Introduction
The global COVID-19 pandemic led governments to implement extraordinary policies that curtailed civil and social rights, including mobility restrictions, school closures, and lockdown measures. Although these restrictions aimed to protect public health, they revealed tensions between individual freedoms and collective benefits, thereby challenging the democratic principles of liberal governance (Boin and Bynander, Reference Boin and Bynander2015; Larsson and Rhinard, Reference Larsson and Rhinard2021). Public perceptions of these crisis measures were influenced not only by the policies themselves but also by trust in institutions and fear of illness, both of which have been identified as important correlates of support for restrictive measures (Christensen et al., Reference Christensen, Fimreite and Lægreid2011; Amirkhanyan et al., Reference Amirkhanyan, Meier, Song, Roberts, Park, Vogel, Bellé, Molina and Guul2023; Sefton and Haug, Reference Sefton and Haug2025). Trust in institutions has been linked to greater compliance and lower uncertainty, while fear of illness has been associated with stronger perceived necessity of restrictions (Hillebrand, Reference Hillebrand2021; Borisova et al., Reference Borisova, Frye, Schoors and Zabolotskiy2023; Hrbková and Kudrnáč, Reference Hrbková and Kudrnáč2024). In high-trust societies such as the Nordic countries, trust can mitigate the effects of fear, whereas low trust can intensify scepticism and resistance to regulations (Esaiasson et al., Reference Esaiasson, Sohlberg, Ghersetti and Johansson2021; Fimreite et al., Reference Fimreite, Løvseth, Lægreid and Rykkja2024).
In addition to trust and fear, the pandemic intensified existing social inequalities, particularly along gender lines. International research demonstrates that women faced disproportionate caregiving responsibilities and work–family conflicts as school and kindergarten closures disrupted their dual roles as caregivers and earners (Fortier, Reference Fortier2020; Johnston et al., Reference Johnston, Mohammed and Van Der Linden2020; Petts et al., Reference Petts, Carlson and Pepin2021; Yavorsky et al., Reference Yavorsky, Qian and Sargent2021; van Tienoven et al., Reference van Tienoven, Minnen, Glorieux, Laurijssen, te Braak and Glorieux2023). Furthermore, studies consistently indicate that women are more likely than men to perceive health risks seriously, support restrictive measures, and comply with guidelines (Galasso et al., Reference Galasso, Pons, Profeta, Becher, Brouard and Foucault2020; Shay, Reference Shay2020; Cardinal et al., Reference Cardinal, Bunn, Schley, Fulton and Keathley2022). These dynamics are context-dependent: women’s support for restrictions often intersects with the burdens they experience, particularly among single mothers balancing caregiving and paid work (Hipp and Bünning, Reference Hipp and Bünning2021; Fan and Moen, Reference Fan and Moen2024). Restrictions such as school closures and remote work mandates may unintentionally exacerbate gendered inequalities, even in welfare-oriented societies such as the Nordic countries. These unequal caregiving burdens may help explain why some restrictions, particularly school and kindergarten closures, were experienced differently across groups.
The Nordic countries provide valuable context for examining these dynamics due to their robust welfare states, high institutional trust, and gender equality policies. Despite these similarities, their pandemic responses varied considerably: Norway implemented strict lockdowns, Sweden adopted relatively relaxed measures, and Denmark, Finland, and Iceland pursued intermediate approaches (Garcia et.al., Reference Garcia, Järnland, Nordensvärd, Sommar, Wihlborg and Haug2024; Nordensvärd et al., Reference Nordensvärd, Sefton and Godenhjelm2023; Nguyen Duy and Stokstad, Reference Nguyen Duy, Stokstad and Haug2024). These differences in policy stringency offer an opportunity to explore how national contexts interact with social factors such as gender, trust, fear, and family structure to shape public perceptions of the reasonableness of restrictions. This study examines how perceptions of the reasonableness of COVID-19 restrictions varied across five Nordic countries and how these perceptions were associated with gender, parenthood, family structure, institutional trust, and fear of illness. The Nordic case is particularly useful because it combines relatively strong welfare states, high levels of institutional trust, and ambitious gender equality policies with meaningful variation in pandemic response strategies. This makes it possible to explore whether broadly similar institutional settings nevertheless produced different public evaluations of restrictive measures and whether such evaluations varied across social groups.
Although cross-country differences in perceptions of reasonableness were modest, the findings highlight persistent social inequalities exacerbated by crisis measures. Women, particularly single mothers, experienced restrictions such as school and kindergarten closures as disproportionately burdensome, illustrating how caregiving responsibilities can intensify inequalities even in highly egalitarian societies. Additionally, high levels of institutional trust and fear of illness were crucial in shaping public attitudes, emphasising the importance of trust-building in crisis policy. More broadly, the study speaks to debates about legitimacy, proportionality, and equity in crisis governance. It highlights the importance of examining not only whether restrictions are effective, but also how they are experienced across different social positions.
Research questions
This study addresses the following questions:
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1. How did perceptions of the reasonableness of COVID-19 restrictions vary across Nordic countries, and how were perceptions associated with institutional trust and fear of illness?
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2. How were these perceptions associated with gender, parenthood, and family structure, and how substantial were these differences?
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3. What broader lessons can be drawn from the Nordic case for designing crisis policies that are both effective and attentive to social inequality?
This study bridges theoretical debates on gender, trust, and crisis governance with comparative policy analysis, utilising survey data from representative samples across all Nordic countries. The analysis employs both descriptive statistics and regression models with interaction terms to assess the influence of factors such as institutional trust and fear of illness. The structure of the paper is as follows: the next section reviews the theoretical framework and literature on perceptions of reasonableness and gendered inequalities in crisis policies, followed by a detailed description of the methodology and data analysis. The findings are subsequently presented and discussed, emphasising their policy implications and contributions to the broader literature on equitable crisis governance.
Background
The Nordic model and policy stringency
The Nordic countries are internationally recognised for their strong welfare states, progressive gender equality policies, and high levels of institutional trust (Martela et al., Reference Martela, Greve, Rothstein, Saari, Helliwell, Layard, Sachs and De2020). These shared characteristics make the region a unique context for studying public perceptions of crisis policies. However, the Nordic countries diverged significantly in their responses to the COVID-19 pandemic. Norway implemented strict lockdown measures, Sweden pursued a more relaxed approach, and Denmark, Finland, and Iceland adopted intermediate responses (Nordensvärd et al., Reference Nordensvärd, Sefton and Godenhjelm2023; Sefton and Haug, Reference Sefton and Haug2025). These variations in policy stringency provide an ideal comparative framework for examining how differences in national policies shape public perceptions of the reasonableness of restrictive measures.
The concept of reasonableness is central to understanding public attitudes towards crisis policies.
Reasonableness is shaped not only by the content, scope, and timing of policies but also by broader societal factors, including institutional trust, communication strategies, and the socio-political environment in which policies are implemented. The Nordic model, with its emphasis on egalitarianism, universal welfare, and high public trust, offers a lens through which we can investigate how individuals evaluate the fairness, necessity, and proportionality of restrictive measures during crises.
Reasonableness and intersectionality
Reasonableness is a multidimensional concept rooted in legal theory and political philosophy, extending beyond “formal rationality” to encompass the diverse lived experiences and social contexts of individuals (Weinstock, Reference Weinstock2006; Young, Reference Young, Jackson and Tushnet2017; Grossmann et al., Reference Grossmann, Eibach, Koyama and Sahi2020). It requires balancing competing interests across social, economic, and cultural dimensions to ensure fairness and equity (Brynard, Reference Brynard2013; Borriello, Reference Borriello2021; Möller, Reference Möller2021; Mangini, Reference Mangini2022). Thus, an intersectional lens (Harris and Patton, Reference Harris and Patton2019; Bond, Reference Bond and Bond2021) is essential for understanding how perceptions of reasonableness are shaped by overlapping social identities, including gender, caregiving roles, and housing conditions (Cathaoir, Reference Cathaoir, Kjaerum, Davis and Lyons2021; Høgberg et al., Reference Høgberg, Eriksen, Holmøyvik, Høgberg, Eriksen and Holmøyvik2023). For example, women, particularly those with caregiving responsibilities, may experience restrictions differently from men due to their dual roles as caregivers and breadwinners. Single parents and individuals living in smaller or shared accommodations may face additional challenges complying with measures such as quarantine or remote work.
The pandemic further highlighted these dynamics, as existing structural inequalities intersected with restrictive measures, exacerbating vulnerabilities. For instance, marginalised communities, including Somali populations in Norway and Sweden, experienced disproportionately high rates of COVID-19 infections during the early months of the pandemic, which illustrates how social positions intersect with policies to shape their impact (Gostin et al., Reference Gostin, Friedman, Hossain, Mukherjee, Zia-Zarifi, Clinton, Rugege, Buss, Were and Dhai2023). These dynamics further underscore the importance of examining how restrictive measures can disproportionately affect certain groups and how such disparities, in turn, influence public attitudes.
Trust and fear
Trust in institutions and fear of illness are two critical factors mediating public perceptions of restrictive measures. High institutional trust promotes compliance with government policies and may reduce public uncertainty regarding the appropriateness of governmental responses to crises. Conversely, fear of illness can heighten the perceived necessity of restrictions (Jennings et al., Reference Jennings, Stoker, Valgarðsson, Devine and Gaskell2021; Borisova et al., Reference Borisova, Frye, Schoors and Zabolotskiy2023; Hrbková and Kudrnáč, Reference Hrbková and Kudrnáč2024).
