

Procedure

The first study was conducted in November 2020 at the peak of the second wave of the coronavirus in Poland. Due to pandemic restrictions, the study was conducted online. Participants received an email invitation to take part in the study. If they clicked the link received in the email, they were redirected to an online survey. Firstly, they were informed about data privacy and gave active, informed consent. Afterwards they were randomly assigned to control condition—in which they were showed neutral images unrelated to disease or death, and experimental condition—in which they were showed images related to death or disease (see supplementary materials). Then, after assignment to research conditions, they were asked two questions regarding the perceived chance of contracting coronavirus—by themselves and someone similar to them. Finally, the participants filled in demographic data and were thanked for participating in the study. Detailed information about all the additional materials and scales used in the study can be found in the supplementary materials.

Results

Due to the fact that being infected with COVID-19 at some point could influence the assessment of the risk of contracting coronavirus, participants who had been diagnosed with COVID-19 (n = 4) and participants who were in quarantine (n = 2) were excluded from the analysis. This exclusion has no effect on results significance. The effect of UO is observed also when we included these participants (t (110) = −5.29; p < .001). Preliminary analysis (general linear model with the assessment of the chance of infection as a within-subject factor and sex, age, and condition as between-subject factors) showed that the assessment of the chance of infection was not influenced by the experimental condition (see pandemic vs. neutral photos; F(1, 79) = 0.07, p = .791. We control also demographical variables in a general linear model. There were also no differences related to the age (F(12, 107) = 1.53, p = .130) and sex (F(1, 79) = 0.03, p = .869) of the participants. Therefore, in further analysis, all results were considered jointly, regardless of the manipulation of the pandemic versus the non-pandemic context, age, and gender of the participants. A paired t-test showed that the estimate of contracting coronavirus oneself was significantly different from the estimate of it being contracted by someone else. The participants assessed their chance (%) of becoming infected (M = 52.97, SD = 24.24) as lower than the chance of someone else becoming infected (M = 61.18, SD = 23.26). This difference is statistically significant and effect size is of moderate strength (t (103) = −4.69; p < .001, Cohen’s d = −0.34).

Discussion

Our study initially confirmed—in line with the prediction derived from Weinstein’s model—that there was a continuing tendency to underestimate the chances of contracting COVID-19 during an exacerbating pandemic in Poland and corresponds with other reports confirming a tendency to UO in the context of the assessment of life- or health-threatening events (Clarke et al., 2000; Dillard et al., 2009; Radcliffe & Klein, 2002).

Study 2

In our second study, we decided to extend the scope of UO exploration to more specific aspects of pandemic risk. During the development of a pandemic, two aspects seem to be particularly important, and little known from the point of view of UO: estimating the chances of serious complications as a consequence of a possible COVID-19 infection, and the perceived risk of developing adverse vaccine reactions. There is strong evidence in the literature on UO suggesting that this effect occurs rather in the case of events that we assume we can control to some extent (Dolinski et al., 2020; Weinstein, 1980). According to Weinstein’s (1980) moderator (c) the controllability of the situation (see Table 1), in the case of events that people feel they can control it is easier for them to visualize their own behavior aimed at reducing the risk. Thus, they overestimate their influence on the situation and are more susceptible to UO. People may, to some extent, try to minimize the risk of contracting COVID-19 through their behavior, thus, the possibility of becoming infected seems to be dependent on a person’s actions and under their control. However, people may believe that they have no control over whether they will develop serious complications as a result of the infection, which may result in death or a serious threat to life. Thus, we hypothesize that although people will underestimate the chances of getting ill, at the same time they will not underestimate the chances of developing a serious course of the disease as a consequence of a possible COVID-19 infection. Indeed in a study by Asimakopoulou et al. (2020), participants showed lower UO when asked about the risk of hospitalization, being taken into the intensive care unit, and being ventilated due to COVID-19 (less manageable situations) than when asked about the risk of contracting coronavirus or infecting someone else (more manageable situations). Therefore, we assume that in the case of the risk of a severe course of COVID-19, the effect of UO would be weaker.

