Introduction

At the time of this research (December 2020), the coronavirus disease (COVID-19) was imposing substantial restrictions on the way people were living. As an efficient therapeutic cure was still lacking and vaccination programs had not yet started, many countries resorted to non-pharmaceutical containment measures, including the reduction of physical contact, the suspension of gatherings, the closing of borders, among others. Mathematical modeling of the COVID-19 transmission dynamics has demonstrated that these measures can be effective in limiting the spread of the virus (e.g., Kucharski et al., 2020; Prem et al., 2020). However, for these measures to be effective, individual compliance is critical. One psychological construct that has been proposed to affect compliance is boredom (Martarelli and Wolff, 2020) and research suggests that boredom proneness (i.e., a general tendency to experience boredom more frequently and more intensely, Farmer and Sundberg, 1986) undermines peopleā€™s compliance with containment measures (Bieleke et al., 2021; Boylan et al., 2020; Wolff et al., 2020). However, while research indicates that trait-like boredom proneness might threaten adherence to containment measures, less is known about whether adherence to containment measures can in turn elicit state boredom. Investigating whether compliance with containment measures is a determinant of state boredom is the main goal of this study.

Pandemic boredom: the role of perceived value and effort

Several theories of boredom have been proposed (for a comprehensive review see Westgate and Wilson, 2018) and despite disagreement whether boredom is one or many (Elpidorou, 2021), researchers agree that boredom is an aversive experience of wanting but failing to satisfy the want (Eastwood et al., 2012; Danckert et al., 2018). The Meaning and Attentional Components (MAC) model (Westgate and Wilson, 2018) as well as the Control-Value Theory (CVT) of achievement emotions (Pekrun, 2006; Pekrun et al., 2010) are both compatible with the idea that perceived value and effort play an important role in the experience of boredom. Indeed, boredom might occur when (1) there is nothing meaningful available to do (see also Fahlman et al., 2009; van Tilburg and Igou, 2012) and (2) when one experiences a high degree of mental effort in trying to engage with an ongoing activity (understimulation or overstimulation, see also Bieleke et al., 2021; Eastwood et al., 2012). First, a perceived lack of meaning has been highlighted as an important determinant of the experience of boredom (e.g., Pekrun, 2006; Fahlman et al., 2009; Pekrun et al., 2010). Van Tilburg and Igou (2013) proposed that individuals take into account two aspects when evaluating the meaningfulness of behavior: The value of the superordinate goal and the usefulness of the actual behavior to reach that goal (see also Westgate and Wilson, 2018). Second, being trapped in a boring situation with constrained opportunities to engage in alternative, rewarding activities should be accompanied by feelings of mental effort (e.g., Eastwood et al., 2012). But why is being bored accompanied by the sense of effort? One likely answer comes from recent functional accounts of boredom and its interplay with self-control (e.g., Bieleke and Wolff, 2021; Wolff and Martarelli, 2020), in which boredom is understood to act as a signal to engage with something else that is more rewarding (e.g., Bench and Lench, 2013, 2019; Kurzban et al., 2013; Elpidorou, 2014, 2018; Danckert, 2019). More precisely, boredom signals that an activity is decreasing in value and that the available resources might be better spent engaging in something else. In turn, choosing (or being forced) to stay engaged with an activity that is boring requires self-control, the application of which creates the sense of effort (e.g., Shenhav et al., 2017).

Boredom has been highlighted as a potential consequence of prolonged adherence to containment measures before (Droit-Volet et al., 2020; Yan et al., 2021). After almost one year of behavioral restrictions due to the COVID-19 pandemic, it is conceivable that changes in perceived value and in perceived effort give rise to boredom during the pandemic: The limited set of available activities has likely become monotonous and uninteresting, and compliance might likewise feel difficult and exhausting. Indeed, media outlets have coined the term ā€œpandemic fatigueā€ (e.g., Badre, 2021) and have started to focus on the potential rise of boredom during the pandemic (e.g., Ehl, 2021). A time where adhering to containment measures might feel particularly hard and void of meaning are the thanksgiving and winter holidays. While these holidays traditionally entail visiting loved ones, travel and gathering restrictions substantially limit the degree to which it is safe and legal to do so. Staying home alone during this time and complying with restrictions therefore likely requires additional effort and severely tests the degree to which one perceives these measures as being valuable (particularly in contrast with what one is missing out on).

