The new SARS-Cov-2 coronavirus disease (COVID-19) has become the most serious global pandemic in modern times. It has called the attention of our communities to infectious diseases that had seemed controlled in the eyes of the public and led governments to take drastic measures. Among these were the promotion of preventive measures (e.g., hand-washing, social distancing) that require behavior change in daily habits. The need for such widespread behavior changes calls for the understanding of its determinants. This is important, as the level of adherence of the community to these measures should impact the course (e.g., new waves of cases) and severity of the pandemic.

The way people perceive illness is one of the relevant factors to understand the adoption of preventive and health management behaviors. Illness perceptions are cognitive representations of disease present in both patients and healthy individuals. The most widely researched theoretical formulation of these representations is based on Leventhal and colleagues' model of self-regulation (Diefenbach and Leventhal, 1996; Leventhal et al., 2003, 2016) - see Figure 1. They proposed that illness perceptions are grouped in different but interrelated components. These components have been classified as cognitive or emotional illness representations (Broadbent et al., 2006). The cognitive representations include perceptions about (a) the consequences of a particular illness, (b) the expected timeline or duration of the illness, (c) personal control of aspects of the disease, (d) the extent of usefulness of treatment in controlling or managing the illness, (e) the perception of the experience of an illness, and (f) its symptoms and understanding or being knowledgeable of the disease. The emotional representations focus on the following: (g) concern or worry about the disease or its consequences, and (h) the emotional response (e.g., fear, anger, and distress) associated with the illness. Illness perceptions are generated by situational stimuli such as symptoms or health information and are assumed to influence coping (Weinman et al., 1996; Broadbent et al., 2006).

With research spanning over 40 years, hundreds of studies and dozens of meta-analyses have been conducted on illness perceptions. Most studies on illness perceptions have been conducted with clinical samples, and consistent associations have been found with help-seeking behaviors and service usage (Baines and Wittkowski, 2013), fear of recurrence of the disease (e.g., breast cancer), quality of life, mood (Foxwell et al., 2013; Kaptein et al., 2015; Rijken et al., 2020), and stress (Karademas et al., 2009; Westbrook et al., 2016; Zhang et al., 2016).

Some conflicting results have emerged concerning the predictive value of illness perceptions to treatment adherence and illness management behaviors, with some authors finding little to no relationship (Aujla et al., 2016). Given the theoretical link to coping and behavior, these conflicting results pose a challenge to the self-regulation model. In a meta-analysis of 31 studies with different physical health conditions Dempster et al. (2015) found a strong relationship between illness perceptions and emotional health outcomes (e.g., depression and anxiety), but little evidence for the role of coping as a mediator between illness perceptions and outcomes. Again, this reinforces the need for further research given the expected relationship between illness perceptions and coping in self-regulation of health outcomes. Another venue for studying the impact of illness perceptions on coping and behavior is to study interventions aiming at correcting misconceptions. The few studied interventions, aimed at addressing illness misconceptions, have been found to have an impact in health outcomes including behavioral change (Figueiras et al., 2017).

The study of illness perceptions in healthy individuals has examined their role in prevention and early detection of particular illnesses. For example, in breast cancer risk, illness perceptions are a significant predictor of screening (Marmarà et al., 2017) and increased distress among women who are at higher risk for developing this illness (Rees et al., 2004). One important question is whether illness perceptions have the same meanings for healthy individuals. Figueiras and Alves (2007) compared the perceptions of healthy individuals using the IPQ-R for AIDS, tuberculosis, and skin cancer. They found the same factorial structure as in clinical samples, and the illness perceptions accounted for significant variance in attitudes and intentions toward the adoption of preventive behaviors. This supports the similarity of illness perceptions in healthy and sick individuals.

Overall the literature on the impacts of illness perceptions suggests that they are relevant for preventing and adjusting to illness (Figueiras and Neto, 2019). Two other aspects of the self-regulation model (Diefenbach and Leventhal, 1996) need to be considered: cultural differences and illness perceptions development. First, since particular elements differ across countries (e.g., culture, available treatments, and health information availability), national differences in illness perceptions of particular diseases are expected. The few existing studies present a mixed picture, with either significant differences (Bean et al., 2007) or minor differences (Kaptein et al., 2013) across cultural contexts. Secondly, illness perceptions are not expected to be static. This is anticipated from the original model (Leventhal et al., 2003) that assumes illness perceptions are informed by the appraisal of the consequences of the patient coping strategies (See Figure 1). This feedback cycle (i.e., the effect of the consequences of personal behavior in illness perceptions) suggests that illness perception formation is an iterative process. This process is also influenced by factors, such as the response to treatment, illness progression, and evolution on the shared representations of a given illness. Research that supports this assumption comes from the evolution of illness perceptions with the course of the illness. Significant trends have been found for particular illness perceptions during the course of diabetes (Fortenberry et al., 2014), cancer (De Castro et al., 2012), and patients undertaking hemodialysis (Tasmoc et al., 2013).