We decided to include one more variable which was not included in previous studies as they were conducted during a different stage of the pandemic. Our second study was conducted in February 2021, after the second coronavirus wave in Poland, which turned out to be much more severe than the first one. Between September and December 2020, 1,205,878 new cases of coronavirus infections were confirmed and 25,656 people died due to a COVID-19 infection. At the peak of the second wave, COVID-19 patients occupied 20,000 hospital beds (Polish Ministry of Health, 2020).

We assumed that, at this point, most of the participants will already have had their own experiences related to coronavirus, and in particular, they might personally know someone for whom contracting coronavirus had serious consequences, thus we decided to include (e) personal experience (see Tabel 1) as another moderator of UO. We decided to verify if the personal experience of knowing someone who had developed a severe illness due to COVID-19 or died from it would affect UO of the participants.

In the literature on UO, we found mixed results related to the influence of personal experience (Dillard et al., 2009; McKenna & Albery, 2001). In a study by McKenna and Albery (2001), participants who were involved in a car accident showed lower UO concerning their driving skills than other participants, but only if they were hospitalized as a result of the accident. In contrast, in a longitudinal study related to alcohol abuse (Dillard et al., 2009), people who experienced negative consequences related to alcohol consumption at subsequent stages of the study still rated their own risk of developing serious problems related to alcohol abuse as lower than others. Considering the mixed results on the role of personal experience in literature, we had no clear prediction about its moderating role. Finally, since the date of the study coincided with the commencement of the vaccination program in Poland, we were also interested in the assessment of the chances of adverse vaccination reactions—self versus others. We assumed that as the chances of adverse vaccination reactions are beyond one’s control, we will not observe UO in this case.

Method

Participants

The second study involved 84 participants (57 female, 26 male, and 1 nonbinary), aged from 19 to 65 (M = 35.42, SD = 9.07). Out of 84 participants, 78 knew someone diagnosed with COVID-19, 47 knew someone who manifested severe symptoms of COVID-19, and 30 participants knew someone who died due to COVID-19.

Materials

Pandemic and Neutral Context

Similarly, as in Study 1, we used the manipulation of the context of the UO. Before the assessment, half of the participants were presented with pandemic-associated, death-related pictures whereas the other half were presented with—the same as in Study 1—neutral images. The materials were chosen based on a separate pilot study. The stimuli used in the second study can be found in the supplementary materials. Detailed information on the materials and instructions for study 2 can be found in the repository: https://zenodo.org/record/5984642.

Unrealistic Optimism Measurement

As we wanted to verify whether UO would also apply to other aspects related to the coronavirus pandemic (apart from the assessment of the chances of being infected), we additionally asked the participants the following questions:

(1) How would you rate your chances of a severe course of the disease if you contract coronavirus?

(2) How would you rate the chances of someone else becoming severely ill if they contract coronavirus?

These questions related to the possible UO about a severe course of coronavirus disease. As the coronavirus vaccination program was already underway during the second study, we also wanted to check if there were some differences in the assessment of the possible side effects of vaccination:

(1) How would you rate your chances of developing severe side effects after a coronavirus vaccination?

(2) How would you rate the chances of someone else developing severe side effects after a coronavirus vaccination?

Personal Experience of COVID-19

The second study was conducted on the verge of the third wave of the coronavirus pandemic in Poland. Thus, we assumed that the participants may have had some personal experience of COVID-19 at this point, which might have influenced the way they assessed their chances of getting infected and developing severe symptoms of COVID-19. At the end of the study, participants reported if they personally knew someone diagnosed with COVID-19, if they personally knew someone who developed severe symptoms of COVID-19, and if they personally knew someone who died due to a COVID-19 infection.

Procedure

Again, due to the pandemic restrictions, the study was conducted online. Participants received an email invitation to take part in the study. If they clicked on the link received in the email, they were redirected to the online survey. Firstly, they were informed about data privacy and gave active, informed consent. Similar to the first study, participants were assigned to the research condition quasi-randomly, based on their day of birth. Depending on the condition, participants saw either neutral photos (control conditions) or photos related to the coronavirus pandemic (experimental conditions).