The present study

When data were collected for the present study, there was a rise of COVID-19 infections, hospitalizations, and deaths across the world. Countries were facing the coronavirus second wave, and there were no therapeutic agents available. Thus, several containment measures restricting the freedom of movement (e.g., closing of workplaces, schools, and borders, among others) used during the coronavirus first wave were again employed by governments. Countries were in the process of gradually tightening the containment measures. Restrictions on freedom of movement have been suggested to amplify the experience of boredom in boredom prone individuals (Martarelli and Wolff, 2020). Indeed, behavioral alternatives are reduced when containment measures come into force, which should increase and intensify the experience of boredom.

In line with this idea, we examined experienced and forecasted pandemic boredom as a result of avoiding to travel and to gather with others (Owens and Baker, 2020) during the past thanksgiving (retrospective) and intending to do so during the upcoming winter holidays (prospective) in the US, respectively. Including both retrospective and prospective behaviors allows us to test the same model at two timepoints and serves as a robustness check. We further investigated pandemic boredom by adopting a cost-value approach to behavior and boredom. A lack of meaning and value as well as effort-related costs are known to prompt the experience of boredom (Eastwood et al., 2012; Westgate and Wilson, 2018). We thus expected boredom to be experienced especially when low value and high effort are ascribed to avoiding traveling and gathering (i.e., direct effects of value and effort on boredom). However, people should also be less likely to avoid traveling and gathering if they ascribe low value and high effort to these measures, which then should lead to reduced boredom (i.e., indirect effects of value and effort on boredom). Note that the direct and indirect effects should be inverted: While low value and high effort increase boredom directly, they also reduce boredom by instigating non-compliance with behavioral recommendations. Which of these two effects ultimately determines the experience of boredom is an open question that we address in the present research. To scrutinize the impact of the pandemic situation, we additionally controlled for the effects of individual differences in boredom proneness as a predictor of pandemic boredom. Figure 1 summarizes the proposed model and the hypothesized direction of direct and indirect effects. Besides these main hypotheses, we predicted an association between pandemic boredom, boredom proneness, and negative state-like affect. The degree to which countries have been and are still affected by COVID-19 as well as the specific containment measures that they employ vary. Therefore, we additionally aimed to test the proposed model in states with COVID-19 restrictions vs. states without COVID-19 restrictions to explore the impact of this dimension on the proposed relationships.

Fig. 1: Conceptual model in which the effect of effort and value on pandemic boredom is mediated by avoiding to travel and to gather.
figure 1

Avoiding to travel and to gather (situational variables) as well as boredom proneness (personality) predict pandemic boredom. The hypothesized direction of effects is illustrated by [+] and [āˆ’] signs.

Methods

Participants

Participants were recruited on December 18th and 19th 2020 from Amazonā€™s website Mechanical Turk (MTurk; requirements: ā‰„50 HITs, approval rate ā‰„90%, US citizenship). One-thousand five-hundred sixty-six participants completed the online questionnaire for $1.00. Thirteen participants (0.8%) did not answer at the instructional manipulation check item correctly and were thus removed. The remaining sample comprised 1553 participants (47.3% female, 51.7% male, 1% other) with an average age of 40.36 years (SDā€‰=ā€‰12.65). The majority of participants reported 13 years or more of education (86.09%) and was either working full-time (56.15%) or self-employed (13.46%).

A sample size of 1500 participants was targeted to allow recruitment of participants from all the US states and thus assure participation of individuals living in US states with official COVID-19 restrictions and in US states without official restrictions. All US states were represented in the sample, with most participants coming from California (138 participants, 8.89%), followed by Florida (115 participants, 7.41%), Texas (106 participants, 6.83%), and New York (94 participants, 6.05%). The local ethics committee approved the study, which was conducted in accordance with the Declaration of Helsinki. All participants gave their written informed consent prior to their inclusion in the study.

Procedure and materials

Participants completed the study online, using the Qualtrics Survey Software (https://www.qualtrics.com). The full study is available on OSF (https://osf.io/4sje6/). After giving informed consent, participants confirmed to be at least 21 years of age and completed an instructional manipulation check. Next, participants worked on the retrospective questions regarding the thanksgiving holidays, followed by the prospective questions regarding the winter holidays. Finally, participants worked on three personality questionnaires and provided their demographic information (income, education, employment, gender, age). After presenting the personality questionnaires, we additionally included three self-control single items. The data obtained from the personality questionnaires and the three single items were not considered in the context of this study. We used 5-point Likert scales unless otherwise reported (1ā€‰=ā€‰strongly disagree, 5ā€‰=ā€‰strongly agree).

