changing social norms due to pandemic essay

4 Ways That the Pandemic Changed How We See Ourselves

A fter more than two years of pandemic life , it seems like we’ve changed as people. But how? In the beginning, many wished for a return to normal, only to realize that this might never be possible—and that could be a good thing. Although we experienced the same global crisis, it has impacted people in extremely different ways and encouraged us to think more deeply about who we are and what we’re looking for.

Isolation tested our sense of identity because it limited our access to in-person social feedback. For decades, scientists have explored how “the self is a social product.” We interpret the world through social observation. In 1902, Charles Cooley invented the concept “the looking glass self.” It explains how we develop our identity based on how we believe other people see us, but also try to influence their perceptions , so they see us in the way we’d like to be seen. If we understand who we are based on social feedback, what happened to our sense of self under isolation?

Here are four ways that the pandemic changed how we see ourselves.

When lockdown started, our identities felt less stable, but we adjusted back over time

In crisis, our self-concept was challenged. A December 2020 study by Guido Alessandri and colleagues, which was published in Identity: An International Journal of Theory and Research , measured how Italians reacted to the first week of the COVID-19 lockdown in March 2020 by evaluating how their self-concept clarity—the extent to which they have a consistent sense of self—affected their negative emotional response to the sudden lockdown.

Self-concept clarity represents “how much you have [clearly defined who you are] in your mind … not in this moment but in general,” explains Alessandri, a psychology professor at the Sapienza University of Rome. While generally people have high self-concept clarity, those with depression or personality disorders usually experience lower levels. “The lockdown threatened people’s self-concept. The very surprising result was that people with higher self-concept clarity [were] more reactive” and experienced a greater increase in negative affect than those with lower self-concept clarity.

In Alessandri’s study, people eventually returned to their initial stages of self-concept clarity, but it took longer than expected due to the shock and distress of the pandemic. This reflects a concept called emotional inertia , where emotional states are “resistant to change” and take some time to return to a baseline level. At the beginning of the pandemic, we questioned what we believed to be true about ourselves, but since then, we’ve adjusted to this new world.

Many people were forced to adopt new social roles, but the discomfort they felt depends on how important that role is to them

Our identities are not fixed; we hold several different social roles within our family, workplace, and friend groups, which naturally change over time. But in isolation, many of our social roles had to involuntarily change , from “parents homeschooling children [to] friends socializing online and employees working from home.”

As we adapted to a new way of life, a study published in September 2021 in PLOS One found that people who experienced involuntary social role disruptions because of COVID-19 reported increased feelings of inauthenticity—which could mean feeling disconnected from their true self because of their current situation. It was challenging for people to suddenly change their routines and feel like themselves in the midst of a crisis.

But the study also uncovered that “this social role interruption affects people’s sense of authenticity only to the extent that the role is important to you,” says co-author Jingshi (Joyce) Liu, a lecturer in marketing at the City campus of the University of London. If being a musician is central to your identity, for example, it’s more likely that you would feel inauthentic playing virtual shows on Zoom, but if your job isn’t a big part of who you are, you may not be as affected.

To feel more comfortable in their new identity, people can start accepting their new sense of self without trying to go back to who they once were

Over the last two years, our mindset and control over the roles we occupy in many facets of life helped determine how virtual learning and remote work affected us. “We are very sensitive to our environment,” Liu says. “[The] disruption of who we are will nonetheless feed into how we feel about our own authenticity.” But we can do our best to accept these changes and even form a new sense of self. “[If] I incorporated virtual teaching as a part of my self-identity, I [may not] need to change my behavior to go back to classroom teaching for me to feel authentic. I simply just adapt or expand the definition of what it means to be a teacher,” she adds. Similarly, if you’re a therapist, you can expand your understanding of what consulting with patients looks like to include video and phone calls.

During the pandemic, many people have made voluntary role changes, like choosing to become parents, move to a new city or country, or accept a new job. Previous research by Ibarra and Barbulescu (2010) shows that although these voluntary role changes may temporarily cause a sense of inauthenticity, they eventually tend to result in a feeling of authenticity because people are taking steps to be true to themselves or start a new chapter. “The authenticity will be restored as people adapt to their new identity,” Liu says.

Our identities have changed, so it’s important to be authentic with how we present ourselves online and offline

We have more power than we may realize to navigate a crisis by accepting that it’s OK to change. But it’s important to act in a way that’s true to ourselves. “People have a perception of the true self … They have some idea of who they truly are,” Liu says. “When you lend that to the [looking glass self], I think people would feel most inauthentic when they are performing to others in a way that is inconsistent with how they are [thinking and feeling internally],” which can happen on social media.

In isolation , when we didn’t have access to the same level of social feedback as normal, social media in some cases became a lifeline and a substitute for our self-presentation. The pandemic inspired people to take space away from the Internet and others to become increasingly dependent on it for their social wellbeing. “[Our unpublished data shows] that time spent on social media increased people’s sense of inauthenticity, perhaps because social media entails a lot of impression management [and] people are heavily editing themselves on these platforms,” Liu says.

With all that we’ve experienced, many of us have fundamentally changed as people. “In the same way which the first lockdown required us to [self-regulate] and adhere to new social norms, these changes that we’re experiencing now require another self-regulation effort to understand what is happening,” Alessandri says. “We don’t expect that people will simply get back to their previous [lives]—I don’t think this is possible. I think we have to negotiate a new kind of reality.”

The more we accept that we are no longer the same people after this crisis, the easier it will be for us to reconcile who we are now and who we want to become.

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How have new social norms emerged as COVID-19 has spread?

In a study of nine countries, researcher cristina bicchieri found that motivating people to modify behavior requires changing their expectations about the actions and thoughts of those who matter to them..

As COVID-19 spread across the world, it became clear that different countries were responding differently to the virus. Penn ’s Cristina Bicchieri , who studies social norms and how they evolve, wanted to understand how a national response had affected individual behaviors. 

“We decided to do a study in nine different countries, which included Mexico, Colombia, China, South Korea, Italy, Spain, Germany, the United Kingdom, and the United States,” says Bicchieri, the Harvie Professor of Social Thought and Comparative Ethics in the School of Arts & Sciences . 

She and Enrique Fatas , a distinguished fellow in Penn’s Master of Behavioral and Decision Sciences program, which Bicchieri runs, created a survey focused on how COVID-related norms like social distancing and mask wearing have emerged. Broadly, they found that such changes come about under three conditions, two of which relate to expectations about the actions and beliefs of relevant others. These “others” aren’t just family, friends, and neighbors but also people who live in the same city or county and generally people whose behavior matters.  

“Public information and the media may change people’s expectations about what others do and what others believe is appropriate to do,” she says. But even new expectations may not alter behavior. “A crucial step in creating a new social norm is that people must want to change precisely because they have these new expectations,” she says. “In other words, their preference for engaging in new types of behavior must be conditional on having certain expectations.” 

To test this in the context of COVID, Bicchieri and her team presented vignettes to subjects from the nine countries, varying the expectations of the story’s main character, then asked participants the likelihood that person would practice social distancing and stay home. 

The researchers found that motivating people to modify their behavior requires changing their expectations. “This is very important,” Bicchieri says. “It’s not enough to say that sending a message about what others do or approve of will induce a behavioral change. We want to be sure that these social expectations actually push people to behave in a different way.” 

But is changing expectations enough? In a public health crisis like the COVID-19 pandemic, Bicchieri says it’s crucial not to underestimate the importance of trust in science.

“When we have major public health issues, if people don’t trust science, it’s useless to convince them that most people are complying with the new rules,” she says. “In fact, if you expect the majority to social distance and stay home but you don’t trust what scientists say, then you’ll will be tempted to free ride since you’ll believe your risk of contagion is low.”

She offers several recommendations the research has shown can make norm-nudging successful. In circumstances like the pandemic, governments shouldn’t downplay science nor should they send conflicting messages. Beyond that, they should shape their messages for the audience they want to reach. 

Bicchieri gives the example of young people minimizing their risk of getting COVID-19. “A common message, both in Italy and the U.S. was, ‘Older people and people with pre-existing conditions are the most vulnerable.’ A lot of young people thought, ‘I’m not old, I don’t have a pre-existing disease, therefore it’s safe for me,’” she says. “You have to consider tailoring different messages and changing how you send these messages to different groups.”  

That speaks to Bicchieri’s final point. In communication, showing what people actually do far outperforms telling what they approve of. Describe a person who has accepted the lockdown and follows social distancing rules, for example, and most people will infer such a person approves of these behaviors. That same inference doesn’t happen when someone is simply described as supporting the measures. “Words and deeds are different,” Bicchieri says. “We may approve of something and yet still be tempted not to do it. But if we do something, we tend to approve of it.” 

Future work in this realm will consider whether gender, income, or level of instruction matter in eliciting behavior change. “We live in a world so globalized that pandemics will happen more than once,” she says. “We have to be prepared to try to change people’s behaviors. There is a lot of work to be done.” 

Cristina Bicchieri is the S. J. Patterson Harvie Professor of Social Thought and Comparative Ethics in the  School of Arts & Sciences at the University of Pennsylvania . She is also a professor of legal studies at the Wharton School . She is the director of the Center for Social Norms and Behavioral Dynamics and founding director of the Master of Behavioral and Decision Sciences program.

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• Published: 22 July 2022

Perception of strong social norms during the COVID-19 pandemic is linked to positive psychological outcomes

• Shuang Liu 1 ,
• Jiajia Zhu 1 , 2 ,
• Yutong Liu 1 , 2 ,
• Danica Wilbanks 3 ,
• Joshua Conrad Jackson 4 &
• Yan Mu 1 , 2  

BMC Public Health volume  22 , Article number:  1403 ( 2022 ) Cite this article

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Social norms can coordinate individuals and groups during collective threats. Pandemic-related social norms (e.g., wearing masks, social distancing) emerged to curb the spread of COVID-19. However, little is known about the psychological consequences of the emerging norms. We conducted three experiments cross-culturally, during the early period of the COVID-19 pandemic in China (Study 1), the recovery period in China (Study 2), and the severe period in the United States and Canada (Study 3). Across the three studies, we first distinguished the opposite effects of social norms and risk perception on individuals’ psychological characteristics during the COVID-19 pandemic and further revealed that individuals who perceived stronger pandemic norms reported a lower level of COVID-19 risk perception, which in turn would be associated with fewer negative emotions, lower pressure, more positive emotions, higher levels of trusts, and more confidence in fighting against COVID-19. Our findings show that perceived tighter social norms are linked to beneficial psychological outcomes. This research helps governments, institutions, and individuals understand the mechanism and benefits of social norms during the pandemic, thereby facilitating policy formulation and better responses to social crises.

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Introduction

COVID-19 has dramatically impacted people worldwide, with over 500 million reported cases and more than 6,277,241 deaths as of May 17, 2022 ( https://coronavirus.jhu.edu/ ). Moreover, the COVID-19 pandemic puts immense psychological burdens on individuals and society [ 1 ]. For example, an online survey with 1210 Chinese people during the initial stage of the COVID-19 pandemic showed that 54% of respondents rated the psychological impact of the COVID-19 pandemic as moderate or severe and that 29% reported moderate to severe anxiety symptoms [ 2 ]. Evidence from 5065 American adults suggests that as the pandemic continued, each additional day was significantly associated with an 11% increase in the odds of moving up a category of distress among the high-count states (i.e., New York with 50 or more COVID-19 cases as of March 10, 2020) [ 3 ]. People’s psychological well-being was in a vulnerable state during the pandemic, with higher risk sensitivity, more negative emotions, and more frequent interpersonal problems [ 3 , 4 , 5 , 6 , 7 ]. Worldwide research demonstrated that people who felt greater pandemic risk had poorer mental health during the pandemic, with a higher rate of depression, more perceived stress and anxiety, and a higher frequency of preventive behaviors such as washing hands [ 8 , 9 , 10 , 11 , 12 , 13 ]. However, little attention has been paid to whether changing contextual factors (i.e., social norms) may have influenced people’s psychological wellbeing and social attitudes during the global pandemic.

Tightness-Looseness (TL) theory defines social norms as socially agreed-upon standards of behaviors which vary in their strength and enforcement across cultures [ 14 ]. Tighter societies with stronger social norms (e.g., China, Japan, South Korea, Germany), have higher levels of social order, government control, solidarity, and coordination; societies with looser cultures (e.g., the United States, Canada, Greece, Netherlands), have more freedom and openness [ 15 , 16 , 17 ]. Tight cultures tend to have higher historical rates of ecological threats, and some evidence suggests that tightness can help groups coordinate to survive under high threat [ 17 , 18 ]. Previous evolutionary game theory (EGT) modeling work has simulated the evolutionary process of norm adherence and enforcement behavior under different levels of threat and found that stronger norms are more evolutionarily adaptive when facing high collective threat [ 1 , 18 ].

To fight against COVID-19, most nations have promoted new social norms (e.g., wearing masks when going out, washing hands frequently, and keeping social distance). These emerging social norms have proven to help decrease viral transmission speed during the COVID-19 pandemic and reduce risk of infection [ 19 , 20 , 21 , 22 ]. For instance, Gelfand et al. conducted a global analysis of the effect of culture TL (measured before the pandemic ) on COVID-19 cases and deaths [ 23 ]. They found that nations with low levels of TL were estimated to have 4.99 times the number of cases and 8.71 times the number of deaths — even after controlling for important covariates like the national economy, population, median age, and government efficiency. Therefore, we propose that social norms during the pandemic have a positive influence on reducing COVID-19 risk thereby improving psychological outcomes.

In sum, previous research has shown that (a) the COVID-19 pandemic has had a range of negative mental health implications, and (b) strong social norms before the pandemic have been instrumental for slowing the spread of COVID-19 cases. However, there is no direct evidence showing whether and how the strength of social norms during the pandemic affects people’s psychological well-being and attitudes. The current study intends to bridge the gap between these two streams of evidence by investigating whether individual-level perceived strength of social norms can ameliorate some of the adverse psychological consequences of the pandemic.

Considering COVID-19 has become a sustained global crisis, pandemic social norms will likely persist for some time. Therefore, the current study set out to uncover the direct and indirect effects of adherence to these social norms on psychological outcomes during the COVID-19 pandemic. We conducted three studies in different cultural groups during the early period of the COVID-19 pandemic in China (Study 1), the recovery period of COVID-19 in China (Study 2), and the severe period of COVID-19 in the United States and Canada (Study 3).

The goal of Study 1 was to test the association between the perceived strength of social norms during the pandemic and psychological outcomes, and the mediating role of risk perception. We collected data using a large-scale survey from January 30th to February 3rd, 2020 — a period when the COVID-19 pandemic in China was severe and the WHO declared a global alert for COVID-19 [ 24 ]. All Chinese provinces entered the highest level of public health response (Level 1 of 4 levels in the Chinese Emergency System) [ 25 ]. During this time, new social norms related to pandemic prevention emerged in the public like staying at home, washing hands, wearing masks when going out, and alcohol sterilization. We first tested the hypothesis about the adverse effect of COVID-19 risk on both people’s psychological well-being and social attitudes. Then, we set out to examine the link between pandemic norms and psychological consequences (i.e., psychological well-being and social attitudes). As aforementioned, historically tight cultures have experienced higher levels of ecological and social threats, and people in tight cultures have greater obedience to social norms. Therefore, we hypothesize that (1a) the perceived strength of social norms during the pandemic would be positively related to people’s psychological well-being, that is, perceived strength of social norms would be associated with more positive emotions, fewer negative emotions, and lower pressure; (1b) the perceived strength of social norms during the pandemic would predict people’s social attitudes, that is, people who perceived stronger social norms would also show higher trust in organizations and other people. Additionally, considering the function of social norms in facilitating coordination under threats, we hypothesized that the perceived strength of social norms would be associated with lower perception of risk which in turn would be associated with better mental health and more trust in institutions.

To further validate our findings, in Study 2, we collected two waves of data during the recovery period of the COVID-19 pandemic in China, from May 2nd to May 7th, 2020, and from July 6th to July 15th, 2020. We expected to replicate Study 1's findings in this follow-up survey.

Since China is a tighter culture (with a standardized tightness score of .19 according to [ 26 ]), we were also curious about whether findings from data collected in China would still hold in loose cultures. In Study 3, therefore, we set out to replicate our findings in two culturally loose countries — the United States of America and Canada, which have standardized tightness scores of −.13 (US) and − .14 (Canada) [ 26 ].

