Rally and Rage: The Gap between Specific and Pandemic-Specific Support for Governments in Europe

Abstract

In times of the COVID-19 pandemic, the public generally expressed high pandemic-specific support for their governments. Analysis based on ESS Round 10 COVID-19 module data from 20 countries shows, however, that there was a gap between pandemic-specific and specific support for governments in European states. A positive gap in favor of pandemic-specific support for governments was found among 52.7% of the respondents, while a negative trend was observed among 24.0% of the respondents. Younger people, those self-employed or working for family businesses, students, those with better subjective health, and people who tested positive for or thought they had suffered from COVID-19 expressed less satisfaction with the government’s handling of COVID-19 in their country compared to general satisfaction with national government performance. Political opinions affected the support gap too; people who were satisfied with the way democracy works, were less trusting of their government’s ability to control the spread of the pathogen, preferred their own decisions over compliance with government restrictions, and perceived that their government failed to manage the health–economy trade-off restrained their pandemic-specific support for the government as well.

1. Introduction

During the COVID-19 pandemic, satisfaction with governments’ steps in handling the disease rose even in democracies where specific support for the government had been relatively low in the long term. The pandemic crisis created a “rally-round-the-flag” effect, i.e., a sudden and substantial increase in public approval of governments during the period of the international health crisis (Bækgaard et al. 2020; Kritzinger et al. 2021; van der Meer et al. 2023). However, an opposite effect, with declining levels of government support, was also observed in some countries, e.g., Brazil, Japan, and the United States (Bækgaard et al. 2020; Gadarian et al. 2021).

Government policies adopted in fighting the spread of the COVID-19 disease brought serious political, economic, social, and human negative effects (Bol et al. 2021; Bonotti and Zech 2021). As concerns negative political effects, the COVID-19 crisis arrived at times of a broader crisis of democracy. Governments seized power (Guasti and Bustikova 2022), declared states of emergency, limited or even suspended individual freedoms (political rights and civil liberties including the freedom of assembly, religious rights, freedom of movement, and the right to education), and undermined democracy (Delanty 2020; Edgell et al. 2021; Engler et al. 2021; Lewkowicz et al. 2021; Katsanidou et al. 2023).

Governments framed the fight against COVID-19 as a trade-off between public health and the economy while erroneously ignoring that there is a continuum in the stringency of restrictions. Government restrictions imposed to reduce COVID-19 cases, hospitalizations, and deaths caused significant damage to national economies in terms of business shutdowns, lost jobs, GDP decline, and steep inflation. Some economic sectors were heavily affected by pandemic restrictions, e.g., transportation, tourism, agriculture, restaurant and food services, sports, creative arts, and higher education (Bonotti and Zech 2021).

Governments dramatically expanded their spending to save the economy and prop up the healthcare sector. Three types of pandemic heists emerged: irregularities/corruption in pandemic-related procurement, using pandemic opportunities to rewrite fiscal rules, and tilting pandemic relief towards loyalists or regions controlled by governing parties (Guasti and Bustikova 2022). Governments also provided economic benefits to a part of the electorate (Rapeli and Saikkonen 2020).

Governments openly supported the old and neglected the young (Swift and Chasteen 2021). People over 65 years were considered the most vulnerable to serious health complications from the virus, including death. Children and young people were framed as spreaders of the virus and as careless, irresponsible, and dismissive of COVID-19 risks and public health guidance. Intergenerational solidarity eroded during the pandemic (Swift and Chasteen 2021; Spaccatini et al. 2022). The representation of older adults as vulnerable and younger people as invulnerable to COVID-19 infection caused friction between generations and influenced their thinking of how the age groups should behave during and their evaluation of COVID-19 governance. Younger people, especially students, experienced the dramatic effects of the COVID-19 pandemic. The pandemic had a sizable impact on their social life and practices regarding academic work and life (e.g., the switch to online lectures/tutorials, closed libraries, changed communication channels for teachers and administrative support, new assessment methods, different workloads, and performance levels, etc.). Concerned about issues of their future professional careers and studies, they experienced boredom, anxiety, and frustration (Aristovnik et al. 2020).

Social lives were transformed, even militarized, by new regimes of social distancing, face masks, self-isolation, alternative handshakes, and COVID-19 passes. Policies aimed at reducing the spread of COVID-19 through social isolation created additional access barriers to health services, leading to a spike in morbidity, mortality, and suicide rates. Many individuals were left destitute, particularly those already vulnerable or impoverished. Among the most vulnerable were also the unincorporated self-employed, who experienced the largest reductions in employment and employment hours (Kalenkoski and Pabilonia 2021).