Traveling and gathering over thanksgiving (retrospective) and over the winter holidays (prospective)

In the public discourse, restrictions with respect to traveling and gathering to meet people have been highlighted as particularly demanding measures over country-wide holiday periods (Owens and Baker, 2020). Based on a questionnaire of the Harris Poll (Owens and Baker, 2020) we adapted two items to investigate whether participants avoided traveling and gathering with those who do not live in their home over thanksgiving (i.e., ā€œover thanksgiving I avoided travelingā€ and ā€œover thanksgiving I avoided gathering with those who do not live in my homeā€) and how likely they are to do so for the winter holidays (i.e., ā€œover the winter holidays I will avoid travelingā€ and ā€œover the winter holidays I will avoid gathering with those who do not live in my homeā€). Next, it was assessed whether avoiding to travel and to gather was considered valuable over thanksgiving (e.g., ā€œover thanksgiving, avoiding to travel was worth it for me,ā€ ā€œover thanksgiving, avoiding to travel was worthwhile for slowing the spread of COVID-19;ā€ see Supplementary information Appendix A for the complete list of items) and whether it will be valuable over the winter holidays (e.g., ā€œavoiding to gather with those who do not live in my home over the upcoming winter holidays will be worth it for meā€ and ā€œavoiding to gather with those who do not live in my home over the upcoming winter holidays will be worthwhile for slowing the spread of COVID-19;ā€ see Supplementary information Appendix A for the complete list of items). We further investigated whether avoiding to travel and to gather was perceived as effortful over thanksgiving and whether it will be effortful over the winter holidays (e.g., ā€œavoiding to travel over the upcoming winter holidays will require effort from meā€ and ā€œavoiding to gather with those who do not live in my home over the upcoming winter holidays will require effort from me;ā€ see Supplementary information Appendix A for the complete list of items).

Experience of boredom

To assess the experience of boredom we used three adjectives representing pandemic boredom (i.e., bored, dull, monotonous) taken from the Epistemically-Related Emotion Scales (EES) of Pekrun et al. (2017). These scales are well validated and the focus on understimulation (i.e., dull and monotonous) fits with the current pandemic situation, that might trigger experiences of boredom because of understimulation rather than overstimulation. We additionally included the short form of the Positive and Negative Affect Schedule (Mackinnon et al., 1999), which consists of five positive (i.e., alert, inspired, enthusiastic, excited, determined) and five negative items (i.e., distressed, afraid, nervous, upset, scared). The 13 adjectives (regarding boredom, positive affect, and negative affect) were presented in random order. The exact instructions for evaluating the emotional experience over thanksgiving and over the winter holidays read as follows: ā€œWe are interested in your emotional experience over thanksgiving. For each emotion, please indicate the extent you felt this way over thanksgivingā€ and ā€œWe are interested in your forecasted emotional experience over the upcoming winter holidays. For each emotion, please indicate the extent you will feel this way over the upcoming winter holidays.ā€ Five-point Likert scales (1ā€‰=ā€‰very slightly or not at all, 5ā€‰=ā€‰extremely) were used.

Subjective perception of restrictions

Then the subjective perception of COVID-19 restrictions was assessed with four items (i.e., ā€œDo the current regional COVID-19 restrictions permit that you travel over the winter holidaysā€ and ā€œDo the current regional COVID-19 restrictions permit that you gather with those who do not live in your home over the winter holidays;ā€ see Supplementary information Appendix A for the complete list of items). To facilitate interpretation of results, these items were reverse coded (the higher the values, the higher the perceived restrictions).

Boredom proneness

We administered the Boredom Proneness Scale-Short Form (Struk et al., 2017), which is a short questionnaire used to investigate trait boredom (8 items, e.g., ā€œI often find myself at ā€˜loose ends,ā€™ not knowing what to doā€). Mean response scores for this personality variable were computed.