Participants

In Study 1, we distributed a set of questionnaires through an online platform similar to Qualtrics from January 30th to February 3rd, 2020. For large-scale sampling, we pre-calculated the sample size by the widely accepted Monte Carlo method invented by Schoemann and her colleagues [ 27 ] (see Supplementary Methods for Sample Size and Power Analysis). We set an automatic filter to remove invalid data and careless responses through multiple probe items according to recommended reprocessing methods [ 28 ]. Thus, we obtained valid data from 1179 participants who correctly answered the probe questions. Data from 18 participants not living in mainland China within the past 6 months were excluded. We set mandatory options on all key variables, so we did not further exclude data based on missing values. The final sample was 1161 (350 males, 661 females, and 150 not providing; mean age 34.3 ± 10.62), covering 31 provinces, Municipalities, and Autonomous Regions of mainland China (except Hong Kong, Macao, and Taiwan). All participants gave their informed consent and volunteered to participate in the survey without compensation.

In Study 2, according to Monte Carlo methods for mediation analyses [ 27 ], we obtained the minimum required sample size of 100 to reach a power level of .90 ( Supplementary Methods ). We obtained 348 total respondents (1st round: 233; 2nd round: 115). We excluded data with wrong answers in the probe question ( N  = 28) and invalid data (only filled out the informed consent part of the questionnaire) ( N  = 5). We also excluded data with a short completion time (1.5 SD below the mean, 2493.94–1.5*1337.76 seconds) ( N  = 8). Since we didn’t find significant differences in demographic information, TL, perceived norms during the pandemic, and related mentalities between the two waves of the data (Table S1), we collapsed the two waves of data. The final sample in Study 2 was 307 (117 males and 190 females, mean age 24.65 ± 7.13 years) from 11 Chinese provinces. All participants gave their informed consent before the survey and received compensation for participation.

In Study 3, we recruited participants from the United States and Canada through an online participant recruitment platform ( https://www.prolific.co/ ) respectively on May 3rd and May 20th, 2020 — a severe period of COVID-19. We followed the same minimum required sample size requirement calculated in Study 2 to recruit enough participants ( Supplementary Methods ). A total of 156 American participants completed the survey, 7 of which failed to pass the probe question. 149 Canadian participants answered the questionnaire, 10 of which failed to pass the probe question. Taken together, the final sample was 149 (89 males and 60 females, mean age 35.50 ± 12.99 years) and 139 (77 males and 62 females, mean age 30.90 ± 10.20 years) for the American and Canadian samples respectively.

For the three studies, we adopted the strategy that if the omitted missing values were related to demographic information (i.e., age, gender), we kept and reported them in the results. But if they were from the core variables, we excluded them in the following analyses instead of interpolating them. The present research was approved by the ethics committees of the Institute of Psychology, Chinese Academy of Sciences.

Our measures were kept consistent across the three sub-studies. These included the perceived strength of social norms, risk perception, and two aspects of psychological outcomes (psychological well-being and social attitudes). For most of the variables, we used multiple established measures to increase the validity of our research. We included emotions, psychological pressure, and self-confidence respectively as indicators of psychological well-being, and measured organizational trust, interpersonal trust, and confidence in groups and organizations during the pandemic as indicators for social attitudes. We described more details about our measures below.

Perceived social norms

We measured the participants’ perceptions of social norms before and during the pandemic on a 7-point scale (1 = Strongly disagree, 7 = Strongly agree). For perceived strength of social norms in each of the two separate conditions, we used two items that were adapted from the Generalized Cultural Tightness-Looseness (TL) Scale [ 15 ], i.e., “during the pandemic/generally speaking, my habitual residence has a set of clear norms to restrict and guide people’s behavior and performance”, “during the pandemic/generally speaking, if people violate the regulations related to the pandemic in my habitual residence, others will be strongly against”. A higher score on the scale indicates that people perceived stricter social norms during the pandemic, or in general, respectively. The Cronbach’s α coefficients were .63 (during the pandemic) and .68 (in general).

Pandemic risk perception

We used one item for assessing people’s risk perceptions — the possibility of being infected by COVID-19 on a 6-point scale (1 = Very likely, 6 = Very unlikely), e.g. “How likely do you think you are infected with COVID-19?”. We reversed the score. The higher score indicates more perceived risk during the COVID-19 pandemic.

Psychological well-being and social attitudes

Adapting from the 60-item version of The Positive and Negative Affect Schedule (PANAS) [ 29 ], we asked participants to report their current emotions, including two positive emotions (i.e., happy, hopeful) and seven negative emotions (i.e., upset, anxious, scared, worried, tired, confused and angry). They were scored on a 4-point scale from 0 = None to 3 = Very strong. In later analyses, we calculated the mean score of the positive emotions and the mean of the negative emotions as the indicators for emotions. The Cronbach’s α coefficients were .48 and .86 respectively.

Participants were asked to rate their pressure (“What is your psychological pressure currently”) from 0 (None) to 100 (very much). Higher scores correspond to higher pressure felt during the pandemic.

Organizational trust

We measured people’s trust in organizations using a scale which we adapted from the Organizational Trust Scale [ 30 ]. The scale included two dimensions: trust in authoritative institutions or groups and trust in non-authoritative institutions or groups. We included five items for trust in authorities, such as trust in the central and local government, trust in neighborhood offices, grassroots organizations, and neighborhood committees, trust in the World Health Organization, and trust in TV broadcasts and newspapers; and four items for trust in non-authorities, including trust in internet celebrities, trust in online social networks (e.g., WeChat moments and Tencent QQ groups), trust in relatives, friends, and neighbors, and trust in foreign media. Participants were required to rate their trust for those institutions and groups during the pandemic from 1 (Completely not trust) to 7 (Completely trust). We used the mean score of the two subscales (authoritative trust and non-authoritative trust) and the mean score of all items (organizational trust) together. Higher mean scores indicate a higher level of trust. The Cronbach’s α of the subscale of authoritative trust was .81; the Cronbach’s α of the subscale of non-authoritative trust was .66.

Demographic variables

Besides general demographic information like gender, age, education level, and profession, we collected participants’ geographical information, including their permanent residence, and temporary location when completing questionnaires.

To be consistent with Study 1, we included four kinds of measures: (1) individual-level perceived tightness of social norms: social norms during and before the pandemic; (2) pandemic risk perception; (3) pandemic related attitudes and feelings: personal feelings and attitudes toward themselves (incl., positive and negative emotions, pressure) and other people or organizations (incl., COVID-19 stigma, organizational trust, and interpersonal trust). We included additional measures of confidence in COVID-19 pandemic control of themselves, other people, and institutions; (4) participant demographic information.

Similarly, as in Study 1, we measured the perception of social norms before and during the pandemic on 7-point scales (1 = strongly disagree, 7 = strongly agree). For the perceived social norms during the pandemic, the scale was modified from [ 15 ] that of Study 1 and was extended into four items. The Cronbach’s α coefficient was .61. For the perceived social norms before the pandemic, we used the 15-item Daily TL Scale. It was adapted from the Latitude vs. Constraint in Daily Life Scale [ 31 ], assessing the frequency with which individuals are chronically exposed to a wide range of deviant behaviors, and a lack of conformity in their daily lives, e.g., “Is there a lot of littering in the street?”, “Do people wear informal clothing in public?”. Participants were asked to rate the frequency of each statement based on their daily experience from 1 (not at all) to 7 (very frequently). It was equivalent to the Generalized TL Scale but focused on the tightness-looseness of everyday life in public settings. The correlation between Daily TL and Generalized TL was significantly positive ( r (305) = .52, p  < .001). The higher the score, the more often people perceived constraints in their daily life. The Cronbach’s α coefficient for the scale was .81.

To measure risk perception, apart from one single item same as that of Study 1 (assessing the possibility of being infected by COVID-19 by 5-point scale), we developed a Risk Perception Scale in this study. We reasoned  that the degree of risk that COVID-19 caused was closely related to the ability of local authorities to limit and control the pandemic. Therefore, compared with the direct measurement used in Study 1 (assessing the possibility of being infected by COVID-19 by 5-point scale), we used a variety of questions to ask participants about their perceptions of how effectively local institutions could control and prevent COVID-19. Items included ratings about local medical resource management, the general situation of controlling COVID-19, societal recovery, supply of necessities, the order of societal operation, the surveillance of suspected patients, etc. Each item was reversely coded. The scale was inspired by a scale assessing trust in the healthcare system [ 32 ] and a scale measuring the perception of collective community action [ 33 ]. Items included, “During the epidemic, the province and city that I live in had sufficient medical supplies”, “During the epidemic, the supply of daily necessities in my province and city was sufficient”, “I think the province and city that I live in is methodically marching towards the end of the outbreak”. Participants were asked to rate the extent to which they agreed with the descriptions from 1 (Strongly disagree) to 7 (Strongly agree). The Cronbach’s α coefficient of a total of 9 items was .90. The higher the mean score, the higher the perceived risk.

We measured positive and negative emotions from the 20-item version of The Positive and Negative Affect Schedule (PANAS) [ 34 ]. We included seven positive emotions (i.e., interested, proud, alert, inspired, determined, attentive, active), and eight negative emotions (i.e., upset, jittery, guilty, scared, hostile, irritable, nervous, afraid). Participants were asked to report the frequency of their different emotions recently using a 7-point scale from 1 (not at all) to 7 (very frequently). The Cronbach’s α coefficients were .83 and .92 respectively.

Same as Study 1.

Self-confidence during the pandemic

We measured participants’ confidence about themselves during the pandemic with a 7-point scale from 1 (not at all) to 7 (very much). The higher score indicated higher confidence in taking effective measures to prevent COVID-19.

We included 5 items respectively to measure participants’ trust in authoritative organizations (authoritative trust) and non-authoritative trust (non-authoritative trust). Authoritative trust included items like trust in central government, central media, local government, researchers engaged in virus research, and healthcare workers; non-authoritative included questions about trust in local media, online social media, neighborhood offices/grassroots organizations, neighborhood committees, charity foundations, and the Red Cross. The mean scores were calculated separately for trust in authority and non-authority. The Cronbach’s α coefficients were .87 and .83 for authority and non-authority respectively.

Interpersonal trust

We assessed the participants' trust in others with four items from the Interpersonal Trust Scale [ 35 ] (e.g., “Others may take advantage of me if I do not maintain vigilance.”), and three items from the Generalized Trust Scale [ 36 ] (e.g., “Most people were honest,” “Most people were trustworthy,”). Participants were asked to rate their attitudes from 1 (Strongly disagree) to 7 (Strongly agree). After reverse coding the two items from Rotter’s (1968), a higher score indicates a higher level of trust toward other people. The Cronbach’s α coefficient was .74.

COVID-19 prevention confidence

We asked participants about their confidence in their families, places where they worked, where they lived, local and central government, medical workers, China, and other countries on a 7-point scale from 1 (not at all) to 7 (very much). We calculated the mean score of all items as the indicator of people’s confidence in COVID-19 prevention. A higher score indicates a higher level of confidence. The Cronbach’s α coefficient was .83.

Demographic and other variables

We collected participants’ general demographic information, including gender, age, education levels, and socioeconomic status (SES) (using the ladder scale [ 37 ]). Additionally, we assessed participants’ perceptions of restriction during the pandemic in the last week and from January to March (corresponding to Study 1 sampling time) to demonstrate the difference in time between Studies 1 and 2. Items included, “During the epidemic period (mainly from January to March), how do you think your daily life is restricted?” “In the last week, how much do you think your daily life is restricted?”. People’s sense of restriction in the last week was significantly lower than that from January to March (covered our sampling time in Study 1) (M difference  = − 1.87, SD difference  = 1.85, t (306) = − 17.66, p  < .001), but there was no significant difference between sense of restriction in the last week and sense of restriction before the pandemic (M difference  = −.01, SD difference  = 2.15, t (306) = −.11, p  = .92). Therefore, we considered that Study 2, which took place during the recovery period of the pandemic, took place during a different cultural climate than Study 1 (during the outbreak period).

We adopted the same measures as Study 2. The scale of perceived social norms during the pandemic was 6-point (1 = Not agree at all, 6 = Totally agree). We transformed the scale into 7 points. The Cronbach’s α coefficients were .54 in the American sample and .45 in the Canadian sample. For the normal-time social norm perception (i.e., TL), we used the same Latitude vs. Constraint in Daily Life Scale as Study 2 [ 31 ]. The Cronbach’s α coefficients were .41 in the American sample and .57 in the Canadian sample. The higher the score, the more constraints people perceived in their daily life.

We used the same Risk Perception Scale in this study. All 9 items were translated and then back-translated by two proficient English users. The Cronbach’s α coefficients were .82 and .81 in the American and Canadian samples respectively.

As in Study 2, we used items from the 20-item version of The Positive and Negative Affect Schedule (PANAS) [ 34 ] to measure participants’ positive and negative emotions in the last week. The 5-point scale consisted of four positive emotions (i.e., proud, alert, inspired, active) and six negative emotions (i.e., upset, hostile, irritable, ashamed, nervous, and afraid). We used the mean scores of positive emotions and negative emotions as indicators for emotions. The Cronbach’s α coefficients were .81 and .84 for positive and negative emotion in American and .75 and .82 in Canadian.

Self-prevention confidence

Same as Study 2.

Same as Study 2. The authoritative trust Cronbach’s α coefficients were .75 and .68 in the American and Canadian samples respectively; the non-authoritative trust Cronbach’s α coefficients were .88 and .75 respectively.

We used the same structure as Study 2 but deleted one item (“You should better be careful when interacting with strangers unless they provide evidence that proves their trustworthiness.”) due to consideration for internal reliability of the two samples. The Cronbach’s α coefficients in the American and Canadian samples were .85 and .82 respectively.

Same as Study 2. The Cronbach’s α coefficients in the American and Canadian samples were .81 and .84 respectively.

Demographics and other covariates

Besides age, gender, job, and SES, we also asked participants to report their political affiliation (“In general, what is your political affiliation?”) and the population mobility in their community and province/city by 7-point scale respectively, such as “What is the proportion of the recurrent population (e.g., temporary residents, passengers, and in-transit population) in your community?”,” What is the proportion of the recurrent population (e.g. temporary residents, passengers, and in-transit population) in your community?”

We provided the content validity index of the scales that we made in the Supplementary Materials (Table S 2 ).

Statistical analysis

First, we tested whether individual perceived risk was associated with people’s psychological well-being and social attitudes by Pearson r correlation. Correlation analyses were also used to test for the association between perceived pandemic norm strength and psychological outcomes. Finally, if the above pairwise correlations between pandemic norms and risk, and between risk and psychological variables, were supported, we performed mediation analyses to examine whether perceived pandemic norm strength was linked with psychological outcomes through perceived pandemic risk. The mediation analysis used SPSS PROCESS macro version 3.5, Model 4 [ 38 ]. We used the 95% confidence interval (CI) of the indirect effect as the criterion to identify the mediating effect. We set the number of bootstrapped samples as 5000 to ensure stable estimates each time. We additionally ran the power analysis on all mediational models and provided the information in the Supplementary Methods .

First, we tested whether individual perceived risk was associated with psychological well-being and social attitudes by Pearson r correlation. As Table  1 illustrates, higher levels of risk perception correlated with less positive emotions ( r (1148) = −.14, p  < .001) like happy and hopeful; more psychological pressure ( r (1108) = .25, p  < .001) and more negative emotions (e.g., anxious, r (1151) = .34, p  < .001). For trust in groups and organizations, higher levels of risk correlated with lower trust in authoritative organizations ( r (1146) = −.19, p  < .001) but not with trust in non-authoritative organizations ( r (1152) = −.02, p  = .483). Taken together, if people perceived greater pandemic risk, they tended to report worse well-being and less trust in authoritative groups and organizations.