Considering all these negative effects affecting various subsections of the population, this study aims to contribute to this line of investigation by exploring the gap between specific and crisis-specific support for governments in European countries, as measured using the COVID-19 module of European Social Survey Round 10 (hereinafter ESS Round 10) national questionnaires. As the impact of the crisis governance was disproportional within the populations, we explore not only the individual characteristics affecting the satisfaction gap but also people’s political attitudes playing an important role in how they perceived the performance of their governments during the crisis.

Political Attitudes as a Source of the Support Gap

Our research builds on the concept of political support (Easton 1975). We explain the gap between the pandemic-specific (satisfaction with the government’s handling of COVID-19 in the country) and the specific support for the government (satisfaction with the national government). Specific support for the government is based on the satisfaction that members of a political system feel they obtain from the perceived performance and outputs of the political authorities. It arises from perceptions of the day-to-day behavior of the authorities in the aggregate, from the patterns of outputs as they emerge over time. In contrast, pandemic-specific support is object-specific; it arises from people’s perceptions of decisions, policies, actions, utterances, or styles exhibited by the authorities during the COVID-19 pandemic. Generally speaking, policies aimed at reducing the spread of COVID-19 disproportionately affected specific subsections of the population, and we aimed to uncover how. Therefore, we explored what could explain the gap between the government’s handling of COVID-19 and day-to-day government performance.

The Coronavirus crisis emerged at times of fundamental concern about the global state of democracy, and governments adopted control and regulation measures that only seemed possible in dictatorships; this fuelled further concerns about the fragility of democratic systems (Žižek 2020; Delanty 2020; Rapeli and Saikkonen 2020; Flinders 2021). As Delanty (2020, pp. 14–15) pointed out, “the Coronavirus is more than a pathogen that threatens the lives of many people, but democracy is also in danger from the recent experiments with the emergency government”. Governments engaged in practices both illiberal (discriminatory measures, derogations from political and civil rights, and abusive enforcement) and authoritarian (no time limit on emergency measures, disproportionate limitations on the role of the legislature, and official disinformation campaigns), and restrictions on media freedoms were also imposed in response to the COVID-19 pandemic. The severity of the violations of democratic rights and freedoms did not, however, correlate with better public health outcomes (Edgell et al. 2021). Judgments about government policy delivery were positively linked to satisfaction with the way democracy works (Clarke et al. 1993; Katsanidou et al. 2023). As satisfaction with the way democracy works is a summary indicator of people’s views about what democracy delivers but also whether it abstains from undesirable illiberal or authoritarian practices (Linde and Eckman 2003), people satisfied with the way democracy works in their country expressed less satisfaction with the government’s handling of COVID-19 in their country compared to their general satisfaction with the national government performance.

H1. 

Satisfaction with the way democracy works: higher satisfaction with the way democracy works in a country minimizes the positive gap in favor of pandemic-specific support for governments.

Trust in the government is an important factor in generating a rally effect (Chatagnier 2012). It is a type of “strategic trust” that depends upon beliefs about whether an individual (or institution) can be trusted to do a particular thing (Uslaner 2002). Political trust measures the degree to which citizens believe that government actions will lead to good outcomes. Individuals with less trust in the government expect less successful public policy, rendering them less likely to support it. Although these individuals may support certain policy goals, they do not support the policies themselves because they do not believe that the government is capable of bringing about desired outcomes (Hetherington 2005).

H2. 

Trust in the government: higher trust in the national government’s dealing with the impact of the coronavirus pandemic maximizes the positive gap between pandemic-specific and specific support for the government.

The spread of COVID-19 generated fears of a new danger—the COVID-19 disease. Fearful people tend to submit themselves to the protective authority of the state, trust in the government’s problem-solving capacities (Bol et al. 2021; Erhardt et al. 2021; Kritzinger et al. 2021; van der Meer et al. 2023), and adopt authoritarian attitudes even in countries with quality democracy (Filsinger and Freitag 2022). Such people might believe that the successful containment of the pandemic requires following rules, striving for conformist behavior, and punishing deviant actions. Nevertheless, Wróblewski et al. (2022) found that during the (second wave of the) pandemic, there were attitudes ranging from extreme loyalty to all the institutions involved in the fight against the “plague” to contesting almost every aspect of this fight in society.

H3. 