The Nordic countries, with their high levels of public trust and robust welfare institutions, provide an excellent context to explore these dynamics. Trust in institutions enhances collective compliance and mitigates resistance to restrictive measures, particularly in times of crisis (Esaiasson et al., Reference Esaiasson, Sohlberg, Ghersetti and Johansson2021; Baldersheim and Haug, Reference Baldersheim, Haug, Laffin, Wayenberg, Kuhlmann and Bergström2024). However, fear plays a dual role: while it can increase support for restrictions, it may also amplify social divisions, especially in contexts where trust is unevenly distributed. Thus, the interaction between trust and fear, in addition to their respective mediation and/or moderation on perceptions of reasonableness, is particularly important: trust can buffer the paralysing effects of fear, while fear can amplify the demand for government action (Johansson, Sohlberg, and Esaiasson, Reference Johansson, Sohlberg, Esaiasson, Johansson, Ihlen, Lindholm and BlachOrsten2023; Fimreite et al., Reference Fimreite, Løvseth, Lægreid and Rykkja2024). This duality underscores the need to study how trust and fear interact and mediate or moderate other independent variables to shape perceptions of reasonableness during a crisis.
Gendered inequalities in the pandemic
The COVID-19 pandemic amplified pre-existing gendered inequalities, bringing caregiving burdens and work–family conflicts to the fore. The closure of schools and daycare facilities placed significant strain on women, who, according to a wealth of research, disproportionately undertook caregiving responsibilities while managing paid work (Galasso et al., Reference Galasso, Pons, Profeta, Becher, Brouard and Foucault2020; Johnston et al., Reference Johnston, Mohammed and Van Der Linden2020). These burdens were particularly acute for single mothers (single parents), who often lacked the structural support needed to balance caregiving and employment (Hipp and Bünning, Reference Hipp and Bünning2021; Fan and Moen, Reference Fan and Moen2024).
Despite strong gender equality policies in the Nordic countries, the pandemic exposed vulnerabilities in caregiving provision. Institutional disruptions, such as school and kindergarten closures, revealed the uneven distribution of reproductive labour, with women bearing the majority of caregiving responsibilities (Hansen et al., Reference Hansen, Bjørnholt and Horn2021; Kantola, Reference Kantola2021). These challenges underscore the importance of examining how gender and caregiving roles intersect to shape perceptions of the reasonableness of restrictive measures. They also emphasise the necessity for policies that recognise and address the unique burdens placed on women and caregivers during crises.
Research gaps and contributions
While several studies have examined the role of trust, fear, and gender in shaping public attitudes towards crisis policies, important gaps remain to be explored. First, there is a limited understanding of how these factors interact to influence perceptions of reasonableness, particularly in the Nordic context. Second, the intersectional dynamics of gender and caregiving roles, in addition to age and education level, in shaping public attitudes have not been fully explored. Finally, while the Nordic model is often lauded for its egalitarian policies, comparative analyses of public perceptions across Nordic countries remain scarce (cf. Sefton and Haug, Reference Sefton and Haug2025). This study addresses these gaps by examining how trust, fear, and social position (e.g., gender and family structure) intersect to shape perceptions of reasonableness in the Nordic countries. By integrating theories of reasonableness, intersectionality, and crisis governance, this study aims to contribute to the broader understanding of how diverse social groups experience and evaluate restrictive measures during a global health crisis. Additionally, it offers insights into the design of equitable and context-sensitive crisis policies that mitigate social inequalities while maintaining support for public health measures (cf. Sefton and Ubaid, Reference Sefton and Ubaid2025).
Hypotheses
The COVID-19 pandemic and the resulting restrictive measures disrupted daily life and disproportionately affected specific social groups. Drawing on literature concerning gendered caregiving roles, institutional trust, and fear of illness, this study examines how these factors shape perceptions of the reasonableness of restrictions in the Nordic countries. Accordingly, the hypotheses focus on gender, parenthood, and cross-country variations as key predictors of public attitudes.
H1: Gender and perceived reasonableness
Women have historically been more supportive of measures to protect public welfare and public health (Umamaheswar and Tan, Reference Umamaheswar and Tan2020). However, caregiving responsibilities and increased work–family conflicts during the pandemic may have amplified differences in how women and men perceived the reasonableness of restrictions (Stockemer et al., Reference Stockemer, Plank and Niemann2021; Carreras et al., Reference Carreras, Vera and Visconti2023). We test the following hypotheses:
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- H1a: Women perceive COVID-19 policies as more reasonable than men in all Nordic countries.
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- H1b: Women with children perceive school and kindergarten closures as less reasonable compared to women without children.
H2: Parenthood and perceived reasonableness
Parents, and particularly single parents, experienced severe disruptions during the pandemic due to school and kindergarten closures (Fuller and Qian, Reference Fuller and Qian2021; Hipp and Bünning, Reference Hipp and Bünning2021; Lyttelton et al., Reference Lyttelton, Zang and Musick2023). This may have influenced their perceptions of the reasonableness of these measures. We hypothesise:
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- H2a: Parents with children under the age of 18 perceive school and kindergarten closures as less reasonable compared to non-parents.
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- H2b: Single parents perceive school and kindergarten closures as less reasonable compared to two-parent households.
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- H2c: Single mothers perceive school and kindergarten closures as less reasonable compared to single fathers.
H3: Cross-country variation in perceived reasonableness
The Nordic countries’ pandemic responses varied in policy stringency, providing a comparative framework for understanding cross-country differences in public perceptions of the reasonableness of pandemic responses (Saunes et al., Reference Saunes, Vrangbæk, Byrkjeflot, Jervelund, Birk, Tynkkynen, Keskimäki, Sigurgeirsdóttir, Janlöv, Ramsberg, Hernández-Quevedo, Merkur, Sagan and Karanikolos2022; Haug, Reference Haug2024). Based on these differences, we hypothesise:
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- H3a: Citizens in Sweden perceive COVID-19 restrictions as more reasonable compared to citizens in the other Nordic countries.
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- H3b: Citizens in countries with stricter restrictions (e.g., Norway) perceive restrictions as less reasonable compared to citizens in countries with more relaxed measures (e.g., Sweden).
Data and methods
The data for this study were collected through a citizen survey conducted in Sweden, Norway, Denmark, Finland, and Iceland during June and July 2022. Approximately 1,300 respondents participated in each country, with Iceland having the smallest sample size of 549. This resulted in a total sample of 5,674 responses. The survey employed a quota sampling strategy to ensure a representative demographic mix by gender, age, and geographic region (Haug, Reference Haug2024) See Appendix E for distribution of responses. Respondents aged 71 or above were excluded (N = 560), focusing on the working-age population. Additionally, observations with missing responses to dependent variables (N = 565) or key independent variables (N = 939) were removed. Depending on the model used, the final analytical sample ranged from 3,635 to 4,760 observations. A detailed breakdown of respondents by country and observations per model is provided in Appendix B.
Survey design
The survey was conducted in the post-pandemic phase to allow respondents to reflect on both the immediate hardships faced during restrictions and their broader societal impact. To mitigate potential hindsight bias, the survey questions explicitly framed evaluations of reasonableness by referencing both individual and societal experiences during the pandemic. For example, the introduction to the survey emphasised:
“The health authorities have recommended or imposed a series of restrictive measures to contain the spread of COVID-19 but have also sought to compensate individuals and businesses for losses incurred. These measures have varied over time.”
Respondents were then asked to evaluate the reasonableness of restrictive measures:
“How reasonable or unreasonable do you think the following restrictive measure has been in view of the hardships experienced by individuals and society at large?”
This framing prompted respondents to evaluate the reasonableness of restrictions comprehensively, by considering both personal and collective dimensions of the pandemic experience.
Variables
Dependent variables
The main dependent variable is the perceived reasonableness of COVID-19 restrictions. The survey measured perceptions of 17 pandemic policy measures implemented across the five Nordic countries. For the purpose of this study, we focused on four measures selected for their high impact and common experience across all countries surveyed, ensuring they represented significant areas of public and policy relevance. These areas included education, employment, and leisure, which were heavily influenced by pandemic restrictions. Thus, respondents evaluated the reasonableness of four key measures on an 11-point scale (0 = completely unreasonable, 10 = fully reasonable). The four measures were:
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- (i) home schooling or the closure of schools (home school)
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- (ii) kindergarten closures (kindergarten)
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- (iii) mandates requiring work from home (home office)
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- (iv) restrictions on leisure activities for children and young people (leisure activities)
Responses marked as “don’t know” (11) or those falling outside the valid scale range were excluded from the analysis. The choice of an 11-point scale allows for nuanced responses, capturing subtle variations in perceptions of reasonableness across different social groups and national contexts (cf. Sefton and Haug, Reference Sefton and Haug2025).
To enable comparative analysis across countries, we constructed a composite Reasonableness Index by averaging the four measures. For Sweden, where kindergarten closures were not implemented, the index was calculated using the remaining three measures (home school, home office, and leisure activities). Only respondents who provided valid responses to at least three out of four items were included in the calculation of the Reasonableness Index (cf. Appendix B). A robustness check confirmed that results from a three-item index (excluding kindergarten closures) were consistent with those from the full four-item index across all countries. Thus, this composite measure provides a comprehensive metric for examining how perceptions of reasonableness differ across social groups and national contexts.
Independent variables
To explore how perceptions of reasonableness vary by social position, we included several independent variables grouped into key categories based on family structure, trust, fear, and sociodemographic characteristics detailed below:
Family structure variables
Gender: a binary variable coded as 1 for women and 0 for men. This variable captures potential gender differences in perceptions of reasonableness, as prior research has shown that women are often more supportive of public health measures than men (Memoli, Reference Memoli2024). Marital status: a binary variable coded as 1 for respondents who were married or cohabiting with a partner and 0 for those who were single. This variable reflects how partnership status may shape perceptions of pandemic restrictions, as individuals in couples may have different social and household dynamics compared to those who are single.