In the next step, they were asked to estimate their perceived chances of being infected with COVID-19, developing severe symptoms of COVID-19, and suffering severe side effects of vaccination against COVID-19. To assess the tendency to UO, they also answered the same questions regarding their co-workers/other students. Finally, the participants filled in demographic data and information about their personal experience of COVID-19. More detailed information about the other measures used in the study can be found in the supplementary materials.

Results

As in the first study, we excluded participants who declared that they had tested positive for the presence of coronavirus (n = 11) and participants who were in quarantine (n = 2) as their answers may have biased the results. Since, during the second study, the COVID-19 vaccination campaign was already underway in Poland, we also excluded participants who had received at least one dose (n = 2). This exclusion has no effect on results significance. The effect of UO is observed also when we included these participants (t (110) = −5.29; p < .001). First, in the preliminary analysis, we checked if there were any differences in UO measures due to different experimental conditions (pandemic vs. neutral photos). As we found none (F(1,15) = 0.13, p = .726), we decided to analyze all the data together. There were also no differences concerning UO due to the gender (F(1,15) = 0.13, p = .865) and age (F(32,15) = 0.71, p = .795) of the participants. The effect of UO related to the chances of contracting coronavirus has been successfully replicated (t(70) = −5.69, p < .001, Cohen’s d = −0.37). The respondents assessed their chances of becoming infected lower (M = 42.55, SD = 24.67) than the chances of other people (M = 51.03, SD = 22.98).

In the next step, we conducted a moderation analysis to check whether personal experience with COVID-19 changes the unrealistic optimism. There was no effect of UO related to a severe course of COVID-19 infection (see Table 2). However, when assessing the chances of a severe course of the disease, personal experience related to coronavirus turned out to be an important moderator. There was an interaction effect between UO and personal acquaintance with someone who died from a COVID-19 infection (F(1,68) = 6.50, p = .013, Cohen’s d = 0.58). Participants who knew someone who died as a result of COVID-19 infection estimated their chances of a severe course of coronavirus infection significantly lower (M = 26.29, SD = 19.74) than the chances of substantial side effects of COVID-19 infection for other people (M = 36.41, SD = 19.27; p = .028). This effect did not appear in the case of participants who did not personally know any victims of COVID-19 infection (M_self = 33.65 SD_self = 26.47 comparing to M_other = 29.61 SD_other = 22.47; p = .218). This dependency is shown in Figure 1.

Table 2.

Summary of Self and Others’ Chances Assessments from the Two Studies.

		Self		Others		Paired-samples t-test			95% CI
How do you assess the chances of… related to COVID-19		M	SD	M	SD	t	df	p	Lower	Upper
Study 1	Contracting	52.97	24.24	61.18	23.26	4.69	103	<.001	−11.68	−4.74
Study 2	Contracting	42.55	24.67	51.03	22.98	5.69	70	<.001	−11.45	−5.51
	Serious complications	31.13	24.48	31.94	21.53	0.297	69	.768	−6.28	4.65
	Developing adverse vaccine reactions	27.06	24.43	28.33	22.14	0.912	69	.365	−4.05	1.51

Figure 1.

The interactional influence of knowing someone who died due to COVID-19 on chance assessment.

Other experiences with the coronavirus pandemic (i.e., knowing people who have become infected or who have been severely ill) did not contribute to the effect of UO concerning a severe course of COVID-19 disease. There was no interactional effect in the case of a personal acquaintance with someone who has been severely ill (F(1,68) = 2.03, p = .158, Cohen’s d = 0.31). Additionally, we decided not to perform analysis on a personal acquaintance with someone who has been infected as a between-subject factor since 78 of 84 participants knew someone who has been ill.

There was also no effect of UO concerning potential adverse reactions of the COVID-19 vaccination (see Table 2). Overall, respondents rated the chances of experiencing vaccination side effects as low for themselves (M = 27.06; SD = 24.43) as for others (M = 28.33, SD = 22.14). Any type of personal experiences with the coronavirus pandemic were of no importance in this case (knowing someone who has been severely ill: F(1,68) = 0.32, p = .573; Cohen’s d = 0.14; knowing someone who died from COVID-19 infection: F(1,68) = 1.97, p = .166; Cohen’s d = 0.33).

