Pandemic Fatigue: Measurement, Correlates, and Consequences

Home , Pandemic fatigue

Lau Lilleholt1, Ingo Zettler1, Cornelia Betsch2,3, and Robert Böhm1,4,5

1Department of Psychology, University of Copenhagen, Øster Farimagsgade 2A, 1353, Copenhagen,

Denmark; 2Media and Communication Science, University of Erfurt, Norhäuser Str. 63, 99089 Erfurt,

Germany; 3Center for Empirical Research in Economics and Behavioural Sciences (CEREB),

University of Erfurt, Norhäuser Str. 63, 99089 Erfurt, Germany; 4Department of Economics,

University of Copenhagen, Øster Farimagsgade 5, 1353, Copenhagen, Denmark; 5Copenhagen

Center for Social Data Science (SODAS), University of Copenhagen, Øster Farimagsgade 5, 1353,

Copenhagen, Denmark

*Correspondence to: [email protected]

Abstract

With no effective treatment or vaccine widely available, most national COVID-19 response strategies have relied on people’s willingness to comply with health-protective behaviours and behavioural restrictions. Despite generally high levels of public compliance, several countries have reported a recent upsurge in the number of people who no longer sufficiently adhere to restrictions or keep themselves informed about COVID-19. This developing trend has been attributed to Pandemic

Fatigue. Using quota-representative survey data from Denmark and Germany (overall n = 12,191), we introduce a psychometrically sound measure of Pandemic Fatigue, show who experiences it, identify related emotions and perceptions, and shed light on the relation between Pandemic Fatigue and four COVID-19-related health-protective behaviours. Further, based on a preregistered online experiment with US participants (n = 1,584), we establish a causal link between Pandemic Fatigue and people’s intention to comply with recommended heath-protective behaviours.

Introduction

In an attempt to curb the spread of the Coronavirus disease 2019 (COVID-19), governments and health authorities across the globe have both recommended and mandated various health-protective measures, such as mask wearing, physical distancing, and self-isolation. While these and other measures are effective in constraining the COVID-19 pandemic1–5, they require tremendous economic and psychological sacrifices on the part of the public6,7 and ultimately depend on people’s constant willingness to follow guidelines and restrictions. Despite a generally high level of public support for national COVID-19 response strategies8, several countries have reported a growing number of people who no longer sufficiently adhere to restrictions and who have progressively decreased their efforts to keep themselves informed about the pandemic8. This developing trend could potentially undermine national and global efforts to control the spread of the virus, even after vaccination becomes more widely available. In fact, as the full immunization of populations against

COVID-19 could still take several months9 or even years, it will remain important to maintain high public compliance with the recommended health-protective behaviours to curb the spread of the disease, minimize the risk of mutations, and, ultimately, save lives.

According to the World Health Organization (WHO), the recent upsurge in noncompliance with COVID-19-related health-protective measures is likely to be a product of Pandemic Fatigue8.

WHO has proposed that Pandemic Fatigue can be understood ‘as demotivation to follow recommended protective behaviours, emerging gradually over time and affected by a number of emotions, experiences and perceptions’ (p. 7)8. Being a latent phenomenon that is not directly observable, Pandemic Fatigue is believed by WHO to express itself on the behavioural level ‘through an increasing number of people not sufficiently following recommendations and restrictions, [and] decreasing their effort to keep themselves informed about the pandemic’ (p. 7)8.

Indeed, some research suggests that people’s awareness of the pandemic may change over time and, in turn, affect disease spread10–12. Importantly, however, Pandemic Fatigue has thus far solely been derived from observations of behaviour, and, given this lack of direct measurement, some scholars have questioned the importance or even existence of Pandemic Fatigue, since corresponding behavioural patterns could also be explained by other factors (e.g., decreased perceived threat from the disease). In sum, it remains unclear how to measure and quantify Pandemic Fatigue, who is likely to experience it, what emotions and perceptions relate to it, and how much of an impact it has on people’s behaviour. It is thus crucial to conceptualize Pandemic Fatigue indiviudally, disentangling it from its correlates and consequences.

Herein, we present such a conceptualization and introduce a corresponding brief and psychometrically sound measure of Pandemic Fatigue—the Pandemic Fatigue Scale (PFS). Using this measure in a series of 13 cross-sectional, nationally representative surveys conducted in Denmark and Germany (overall n = 12,191), we (i) investigate who experiences Pandemic Fatigue, (ii) identify related emotions and perceptions, and (iii) shed light on the relation between Pandemic Fatigue and four important COVID-19 related health-protective behaviours: physical distancing, hygienic behaviour, mask wearing, and information seeking. In addition, a preregistered online experiment conducted with participants from the US (n = 1,584) establishes a causal link between Pandemic

Fatigue and people’s intention to follow these behaviours. Taken together, we present a clear conceptualization and measurement of Pandemic Fatigue, disentangling this construct from pure observations of behavioural patterns, which have otherwise—without any formal testing or research

—simply been attributed to Pandemic Fatigue. The conceptualization and corresponding brief measure of Pandemic Fatigue introduced herein allows for the identification of fatigue groups for targeted interventions as well as testing how Pandemic Fatigue might be reduced—not only during the COVID-19 pandemic but also in upcoming future pandemics.

Our cross-sectional survey data comes from two COVID-19 Snapshot MOnitoring (COSMO) projects13. Since March 2020, COSMO has assessed citizens’ knowledge, perceptions, emotions, and behavioural reactions related to COVID-19 across several countries, including Denmark14 and

Germany15, using a mixture of weekly, biweekly, and monthly cross-sectional and panel surveys. The

COSMO surveys also collect sociodemographic information, including age, gender, education, employment, and health status. The Danish COSMO surveys further assess people’s basic personality characteristics in terms of the HEXACO traits (Honesty-Humility, Emotionality, Extraversion,

Agreeableness vs. Anger, Conscientiousness, and Openness to Experience)16, which are related to a wide array of humans’ thoughts, feelings, and behaviours17, including health-protective behaviours18.

More specifically, herein, we use data from seven biweekly measurement points (October 19,

2020–January 17, 2021) of the Danish cross-sectional COSMO survey and six weekly measurement points (27 October, 2020–11 November, 2020 and 22 December, 2020–13 January, 2021) of the

German cross-sectional COSMO survey, in which Pandemic Fatigue was assessed with the newly developed PFS. During this period, both Denmark and Germany were experiencing a second wave of COVID-19, during which new and stricter restrictions were imposed after public life had been gradually reopened following the first complete lockdown in early spring 2020. As such, this time period is the perfect setting for studying Pandemic Fatigue, as Danes and Germans alike had already been struggling with COVID-19 for quite some time and were facing yet another highly challenging pandemic-related period—with great uncertainty regarding its length and hardship.

Results

Development and validation of the Pandemic Fatigue Scale (PFS)

We conceptualized Pandemic Fatigue to represent a general feeling of demotivation towards following COVID-19 related health-protective behaviours and staying informed about the development of the pandemic. We first generated an item pool, which we adapted and reduced to 10

5 items in various internal feedback loops. The finally chosen 10 items were then administered in calendar week 49 (19–25 October) of 2020 in the Danish cross-sectional COSMO survey (n = 923).

The 10-item version of the PFS is provided in Table S1.

To explore the factor structure of the PFS, we conducted an ordinary least squares exploratory factor analysis with oblique factor rotation19. In order to determine the number of factors to extract, we considered the scree test20, Very Simple Structure criterion21, and Velicer’s Minimum Average

Partial criterion22, which combined indicated that either one or two factors would best reflect the data

(Figure S1 and Table S2). Results from the exploratory factor analysis showed that a one-factor model did not fit the data well (RMSR = .07, RMSEA = .13, TLI = .84), whereas a two-factor model yielded an acceptable fit (RMSR = .02, RMSEA = .05, TLI = .98). Assessing the content of the items pertaining to each factor, the first factor, consisting of three items, represents what we have termed ‘Information

Fatigue’ (i.e., being tired of hearing about COVID-19), and the second factor, consisting of seven items, represents what we have termed ‘Behavioural Fatigue’ (i.e., feeling demotivated and strained from fighting COVID-19). As our goal was to develop a brief measure of Pandemic Fatigue that could easily be administered in combination with other measures, we aimed to reduce the number of items of the second factor by iteratively removing one item at a time until the scale had been reduced to three items per factor. In doing so, we simultaneously considered factor loadings, cross-loadings, and the content of each item to ensure that the final scale would have good psychometric properties and high content validity23. That is, we sequentially removed the item with the lowest factor loading and highest cross-loading while also considering if the content validity of the Behavioural Fatigue factor would be substantially reduced by removing the item in question. The fit of the final two-factor model based on the six-item PFS was excellent (RMSR = .01, RMSEA = .02, TLI = 1.00). Moreover, the correlation between the composite score of the initial seven items and the final three items pertaining

6 to Behavioural Fatigue was extremely high (r = .92, p <.001). Standardized factor loadings for each item of the six-item PFS from the final two-factor model are presented in Table S3.

After identifying the underlying factor structure of Pandemic Fatigue and its corresponding items, we proceeded to validate our findings from the exploratory factor analysis by conducting two confirmatory factor analyses based on data collected between the second and seventh measurement point (2 November, 2020–17 January, 2021) of the Danish cross-sectional COSMO survey (n =

5,225) as well as at all six measurement points (27 October, 2020–11 November, 2020 and 22

December, 2020–13 January 13, 2021) of the German cross-sectional COSMO survey (n = 6,043).