Parenthood: a binary variable coded as 1 for respondents with children under the age of 18 living in their household and 0 for those without children. This variable accounts for the potential influence of caregiving responsibilities on perceptions of the reasonableness of measures such as school and kindergarten closures.
Trust variables
Institutional trust: Institutional trust is measured using four items that assess respondents’ trust in the Parliament, the Ministry of Health, the municipality, and municipal organiations. Respondents rated their trust on an 11-point scale ranging from 0 (“absolutely no trust”) to 10 (“complete trust”), with the survey explicitly referring to trust in the context of the pandemic. This variable captures how trust in public institutions shapes perceptions of restrictive measures, consistent with prior research indicating that higher institutional trust is associated with greater support for public policies during crises (Lachapelle et al., Reference Lachapelle, Bergeron, Nadeau, Daoust, Dassonneville and Bélanger2021; Siegrist and Bearth, Reference Siegrist and Bearth2021; Hrbková and Kudrnáč, Reference Hrbková and Kudrnáč2024).
Interpersonal trust: Interpersonal trust is measured using a single item: “Generally speaking, would you say that most people can be trusted, or that you can’t be too careful in dealing with people?” Responses were recorded on the same 11-point scale as institutional trust. This variable reflects broader societal trust, which has been linked to collective action and acceptance of policy measures (Siegrist and Bearth, Reference Siegrist and Bearth2021).
Fear of COVID-19 illness: Fear of COVID-19 illness is captured using a binary variable, with respondents asked to indicate whether they or their spouse/partner/children had experienced fear of the health consequences of COVID-19 (1 = yes, 0 = no). This variable allows us to examine how fear influences perceptions of the reasonableness of restrictive measures, as fear has been identified as a significant factor in shaping public attitudes toward pandemic responses (Borisova et al., Reference Borisova, Frye, Schoors and Zabolotskiy2023; Hrbková and Kudrnáč, Reference Hrbková and Kudrnáč2024).
Standardised policy: For the analysis in H3b, we constructed the “standardised policy” variable to measure the strictness of COVID-19 policies across the Nordic countries. This variable was derived from the Oxford COVID-19 Government Response Tracker (OxCGRT) (Hale et al., Reference Hale, Angrist, Goldszmidt, Kira, Petherick, Phillips, Webster, Cameron-Blake, Hallas, Majumdar and Tatlow2021), which provides a composite index based on key restrictive measures, such as school closures, workplace closures, travel restrictions, and stay-at-home orders. The variable was normalised on a scale of 0 (least stringent) to 10 (most stringent) to ensure comparability across countries and time periods.
Control variables
To account for potential variation in reasonableness judgements across sociodemographic groups, we included the following control variables:
Age: a continuous variable measuring respondents’ age in years.
Housing type: a categorical variable with three categories: detached house, townhouse/semi-detached house, and apartment. Housing type accounts for differences in living conditions, which may influence how individuals experience restrictions such as quarantine and isolation.
Education level: a categorical variable with four levels: primary education, secondary education, tertiary education, and postgraduate education.
Employment status: a binary variable coded as 1 for respondents who were employed full-time, part-time, or self-employed, and 0 for those who were unemployed or not in the labour force.
These sociodemographic control variables enable us to account for broader individual and structural characteristics that may influence perceptions of reasonableness. Previous research has demonstrated that factors such as age, housing, education, and employment status are significant predictors of public attitudes toward policy measures (Amirkhanyan et al., Reference Amirkhanyan, Meier, Song, Roberts, Park, Vogel, Bellé, Molina and Guul2023; Cardinal et al., Reference Cardinal, Bunn, Schley, Fulton and Keathley2022; Falk et al., Reference Falk, Neumann-Böhme, Sabat and Schreyögg2023; Siegrist and Bearth, Reference Siegrist and Bearth2021).
The selection of dependent and independent variables aligns with the study’s aim to understand how perceptions of the reasonableness of pandemic restrictions are shaped by individual and contextual factors. Drawing on Sefton and Haug (Reference Sefton and Haug2025) a broad range of variables is incorporated to address the research questions and hypotheses. This analysis provides a comprehensive understanding of the factors influencing public attitudes towards restrictive measures and builds on existing literature to advance knowledge of the social and psychological dimensions of crisis management and public policy acceptance.
Analytical approach
This study employs a Most Different Systems Design (MDSD) to analyse perceptions of the reasonableness of COVID-19 restrictions across the Nordic countries (Anckar, Reference Anckar2008). MDSD is particularly suited to this analysis as it enables the exploration of how differences in policy stringency interact with shared cultural, institutional, and welfare-state characteristics to shape public attitudes. The Nordic countries serve as a unique case for such analysis due to their high levels of gender equality, institutional trust, and welfare support, alongside divergent approaches to pandemic management (Andersson and Aylott, Reference Andersson and Aylott2020; Askim and Bergström, Reference Askim and Bergström2022; Nguyen Duy and Stokstad, Reference Nguyen Duy, Stokstad and Haug2024). This divergence provides a comparative context for investigating how variations in policy stringency, mediated by social position, trust, and fear, influence perceptions of reasonableness. See Appendix C for details on policy stringency differences in which the graph illustrates the divergence in policy stringency across Denmark, Finland, Iceland, Norway, and Sweden as measured by the OxCGRT Hale, Noam Angrist, Goldszmidt, et al. (2021).
Frameworks for analysis
This study employed Ordinary Least Square (OLS) regression models to investigate the relationships between gender, caregiving roles, institutional trust, fear of illness, and perceptions of the reasonableness of COVID-19 restrictions. The analysis focused on identifying the direct effects of these predictors on perceptions of reasonableness, while accounting for sociodemographic variables such as marital status, parenthood, and age.
We incorporated interaction terms to explore whether the effects of gender and caregiving roles varied across contexts, such as institutional trust or fear of illness. Specifically, the interaction between gender and caregiving roles (e.g., presence of children in the household) was included to examine how overlapping identities influence public attitudes. The interaction term (gender × presence of children) shows how the effect of having children differs for women compared to men (Ballo, Reference Ballo2020, p. 343). A positive interaction coefficient indicates that having children has a stronger effect on women than on men, while a negative interaction coefficient indicates the opposite. The coefficients for the individual variables (gender and presence of children) reflect their effects only when the other variable equals zero. Thus, the coefficient for “presence of children” shows its effect for men, and the coefficient for “gender” shows its effect for individuals without children.
A statistically significant interaction term means the relationship between gender, caregiving roles, and perceptions of reasonableness is not consistent across groups. Excluding the interaction term would therefore result in a misspecification of these relationships (Ballo, Reference Ballo2020, p. 343).
Additionally, we conducted cross-country comparisons to examine differences in perceptions of reasonableness across the Nordic countries, focusing on the role of governance, policy stringency, fear of illness, and institutional trust in shaping public attitudes. The analysis also included descriptive statistics to provide additional contextual insights into national differences in public perceptions of restrictive measures.
Robustness and multicollinearity
To ensure the reliability of our results, we conducted extensive robustness checks and addressed potential multicollinearity issues. For the main dataset, we examined the Variance Inflation Factor (VIF) for all predictors across models, both separately and combined, to detect multicollinearity. Initially, some predictors, particularly the interaction terms between country dummies and other variables, exhibited high VIF values (above 10), indicating multicollinearity concerns. To address this, continuous variables involved in interaction terms, such as “standardised policy” and the age variables (cage and cage2), were centred by subtracting their means. These adjustments significantly reduced the VIF values to acceptable thresholds (mean VIF = 1.40, all individual VIF values <10) and minimised the risk of inflated standard errors or unreliable estimates caused by overly correlated predictors.
The “standardised policy” variable was merged with the primary dataset, resulting in a combined dataset for analysis for H3b. This merger increased the number of observations as the merge added all observations per year (2020, 2021, and 2022). This increased the representativeness of the sample. Despite the inclusion of additional observations, the direction and significance of key predictors such as trust in institutions and fear of illness, in addition to other independent variables, remained consistent, thus confirming the robustness of the results.
In addition to addressing multicollinearity, we performed robustness checks by testing alternative specifications of the Reasonableness Index, including a three-item version that excluded kindergarten closures (as these were not implemented in Sweden). These checks confirmed that the findings remained consistent across different model formulations, further supporting the robustness and validity of the results. Full details of the VIF analysis, the construction of the standardised policy variable, and the robustness checks are provided in Appendices B–C.
Methodological limitations
While the data provide a robust basis for cross-country analysis, several limitations should be noted. First, the post-pandemic timing of data collection may lead respondents’ evaluations to be influenced by hindsight and post-event rationalisations (Hipp et al., Reference Hipp, Bünning, Munnes and Sauermann2020). However, the explicit framing of survey questions was designed to mitigate this by encouraging respondents to consider both individual and societal experiences throughout the pandemic. Second, the absence of certain measures in specific countries (e.g., kindergarten closures in Sweden) introduces some variation in the comparability of the Reasonableness Index. While robustness checks using a three-item index confirm consistent results (Appendix D), this limitation highlights the importance of interpreting cross-country findings within their specific policy contexts.
Third, this study uses a variable to measure the presence of children under 18 in the household (1 = yes, 0 = no). However, this approach does not distinguish between younger children (e.g., preschool or primary school-aged) and older children (e.g., teenagers), who may place different demands on caregivers and experience restrictions differently. Future research could benefit from capturing more granular data on children’s age categories to better understand how caregiving responsibilities influence perceptions of pandemic restrictions. Fourth, while the survey includes information on respondents’ country of origin in the background section, it was not explicitly designed to problematise ethnicity. More information about the survey can be found in Haug (Reference Haug2024). As a result, this study does not engage in analysis of how ethnicity may intersect with other social positions (e.g., gender, trust, or fear) to shape perceptions of reasonableness. Including explicit measures of ethnicity in future research is indeed warranted and would allow for a more nuanced understanding of how racial and ethnic identities influence public attitudes towards restrictive measures, particularly in the context of the Nordic states, which is indeed very important (cf. Berchet et al., Reference Berchet, Bijlholt and Ando2023; Gostin et al., Reference Gostin, Friedman, Hossain, Mukherjee, Zia-Zarifi, Clinton, Rugege, Buss, Were and Dhai2023).