Discussion

In study 2, we confirmed that there is a continuous tendency to underestimate the chances of contracting COVID-19 not only during the second wave of the pandemic in Poland, as suggested by study 1, but also during the peak of infection for the whole pandemic outbreak (i.e., the third wave). We were particularly interested in whether the accompanying circumstances (knowledge of infected people, acquaintance with a severe course, and people who died from COVID) could moderate this tendency. The UO effect has only been documented among those who were aware of the lethal consequences of COVID-19. In the context of the above results, the lack of impact of the pandemic context manipulation seems understandable: awareness of the existence of the pandemic itself may not be a sufficient condition for the effects of UO to occur. In the general discussion, we shed more light on the potential psychological mechanism of that phenomenon in the context of Weinstein’s (1980) theory.

General Discussion

The evidence presented in our research supports the assumption that UO is maintained as the COVID-19 pandemic progresses and is not limited to the initial stages of a pandemic outbreak. Bottemanne et al. (2020) suggest that UO may diminish as coronavirus spreads around the world. They argue that in face of an inevitable threat people tend to use unfavorable information more likely to update their beliefs. At first, the coronavirus pandemic was rather distant and novel but with more and more cases the risk of infection was getting higher and, as a result, this might have updated people’s beliefs about their personal chances of getting ill and weakened UO. The premise of the research by Bottemanne et al. (2020) is consistent with two assumptions of Weinstein (1980) model: (a) the perceived probability of the event and (b) ease of recalling a stereotypical victim. The first assumption is that the growing number of COVID-19 cases may subjectively change the assessment of the probability of one’s own infection, increasing its chance relatively to the assessment of the chances of infecting other people in the population. In March 2020, in Poland, there were a dozen new COVID-19 cases a day, while in the second half of the year, the numbers were oscillating around several thousand cases a day and more. As the incidence of the disease increases with the duration of the pandemic, individuals are supposed to make more realistic estimations of the chances of their own illness and should make those assessments similar to others, thus one would expect that the tendency to UO should decrease. If a massive increase in the number of infected people were crucial for reduction of the UO phenomenon, the tendency towards this cognitive bias should weaken as the pandemic progresses. However, the above argumentation assumes that people rationally evaluate the chances of positive and negative events in their lives, which, as we know from the many studies in the field about decision making and judgement, is no longer true (Thaler, 1980; Tversky & Kahneman, 1973). A similar direction of the relationship would result from the ease of imagining a stereotypical COVID-19 victim: along with the diversity of the image of pandemic victims, it is difficult to create a stereotyped image of an infected person. At the peak of the pandemic, the social cross-section of sick people was not limited to one specific group: people of all ages and general health conditions were sick. Likewise, the assumption that a growing number of infections should change the stereotypical image of a typical victim (Weinstein, 1980), which in turn should inhibit the tendency to UO also turned out not to be valid in our studies.

In contrast to the assumptions of Bottemanne et al. (2020), our data, collected in two studies conducted during the second and third waves of the pandemic in Poland, confirm the existence of UO regarding the assessment of the chances of contracting coronavirus. Moreover, as the pandemic progressed, not only did the UO not diminish, but the strength of the effect appears to be stable (i.e., Cohen’s d in Study 1 vs. Study 2 is 0.34 and 0.37, respectively). In both studies, the pandemic and non-pandemic contexts did not affect the assessment of any aspects of pandemic risk. This may be an argument for the high availability of information about the pandemic and relative insensitivity to additional information that would change the perception of reality during the second and third waves of the pandemic in Poland. Interestingly, in the second study, people assessed both their own likelihood of becoming infected and of others as lower than in the first study (i.e., 52.97 vs. 42.10 for one’s own assessment and 61.18 vs. 51.00 for others). However, it is difficult to draw conclusions about the differences in the estimates of absolute values on that basis, because the results come from different groups of respondents at different stages of the pandemic’s development. We do not know whether this result indicates the opposite trend to that observed in the studies by Dolinski et al. (2020) or whether it represents differences in the perceived probability of infection of various groups of people.