Results

We report structural equation modeling in order to investigate the determinants of pandemic boredom over the thanksgiving holidays (retrospective) and over the winter holidays (prospective). In these analyses we included effort, value, avoid traveling and gathering, boredom proneness as well as pandemic boredom in aggregated form. Reliability analyses are reported below. Moreover, we computed a multigroup analysis, to compare US states with COVID-19 restrictions and US states without restrictions. To categorize the US states, we resorted to information from webpages usually taken into account by US citizensā€”i.e., Gale (2020a) for thanksgiving, published on 16.11.2020, and Gale (2020b) for the winter holidays, published on 21.12.2020. When the webpage stated ā€œno restrictionā€ the state was considered as a state without restrictions. All other states were coded as states with restrictions. Four individuals of the total sample did not report their state (remaining sample of Nā€‰=ā€‰1549). Over thanksgiving 907 individuals (58.4%) were living in an US state with restrictions and over the winter holidays it was 818 individuals that were living in a state with restrictions (52.8%). The analyses were computed with R (R core Team 2020) with the functionalities of the lavaan package (Rosseel, 2018). The R code to reproduce the analyses as well as the data set is available on OSF at https://osf.io/4sje6/.

The variables effort, value, avoid traveling and gathering, pandemic boredom, positive affect, negative affect, and subjective restrictions were created by aggregating items across traveling and gathering (but separately for thanksgiving and the winter holidays). In addition, the variable boredom proneness was computed. The internal consistency of the variables was good to very good (see Table 1). The correlations between the variables are reported in Table 2.

Table 1 Descriptive summary of measures.
Table 2 Correlations.

Compliance with the recommended behaviors was high (mean of 4.19 out of 5 over thanksgiving and mean of 4.04 out of 5 over the winter holidays). The perceived value of recommended behaviors was in a similar range (mean of 4.08 out of 5 over thanksgiving and mean of 4.00 out of 5 over the winter holidays) whereas exerted effort was medium (mean of 2.70 out of 5 over thanksgiving and mean of 2.90 out of 5 over the winter holidays). The experience of boredom over thanksgiving as well as the forecasted experience of boredom over the winter holidays were relatively low (mean of 1.95 out of 5 over thanksgiving and mean of 1.88 out of 5 over the winter holidays). As expected, the experience of boredom turned out to be aversive. Indeed, pandemic boredom was strongly positively correlated with negative affect (over thanksgiving rā€‰=ā€‰0.428 and over the winter holidays rā€‰=ā€‰0.482) and negatively with positive affect (over thanksgiving rā€‰=ā€‰āˆ’0.279 and over the winter holidays rā€‰=ā€‰āˆ’0.288). Negative and positive affect did not correlate, which is in agreement with the orthogonality of the two subscales in Watson, Clark and Tellegenā€™s two-factorial model (1988).

Note that the positive affect over thanksgiving as well as the forecasted positive affect over the winter holidays was medium (mean of 2.52 out of 5 over thanksgiving and mean of 2.65 out of 5 over the winter holidays), whereas the negative affect was rather low (mean of 1.57 out of 5 over thanksgiving and mean of 1.61 out of 5 over the winter holidays).

Objective restrictions (coded as 0 for US states without restrictions) was positively associated with subjective restrictions (higher values on this scale reflects restrictions) both over thanksgiving (rā€‰=ā€‰0.178) and the winter holidays (rā€‰=ā€‰0.207). These associations illustrate that official restrictions were taken into account; however, the large amount of unexplained variance suggests that other factors also contribute to the perceived restrictions.

Table 2 further shows correlations between our predictor, mediator, and outcome variables. The correlations were in the expected direction, and stronger in the prospective context (winter holidays) when compared to the retrospective context (thanksgiving). Strong associations were revealed between the variables value and avoid traveling and gathering (rā€‰=ā€‰0.742 over thanksgiving and rā€‰=ā€‰0.795 over the winter holidays). Medium correlations were observed between pandemic boredom and boredom proneness (rā€‰=ā€‰0.388 over thanksgiving and rā€‰=ā€‰0.395 over the winter holidays), as well as between negative affect and boredom proneness (rā€‰=ā€‰0.331 over thanksgiving and rā€‰=ā€‰0.344 over the winter holidays).

Retrospective thanksgiving model

The unstandardized path coefficients, standard errors, and p-values of the thanksgiving model can be found in Table 3 and are depicted in Fig. 2. Individual differences in perceived value had a weak direct influence on boredom, bā€‰=ā€‰āˆ’0.071, Ī²ā€‰=ā€‰āˆ’0.082, SEā€‰=ā€‰0.031, pā€‰=ā€‰0.021. Likewise, effort had a weak direct effect on boredom, bā€‰=ā€‰0.096, Ī²ā€‰=ā€‰0.130, SEā€‰=ā€‰0.018, pā€‰<ā€‰0.001. That is, the less avoiding to travel and to gather was perceived as valuable and the more it was perceived as effortful, the more boredom was experienced over thanksgiving. These direct effects are in line with the conceptualization of boredom as being characteristic of situations that are low in value and effortful to maintain.