Next, correlation analyses were used to test the association between perceived pandemic norm strength and psychological outcomes. As Table 1 showed, we found that people who perceived stronger norms during the pandemic felt less pandemic risk ( r (1156) = −.13, p  < .001). Stronger pandemic norms were correlated with less negative emotion ( r (1151) = −.12, p  < .001) and lower levels of psychological pressure ( r (1108) = −.11, p  < .001), but there was no relationship with average positive emotions ( r (1148) = .04, p  = .221) or specific positive emotions like happy ( r (1150) = .01, p  = .847) or hopeful ( r (1150) = .05, p  = .098). For attitudes toward other people and organizations, stronger pandemic norms corresponded with higher levels of trust in authoritative groups and organizations ( r (1146) = .18, p  < .001) but not with non-authoritative organizations ( r (1152) = −.02, p  = .483). We also found associations between pandemic norm strength and cultural TL (Table S3), even when controlling for covariates (incl., daily cumulative number of COVID-19 cases, provincial population, and environmental risk) (Table S4). As previous research found that there are general psychological differences between people living in tighter vs. looser cultures [ 39 ], we performed partial correlations between pandemic norm strength and a set of outcome variable controlling for cultural TL and found most of the results remained (Table S5).

To test whether perceived strength of social norms during the pandemic was associated with risk perception and individual-level psychological well-being and social attitudes, we conducted mediation analyses (Fig.  1a ). The results showed that, through reduced risk perception, perceived stronger pandemic norm strength was associated with higher positive emotion (B = .02, 95% CI = [.0081, .0319]), lower negative emotion (B = −.04, 95% CI = [−.0667, −.0220]), and less pressure (B = −.03, 95% CI = [−.0522, −.0167]). Through reducing risk perception, perceived pandemic norm strength was also associated with greater trust in authoritative groups or organizations (e.g., government, WHO) (B = .02, 95% CI = [.0103, .0366]) but not in non-authoritative organizations (B = .01, 95% CI = [−.0042, .0136]). Finally, our power analyses for the mediation models reached over .90.

Mediation Models Predicting Psychological Outcomes. Note. The figure shows the mediation role of risk perception in the relationship between perceived social norms and psychological well-being and social attitudes for Study 1 ( a ) (Chinese sample at the severe period of the COVID-19), Study 2 ( b ) (Chinese sample at the recovery period) and Study 3 ( c ) (American sample at the severe period) and ( d ) (Canadian sample at the severe period) respectively. All variables were standardized before the mediation analyses. Pandemic Norm = individual perceived social norm during the pandemic; Risk = the possibility of being infected with COVID-19; Positive/Negative Emotions = positive/negative emotions; Pressure = psychological pressure during the pandemic; Self-Confidence = confidence in self during the pandemic; Interpersonal Trust = generalized interpersonal trust; Organization Trust a  = trust in authoritative groups and organizations; Organization Trust b  = trust in non-authoritative groups and organizations; Confidence = confidence in other people, places, governments and other institutions. Standardized regression coefficients (β) are presented above the arrows. Bold lines represent significant paths. The 95%CI values presented above the bottom line indicate the indirect effect of risk perception exist within the influence of pandemic norms on psychological outcomes. Statistical significance: * p  < 0.05; ** p  < 0.01; *** p  < 0.001

We first replicated key associations involving risk perception. In Study 2, the updated indicator of risk perception was correlated with the single item of perceived susceptibility that was used in Study 1 ( r (296) = .27, p  < .001), and the result of the new risk indicator was consistent with the result linked with the previous indicator (Table S6). In particular, people who perceived more risk during the pandemic showed less frequent positive emotions ( r (296) = −.20, p  = .001), more frequent negative emotions ( r (296) = .19, p  = .001), more pressure ( r (296) = .10, p  = .09), and lower levels of self-confidence ( r (296) = −.37, p  < .001), interpersonal trust ( r (296) = −.27, p  < .001), organizational trust (authoritative: r (296) = −.56, p  < .001); non-authoritative: ( r (296) = −.34, p  < .001), and confidence during the pandemic r (296) = −.55, p  < .001).

It was unclear whether stronger pandemic norms during the recovery period still brought about better psychological outcomes. The results of Study 2 validated our findings in Study 1 (Table S6). Perceived strength of pandemic norms was negatively correlated with perceived pandemic risk ( r (296) = −.35, p  < .001). For psychological well-being, stronger pandemic norms during the pandemic were associated with more positive emotions ( r (305) = .14, p  = .018), more self-confidence ( r (296) = .19, p  = .001) and less negative emotions ( r (305) = −.12, p  = .036), but not correlated with pressure ( r (305) = −.01, p  = .805). For social attitudes, stronger pandemic norms were associated with higher levels of interpersonal trust ( r (305) = .16, p  = .005), organizational trust (authoritative: r (296) = .29, p  < .001; non-authoritative: r (296) = .18, p  = .001), and confidence ( r (305) = .29, p  < .001). Perceived strength of social norms before the pandemic (e.g., cultural TL) was also associated with positive psychological outcomes (Table S6).

As Fig. 1b illustrated, mediation results of Study 2 showed that, through lower perceived risk, the perceived strength of pandemic norms was associated with greater positive emotions and self-confidence in COVID-19 prevention and lower negative emotions; perception of stronger social norms was also positively associated with interpersonal trust, organizational trust, and confidence in other people, places, governments, and organizations. Our power analyses for the mediation models reached over .80 ( Supplementary Methods ). This result was also consistent with the result measured with the original single item assessing risk perception (Fig. S1).

In Study 3, data from the United States and Canada were not significantly different across all measures but perceptions of pandemic norm strength (Table S7). We thus analyzed these countries  separately and also reported merged results in the main text. Consistent with Studies 1 and 2, the results of Study 3 showed that people who perceived higher risk during the pandemic showed less frequent positive emotions, more frequent negative emotions, lower self-confidence, and lower levels of interpersonal trust, organizational trust, and confidence in other people and organizations. In general, risk perception was associated with worse well-being and less positive attitudes in American (Table S8) and Canadian (Table S9).

In Study 3, within loose cultures, we also found that stronger perceived pandemic norms were correlated with lower perceived risk both in American and Canadian samples (All: r (145) = −.47, p  < .001; US: r (145) = −.41, p  < .001; Canada: r (137) = −.50, p  < .001). Similarly, the relationship between pandemic norms and psychological well-being and social attitudes replicated the results shown in Chinese samples. Across the two loose culture samples, the perception of stronger pandemic norms was associated with more positive emotions ( r (285) = .12, p  = .036), less negative emotions ( r (286) = −.14, p  = .018) and higher level of self-confidence ( r (286) = .32, p  < .001). As for social attitudes, stronger perceived pandemic norms were correlated with higher levels of interpersonal trust ( r (286) = .26, p  = <.001), trust in both authoritative organizations ( r (285) = .40, p  < .001) and non-authoritative groups and organizations ( r (286) = .30, p  < .001), and confidence in other people and organizations during the pandemic ( r (286) = .55, p  < .001). The separate results for American and Canadian samples are provided in Tables S8–S9. When cultural TL was controlled by partial correlation, the above results were all supported (Table S10).

As Fig. 1c and d showed, the results of the loose cultures replicated the findings in the Chinese sample. Through reducing perceived pandemic risk, stronger perceived pandemic-related social norms was associated with higher  positive emotions and self-confidence in COVID-19 prevention, lower negative emotions, higher levels of interpersonal and organizational trusts, and more confidence in other people, places, governments, and other institutions.

Discussions

COVID-19 changed social norms around the world [ 40 ]. However, insufficient attention has been paid to the relationship between the emerging pandemic norms and people’s psychological well-being and attitudes during the COVID-19 pandemic. The current study fills this gap by showing that the strength of pandemic norms, as relative but distinct from TL (which describes the generalized strength of social norms across domains of life), is positively associated with individual psychological well-being and attitudes toward other people and organizations during the pandemic (Study 1, 2, & 3). People who perceive stronger pandemic norms report better psychological well-being, e.g., more frequent positive emotions and less frequent negative emotions (all studies), less psychological pressure (Study 1 & Study 2) and more self-confidence (Study 2 & Study 3); and report more positive social attitudes, e.g., more trust in both authoritative and non-authoritative organizations (all studies), more generalized interpersonal trust (Study 2 & Study 3), and higher levels of confidence in other peoples and organizations (Study 2 & Study 3). Further, pandemic norm strength is negatively related to individual-level risk perception about COVID-19 in both tight (China) (Study 1 & 2) and loose cultures (America and Canada) (Study 3). Additionally, stronger perceived social norms during the pandemic are linked with psychological well-being and attitudes through a lower level of perceived pandemic risk in both culturally tight and loose countries.

Previous literature has suggested that tight cultures are more prepared to deal with ecological and societal threats because tighter social norms improve social coordination at the group level [ 15 , 18 ]. Now, there is growing evidence that stronger social norms also have a positive psychological effect at the individual level. For example, a research on 1827 Chinese adolescents found that increased risk perception of COVID-19 was associated with more emotional disorders, i.e., anxiety and depression, but that this link was weaker among people who perceived more cultural tightness [ 41 ]. They further found that tight culture alleviated the psychological disorders by enhancing perceived protection efficacy. Consistent with their findings, across three studies, we found that increased risk perception and tighter perceived norms were each associated with psychological outcomes and prosocial attitudes. Whereas this previously published study failed to find the link between cultural TL and risk perception among Chinese adolescents, we found medium-to-strong negative associations between pandemic norms and risk perception across the three studies (β = − 0.13 in Study 1; − 0.36 in Study 2; − 0.41 and − 0.50 in Study 3). One possible explanation for this difference in findings is that the pandemic norm measure in the current study is more relevant to the COVID-19 situation and linked with behaviors geared toward protecting individuals from infection [ 42 ].

Tighter norms are theorized to have evolutionary benefits in promoting society security and stability in ancient times [ 17 ]. Consistently, our study and previous research [ 23 ] both show that stronger social norms were linked to positive outcomes at the group and individual level during the COVID-19 pandemic. The current study reveals the paramount importance of studying the strength of social norms, and how this strength changes over time. For example, routinely practicing emergency drills for pandemic prevention and related security drills can help control the spread of pandemics and prevent social turmoil.

Our research also distinguished between the perceived risk of COVID-19 and the perceived strength of social norms during COVID-19. Some previous studies have found that the perceived risk of COVID-19 is associated with more negative emotions and higher degrees of depression, and declined trust in public information [ 11 , 43 ]; however, another study found that people in the pandemic reported higher trust in science, politicians, and police, and higher levels of patriotism, but higher rates of mental distress compared to people in the pre-lockdown pre-pandemic group [ 44 ]. Potentially resolving this discrepancy, this study provides a new insight that stronger pandemic norms correspond with lower risk perception, which ameliorates negative feelings and attitudes in both tight and loose cultures. Previous research also found that the impact of COVID-19 has a negative association with psychological well-being but a positive association with social attitudes [ 44 ]. Thus, we do not only measure people’s psychological well-being (i.e., emotions, pressure, and self-related confidence), but also attitudes toward other people, groups and organizations. Trust in organizations reflects the interaction between individuals, groups, and government agencies during the pandemic. Government agencies may benefit from paying attention to how people perceive tightened social norms, and COVID-19 risk in order to maintain a better relationship with the people, and facilitate social harmony and stability.

Limitations

Despite the intriguing findings, the current work has some limitations. First, we focus on the strength of pandemic norms, an extension of TL and its psychological influence, instead of measuring TL directly. We do not intend to exclude the possible role of TL. In fact, our results show that pandemic norm strength seems to show a positive correlation with TL (See Supplementary Results ). However, more evidence is needed to investigate the influence of TL on pandemic norm strength. Future research could extend our results by investigating the association between emerging norms and long-term norms. Second, the current study is a cross-sectional study which cannot assess causality. Caution is needed when interpreting our results. Third, given that the data of non-responders were not available, we cannot reliably estimate the non-response bias. Future work is suggested to compare responders with non-respondents on the measures of interest. Finally, as the pandemic situation changes, we assume that the strength of pandemic norms also changes across time, but we have not investigated the psychological influence of changes in pandemic norm strength. Future research can use multiple methods, such as qualitative analysis, to analyze the changes of the pandemic norms in countries and regions, e.g., the trends of social norms over time, the inflection points of the COVID-19 pandemic, and their associations with the public’s psychological characteristics. These, we believe, will help extend current findings and enlighten future pandemic management.

The current study deepens our understanding of COVID-19’s influence on both psychological well-being and social attitudes. The current research provides a cultural psychology perspective to examine the changes in social norms brought about by COVID-19, the relationship between social norm strength and perceived risk, and the association between the two and both psychological well-being (emotions, psychological pressure, and self-confidence) and social attitudes (interpersonal trust, organizational trust, and confidence in others and organizations). This complements previous literature by illustrating the potential benefits of tight norms in managing public health crises. For example, tightening social norms could also improve psychological well-being during the pandemic. Policy makers may need to specifically target people are less sensitive to social norms and their dynamic changes.

Availability of data and materials

De-identified data and code of the present study is available upon request to the corresponding author Prof. Mu.

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Acknowledgements

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This research was supported by the National Natural Science Foundation of China (32071016), the Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences (2019000050, E2CX3935CX), and CAS Key Laboratory of Behavioral Science, Institute of Psychology (Y5CX052003).

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Shuang Liu, Jiajia Zhu, Yutong Liu & Yan Mu

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Jiajia Zhu, Yutong Liu & Yan Mu

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Contributions

Y.M. conceived of the project. Y.M. J.Z. and Y.L. designed the project, implemented the experiment, and collected data. S.L., J.Z., and Y.L. pre-processed the data and performed analyses. All authors discussed the results. S.L., J.Z., D.W., J.C.J., Y.M. wrote the paper. The author(s) read and approved the final manuscript.

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Correspondence to Yan Mu .

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All methods were carried out in accordance with relevant guidelines and regulations. This study was approved by the Ethics Committee of the Institute of Psychology, Chinese Academy of Sciences(H19048). All participants gave their written informed consent before the survey for participation.

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Liu, S., Zhu, J., Liu, Y. et al. Perception of strong social norms during the COVID-19 pandemic is linked to positive psychological outcomes. BMC Public Health 22 , 1403 (2022). https://doi.org/10.1186/s12889-022-13744-2

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DOI : https://doi.org/10.1186/s12889-022-13744-2

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• Cultural tightness-looseness
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• Public mental health

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Adapting to the culture of ‘new normal’: an emerging response to COVID-19

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Jeff Clyde G Corpuz, Adapting to the culture of ‘new normal’: an emerging response to COVID-19, Journal of Public Health , Volume 43, Issue 2, June 2021, Pages e344–e345, https://doi.org/10.1093/pubmed/fdab057

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A year after COVID-19 pandemic has emerged, we have suddenly been forced to adapt to the ‘new normal’: work-from-home setting, parents home-schooling their children in a new blended learning setting, lockdown and quarantine, and the mandatory wearing of face mask and face shields in public. For many, 2020 has already been earmarked as ‘the worst’ year in the 21st century. Ripples from the current situation have spread into the personal, social, economic and spiritual spheres. Is this new normal really new or is it a reiteration of the old? A recent correspondence published in this journal rightly pointed out the involvement of a ‘supportive’ government, ‘creative’ church and an ‘adaptive’ public in the so-called culture. However, I argue that adapting to the ‘new normal’ can greatly affect the future. I would carefully suggest that we examine the context and the location of culture in which adaptations are needed.

To live in the world is to adapt constantly. A year after COVID-19 pandemic has emerged, we have suddenly been forced to adapt to the ‘new normal’: work-from-home setting, parents home-schooling their children in a new blended learning setting, lockdown and quarantine, and the mandatory wearing of face mask and face shields in public. For many, 2020 has already been earmarked as ‘the worst’ year in the 21st century. 1 Ripples from the current situation have spread into the personal, social, economic and spiritual spheres. Is this new normal really new or is it a reiteration of the old? A recent correspondence published in this journal rightly pointed out the involvement of a ‘supportive’ government, ‘creative’ church and an ‘adaptive’ public in the so-called culture. 2 However, I argue that adapting to the ‘new normal’ can greatly affect the future. I would carefully suggest that we examine the context and the location of culture in which adaptations are needed.