While people in our research showed UO about coronavirus infection, the attempt to explain this phenomenon should focus on the role of moderators that, from the theoretical point of view, could contribute to their maintenance. There are at least two reasons why individuals may be motivated to maintain UO. One is the motivation to control an unpredictable situation (Makridakis & Moleskis, 2015). In line with Weinstein’s (1980) model individuals tend to gain control in an unpredictable situation and are vulnerable to illusion of control (moderator c controllability of the situation) and the tendency to redefining threatening situations as safer (moderator d degree of desirability).

The outbreak of a pandemic is undoubtedly a circumstance that increases the unpredictability and uncertainty of actions and raises many risks related to the consequences of the decisions that individuals are making. There is a growing body of literature suggesting that the experience of uncontrollability increases uncertainty (Kofta & Sedek, 1999) and leads to the experience of lack of control which is challenging for various aspects of human functioning (Kofta & Sędek, 1989). In the context of our research, the most interesting seems the self-protection motivation (Agostinelli et al., 1992; Alicke & Sedikides, 2009) and regaining control when people are facing unpredictable situations (Greenaway et al., 2017). UO may be a form of self-protection and could serve as promoting positivity in one’s self-views. Following this argument, it could be expected that the growing number of infections will not only reduce UO but would foster uncertainty about the future and enhance motivation to regain control of the situation, especially in terms of those aspects that may be perceived as controllable. We expected, according to Weinstein’s (1980) model, that UO will be especially strong in the case of the relatively controllable aspect of the pandemic situation (the chances of contracting of COVID-19) but not for those aspects that are beyond control (a severe course of COVID-19, adverse vaccine reactions). The results of Study 2 are consistent with the above assumptions and other studies suggesting the existence of UO for manageable rather than unmanageable situations (Asimakopoulou et al., 2020). We predicted that in the case of the chances of infection, such an illusion of control is more likely to occur than for other aspects of assessment. Hand disinfection, self-isolation, and wearing a mask are actions that an individual can take at any time because they depend solely on their will. There is, however, an interesting contradiction in this aspect. Paradoxically, research shows that unrealistically optimistic people less often follow the rules and respect limitations. In fact, they tend to ignore protective measures and thus contribute to the spread of the virus. UO can therefore be a knife that cuts both sides: from an individual’s perspective, the belief that preventive measures are readily available strengthens the illusion of control, but it actually leads to the ignoring of limitations, which not only does not reduce the risk but also seriously increases it.

We did not expect to report UO in regard to a severe course of COVID-19. The results obtained are consistent with our assumptions that an individual will not be prone to UO when assessing a serious course of the disease. However, there is an interesting exception regarding people who knew someone who died from a COVID-19 infection. The results obtained in Study 2 show that people who experienced the death of a person they knew are unrealistically optimistic in regard to the assessment their own chances of a severe course of COVID-19. Knowing a person who died of COVID-19 may indicate the role of the fifth moderator in Weinstein model: personal experience. The existing literature does not allow for conclusive assumptions about the influence of personal experience in the development of UO. Our findings also do not contribute to clarifying this doubt. Based on the results obtained in Study 2, it cannot be clearly stated that personal experience favors UO towards chances of severe course of coronavirus. We controlled for personal experience at three different levels: knowing someone who contracted COVID-19, knowing someone who developed severe symptoms of COVID-19, and finally knowing someone who died as a result of COVID-19. Only the third type of personal experience predicted UO toward severe course of COVID-19. This result suggests that it is the specific type of personal experience that matters, rather than any personal experience related to the threatening situation. There is a considerable number of empirical findings suggesting the consequences of mortality salience evoke a psychological defense mechanism to protect self-esteem and reduce the psychological threat and anxiety (Greenberg et al., 1986; Pyszczynski et al., 2015). During the third wave of the pandemic, almost all respondents knew someone who had already been infected with coronavirus and our results suggest that those kinds of experiences are not sufficient to enhance UO towards a severe course of the disease. Unfortunately, our study does not allow us to make a conclusion about the role of the specificity of these kinds of personal experiences. More research is needed to verify the role of assessing the consequences of infecting others in creating UO about the seriousness of the disease. It cannot be ruled out that UO may be a specific consequence of the awareness of one’s own mortality, which has not been verified in the empirical research so far.