Finally, the use of a binary gender variable (woman = 1, man = 0) limits the study’s capacity to capture the experiences of non-binary or gender-diverse individuals. Future research should incorporate more inclusive measures of gender. Despite these limitations, we argue that the data provide valuable insights into the multidimensional factors shaping perceptions of reasonableness during a global health crisis.
Results
Descriptive statistics
Trust and fear varied across the Nordic countries (Table 1). Trust in national government was highest in Finland (64.57) and Norway (63.48) and lowest in Iceland (55.19), while fear of COVID-19 illness was highest in Sweden (59.97%) and lowest in Finland (44.11%). Descriptive differences in perceived reasonableness were also modest across countries. Iceland recorded the highest overall mean on the reasonableness index (7.23), whereas Finland recorded the lowest (6.62) (Table 2). Across countries, gender differences in descriptive means were generally small. See table A1 in Appendix A for a full overview over descriptive statistics.
Trust, fear, and perceptions of reasonableness across the Nordic countries, 2022
Table 1. Long description
The table contains eight rows of data across five countries.
* Female respondents (percent): Norway 46.70 percent, Sweden 50.30 percent, Denmark 49.23 percent, Finland 51.21 percent, Iceland 52.64 percent.
* Children under 18 in household (percent): Norway 28.07 percent, Sweden 34.88 percent, Denmark 33.28 percent, Finland 26.86 percent, Iceland 37.43 percent.
* Married or cohabiting (percent): Norway 63.22 percent, Sweden 58.54 percent, Denmark 57.69 percent, Finland 56.07 percent, Iceland 70.20 percent.
* Trust in national government (scale 0 to 100): Finland has the highest trust at 64.568, followed by Norway at 63.483, Denmark at 59.984, Sweden at 57.248, and Iceland at 55.195.
* Trust in municipalities (scale 0 to 100): Norway 65.615, Sweden 58.286, Denmark 61.611, Finland 65.594, Iceland 59.381.
* Interpersonal trust (scale 0 to 10): All countries score high and similarly, ranging from 7.257 in Iceland to 7.667 in Norway.
* Fear of C O V I D 19 illness (percent): Sweden reports the highest fear at 59.97 percent, followed by Iceland at 53.92 percent, Denmark at 53.48 percent, Finland at 44.11 percent, and Norway at 42.94 percent.
* Total respondents (N): Norway 1289, Sweden 1304, Denmark 1292, Finland 1240, Iceland 549.
Descriptive statistics for perceptions of reasonableness of COVID-19 restrictions by gender and country, Nordic countries, 2022
Table 2. Long description
The table contains five columns for countries (Norway, Sweden, Denmark, Finland, and Iceland) and five rows for policy measures. Each cell provides scores for Males (M), Females (F), and a Total (Tot) on a scale of 0 to 10.
* Home office: Scores range from a low of 7.037 in Finland to a high of 7.718 in Iceland. Females generally rated this higher than males, notably in Iceland (7.96) and Sweden (7.601).
* Home school: Total scores range from 6.559 in Norway to 7.177 in Iceland. In Norway and Finland, males rated this more reasonable than females, while the opposite is true for Sweden, Denmark, and Iceland.
* Leisure activities: Total scores range from 6.535 in Norway to 7.377 in Iceland. Iceland shows the highest gender gap with females at 7.62 and males at 7.097.
* Kindergarten closures: Sweden has no data for this measure. Other totals range from 6.473 in Norway to 6.966 in Iceland. In Norway and Finland, males rated this higher than females.
* Reasonableness index: This summary row shows Iceland with the highest overall reasonableness score (7.234) and Finland with the lowest (6.625). Females in Iceland (7.455) and Sweden (7.156) provided the highest index scores across the dataset.
Note: Higher scores indicate that respondents perceived the restriction as more reasonable (0 = completely unreasonable, 10 = fully reasonable).
In terms of gendered differences, Iceland recorded the highest mean scores across policy measures, with a reasonableness index of 7.23 (males = 6.99, females = 7.45), while Finland reported the lowest (6.62; males = 6.74, females = 6.51). These findings highlight the critical role of national context in shaping public perceptions, with Iceland’s higher ratings potentially reflecting strong social cohesion, and Finland’s lower scores suggesting unmet caregiving needs or dissatisfaction with policy stringency.
Multivariate regression analysis
H1: Gender and perceived reasonableness
The initial descriptive comparisons suggested small gender differences in perceptions of the reasonableness of COVID-19 restriction measures. However, adjusted models showed little overall gender difference in the pooled sample. Some heterogeneity emerged by parenthood and education, as reported below.
H1a: Gender and perceived reasonableness
Figure 1 presents adjusted predicted margins for perceived reasonableness by gender in the pooled sample. Men had a slightly higher predicted value (6.64, 95% CI: 6.57–6.71) than women (6.60, 95% CI: 6.52–6.67), but the confidence intervals overlapped, indicating little difference at the pooled level (Figure 1).
H1a: Adjusted predicted margins for perceived reasonableness of COVID-19 restriction measures by gender in the pooled sample from Denmark, Finland, Iceland, Norway, and Sweden, 2022. Estimates are based on the full OLS model (Table 3).
Note: Points represent predicted values; whiskers indicate 95% confidence intervals.
Figure 1. Long description
The vertical Y axis is labeled Linear prediction and ranges from 6.5 to 6.7 with increments of 0.05. The horizontal X axis is labeled Male 0 Female 1.
Two data points are plotted in green and connected by a downward-sloping line.
* The first point at X equals 0 (Male) has a predicted value of approximately 6.64. It includes a vertical error bar extending from roughly 6.57 to 6.71.
* The second point at X equals 1 (Female) has a predicted value of approximately 6.60. It includes a vertical error bar extending from roughly 6.52 to 6.68.
The line connecting the two points shows a slight decrease in the linear prediction from males to females. The title at the top reads Gender Differences in Perceived Reasonableness.
H1b: Parenthood and gender differences in perceptions of reasonableness
Figure 2 shows the predicted margins for the interaction between gender and parenthood. For men, predicted values were similar among those without children (6.62, 95% CI: 6.53–6.72) and those with children (6.66, 95% CI: 6.54–6.78). Among women, the predicted value was 6.63 (95% CI: 6.54–6.73) for those without children and 6.53 (95% CI: 6.39–6.66) for those with children. Overall, the results indicate a modest gendered pattern, with parenthood associated with somewhat lower perceived reasonableness among women but not among men (Figure 2).
H1b: Adjusted predicted margins for perceived reasonableness of COVID-19 restriction measures by gender and parenthood in the pooled sample from Denmark, Finland, Iceland, Norway, and Sweden, 2022. Estimates are based on the interaction model.
Note: Points represent predicted values; whiskers indicate 95% confidence intervals.
Figure 2. Long description
The graph is titled Parenthood and Gender Differences in Reasonableness. The Y axis is labeled Linear prediction and ranges from 6.4 to 6.8. The X axis is labeled Male 0 Female 1 with tick marks at 0 and 1. Two lines with error bars represent parenthood status: a green line for No and an orange line for Yes.
* For Males at X equals 0: The orange line (Yes) starts higher at approximately 6.66 with a wide confidence interval. The green line (No) starts lower at approximately 6.62 with a narrower confidence interval.
* For Females at X equals 1: The green line (No) shows a slight linear increase to approximately 6.64. The orange line (Yes) shows a linear decrease to approximately 6.53.
* The lines intersect between the Male and Female categories. For non-parents, the reasonableness prediction is relatively stable across genders, while for parents, there is a notable decline from males to females.
Gender differences across education levels.
To assess whether gender differences in perceived reasonableness varied by educational attainment, we estimated interaction terms between gender and education. Overall, gender differences were small across most education categories. Among respondents with elementary education, women had a slightly higher predicted value (6.88) than men (6.68). A larger gender difference was observed in the “Don’t know” category, which refers to respondents who did not report their educational attainment: men in this category had a higher predicted value (7.13) than women (5.89). For the remaining education categories, including secondary, undergraduate/vocational, and master’s/graduate education, differences between men and women were minimal (Figure C1).
H2: Parenthood and perceived reasonableness
Parents with children under 18 generally rated school and kindergarten closures as slightly less reasonable than respondents without children, although the size and direction of these differences varied across subgroups and countries. To keep the presentation focused, the main text presents the central pattern for school closures, while additional heterogeneity analyses are reported in Appendix C.
H2a: Parenthood and perceived reasonableness
Figure 3 shows predicted margins for perceived reasonableness of school closures by parenthood status across the five Nordic countries. Differences between respondents with and without children under 18 were generally modest, but the pattern varied across countries. Sweden and Denmark showed little difference by parenthood status, Norway and Finland showed slightly lower predicted values among respondents with children, while Iceland showed a higher predicted value among respondents with children (Figure 3).
H2a: Adjusted predicted margins for perceived reasonableness of school closures by parenthood status across Denmark, Finland, Iceland, Norway, and Sweden, 2022. Estimates are based on the interaction between parenthood and country.
Note: Points represent predicted values for respondents with and without children under 18; whiskers indicate 95% confidence intervals.