Table 3 Regression coefficients, standard errors, and summary information for the thanksgiving model.
Fig. 2: Thanksgiving model. Coefficients are unstandardized.
figure 2

***Difference is significant at the 0.001 level (two-tailed) and *Difference is significant at the 0.05 level (two-tailed). Nā€‰=ā€‰1553.

Turning to the indirect effects, we observed that avoiding to travel and to gather were strongly positively influenced by their perceived value, bā€‰=ā€‰0.780, Ī²ā€‰=ā€‰0.742, SEā€‰=ā€‰0.024, pā€‰=ā€‰<0.001. However, effort was not a significant predictor, bā€‰=ā€‰āˆ’0.025, Ī²ā€‰=ā€‰āˆ’0.027, SEā€‰=ā€‰0.014, pā€‰=ā€‰0.088, although the direction of the effect was as expected. Avoiding to travel and to gather in turn had the expected positive impact on boredom, bā€‰=ā€‰0.219, Ī²ā€‰=ā€‰0.266, SEā€‰=ā€‰0.028, pā€‰=ā€‰<0.001. The resulting indirect effect of value on boredom, bā€‰=ā€‰0.171, Ī²ā€‰=ā€‰0.197, SEā€‰=ā€‰0.023, pā€‰=ā€‰<0.001, was significant, whereas the indirect effect of effort on boredom was not, bā€‰=ā€‰āˆ’0.005, Ī²ā€‰=ā€‰āˆ’0.007, SEā€‰=ā€‰0.003, pā€‰=ā€‰0.104. These results were obtained while accounting for the moderate association between boredom proneness and pandemic boredom, bā€‰=ā€‰0.403, Ī²ā€‰=ā€‰0.382, SEā€‰=ā€‰0.026, pā€‰=ā€‰<ā€‰0.001. In other words, boredom was predicted by the value and effort associated with containment measures over and beyond stable interindividual differences in boredom proneness. The total effect of value on boredom, bā€‰=ā€‰0.100, Ī²ā€‰=ā€‰0.115, SEā€‰=ā€‰0.020, pā€‰=ā€‰<0.001, was significant, as well as the total effect of effort on boredom, bā€‰=ā€‰0.091, Ī²ā€‰=ā€‰0.123, SEā€‰=ā€‰0.018, pā€‰=ā€‰<0.001. The model fitted the data very well, RSMEAā€‰=ā€‰0.054, SRMRā€‰=ā€‰0.030, CFIā€‰=ā€‰0.992, TLIā€‰=ā€‰0.972. The model explained 55.2% of variance in the variable avoid traveling and gathering and 20.5% of variance in the variable pandemic boredom.

Thanksgiving model adjusted for age and gender

We additionally estimated the model including age and gender. Age had a small significant impact on avoid traveling and gathering, bā€‰=ā€‰0.004, Ī²ā€‰=ā€‰0.044, SEā€‰=ā€‰0.002, pā€‰=ā€‰0.004 but not on the experience of boredom (pā€‰=ā€‰0.725). Gender had no impact on both variables (pā€‰>ā€‰0.396). Accounting for age and gender did not change the other results (no change in accepting or rejecting the null hypotheses).

Objective restrictions

Next the same model was fitted separately for US states with COVIDāˆ’19 restrictions and US states without restrictions (multigroup analysis). The regression coefficients and summary information are reported in Table 4. The results turned out to be highly similar between groups. The only change in statistical significance pertains to the direct effect of value on pandemic boredom, which turned out to be non-significant in the US states without restrictions (pā€‰=ā€‰0.386). The model fitted the data very well, RSMEAā€‰=ā€‰0.062, SRMRā€‰=ā€‰0.030, CFIā€‰=ā€‰0.989, TLIā€‰=ā€‰0.964. The descriptive summary of measures between groups is reported in Supplementary information Appendix B (Table B1).

Table 4 Regression coefficients, standard errors, and summary information for the thanksgiving model fitted in US states with restrictions and US states without restrictions (multigroup analysis).