Compliance: the preference for following government rules before selecting one’s own decisions when fighting a pandemic maximizes the positive gap between pandemic-specific and specific support for the government.

Governments framed the fight against COVID-19 as a trade-off between “health and wealth” and preferred steps that were supposed to save health and lives. Public opinion, too, generally favored saving lives, even at a steep economic cost (Lesschaeve et al. 2021). However, society faced a stark trade-off between lost lives and livelihoods. Health and economic risks were not perceived as uniform in populations and influenced the individual differences between the pandemic and the general support for the government. People who perceived that their government was damaging the economy by stringent restrictions expressed less enthusiasm towards pandemic governance than those who perceived that such restrictions were saving lives.

H4. 

Economic threat vs. health threat: perceptions that a government prefers health over the economy minimize the positive gap between pandemic-specific and specific support for the government.

2. Materials and Methods

The analysis utilized a data set of 35,263 respondents from 20 European countries based on ESS Round 10, which included a complete COVID-19 module in the questionnaire. Due to the measures that were implemented to mitigate the spread of the virus, the data were collected from September 2020 to September 2022. Our file consisted of the countries that used face-to-face data collection, namely Belgium, Bulgaria, Croatia, Czechia, Estonia, Finland, Greece, Hungary, Iceland, Ireland, Italy, Lithuania, the Netherlands, North Macedonia, Norway, Portugal, Slovakia, Slovenia, and the UK. The data that were self-completed were excluded from the analysis as differences between the face-to-face and self-completion modes have the potential to damage comparability (Villar and Fitzgerald 2017).

The dependent variable “support gap” was constructed as a difference between the pandemic-specific support for the government (a variable measuring the satisfaction with the government’s handling of COVID-19 in the country) and specific support for the government (a variable measuring the satisfaction with the national government). The first variable was measured using the question, “Overall, how satisfied are you with the [country] government’s handling of the coronavirus pandemic?”. The second variable was measured using the question, “Now thinking about the [country] government, how satisfied are you with the way it is doing its job?”. Both were measured using a scale from extremely dissatisfied = 0 to extremely satisfied = 10.

The explanatory variables included:

(a)

Individual control variables: age (interval from 15 years of age), gender (male = 1, female = 2), ISCED education level (less than lower secondary = 1, lower secondary = 2, upper secondary = 3, post-secondary = 4, tertiary = 5), income deprivation (living comfortably on present income = 1, coping on present income = 2, finding it difficult on present income = 3, Finding it very difficult on present income = 4), main job (1 = self-employed + family business, 2 = employee);

(b)

Main activity in the last 7 days: paid work, education, unemployed, actively looking for a job, permanently sick or disabled, retired, housework and/or looking after children or others (0 = not marked, 1 = marked);

(c)

Subjective health (1 = very good, 2 = good, 3 = fair, 4 = bad, 5 = very bad)

(d)

Personal experience with COVID-19 (1 = tested positive, 2 = I think I had it)

(e)

Year of data collection (2020, 2021, 2022);

(f)

Satisfaction with the way democracy works (0 = extremely dissatisfied, 10 = extremely satisfied)1;

(g)

Trust in the national government’s dealing with the impact of the coronavirus pandemic (0 = no trust at all, 10 = complete trust)2;

(h)

Compliance (the importance of following government rules or selecting your own decisions when fighting a pandemic) (0 = much more important to follow government rules, 10 = much more important to make your own decisions)3; and

(i)

Economic threat vs. health threat (the view on how the [country] government balanced protecting the economy and protecting people’s health when responding to the coronavirus pandemic) (0 = they placed far too much importance on protecting the economy and not enough on protecting people’s health, 5 = they got the balance about right, 10 = they placed far too much importance on protecting people’s health and not enough on protecting the economy)4.

For clarity, the results for the recoded variables (0/1 = 1, 2/3/4 = 2, 6/7/8 = 3, 9/10 = 4, and with category 5 = “they got the balance about right” as the reference) are presented in

Table 1. Regression models for the gap between the specific and pandemic-specific support for the government.

