Daily emotional well-being during the COVID-19 pandemic.

The COVID-19 outbreak has become one of the largest public health crises of our time. Governments have responded by implementing self-isolation and physical distancing measures that have profoundly impacted daily life throughout the world. In this study, we aimed to investigate how people experience the activities, interactions, and settings of their lives during the pandemic. The sample (N = 604) was assessed in Ireland on the 25 March 2020, following the closure of schools and non-essential businesses. We examined within-person variance in emotional well-being and how people spend their time. We found that while most time was spent in the home (74%), time spent outdoors (8%) was associated with markedly raised positive affect and reduced negative emotions. Exercising, going for walks, gardening, pursuing hobbies, and taking care of children were the activities associated with the greatest affective benefits. Home-schooling children and obtaining information about COVID-19 were ranked lowest of all activities in terms of emotional experience. These findings highlight activities that may play a protective role in relation to well-being during the pandemic, the importance of setting limits for exposure to COVID-19-related media coverage, and the need for greater educational supports to facilitate home-schooling during this challenging period.

The existing subjective well‐being literature offers some insight into potential effects of the dramatic COVID‐19‐induced changes in people’s daily lives on their emotional well‐being. Activities affected by movement restrictions such as spending time in nature (MacKerron & Mourato, 2013, Global Environmental Change, 23, 992), exercising (Reed & Ones, 2006, Psychology of Sport and Exercise, 7, 477), walking (Hanson & Jones, 2015, British Journal of Sports Medicine, 49, 710), and supportive interpersonal interactions (Gonza & Burger, 2017, Journal of Happiness Studies, 18, 1763; Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004, Science, 306, 1776) have been associated with enhanced well‐being. In contrast, time spent alone, engaged in social media use, and caring for children have been associated with reduced emotional well‐being (Allcott, Braghieri, Eichmeyer, & Gentzkow, 2020, American Economic Review, 110, 629; Kahneman et al., 2004, Science, 306, 1776; White & Dolan, 2009, Psychological Science, 20, 1000). While these findings offer suggestive evidence, their applicability to the current situation – daily life during the COVID‐19 pandemic – is unclear. Moreover, previous studies of well‐being during virus outbreaks have chiefly relied on global reports of past ‘usual’ feelings and the dynamics of daily experience have been neglected.

Aspects of everyday life associated with raised positive and reduced negative affect during the COVID‐19 pandemic include the following: Time spent outdoors; Exercising; Going for a walk; Gardening; Taking care of children; and Engaging in in‐person social interactions with friends.

Aspects of everyday life associated with reduced positive and raised negative affect during the COVID‐19 pandemic include the following: Being at work; Home‐schooling children; Obtaining information about COVID‐19; Work‐related social interactions; and Interactions with one’s spouse or significant other.

Background

In the rapidly changing landscape following the emergence of COVID‐19, a constant has been the request from governments across the globe for citizens to practice physical distancing and to isolate themselves at home. Following these guidelines, billions of people have dramatically changed their daily routines and restricted their movements and interactions, potentially with significant welfare effects (Brooks et al., 2020; Lima et al., 2020). Currently, little systematic evidence exists on how people are experiencing daily life during the pandemic. In this study, we therefore asked a sample of the Irish population to reconstruct the activities, interactions, and emotional experiences of the previous day. We conducted the survey on March 25th, one day after the Irish government had told all non‐essential business to close, and when citizens and workplaces had been strongly encouraged to move to home‐working. The government had previously closed all schools and universities on March 12th, and the country subsequently entered a more restrictive lockdown on March 27th. Polling during the same week indicated widespread support for the restrictions that had been put in place (Delaney & Lunn, 2020).

Set against this backdrop, the existing subjective well‐being literature offers some insight into the effects of the dramatic changes in people’s daily lives on their emotional well‐being. Activities affected by movement restrictions such as spending time in nature (MacKerron & Mourato, 2013), exercising (Reed & Ones, 2006), walking (Hanson & Jones, 2015), and supportive interpersonal interactions (Gonza & Burger, 2017; Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004) have been associated with enhanced well‐being.

In contrast, time spent alone, engaged in social media use, and caring for children have been associated with reduced emotional well‐being (Allcott, Braghieri, Eichmeyer, & Gentzkow, 2020; Kahneman et al., 2004; White & Dolan, 2009). While these findings offer suggestive evidence, their applicability to the current situation – daily life during the COVID‐19 pandemic – is unclear.