The term ‘new normal’ first appeared during the 2008 financial crisis to refer to the dramatic economic, cultural and social transformations that caused precariousness and social unrest, impacting collective perceptions and individual lifestyles. 3 This term has been used again during the COVID-19 pandemic to point out how it has transformed essential aspects of human life. Cultural theorists argue that there is an interplay between culture and both personal feelings (powerlessness) and information consumption (conspiracy theories) during times of crisis. 4 Nonetheless, it is up to us to adapt to the challenges of current pandemic and similar crises, and whether we respond positively or negatively can greatly affect our personal and social lives. Indeed, there are many lessons we can learn from this crisis that can be used in building a better society. How we open to change will depend our capacity to adapt, to manage resilience in the face of adversity, flexibility and creativity without forcing us to make changes. As long as the world has not found a safe and effective vaccine, we may have to adjust to a new normal as people get back to work, school and a more normal life. As such, ‘we have reached the end of the beginning. New conventions, rituals, images and narratives will no doubt emerge, so there will be more work for cultural sociology before we get to the beginning of the end’. 5

Now, a year after COVID-19, we are starting to see a way to restore health, economies and societies together despite the new coronavirus strain. In the face of global crisis, we need to improvise, adapt and overcome. The new normal is still emerging, so I think that our immediate focus should be to tackle the complex problems that have emerged from the pandemic by highlighting resilience, recovery and restructuring (the new three Rs). The World Health Organization states that ‘recognizing that the virus will be with us for a long time, governments should also use this opportunity to invest in health systems, which can benefit all populations beyond COVID-19, as well as prepare for future public health emergencies’. 6 There may be little to gain from the COVID-19 pandemic, but it is important that the public should keep in mind that no one is being left behind. When the COVID-19 pandemic is over, the best of our new normal will survive to enrich our lives and our work in the future.

No funding was received for this paper.

UNESCO . A year after coronavirus: an inclusive ‘new normal’. https://en.unesco.org/news/year-after-coronavirus-inclusive-new-normal . (12 February 2021, date last accessed) .

Cordero DA . To stop or not to stop ‘culture’: determining the essential behavior of the government, church and public in fighting against COVID-19 . J Public Health (Oxf) 2021 . doi: 10.1093/pubmed/fdab026 .

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El-Erian MA . Navigating the New Normal in Industrial Countries . Washington, D.C. : International Monetary Fund , 2010 .

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Alexander JC , Smith P . COVID-19 and symbolic action: global pandemic as code, narrative, and cultural performance . Am J Cult Sociol 2020 ; 8 : 263 – 9 .

Biddlestone M , Green R , Douglas KM . Cultural orientation, power, belief in conspiracy theories, and intentions to reduce the spread of COVID-19 . Br J Soc Psychol 2020 ; 59 ( 3 ): 663 – 73 .

World Health Organization . From the “new normal” to a “new future”: A sustainable response to COVID-19. 13 October 2020 . https: // www.who.int/westernpacific/news/commentaries/detail-hq/from-the-new-normal-to-a-new-future-a-sustainable-response-to-covid-19 . (12 February 2021, date last accessed) .

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Changes in Social Norms during the Early Stages of the COVID-19 Pandemic across 43 Countries

The emergence of COVID-19 dramatically changed social behavior across societies and contexts. Here we study whether social norms also changed. Specifically, we study this question for cultural tightness (the degree to which societies generally have strong norms), specific social norms (e.g. stealing, hand washing), and norms about enforcement, using survey data from 30,431 respondents in 43 countries recorded before and in the early stages following the emergence of COVID-19. Using variation in disease intensity, we shed light on the mechanisms predicting changes in social norm measures. We find evidence that, after the emergence of the COVID-19 pandemic, hand washing norms increased while tightness and punishing frequency slightly decreased but observe no evidence for a robust change in most other norms. Thus, at least in the short term, our findings suggest that cultures are largely stable to pandemic threats except in those norms, hand washing in this case, that are perceived to be directly relevant to dealing with the collective threat.

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• Volume 76, Issue 2
• COVID-19 pandemic and its impact on social relationships and health
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• http://orcid.org/0000-0003-1512-4471 Emily Long 1 ,
• Susan Patterson 1 ,
• Karen Maxwell 1 ,
• Carolyn Blake 1 ,
• http://orcid.org/0000-0001-7342-4566 Raquel Bosó Pérez 1 ,
• Ruth Lewis 1 ,
• Mark McCann 1 ,
• Julie Riddell 1 ,
• Kathryn Skivington 1 ,
• Rachel Wilson-Lowe 1 ,
• http://orcid.org/0000-0002-4409-6601 Kirstin R Mitchell 2
• 1 MRC/CSO Social and Public Health Sciences Unit , University of Glasgow , Glasgow , UK
• 2 MRC/CSO Social and Public Health Sciences Unit, Institute of Health & Wellbeing , University of Glasgow , Glasgow , UK
• Correspondence to Dr Emily Long, MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow G3 7HR, UK; emily.long{at}glasgow.ac.uk

This essay examines key aspects of social relationships that were disrupted by the COVID-19 pandemic. It focuses explicitly on relational mechanisms of health and brings together theory and emerging evidence on the effects of the COVID-19 pandemic to make recommendations for future public health policy and recovery. We first provide an overview of the pandemic in the UK context, outlining the nature of the public health response. We then introduce four distinct domains of social relationships: social networks, social support, social interaction and intimacy, highlighting the mechanisms through which the pandemic and associated public health response drastically altered social interactions in each domain. Throughout the essay, the lens of health inequalities, and perspective of relationships as interconnecting elements in a broader system, is used to explore the varying impact of these disruptions. The essay concludes by providing recommendations for longer term recovery ensuring that the social relational cost of COVID-19 is adequately considered in efforts to rebuild.

• inequalities

Data availability statement

Data sharing not applicable as no data sets generated and/or analysed for this study. Data sharing not applicable as no data sets generated or analysed for this essay.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/jech-2021-216690

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Introduction

Infectious disease pandemics, including SARS and COVID-19, demand intrapersonal behaviour change and present highly complex challenges for public health. 1 A pandemic of an airborne infection, spread easily through social contact, assails human relationships by drastically altering the ways through which humans interact. In this essay, we draw on theories of social relationships to examine specific ways in which relational mechanisms key to health and well-being were disrupted by the COVID-19 pandemic. Relational mechanisms refer to the processes between people that lead to change in health outcomes.

At the time of writing, the future surrounding COVID-19 was uncertain. Vaccine programmes were being rolled out in countries that could afford them, but new and more contagious variants of the virus were also being discovered. The recovery journey looked long, with continued disruption to social relationships. The social cost of COVID-19 was only just beginning to emerge, but the mental health impact was already considerable, 2 3 and the inequality of the health burden stark. 4 Knowledge of the epidemiology of COVID-19 accrued rapidly, but evidence of the most effective policy responses remained uncertain.

The initial response to COVID-19 in the UK was reactive and aimed at reducing mortality, with little time to consider the social implications, including for interpersonal and community relationships. The terminology of ‘social distancing’ quickly became entrenched both in public and policy discourse. This equation of physical distance with social distance was regrettable, since only physical proximity causes viral transmission, whereas many forms of social proximity (eg, conversations while walking outdoors) are minimal risk, and are crucial to maintaining relationships supportive of health and well-being.

The aim of this essay is to explore four key relational mechanisms that were impacted by the pandemic and associated restrictions: social networks, social support, social interaction and intimacy. We use relational theories and emerging research on the effects of the COVID-19 pandemic response to make three key recommendations: one regarding public health responses; and two regarding social recovery. Our understanding of these mechanisms stems from a ‘systems’ perspective which casts social relationships as interdependent elements within a connected whole. 5

Social networks

Social networks characterise the individuals and social connections that compose a system (such as a workplace, community or society). Social relationships range from spouses and partners, to coworkers, friends and acquaintances. They vary across many dimensions, including, for example, frequency of contact and emotional closeness. Social networks can be understood both in terms of the individuals and relationships that compose the network, as well as the overall network structure (eg, how many of your friends know each other).

Social networks show a tendency towards homophily, or a phenomenon of associating with individuals who are similar to self. 6 This is particularly true for ‘core’ network ties (eg, close friends), while more distant, sometimes called ‘weak’ ties tend to show more diversity. During the height of COVID-19 restrictions, face-to-face interactions were often reduced to core network members, such as partners, family members or, potentially, live-in roommates; some ‘weak’ ties were lost, and interactions became more limited to those closest. Given that peripheral, weaker social ties provide a diversity of resources, opinions and support, 7 COVID-19 likely resulted in networks that were smaller and more homogenous.

Such changes were not inevitable nor necessarily enduring, since social networks are also adaptive and responsive to change, in that a disruption to usual ways of interacting can be replaced by new ways of engaging (eg, Zoom). Yet, important inequalities exist, wherein networks and individual relationships within networks are not equally able to adapt to such changes. For example, individuals with a large number of newly established relationships (eg, university students) may have struggled to transfer these relationships online, resulting in lost contacts and a heightened risk of social isolation. This is consistent with research suggesting that young adults were the most likely to report a worsening of relationships during COVID-19, whereas older adults were the least likely to report a change. 8

Lastly, social connections give rise to emergent properties of social systems, 9 where a community-level phenomenon develops that cannot be attributed to any one member or portion of the network. For example, local area-based networks emerged due to geographic restrictions (eg, stay-at-home orders), resulting in increases in neighbourly support and local volunteering. 10 In fact, research suggests that relationships with neighbours displayed the largest net gain in ratings of relationship quality compared with a range of relationship types (eg, partner, colleague, friend). 8 Much of this was built from spontaneous individual interactions within local communities, which together contributed to the ‘community spirit’ that many experienced. 11 COVID-19 restrictions thus impacted the personal social networks and the structure of the larger networks within the society.

Social support

Social support, referring to the psychological and material resources provided through social interaction, is a critical mechanism through which social relationships benefit health. In fact, social support has been shown to be one of the most important resilience factors in the aftermath of stressful events. 12 In the context of COVID-19, the usual ways in which individuals interact and obtain social support have been severely disrupted.

One such disruption has been to opportunities for spontaneous social interactions. For example, conversations with colleagues in a break room offer an opportunity for socialising beyond one’s core social network, and these peripheral conversations can provide a form of social support. 13 14 A chance conversation may lead to advice helpful to coping with situations or seeking formal help. Thus, the absence of these spontaneous interactions may mean the reduction of indirect support-seeking opportunities. While direct support-seeking behaviour is more effective at eliciting support, it also requires significantly more effort and may be perceived as forceful and burdensome. 15 The shift to homeworking and closure of community venues reduced the number of opportunities for these spontaneous interactions to occur, and has, second, focused them locally. Consequently, individuals whose core networks are located elsewhere, or who live in communities where spontaneous interaction is less likely, have less opportunity to benefit from spontaneous in-person supportive interactions.

However, alongside this disruption, new opportunities to interact and obtain social support have arisen. The surge in community social support during the initial lockdown mirrored that often seen in response to adverse events (eg, natural disasters 16 ). COVID-19 restrictions that confined individuals to their local area also compelled them to focus their in-person efforts locally. Commentators on the initial lockdown in the UK remarked on extraordinary acts of generosity between individuals who belonged to the same community but were unknown to each other. However, research on adverse events also tells us that such community support is not necessarily maintained in the longer term. 16

Meanwhile, online forms of social support are not bound by geography, thus enabling interactions and social support to be received from a wider network of people. Formal online social support spaces (eg, support groups) existed well before COVID-19, but have vastly increased since. While online interactions can increase perceived social support, it is unclear whether remote communication technologies provide an effective substitute from in-person interaction during periods of social distancing. 17 18 It makes intuitive sense that the usefulness of online social support will vary by the type of support offered, degree of social interaction and ‘online communication skills’ of those taking part. Youth workers, for instance, have struggled to keep vulnerable youth engaged in online youth clubs, 19 despite others finding a positive association between amount of digital technology used by individuals during lockdown and perceived social support. 20 Other research has found that more frequent face-to-face contact and phone/video contact both related to lower levels of depression during the time period of March to August 2020, but the negative effect of a lack of contact was greater for those with higher levels of usual sociability. 21 Relatedly, important inequalities in social support exist, such that individuals who occupy more socially disadvantaged positions in society (eg, low socioeconomic status, older people) tend to have less access to social support, 22 potentially exacerbated by COVID-19.

Social and interactional norms

Interactional norms are key relational mechanisms which build trust, belonging and identity within and across groups in a system. Individuals in groups and societies apply meaning by ‘approving, arranging and redefining’ symbols of interaction. 23 A handshake, for instance, is a powerful symbol of trust and equality. Depending on context, not shaking hands may symbolise a failure to extend friendship, or a failure to reach agreement. The norms governing these symbols represent shared values and identity; and mutual understanding of these symbols enables individuals to achieve orderly interactions, establish supportive relationship accountability and connect socially. 24 25

Physical distancing measures to contain the spread of COVID-19 radically altered these norms of interaction, particularly those used to convey trust, affinity, empathy and respect (eg, hugging, physical comforting). 26 As epidemic waves rose and fell, the work to negotiate these norms required intense cognitive effort; previously taken-for-granted interactions were re-examined, factoring in current restriction levels, own and (assumed) others’ vulnerability and tolerance of risk. This created awkwardness, and uncertainty, for example, around how to bring closure to an in-person interaction or convey warmth. The instability in scripted ways of interacting created particular strain for individuals who already struggled to encode and decode interactions with others (eg, those who are deaf or have autism spectrum disorder); difficulties often intensified by mask wearing. 27

Large social gatherings—for example, weddings, school assemblies, sporting events—also present key opportunities for affirming and assimilating interactional norms, building cohesion and shared identity and facilitating cooperation across social groups. 28 Online ‘equivalents’ do not easily support ‘social-bonding’ activities such as singing and dancing, and rarely enable chance/spontaneous one-on-one conversations with peripheral/weaker network ties (see the Social networks section) which can help strengthen bonds across a larger network. The loss of large gatherings to celebrate rites of passage (eg, bar mitzvah, weddings) has additional relational costs since these events are performed by and for communities to reinforce belonging, and to assist in transitioning to new phases of life. 29 The loss of interaction with diverse others via community and large group gatherings also reduces intergroup contact, which may then tend towards more prejudiced outgroup attitudes. While online interaction can go some way to mimicking these interaction norms, there are key differences. A sense of anonymity, and lack of in-person emotional cues, tends to support norms of polarisation and aggression in expressing differences of opinion online. And while online platforms have potential to provide intergroup contact, the tendency of much social media to form homogeneous ‘echo chambers’ can serve to further reduce intergroup contact. 30 31

Intimacy relates to the feeling of emotional connection and closeness with other human beings. Emotional connection, through romantic, friendship or familial relationships, fulfils a basic human need 32 and strongly benefits health, including reduced stress levels, improved mental health, lowered blood pressure and reduced risk of heart disease. 32 33 Intimacy can be fostered through familiarity, feeling understood and feeling accepted by close others. 34

Intimacy via companionship and closeness is fundamental to mental well-being. Positively, the COVID-19 pandemic has offered opportunities for individuals to (re)connect and (re)strengthen close relationships within their household via quality time together, following closure of many usual external social activities. Research suggests that the first full UK lockdown period led to a net gain in the quality of steady relationships at a population level, 35 but amplified existing inequalities in relationship quality. 35 36 For some in single-person households, the absence of a companion became more conspicuous, leading to feelings of loneliness and lower mental well-being. 37 38 Additional pandemic-related relational strain 39 40 resulted, for some, in the initiation or intensification of domestic abuse. 41 42

Physical touch is another key aspect of intimacy, a fundamental human need crucial in maintaining and developing intimacy within close relationships. 34 Restrictions on social interactions severely restricted the number and range of people with whom physical affection was possible. The reduction in opportunity to give and receive affectionate physical touch was not experienced equally. Many of those living alone found themselves completely without physical contact for extended periods. The deprivation of physical touch is evidenced to take a heavy emotional toll. 43 Even in future, once physical expressions of affection can resume, new levels of anxiety over germs may introduce hesitancy into previously fluent blending of physical and verbal intimate social connections. 44

The pandemic also led to shifts in practices and norms around sexual relationship building and maintenance, as individuals adapted and sought alternative ways of enacting sexual intimacy. This too is important, given that intimate sexual activity has known benefits for health. 45 46 Given that social restrictions hinged on reducing household mixing, possibilities for partnered sexual activity were primarily guided by living arrangements. While those in cohabiting relationships could potentially continue as before, those who were single or in non-cohabiting relationships generally had restricted opportunities to maintain their sexual relationships. Pornography consumption and digital partners were reported to increase since lockdown. 47 However, online interactions are qualitatively different from in-person interactions and do not provide the same opportunities for physical intimacy.