	M1	M2	M3
Intercept	0.882 ***	1.953 ***	2.319 ***
Age	0.011 ***	0.013 ***	0.007 ***
Male	−0.008	−0.007	−0.010
Education (tertiary)
<Lower secondary	0.062	0.005	0.009
Lower secondary	0.087 *	0.017	0.021
Upper secondary	0.130 *	0.014	0.018
Post-secondary	0.021	−0.013	0.040
Feeling about household income (Finding it very difficult)
Living comfortably	−0.370 ***	−0.057	−0.184 *
Coping	−0.228 ***	−0.014	−0.021
Finding it difficult	−0.169 *	−0.068	−0.018
Self-employed + family business	−0.198 ***	−0.194 ***	−0.133 ***
Paid work	0.050	0.0478	0.054
Education	0.335 ***	0.236 **	−0.262 ***
Unemployed, looking for a job	−0.050	−0.092	−0.031
Sick/disabled	−0.191 *	−0.166	−0.160
Retired	−0.134 *	−0.103	−0.105
Homemaker	−0.072	−0.060	−0.066
Subjective health (very bad)
Very good	−0.652 ***	−0.521 ***	−0.479 **
Good	−0.655 ***	−0.590 ***	−0.568 ***
Fair	−0.491 ***	−0.503 ***	−0.484 ***
Bad	−0.469 **	−0.515 **	−0.432 **
COVID-19 (No)
Tested positive	−0.164 ***	−0.164 ***	−0.120 **
I think I had it	−0.369 ***	−0.369 ***	−0.276 ***
Satisfaction with the way democracy works		−0.246 ***	−0.412 ***
Trust in the government to deal with COVID-19			0.254 ***
Compliance with government rules or dissent			−0.071 ***
Health–economy balance in COVID-19 (They got the balance about right)
Too much of protecting the economy			−0.605 ***
2			−0.291 ***
3			−0.124 ***
Too much of protecting health			−0.300 ***
Year (2021)
2020	0.150	0.221	0.056
2022	0.167 ***	0.176 ***	0.201 ***
Individual variance	5.010 ***	5.012 ***	4.532 ***
Country variance	0.335 **	0.354 **	0.211 **
AIC	129,013	125,784	117,755
BIC	129,030	125,800	117,772

* p < 0.05, ** p < 0.01, *** p < 0.001.

. The variable transformation did not affect the quality of the statistical model containing the original variable (AIC = 117,761, BIC = 117,778).

A set of multilevel mixed-effect regressions (linear mixed models) was estimated. The ESS sample designs differed greatly across countries. The goal was to achieve a minimum effective sample size (which results in similar confidence intervals across countries) in the most cost-effective way for each country, taking into account the country’s context. Thus, the countries differed in the magnitude of selection probabilities, the variation among them, as well as the clustering and stratification (Kaminska 2020). For that reason, the respondents were treated as nested within countries, and we accounted for interdependence between the observations. The models were evaluated at the given significance level using Z-statistics, the Akaike information criterion (AIC), and the Bayesian information criterion (BIC).

The data was weighted using “anweight” for the bivariate analysis (Kaminska 2020).

3. Results

3.1. Descriptive Statistics

The results of the descriptive analysis showed that 1.8% of the interviews were collected in 2020 (approximately half of the Slovenian sample), 70.1% were collected in 2021, and 28.1% were collected in 2022. In the total sample, 46.4% of the respondents were men, the average age was 50.8, and 29.2% of the respondents achieved tertiary or higher education. Those self-employed or working for a family business accounted for 14.4%, employees in paid work accounted for 46.6%, unemployed people looking for a job accounted for 4.1%, 27.1% were retired, 2.7% were permanently sick or disabled, 11.3% were homemakers or looking after children, and those who reported education as their main economic activity accounted for 7.7% of the data. Regarding the concerns of subjective income deprivation, 30.3% of the respondents lived comfortably, and 45.6% were coping with their present income. The majority of the respondents rated their health as “very good” (26.1%) or “good” (41.9%), 16.9 % reported having tested positive for COVID-19, and 6.5% thought they had suffered COVID-19.

The share of respondents who did not evaluate their general satisfaction with the national government accounted for 2.1%; the most were in Montenegro (4.1%), and the least were in the UK (0.3%). In contrast, the respondents who did not evaluate the government’s handling of the coronavirus pandemic accounted for 9.7% of the whole data; most were in Spain (9.3%), and the least were in Belgium, Finland, and Norway (0.4%). The missing cases were excluded from the analysis. No support gap, i.e., equal ratings of general satisfaction with the national government and the government’s handling of the coronavirus pandemic, was found among 23.3% of the respondents. A positive support gap was found among 52.7% of the respondents.