Figure 3. Long description
The X-axis is labeled Children (Yes) with two categories: No and Yes. The Y-axis is labeled Linear prediction, ranging from 6.2 to 7.0. Five colored lines with error bars represent different countries:
* Iceland (light blue): Shows a significant upward trend from approximately 6.68 for those without children to 6.83 for those with children. It has the largest confidence interval at the Yes position.
* Sweden (orange): Remains nearly flat at approximately 6.7 for both categories.
* Denmark (dark blue): Shows a very slight downward trend, starting just below 6.65 and ending slightly lower.
* Norway (green): Shows a downward trend from approximately 6.61 to 6.55.
* Finland (maroon): Positioned lowest on the graph, showing a slight downward trend from approximately 6.47 to 6.45.
A legend on the right side identifies the colors for Norway, Sweden, Denmark, Finland, and Iceland.
A similar overall pattern was observed for kindergarten closures; these results are reported in Appendix C (Figure C2). Additional analyses by family structure and among single-parent households suggested some heterogeneity in the association between parenthood and perceived reasonableness, but these patterns were modest in the adjusted models and are therefore reported in Appendix C (Figures C3–C6).
H3: Cross-country variation in perceived reasonableness
The Nordic countries differed in their pandemic responses, providing a useful comparative context for examining whether perceived reasonableness varied across country settings. We therefore examined cross-country differences in perceived reasonableness and the role of institutional trust and fear of illness in the pooled models.
H3a: Perceived reasonableness across countries
Some cross-country differences emerged in perceptions of reasonableness. Iceland showed the highest predicted value, followed by Sweden and Denmark, while Norway and Finland showed lower predicted values. Although some differences across countries were observed, the overall pattern remained broadly similar, which suggests that differences in pandemic response strategies alone did not produce sharp divergence in public perceptions of reasonableness (Figure 4).
H3a: Adjusted predicted margins for perceived reasonableness of COVID-19 restrictions across Norway, Sweden, Denmark, Finland, and Iceland, 2022.
Note: Points represent predicted values; whiskers indicate 95% confidence intervals.
Figure 4. Long description
The Y-axis is labeled Linear prediction and ranges from 6.4 to 7. The X-axis is labeled Children (Yes) with two categories: No and Yes. A legend on the right identifies four countries by color: Norway (green), Denmark (orange), Finland (blue), and Iceland (maroon).
* Iceland: Starts at the highest point (approximately 6.85) for ‘No’ and shows a slight downward slope to approximately 6.76 for ‘Yes’.
* Denmark: Starts at approximately 6.61 for ‘No’ and slopes downward to approximately 6.55 for ‘Yes’.
* Finland: Starts at approximately 6.55 for ‘No’ and shows the steepest downward slope to approximately 6.46 for ‘Yes’.
* Norway: Starts at approximately 6.52 for ‘No’ and remains nearly flat, ending at approximately 6.52 for ‘Yes’.
Vertical whiskers representing 95 percent confidence intervals are attached to each data point. The whiskers for Iceland are the longest, while those for Norway are the shortest.
H3b: Interaction between country and policy stringency levels
Policy stringency did not significantly predict perceived reasonableness (p > 0.05), and the interaction between country and policy stringency was likewise non-significant. Across low, medium, and high levels of policy stringency, the relative country pattern remained unchanged, suggesting that policy stringency alone did not account for public evaluations of reasonableness (Figure 5). The same null finding for policy stringency was observed in robustness analyses excluding Sweden (Appendix D).
H3b: Adjusted predicted margins for perceived reasonableness of COVID-19 restrictions across the Nordic countries at three levels of policy stringency.
Note: Points represent predicted values; whiskers indicate 95% confidence intervals.
Figure 5. Long description
The X-axis is labeled Marital Status with four categories: Single, Partnered, With parents, and Not specified. The Y-axis is labeled Linear prediction ranging from 5.5 to 7.5.
Four data series are plotted with points and vertical error bars representing 95 percent confidence intervals:
* Two-Parent w/o Children (green line with horizontal tick markers): Remains relatively stable between 6.5 and 6.7 across all categories.
* Two-Parent w/ Children (orange line with horizontal tick markers): Follows a similar stable path to the green line.
* Single Parent w/o Children (green line with circular markers): Starts at 6.6 for Single, stays at 6.6 for Partnered, dips to 6.4 for With parents, and rises back to 6.6 for Not specified.
* Single Parent w/ Children (orange line with circular markers): Starts at 6.7 for Single, drops slightly to 6.6 for Partnered, reaches a low of 6.3 for With parents, and rises to 6.5 for Not specified.
The Not specified category for Single Parent w/ Children shows the largest error bar, extending from approximately 5.5 to 7.5.
Importantly, institutional trust and fear of illness emerged as significant predictors across all models. A one-unit increase in trust was associated with a 0.056-point increase in perceived reasonableness (p < 0.001), while respondents reporting fear of illness rated restrictions 0.622 points higher on average (p < 0.001; Table 3; Figures C7).
Key results from pooled OLS models*
Table 3. Long description
The table presents coefficients and standard errors in parentheses for nine models labeled 1 through 9.
Header Row:
(1) H 1 Base, (2) H 1 Full, (3) H 2 a School, (4) H 2 a Kindergarten, (5) H 2 b School, (6) H 2 b Kindergarten, (7) H 2 c School, (8) H 2 c Kindergarten, (9) H 3 a Reasonableness.
Key Variables and Coefficients:
* Female: Values range from -0.303 to 0.015. Significant negative effects are seen in models 3, 4, 5, 6, and 8.
* Yes children: Values range from -0.267 to 0.148. A significant negative effect of -0.267 is noted in model 5.
* Trust index (mean of Q 2): Shows a consistent, highly significant positive effect across all models, ranging from 0.054 to 0.060.
* Fear of illness: Shows a consistent, highly significant positive effect across all models, ranging from 0.524 to 0.673.
* S E: Significant positive coefficients in models 3 (0.771), 5 (0.711), 7 (0.711), and 9 (0.604).
* D K: Significant positive coefficients in models 3 through 9, ranging from 0.410 to 0.556.
* F I: Significant positive coefficient in model 3 (0.231); other models are non-significant.
* I S: Highly significant positive coefficients in models 3 through 9, ranging from 0.556 to 0.994.
Model Statistics:
* R-squared: Values range from 0.267 to 0.348.
* Observations: Sample sizes range from 3635 to 5015.
Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001.
*The models correspond to the four individual policy measures, home office mandates, school closures, leisure activity restrictions, and kindergarten closures, and the composite Reasonableness Index. The coefficients represent the effect of each predictor (i.e., independent variable) on perceptions of reasonableness, controlling for other variables in the model. Standard errors are reported in parentheses, and statistically significant coefficients are marked at the 0.05 (*), 0.01(**), and 0.001(***) levels. Mean VIF 1.31. All variables, variables display VIF under 2.
Overall, the pooled OLS models showed that institutional trust and fear of illness were consistently and positively associated with perceived reasonableness across outcomes, whereas gender and parenthood effects were more mixed and outcome specific. Model fit ranged from R-squared = 0.267 to 0.348 (Table 3).
Discussion
This study examined how gender, parenthood, institutional trust, fear of illness, and national context were associated with perceptions of the reasonableness of COVID-19 restrictions in five Nordic countries. Overall, the findings suggest that public evaluations of restrictive measures were shaped less by any single demographic factor than by the intersection of caregiving responsibilities, trust, fear, and country context. At the same time, the overall Nordic pattern remained more similar than different, despite variation in policy responses across countries.
Gender, parenthood, and caregiving contexts
In the pooled adjusted models, overall gender differences in perceived reasonableness were small. This is an important finding in itself, as it suggests that women and men did not differ markedly in their general evaluations of COVID-19 restrictions once we considered other factors. However, some differences (i.e., heterogeneity) emerged when gender was considered together with parenthood and education (the interaction terms). In particular, parenthood was associated with somewhat lower perceived reasonableness among women, whereas differences among men were minimal. This pattern is consistent with the possibility that the practical consequences of restrictions were experienced differently depending on caregiving responsibilities (cf. Galasso et al., Reference Galasso, Pons, Profeta, Becher, Brouard and Foucault2020; Johnston et al., Reference Johnston, Mohammed and Van Der Linden2020).
The analyses of school and kindergarten closures point in the same general direction. Respondents with children under 18 often rated these measures as slightly less reasonable than respondents without children, although the size and direction of the differences were not uniform across all countries and subgroup analyses (see Appendix C). These findings are in line with previous research showing that the closure of schools and childcare institutions had uneven consequences across households during the pandemic, often increasing the everyday burden of combining paid work and caregiving (Fortier, Reference Fortier2020; Petts et al., Reference Petts, Carlson and Pepin2021). In this sense, support for restrictive measures appears to have been shaped not only by health concerns, but also by how directly those measures affected family life and care arrangements.
The education analyses also suggest that gender differences were generally modest across most education groups, with somewhat clearer differences among respondents with elementary education and in the “Don’t know” category. Thus, this pattern supports an intersectional interpretation: the association between gender and perceived reasonableness varied across groups and appeared to depend in part on educational attainment, caregiving position, and other contextual factors.
Trust and fear of illness as key predictors
Institutional trust and fear of illness emerged as the most consistent predictors of perceived reasonableness across the models. Higher institutional trust was associated with higher support for restrictive measures, while fear of illness was likewise associated with perceiving restrictions as more reasonable. These findings align with research showing that governance legitimacy during crises depends not only on state capacity, but also on whether citizens perceive institutions as credible, crisis measures as proportionate, and institutions acting in the public interest (Christensen et al., Reference Christensen, Lægreid and Rykkja2016; Christensen and Lægreid, Reference Christensen and Lægreid2020).