Recommendations and conclusions

In the sections above we have outlined the ways in which COVID-19 has impacted social relationships, showing how relational mechanisms key to health have been undermined. While some of the damage might well self-repair after the pandemic, there are opportunities inherent in deliberative efforts to build back in ways that facilitate greater resilience in social and community relationships. We conclude by making three recommendations: one regarding public health responses to the pandemic; and two regarding social recovery.

Recommendation 1: explicitly count the relational cost of public health policies to control the pandemic

Effective handling of a pandemic recognises that social, economic and health concerns are intricately interwoven. It is clear that future research and policy attention must focus on the social consequences. As described above, policies which restrict physical mixing across households carry heavy and unequal relational costs. These include for individuals (eg, loss of intimate touch), dyads (eg, loss of warmth, comfort), networks (eg, restricted access to support) and communities (eg, loss of cohesion and identity). Such costs—and their unequal impact—should not be ignored in short-term efforts to control an epidemic. Some public health responses—restrictions on international holiday travel and highly efficient test and trace systems—have relatively small relational costs and should be prioritised. At a national level, an earlier move to proportionate restrictions, and investment in effective test and trace systems, may help prevent escalation of spread to the point where a national lockdown or tight restrictions became an inevitability. Where policies with relational costs are unavoidable, close attention should be paid to the unequal relational impact for those whose personal circumstances differ from normative assumptions of two adult families. This includes consideration of whether expectations are fair (eg, for those who live alone), whether restrictions on social events are equitable across age group, religious/ethnic groupings and social class, and also to ensure that the language promoted by such policies (eg, households; families) is not exclusionary. 48 49 Forethought to unequal impacts on social relationships should thus be integral to the work of epidemic preparedness teams.

Recommendation 2: intelligently balance online and offline ways of relating

A key ingredient for well-being is ‘getting together’ in a physical sense. This is fundamental to a human need for intimate touch, physical comfort, reinforcing interactional norms and providing practical support. Emerging evidence suggests that online ways of relating cannot simply replace physical interactions. But online interaction has many benefits and for some it offers connections that did not exist previously. In particular, online platforms provide new forms of support for those unable to access offline services because of mobility issues (eg, older people) or because they are geographically isolated from their support community (eg, lesbian, gay, bisexual, transgender and queer (LGBTQ) youth). Ultimately, multiple forms of online and offline social interactions are required to meet the needs of varying groups of people (eg, LGBTQ, older people). Future research and practice should aim to establish ways of using offline and online support in complementary and even synergistic ways, rather than veering between them as social restrictions expand and contract. Intelligent balancing of online and offline ways of relating also pertains to future policies on home and flexible working. A decision to switch to wholesale or obligatory homeworking should consider the risk to relational ‘group properties’ of the workplace community and their impact on employees’ well-being, focusing in particular on unequal impacts (eg, new vs established employees). Intelligent blending of online and in-person working is required to achieve flexibility while also nurturing supportive networks at work. Intelligent balance also implies strategies to build digital literacy and minimise digital exclusion, as well as coproducing solutions with intended beneficiaries.

Recommendation 3: build stronger and sustainable localised communities

In balancing offline and online ways of interacting, there is opportunity to capitalise on the potential for more localised, coherent communities due to scaled-down travel, homeworking and local focus that will ideally continue after restrictions end. There are potential economic benefits after the pandemic, such as increased trade as home workers use local resources (eg, coffee shops), but also relational benefits from stronger relationships around the orbit of the home and neighbourhood. Experience from previous crises shows that community volunteer efforts generated early on will wane over time in the absence of deliberate work to maintain them. Adequately funded partnerships between local government, third sector and community groups are required to sustain community assets that began as a direct response to the pandemic. Such partnerships could work to secure green spaces and indoor (non-commercial) meeting spaces that promote community interaction. Green spaces in particular provide a triple benefit in encouraging physical activity and mental health, as well as facilitating social bonding. 50 In building local communities, small community networks—that allow for diversity and break down ingroup/outgroup views—may be more helpful than the concept of ‘support bubbles’, which are exclusionary and less sustainable in the longer term. Rigorously designed intervention and evaluation—taking a systems approach—will be crucial in ensuring scale-up and sustainability.

The dramatic change to social interaction necessitated by efforts to control the spread of COVID-19 created stark challenges but also opportunities. Our essay highlights opportunities for learning, both to ensure the equity and humanity of physical restrictions, and to sustain the salutogenic effects of social relationships going forward. The starting point for capitalising on this learning is recognition of the disruption to relational mechanisms as a key part of the socioeconomic and health impact of the pandemic. In recovery planning, a general rule is that what is good for decreasing health inequalities (such as expanding social protection and public services and pursuing green inclusive growth strategies) 4 will also benefit relationships and safeguard relational mechanisms for future generations. Putting this into action will require political will.

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Twitter @karenmaxSPHSU, @Mark_McCann, @Rwilsonlowe, @KMitchinGlasgow

Contributors EL and KM led on the manuscript conceptualisation, review and editing. SP, KM, CB, RBP, RL, MM, JR, KS and RW-L contributed to drafting and revising the article. All authors assisted in revising the final draft.

Funding The research reported in this publication was supported by the Medical Research Council (MC_UU_00022/1, MC_UU_00022/3) and the Chief Scientist Office (SPHSU11, SPHSU14). EL is also supported by MRC Skills Development Fellowship Award (MR/S015078/1). KS and MM are also supported by a Medical Research Council Strategic Award (MC_PC_13027).

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

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Social norms, social identities and the COVID-19 pandemic: Theory and recommendations

Affiliations.

• 1 School of Management University of St Andrews St Andrews UK.
• 2 School of Philosophy, Psychology and Language Sciences University of Edinburgh Edinburgh UK.
• 3 School of Psychology University of Exeter Exeter UK.
• 4 School of Psychology University of Queensland Brisbane Queensland Australia.
• PMID: 34230834
• PMCID: PMC8250129
• DOI: 10.1111/spc3.12596

Sustained mass behaviour change is needed to tackle the COVID-19 pandemic, but many of the required changes run contrary to existing social norms (e.g., physical closeness with in-group members). This paper explains how social norms and social identities are critical to explaining and changing public behaviour. Recommendations are presented for how to harness these social processes to maximise adherence to COVID-19 public health guidance. Specifically, we recommend that public health messages clearly define who the target group is, are framed as identity-affirming rather than identity-contradictory, include complementary injunctive and descriptive social norm information, are delivered by in-group members and that support is provided to enable the public to perform the requested behaviours.

© 2021 The Authors. Social and Personality Psychology Compass published by John Wiley & Sons Ltd.

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Open Access

Peer-reviewed

Research Article

Changes in social connection during COVID-19 social distancing: It’s not (household) size that matters, it’s who you’re with

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

¶ ‡ The first and second authors contributed equally and authorship was decided by a coin flip.

Affiliation Department of Psychology, University of California, Riverside, Riverside, California, United States of America

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – review & editing

Affiliation Department of Psychology, University of British Columbia, Vancouver, B. C., Canada

Roles Conceptualization, Methodology, Writing – review & editing

• Karynna Okabe-Miyamoto, 
• Dunigan Folk, 
• Sonja Lyubomirsky, 
• Elizabeth W. Dunn

• Published: January 20, 2021
• https://doi.org/10.1371/journal.pone.0245009
• Reader Comments

To slow the transmission of COVID-19, countries around the world have implemented social distancing and stay-at-home policies—potentially leading people to rely more on household members for their sense of closeness and belonging. To understand the conditions under which people felt the most connected, we examined whether changes in overall feelings of social connection varied by household size and composition. In two pre-registered studies, undergraduates in Canada (N Study 1 = 548) and adults primarily from the U.S. and U.K. (N Study 2 = 336) reported their perceived social connection once before and once during the pandemic. In both studies, living with a partner robustly and uniquely buffered shifts in social connection during the first phases of the pandemic (β Study 1 = .22, β Study 2 = .16). In contrast, neither household size nor other aspects of household composition predicted changes in connection. We discuss implications for future social distancing policies that aim to balance physical health with psychological health.

Citation: Okabe-Miyamoto K, Folk D, Lyubomirsky S, Dunn EW (2021) Changes in social connection during COVID-19 social distancing: It’s not (household) size that matters, it’s who you’re with. PLoS ONE 16(1): e0245009. https://doi.org/10.1371/journal.pone.0245009

Editor: Daniel Romer, University of Pennsylvania, UNITED STATES

Received: August 6, 2020; Accepted: December 18, 2020; Published: January 20, 2021

Copyright: © 2021 Okabe-Miyamoto et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All files are available on OSF. Study 1 data: https://tinyurl.com/y7nvg5vf . Study 2 data: https://tinyurl.com/yc8b2n44 .

Funding: UC Riverside provided financial support to recruit participants for Study 2 (S. L. and K.O.M.), but did not play any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of each of the authors are articulated in the "author contributions" section.

Competing interests: The authors have declared that no competing interests exist.

Introduction

On March 11, 2020, the Centers for Disease Control and Prevention [ 1 ] declared the COVID-19 outbreak a pandemic. By early April, COVID-19 had already spread to nearly 1.5 million people worldwide [ 2 ]. In an effort to slow down its transmission, countries around the world implemented social/physical distancing guidelines [ 3 ], compelling individuals to stay at least 6 feet (2 meters) away from anyone outside their household [ 4 ]. Early in its implementation, the WHO [ 2 ] announced that it would be moving away from the term “social distancing” and begin using “physical distancing” to more accurately describe the practice. However, the original term stuck, especially in the U.S., U.K., Australia, Italy, France, Poland, Russia, India, South Korea, and Hong Kong, even though the very label of “social distancing” arguably undermines feelings of social connection. We use “social distancing” in this paper to reflect common usage. Such non-pharmaceutical public health interventions have been long proposed to reduce the spread of infectious disease. For example, mathematical modeling suggests that social distancing can reduce transmission of influenza by over 90% [ 5 ], and retrospective analyses of past pandemics (e.g., in 1918–1919) show that areas that implemented social distancing measures earlier were slower to reach peak and total mortality rates [ 6 ]. However, although social distancing policies have historically helped protect physical health worldwide, these policies have also greatly limited people’s range of social interactions, an important cost to weigh against their benefits.

Understanding the ways in which policy makers can balance physical health and psychological health while continuing social distancing has generated recent interest [ 7 – 9 ]. This calculus is crucial, as social distancing for extended periods of time may strain people’s needs for social connection to such an extent that they may eventually disregard policy guidelines. Social connection, or a sense of belonging and closeness with others, is fundamental to human development and well-being [ 10 – 13 ]. For example, having frequent social interactions and spending more time talking with others are both associated with greater well-being [ 14 – 16 ]. Furthermore, experiments have shown that people prompted to engage in more social interactions relative to control activities report higher levels of positive emotion and social connectedness [ 17 – 19 ]. In sum, understanding the conditions under which social connection is maximized during COVID-19 social distancing may inform future policies that can strike a balance between ensuring that people continue to social distance to protect physical health and ensuring that they stay socially connected to protect psychological health.

Social distancing initiatives have led millions of people globally to stay in their homes [ 20 ], abruptly forcing individuals to rely on their household members for their sense of overall social connection. This shift may pose a risk for those living alone, who report experiencing relatively more loneliness even under normal circumstances [ 21 , 22 ]. Living in a larger household has been shown to be protective of loneliness [ 23 ], suggesting that living in larger households may safeguard people from declines in social connection during the pandemic. In light of the stressful and uncertain nature of the pandemic, a larger household may offer not only more opportunity for social interactions but greater social support, which is associated with well-being [ 24 ]. However, living in bigger households, which requires sharing a space day in, day out with the same people, may lead to greater tension, conflict, and sense of being crowded [ 25 ].

Living with a partner in particular may offer unique advantages [ 21 ], especially during stressful times [ 26 ]. Living with a partner is also protective of loneliness compared to being single and living alone—and even compared to having a partner but not cohabiting [ 21 ]. In a large study following 30,000 people, the most important social behavior that predicted well-being was the amount of time spent with a partner [ 27 ]. However, although the weight of the evidence supports the benefits of living with partners on social connection, the stress caused by the pandemic—and the friction associated with couples forced to spend all day together in close quarters (see [ 28 ], for examples)—may also negatively impact relationships [ 29 ].

Aside from partners, other household members may also provide feelings of closeness and opportunities for interaction. For example, living with children is linked with higher well-being [ 30 ] and lower levels of loneliness [ 31 ], and so is sharing a household with pets [ 32 ]. However, such benefits may be limited during a pandemic in which children are homeschooled, parents are working remotely from home or else looking for work, and neither pet owners nor their pets are able to interact socially with their peers.

Unlike social distancing policies during past pandemics, COVID-19 is unique because people today have the ability to connect digitally not only by phone, but through the use of social media, video calling, and text messaging. However, although connecting via digital and social media has been found to enhance offline relationships [ 33 , 34 ], digital communication often feels unnatural and lacks rich nonverbal cues, which may hinder mutual understanding [ 35 ] and be cognitively taxing [ 36 ]. In times of stress and crisis, these forms of online communication may in turn promote other negative outcomes, such as “Zoom fatigue” [ 37 ]. Thus, face-to-face interactions with household members are likely to be essential to increased feelings of social connectedness.

In sum, social connection is crucial for both psychological and physical health, perhaps especially so during an unprecedented global pandemic that has claimed more lives than every war since the Korean War [ 38 ]. How can future policy guidelines balance protecting physical health through social distancing with protecting psychological health by maintaining feelings of connection? To understand the conditions under which people felt the most connected, we examined whether changes in overall feelings of social connection varied as a function of household size and composition.

Present research

In two pre-registered studies of undergraduates at a Canadian university (N Study 1 = 548) and adults primarily residing in the United States and United Kingdom (N Study 2 = 336), we followed individuals before and during the COVID-19 pandemic to examine changes in feelings of social connection based on (1) household size and (2) household composition. Using two-tailed tests, we tested the following primary hypotheses. First, we expected that people in larger households to show relatively smaller declines (or bigger increases) in social connection as a result of the COVID-19 pandemic. Second, we hypothesized that household composition would predict changes in social connection as a result of the COVID-19 pandemic. In examining household composition, we focused on whether participants lived with a partner (or not), lived with a pet (or not), and were caregivers (or not). Feelings of social connection were assessed with three different measures—the Social Connectedness Scale (Study 1; [ 39 ]), the relatedness subscale of the Balanced Measure of Psychological Needs (BMPN; Study 2; [ 40 ]), and the UCLA Loneliness Scale (Study 2; [ 41 ]).

Undergraduates at the University of British Columbia completed our measures as part of two separate surveys. We obtained ethics approval from the Behavioral Research Ethics Board at the University of British Columbia, and participants provided written consent to be part of our study. The first survey was completed before the COVID-19 pandemic (Time 1 ), and the second survey was completed during the COVID-19 pandemic (Time 2 ). We pre-registered our analysis plan and stopping rules on the OSF and they are available at [ https://tinyurl.com/yddwt28v ]. A separate pre-registered study that used a portion of the data to answer a different research question can also be found on the OSF at [ https://tinyurl.com/ybwz8ufb ].

Between January 6, 2020 and the end of March 2020, 3,504 participants completed demographic questions and a social connection measure alongside other items as part of an optional department-wide pre-screening. For consistency with Study 2, we only included participants who completed this questionnaire on or before February 12, 2020, resulting in a Time 1 sample of 2,903 students. After removing participants who were missing more than two items on the social connection measure (as pre-registered), we obtained a total sample of 2,708 eligible participants.

We invited participants who had completed pre-screening at Time 1 to complete a second survey between April 1–8 th , 2020. The Time 2 survey consisted of the same measure of social connection as in the Time 1 survey, as well as measures assessing students’ living arrangements, behaviors, and experiences during the COVID-19 pandemic. A total of 1,059 participants completed the Time 2 survey. As pre-registered, 8 participants were removed for responding 12 or more times in a row with the same answer on the social connectedness measure and 1 participant was removed for failing to answer more than 2 items on the social connectedness measure. Although not pre-registered, we also removed participants who did not supply an ID number to link responses ( n = 125) or completed the survey twice ( n = 22), For those who completed the survey twice, we only included their responses from the first survey.