Prospective winter holidays model

The unstandardized path coefficients, standard errors, and p-values of the winter holidays model are reported in Table 5 and are depicted in Fig. 3. The results are highly similar to the thanksgiving model. In the winter holiday model, the effects were slightly stronger, and all paths turned out to be significant. Individual differences in perceived value weakly influenced the forecasted experience of boredom during the upcoming winter holidays, bā€‰=ā€‰āˆ’0.093, Ī²ā€‰=ā€‰āˆ’0.112, SEā€‰=ā€‰0.034, pā€‰=ā€‰0.006. Likewise, effort directly but weakly affected the experience of boredom, bā€‰=ā€‰0.093, Ī²ā€‰=ā€‰0.133, SEā€‰=ā€‰0.017, pā€‰=ā€‰<0.001. That is, the less individuals valued to avoid traveling and gathering during the winter holidays and the more effortful they expected it to be, the higher the forecasted boredom. Therefore, the direct effects are once more in line with the conceptualization of boredom as being characteristic of situations that are low in value and effortful to maintain.

Table 5 Regression coefficients, standard errors, and summary information for the winter holidays model.
Fig. 3: Winter holidays model.
figure 3

Coefficients are unstandardized. ***Difference is significant at the 0.001 level (two-tailed) and **Difference is significant at the 0.01 level (two-tailed). Nā€‰=ā€‰1553.

Turning to the indirect effects, we found that the intention to avoid traveling and gathering was strongly positively related to its value, bā€‰=ā€‰0.821, Ī²ā€‰=ā€‰0.790, SEā€‰=ā€‰0.021, pā€‰=ā€‰<0.001, and weakly negatively to its perceived effort, bā€‰=ā€‰āˆ’0.051, Ī²ā€‰=ā€‰āˆ’0.058, SEā€‰=ā€‰0.013, pā€‰<ā€‰0.001. Moreover, the intention to avoid traveling and gathering also had a small positive impact on pandemic boredom, bā€‰=ā€‰0.256, Ī²ā€‰=ā€‰0.319, SEā€‰=ā€‰0.032, pā€‰=ā€‰<0.001. The resulting indirect effects of value on boredom, bā€‰=ā€‰0.210, Ī²ā€‰=ā€‰0.252, SEā€‰=ā€‰0.026, pā€‰=ā€‰<0.001, and of effort on boredom, bā€‰=ā€‰āˆ’0.013, Ī²ā€‰=ā€‰āˆ’0.018, SEā€‰=ā€‰0.004, pā€‰=ā€‰0.001, both turned out to be significant. These results were obtained while accounting for the moderate association between boredom proneness and pandemic boredom, bā€‰=ā€‰0.418, Ī²ā€‰=ā€‰0.386, SEā€‰=ā€‰0.028, pā€‰=ā€‰<0.001. Accordingly, the forecasted pandemic boredom during the winter holidays was predicted by the expected value and effort of the containment measures over and beyond stable interindividual differences in boredom. The total effect of value on boredom, bā€‰=ā€‰0.117, Ī²ā€‰=ā€‰0.140, SEā€‰=ā€‰0.019, pā€‰=ā€‰<0.001, was significant, as well as the total effect of effort on boredom, bā€‰=ā€‰0.080, Ī²ā€‰=ā€‰0.114, SEā€‰=ā€‰0.018, pā€‰=ā€‰<0.001. The model fitted the data very well, RSMEAā€‰=ā€‰0.061, SRMRā€‰=ā€‰0.028, CFIā€‰=ā€‰0.991, TLIā€‰=ā€‰0.971. The model explained 63.6% of variance in the variable avoid traveling and gathering and 21.6% of variance in the variable pandemic boredom.

Winter holidays model adjusted for age and gender

We additionally estimated the model including age and gender. Both predictors turned out to be non-significant (pā€‰>ā€‰0.237) and they did not change the other results (no change in accepting or rejecting the null hypotheses).

Objective restrictions

The same model was fitted in US states with COVID-19 restrictions and US states without restrictions (multigroup analysis). The regression coefficients and summary information are reported in Table 6. The results turned out to be highly similar between groups. Again, the only change in statistical significance pertains the direct effect of value on boredom pandemic, which turned out to be non-significant in the US states without restrictions (pā€‰=ā€‰0.195). The model fitted the data very well, RSMEAā€‰=ā€‰0.058, SRMRā€‰=ā€‰0.026, CFIā€‰=ā€‰0.992, TLIā€‰=ā€‰0.973. The descriptive summary of measures between groups is reported in Supplementary information Appendix B (Table B2).

Table 6 Regression coefficients, standard errors, and summary information for the winter holidays model fitted in US states with restrictions and US states without restrictions (multigroup analysis).