The highest average satisfaction with the country’s government’s handling of the coronavirus pandemic was found in Iceland (7.45), and the lowest was found in Slovakia (3.91). The highest average satisfaction with the way a government was doing its job generally was found in Switzerland (6.98) and the lowest was in in Bulgaria (3.02). Figure 1 presents the gap between the specific and pandemic-specific support. The highest average difference, indicating a preference for “crisis” governance, was in Portugal (2.02), and the lowest and negative values, indicating a preference for how the government normally performs, was in Switzerland (−0.34). Switzerland was the only country where the satisfaction with the government’s handling of the coronavirus pandemic was lower than the satisfaction with general government performance.

Figure 2 presents the mean values of the political opinions used to explain the dependent variable in the countries of interest. The average support for democratic regime performance reached 5.4, with the lowest value in Bulgaria and the highest in Switzerland. The data show less satisfaction with democracy in the countries of central and eastern Europe.

The mean value of the trust in the government’s handling of COVID-19 was 5.2, with the least trusting respondents in Slovakia and the most trusting respondents in Norway. People believed that, on average, the government balanced the protection of health and the economy correctly, as the mean value on the economy–health scale was 5.1. The belief that the government placed far too much importance on protecting the economy and not enough on protecting people’s health was the most present in the UK, and the opposite belief that the government placed far too much importance on protecting people’s health was the most widespread in Czechia. Respondents found it important to follow epidemiological governance overall, as the mean value on the compliance–dissent scale was 4.2. The strongest consent with the epidemiological governance was found in Iceland, and the strongest belief that it was important to follow one’s own decisions existed in Czechia. A stronger tendency to oppose epidemiological governance was present in central and eastern European countries, and stronger conformism was apparent in Nordic countries.

Statistically significant (p = 0.001) correlations between the support gap and satisfaction with the performance of democracy (−0.20), trust in the national government’s dealing with the impact of the coronavirus pandemic (0.12), the compliance–dissent scale, and the rating of the health–economy trade-off (−0.10) were found in the data. An analysis of variance also confirmed that the support gap varied according to the health–economy trade-off rating (F = 24.81, p = 0.001 for the original variable, F = 54.55, p = 0.001 for the recoded variable).

3.2. Regression Results

In order to test our hypotheses, a set of multilevel mixed-effect regression models was estimated (Table 1). We examined the effects of individual characteristics, the effects of political support (satisfaction with the way democracy works and trust in the national government’s dealing with the impact of the coronavirus pandemic), the compliance–dissent scale, the rating of the health–wealth (economy) trade-off, and the country effect.

The first model, M1, contained only the individual control variables, i.e., age, gender, education, subjective income deprivation, main economic activity, subjective health, personal experience with COVID-19, year of data collection, and country. The individual control variables were considered to be fixed effects, and the country was considered a random effect. The results of the M1 model showed that the positive gap between the pandemic support for the government and the general support for the government rose with age, income deprivation, and worse subjective health. In contrast, the positive support gap was smaller for people with higher education, people who tested positive or thought they had COVID-19, those who were self-employed and working for family businesses, and students. These results support the observations that government policies adopted while fighting the spread of the COVID-19 disease negatively affected the lives of people who were younger, healthier, worse off, self-employed, working for family businesses, in full-time education, or had recovered from the disease. The positive support gap was significantly larger in 2022 when governments dropped the restrictions on daily life after the virus had become endemic, compared to 2021, when they adopted the strictest measures. The second and third models tested the effects of political opinions (satisfaction with the way democracy works in the country and trust in the national government’s dealing with the impact of the coronavirus pandemic), the compliance-dissent scale, and the view on how the government balanced protecting the economy and protecting people’s health. Model M2 considered all the variables of the first model and added satisfaction with the way democracy works. The results of the analysis proved that support for the way democracy works in a country significantly affected the gap between the specific and pandemic-specific support for the government, thus supporting hypothesis H1 that higher satisfaction with democracy minimizes the gap between the specific support for the government and the support for pandemic rules. The effects of individual variables, including age, subjective health, a positive test or presumption of having had COVID-19, self-employment or working for a family business, student status, and year of data collection remained statistically significant, and the effects of education and relative income deprivation lost their statistical significance.