Of the remaining 903 participants, 548 participants ( M age = 20.78, SD age = 2.96; 77% women) completed both surveys and met our inclusion criteria. Participants in this final dataset did not significantly differ from the remaining eligible participants who completed the Time 1 survey in Time 1 social connection ( p = .359) or household income ( p = .154). Because we aimed to recruit as many participants as possible, we did not conduct an a priori power analysis; however, based on sensitivity analyses using GPower [ 42 ] and assuming two-tailed α = 0.05 and 80% power, we should have been able to detect a small effect size of ƒ 2 = .01 (R adj 2 = .02) in a 2-predictor regression model and ƒ 2 = .01 (R adj 2 = .001) in a 5-predictor regression model. R adj 2 is reported in the manuscript. The dataset for the final sample can be found on the OSF at [ https://tinyurl.com/y7nvg5vf ].

The measures for Study 1 can be found on OSF at [ https://tinyurl.com/y7jfk4al ].

Social connection

Social connection was assessed with the revised 20-item Social Connectedness Scale [ 39 ]. Participants indicated their level of agreement with items such as, “I feel close to people” and “I feel understood by the people I know” (1 = strongly disagree , 6 = strongly agree ). We removed the item, “I feel comfortable in the presence of strangers” from both time points, because it may have had a different meaning in the midst of the pandemic. Participants completed the measure at Time 1 with reference to their general view of themselves ( α = .94). At Time 2 however, due to the rapid changes to daily life that participants were experiencing, we asked them to think about the past week ( α = .93).

Household size and composition

To assess household size, we asked participants “other than yourself, how many people are currently living in the same place you are now?” with answer choices ranging from “living alone” to “10+ people.” For each person in their household, participants specified whether the person was a “spouse/partner/girlfriend/boyfriend” (subsequently referred to as partner ), “child,” “parent,” “brother/sister,” “other family member,” “friend,” “roommate/acquaintance,” “live-in help,” or “other.” Participants could only select one option per household member.

Living with pets

We asked whether participants were “currently living with any pets” (yes/no).

Being a caregiver

Participants were asked whether they were “currently the primary caregiver for anyone else (e.g., children or elderly family members)” (yes/no).

Social/physical distancing

Participants indicated whether they were “currently practicing social or physical distancing,” and to indicate how many people aside from their household members got to within 6 feet or less of them on the previous day.

Hours spent video calling with family and friends

Participants were asked “yesterday, how many hours did you video call with family and friends” with answer choices ranging from “0” to “10+ hours.”

Study 1 results

The code used to conduct the Study 1 analyses can be found on the OSF at [ https://tinyurl.com/y7b8cnw3 ]. Correlations between all variables in Study 1 can be found in Table 1 .

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https://doi.org/10.1371/journal.pone.0245009.t001

Did household size buffer changes in social connection as a result of the COVID-19 pandemic?

As reported in Folk et al. [ 43 ], our sample exhibited a slight but significant decrease in feelings of social connectedness from Time 1 to Time 2 , and 98% of participants indicated they were social/physical distancing (see Table 2 ).

https://doi.org/10.1371/journal.pone.0245009.t002

Pre-registered analyses . First, we examined whether household size (i.e., number of people in the household other than themselves) as a continuous measure ( M = 2.54, range = 0 to 9 [with 77% living with 3 others or fewer], SD = 1.58) was associated with Time 2 social connectedness, controlling for Time 1 connectedness. After controlling for Time 1 connectedness, household size did not significantly predict Time 2 connectedness, b = 0.01, 95% CI = [-0.02, 0.04], p = .532 (see Table 3 , Model 1). We then examined the association between living alone and Time 2 social connectedness, controlling for Time 1 connectedness. In this model, living alone ( n = 49) was not significantly associated with Time 2 connectedness b = -0.12, 95% CI = [-0.30, 0.07], p = .230 (see Table 3 , Model 2).

https://doi.org/10.1371/journal.pone.0245009.t003

Did household composition buffer changes in social connection as a result of the COVID-19 pandemic?

Pre-registered analyses . While household size did not appear to play a role in changes in social connectedness from before to mid-pandemic, we investigated whether features of household composition were related to Time 2 connectedness. Controlling for Time 1 connectedness, living with a partner ( n = 67) predicted significantly greater social connectedness at Time 2 , b = 0.22, 95% CI = [0.06, 0.38], p = .008 (see Table 3 , Model 3). See Fig 1 for an illustration of this finding. In contrast, living with a pet ( n = 184) was associated with lower Time 2 connectedness after controlling for Time 1 connectedness, b = -0.12, 95% CI = [-0.24, -0.01], p = .036 (see Table 3 , Model 4). Although we also pre-registered a similar analysis investigating the effects of being a caregiver on social connection, we did not conduct it, as only 6 out of 548 participants reported being a caregiver.

Changes in social connection for those living with and without partners in Study 1 (left) and Study 2 (right). Note . Across both Study 1 and Study 2, those living with a partner reported greater increases in social connection from before the pandemic (Time 1 ) to during the pandemic (Time 2 ) than those not living with a partner. Error bars represent 95% Confidence Intervals.

https://doi.org/10.1371/journal.pone.0245009.g001

Exploratory analyses . To further investigate the relationship between household size and composition and Time 2 social connection, we entered the household variables (household size, living alone, living with a partner, and having a pet) into a single model predicting Time 2 social connectedness while controlling for Time 1 connectedness. Consistent with the results of our pre-registered analyses, in this full model, living with a partner was significantly associated with higher Time 2 social connectedness, b = 0.22, 95% CI = [0.06, 0.39], p = .008, whereas having a pet was significantly associated with lower Time 2 social connectedness, b = -0.15, 95% CI = [-0.26, -0.03], p = .014 (see Table 3 , Model 5). No other effects were significant.

Was the relationship between household size and changes in social connection mediated by total hours video calling with family and friends or social distancing?

Pre-registered analyses . It is possible that we observed no relationship between household size and shifts in social connection because individuals in smaller households may be more likely to engage in video calling or may be less likely to socially distance from non-household members. However, correlations among these variables were nonsignificant (see Table 1 ), precluding mediation. The pre-registered mediation analyses are presented in S1 Table .

Given our first study’s reliance on college students, we sought to replicate its results with a sample of adults from around the globe (U.S., U.K., and 26 other countries), who were recruited to complete our survey at two timepoints: once prior (Time 1 ) and once during (Time 2 ) the COVID-19 pandemic. We obtained ethics approval from the Institutional Review Board at the University of California, Riverside, and participants provided written consent to join our study. Our pre-registered stopping rules and analysis plans for Study 2 are available at [ https://tinyurl.com/y8s5ssm9 ] on the OSF website. A portion of the data was also included in another pre-registered study [ https://tinyurl.com/yc8b2n44 ].

On February 12, 2020, participants ( N = 396; M age = 31.61, SD age = 11.88; 55% Male; 80% White; 46% single/never married; 32% U.S.; 27% U.K.) completed measures of social connection, loneliness, and demographics (along with other measures that were not part of our pre-registered analysis plan). All participants were recruited from Prolific Academic TM , a recruitment platform demonstrated to provide quality online data [ 44 ].

From April 1 to April 8, 2020, we re-recruited the same Prolific users who had completed all Time 1 measures to participate in our Time 2 survey. Time 2 included the same measures assessed at Time 1 , as well as additional exploratory measures about participants’ experiences during COVID-19. Our final sample comprised 336 participants ( M age = 32.03, SD age = 11.94; 55% Male; 80% White; 45% single/never married; 32% U.S.; 27% U.K.) who completed both Time 1 and Time 2 surveys and met our pre-registered inclusion criteria. A sensitivity analysis using GPower [ 42 ], assuming two-tailed α = 0.05 and 80% power, revealed the power to detect a small effect size of ƒ 2 = .03 (R adj 2 = .02) in a 2-predictor regression model and ƒ 2 = .03 (R adj 2 = .01) in a 7-predictor regression model. R adj 2 is reported in the manuscript. The final dataset for Study 2 can be found on OSF at [ https://tinyurl.com/yc8b2n44 ].

The measures for Study 2 can be found on OSF at [ https://tinyurl.com/yapg6tdt ]. The same measures of (1) household size, (2) household composition (i.e., living with a partner), (3) living with pets, (4) being a caregiver, (5) social/physical distancing, and (6) hours spent video calling with family and friends were used as in Study 1.

Social connection in this study was assessed with two measures: (1) the 6-item relatedness subscale of the BMPN [ 1 , 40 ] and (2) the 20-item UCLA Loneliness Scale [ 41 ]. The relatedness subscale asked participants to think about the past week and rate agreement with statements such as, “I felt close and connected with other people who are important to me” (1 = strongly disagree , 7 = strongly agree ). Relatedness scores were highly reliable at both Time 1 ( α = .76) and Time 2 ( α = .77). The UCLA Loneliness Scale prompted participants to respond to statements based on how they feel in general (e.g., “People are around me but not with me”; 1 = never , 4 = often ). Loneliness scores were highly reliable at both Time 1 ( α = .88) and Time 2 ( α = .88).

Hours spent working outside the home

Participants were additionally asked “how many hours per week do you work outside the home?” with answer choices ranging from “0” to “40+ hours.”

Additional exclusion criteria

As pre-registered, to screen out inattentive participants, we planned to exclude those who provided the same answer 15 times in a row on the 20-item UCLA Loneliness Scale. We also pre-registered to exclude those who were missing more than 1 item on the 6-item BMPN relatedness subscale and missing more than 2 items on the UCLA Loneliness Scale. However, we did not have any instances of inattentiveness or missing data.

Study 2 results

The R code used for the analyses in Study 2 can be found on OSF at [ https://tinyurl.com/y7nhpx7h ]. Correlations among variables in Study 2 can be found in Table 4 .

https://doi.org/10.1371/journal.pone.0245009.t004

Did household size buffer changes in social connection as a result of the COVID-19 pandemic?. As reported by Folk et al. (2020), our sample showed no changes in relatedness and small but significant improvements in loneliness from before to after the pandemic. Additionally, 93% of participants reported that they were social distancing (see Table 5 ).

https://doi.org/10.1371/journal.pone.0245009.t005

Pre-registered analyses . We first examined whether a continuous measure of household size ( M = 2.38, range = 0 to 5 [with 88% living with 2 others or fewer], SD = 0.98) was associated with our two measures of Time 2 social connection (relatedness and loneliness), after controlling for Time 1 social connection. Similar to Study 1, after controlling for Time 1 social connection, household size did not predict Time 2 social connection for relatedness, b = -.003, 95% CI = [-0.11, 0.10], p = .954 (see Table 6 , Model 1) or loneliness, b = -0.01, 95% CI [-0.04, 0.02], p = .456 (see Table 6 , Model 2). Similarly, living alone ( n = 55) compared to not living alone ( n = 281) was not reliably associated with Time 2 social connection for relatedness, b = -.23, 95% CI [-0.51, 0.06], p = .119 (see Table 6 , Model 3) or loneliness, b = .004, 95% CI [ -0.08, 0.09], p = .925 (see Table 6 , Model 4) after controlling for Time 1 social connection.

https://doi.org/10.1371/journal.pone.0245009.t006

Pre-registered analyses . Next, we tested whether aspects of household composition were associated with Time 2 social connection, controlling for Time 1 levels of social connection, for our two measures of social connection (loneliness and relatedness). None of the household composition variables were significantly associated with Time 2 loneliness, when controlling for Time 1 loneliness (see Table 6 ). However, consistent with Study 1, living with a partner ( n = 124) was associated with greater Time 2 relatedness after controlling for Time 1 relatedness, b = .43, 95% CI [0.21, 0.65], p < .001 (see Table 6 , Model 5; see Fig 1 for an illustration of this finding). We repeated the same analysis with each of the other household composition variables. Living with children was linked to marginally greater Time 2 relatedness after controlling for Time 1 relatedness, ( n = 74; b = .25, 95% CI [-0.004, 0.51], p = .053 (see Table 6 , Model 7). Finally, living with pets ( n = 168; b = .18, 95% CI [-0.03, 0.40], p = .093 (see Table 6 , Model 9) and being a caregiver ( n = 63; b = .25, 95% CI [-0.02, 0.52], p = .074 (see Table 6 , Model 11) showed similar marginal positive effects.

Exploratory analyses . As in Study 1, we examined which aspects of household size and composition—when tested in a single model—best predicted Time 2 social connection after controlling for Time 1 social connection. None of the household size and composition variables were significantly associated with Time 2 loneliness, when controlling for Time 1 loneliness (see Table 7 , Model 14). However, when we examined the same variables (household size, living alone, living with a partner, living with a child, living with a pet, and being a caregiver) in a single model predicting Time 2 relatedness, controlling for Time 1 relatedness, living with a partner was the only factor that buffered changes in social connection, b = .38, 95% CI. [0.09, 0.67], p = .012 (see Table 7 , Model 13). This finding was consistent with Study 1.

https://doi.org/10.1371/journal.pone.0245009.t007

Did working outside of the home moderate the effects of household size and composition on changes in social connection?

Pre-registered analyses . We expected that household size and household composition might matter less for social connection for individuals who worked outside the home. However, we did not find that hours working outside the home moderated the relationship between household size (continuous and living alone) or composition (living with a partner, living with children, living with a pet, being a caregiver) and changes in relatedness or loneliness (see S2 Table ).

Pre-registered analyses . No significant correlations emerged between our outcome variable (relatedness, loneliness) and 1) our predictor variable (household size) and 2) our mediator variables (hours video calling, social distancing; see Table 4 for correlations). Thus, parallel to Study 1, the number of hours spent video calling with family and friends or social distancing did not mediate the relationship between household size (continuous and living alone) and changes in relatedness or loneliness (see S3 Table ).

Across two pre-registered studies that followed the same participants from before the COVID-19 pandemic into its early stages, we found that living with a partner was the strongest predictor of shifts in social connection across time. This finding replicated across two different samples—a sample of undergraduates at a Canadian university and a sample of adults from mostly the U.S. and the U.K. Both of our studies revealed robust positive regression coefficients indicating that people living with a partner were more likely to improve in social connection after social distancing guidelines were in place than those not living with a partner. This finding is consistent with past research demonstrating that being in a relationship is one of the strongest predictors of connection and well-being [ 11 , 45 ], in part because happier people are more likely to find partners [ 46 , 47 ]. Additionally, during times of worry and uncertainty, partners have been found to be more valuable for coping than other types of household members [ 26 ]. Moreover, recent research has shown that, on average, romantic relationships have not deteriorated over the course of the pandemic; indeed, people are relatively more willing to forgive their partners during COVID-19 [ 48 ]. In light of this evidence, it is not surprising that partners showed the strongest effect, especially during a pandemic.

Contrary to our pre-registered hypotheses, changes in loneliness were not predicted by any other aspects of household composition. Furthermore, we found only nonsignificant trends for the impact of household size, including living alone, on social connection during COVID-19, perhaps because both our studies included small samples of those living in large households and households of one. It is important to keep in mind that the pandemic has forced people to spend unusually large amounts of time confined to home. Given that interpersonal interactions must be positive to contribute to one’s overall sense of connectedness [ 10 ], those who live in larger households—relative to those who live alone or in smaller households—may have had more interactions that were negative (e.g., due to bickering or lack of privacy and alone time) and, as a result, failed to experience benefits in terms of social connection. Moreover, our studies measured experiences fairly early in the pandemic (April 2020); thus, as people continue to distance over long periods of time, their feelings of social connection may suffer. Going beyond household size and structure, future studies should examine the effects of relationship quality on social connection over time.

When examining how other features of household composition were associated with shifts in social connection during the pandemic, we obtained mixed findings regarding living with pets and null findings for all other household variables. However, because households are multifaceted, larger sample sizes will be needed to fully dissect the household composition findings, as well as to reveal interactions (such as with household size, gender, or country of residence). For example, studies with larger sample sizes may uncover differences in connection between those in households of four (with a partner and two children) versus households of five (with a partner and three children), and so on. Importantly, future investigators may wish to further unpack the role of household dynamics, as some households include unhealthy relationships that may be exacerbated by social distancing measures and others include housemates that minimally interact. As such, the quality and frequency of interaction among household members—perhaps with experience sampling or daily diary measures—is an important factor to explore in future work.