Results from the confirmatory factor analyses (Figure S2) indicated that a two-factor model fit the data well in both Denmark (RMSEA = .06, SRMR = .03, TLI = .97, CFI = .99) and Germany (RMSEA

= .07, SRMR = .03, TLI = .97, CFI = .99) and that the two factors are highly correlated (rDenmark =

.69, p <.001; rGermany = .77, p <.001). In light of this high intercorrelation between the factors, we decided to model Pandemic Fatigue as a second-order latent construct with Behavioural and

Information Fatigue as first-order subfactors. While the second-order model is statistically equivalent to the two-factor model and thus fits the data equally well, it arguably represents a better model, as it allows for the combination of Behavioural and Information Fatigue into an overall measure of

Pandemic Fatigue while at the same time makes it possible to explore the correlates and consequences of these two factors separately. The fully standardized factor loadings and (residual) variances for the second-order models are presented in Figure 1. To check the internal consistency of the full six-item

PFS and the Behavioural and Information Fatigue subscales, we calculated Cronbach’s α as well as

McDonald’s ω. In both Denmark and Germany, the internal consistency of the full six-item PFS (α

= .83/.87, ω = .82/.87) as well as the Behavioural (α = .72/.78, ω = .73/.78) and Information Fatigue

(α = .82/.85, ω = .83/.86) subscales was high. Taken together, results from the exploratory and confirmatory factor analyses suggest that Pandemic Fatigue consists of two distinct yet highly

correlated factors—Behavioural and Information Fatigue—which both add to people’s overall

experience of Pandemic Fatigue. Moreover, our results show that the newly developed six-item PFS

has good psychometric properties.

Figure 1. Second-order model of Pandemic Fatigue fitted with data from Denmark and

Germany. 1.00 1.00 1.00 1.00

Pandemic Pandemic Pandemic Pandemic Fatigue Fatigue Fatigue Fatigue

0.83 0.83 0.83 0.83 0.88 0.88 0.88 0.88

0.31 0.31 0.31 0.31 0.23 0.23 0.23 0.23

Information InformationBehavioural Behavioural Information InformationBehavioural Behavioural Fatigue FatigueFatigue Fatigue Fatigue FatigueFatigue Fatigue

0.80 0.87 0.670.80 0.87 0.670.80 0.57 0.660.80 0.57 0.66 0.84 0.88 0.710.84 0.88 0.710.68 0.75 0.770.68 0.75 0.77

Item 1 ItemItem 2 1 ItemItem 3 2 ItemItem 4 3 ItemItem 5 4 ItemItem 6 5 Item 6 Item 1 ItemItem 2 1 ItemItem 3 2 ItemItem 4 3 ItemItem 5 4 ItemItem 6 5 Item 6

0.36 0.230.36 0.550.23 0.350.55 0.670.35 0.570.67 0.57 0.30 0.220.30 0.500.22 0.540.50 0.440.54 0.410.44 0.41 Denmark (n = Denmark5,225) (n = 5,225) Germany (n = German6,043) y (n = 6,043)

Figure 1 shows the second-order model of Pandemic Fatigue with fully standardized factor loadings and (residual)

variances for Denmark (left panel) and Germany (right panel). Item 1= ‘I am tired of all the COVID-19 discussions in

TV shows, newspapers, and radio programs, etc.’; Item 2 = ‘I am sick of hearing about COVID-19’; Item 3 = ‘When

friends or family members talk about COVID-19, I try to change the subject because I do not want to talk about it

anymore’; Item 4 = ‘I feel strained from following all of the behavioural regulations and recommendations around

COVID-19’; Item 5 = ‘I am tired of restraining myself to save those who are most vulnerable to COVID-19’; Item 6 = ‘I

am losing my spirit to fight against COVID-19’.

Correlates and consequences of Pandemic Fatigue

Having established a psychometrically sound measure of Pandemic Fatigue, we turned to investigate

who experiences it, which emotions and perceptions are related to it, as well as whether—and, if so,

8 how much—Pandemic Fatigue affects (non)adherence to recommended health-protective behaviours.

To answer these questions, we conducted several ordinary least squares regression analyses. Across all models, we consider Pandemic Fatigue to be a second-order latent construct and Behavioural and

Information Fatigue as first-order subfactors and thus rely on a composite score of these two factors as an overall measure of Pandemic Fatigue. Although there most certainly is much to gain from considering Behavioural and Information Fatigue separately, we focus here on the overall measure of

Pandemic Fatigue in order to explore its correlates and consequences from a more general perspective. That is, we aimed to identify what predicts people’s overall experience of Pandemic

Fatigue and how it relates to their willingness to comply with COVID-19-related health-protective behaviours. In the Supplementary Information, we additionally report results from regression analyses in which Behavioural and Information Fatigue are considered as two independent factors

(Figures S3–S6). Given that neither the timing nor the content of the Danish and German cross- sectional COSMO surveys were exactly the same (see Methods), we conducted all analyses separately for these two countries. In light of the exploratory nature of the regression analyses, we primarily focus on results that are stable across countries when presenting and interpreting our findings. This notwithstanding, and acknowledging the differences between the surveys conducted in Denmark and

Germany, we also highlight some pronounced country-specific results.

Who experiences Pandemic Fatigue and which emotions and perceptions relate to it?

First, we explored who tends to experience Pandemic Fatigue as well as which emotions and perceptions relate to it. To this end, we considered several sociodemographic variables, namely, age, gender, educational background, employment, and health status, as well as basic personality traits in line with the HEXACO model of personality structure16. Next to this, we also considered a wide range of emotions and perceptions that have previously been linked with (non)adherence to recommended

9 health-protective behaviours, including cognitive and affective risk perceptions24, trust25, worries26, optimism27, negative affect28, and empathy29.

Figure 2. OLS regressions predicting Pandemic Fatigue in Denmark and Germany.

Pandemic Fatigue − DK Pandemic Fatigue − GER Pandemic Fatigue − DK (n = 5,898) (n = 4,515) (n = 5,898) 0.21 *** 0.07 0.23 *** Intercept 0.06 *** 0.03 ** 0.02 * Time −0.18 *** −0.23 *** −0.06 *** Age −0.07 ** 0.01 −0.07 ** Gender (Male) −0.17 *** −0.04 −0.16 *** Education (10 years or more) −0.07 * −0.06 −0.13 *** Employment (Unemployed) 0.03 −0.07 ** 0.01 Chronic disease (Yes) −0.02 −0.03 * −0.04 ** Cognitive Risk −0.10 *** −0.21 *** −0.16 *** Affective Risk −0.31 *** −0.39 *** −0.23 *** Trust 0.10 *** 0.16 *** 0.10 *** Worries −0.06 *** Optimism 0.28 *** Negative Affect −0.09 *** Empathy −0.06 *** Honesty−Humility 0.02 Emotionality 0.04 ** Extraversion −0.02 Agreeableness vs. Anger −0.02 Conscientiousness −0.12 *** Openness to Experience

−.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 Estimates Figure 2 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

As shown in Figure 2, the analysis shows that older people as well as people who think a lot about the pandemic and feel that it is physically close to them, fast spreading, out of their control, worrisome, and terrifying (i.e., feel higher risk) experience less pandemic fatigue. Conversely, we find that individuals who frequently worry about the potential consequences of the pandemic (e.g.,

10 economic recession, businesses going bankrupt, etc.) experience more Pandemic Fatigue. Of note,

Pandemic Fatigue increased over time in both countries (see Figure S7). Finally, with regard to the variables that were only assessed in Denmark, our results indicate that people with high Openness to

Experience and Honesty-Humility, as well as those who are optimistic and have a strong sense of empathy toward those most vulnerable to COVID-19, experience less Pandemic Fatigue. On the other hand, we find that people high in Extraversion and those who find themselves in a negative affective state are more prone to experiencing Pandemic Fatigue.

Relations between Pandemic Fatigue and health-protective behaviours

Next, we explored the relations between Pandemic Fatigue and four COVID-19 related health- protective behaviours: physical distancing, hygienic behaviour, mask wearing, and information seeking. As shown in Figure 3, we find that Pandemic Fatigue is negatively related to people’s self- reported tendency to follow each of the four health-protective behaviours in both Denmark and

Germany—even when controlling for sociodemographic variables as well as relevant emotions and perceptions. Moreover, as shown in Figure 4, Pandemic Fatigue remains a significant predictor of all four health-protective behaviours after controlling for personality in terms of the HEXACO traits as well as additional emotions and perceptions that were only assessed in Denmark (i.e., optimism, negative affect, and empathy). Considering Behavioural and Information Fatigue separately (Figures

S5–S6), we find that Behavioural Fatigue is a stronger predictor of physical distancing, hygienic behaviour, and mask wearing, while Information Fatigue is a stronger predictor of information seeking. In combination, these results suggest that Pandemic Fatigue is likely to be an important driver of (non)adherence to recommended health-protective behaviours together with a range of other factors, including age, gender, affective risk perceptions, trust, worries, empathy, and certain personality traits.

Figure 3. OLS regressions predicting health-protective behaviours in Denmark and Germany.

Figure 3 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and

scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

Figure 4. OLS regressions predicting health-protective behaviours in Denmark with additional controls.