With the emergence of COVID-19, two public health goals become particularly relevant to manage the pandemic. First, the promotion of behavior change toward protective behaviors (e.g., hand-washing, social distancing). Second, to help establish the conditions for an emotional reaction (e.g., stress) within a normal range. The reviewed research suggests that illness perceptions may play an important role in the emotional and behavioral reaction to a particular illness. Therefore, understanding illness perceptions of COVID-19 may have relevant consequences for reaching these public health goals and developing public health measures, including health-promoting campaigns and their context-specific adjustments (e.g., in school settings). In the present study, we investigate illness perceptions, their predictors, and impacts across a large number of European countries.

The goals of the present study are to (1) study the development of illness perceptions across time (absolute and relative to the progression of the illness in each country); (2) understand the effect of demographic, risk and personal contact with COVID-19 (e.g., having been infected with COVID-19) on illness perceptions; and (3) assess the impacts of illness perceptions regarding general stress and preventive behaviors (e.g., hand-washing). All of these goals are studied considering the hierarchical structure of the data, with individuals nested in countries. We expect that the differences in culture and in severity of the pandemic in different countries will contribute to explaining the results.

The present study sought to investigate illness perceptions for COVID-19 and study three goals. The first goal was to understand the development of illness perceptions across time—considering chronological time and time adjusted to the epidemiological evolution of the pandemic in each county. The first consideration about these results is that chronological time and adjusted time showed the same results in terms of the direction and significance of their trends. This may suggest that individuals in Europe were reacting similarly to information from the progression of COVID-19 in other countries. The second consideration is that the magnitude of the temporal effects is small and only observed in some illness perceptions (i.e., consequences, timeline, concern, and understanding). This result needs to be interpreted considering the data gathering period—starting 46 days after the first COVID-19-related death in Europe. The small magnitude of the trend can have several interpretations. First, it may be that illness perceptions of COVID-19 were formed early in the pandemic and remained fairly stable. If so, the small magnitude of the trends would reflect the later stage of this formation. Specifically, the results suggest a linear decrease in the perceived understanding and perceived negative consequences and concern about COVID-19. The linear progression suggests a decrease in the negativity of illness perceptions over time. Second, illness perceptions may change across time as a function of the socially perceived dangerousness of COVID-19. This perception could be shaped by variables such as the perceived incidence of the condition on a given region or in a given time. If so, the current study only presents a picture of a given period, and evolution would be non-linear. The quadratic function of the trajectory of the timeline may be understood in this light. Future research, including longitudinal studies, will allow testing these alternative interpretation hypotheses, confirming either the stable or fluctuating nature of COVID-19 illness perceptions.

The second goal was to examine the predictors of the illness perceptions, across European countries. The first finding is that country showed no influence as a level of the model due to small ICC values. Different countries reflect not only cultural differences but also different epidemiological situations—at the considered time span. In any case, these results suggest a cross-national character of illness perceptions, at least for COVID-19 in Europe. As aforementioned, the cultural comparisons of illness perceptions are conflicting (Bean et al., 2007; Kaptein et al., 2013). Future research could consider countries outside of Europe or change the considered level for the analysis from individual countries to European regions (northern vs. southern; western vs. eastern).

The age risk group and gender showed a significant effect on several illness perceptions. Being considered in an age risk group was associated with illness perceptions in a mixed way. Age older than 60 years was positively associated with concern and timeline; however, concerningly, it was associated with lower perceived consequences, higher personal control, and with a better emotional response. This mixed pattern of associations may be related to general representations of old age interacting with illness perceptions (e.g., “my body is frail” vs. “I have survived so many ordeals, it is not a flu that will keep me from living”). Gender was also associated with illness perceptions in a mixed way. Female gender was associated with higher perceived personal and treatment control; however, it was associated with higher perceived consequences, timeline, negative emotional response, concern, and lower understanding. Again this could be related to general gender attitudes that associate being male with minimization of health threats. The results are consonant with findings on health-related attitudes associated with gender and age (Deeks et al., 2009), which are in agreement with the influence of general culture in the Common-sense model of self-regulation (e.g., Diefenbach and Leventhal, 1996). Given that male gender and age older than 60 years are risk factors for COVID-19, these results are unsettling. Some of the illness perceptions are linked to the risk factors in a way that is contrary to what would be desirable (i.e., higher risk, higher negativity). Understanding the specific illness perceptions that differ in these groups may inform specific focuses on health-promoting campaigns. Higher education levels, expectedly, were associated with a lower level of perceived lack of understanding—but no difference was found for the remaining perceptions. Personal contact with COVID-19 presented mixed results. For participants reporting having contracted COVID-19, higher negative consequences were perceived. However, when it was the partner that was infected with COVID-19, the participants tended to report higher levels of perceived personal control. It may be the case that while having COVID-19 may make participants realize its negative consequences, taking care of a partner with COVID-19 may foster the idea of personal control over the condition.