Implications and conclusions

Directed by social distancing interventions in the spring of 2020, millions of people were no longer commuting to work, attending school, or leaving their homes to spend time with friends and family. These extraordinary conditions likely led people to rely more on their household members to fulfill their needs for closeness, belonging, and connection [ 10 ]. The results from our two studies revealed that living with a partner—but not how many people or who else one lives with—appeared to confer unique benefits during these uncertain and unprecedented times. Indeed, demonstrating its robustness, this finding replicated across our two studies, despite weak and opposite correlations between household size and living with a partner ( r = -.06 in Study 1 and .11 in Study 2).

In light of these results, policy makers might consider developing guidelines for social/physical distancing that protect people’s physical health while ensuring they retain a sense of closeness and connection by spending time in close proximity with partners, even outside their households. Some areas in the world, such as New Zealand, have implemented a strategy known as the “social bubble,” which is the easing of social distancing to allow close contact with another household [ 49 ]. Such approaches might be especially helpful for individuals who have been unintentionally and disproportionally socially isolated by social distancing measures, such as those who are cut-off, separated from their partners, or generally struggling with staying at home. However, social bubbles pose a risk of increased infection rates [ 49 ]. Hence, just as safe sex education aims to reduce the rate of sexually transmitted diseases and unintended pregnancy, education on safe social distancing (or social bubbling) strategies might guide individuals across the globe how to connect with others safely while simultaneously curtailing COVID-19 rates. In sum, recommendations that reduce the risk of transmission while prioritizing social connection can ensure that people’s physical and psychological health are optimally balanced.

Supporting information

S1 table. results of mediation analyses (study 1)..

https://doi.org/10.1371/journal.pone.0245009.s001

S2 Table. Results of moderation analyses for hours spent working (Study 2).

https://doi.org/10.1371/journal.pone.0245009.s002

S3 Table. Results of mediation analyses (Study 2).

https://doi.org/10.1371/journal.pone.0245009.s003

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• Social Policy

The importance of new social norms in a COVID-19 outbreak

To contain the rapid spread of COVID-19, we’ve all been asked to practice social distancing . Its wider social benefits are clear: reduced disease transmission, less stress on the health care system, and fewer deaths. So why are some people resistant to doing it ? The personal benefits of social distancing are uncertain, whereas the burden on individuals is high, from disrupted family routines to loneliness . To outweigh these personal costs without jeopardizing civil liberties , social distancing must become a social norm.

How can we achieve this?

Our study of the 2009 H1N1 influenza outbreak offers lessons about the role of consistent and continuous public messaging in helping people choose behaviours that promote the social good over a personal cost.

How can social norms help?

A social norm is an informal rule of behaviour that governs interactions when they can lead to more than one outcome. Social norms prescribe actions that produce socially beneficial outcomes, even when those actions have costs for individuals such as monetary expenses, psychological costs or extra effort. In the case of social distancing, some behaviours are less costly than others. Greeting each other in a way other than shaking hands is a low-cost change. Other changes, like self-isolation or homeschooling, are much costlier. When a social norm is established, these personal costs will be offset by the psychological benefits of acting properly and experiencing social acceptance.

Social norms reflect commonly shared beliefs about appropriate actions, with the expectation that others will follow them, too. These appropriate actions then become prominent among all possible behaviours. They stand out.

Take, for example, greetings. Shaking hands is normally a prominent action that is used to greet others in many cultures. By extending your arm, you expect the other person to do the same. If this belief is shared, the two of you shake hands. Otherwise, no handshaking occurs, as illustrated in early March when Germany’s Interior Minister refused to shake Chancellor Angela Merkel’s hand . Since the COVID-19 pandemic started, alternative greetings have been quick to appear, such as the elbow bump, the Namaste hand prayer, the Vulcan salute and the “ Wuhan shake .” But none of these has become prominent yet.

For preventive measures to become prominent and gain footing as a new norm, common knowledge needs to be provided by health authorities to instill common beliefs. Will public messages be efficient enough and sufficient to achieve consensus around new behaviours? No one knows.

However, there are lessons to be learned from the 2009 H1N1 influenza outbreak, which emerged in the spring of 2009, and has some similarities to and important differences from the coronavirus outbreak.

The 2009 H1N1 influenza was less contagious and less fatal than COVID-19, and its social and economic impacts were not as severe as that those we are likely facing today. Consequently, we’ll need far greater behavioural changes now, because of the closure of schools, workplaces, and international borders. In 2009, authorities recommended self-isolation only to people with flu-like symptoms and asked them to seek medical care only if their symptoms worsened. This was the extent of efforts needed to stop virus transmission and to avoid overcrowding emergency rooms. By late November 2009 a targeted H1N1 influenza vaccine had become widely available , adding one more thing to the list of prevention measures.

However, the main public messages about prevention in 2009 overlapped with those we hear today: wash your hands, cough or sneeze into your sleeve, and stay home if you have symptoms. Tailored to create common beliefs, these messages were highly visible in public spaces, in the media and online.

To understand how Canadians responded to these messages, we conducted an economic experiment with 120 volunteers in Montreal, measuring changes in their common beliefs about prominent health actions before and after the 2009 H1N1 outbreak.

Three findings stand out:

• Common beliefs about prominent actions for those who were sick shifted from being individualistic to favouring public benefit. Before the outbreak, seeking medical help was the prominent thing to do; after the outbreak, avoiding contact with other people gained prominence.
• Common beliefs about prominent preventive measures moved from a focus on hygiene to one on getting vaccinated, despite widely circulated misinformation about the vaccine’s safety and the availability of easier actions like hand washing.
• Common beliefs about the vaccine’s side effects changed as well. Before the outbreak, participants believed nobody knew what the correct side effects were. Afterward, most of them believed the correct side effects were widely known.

Our findings imply that exposure to common information, including messages from public health authorities, was responsible for these changes in common beliefs. The findings were independent of participants’ characteristics, medical knowledge, and personal experience with the illness or the vaccine.

What does this mean for the COVID-19 pandemic?

First, public messaging that strongly emphasizes the health of others is even more important today than it was for 2009 H1N1 influenza, because COVID-19 can be transmitted by nearly asymptomatic people who may be unwilling to self-isolate for weeks. In 2009, the focus of official messages on the public health benefits rather than personal needs appeared to work.

However, the authorities and the media should be aware of possible unintended effects of their messages on peoples’ behaviour. First, recent reports about older peoples’ vulnerability to COVID-19 might have had the adverse effect of lowering the perceived risk among the younger population and muting the prominence of social distancing, an oversight that is being corrected only now . In 2009, young adults were more vulnerable to the H1N1 influenza than were older individuals. Hence, it is possible our participants, whose median age was 27, paid more attention to public messages to protect themselves and their peers.

Second, once a vaccine is available, it might become a prominent option recognized by most people, either because it is less costly to get a shot than make behavioural changes, or because vaccines are seen as more effective at preventing contagious diseases. Without a vaccine, more efforts are needed to emphasize better hygiene and social distancing as vital preventive measures, which might also become helpful in the long run if they help contain future pandemics of new viruses.

Finally, there are three relevant takeaways about the role of public messages in the fight against the misinformation about COVID-19 . First, misinformation about the 2009 H1N1 vaccine, often self-contradicting, failed to create false common beliefs about the vaccine’s side effects. Second, this misinformation might have inadvertently attracted attention to the H1N1 vaccine as a prominent prevention action. Third, high prominence of correct responses about side effects post-outbreak clearly indicates the effectiveness of public messages in correcting misinformation.

There are also new factors at play in 2020

The presence of social media in our lives is much stronger today than it was in 2009. What role will mass communication and message personalization play in establishing/reinforcing norms , spreading (mis)information , and helping people stay connected to cope with isolation ? Can authorities effectively use social media to engage youth and gain access to a wider audience in order to “ spread the info, not the virus ”?

Media and opinion polarization have increased since 2009. Will common beliefs vary across population subgroups, depending on where they get their news or which political party they identify with ?

Whatever happens, we must change our behaviour in this critical time if we hope to minimize the social and economic impact of the pandemic without introducing draconian measures. More interconnected now than ever, we must use all available tools to disseminate scientific and medical expertise, communicate key messages prominently and widely, and adopt new social norms to collectively tackle this challenge facing all humanity. Lessons learned during this outbreak might help societies better coordinate and cooperate when dealing with future pandemics.

This article is based on Coordination, Common Knowledge and an H1N1 Outbreak , by Jim Engle-Warnick, Sonia Laszlo, Natalia Mishagina, and Erin Strumpf, CIRANO Scientific Series 2013s.

This article is part of the  The Coronavirus Pandemic: Canada’s Response   special feature.

Photo: The elbow bump is one of the new alternatives to the handshake. Shutterstock, by Linda Bestwick. 

You are welcome to republish this Policy Options article online or in print periodicals, under a Creative Commons/No Derivatives licence.

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by Natalia Mishagina, Sonia Laszlo, Erin Strumpf. Originally published on Policy Options March 31, 2020

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National identity plays a part in how likely people are to support public-health policies such as mask wearing. Credit: Benoit Tessier/Reuters/Alamy

During the early months of the COVID-19 pandemic, Jay Van Bavel, a psychologist at New York University, wanted to identify the social factors that best predict a person’s support for public-health measures, such as physical distancing or closing restaurants. He had a handful of collaborators ready to collect survey data. But because the pandemic was going on everywhere, he wondered whether he could scale up the project. So he tried something he’d never done before.

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Nature 593 , 331-333 (2021)

doi: https://doi.org/10.1038/d41586-021-01317-z

Van Bavel, J. J. et al. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/ydt95 (2020).

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New Social Norms During the Pandemic

Cristina Bicchieri, Sascha Jane Patterson Harvie Professor of Social Thought and Comparative Ethics, says expectations fuel behavior modification.

As COVID-19 spread across the world, it became abundantly clear that different countries were responding differently to the virus. Cristina Bicchieri, Sascha Jane Patterson Harvie Professor of Social Thought and Comparative Ethics, who studies social norms and how they evolve, wanted to understand how a nation’s response had affected individual behaviors. 

“We decided to do a study in nine different countries, which included Mexico, Colombia, China, South Korea, Italy, Spain, Germany, the U.K., and the U.S.,” says Bicchieri, also a professor of philosophy, psychology, and legal studies. 

Bicchieri and Enrique Fatas, a distinguished fellow in Penn’s Master of Behavioral and Decision Sciences program, which Bicchieri runs, created a survey focused on how COVID-related norms like social distancing and mask-wearing have emerged. Broadly, they found that changes come about under three conditions, two of which relate to expectations about the actions and beliefs of relevant others. These “others” aren’t just family, friends, and neighbors, but also people who live in the same city or county, and generally people whose behavior matters to us. 

“Public information and the media may change people’s expectations about what others do and what others believe is appropriate to do,” she says. But new expectations alone aren’t enough; they need to cause people to want to change their behavior. 

To test this in the context of COVID, Bicchieri and her team presented vignettes to subjects from all nine countries, varying the expectations of the vignette protagonist, then asked participants the likelihood that person would practice social distancing and stay home. 

The researchers found that to motivate people to modify their behavior, it’s first necessary to change their expectations. “This is very important,” Bicchieri says. “It’s not enough to say that sending a message about what others do or approve of will induce a behavioral change. We want to be sure that these social expectations actually push people to behave in a different way.” 

But is changing expectations enough? In a public health crisis like the COVID-19 pandemic, Bicchieri adds it’s crucial not to underestimate the importance of trust in science. When people don’t trust the science, they may be tempted to free ride on the behavior of others because they believe their own risk to be low, she says.

She offers several recommendations the research has shown can make norm-nudging successful: In circumstances like the pandemic, governments shouldn’t downplay science, nor should they send conflicting messages. Beyond that, they should shape their message for the audience they want to reach. 

Bicchieri gives the example of young people minimizing their risk of getting COVID-19. “A common message in both Italy and the U.S. was, ‘Older people and people with pre-existing conditions are the most vulnerable.’ A lot of young people thought, ‘I’m not old, I don’t have a pre-existing disease, therefore it’s safe for me,’” she says. “You have to consider tailoring different messages and changing how you send these messages to different groups.” 

That speaks to Bicchieri’s final point: In communication, showing what people actually do far outperforms telling what they approve of. Describe a person who has accepted the lockdown and follows social distancing rules, for example, and most people will infer such a person approves of these behaviors. That same inference doesn’t happen when someone is simply described as supporting the measures. “Words and deeds are different,” Bicchieri says. “We may approve of something and yet still be tempted not to do it. But if we do something, we tend to approve of it.” 

Future work in this realm will consider whether gender, income, or level of instruction matter in eliciting behavior change. “We live in a world so globalized that pandemics will happen more than once,” she says. “We have to be prepared to try to change people’s behaviors. There is a lot of work to be done.”

By Michele Berger

Fall/Winter 2020

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Changing Social Norms in the Time of a Pandemic

Psychological research tells us how to change social norms and save lives..

Posted March 18, 2020 | Reviewed by Gary Drevitch

Within hours of planes crashing into the World Trade Center on 9/11, the government took fast action. All flights were grounded and the president, police commissioner, and mayor of New York issued regular, factual and clear updates. When the airports did open two days later, immediate changes were implemented, signaling that these were new times.

Unfortunately, the coronavirus pandemic doesn’t have the features that naturally lead to rapid social change, like a sudden crisis with unmistakable consequences. The number of cases in the United States appears relatively small, which makes it harder for people to take it seriously. It also means most of us don’t yet know anyone who has tested positive – or worse, died.

Reports from other countries have given us a glimpse of how quickly the virus spreads, but it’s psychologically very hard for us to play out hypothetical future scenarios that require difficult changes now. We tend to focus on the here-and-now, so playing out what the world may look like in two to four weeks isn’t easy. This cognitive limitation explains why most of us have trouble prioritizing long-term consequences over short-term gain. It's why we fail to keep our New Year’s Resolutions and have trouble saving for retirement .

All of these factors are magnified for young people. Teenagers and young adults are especially likely to prioritize short-term rewards over long-term consequences, which explains why so many continue to vape even as growing evidence comes out about the serious health consequences. Their propensity for risk-taking and strong desire to fit in leads teens to engage in risky behavior, especially when they are with their peers. This helps explain the many photos of young people hanging out in crowded bars and restaurants, despite the growing awareness that this is precisely how the virus spreads.

Not everyone is embracing the new normal, but we need to, quickly. Psychology research fortunately provides several important insights as to how we can change social norms, fast, to reduce the spread and severity of this pandemic.

First, it is important to realize that one person can make a difference. Each of us individually can feel powerless in the face of this pandemic, but just a single person practicing social distancing matters. You’ve probably seen the picture circulating on social media of a row of burning matches followed by one match moving away – which then protects the unlit matches from catching fire. So your own individual choice – to limit grocery store runs, or to refuse to host playdates – can and will make a difference.

Second, widen the in-group. We are far more willing to help those we know—or feel connected to—than anonymous strangers. That explains why many people weren’t particularly concerned about the virus when it appeared to be confined to China, South Korea, or Iran. Broadening how we think about our connections to others—focusing on our own older relatives or friends with underlying health conditions—can help us overcome the ingrained human tendency toward inaction.

Third, role models of all types—not just political leaders but also celebrities and sports stars—should actively be pushing for behavioral change . NBA star Steph Curry posted a video to social media encouraging social distancing, which may help with adolescents and young adults. As Golden State Warriors coach Steve Kerr says, “Everyone has to understand that every individual can play a role in this and that’s the only way it’s going to work to shift the momentum of what we’re facing.”

Research by Damon Centola at the University of Pennsylvania suggests that large-scale social change doesn’t require the support of the majority. If only about 25 percent of people in a group take a stand, that is enough to create a tipping point that can relatively quickly lead to the establishment of a new norm. A small but vocal minority can change what’s seen as socially expected, whether it’s bumping elbows instead of shaking hands or staying home instead of going out.

We don't need everyone to immediately adopt new norms. What we need is for enough of us to do so. If 25 percent of us change our behavior—and publicize making this change to friends, neighbors, and family members—we can shape social norms more broadly.

So here's my request to all who read this: Follow recommended guidelines from the CDC and other public health experts. Wash your hands. Practice social distancing. Stay home. But what's equally important is that you share this choice with others in your social network , by email, Facebook, Twitter, and Instagram.