Physical Distancing − DK Hygienic Behaviour − DK Mask Wearing − DK Information Seeking − DK (n = 5,898) (n = 5,898) (n = 5,898) (n = 5,025) −0.02 0.17 *** 0.10 −0.09 Intercept 0.05 *** −0.03 * 0.10 *** 0.03 * Time 0.13 *** 0.10 *** −0.04 * 0.10 *** Age −0.06 * −0.23 *** −0.22 *** −0.02 Gender (Male) 0.04 −0.08 −0.13 ** 0.09 * Education (10 years or more) 0.01 0.01 0.18 *** 0.01 Employment (Unemployed) 0.01 0.01 0.12 *** 0.02 Chronic disease (Yes) −0.07 *** −0.04 ** −0.05 ** −0.21 *** Pandemic Fatigue 0.02 0.05 *** 0.07 *** 0.03 * Cognitive Risk 0.10 *** 0.10 *** 0.03 * 0.22 *** Affective Risk 0.15 *** 0.12 *** −0.01 0.16 *** Trust −0.01 0.09 *** 0.13 *** 0.04 ** Worries 0.02 0.03 * 0.00 0.04 ** Optimism 0.03 −0.00 0.03 0.08 *** Negative Affect 0.14 *** 0.14 *** 0.07 *** 0.13 *** Empathy 0.04 ** 0.04 *** −0.08 *** 0.02 Honesty−Humility −0.02 −0.01 −0.00 −0.00 Emotionality −0.00 0.08 *** 0.00 0.06 *** Extraversion 0.01 0.05 *** 0.05 *** −0.03 * Agreeableness vs. Anger 0.11 *** 0.13 *** 0.04 ** 0.05 *** Conscientiousness 0.07 *** 0.04 ** 0.05 *** 0.03 * Opennes to Experience

−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50 Estimates Figure 4 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

Experimentally manipulating Pandemic Fatigue

Although the results from the regression analyses suggest that people’s experience of Pandemic

Fatigue is associated with their (self-reported) tendency to follow recommended health-protective behaviours, it remains unclear if the nature of this relation is a causal one. To tackle this question, we set up a preregistered online experiment in which we manipulated participants’ experience of

Pandemic Fatigue before asking them to report their intentions to comply with recommendations regarding physical distancing, hygienic behaviour, mask wearing, and information seeking. In particular, we recruited a total of 1,854 participants from the US via Prolific Academic30 and

13 randomized them into three experimental conditions: Control, Low Pandemic Fatigue, and High

Pandemic Fatigue. To manipulate participants’ experience of Pandemic Fatigue, we relied on a brief self-reflection task. In this task, participants in the Low Pandemic Fatigue condition were asked to write a few sentences about some of the things over the last two weeks that had motivated them to follow recommended health-protective behaviours and keep themselves informed about the pandemic

(e.g., ‘So I would say in general, like most people, I don't want to get sick ever. My understanding is this virus can have serious long-term health implications that I don't want. More importantly, my wife is pregnant so I really don't want to potentially pass the virus along to her or our future child’). In contrast, participants in the High Pandemic Fatigue condition were asked to write about some of the things that had demotivated them (e.g., ‘I have been somewhat demotivated by the lack of evidence that everyone is at risk for COVID-19. I feel that there is a lot of fear-mongering when, in fact, there are select groups that are most at risk. It also seems that, from the data, the behaviours did not protect those groups’), whereas participants in the Control condition were simply asked to write about some of the ordinary things that had happened and affected their everyday behaviour in some way over the past two weeks (e.g., ‘I try to reduce my consumption of red meat (steaks) to less than 1–2 times per month. Porterhouse steak was on sale at my nearest grocery store; so, I bought it and ate it. The fact that it was on sale made me change my behaviour of eating it’). After having completed the self- reflection tasks, all participants were asked to fill out the PFS before responding to four items assessing their intentions to keep themselves informed about the pandemic and current COVID-19 restrictions as well as comply with recommendations regarding physical distancing, hygiene, and mask wearing in the next two weeks. We hypothesized that participants in the High Pandemic Fatigue condition would express weaker intentions to follow recommended health-protective behaviours compared to the participants in the Low Pandemic Fatigue condition (see https://aspredicted.org/blind.php?x=2cp7k9).

In line with our pre-analysis plan, we excluded all participants who in the experiment wrote fewer than 100 characters (including spaces) in the self-reflection task (n = 245) or who failed at least one (of the two) attention check(s) (n = 10). Moreover, we excluded participants who experienced technical issues during the experiment (n = 15). A total of 1,584 participants were included in the final analysis. To ensure that our experimental manipulation had been successful, we first compared the mean score of the PFS across the three experimental conditions. As shown in Figure 5 (left panel), results from an independent samples t-test reveal that participants in the Low Pandemic Fatigue condition (M = 3.08, SD = 1.36) indeed reported lower levels of Pandemic Fatigue when compared to the participants in the High Pandemic Fatigue condition (M = 3.55, SD =1.43; t(1017.8) = -5.43, p < .001, Cohen’s d = .34). Similarly, results from two additional independent samples t-tests show that participants in the Control condition (M = 3.29, SD = 1.45) reported higher levels of Pandemic

Fatigue than participants in the Low Pandemic Fatigue condition (t(1079.3) = -2.49, p = .013,

Cohen’s d =.15) as well as lower levels than participants in the High Pandemic Fatigue condition

(t(1044.5), p = .004, Cohen’s d =.18). Thus, these results indicate that the experimental manipulation was successful. In order to test the hypothesis that participants in the High Pandemic Fatigue condition would express weaker intentions to follow recommended health-protective behaviours compared to participants in the Low Pandemic Fatigue condition, we relied on a composite score of the four items used to assess participants’ behavioural intentions (Cronbach’s α = .76). As illustrated in Figure 5 (right panel), results from an independent samples t-test confirm the hypothesis, showing that participants in the High Pandemic Fatigue condition (M = 5.65, SD = 1.18) expressed weaker intentions to comply with recommended health-protective behaviours when compared to participants in the Low Pandemic Fatigue condition (M = 5.94, SD = 1.13; t(1019.9) = 4.13, p < .001, Cohen’s d

= .26). Moreover, we find that participants in the High Pandemic Fatigue condition also expressed weaker intentions to follow recommended health-protective behaviours than participants in the

Control condition (M = 5.86, SD = 1.13; t(1031.3) = 2.98, p = .003, Cohen’s d = .18). On the contrary, there was no significant difference between the Control condition and the Low Pandemic Fatigue condition concerning participants’ intentions to follow recommended health-protective behaviours

(t(1078.1) = 1.25, p = .213, Cohen’s d = .08). Importantly, the results remain robust when controlling for participants’ age, gender, education, and cognitive risk perceptions (Table S4). Overall, these results substantiate the idea that Pandemic Fatigue causally influence people’s willingness to comply with recommended health-protective behaviours.

Figure 5. Pandemic Fatigue and health-protective behaviours by experimental condition.

Figure 5 shows raincloud plots31 for the PFS (left) and participants’ intentions to comply with recommended health- protective behaviours (right) per experimental condition. *** p < 0.001; ** p < 0.01; * p < 0.05; ns. p > 0.05.

Discussion

Pandemic Fatigue has been proposed to impact people’s perceptions of and behavioural responses to the COVID-19 pandemic8. Closing a gap in the literature, we herein conceptualize and introduce a brief self-report measure of Pandemic Fatigue, allowing for the disentanglement of this concept from other emotions regarding, perceptions of, and behavioural responses to the pandemic. Our results suggest that Pandemic Fatigue consists of two distinct yet highly correlated factors—Behavioural and

Information Fatigue—which both add to people’s overall experience of Pandemic Fatigue. Further, we find that people high in Extraversion as well as younger people in particular are more likely to experience Pandemic Fatigue—perhaps because they feel that they constantly have to put the needs of those at a higher risk (e.g., senior citizens) before their own. These results may inform policymakers with regard to at whom interventions aimed at mitigating Pandemic Fatigue should be targeted32. In addition, we show that Pandemic Fatigue is related to several emotions and perceptions, including affective risk perceptions, trust, worries, negative affect, optimism, and empathy towards those most vulnerable to COVID-19. More specifically, we find that affective risk perceptions, trust, optimism, and feelings of empathy towards those most vulnerable to COVID-19 are negatively related to Pandemic Fatigue, whereas worries and negative affective states are positively associated with Pandemic Fatigue. While these results are all correlational in nature, which precludes us from drawing any causal inferences, they do provide important first insights into the kind of emotions and perceptions that might be targeted by different interventions aimed at mitigating Pandemic Fatigue.

Crucially, the results from our experimental study suggest that Pandemic Fatigue may be influenced by simple interventions. In this same vein, it suggests that it is important to keep the public from pondering too much about the things that make them feel demotivated to comply with recommended health-protective behaviours, thus emphasizing the responsibility of the media in setting the agenda and potentially influencing the framing of the pandemic and how people cope with it. In light of these results, future research should aim to more closely investigate how governments and health authorities might mitigate Pandemic Fatigue and, in turn, reinvigorate the public when necessary.