Trust may help explain why restrictive measures were accepted even when they imposed substantial burdens on everyday life. When citizens perceive institutions as competent and well-intentioned, restrictions may be interpreted as legitimate and necessary rather than excessive or arbitrary. Fear of illness appears to operate differently but in a complementary way: respondents who were more concerned about illness also tended to view restrictions as more reasonable. This suggests that support for restrictions was shaped both by confidence in governing institutions and by perceptions of health risk.
These findings are consistent with broader research on crisis management during the COVID-19 pandemic, which emphasises the importance of transparent communication, institutional credibility, and perceived proportionality for sustaining public compliance and support (Christensen and Lægreid, Reference Christensen and Lægreid2020; Fimreite et al., Reference Fimreite, Løvseth, Lægreid and Rykkja2024; Hrbková and Kudrnáč, Reference Hrbková and Kudrnáč2024). In this sense, trust and fear of illness appear to have captured different but related dimensions of public support: fear of illness may have increased the perceived need for protective measures, whereas trust may have shaped whether those measures were seen as fair, proportionate, and legitimate.
More broadly, the findings support the view that crisis responses are judged not only by their formal design, but also by how they are interpreted by citizens. Public support for restrictions appears to have depended not only on policy content, but also on whether institutions were trusted and the health threat was perceived as serious. Together, these results highlight the importance of maintaining institutional credibility and socially sensitive crisis communication when restrictive measures are introduced.
Cross-country differences in a shared Nordic context
Some cross-country differences were observed, particularly in descriptive levels of perceived reasonableness and in the school-closure models. Iceland generally showed higher predicted values, whereas Finland and Norway tended to show lower values in some of the models. At the same time, these differences should be interpreted with caution. The overall pattern across the Nordic countries was broadly similar, and the results do not suggest markedly divergent public understandings of reasonableness despite important differences in pandemic response strategies.
This is a notable finding in itself. One possible interpretation is that the shared institutional features of the Nordic countries, including relatively strong welfare states, comparatively high institutional trust, and well-developed public sectors, may have contributed to broadly similar evaluative frameworks even where specific policy measures differed. It is also consistent with the broader finding that trust and fear of illness were associated with perceived reasonableness across models. We had expected that diverging levels of policy stringency would be associated with sharper divergence in public perceptions, but the findings did not support this expectation.
The results therefore add nuance to arguments that more lenient or stricter national strategies would necessarily produce correspondingly higher or lower public support. In this study, perceived reasonableness was not strongly structured by policy stringency alone. Rather, support appears to have reflected a combination of trust, fear, and the everyday consequences of specific restrictions.
Implications for crisis policy
The findings have several implications for crisis policy. First, they suggest that restrictive measures are not judged only in terms of their epidemiological rationale, but also in relation to how they are experienced in everyday life. Measures such as school and kindergarten closures may be evaluated differently from other restrictions because they redistribute practical burdens across households in unequal ways. This means that perceptions of reasonableness are shaped not only by public health concerns, but also by whether restrictions are experienced as proportionate in social terms.
Second, the consistent role of institutional trust highlights the importance of governance legitimacy during crises. Public support for restrictive measures is unlikely to depend only on formal rules or state capacity. It also depends on whether authorities are perceived as transparent, credible, and fair. Trust may shape whether restrictions are interpreted as necessary and proportionate rather than arbitrary or excessive.
Third, the findings suggest that crisis communication and policy design should acknowledge unequal social consequences. Even when restrictive measures are considered necessary, they may be perceived differently by groups who bear a disproportionate share of their practical costs. This is particularly important for households with caregiving responsibilities, for whom restrictive measures may create additional strain that is not evenly distributed across the population. In this sense, socially sensitive and context-aware policy design is not only normatively important, but also relevant for maintaining public legitimacy and compliance.
More broadly, the findings suggest that crisis governance cannot be understood only in terms of how strict policies are. It also depends on whether restrictions are perceived as legitimate, reasonable, and fair in their everyday consequences. In this sense, proportionality is not only a legal or administrative principle, but also a social and political one: restrictions must be experienced as reasonable in relation to the burdens they impose. Restrictive measures may therefore be more likely to gain public support when governments combine effective public health responses with clear communication and attention to social equity.
Limitations and directions for future research
This study has several limitations. First, the analyses are observational and cross-sectional, and causal conclusions therefore cannot be drawn. The study identifies associations between demographic position, trust, fear, and perceived reasonableness, but it cannot determine whether these factors directly caused attitudes towards restrictions.
Second, some subgroup analyses should be interpreted cautiously, as several categories are relatively small and therefore less suited to strong substantive conclusions. This is particularly relevant for detailed interaction analyses and for the “Don’t know” category in the education variable.
Third, the data were collected in 2022 and capture retrospective evaluations of restrictions after different phases of the pandemic had already unfolded. Responses may therefore reflect both lived experiences and later reinterpretations. In addition, perceived reasonableness should not be treated as identical to actual compliance behaviour.
Finally, although the comparative design is a strength, country-level conclusions should remain cautious. With only five countries, the study is better suited to identifying broad comparative patterns than to making strong claims about country-level mechanisms. For instance, the analyses indicate that some countries, such as Iceland, tended to show higher predicted values than others in certain models, but they cannot establish which specific national features explain those differences.
Future research could examine how perceptions of reasonableness change over time and how they are shaped by household structure, labour-market position, policy design, and actual compliance behaviour.
Conclusion
This study examined how gender, parenthood, trust, fear of illness, and national context were associated with perceptions of the reasonableness of COVID-19 restrictions in the Nordic countries. The findings suggest that public support for restrictive measures was shaped not only by policy context, but also by how restrictions were experienced in everyday life and whether they were perceived as legitimate and proportionate.
Across the analyses, institutional trust and fear of illness emerged as the most consistent predictors of perceived reasonableness. Gender differences were generally modest in the pooled models, but some variation appeared when gender was considered together with parenthood and educational attainment. Parents often viewed school and kindergarten closures as somewhat less reasonable than respondents without children, which suggests that the practical consequences of restrictions mattered for how they were evaluated. At the same time, the overall pattern across the Nordic countries remained broadly similar despite differences in pandemic response strategies.
Taken together, the findings underline the importance of combining public health effectiveness with institutional legitimacy and social sensitivity in crisis policy. Restrictive measures are more likely to be seen as reasonable when governments are trusted, when risks are understood as serious, and when the unequal burdens of restrictions are acknowledged. The study therefore points to the value of crisis responses that are not only effective, but also perceived as fair, proportionate, and attentive to everyday social realities.
Acknowledgements
This paper is part of the POLYGOV project, funded by the Norwegian Research Council (Project Number: 326136). The POLYGOV project complies with national ethical guidelines (Sikt reference 701017).
We sincerely thank the reviewers and editors of the Journal of International and Comparative Social Policy for their valuable feedback, which has substantially improved this manuscript.
The authors used Elicit (Pro) in a limited manner to support the identification of potentially relevant literature. Elicit was not used to generate the literature review itself. The authors also used Sikt KI-chat, an AI-based tool provided by the Norwegian Agency for Shared Services in Education and Research (Sikt), in a limited manner to support language refinement, Stata syntax for figures and model presentation, and clarification of statistical output. AI was not used to generate data, conduct analyses independently, or determine the study’s conclusions. All analyses, interpretations, and final wording were reviewed and verified by the authors, who take full responsibility for the manuscript.
A. Appendix
Descriptive statistics by country and gender, mean value and share
Table A1. Long description
The table presents mean values and shares for various social and demographic indicators across five Nordic countries. The columns are divided by country: Norway, Sweden, Denmark, Finland, and Iceland, each with sub-columns for M (Male), F (Female), and Total.
Key rows include:
* Home office: Mean values range from 7.037 in Finland to 7.718 in Iceland.
* Home school: Mean values range from 6.559 in Norway to 7.177 in Iceland.
* Leisure activities: Mean values range from 6.535 in Norway to 7.376 in Iceland.
* Kindergarten closure: Data is missing for Sweden; other totals range from 6.473 to 6.966.
* Composite index: Totals range from 6.625 in Finland to 7.234 in Iceland.
* Female share: Norway 46.70%, Sweden 50.30%, Denmark 49.23%, Finland 51.21%, and Iceland 52.64%.
* Children under 18 (Yes/No): Totals range from 26.86% in Finland to 37.43% in Iceland.
* Married/cohabiting: Totals range from 56.07% in Finland to 70.20% in Iceland.
* Age: Mean ages range from 46.167 in Denmark to 48.975 in Norway.
* Education levels: Categorized into Elementary, Secondary, Undergrad/Vocational, and Master/graduate shares.
* Employment: Share of ‘Yes’ responses ranges from 1.85% in Iceland to 10.12% in Finland.
* Residence type: Shares for Detached house, Townhouse/Semi-detached, and Apartment.
* Trust levels: Mean scores (0-100 scale) for Parliament, Government, Ministry of Health, Municipality, and Municipal organizations. Trust in Parliament is highest in Finland (64.636) and lowest in Iceland (55.85).
* Interpersonal trust: Mean values range from 7.257 in Iceland to 7.636 in Norway.
* Fear covid-19: Share of ‘Yes’ responses is highest in Sweden (59.97%) and lowest in Finland (44.11%).
* Sample size (N): Norway (1289), Sweden (1304), Denmark (1292), Finland (1240), and Iceland (549).
B. Appendix
Combined models across hypotheses
Table B1. Long description
A complex regression table with 9 columns labeled 1 through 9, corresponding to hypotheses H 1 Base, H 1 Full, H 2 a School, H 2 a Kindergarten, H 2 b School, H 2 b Kindergarten, H 2 c School, H 2 c Kindergarten, and H 3 a Reasonableness.