Discussion

We investigated the cognitive and behavioral mechanisms that underlie pandemic boredom. Besides examining the effect of behavioral compliance with COVIDāˆ’19 recommendations on boredom, we were particularly interested in teasing apart the direct and indirect effects of the value and effort ascribed to following these recommendations on the experience of boredom. In line with current theorizing on pandemic boredom (Martarelli and Wolff, 2020) higher retrospective and prospective compliance with behavioral recommendations predicted more boredom. In other words, individuals who bothered to comply with the behavioral recommendations experienced higher levels of boredom than individuals who did not bother.

Moreover, we found that direct and indirect effects of value and effort on boredom went into opposite directions. Higher value had negative direct effects on boredom (perceiving measures as being valuableā€‰ā†’ā€‰lower boredom) but also positive indirect effects (higher valueā€‰ā†’ā€‰higher complianceā€‰ā†’ā€‰higher boredom). The total effects of value on boredom were positive, suggesting that, overall, higher value led to more boredom by facilitating compliance with behavioral restrictions. The inverse pattern of results emerged for effort: We found a positive direct impact on boredom (perceiving adherence as effortfulā€‰ā†’ā€‰higher boredom) but a negative indirect impact (higher effortā€‰ā†’ā€‰lower complianceā€‰ā†’ā€‰lower boredom). The total effect of effort on boredom was positive, suggesting that, overall, higher effort led to more boredom directly rather than by changing behavior. These results underline that the socially desired behavior of bothering to follow government recommendations during COVIDāˆ’19 comes at the individual cost of increased boredom, which is an aversive experience and strongly linked with negative affect. Crucially, these findings also highlight that increasing perceived value of containment measures might be psychologically demanding if people are void of strategies to cope with the boredom resulting from adherence. In contrast, reducing the effort ascribed to behavioral restrictions not only increases adherence but also leads to less boredom.

Beyond these main findings, at least three other findings warrant further discussion. First, the effects of value and effort on reported behavior differed substantially with respect to their magnitude; second, boredom proneness affected pandemic boredom, attesting to the importance of individual difference variables in understanding behavior during the pandemic; and third, the overall pattern of results was independent of the objective pandemic-imposed restrictions and robust for forecasted and retrospective behavior and experiences alike. We discuss these three points below.

First, when considering the impact of value and effort on recommended behaviors (first part of the proposed mediation model), the results revealed a more potent role of value for behavior (see for example Frƶmer et al., 2021). Individuals are more likely to restrict their behavior if they value this choice. Effort played a smaller but still significant role in the models reported here. It is possible that the effect of effort on recommended behaviors turned out to be small due to structural relationships between value and effort: The value of engaging with behavioral recommendations was on average high and accompanied by a willingness to invest effort. In line with this, theoretical work proposes that ascribing high value to an action might reduce the effort that is felt when engaging in this action (SzƩkely and Michael, 2020).

Second, when it comes to trait-like boredom proneness, the results revealed an impact of this stable personality dimension on the experience of boredom. Boredom proneness significantly predicted pandemic boredom and the effect was even stronger than the effect of actual behavior (avoid traveling and gathering) on pandemic boredom, corroborating existing research that shows a relation between state and trait measures of boredom (Mercer-Lynn et al., 2014). Our results illustrate that boredom prone individuals are especially vulnerable, because they experience higher levels of pandemic boredom (Tam et al., 2021). This is in line with previous research that has found a robust link between high trait boredom and less adherence to COVID-19 containment measures (Bieleke et al., 2021; Boylan et al., 2020; Wolff et al., 2020). This finding was also replicated in a recent high-powered cross-national study of Westgate et al. (2021); however, this longitudinal study also provided evidence that other variables than boredom proneness might be the drivers of adherence. Therefore, the causality of the relationship between boredom proneness and adherence remains an open question that requires other methodological approaches than those previously used in the literature.