Across the analyses, our findings indicate that Pandemic Fatigue is related to (non)adherence to recommended health-protective behaviours. For all health-protective behaviours considered herein, we do, however, find that other emotions and perceptions matter as well, thus calling for a multifaceted approach to maintaining high public compliance with various health-protective

17 behaviours. This notwithstanding, we found empirical evidence for a causal link between people’s experience of Pandemic Fatigue and their intention to comply with recommended health-protective behaviours. Although people’s intentions and actual behaviours generally do not perfectly match, there is ample evidence showing that, in many cases, their intentions are good predictors of their future actions33 and that changes in people’s intentions can lead to corresponding behavioural change34. Taken together, these results lend support to the idea that Pandemic Fatigue could lead to an upsurge in noncompliance with recommended health-protective behaviours over time. To obtain a more precise estimate of the degree to which Pandemic Fatigue actually influences people’s tendencies to follow recommended health-protective behaviours, future research should aim to link people’s experiences of Pandemic Fatigue with their actual (not self-reported) behaviour using tools such as mobility data35. Further, it should be noted that the purpose of the experimental study presented herein was not to design and test a ready-made intervention but rather to establish a causal link between Pandemic Fatigue and health-protective behaviours. Future research should thus aim to design new and more effective interventions to decrease people’s experiences of Pandemic Fatigue.

The effects of the ways in which the media frames the pandemic should also be investigated.

From a more general perspective, the PFS developed herein is a short, valid, and economic measure that may be used in future research and in the country-wide monitoring of public opinion across the globe during the remainder of the COVID-19 pandemic as well as from the beginning of future pandemics. In fact, since health-protective behaviours will continue to play an important role in the fight against COVID-19 until the vast majority of people have been vaccinated, it is crucial to both monitor and find ways to counteract Pandemic Fatigue in order to maintain high public compliance with these behaviours. Upon failing to do so, Pandemic Fatigue may rise and ultimately endanger public health.

Methods

Danish and German cross-sectional COSMO surveys

Danish cross-sectional COSMO survey procedure

In 2020, following ethical approval, the second author received contact information for a representative sample of approx. 100,000 adult Danish citizens via Statistics Denmark. From this sample, 7,500–8,000 Danes were invited every other week from October 19, 2020 to January 17,

2021 to participate in a survey via the official digital mail system in Denmark, called e-Boks

(https://www.e-boks.com/danmark/en). The survey was set up in formr36 on a secure server located at the University of Copenhagen. Participation was voluntary, and informed consent was obtained from all participants. A total of 6,148 Danish citizens participated in the COSMO surveys from

October 19, 2020 to January 17, 2021. Sociodemographic information for all Danish participants is presented in Table S5. Across the seven measurement points of the Danish cross-sectional COSMO surveys used herein, some variables were assessed consistently, while others were only measured sporadically. An overview of all variables assessed at the seven measurement points of the Danish cross-sectional COSMO surveys can be found at: https://docs.google.com/spreadsheets/d/10TvgDYpPqIu0O5s8jx4TL0KF1NcfR9AUqm4AqNU2Ty c/edit?usp=sharing

German cross-sectional COSMO survey procedure

The study obtained ethical clearance from the University of Erfurt’s IRB (#20200302/20200501), and all participants provided informed consent prior to the data collection. The study involved a weekly to fortnightly serial cross-sectional online survey with approximately 1,000 individuals participating each week, using non-probability quota samples representative of the German population regarding age, gender, and federal state. The first data collection date was 3 March, 2020. A total of 6,043

German citizens participated in the six focal COSMO surveys from 27 October, 2020 to 11

November, 2020 as well as from 22 December, 2020 to 13 January, 2021. The sociodemographic

19 information of all the German participants is presented in Table S5. As in the Danish cross-sectional

COSMO survey, some variables of the German cross-sectional COSMO survey were measured consistently across the six measurement points considered herein, while others were only assessed sporadically. An overview of all variables measured at the six measurement points of the German cross-sectional COSMO survey can be found at: http://dx.doi.org/10.23668/psycharchives.2776.

Scales and measures

To best capture people’s perceptions, emotions, and behavioural reactions to the COVID-19 pandemic, all COSMO surveys have been specifically tailored to each country. Hence, although there is a substantial overlap between the COSMO surveys conducted in Denmark and Germany, there are also some differences with regard to the content of the surveys as well as how certain variables were assessed. Across both countries, participants’ cognitive and affective risk perceptions regarding

COVID-19, their experiences of Pandemic Fatigue, and their chronic disease status were measured in the exact same manner. Participants’ overall level of trust, worries, physical distancing, hygienic behaviour, mask wearing, information seeking, age, gender, education, and employment status were also measured in both Denmark and Germany but with slightly different items and/or response formats. Finally, respondent’s feelings of optimism, negative affect, and empathy towards those most vulnerable to COVID-19, as well as their personality characteristics in terms of the HEXACO traits, were only assessed in Denmark. All variables, with the exception of sociodemographics (i.e., age, gender, education, employment, and chronic disease status), were measured with either a five- or seven-point Likert-type scale with different anchors. In both the Danish and German cross-sectional

COSMO survey, participants had the opportunity to answer ‘Not relevant’ or ‘Don’t know’ to some items. In all cases, we treated these responses as missing, which is why the n differs slightly across the regression analyses. The mean scores, standard deviations, and Cronbach’s α for all variables from the Danish and German cross-sectional COSMO surveys considered herein can be found in

Table S6. In Tables S7–S8 we further provide an overview of all scales and items from the Danish and German cross-sectional COSMO surveys used in this investigation.

Online experiment

Procedure

An online experiment with three conditions (i.e., Control, Low Pandemic Fatigue, and High Pandemic

Fatigue) was set up and run in formr (https://formr.org)36. The experiment took approximately seven minutes to complete, and participants were paid a flat fee of £0.75 for their participation. In all three conditions, participants were first asked to provide some sociodemographic information about themselves (i.e., age, gender, and education) and respond to two items assessing their cognitive risk perception regarding COVID-19. Next, they completed a brief self-reflection task (see Wildschut et al., 2006, for a similar self-reflection task)37. In this task, participants in the Low Pandemic Fatigue condition were presented with the following instruction: ‘Using the space provided below, please spend the next few minutes to describe some of the things that, over the last two weeks, have motivated you to follow recommended protective behaviours (e.g., physical distancing, mask wearing, hygienic behaviours) and keep yourself informed about the COVID-19 pandemic’. Participants in the High

Pandemic Fatigue condition, on the other hand, read this instruction: ‘Using the space provided below, please spend the next few minutes to describe some of the things that, over the last two weeks, have demotivated you to follow recommended protective behaviours (e.g., physical distancing, mask wearing, hygienic behaviours) and keep yourself informed about the COVID-19 pandemic’. Finally, participants in the Control condition were instructed as follows: ‘Using the space provided below, please spend the next few minutes to describe some of the ordinary things that have happened over the last two weeks and affected your behaviour in some way’. Thereafter, all participants were asked to fill out the PFS and respond to four items assessing their intention to keep themselves informed about the pandemic and current COVID-19 restrictions as well as to comply with recommendations

21 regarding physical distancing, hygiene, and mask wearing. The mean scores, standard deviations and

Cronbach’s α for all measures obtained in the experiment can be found in Table S9. An overview of all items and scales used in the experiment is available in Table S10.

Power analysis

In order to determine an appropriate sample size to test our hypothesis, we conducted an a priori power analysis based on results from a small pilot study (n = 299) using G*Power38. Aiming to be able to detect a small effect size (Cohen’s d =.20) in an independent samples t-test with a two-tailed alpha level of .05 and high statistical power (1-β = .90), the a priori power analysis revealed that a total of 1,581 participants would be sufficient (i.e., 527 participants per condition). In order to compensate for potential exclusions, we decided to oversample by approximately 15% and thus aimed to recruit a total of 1,850 participants.

Participants

In line with the results from the a priori power analysis, a total of 1,854 participants from the US were recruited via Prolific Academic (https://www.prolific.co) to participate in the experiment. Of these, a total of 270 participants were excluded based on our a priori exclusion criteria (see https://aspredicted.org/blind.php?x=2cp7k9), resulting in a final sample of 1,584 (50.32% female,

47.98% male, 1.70% other; Mage = 35.58, SDage = 11.87 years). Sociodemographic information for each of the three experimental conditions can be found in Table S11.

Data availability

Data and scripts for replicating the results presented herein are available via the following link on the Open Science Framework https://osf.io/xd463/?view_only=7dfd0586c05f450b8c4421cfc18c9d84.

Acknowledgements

The Danish COVID-19 Snapshot Monitoring (COSMO) project was funded by grants from both the

Lundbeck Foundation (R349-2020-592) and the Faculty of Social Sciences, University of

Copenhagen (Denmark) to Robert Böhm and Ingo Zettler.

The German COVID-19 Snapshot Monitoring (COSMO) is a joint project of the University of Erfurt (Cornelia Betsch [PI], Lars Korn, Philipp Sprengholz, Philipp Schmid, Lisa Felgendreff,

Sarah Eitze), the Robert Koch Institute (RKI; Lothar H. Wieler, Patrick Schmich), the Federal Centre for Health Education (BZgA; Heidrun Thaiss, Freia De Bock), the Leibniz Centre for Psychological

Information and Documentation (ZPID; Michael Bosnjak), the Science Media Centre (SMC; Volker

Stollorz), the Bernhard Nocht Institute for Tropical Medicine (BNITM; Michael Ramharter), and the

Yale Institute for Global Health (Saad Omer). The study was funded by the German Research

Foundation (BE3970/11-1, 12-1 to CB), University of Erfurt, Robert Koch-Institute, Leibniz Institute for Psychology Information, Federal Centre for Health Education.

Author contributions

All: Conceptualization, Methodology, Writing–Original Draft, Writing–Review & Editing, Project administration, Investigation, Resources, Data Curation; Lau Lilleholt: Visualization, Software,

Validation, Formal analysis; Cornelia Betsch, Robert Böhm and Ingo Zettler: Supervision, Funding acquisition.