Key findings include:
* Female: Coefficients range from -0.303 in model 8 to 0.011 in model 2. Significant negative correlations are found in models 3, 4, 5, 6, and 8.
* Yes children: Shows a significant negative coefficient of -0.267 in model 5.
* With parents: Shows significant negative coefficients in models 1, 2, 4, 8, and 9, with the strongest being -0.568 in model 4.
* Trust index (mean of Q 2): Consistently positive and highly significant across all models, ranging from 0.055 to 0.060.
* Fear of illness: Consistently positive and highly significant across all models, with coefficients between 0.524 and 0.679.
* Age centred: Positive and significant in most models, except 3, 5, and 7.
* Interaction terms: Significant negative interactions for Yes children and I S in models 3 (-0.646) and 4 (-0.448).
* Model Statistics: R-squared values range from 0.267 to 0.348. Total observations vary between 3635 and 4760. Standard errors are provided in parentheses below each coefficient. Significance levels are indicated by asterisks: * p < 0.1, ** p < 0.05, *** p < 0.01.
Standard errors in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01. Mean VIF 1.31.
Regression results examining the interaction between education level and gender on perceptions of the reasonableness of COVID-19 restrictions. This additional table complements the main analysis in Appendix B by providing a detailed breakdown of how education, gender, and other covariates such as trust, fear of illness, and age influence perceptions. Standard errors are reported in parentheses, and significance levels are indicated (* p < 0.05, ** p < 0.01, *** p < 0.001)”
Table B2. Long description
The table lists regression coefficients with standard errors in parentheses.
Education levels (Reference: Elementary school at 0.000):
* Secondary school/Upper secondary school: 0.024 (0.116)
* Bachelor/Undergrad/Vocational education: minus 0.084 (0.122)
* Master/Graduate programme: minus 0.110 (0.123)
* Do not know: 0.458 (0.499)
Gender (Reference: Male at 0.000):
* Female: 0.202 (0.174)
Interactions (Education # Gender):
* Secondary school/Upper secondary school # Female: minus 0.266 (0.194)
* Bachelor/Undergrad/Vocational education # Female: minus 0.346 (0.201)
* Master/Graduate programme # Female (Yes) = 1: minus 0.124 (0.209)
* Do not know # Female: minus 1.444* (0.561)
Other Covariates:
* Yes (Children in household): minus 0.034 (0.064)
* Partnered: 0.025 (0.060)
* With parents: minus 0.245 (0.129)
* Not specified: minus 0.048 (0.286)
* Trust in national government: 0.055*** (0.002)
* Fear of illness: 0.674*** (0.055)
* Age (centred): 0.009*** (0.002)
* Age^2 (centred): minus 0.000 (0.000)
* Constant: 2.850*** (0.154)
Total Observations: 4534. Significance levels: * p < 0.05, ** p < 0.01, *** p < 0.001.
Standard errors in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001
C. Appendix
Adjusted predicted margins for perceived reasonableness of COVID-19 restriction measures by educational level, pooled sample from Denmark, Finland, Iceland, Norway, and Sweden, 2022. Note: Estimates are based on the education model and adjusted for gender and other covariates. Points represent predicted values; whiskers indicate 95% confidence intervals.
Figure C1. Long description
The Y axis is labeled Linear prediction and ranges from 5.5 to 7.5. The X axis is labeled Marital Status and includes four categories from left to right: Single, Partnered, With parents, and Not specified.
Four data series are plotted with points and 95 percent confidence interval whiskers:
* Two-Parent w/o Children (green line with horizontal bar markers)
* Two-Parent w/ Children (orange line with horizontal bar markers)
* Single Parent w/o Children (green line with circular markers)
* Single Parent w/ Children (orange line with circular markers)
Key trends:
* For Single and Partnered statuses, all groups cluster closely between 6.5 and 6.7.
* In the With parents category, there is a noticeable dip for those with children (orange lines), dropping to approximately 6.3, while those without children (green lines) stay higher at approximately 6.5.
* In the Not specified category, the predictions rise back toward 6.5 to 6.7, but the confidence intervals become significantly wider, especially for the Single Parent w/ Children group, spanning from 5.5 to over 7.5.
H2b: Kindergarten closures: Interaction of parenthood and country. This figure shows the predicted margins for parents and non-parents in perceptions of the reasonableness of kindergarten closures across countries. Note: Non-parents consistently rated kindergarten closures as slightly more reasonable than parents, with the smallest differences observed in Norway and Denmark. Iceland reported the highest overall ratings for both groups, reflecting stronger public consensus on the reasonableness of these measures.
Figure C2. Long description
The graph features a Y-axis labeled Linear prediction ranging from 6.4 to 7.2 and an X-axis labeled Male 0 Female 1. Two data series are plotted with error bars.
* The Single Fathers series, represented by a green line with circular markers, starts at approximately 6.75 for Male 0 and shows a linear increase to approximately 6.9 for Female 1.
* The Single Mothers series, represented by an orange line with circular markers, starts at approximately 6.64 for Male 0 and shows a slight linear decrease to approximately 6.54 for Female 1.
A legend on the right side identifies the green line as Single Fathers and the orange line as Single Mothers. The error bars for both groups are wider at the Female 1 position than at the Male 0 position.
The margin plots for both school and kindergarten closures visually demonstrate these trends. Each line represents a specific family structure (e.g., single, partnered, living with parents), and the colours differentiate between respondents with and without children. The plots highlight that while non-parents consistently rated these measures as more reasonable, the differences between parents and non-parents were smallest for single respondents and largest for those living with their parents. We can think of the last category as multigenerational households, and that respondents living with their parents likely reported lower perceptions of reasonableness due to shared caregiving dynamics or plausibly also added responsibilities of managing multigenerational households.
H2c: School closures – interaction of family structure and parenthood. Note: This figure shows the predicted margins for the interaction between family structure and parenthood in perceptions of school closures.
Figure C3. Long description
The graph features a y-axis labeled Linear prediction ranging from 6.4 to 7.2 and an x-axis labeled Male 0 Female 1. A legend to the right identifies two groups: Single Fathers represented by a green line with circular markers and Single Mothers represented by an orange line with circular markers. Both lines include vertical error bars at each data point.
* For the Single Fathers green line: The prediction starts at approximately 6.75 for Male 0 and shows a linear increase to approximately 6.9 for Female 1.
* For the Single Mothers orange line: The prediction starts at approximately 6.63 for Male 0 and shows a slight linear decrease to approximately 6.53 for Female 1.
The error bars for Single Fathers are generally higher on the y-axis than those for Single Mothers, with the gap between the two groups widening as the x-axis moves from 0 to 1.
Adjusted predicted margins for perceived reasonableness of kindergarten closures by family structure and parenthood status in the pooled sample from Denmark, Finland, Iceland, Norway, and Sweden, 2022. Note: The “Not specified” marital-status category was omitted from the figure because it reflects missing information rather than a substantively interpretable family-structure category. Points represent predicted values; whiskers indicate 95% confidence intervals.
Figure C4. Long description
The graph is titled Perceived Reasonableness Across Countries. The y-axis is labeled Linear prediction with a scale from 6.2 to 7.2 in increments of 0.2. The x-axis is labeled countrycode underscore num and lists five countries as initialisms from left to right.
* N O (Norway) has a predicted value of approximately 6.32 with a vertical error bar extending from 6.26 to 6.38.
* S E (Sweden) shows a sharp increase to a predicted value of approximately 6.92 with an error bar from 6.86 to 6.98.
* D K (Denmark) shows a decrease to a predicted value of approximately 6.73 with an error bar from 6.67 to 6.79.
* F I (Finland) shows a sharp decrease to the lowest point on the graph at approximately 6.28 with an error bar from 6.21 to 6.34.
* I S (Iceland) shows a sharp increase to the highest point on the graph at approximately 7.05 with an error bar from 6.94 to 7.16.
A solid green line connects the data points, forming a zigzag pattern that peaks at S E and I S and troughs at N O and F I.
H2c Kindergarten closures – single mothers versus single fathers. Note: This figure illustrates the predicted margins for single mothers and single fathers in perceptions of the reasonableness of kindergarten closures.
Figure C5. Long description
A multi-panel figure with three panels titled Low Stringency, Medium Stringency, and High Stringency. All panels share a Y axis labeled Linear prediction and an X axis listing five countries: Norway, Sweden, Denmark, Finland, and Iceland.
* In the Low Stringency panel, the Y axis ranges from 5.5 to 7.5. The data shows a jagged trend: Norway starts at approximately 6.3, rises to 6.9 for Sweden, drops slightly for Denmark, falls to 6.3 for Finland, and peaks at 7.0 for Iceland. Each point includes vertical error bars.
* In the Medium Stringency panel, the Y axis ranges from 6.2 to 7.2. The trend is similar: Norway is at 6.3, Sweden rises to 6.9, Denmark drops to 6.7, Finland falls to 6.3, and Iceland peaks at 7.0.
* In the High Stringency panel, the Y axis ranges from 6 to 7.5. The pattern repeats: Norway is at 6.3, Sweden rises to 6.9, Denmark drops to 6.7, Finland falls to 6.3, and Iceland peaks at 7.0.
Across all three panels, Sweden and Iceland consistently show the highest linear predictions, while Norway and Finland consistently show the lowest.
Effect of trust on perceived reasonableness of restrictions. Note: This figure illustrates the positive and statistically significant association between trust in institutions and perceptions of the reasonableness of COVID-19 restrictions. A one-unit increase in the trust index is associated with a 0.056-point increase in perceived reasonableness (p < 0.001). Error bars represent 95% confidence intervals.