A small set of studies have shown that self‐isolation and quarantine following previous virus outbreaks (e.g., SARS, H1N1) may produce negative psychological effects (Brooks et al., 2020). In a Chinese sample one month into the COVID‐19 outbreak, the well‐being of those who were highly physically active prior to the outbreak was particularly sensitive to the severity of the outbreak in their local area (Zhang, Wang, Rauch, & Wei, 2020). Such studies of well‐being during virus outbreaks have chiefly relied on global reports of past ‘usual’ feelings, and the dynamics of daily experience have been neglected.

In the current study, we therefore generated a snapshot of the experiences of people living through the COVID‐19 outbreak in Ireland using the Day Reconstruction Method (DRM). The DRM is a diary‐based tool designed to collect data on the experiences a person has on a given day, through a systematic reconstruction conducted on the following day (Kahneman et al., 2004). Drawing on the DRM, we estimated how affective experiences are associated with daily activities, time spent indoors/outdoors, and social interaction during the pandemic with a view to providing evidence to inform academic and policy debates on how the emotional consequences of self‐isolation measures may be mitigated or exacerbated.

Method

Participants

We asked a large Irish market research company to distribute the survey link to their access panel on Wednesday, March 25th. To be eligible for the study, participants needed to be aged 18 or above and live in the Republic of Ireland. Eligible participants received an email from the research company that invited them to complete our survey before 8 pm that day. The company offered a prize draw for one prize of €250 and five prizes of €50 additional to other draws they run for regular survey participants. The panel contained 3,500‐4,000 active members, most of them recruited face‐to‐face to obtain a quota‐controlled basis to be representative of the adult population. Additionally, some participants were invited to join the panel at the end of other surveys or using snowball recruitment. A total of 604 participants completed our survey. The sample consisted of 191 men and 413 women, with a mean age of 47 (SD = 12). The sample was drawn from across Irish regions (Dublin = 31.1%, rest of Leinster = 25.8%, Muster = 23.7%, and Connaught/Ulster = 19.4%). The majority of the sample (54.8%) had an ordinary bachelor degree or national diploma, just under half of the sample (47.02%) were in full‐time employment, and the median household income was €50,000‐€59,999. Full details of the sample demographic characteristics can be found in Table S1.

Measures

Day reconstruction method

We utilized a short version of the DRM (Kahneman et al., 2004) where participants completed a diary documenting what they did and how they felt during a set of up to 5 sequential ‘episodes’ from a randomly allocated section of their day. Participants were prompted to think of episodes as scenes in a movie demarcated by transitions such as going to a different location, or ending one activity and starting another. Participants could describe less than 5 episodes if an earlier episode was the last episode of their day. Participants described 4.63 episodes on average so that we recorded 2795 episodes of March 24th in total.

Positive affect scores were calculated as the average rating of three items, that is, how happy, how calm/relaxed, and how energetic participants reported feeling during each episode (Cronbach’s alpha = 0.84). We selected these items to ensure positive feelings associated with different levels of arousal were assessed (Posner, Russell, & Peterson, 2005). Negative affect was calculated using six items as the average of how sad, bored, frustrated/annoyed, lonely, worried/anxious, and overwhelmed participants were (Cronbach’s alpha = 0.87). Once again, we picked items to ensure negative feelings associated with a range of arousal levels were included (e.g., bored, worried/anxious) and to capture feelings likely to be impacted by the pandemic (e.g., overwhelmed, lonely). The affect items assessed were similar to those included in prior DRM research (Kahneman et al., 2004) and in mood adjective checklists such as the Positive and Negative Affect Schedule (PANAS) (Watson & Clark 1994). Emotions were rated on a numerical scale ranging from 1 = not at all to 7 = very much.

Statistical analysis

We first examined descriptive statistics of affect levels measured while participants were in specific locations or engaged in specific activities. Next, we focused on how affect ratings varied within individuals using individual fixed effect specifications that control for fixed observable and unobservable differences across individuals using the following regression model: where is the affect rating of individual in episode ; is a vector representing all activities undertaken in episode by individual , and the parameters are to be estimated; is the individual fixed effect; and is the robust error term. To ease comparison with other studies, we standardized affect levels to have a mean of zero and standard deviation of one. We applied this basic model to the whole sample and conducted separate fixed effects regressions examining the associations between activities, locations, and social interactions on the one hand and affect levels on the other hand. To manage the risk of finding false associations in our multiple testing approach, we used the Benjamini–Hochberg method, identifying significant associations at a false discovery rate of 0.05 (see Supplementary Materials).