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Pandemic Fatigue: Measurement, Correlates, and Consequences

Supplementary Information

Lau Lilleholt1, Ingo Zettler1, Cornelia Betsch2,3, and Robert Böhm1,4,5

1Department of Psychology, University of Copenhagen, Øster Farimagsgade 2A, 1353, Copenhagen,

Denmark; 2Media and Communication Science, University of Erfurt, Norhäuser Str. 63, 99089 Erfurt,

Germany; 3Center for Empirical Research in Economics and Behavioural Sciences (CEREB),

University of Erfurt, Norhäuser Str. 63, 99089 Erfurt, Germany; 4Department of Economics,

University of Copenhagen, Øster Farimagsgade 5, 1353, Copenhagen, Denmark; 5Copenhagen

Centre for Social Data Science (SODAS), University of Copenhagen, Øster Farimagsgade 5, 1353,

Copenhagen, Denmark

*Correspondence to: [email protected]

1 Table of Contents Supplementary figures ...... 3 Figure S1. Scree plot...... 3 Figure S2. Two-factor model of Pandemic Fatigue fitted with data from Denmark and Germany...... 3 Figure S3. OLS regressions predicting Behavioural Fatigue in Denmark and Germany...... 5 Figure S4. OLS regressions predicting Information Fatigue in Denmark and Germany...... 6 Figure S5. OLS regressions predicting health-protective behaviours in Denmark and Germany with Behavioural and Information Fatigue as independent predictors...... 7 Figure S6. OLS regressions predicting health-protective behaviours in Denmark with Behavioural and Information Fatigue as independent predictors and additional controls. ... 8 Figure S7. Development of Pandemic Fatigue over time in Denmark and Germany...... 9 Figure S8. Two-factor and second-order model of Pandemic Fatigue fitted with data from USA...... 10 Figure S9. OLS regressions predicting Pandemic, Behavioural and Information Fatigue in USA...... 11 Figure S10. OLS regressions predicting health-protective behaviours in USA...... 12 Figure S11. OLS regressions predicting health-protective behaviours in USA with Behavioural and Information Fatigue as independent predictors...... 13 Supplementary tables ...... 14 Table S1. Initial 10-item Pandemic Fatigue Scale...... 14 Table S2. Very Simple Structure and Velicer’s Minimum Average Partial...... 15 Table S3. Standardized factor loadings for each item in the six-item Pandemic Fatigue Scale...... 16 Table S4. OLS regressions controlling for age, gender, education and cognitive risk perception...... 17 Table S5. Sociodemographics Danish and German cross-sectional COSMO surveys...... 18 Table S6. Number of items, means, standard deviations, and Cronbach’s α for all measures considered from the Danish and German cross-sectional cosmo surveys...... 19 Table S7. Item overview Danish cross-sectional COSMO survey...... 20 Table S8. Item overview German cross-sectional COSMO survey...... 33 Table S9. Number of items, means, standard deviations, and Cronbach’s α for all measures obtained in the experiment...... 40 Table S.10 Item overview for the experimental study...... 41 Table S11. Sociodemographic information per condition in the experimental study...... 44

2 Supplementary figures

Scree plot

Figure S1. Scree plot.

1 0

2 4 6 8 10

factor number

3 Figure S2. Two-factor model of Pandemic Fatigue fitted with data from Denmark and Germany.

1.00 1.001.00 1.00 1.00 1.001.00 1.00

0.69 0.69 0.77 0.77 Information InforBehamationvioural Behavioural Information InforBehamationvioural Behavioural Fatigue FatigueFatigue Fatigue Fatigue FatigueFatigue Fatigue

0.80 0.87 0.67 0.80 0.87 0.800.67 0.57 0.66 0.80 0.57 0.66 0.84 0.88 0.71 0.84 0.88 0.680.71 0.75 0.77 0.68 0.75 0.77

Item 1 Item 2Item 1 Item 3Item 2 Item 4Item 3 Item 5Item 4 Item 6Item 5 Item 6 Item 1 Item 2Item 1 Item 3Item 2 Item 4Item 3 Item 5Item 4 Item 6Item 5 Item 6

0.36 0.23 0.36 0.55 0.23 0.35 0.55 0.67 0.35 0.57 0.67 0.57 0.30 0.22 0.30 0.50 0.22 0.54 0.50 0.44 0.54 0.41 0.44 0.41 Denmark (n = 5,225)Denmark (n = 5,225) Germany (n = 6,043)Germany (n = 6,043) Figure S2 shows the two-factor model of Pandemic Fatigue with fully standardized factor loadings, (residual) variances,

and covariances for Denmark and Germany.

4 Figure S3. OLS regressions predicting Behavioural Fatigue in Denmark and Germany.

Behavioural Fatigue − DK Behavioural Fatigue − GER Behavioural Fatigue − DK (n = 5,898) (n = 4,515) (n = 5,898) 0.22 *** 0.07 0.25 *** Intercept 0.06 *** 0.02 0.03 * Time −0.16 *** −0.22 *** −0.01 Age −0.09 *** 0.04 −0.09 *** Gender (Male) −0.18 *** −0.05 −0.17 *** Education (10 years or more) −0.05 −0.02 −0.13 *** Employment (Unemployed) 0.04 −0.10 *** 0.01 Chronic disease (Yes) −0.02 0.01 −0.03 ** Cognitive Risk 0.02 −0.19 *** −0.05 *** Affective Risk −0.28 *** −0.35 *** −0.19 *** Trust 0.13 *** 0.14 *** 0.13 *** Worries −0.09 *** Optimism 0.32 *** Negative Affect −0.09 *** Empathy −0.09 *** Honesty−Humility 0.02 Emotionality 0.04 ** Extraversion 0.00 Agreeableness vs. Anger −0.03 * Conscientiousness −0.13 *** Openness to Experience

−.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 Estimates Figure S3 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

5 Figure S4. OLS regressions predicting Information Fatigue in Denmark and Germany.

Information Fatigue − DK Information Fatigue − GER Information Fatigue − DK (n = 5,898) (n = 4,515) (n = 5,898) 0.16 ** 0.07 0.17 *** Intercept 0.04 *** 0.04 ** 0.02 Time −0.16 *** −0.21 *** −0.08 *** Age −0.04 −0.02 −0.03 Gender (Male) −0.13 ** −0.02 −0.12 ** Education (10 years or more) −0.07 * −0.08 ** −0.10 *** Employment (Unemployed) 0.01 −0.04 0.00 Chronic disease (Yes) −0.03 * −0.05 *** −0.03 ** Cognitive Risk −0.19 *** −0.19 *** −0.22 *** Affective Risk −0.27 *** −0.37 *** −0.21 *** Trust 0.05 *** 0.15 *** 0.06 *** Worries −0.02 Optimism 0.19 *** Negative Affect −0.07 *** Empathy −0.03 * Honesty−Humility 0.01 Emotionality 0.03 * Extraversion −0.03 ** Agreeableness vs. Anger −0.01 Conscientiousness −0.08 *** Openness to Experience

−.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 Estimates Figure S4 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

6 Figure S5. OLS regressions predicting health-protective behaviours in Denmark and Germany with Behavioural and Information Fatigue as independent predictors.

Figure S5 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

7 Figure S6. OLS regressions predicting health-protective behaviours in Denmark with Behavioural and Information Fatigue as independent predictors and additional controls.

Physical Distancing − DK Hygienic Behaviour − DK Mask Wearing − DK Information Seeking − DK (n = 5,898) (n = 5,898) (n = 5,898) (n = 5,025) −0.02 0.18 *** 0.10 −0.11 * Intercept 0.05 *** −0.03 * 0.10 *** 0.03 * Time 0.13 *** 0.11 *** −0.04 * 0.09 *** Age −0.06 * −0.23 *** −0.21 *** −0.01 Gender (Male) 0.04 −0.09 * −0.13 ** 0.10 * Education (10 years or more) 0.01 0.01 0.18 *** 0.02 Employment (Unemployed) 0.01 0.01 0.12 *** 0.02 Chronic disease (Yes) −0.10 *** −0.07 *** −0.00 0.05 *** Behavioural Fatigue 0.01 0.02 −0.05 ** −0.28 *** Information Fatigue 0.02 0.05 *** 0.07 *** 0.03 * Cognitive Risk 0.11 *** 0.10 *** 0.03 0.19 *** Affective Risk 0.15 *** 0.12 *** −0.01 0.16 *** Trust −0.00 0.10 *** 0.13 *** 0.03 * Worries 0.01 0.03 * 0.00 0.05 *** Optimism 0.03 * 0.00 0.03 0.06 *** Negative Affect 0.14 *** 0.14 *** 0.07 *** 0.13 *** Empathy 0.04 ** 0.04 ** −0.08 *** 0.03 * Honesty−Humility −0.02 −0.01 −0.00 −0.00 Emotionality −0.00 0.08 *** 0.00 0.06 *** Extraversion 0.01 0.05 *** 0.05 *** −0.03 * Agreeableness vs. Anger 0.11 *** 0.13 *** 0.04 ** 0.06 *** Conscientiousness 0.06 *** 0.03 ** 0.05 *** 0.04 ** Opennes to Experience

−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50 Estimates Figure S6 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

8 Figure S7. Development of Pandemic Fatigue over time in Denmark and Germany.

7.0 Country DK 6.5 GER

6.0

5.5

5.0

e u

g 4.5

i 4.0

e d

n 3.5

a P

3.0

2.5

2.0

1.5

1.0

3 4 5 6 7 9 1 2 3 2 4 4 4 4 4 4 5 5 5 0 W W W W W W W W W W − − − − − − − − − − 0 0 0 0 0 0 0 0 0 1 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 2 2 2 2 2