The last model, M3, tested the hypotheses H2, H3, and H4. The remaining political opinions concerning the government were introduced into the analysis, including trust in the national government’s dealing with the impact of the coronavirus pandemic, the compliance–dissent scale, and the perception of how the government balanced the protection of health and the economy when responding to the pandemic. Trust in the national government appeared as a strong predictor of the support gap. The results of the analysis confirmed hypotheses H2 and H3. The more trust people had in the government policies adopted to fight the spread of the COVID-19 disease, the higher their satisfaction with the government’s handling of the plague compared to their general satisfaction with government performance. Preference for compliance or dissent, i.e., following government rules or following one’s own decisions in the crisis situation, also significantly affected the gap between the specific and pandemic-specific support for the government. Those who shared the opinion that following government rules is more important in the crisis situation tended to express higher satisfaction with the government’s handling of the plague compared to the general satisfaction with government performance. The effect of this variable was, however, weaker than in the case of trust in the government’s ability to regulate the pandemic.

The last hypothesis, H4, was not confirmed using the results of the analysis. The perceptions of how the government balanced the protection of health and the economy significantly contributed to explaining the support gap as well. However, it was the respondents who believed that the government balanced the protection of health and economy correctly who expressed higher satisfaction with the government’s handling of the plague compared to the general satisfaction with government performance. A lower support gap was found among those who perceived that their government had failed in the health–economy trade-off and had given too much preference either to health or the economy.

When controlling for the three political opinions concerning the government in M3, the size of the coefficient for satisfaction with the performance of democracy increased while the effects of subjective health and personal experience with COVID-19 decreased. The effects of age, self-employment or working for a family business, student status, subjective health, a positive test or presumption of having had COVID-19, and year of data collection remained statistically significant.

Figure 3 and Figure 4 illustrate how the gap between specific and pandemic-specific support for governments expands with age and satisfaction with democracy. The predicted values of the dependent variable in M3 for the age categories shown in Figure 3 confirm that younger age categories expressed lower satisfaction than older ones with the government’s handling of the plague compared to the general satisfaction with government performance. Predicted values of the dependent variable in M3 for the satisfaction with democracy are shown in Figure 4. The figure presents how the support gap shrinks with satisfaction with the performance of democracy and becomes negative for category 10, which is extreme satisfaction with the way democracy works.

The AIC and BIC indicate that model M3 performed the best. Political opinions explained a large part of the support gap. This means that research on the gap between specific and crisis-specific support for governments should consider how crisis governance affects specific subsections of the population and how it interferes with the population’s political perceptions concerning the regime and government.

4. Discussion and Conclusions

The study contributes to the literature on the public approval of governance at the time of the COVID-19 pandemic and a crisis in general. It reveals and explores the gap between the specific and crisis-specific support for governments in Europe. The results of the analysis illustrate that the government’s handling of COVID-19 was less acceptable for younger (Hegewald and Schraff 2024), worse off, healthy, self-employed or working for family businesses, students, or those familiar with the new danger (tested positive or thought they had COVID-19). Public approval of crisis governance was more positive among the public that was more vulnerable to the danger, including those who were older, had worse subjective health, or were inexperienced with the new danger. Nevertheless, the support gap could not be sufficiently explained without taking political attitudes and opinions into consideration. Political attitudes and opinions play an important role in sustaining democratic legitimacy and can affect societal response to government steps in times of crisis. Our study suggests that governments interfere with public expectations about the performance of democracy, economic or health policies, and personal responsibilities for life and health in times of crisis. This generates temporal discontent with political institutions, but it does not necessarily erode diffuse support for the regime or political community.

In our analysis, we had a chance to compare the support gap between large groups of respondents interviewed in 2021 and 2022. The two groups were not confronted with the same stringency of policies aimed at mitigating COVID-19. Those responding in 2021 (especially in its last quarter) faced more restrictions to daily life than those responding in 2022 after the omicron variant had spread and the restrictions had been dropped. The large data collection window might be advantageous to explaining the support gap concerning policy changes, or it might represent a limitation of the study, as the immediate feeling from governments’ handling of COVID-19 during 2020–2021 vanished in 2022.

The second limitation of the study might lie in its cross-sectional data. A substantial part of research on the “rally-round-the-flag” effect during the COVID-19 pandemic has been conducted using panel surveys (Bækgaard et al. 2020; Kritzinger et al. 2021; Kudrnáč and Klusáček 2022; van der Meer et al. 2023; Hegewald and Schraff 2024). The data collected from the same sample of respondents before and after the pandemic crisis allowed us to analyze individual-level changes in political support. In contrast, cross-sectional data is considered insufficient for testing changes in political support (Bernardi and Gotlib 2023; van der Meer et al. 2023). Nevertheless, the approach used in the cross-sectional European Social Survey, a measurement based on two questions on specific support and crisis-specific support might be a viable alternative.