Figure C6. Long description
The horizontal X axis is labeled Trust index mean of Q 2 and ranges from 1 to 10. The vertical Y axis is labeled Linear prediction and ranges from 3 to 3.8 in increments of 0.2. A dark green line shows a steady linear increase across the plot. Ten data points are plotted as solid green circles at each integer on the X axis. Each point includes vertical error bars representing 95 percent confidence intervals. The first data point at X equals 1 has a Y value of approximately 3.14. The line ascends diagonally to the final data point at X equals 10, which has a Y value of approximately 3.64. The vertical spread of the error bars remains relatively consistent across all ten data points.
Adjusted predicted margins for perceived reasonableness of COVID-19 restrictions by fear of illness in the pooled sample from Denmark, Finland, Iceland, Norway, and Sweden, 2022. Note: Points represent predicted values; whiskers indicate 95% confidence intervals.
Figure C7. Long description
The graph is titled Effect of Standardized Fear on Perceived Reasonableness. The horizontal X axis is labeled Standardized values of Fear underscore illness and ranges from minus 3 to 3 in increments of 1. The vertical Y axis is labeled Linear prediction and ranges from 5.5 to 7.5 in increments of 0.5.
A solid green line shows a constant linear increase from the bottom-left to the top-right. Seven data points are plotted along this line with vertical error bars representing 95 percent confidence intervals.
Specific data points include:
* At X equals minus 3, the linear prediction is approximately 5.6.
* At X equals minus 2, the linear prediction is approximately 5.9.
* At X equals minus 1, the linear prediction is approximately 6.3.
* At X equals 0, the linear prediction is approximately 6.6.
* At X equals 1, the linear prediction is approximately 6.9.
* At X equals 2, the linear prediction is approximately 7.3.
* At X equals 3, the linear prediction is approximately 7.6.
The confidence intervals are narrowest at the center (X equals 0) and slightly wider at the extremes of the X axis.
D. Appendix
This table presents regression analysis results for H3b (Policy Stringency and Perceptions of Reasonableness) using the merged dataset. The inclusion of additional observations from the Oxford COVID-19 Government Response Tracker (OxCGRT) expanded the analytical sample to 9,120 observations, resulting in a broader population representation.
Importantly, despite the added observations, the direction and significance of key predictors, trust in institutions (β = 0.056, p < 0.001) and fear of illness (β = 0.622, p < 0.001), remained consistent, underscoring the reliability and generalisability of the results.
The policy stringency index (0–100, with 100 being the most stringent) was derived from OxCGRT, normalised, and merged with citizen survey data from POLYGOV. Error bars and standard errors represent 95% confidence intervals. Data for the policy stringency index were sourced from ourworldindata.org. Hale, Noam Angrist, Goldszmidt, et al. (2021). “A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker).” Nature Human Behaviour.
https://doi.org/10.1038/s41562-021-01079-8.
H3b policy stringency and perceptions
Table D1. Long description
A statistical table with two columns. The first column lists variables and the second column, labeled 1 Reasonableness index, provides coefficients with standard errors in parentheses below them.
Geographic variables relative to N O (0.000):
* S E: 0.604 with standard error 0.054 (significant at p < 0.01).
* D K: 0.410 with standard error 0.056 (significant at p < 0.01).
* F I: minus 0.044 with standard error 0.060.
* I S: 0.729 with standard error 0.080 (significant at p < 0.01).
Demographic variables:
* Female: minus 0.045 (standard error 0.038) relative to Male (0.000).
* Children yes: minus 0.093 (standard error 0.045) relative to Children no (0.000).
* Partnered: 0.002 (standard error 0.042) relative to Single (0.000).
* With parents: minus 0.272 (standard error 0.092, significant at p < 0.1).
* Not specified: minus 0.009 (standard error 0.189).
Indices and other factors:
* Trust index mean of Q 2: 0.056 (standard error 0.001, significant at p < 0.01).
* Fear of illness: 0.622 (standard error 0.038, significant at p < 0.01).
* Age centred: 0.008 (standard error 0.001, significant at p < 0.01).
* Age super 2 centred: minus 0.000 (standard error 0.000).
* Constant: 2.496 (standard error 0.136, significant at p < 0.01).
Model Statistics:
* R-squared: 0.348.
* Adjusted R-squared: 0.347.
* Observations: 9120.
* Mean V I F: 1.35.
Standard errors in parentheses * p < 0.1, ** p < 0.05, *** p < 0.01. Mean VIF 1.35
Policy stringency across Nordic countries during COVID-19, as measured by the Oxford COVID-19 government response tracker (OxCGRT).
Figure D1. Long description
The y-axis is labeled Linear prediction with a scale from 6 to 7. The x-axis is labeled Highest level of education. A green line connects five data points with vertical error bars.
* Elementary: The point is at approximately 6.78 with a narrow error bar between 6.6 and 6.95.
* Secondary: The point drops to approximately 6.67 with an error bar between 6.58 and 6.75.
* Undergrad/Vocational: The point drops further to approximately 6.52 with an error bar between 6.42 and 6.62.
* Master/Graduate: The point rises slightly to approximately 6.6 with an error bar between 6.49 and 6.72.
* Don’t know: The point is at approximately 6.51 but features a very large error bar extending from 5.99 to 7.05.
Policy stringency index (OxCGRT)*
Table D2. Long description
The table contains three columns: Country, Year, and Stringency index (O x C G R T). Data is grouped by country with a total mean calculated for each.
* Denmark: 46 in 2020, 46 in 2021, and 14 in 2022. Total mean Denmark is 35.
* Finland: 39 in 2020, 42 in 2021, and 18 in 2022. Total mean Finland is 33.
* Iceland: 39 in 2020, 38 in 2021, and 16 in 2022. Total mean Iceland is 31.
* Norway: 42 in 2020, 50 in 2021, and 16 in 2022. Total mean Norway is 36.
* Sweden: 49 in 2020, 46 in 2021, and 16 in 2022. Total mean Sweden is 37.
Across all countries, the stringency index shows a significant decrease in 2022 compared to the previous two years.
Mean is additive in this table.
Robustness checks excluding Sweden
To assess whether the null finding for policy stringency was driven by Sweden’s distinctive pandemic strategy, the H3b model was re-estimated after excluding Sweden from the sample. The results remained substantively unchanged. Policy stringency was still non-significant, the interaction between country and policy stringency remained non-significant, and predicted values were stable across low, medium, and high levels of policy stringency.
Robustness check for H3b excluding Sweden see Oxford COVID-19 government response tracker (OxCGRT).
Table D3. Long description
The table presents coefficients and standard errors in parentheses for several variables.
* Denmark: 0.420 (0.285)
* Finland: minus 0.040 (0.283)
* Iceland: 0.742* (0.341)
* Standardised policy stringency: minus 0.000 (0.048)
* countrycode_num = 1 # standardized_policy: 0.000 (.)
* Denmark times policy stringency: 0.000 (0.050)
* Finland times policy stringency: 0.000 (0.050)
* Iceland times policy stringency: 0.000 (0.065)
* Gender = 0: 0.000 (.)
* Yes: minus 0.106* (0.052)
* Single: 0.000 (.)
* Partnered: minus 0.312** (0.102)
* With parents: 0.088 (0.227)
* Trust index: 0.059*** (0.001)
* Fear of illness: 0.637*** (0.044)
* Age (centred): 0.007*** (0.002)
* Age super 2 (centred): minus 0.000 (0.000)
* Constant: 2.402*** (0.295)
Summary statistics at the bottom show an R-squared of 0.357 and 7036.000 observations. Significance levels are indicated by asterisks: * p < 0.05, ** p < 0.01, *** p < 0.00.
Standard errors in parentheses * p < 0.05, ** p < 0.01, *** p < 0.00
E. Appendix
Citizen surveys, compositions of net sample (gender and total) per country
Table 9 Sample for the citizen surveys. Selected through quota sampling. Quota sampling is a non-probabilistic sampling model where the population is divided into mutually exclusive subgroups based on certain known (non-random) features. In this case, quotas were based on the respondents’ demographic profile (age, gender, and geographic region). The geographic quotas were defined based on counties in all five countries. A total of 5,674 responses were collected. The final net dataset for each country was weighted to adjust for inconsistencies with population statistics. This weight makes an adjustment to ensure that the size of the groups for regions, age, and gender is proportional to their size in the population (Haug, Reference Haug2024, p. 16).
Citizen survey.
Table E1. Long description
The table contains six columns: Country, Population (Above 18), Net sample, Net sample proportion, Population proportion, and Difference (Net Sample/Population).
* Norway: Population 4,316,747; Net sample 1,289. Net sample proportion is 100 percent (M: 53 percent, F: 47 percent). Population proportion is 100 percent (M: 50 percent, F: 50 percent). Difference is M: plus 3 percent, F: minus 3 percent.
* Sweden: Population 8,195,551; Net sample 1,304. Net sample proportion is 100 percent (M: 50 percent, F: 50 percent). Population proportion is 100 percent (M: 50 percent, F: 50 percent). Difference is M: plus 2 percent, F: minus 2 percent.
* Denmark: Population 4,686,381; Net sample 1,292. Net sample proportion is 100 percent (M: 51 percent, F: 49 percent). Population proportion is 100 percent (M: 49 percent, F: 51 percent). Difference is M: plus 2 percent, F: minus 2 percent.
* Finland: Population 4,493,993; Net sample 1,240. Net sample proportion is 100 percent (M: 52 percent, F: 48 percent). Population proportion is 100 percent (M: 49 percent, F: 51 percent). Difference is M: plus 2 percent, F: minus 2 percent.
* Iceland: Population 286,421; Net sample 549. Net sample proportion is 100 percent (M: 47 percent, F: 53 percent). Population proportion is 100 percent (M: 51 percent, F: 49 percent). Difference is M: minus 4 percent, F: plus 4 percent.
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