Time

9 Figure S8. Two-factor and second-order model of Pandemic Fatigue fitted with data from USA.

1.00 1.001.00 1.00 1.00 1.00

0.69 0.69 Information InforBehamationvioural Behavioural Pandemic Pandemic Fatigue FatigueFatigue Fatigue Fatigue Fatigue

0.83 0.83 0.83 0.83

0.31 0.31 0.31 0.31

Information InforBehamationvioural Behavioural 0.90 0.88 0.69 0.90 0.88 0.740.69 0.67 0.71 0.74 0.67 0.71 Fatigue FatigueFatigue Fatigue

0.90 0.88 0.69 0.90 0.88 0.740.69 0.67 0.71 0.74 0.67 0.71

Item 1 Item 2Item 1 Item 3Item 2 Item 4Item 3 Item 5Item 4 Item 6Item 5 Item 6 Item 1 Item 2Item 1 Item 3Item 2 Item 4Item 3 Item 5Item 4 Item 6Item 5 Item 6

0.19 0.23 0.19 0.53 0.23 0.45 0.53 0.55 0.45 0.50 0.55 0.50 0.19 0.23 0.19 0.53 0.23 0.45 0.53 0.55 0.45 0.50 0.55 0.50 Two factor modelTwo factor model Second−order modelSecond−order model

Figure S8. shows the two-factor and second-order model of Pandemic Fatigue with fully standardized factor loadings,

(residual) variances, and covariances for USA. The model fit for both the two factor and second-order model is good

(RMSEA = .08, SRMR = .04, TLI = .97, CFI = .98).

10 Figure S9. OLS regressions predicting Pandemic, Behavioural and Information Fatigue in USA.

Pandemic Fatigue − USA Behavioural Fatigue − USA Information Fatigue − USA (n = 1,557 (n = 1,557) (n = 1,557)

−0.06 −0.11 * −0.00 Intercept

−0.03 −0.06 * −0.00 Age

−0.01 −0.03 0.01 Gender (Male)

0.10 0.19 *** 0.00 Education (University − Yes)

−0.11 *** −0.02 −0.16 *** Cognitive Risk

−.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 −.50 −.25 0 .25 .50 Estimates Figure S9 shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

11 Figure S10. OLS regressions predicting health-protective behaviours in USA.

Physical Distancing − USA Hygienic Behaviour − USA Mask Wearing − USA Information Seeking − USA (n = 1,557) (n = 1,557) (n = 1,557) (n = 1,557)

0.11 * 0.18 *** 0.14 ** −0.09 * Intercept

0.05 * −0.02 0.01 0.02 Age

−0.16 *** −0.31 *** −0.20 *** −0.04 Gender (Male)

−0.04 −0.04 −0.06 0.16 *** Education (University − Yes)

0.23 *** 0.18 *** 0.16 *** 0.25 *** Cognitive Risk

−0.35 *** −0.22 *** −0.26 *** −0.43 *** Pandemic Fatigue

−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50 Estimates Figure S10. shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

12 Figure S11. OLS regressions predicting health-protective behaviours in USA with Behavioural and Information Fatigue as independent predictors.

Physical Distancing − USA Hygienic Behaviour − USA Mask Wearing − USA Information Seeking − USA (n = 1,557) (n = 1,557) (n = 1,557) (n = 1,557)

0.10 * 0.17 *** 0.14 ** −0.07 Intercept

0.05 * −0.03 0.01 0.03 Age

−0.16 *** −0.31 *** −0.20 *** −0.03 Gender (Male)

−0.04 −0.03 −0.06 0.13 ** Education (University − Yes)

0.23 *** 0.19 *** 0.16 *** 0.23 *** Cognitive Risk

−0.22 *** −0.20 *** −0.15 *** −0.07 ** Behavioural Fatigue

−0.18 *** −0.05 −0.15 *** −0.41 *** Information Fatigue

−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50−.50 −.25 0 .25 .50 Estimates Figure S11. shows standardized β values with 95% confidence intervals. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

13 Supplementary tables

Table S1. Initial 10-item Pandemic Fatigue Scale. Items in English It bothers me to adhere to the behavioural guidelines.

I am tired of restricting my liberty to avoid the spread of COVID-19.

I am tired of all the COVID-19 discussions in TV shows, newspapers, and radio programs, etc.

I am exhausted from trying to keep up with the constantly changing recommendations around COVID-19.

I feel strained from following all of the behavioural regulations and recommendations around COVID-19.

I am sick of hearing about COVID-19.

I am tired of restraining myself to save those who are most vulnerable to COVID-19.

These days I am finding it more and more difficult to force myself to follow the COVID-19 regulations.

When friends or family members talk about COVID-19, I try to change the subject because I do not want to talk about it anymore.

I am losing my spirit to fight against COVID-19. Note. Response scale: 1 = strongly disagree, 2 = disagree, 3 = somewhat disagree, 4 = neutral/neither disagree nor agree, 5 = somewhat agree, 6 = agree, 7 = strongly agree. Items that were retained in the final six-item Pandemic Fatigue Scale are bolded.

Table S2. Very Simple Structure and Velicer’s Minimum Average Partial. Number of factors VVS 1 VVS 2 MAP 1 .89 .00 .03

2 .66 .74 .03

3 .41 .61 .06

4 .41 .52 .09

5 .33 .46 .14 Note. Abbreviations: Very Simple Structure (VVS); Minimum Average Partial (MAP).

15 Table S3. Standardized factor loadings for each item in the six-item Pandemic Fatigue Scale. Item number Item IF BF 1. I am tired of all the COVID-19 discussions in TV shows, newspapers, and radio programs, .85 -.04 etc.

2. I am sick of hearing about COVID-19. .88 .01

3. When friends or family members talk about COVID-19, I try to change the subject because .50 .22 I do not want to talk about it anymore.

4. I feel strained from following all of the behavioural regulations and recommendations .02 .83 around COVID-19.

5. I am tired of restraining myself to save those who are most vulnerable to COVID-19. .09 .58

6. I am losing my spirit to fight against COVID- -.06 .71 19. Note. Abbreviation: Information Fatigue (IF); Behavioural Fatigue (BF).

16 Table S4. OLS regressions controlling for age, gender, education and cognitive risk perception. Variable β (SE) Variable β (SE) Intercept (Control) .15** Intercept (High Pandemic Fatigue) -.02 (.06) (.06)

Low Pandemic Fatigue .09 Low Pandemic Fatigue .25*** (.06) (.06)

High Pandemic Fatigue -.17** Control .17** (.06) (.06)

Age .03 Age .03 (.02) (.02)

Gender (Male) -.22** Gender (Male) -.22** (.05) (.05)

Education (University – Yes) -.02 Education (University – Yes) -.02 (.05) (.05)

Cognitive Risk .31** Cognitive Risk .31** (.02) (.02)

N 1,557 N 1,557

R2 .13 R2 .13 Note. Standardized β values with standard errors in parentheses. Continuous variables are mean-centred and scaled by 1 standard deviation. *** p < 0.001; ** p < 0.01; * p < 0.05.

17 Table S5. Sociodemographics Danish and German cross-sectional COSMO surveys. Variable Denmark Germany Age

Mean 56.61 45.15

SD 15.26 15.70

Gender

Female 54.36% 50.19%

Male 45.41% 49,81%

Other 0.23% -

Education

Less than 10 years 7.81% 10.76%

10 years or more 92.19% 89.24%

Employment

Employed 53.32% 68.53%

Unemployed 46.68% 31.47%

Chronic disease

Yes 29.98% 34.92%

No 66.17% 62.04%

Don’t know 3.85% 3.04% Note. Abbreviations: Standard deviation (SD).

18 Table S6. Number of items, means, standard deviations, and Cronbach’s α for all measures considered from the Danish and German cross-sectional cosmo surveys. Denmark Germany Variable Items Mean SD α Items Mean SD α Physical distancing 2 6.49 0.78 .56 10 4.31 0.69 .90

Hygienic behaviour 3 6.25 0.79 .61 5 4.16 0.69 .75

Mask wearing 1 2.26 1.31 - 1 4.61 0.75 -

Information seeking 5 5.53 1.17 .86 1 5.34 1.49 -

Pandemic fatigue 6 3.22 1.29 .83 6 3.30 1.52 .87

Behavioural fatigue 3 2.80 1.35 .72 3 2.79 1.56 .78

Information fatigue 3 3.64 1.58 .82 3 3.82 1.80 .85

Cognitive risk 2 15.53 9.19 - 2 16.71 9.57 -

Affective risk 6 4.65 0.96 .75 6 4.65 1.14 .79

Trust 6 5.42 0.94 .83 11 4.53 1.43 .95

Worries 7 4.18 1.04 .72 9 4.89 1.03 .75

Optimism 1 3.61 0.90 - - - - -

Negative affect 4 2.25 1.00 .82 - - - -

Empathy 3 5.74 1.20 .86 - - - -

Honesty-Humility 4 4.35 0.58 .38 - - - -

Emotionality 4 2.94 0.67 .30 - - - -

Extraversion 4 4.13 0.67 .63 - - - -

Agreeableness vs. Anger 4 3.37 0.66 .44 - - - -

Conscientiousness 4 3.78 0.66 .48 - - - -

Openness to Experience 4 3.63 0.71 .53 - - - - Note. Abbreviations: Standard deviation (SD). Participants’ cognitive risk perception was estimated by taking the product of one item measuring participants’ assessment of how serious it would be for them to get infected and one item asking them to judge their own likelihood of contracting the virus.