Results

Our examination of how participants allocated their time showed that they spent the majority of their day at home (73.5%) and in the presence of people from their household (51.8%), as anticipated. The most frequently endorsed activities were eating, watching TV/streaming, and working or studying. Participants were alone for 27.0% of the day.

Location

Individual fixed effect regression models of the relationship between the location of the individual and affect levels at the same time showed that being outdoors or in nature is the location with highest positive (b = .59, SE = .05, p < .01) and lowest negative affect (b = −.25, SE = .05, p < .01). Being at work is perceived as less positive and more negative compared to being at home as is typical (Bryson & MacKerron, 2017), as shown in Figure 1. See Table S2 for the accompanying regression coefficients.

Figure 1

Within‐person estimates of the relationship between (a) activities, (b) locations, (c) personal interactions, and (d) remote interactions and affect levels. Each graph presents the results of separate fixed effects regressions. Z‐scores and 95% confidence intervals are presented.

Everyday activities

Exercising (b = .46, SE = .07, p < .01), going for a walk (b = .33, SE = .06, p < .01), gardening (b = .29, SE = .09, p < .01), and pursuing a hobby (b = .23, SE = .09, p < .05) were ranked as the most enjoyable activities (see Table 1) and associated with the largest increase in positive affect in our within‐person analyses (see Figure 1). Taking care of children was also linked to raised positive affect (b = .21, SE = .06, p < .01) and reduced negative feelings (b = −.19, SE = .05, p < .01). In contrast, levels of negative affect were notably higher when participants were using social media (b = .11, SE = .04, p < .05), home‐schooling children (b = .30, SE = .07, p < .01), and informing themselves about COVID‐19 (b = .27, SE = .04, p < .01). Within‐person effects of all daily activities on affect levels are shown in Figure 1 and presented in Table S2.

Table 1

Mean levels of positive and negative affect in each activity and the percentage of episodes where each activity was reported

	Mean positive affect a	Mean negative affect b	% of episodes where reported c
Activities
Exercising	5.53	2.05	5
Going for a walk	5.21	2.54	7
Gardening	5.19	2.15	3
Pursuing a hobby	4.97	2.07	3
Pray/worship/meditate	4.75	2.53	1
Socializing	4.49	2.71	6
Eating	4.39	2.67	22
Taking care of children	4.34	2.92	13
Drinking	4.29	2.82	12
Other	4.26	2.68	9
Preparing food	4.26	2.76	16
Commuting to work	4.25	3.12	3
Resting/relaxing	4.22	2.70	11
Doing housework	4.22	3.06	15
Listening to the radio	4.17	2.92	8
Drinking alcohol	4.13	3.10	2
Schooling children	4.07	3.50	3
Watching TV/ Netflix	4.07	2.92	19
Internet	4.03	3.04	1
Working/studying	3.94	2.86	17
Using social media	3.83	3.10	12
Shopping	3.80	3.03	5
Informing myself about Covid‐19	3.62	3.56	11
Doing nothing	3.26	3.69	2
Location
Outdoors/nature	5.51	2.16	8
At other people’s homes	4.67	2.42	1
At home	4.14	2.79	74
At work	4.1	2.97	9
Somewhere else	4.09	2.87	4
At a shop	3.73	3.01	4

Positive affect is the average of calm and happy affect items.

Negative affect is the average of overwhelmed, sad, bored, frustrated, lonely, and worried affect items.

Participants reported on average 2.2 activities per episode.

Social interaction

Engaging in in‐person social interactions with friends was associated with raised positive affect ratings (b = .34, SE = .10, p < .05). In line with prior research (Bryson & MacKerron, 2017), time spent in work‐related personal or remote interactions was linked to reduced positive and increased negative affect (see Figure 1 and Table S2). Surprisingly, interactions with one’s spouse or significant other were linked to significantly lower positive affect (b = −.17, SE = .05, p < .01).

Additional analyses

Sensitivity tests indicated that the study findings did not differ markedly when fixed effects regressions included activity dummies, location, and interaction dummies simultaneously (see Figure S1) or when random effects regressions were employed (see Figures S2 and S3). We did not find evidence of systematic differences between males and females in the relationship between activities, interactions, locations, and affect levels.

Discussion

We present a rich snapshot of how people are experiencing the activities and settings of their daily lives during the COVID‐19 pandemic on a day when the government had announced strict restrictions such as the closure of all non‐essential businesses. Average positive and negative affect ratings on this day were 4.47 and 2.76, respectively. Our analyses provide the first available estimates of how within‐person variation in emotional well‐being is linked to the ways people are spending their time during the outbreak. The findings also provide important information from a population health perspective by highlighting key issues related to everyday activities and experiences that may require policy consideration and inform the mental health guidelines of governments and international bodies during the crisis.