The third goal was to understand the impact of illness perceptions on general stress and COVID-19 preventive behaviors. Given the response scale of the IPQ items, higher scores reflect more negative illness perceptions. Concerning stress, the results were overall as expected, with all illness perceptions showing a significant and positive association with stress (i.e., all except for treatment control). The results of COVID-19 preventive behavior are less clear. As expected, higher scores in concern are associated with higher social distance, social isolation, and hand-washing. Perceived personal control is associated with higher social distance, social isolation, and hand-washing. Understanding shows a mixed result—with a association with lower social distance but with higher social isolation and hand-washing. These results show that illness perceptions explain general stress more consistently than the adoption of COVID-19 preventive behaviors. However, several points should be mentioned to caution such interpretation. First, the behavior dimensions are measured with a self-report scale, which raises questions about whether actual behavior is being measured. Second, during the period of the study, there were state-mandated guidelines (including lockdowns in some countries) to perform specific behaviors. This is unlike most conditions under which illness perceptions have been studied and raises the possibility of different determinants of this adherence. The third consideration is with respect to interpretation of the IPQ for COVID-19. Unlike other diseases in which illness perception has been studied, COVID-19 is a new condition. The participant's interpretation of items such as treatment control or understanding may be affected by the lack of scientific knowledge or consensus on the disease. It could be argued that such objective considerations are irrelevant for the consideration of illness perceptions. However, this is an important difference from most of the existing literature on familiar diseases, and it may create differences from other illnesses perceptions less dependent on such knowledge—such as concern. The implications of this consideration are two-fold. First, some of the inconsistencies among illness perceptions and other variables found in the present study may be due to interpretation issues. Second, these inconstancies may reflect illness perception formation—rendering these results an exceptional snapshot of this process.

The differential relationship between illness perceptions outcomes is similar to other studies that find that illness perceptions are better at explaining psychological dimensions than behavioral dimensions (Dempster et al., 2015; Aujla et al., 2016). Therefore, it may be advantageous to add other variables (e.g., existing barriers, self-efficacy) to illness perceptions in explaining the behavior. Risk perception has been showing promise to complement illness perception since it specifically refers to personal risk of contracting the disease. The few studied conducted for COVID-19 have shown risk perceptions to be relevant for precautionary health behavior in health professionals (Girma et al., 2020) perceived negative feeling in quarantined adolescents (Commodari and La Rosa, 2020) depression (Ding et al., 2020).

This study has several limitations. First, the cross-sectional nature of the analysis implies added care in extrapolating temporal variations or predictive relations between variables. Second, all measures were self-reported, which may introduce bias in reporting such as social desirability bias. Third, mask-wearing was not included as a preventive behavior. During the period of the design and implementation of the study, the recommendation of wearing masks was not so widespread. Fourth, despite the large number of participants and the effort to have multiple recruitment sources, the sample is not representative of the population. This opens the possibility of selection bias affecting the results. Concerning the analysis, despite the ability to adjust growth models to illness perceptions, standardized estimates and ICC values were small and AIC and BIC values were quite similar between models, suggesting a residual impact of both time and country, thereby requiring cautiousness in its interpretation. Nevertheless, these findings are aligned with other research addressing health outcomes in secondary schools, where strong variation in ICCs occurs, with some values lower than 0.10 (Shackleton et al., 2016). In addition, different operationalizations of time may lead to different results, reinforcing the need to interpret results cautiously.

Irrespective of the care that should be taken given the nature of the study and the recent character of COVID-19, this study has several implications. First it supports illness perceptions as a relevant concept in understanding disease—even with non-clinical samples. The results of this study may, for example, be used to inform health promotion campaigns for particular themes that may be relevant for particular risk groups—namely, in targeting particular representations. Second, the results suggest that time may play a role in explaining perceptions, with some perceptions revealing a higher predisposition to be temporally modeled. Despite the need for research to clarify temporal evolution, knowledge of such a progression may have implications for relevant issues for pandemic management, such as reducing societal panic vs. managing public saturation and avoidance. Finally, the consideration of illness perceptions with other relevant variables may help to promote behavioral change associated with preventive measures that are required for the general public.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by Cyprus National Bioethics Committee (ref.: EEBK EΠ 2020.01.60). The patients/participants provided their written informed consent to participate in this study.

DD, AN, MR, AG, MK, and AK: design of the study. DD, AN and MR: literature review and data analysis. DD, AN, AG, MK, AK, JL, MC, CN, DL, SP, SH, GP, VS, VV, LM, J-LM, AB, JA-G, M-PB, FM, SV-S, DO, RL, and BK: data gathering. DD, AN, MR, AG, MK, AK, JL, MC, CN, DL, SP, SH, GP, VS, VV, LM, J-LM, AB, JJ, M-PB, FM, SV-S, DO, RL, and BK: discussing the results. DD, AN, MR, and AK: writing up. DD, AN, MR, AG, MK, AK, JL, MC, CN, DL, SP, SH, GP, VS, VV, LM, JM, AB, JA-G, MP-B, FM, SV-S, DO, RL, and BK: reviewing and amending the paper. All authors contributed to the article and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.