19 Table S7. Item overview Danish cross-sectional COSMO survey. Variable Item Response format Age What year were you born? 1900-2020

Gender What is your gender? Male Female None of the above

Education What is your highest level of education completed? (1) No schooling, pre-school or primary school (Danish 1st-5th grade)

(2) Middle school (Danish 6th-8th grades)

(3) Middle/high school (Danish 9th- 10th grade)

(4) High school (Danish 12th grade completed)

(5) Short vocational education, basic programme completed

(6) Vocational education, main programme completed

(7) Middle-length higher education of 2-3 years

(8) Middle-length higher education of 3-4 years

20 (9) University degree, bachelor level

(10) University degree, master's level

(11) Licentiate

(12) Ph.D.

(99) Other

Employment What best describes your current situation? (1) I am a student

(2) I have a job

(3) I have my own company

(4) I am unemployed

(5) I am retired

(6) I am retired early and/or receive incapacity benefit

(99) Other

Chronic disease Do you suffer from any chronic illness? Yes No Don’t know

21 Pandemic fatigue Please indicate the extent to which you disagree or agree with the following statements.

(1) Strongly I am tired of all the COVID-19 discussions in TV shows, disagree newspapers, and radio programs, etc. - (7) Strongly agree

I am sick of hearing about COVID-19 (1) Strongly disagree - (7) Strongly agree

When friends or family members talk about COVID-19, I (1) Strongly disagree try to change the subject because I do not want to talk - about it anymore (7) Strongly agree

I feel strained from following all of the behavioural (1) Strongly disagree regulations and recommendations around COVID-19 - (7) Strongly agree

I am tired of restraining myself to save those who are most (1) Strongly disagree vulnerable to COVID-19 - (7) Strongly agree

I am losing my spirit to fight against COVID-19 (1) Strongly disagree - (7) Strongly agree

Cognitive risk perception How likely do you think it is that you will be infected? (1) Very unlikely - with the novel coronavirus (COVID-19)? (7) Very likely

How serious would it be for you if you contracted the (1) Not serious at all novel coronavirus (COVID-19)? - (7) Very serious

Affective risk perception (1) Close to me To me, the novel coronavirus (COVID-19) feels... - (7) Far away from me

To me, the novel coronavirus (COVID-19) feels... (1) Terrifying - (7) Not terrifying

To me, the novel coronavirus (COVID-19) feels... (1) Like something that makes me feel helpless - (7) Like something I can combat with my own actions

To me, the novel coronavirus (COVID-19) feels... (1) Slowly spreading - (7) Fast spreading

To me, the novel coronavirus (COVID-19) feels... (1) Like something I think of all the time - (7) Like something I don't think about at all

(1) Like To me, the novel coronavirus (COVID-19) feels... something to worry about - (7) Like something not to worry about

23 Trust How much confidence do you have that the following individuals and organizations are capable of handling

the novel coronavirus well and correctly? (1) Very low The police confidence - (7) Very high confidence

(1) Very low confidence Private businesses - (7) Very high confidence

Hospitals and doctors (1) Very low confidence - (7) Very high confidence

State authorities (1) Very low confidence - (7) Very high confidence

Experts (e.g. researchers) (1) Very low confidence - (7) Very high confidence

Politicians (1) Very low confidence - (7) Very high confidence

Worries Crises often involve fears and worries. At present, how much do you worry about:

(1) Don´t worry Loosing someone I love me at all - (7) Worries me a lot

24 The health care system being overloaded (1) Don´t worry me at all - (7) Worries me a lot

Small businesses going bankrupt (1) Don´t worry me at all - (7) Worries me a lot

Economic recession (1) Don´t worry me at all - (7) Worries me a lot

Shortage of food supplies (1) Don´t worry me at all - (7) Worries me a lot

Blackouts (1) Don´t worry me at all - (7) Worries me a lot

Society becoming more egoistic (1) Don´t worry me at all - (7) Worries me a lot

Physical distancing Please indicate the extent to which you disagree or agree with the following statements.

(1) Strongly I keep a distance to the elderly and/or people that I know disagree to suffer from a chronic illness - (7) Strongly agree

I try to limit the amount of physical contact I have with (1) Strongly disagree others (e.g. handshakes, kisses on the cheek, hugs) - (7) Strongly agree

Hygienic behaviour Please indicate the extent to which you disagree or agree with the following statements.

(1) Strongly I wash my hands often or use hand disinfectant disagree - (7) Strongly agree

I pay extra attention to cleaning at the moment (1) Strongly disagree - (7) Strongly agree

I make sure to cough or sneeze in my sleeve rather than in (1) Strongly disagree my hands - (7) Strongly agree

Mask wearing Do you use a mask when you go outside? (1) Never - (5) Always

Information seeking Please indicate the extent to which you disagree or agree with the following statements.

(1) Strongly I regularly seek out information on the current COVID-19 disagree situation. - (7) Strongly agree

I try to stay updated on the current COVID-19 restrictions. (1) Strongly disagree - (7) Strongly agree

I often read, listen to, or watch news about COVID-19. (1) Strongly disagree - (7) Strongly agree

I closely follow the announcements from the government (1) Strongly and/or the health authorities concerning COVID-19. disagree - (7) Strongly agree

I spend a considerable amount of time learning more about (1) Strongly disagree COVID-19. - (7) Strongly agree

Negative affect Please answer the following questions.

I am bored at the moment (1) Not at all - (5) Extremely

I feel lonely at the moment (1) Not at all - (5) Extremely

I feel isolated at the moment (1) Not at all - (5) Extremely

I feel stressed out at the moment (1) Not at all - (5) Extremely

Optimism Please answer the following question

I am very optimistic when I think about the future (1) Not at all - (5) Extremely

Empathy Please indicate the extent to which you disagree or agree with the following statements.

I am very concerned about those most vulnerable to the (1) Strongly novel coronavirus (COVID-19) disagree - (7) Strongly agree

27 I feel compassion for those most vulnerable to the novel (1) Strongly coronavirus (COVID-19) disagree - (7) Strongly agree

I am quite affected by what could happen to those most (1) Strongly vulnerable to the novel coronavirus (COVID-19) disagree - (7) Strongly agree

Honesty-Humility Please read the statements listed below and indicate for each of these to which extent you agree or disagree. Note

that there are no "right" or "wrong" answers. Please answer all statements even if you aren't completely certain of your answer. If nothing else is specified the statements refer to your behaviour (towards other people) or your general opinion.

(1) Strongly I find it difficult to lie disagree - (5) Strongly agree

I would like to know how to make lots of money in a (1) Strongly disagree dishonest manner - (5) Strongly agree

I want to be famous (1) Strongly disagree - (5) Strongly agree

I am entitled to special treatment (1) Strongly disagree - (5) Strongly agree

28 Emotionality Please read the statements listed below and indicate for each of these to which extent you agree or disagree. Note

(1) Strongly I am afraid of feeling pain disagree - (5) Strongly agree

I worry less than others (1) Strongly disagree - (5) Strongly agree

I can easily overcome difficulties on my own (1) Strongly disagree - (5) Strongly agree

I have to cry during sad or romantic movies (1) Strongly disagree - (5) Strongly agree

Extraversion Please read the statements listed below and indicate for each of these to which extent you agree or disagree. Note

(1) Strongly Nobody likes talking with me disagree - (5) Strongly agree

I easily approach strangers (1) Strongly disagree - (5) Strongly agree

I like to talk with others (1) Strongly disagree - (5) Strongly agree

I am seldom cheerful (1) Strongly disagree - (5) Strongly agree

Agreeableness Please read the statements listed below and indicate for vs. Anger each of these to which extent you agree or disagree. Note

(1) Strongly I remain unfriendly to someone who was mean to me disagree - (5) Strongly agree

I often express criticism (1) Strongly disagree - (5) Strongly agree

I tend to quickly agree with others (1) Strongly disagree - (5) Strongly agree

(1) Strongly Even when I'm treated badly, I remain calm disagree - (5) Strongly agree

30 Conscientiousness Please read the statements listed below and indicate for each of these to which extent you agree or disagree. Note

(1) Strongly I make sure that things are in the right spot disagree - (5) Strongly agree

I postpone complicated tasks as long as possible (1) Strongly disagree - (5) Strongly agree

I work very precisely (1) Strongly disagree - (5) Strongly agree

I often do things without really thinking (1) Strongly disagree - (5) Strongly agree

Openness to Experience Please read the statements listed below and indicate for each of these to which extent you agree or disagree. Note

(1) Strongly I can look at a painting for a long time disagree - (5) Strongly agree

I think science is boring (1) Strongly disagree - (5) Strongly agree

I have a lot of imagination (1) Strongly disagree - (5) Strongly agree

I like people with strange ideas (1) Strongly disagree - (5) Strongly agree

32 Table S8. Item overview German cross-sectional COSMO survey. Variable Item Response format Age How old are you? 0-100 years

Gender What is your gender? Male Female

Education Please provide information about your education. (1) Up to 9 years of schooling;

(2) At least 10 years (without university qualification);

(3) At least 10 years (with university qualification)

Employment Are you employed? Yes No

Chronic disease Do you suffer from any chronic illness? Yes No Don’t know

Pandemic fatigue Please indicate the extent to which you disagree or agree with the following statements.