First, in line with prior research (e.g., Hanson & Jones, 2015; MacKerron & Mourato, 2013; Reed & Ones, 2006), we find that positive affect is greatest when outdoors and that engaging in hobbies and physically active pursuits such as exercising, walking, and gardening are particularly positive activities. The well‐being during outdoor activities is an important public policy consideration and needs to be viewed in light of the trade‐off between population well‐being and compliance with physical distance guidance that form part of virus mitigation efforts. However, it is not possible to infer from the current data that elevated well‐being observed in outdoor pursuits could not be attained by substitute indoor activities. Second, our results suggest that spending time with children following the closure of schools and childcare facilities may benefit rather than reduce parents’ emotional well‐being, as suggested by prior research (White & Dolan 2009; Kahneman et al., 2004). In contrast, taking on the role of educator poses significant challenges, and co‐ordinated mental health and education policies in relation to home‐schooling may help to provide necessary supports to parents at this challenging time. Third, we find that social media use and informing oneself about COVID‐19 are both associated with elevated levels of negative affect. These results suggest that setting personal limits for news and social media consumption, as recommended by recent research (Garfin, Silver, & Holman, 2020) and World Health Organization guidelines (WHO, 2020), may help to safeguard people’s emotional well‐being at this difficult time. Fourth, we observed reduced emotional well‐being levels during interactions with one’s spouse or partner, which is an atypical finding (Kahneman et al., 2004) and may reflect difficulties in adapting to major changes in household routines and responsibilities following the outbreak.

The current study is not without limitations. While our sample included a diverse range of age and socioeconomic groups, it likely differs in observable and unobservable variables from the overall population: all participants had agreed to be part of a survey panel of a market research company, they were contacted via email and hence were Internet savvy, and they were incentivized by various lottery prizes. While the survey company recruited the panel on a quota‐controlled basis to be representative of the adult population, our study sample was predominantly female indicating some selection effects. Hence, it is important to work with larger probability‐based samples to build up a full profile of everyday life during the crisis, and the current study should not be seen as a substitute for such work (Lehdonvirta, Oksanen, Räsänen, & Blank, 2020). However, we examine within‐person effects and did not identify evidence that the effects identified differed systematically between males and females. Some of our results (e.g., related to exercising and home‐schooling) rely on a small percentage (e.g., ≤ 5%) of episodes. While these findings remain significant after controlling the false discovery rate, follow‐up studies are needed to verify these associations. Our results capture a snapshot of one point in time, precluding an understanding of whether and how people’s routines and emotional well‐being are adapting during the crisis. For instance, as people become more accustomed to virtual interactions, well‐being benefits may follow. Multi‐wave data from a range of countries are needed to provide insight into the effects of crisis trajectories and isolation measures on well‐being on a global scale.

In conclusion, distancing people from others to limit infection is a crucial public health measure but may also pose significant mental health risks. We aimed to untangle the relationship between everyday activities, interactions, and emotional well‐being at a time when our sample was facing significant restrictions to their daily activities. Our findings point to everyday activities that may mitigate (e.g., outdoor activities, gardening, exercise, pursuing hobbies) or exacerbate (e.g., social media use, home‐schooling, listening to COVID‐19 news) the welfare effects of isolation. The current study also highlights the value in monitoring people’s daily emotional well‐being during the pandemic to understand how people are faring and to inform actions that may promote well‐being and enhance the sustainability of self‐isolation measures.

Conflicts of interest

All authors declare no conflict of interest.

Author contributions

Leonhard Lades (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Validation; Visualization; Writing – original draft; Writing – review & editing) Kate Laffan (Conceptualization; Investigation; Methodology; Writing – original draft; Writing – review & editing) Michael Daly (Conceptualization; Investigation; Methodology; Writing – original draft; Writing – review & editing) Liam Delaney (Conceptualization; Funding acquisition; Investigation; Methodology; Writing – original draft; Writing – review & editing).

Table S1. Descriptive statistics for the study sample (N = 604).

Table S2. Separate within‐person estimates of the relationship between activities, locations, personal interactions and remote interactions and affect levels.

Figure S1. Mutually adjusted individual fixed effects regressions in which we added activities, locations, in‐person and remote social interactions in the same model.

Figure S2. Random effects specifications without additional controls.

Figure S3. Random effects specifications controlling for age and gender.

Click here for additional data file.