Third, the models estimated for the different contexts (thanksgiving, winter holidays, US states without restrictions, US states with restrictions) yielded highly similar results, speaking to the robustness and generalizability of our findings. The only difference pertained to the direct effect of value on the experience of boredom, which turned out to be significant in the US states with restrictions but not in the US states without restrictions. That said, this particular direct effect was small in all models, meaning that the difference could be a statistical artifact (e.g., larger standard errors). Apart from this difference, the multigroup analysis revealed similar structural relationships among the investigated variables in the US states with vs. without COVID-19 restrictions. Despite the rules in force in each state, there is a general agreement of recommended behaviors in the US (beyond the states). This common discourse about recommendations might have homogenized the perceptions and behaviors of individuals in the different states with different rules. We found a small relation between objective and subjective restrictions, suggesting that actual COVID-19 restrictions played a surprisingly small role in determining the restrictions the population feels to be in place. In general, compliance with the recommended behaviors was high. Nevertheless, it seems that independent of the specific laws, it is the value that individuals attribute to the recommended behaviors that predominantly determines their behavior.

Our findings have several important implications beyond behavioral and psychological science in that they provide hints for non-pharmaceutical interventions in the current COVID-19 pandemic. One option for governments could be to highlight the value of recommended behaviors. Previous experimental research has identified the incongruence of current activities and oneā€™s own goals as main cause of feeling bored (e.g., van Tilburg and Igou, 2013). Further, knowing that other individuals and oneself benefit from the recommended behaviors makes it easier to comply with them (Brooks et al., 2020; Roma et al., 2021; Seale et al., 2020). However, in our study we highlight an important trade-off: Increases in value are accompanied by increases in the experienced boredom (indirect and total effects of value on boredom). This finding suggests that highlighting the value of containment measures might not be sufficient, it might also be crucial to focus on consequences for emotional experience in general and on boredom in particular. Another promising route for governmentsā€™ interventions could be to reduce the effort needed to comply with behavioral restrictions. For instance, it has been suggested that simple action planning (e.g., what to do when feeling bored) could help people navigate the pandemic by supporting them in dealing with the difficulties of compliance (Bieleke et al., 2021; ThĆ¼rmer et al., 2021). Our present results suggest that reducing effort has beneficial effects on behavior and simultaneously reduces boredom. As the direct effect of effort on boredom exceeded the indirect effect via behavior, measures that reduce effort should have an unequivocally beneficial effect during the pandemic.

Limitations, future research, and conclusion

Four limitations of the study should be considered when interpreting the findings. First, mediation analyses on cross-sectional data are mostly uninformative about longitudinal causal processes because temporal precedence as well as stability of the effects is not given (e.g., Maxwell and Cole, 2007; Maxwell et al., 2011). Furthermore, our aggregated estimates might only partially reflect individual experiences and behaviors (Fisher et al., 2018; see also Hamaker and Ryan, 2019; Adolf and Fried, 2019). Moreover, the evidence for past and prospective boredom should be interpreted with caution. Empirical work has shown that participants are poor at remembering and predicting their emotional states, particularly because their lay causal theories can influence their answers (Wilson et al., 1989; Wilson and Klaaren, 1992; Klaaren et al., 1994). A final limitation is that we collected data from US MTurk participants, thus results cannot be generalized to other cultures and countries. Socio-cultural variables such as inequalities in access to resources, economic disadvantage, and different rates/responses to COVID-19 across countries are likely to affect the constructs under investigation here (Westgate and Steidle, 2020; Van Bavel et al., 2020).

To address these limitations, future research should experimentally manipulate value and effort in a between-subjects design with random assignment, which is a necessary condition for mediation analyses of causal effects (MacKinnon, 2008). Yet another possibility to assure temporal precedence are longitudinal studies with sufficient timepoints to partial out between-person from within-person effects in the regression of an outcome on a time-varying covariate (Hamaker et al., 2015). Instead of using retrospective and prospective self-report measures future research might use experience sampling methods and, for example, ask participants to briefly describe momentary emotions when a probe interrupts their current task. Future research might also include samples from other cultures and countries to warrant generalizability of results

Despite these limitations, the present findings underline the importance of considering boredom in the context of a pandemic. The results of prior work suggest that boredom prone individuals are less likely to comply with social distancing guidelines (e.g., Wolff et al., 2020). Here, we demonstrate that complying with behavioral recommendations can be a source of boredom that is not only aversive itself but also linked with negative affect. In addition, and in line with theoretical work on boredom and the regulation of goal-directed behavior (Eastwood et al., 2012; Shenhav et al., 2017; Westgate and Wilson, 2018; Wolff and Martarelli, 2020), by showing that perceptions of value and effort are not only robust predictors of behavior but also of the experience of pandemic boredom, our findings provide insights into the mechanisms that underlie pandemic boredom. We hope that the ideas and findings that we present here will inspire future research on how to improve compliance with containment measures as well as understanding the individual pandemic emotional experiences.