I am tired of all the COVID-19 discussions in TV shows, (1) Strongly disagree newspapers and radio programs, etc. - (7) Strongly agree

(1) Strongly disagree I am sick of hearing about COVID-19 - (7) Strongly agree

(1) Strongly disagree When friends or family members talk about COVID-19, I - try to change the subject because I do not want to talk (7) Strongly agree about it anymore

(1) Strongly disagree I feel strained from following all of the behavioural - regulations and recommendations around COVID-19 (7) Strongly agree

I am tired of restraining myself to save those who are most (1) Strongly disagree vulnerable to COVID-19 - (7) Strongly agree

(1) Strongly disagree I am losing my spirit to fight against COVID-19 - (7) Strongly agree

Cognitive risk perception (1) Very unlikely How likely do you think it is that you will be infected with - the novel coronavirus (COVID-19)? (7) Very likely

(1) Not serious at all How serious would it be for you if you contracted the novel - coronavirus (COVID-19)? (7) Very serious

Affective risk perception (1) Close to me To me, the novel coronavirus (COVID-19) feels... - (7) Far away from me

(1) Terrifying To me, the novel coronavirus (COVID-19) feels... - (7) Not terrifying

(1) Like something To me, the novel coronavirus (COVID-19) feels... that makes me feel helpless - (7) Like something I can combat with my own actions

To me, the novel coronavirus (COVID-19) feels... (1) Slowly spreading - (7) Fast spreading

To me, the novel coronavirus (COVID-19) feels... (1) Like something I think of all the time - (7) Like something I don't think about at all

(1) Like something to To me, the novel coronavirus (COVID-19) feels... worry about - (7) Like something not to worry about

Trust How much confidence do you have that the following individuals and organizations are capable of handling the

novel coronavirus well and correctly?

Media (1) Very low confidence - (7) Very high confidence

Hospitals (1) Very low confidence - (7) Very high confidence

Your doctor (1) Very low confidence - (7) Very high confidence

Local health authorities (1) Very low confidence - (7) Very high confidence

Ministry of Health in your state (1) Very low confidence - (7) Very high confidence

35 Federal Ministry of Health (1) Very low confidence - (7) Very high confidence

Robert Koch Institute (RKI) (1) Very low confidence - (7) Very high confidence

Federal Centre for Health Education (BZgA) (1) Very low confidence - (7) Very high confidence

Science (1) Very low confidence - (7) Very high confidence

Federal government (1) Very low confidence - (7) Very high confidence

World Health Organization (WHO) (1) Very low confidence - (7) Very high confidence

Worries Crises often involve fears and worries. At present, how much do you worry about:

(1) Don´t worry me at Loosing someone I love all - (7) Worries me a lot

The health care system being overloaded (1) Don´t worry me at all - (7) Worries me a lot

36 Small businesses going bankrupt (1) Don´t worry me at all - (7) Worries me a lot

Economic recession (1) Don´t worry me at all - (7) Worries me a lot

Society becoming more egoistic (1) Don´t worry me at all - (7) Worries me a lot

Financial difficulties due to a loss of income (1) Don´t worry me at all - (7) Worries me a lot

An increasing gap between the rich and the poor (1) Don´t worry me at all - (7) Worries me a lot

Getting sick (1) Don´t worry me at all - (7) Worries me a lot

Restrictions on social life in the long run (1) Don´t worry me at all - (7) Worries me a lot

Physical distancing During the past week how often have you adhered to the following regulations to avoid the spread and infection

of the novel coronavirus?

Avoided handshakes (1) Never - (5) Always

Kept 1.5 meters distance to other people in public places (1) Never - (5) Always

37 Avoided public places (1) Never - (5) Always

Avoided private parties (1) Never - (5) Always

Only gone out to do what is necessary (e.g. grocery (1) Never - shopping) (5) Always

Refrained from travelling (1) Never - (5) Always

Avoided crowded rooms with poor ventilation (1) Never - (5) Always

Avoided crowded places (1) Never - (5) Always

Avoided lively conversations and close contact with others (1) Never - (5) Always

Avoided people I know (1) Never - (5) Always

Hygienic behaviour During the past week how often have you adhered to the following regulations to avoid the spread and infection

of the novel coronavirus?

Avoided touching my eyes, nose and mouth with unwashed (1) Never hands - (5) Always

Used hand sanitizer (1) Never - (5) Always

38 Covered my mouth when coughing (1) Never - (5) Always

Washed my hands for 20 seconds (1) Never - (5) Always

Ventilated rooms on a regular basis (1) Never - (5) Always

Mask wearing During the past week how often have you adhered to the following regulations to avoid the spread and infection of

the novel coronavirus?

Worn a mask (1) Never - (5) Always

Information seeking

(1) Never How often do you seek out information about the - Coronavirus / COVID-19? (7) Very often

39 Table S9. Number of items, means, standard deviations, and Cronbach’s α for all measures obtained in the experiment. Full sample Control Low Pandemic High Pandemic Fatigue Fatigue Variable Items Mean SD α Mean SD Mean SD Mean SD Cognitive risk 2 17.37 10.40 - 17.43 10.89 17.40 10.02 17.27 10.28

Pandemic fatigue 6 3.30 1.43 .85 3.29 1.45 3.08 1.36 3.55 1.43

Behavioural 3 2.94 1.48 .75 2.91 1.48 2.74 1.47 3.20 1.46 fatigue

Information 3 3.66 1.73 .86 3.67 1.77 3.41 1.62 3.90 1.75 fatigue

Physical 1 5.96 1.48 - 5.99 1.46 6.07 1.47 5.81 1.51 distancing

Hygienic 1 6.08 1.30 - 6.14 1.29 6.11 1.34 5.98 1.26 behaviour

Mask wearing 1 6.14 1.52 - 6.21 1.51 6.20 1.49 6.00 1.55

Information 1 5.10 1.74 - 5.09 1.73 5.39 1.67 4.79 1.77 seeking

Behavioural intentions 4 5.82 1.15 .76 5.86 1.13 5.94 1.13 5.65 1.18 composite score Note. Abbreviations: Standard deviation (SD). Participants’ cognitive risk perception was estimated by taking the product of one item measuring participants’ assessment of how serious it would be for them to get infected and one item asking them to judge their own likelihood of contracting the virus.

40 Table S.10 Item overview for the experimental study. Variable Item Response format Age Please indicate your age 0-100 years

Gender Please indicate your gender Male Female Other

Education Please indicate your highest level of education (1) Elementary school

(2) Secondary school

(3) High school

(4) Bachelor

(5) Master

(6) Ph.D.

(7) Other

Cognitive risk On this page we kindly ask you to answer the following perception two questions concerning your perceived risk

of contracting the novel coronavirus (COVID-19) (1) Very unlikely How likely do you think it is that you will be infected with - the novel coronavirus (COVID-19)? (7) Very likely

(1) Not serious at all How serious would it be for you if you contracted the novel - coronavirus (COVID-19)? (7) Very serious

Pandemic fatigue On this page we kindly ask you to indicate how much you disagree or agree with the following statements

I am tired of all the COVID-19 discussions in TV shows, (1) Strongly disagree newspapers, and radio programs, etc. - (7) Strongly agree

(1) Strongly disagree I am sick of hearing about COVID-19 - (7) Strongly agree

When friends or family members talk about COVID-19, I (1) Strongly disagree - try to change the subject because I do not want to talk (7) Strongly agree about it anymore

I feel strained from following all of the behavioural (1) Strongly disagree - regulations and recommendations around COVID-19 (7) Strongly agree

I am tired of restraining myself to save those who are most (1) Strongly disagree vulnerable to COVID-19 - (7) Strongly agree

(1) Strongly disagree I am losing my spirit to fight against COVID-19 - (7) Strongly agree

Physical distancing On this page we kindly ask you to indicate how much you disagree or agree with the following statements.

Over the next two weeks I will avoid physical contacts and (1) Strongly disagree keep a safe distance to people outside my own household - (7) Strongly agree

Hygienic behaviour On this page we kindly ask you to indicate how much you disagree or agree with the following statements.

Over the next two weeks I will wash my hands very often (1) Strongly disagree and thoroughly and/or use hand disinfectant frequently - (7) Strongly agree

Mask wearing On this page we kindly ask you to indicate how much you disagree or agree with the following statements.

Over the next two weeks I will wear a face mask whenever (1) Strongly disagree I am inside and cannot keep a safe physical distance to - people outside my own household (7) Strongly agree

42 Information On this page we kindly ask you to indicate how much you seeking disagree or agree with the following statements.

Over the next two weeks I will do everything I can to keep (1) Strongly disagree myself updated about the development of the pandemic, and - stay informed about the current COVID-19 restrictions (7) Strongly agree

Table S11. Sociodemographic information per condition in the experimental study. Variable Control Low Pandemic Fatigue High Pandemic Fatigue Age

Mean 36.37 35.48 34.83

SD 12.16 11.84 11.55

Gender

Female 52.90% 47.17% 50.80%

Male 45.29% 51.13% 47.61%

Other 1.81% 1.70% 1.59%

Education

Elementary school 0.00% 0.00% 0.00%

Secondary school 0.00% 0.57% 0.40%

High school 26.45% 24.91% 23.51%

Bachelor 45.29% 42.64% 44.82%

Master 18.30% 21.89% 20.92%

Ph.D. 3.44% 3.02% 3.78%

Other 6.52% 6.98% 6.57% Note. Abbreviations: Standard deviation (SD).