Limitations

One constraint of the study is that the sample used is not representative of the entire population, which limits our ability to compare our findings with previous measurements taken during the early stages of the pandemic in Poland (Dolinski et al., 2020). One of the main limitations of our research is its exploratory nature related to the pandemic situation in which the research took place. Our conclusions related to the role of moderators included in Winstein’s model were necessarily more conceptual than empirical. It is impossible to determine the relative strength of individual moderators, to what extent their mutual influence balances each other, and which of them have a stronger and weaker effect. Our inferences were therefore indirect and we were unable to precisely measure and control the impact of individual moderators. Thus, we are aware that the inference about the relationship of risk assessment with the moderating role identified by Weinstein factors are highly hypothetical. Further efforts should be made to better demonstrate the direct relationship of moderators in the Weinstein (1980) model with the development of UO regarding the assessment of various aspects of pandemic risk (contracting the virus, risk of a severe course, risk of unexpected vaccine reactions) and the role of mortality salience in upholding UO. Although the current studies concerned the specific situation of the COVID-19 pandemic, we believe that the examined aspects of assessing unrealistic optimism are universal and apply to many other similar situations of pandemic threats, which will probably repeat in the future.

Conclusions and Further Research Directions

We can summarize the most important conclusions of our research, despite its limitations. In two studies we confirmed the constant tendency to unrealistic optimism toward the chances of contracting COVID-19. However, the vulnerability towards UO does not apply to the assessment of the risk of the severe course of COVID-19 nor adverse post-vaccine reactions. To our best knowledge, most research on UO during the COVID-19 pandemic was focused on the aspect of contracting COVID-19. Examining whether there is a tendency toward unrealistic optimism on various aspects of pandemic risk is a valuable opportunity to test some theoretical predictions. We used Weinstein’s model to make detailed predictions about the five identified moderators of UO and their significance for the aspects we examined. Two of them seem to be of particular importance from the point of view of the analyzed situation of the COVID-19 pandemic: the pursuit of controllability of the situation and the personal experience of knowing someone who died as a result of COVID-19. Probably, the unrealistic assessment of the chances of getting infected with the virus despite the growing number of COVID-19 cases supports the hypothetical ease of use of the illusion of control that can be increased by the relative availability of preventive means: wearing a mask, keeping distance, and disinfecting hands. The observed relationship between the specificity of the personal experience related to death and its impact on the development of a positive illusion suggests that not every personal experience increases the chance of unrealistic optimism. The conducted research does not make it possible to determine what specific characteristics of the situation contribute to people’s feeling of the illusion of control and how this illusion may influence the development of unrealistic optimism. For this purpose, more precise experimental research is needed on the relationship between the illusion of control and the phenomenon of unrealistic optimism. As far as we know, little is known about the meaning of mortality experiences and positive illusions. One of the possible directions of research in this area is the use of mortality salience manipulation and verification whether it leads to a greater tendency to unrealistic assessment of chances in various aspects of human functioning.

Supplemental Material

sj-docx-1-sgo-10.1177_21582440241290926 – Supplemental material for Unrealistic Optimism in the Eye of the Storm: Positive Bias Towards the Consequences of COVID-19 During the Second and Third Waves of the Pandemic

Supplemental material, sj-docx-1-sgo-10.1177_21582440241290926 for Unrealistic Optimism in the Eye of the Storm: Positive Bias Towards the Consequences of COVID-19 During the Second and Third Waves of the Pandemic by Ada Maksim, Sławomir Śpiewak, Natalia Lipp, Natalia Dużmańska-Misiarczyk, Grzegorz Gustaw, Krzysztof Rębilas and Paweł Strojny in SAGE Open

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The proofreading of the publication was funded by the Priority Research Area Society of the Future under the program “Excellence Initiative—Research University” at the Jagiellonian University in Krakow.

ORCID iDs

Ada Maksim

Sławomir Śpiewak

Paweł Strojny

Data Availability Statement

Dataset for study 1 and 2 can be found in the repository: .

Supplemental Material

Supplemental material for this article is available online.

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