Because in this case, changing how we go about our daily lives can save lives.

Catherine A. Sanderson, Ph.D., is the Manwell Family Professor of Life Sciences (Psychology) at Amherst College.

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In Their Own Words, Americans Describe the Struggles and Silver Linings of the COVID-19 Pandemic

The outbreak has dramatically changed americans’ lives and relationships over the past year. we asked people to tell us about their experiences – good and bad – in living through this moment in history..

Pew Research Center has been asking survey questions over the past year about Americans’ views and reactions to the COVID-19 pandemic. In August, we gave the public a chance to tell us in their own words how the pandemic has affected them in their personal lives. We wanted to let them tell us how their lives have become more difficult or challenging, and we also asked about any unexpectedly positive events that might have happened during that time.

The vast majority of Americans (89%) mentioned at least one negative change in their own lives, while a smaller share (though still a 73% majority) mentioned at least one unexpected upside. Most have experienced these negative impacts and silver linings simultaneously: Two-thirds (67%) of Americans mentioned at least one negative and at least one positive change since the pandemic began.

For this analysis, we surveyed 9,220 U.S. adults between Aug. 31-Sept. 7, 2020. Everyone who completed the survey is a member of Pew Research Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories.  Read more about the ATP’s methodology . 

Respondents to the survey were asked to describe in their own words how their lives have been difficult or challenging since the beginning of the coronavirus outbreak, and to describe any positive aspects of the situation they have personally experienced as well. Overall, 84% of respondents provided an answer to one or both of the questions. The Center then categorized a random sample of 4,071 of their answers using a combination of in-house human coders, Amazon’s Mechanical Turk service and keyword-based pattern matching. The full methodology  and questions used in this analysis can be found here.

In many ways, the negatives clearly outweigh the positives – an unsurprising reaction to a pandemic that had killed  more than 180,000 Americans  at the time the survey was conducted. Across every major aspect of life mentioned in these responses, a larger share mentioned a negative impact than mentioned an unexpected upside. Americans also described the negative aspects of the pandemic in greater detail: On average, negative responses were longer than positive ones (27 vs. 19 words). But for all the difficulties and challenges of the pandemic, a majority of Americans were able to think of at least one silver lining. 

Both the negative and positive impacts described in these responses cover many aspects of life, none of which were mentioned by a majority of Americans. Instead, the responses reveal a pandemic that has affected Americans’ lives in a variety of ways, of which there is no “typical” experience. Indeed, not all groups seem to have experienced the pandemic equally. For instance, younger and more educated Americans were more likely to mention silver linings, while women were more likely than men to mention challenges or difficulties.

Here are some direct quotes that reveal how Americans are processing the new reality that has upended life across the country.

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Adapting to change: How has COVID-19 affected people’s work and personal goals?

Laura m. vowels.

School of Psychology, Life and Environmental Sciences, University of Southampton, Southampton, United Kingdom

Rachel R. R. Francois-Walcott

Katherine b. carnelley, emily l. checksfield, associated data.

All data, materials, and related manuscripts are available on the Open Science Framework: https://osf.io/qr7cm .

COVID-19 has had a devastating impact on the global economy and affected millions of people’s work and personal lives across the world. The purpose of the present study was to better understand how individuals’ work and personal goals have been affected by the pandemic and how they have adapted to these changes. We conducted qualitative semi-structured interviews ( n = 48) and surveyed participants ( n = 200) weekly for 5 weeks. Both methods revealed similar themes regarding the adaptation and pursuit of goals (social support, handling unpredictable situations, logistics, solving problems creatively, goal postponement, and no changes). Survey responses also showed that most individuals experienced their goals as more difficult (79%; 13% easier; 9% no change) and found that many had had to adapt or postpone their work and personal goals, often due to logistical difficulties. Businesses and governments should do more to help individuals adapt their goals to the new circumstances.

Introduction

The COVID-19 pandemic has had a devastating impact on the world economy, affecting millions of people’s working lives and careers globally. In 2020, The World Economic Forum [ 1 ] forecasted that the pandemic would cause the worst global recession since World War II with global unemployment expected to rise to its highest level since 1965. Indeed, global working hours reduced by 8.8% in the fourth quarter of 2020 (the equivalent of 255 million full-time jobs), and worldwide employment losses increased by 114 million jobs relative to 2019 [ 2 ]. In order to curtail the spread of the coronavirus, most countries imposed social distancing measures including working from home, school closures, and avoiding social situations [ 3 ]. Therefore, even the people who have been able to keep their jobs during the pandemic are likely to have experienced changes to how they work.

Furthermore, working remotely from home can lead to a gradual blurring of lines between work and family [ 4 ]. At the same time as adjusting to working from home, many couples have had to balance childcare and home-schooling responsibilities due to school closures. Because undertaking multiple role transitions can be challenging, the impact of these changes cannot be underestimated [ 5 ]. Simultaneously, social distancing measures have meant that individuals have fewer opportunities to replenish their emotional and cognitive resources that have been depleted by work and family demands [ 6 ]. This may result in underperforming both at work and in one’s personal life and can result in exhaustion, stress, and burnout [ 7 ].

Little empirical evidence exists currently on how the pandemic has affected individuals’ ability to complete tasks and goals at work and in their personal life, and how individuals and families have adapted to changes in circumstances. A poll of 180 employees found work-life balance and productivity had improved whereas work morale and motivation had decreased since the pandemic [ 8 ]. Another UK poll of 1,500 business owners and staff found that 53% of respondents believed they or their employees were more productive and had better mental health while remote working [ 9 ]. While this research provides some understanding of how the pandemic has affected productivity, it does not address change over time or whether the pandemic has impacted goals beyond work productivity. In the present study, our aim was to add to this literature by studying the impact of the pandemic on goal adaptation over a period of five weeks using a combination of methods (qualitative semi-structured interviews and open-ended survey responses). Specifically, we examined how the pandemic affected individuals’ work and personal goals (e.g., education, health, leisure) and how individuals adapted to the new circumstances.

A number of theories on self-regulation and goal pursuit exist. Examples of these theories include the multiple resource allocation model [ 10 ], task goal theory [ 11 ], and social-cognitive theory [ 12 ]. A common thread among all of these theories is the description of a dynamic and cyclical self-regulation process by which individuals set goals, allocate resources to pursue and maintain these goals, seek feedback from others, evaluate progress, and adjust their goals as needed [ 13 ]. In the current research, we would expect to find that participants have regulated and adapted their goals during the pandemic in ways that are reflective of the cyclical self-regulation process described by Vohs and Baumeister [ 13 ]. For example, the new changes to people’s work and personal lives will likely have led to a reallocation of resources to maintain current goals, while changing circumstances will have led to the formation of new goals and the alteration or abandonment of others. It is also likely that social support and feedback from others will have become increasingly important for effective goal adaptation and pursuit, due to the new norm for many of working remotely.

Goal adaptation itself can be defined as an individual altering a pre-existing goal and their pursuit of it, particularly in response to a change in circumstances outside of their control [ 14 ]. According to goal-setting theory [ 11 ], individuals set themselves specific and challenging goals, and then aim to achieve them. However, if an original goal suddenly becomes unattainable, for example, due to a change in circumstances, the individual may be required to adapt their goal and how they continue to pursue it. Goal adaptation is an effective means of self-regulating one’s goals, and can include strategies such as reprioritization, goal postponement, and in the case of unattainable goals, goal disengagement [ 14 ].

Adjusting goals (including changing, stopping, or starting goals); reallocating resources across multiple simultaneous demands; and adjusting expectations on progress, may be particularly important during the pandemic, given the changes to people’s work and personal lives. For example, many people are having to adjust how they complete work-related tasks because access to support from colleagues or required technology may not be readily available. Some have lost their employment and have a new goal of applying for jobs. Yet others may have to reallocate resources to particular goals such as housework, childcare, and work given the increased demands across these areas. Given these new challenges that many individuals are facing in the pursuit of their goals, it is important to explore how individuals adapt their goals within the context of this new environment, particularly since the sustained pursuit of these projects has been shown to significantly enhance psychological wellbeing [ 15 , 16 ].

Previous research into goal pursuit in the context of COVID-19 has explored the impact of the pandemic on the pursuit of personal goals [ 17 ]. The study found that, over a ten-day window during the early period of the first lockdown, individuals experienced a significant drop in their self-efficacy beliefs for goal achievement compared to retrospective pre-pandemic ratings. Over a quarter of the participants were no longer pursuing, or were unsure about continuing to pursue, their current goals despite nearly 90% of people reporting that they still cared about their goal. The study provided an important “snapshot” of how COVID-19 has disrupted pursuit of personal goals.

The current study

Our current research aimed to extend Ritchie et al.’s [ 17 ] study by examining how individuals adapted their goal pursuit over a longer period (five weeks) during the initial lockdown. The present research also focused on both the pursuit of personal goals as well as work goals, to shed light on adaptability for both types of goals under the new circumstances. This is particularly important considering the preponderance of individuals working from home during the lockdown, a circumstance which puts their work and personal goals into closer proximity. We also conducted semi-structured interviews to provide further insight into how the pandemic affected goal pursuit and how individuals adapted to the new circumstances. Specifically, we asked participants to report how their goal pursuit had changed as a result of the pandemic and how they had adapted to these changes. Some participants were interviewed about their experiences and some were surveyed weekly over five-weeks. We collected data from individuals currently living with their partner as they were likely to experience work and family conflict and were thus having to adapt their performance across multiple domains (work, family, hobbies).

Participants

Survey (n = 200, with an attrition rate of 8.5% at the end of the five weeks) and interview participants (n = 48) had similar demographic characteristics (see Table 1 ). Participants were 36 years old on average and had been in a relationship for 11 years. The samples were primarily white, heterosexual, and from the United Kingdom. Across both samples, around half the participants were married and half cohabiting, and half of them had children. About 25% of the samples reported that their employment status had changed as a result of the pandemic: seven participants reported that they had been furloughed, 26 had had to stop working, and eight said their workload had reduced. Most participants were now working from home compared to 31% who would normally work from home. Only a minority were keyworkers. Keyworkers are considered critical during the coronavirus pandemic, for example, healthcare, supermarket, and teaching staff.

The data were collected as part of a larger concurrent mixed-methods study and the number of study participants were chosen based on the requirements for that study. The data, code, and materials for the project can be found here: https://osf.io/qr7cm/?view_only=365bf35f7ddd45548143b851e10cfcd9 . Ethical approval was obtained from the authors’ institutional review board. Participants consented to participate in the study, and they were told that their participation was entirely voluntary and their responses would be kept confidential. Survey data were collected via Prolific, an online participant recruitment website, and qualitative interviews were based on a convenience sample recruited via social media. Participants were eligible for the study if they were 18 years old or above and living with their romantic partner in a country where social distancing measures were in place at the time of the baseline survey. Participants recruited through Prolific received up to £6.70 if they completed all follow-ups. Qualitative interview participants were entered into a raffle to win one of two £30 Amazon vouchers after the first interview and one of two £20 Amazon vouchers after the second interview.

Participants completed a survey weekly for five weeks via a survey platform Qualtrics. Participants also completed a daily diary for the first week but these data are not used in the present report as we did not ask how the goals were being affected on a daily basis. The first survey was completed on 31 st March, 2020, which was shortly after many countries had gone under lockdown, and included additional baseline demographic questions. Participants were also asked if they had experienced coronavirus symptoms in the past two weeks at baseline and whether anyone was currently experiencing symptoms at each follow-up. In all surveys, we asked participants questions about their relationship and goals. The questions relevant to this study were: “Please list up to 3 tasks or goals you worked on in the past week.” and “Briefly describe how your goals and how you pursue them have been affected by the pandemic.”

The semi-structured qualitative interviews were conducted via Zoom and audio recorded. Interviews were conducted by the first author. The recordings were then transcribed using an artificial intelligence transcription service and edited by research assistants. The semi-structured interview questions were selected based on the requirements for the larger study which focused on romantic relationships and personal goals during the pandemic. The selection of the questions was based on theory and previous research. We asked participants a range of questions about their relationship and goal pursuit during the pandemic; the following question was the most relevant to the present study: “How has working toward goals and tasks changed as a result of the pandemic?” Participants were prompted further to describe how goal pursuit had gotten better or worse and how they had adapted. We also used data from other questions regarding participants’ relationship where goal pursuit was also mentioned (The full interview guide is provided on the OSF project page). All first interviews were completed between 30 th March 2020 and 21 st April 2020. Participants recruited via Prolific were given an opportunity to also participate in the qualitative interview. A total of 48 participants completed the first qualitative interview (30 were recruited via social media, 18 via Prolific who participated in both survey and interview parts of the study). We invited participants who had completed the first interview in the first two weeks of the qualitative data collection ( n = 23) to participate in the follow-up interview to better understand how goal pursuit had changed during the course of the lockdown. Nineteen participants completed the second interview. The initial interviews lasted between 14–49 minutes and second interviews between 7–24 minutes.

Data analysis plan

The qualitative interviews were analyzed using reflexive thematic analysis [ 18 , 19 ] and completed using NVivo 12.0. The authors utilized a combination of inductive and deductive approaches to coding by using previous literature and theory to guide coding but allowing for new codes to be created throughout the coding process. The first and second author coded the interviews; both familiarized themselves with the data before creating the initial codes. Codes were then refined iteratively by the two coders and the final themes were agreed jointly. Any disagreements regarding the classification of codes were discussed until 100% agreement was reached. ‘[…]’ was used in the quotes if unnecessary detail was removed or to provide needed additional information in the quoted data provided. Repeated filler words such as ‘like’ and ‘yeah’ were excluded to aid readability. Identifying information was removed.

Content analysis [ 20 ] was used to analyze the open-ended questions from survey responses. The codes were created based on the qualitative interviews and were divided into no change, goals more difficult, goals easier, and productivity changed. Two trained coders coded the responses. In order to assess inter-rater reliability, 30% ( n = 299) of the codes were coded by both coders. The inter-rater reliability (weighted Cohen’s Kappa) between the coders indicated almost perfect alignment for main codes (.85) and substantial alignment for sub-codes (.74; [ 21 ]). Any discrepancies or questions in the coding were discussed to ensure consistency among coders.

Thematic analysis of interviews

A total of six themes (social support, handling unpredictable situations, logistics, solving problems creatively, goal postponement, and no changes) were identified and are described below with additional representative quotes for each theme presented in Table 2 . A total of six sub-themes were identified: four within handling unpredictable situations and two within logistics.

Social support

Many participants demonstrated and noted a change in social support due to the pandemic. For most participants this had been a positive change: they reported having increased feelings of supportiveness and understanding which they noted had been reciprocated by others: “everyone [being] a lot more understanding about work being completed […] with delays or needing more time to do things. Just because it’s really difficult to be at work and you have distractions” (#45, W, 30). In turn, many participants who had initially felt stressed managing home life and childcare mentioned this increased feeling of understanding, changed their own and others’ behaviors to being more open-minded, and sought more feedback from others. For example, one participant noted that “there’s been a lot of online support and sort of tips coming from other people when it comes to everything children related. So, that has been really good” (#29, W, 32).

Many participants additionally mentioned the support from their partner had changed as they developed a new working relationship to allow them both to achieve work goals. As such, many participants noted they had received encouragement and motivation from their partner and were also able to provide this encouragement back. For example, “having my husband here when he’s also working on things like college work or a bit of housework, that sort of thing, then doing it at the same time, it just feels nice to have some company and it helps motivation.” (#8, W, 30) Thus, some participants stated working from home was beneficial to their work goals as they were able to have their partner as their colleague.

Conversely, many participants identified that the lack of social interaction had made them feel lonely and had created difficulty in completing work. Such difficulty in reaching work goals during the pandemic, despite having a partner who worked from home or liaising virtually, was typically attributed to the sheer differences in the number of people they were able to interact with. For example, one participant noted they “have come from interacting with 300 people in a day. Now one.” (#38, M, 33) As such, many participants felt isolated and struggled to adapt to working in a less social setting. Additionally, this lack of social interaction went further than participants feeling isolated and alone but for many participants it practically deterred achieving work goals. For example, one participant remarked that “it’s a lot more isolating, because I’m used to working in a shared office and having friends and colleagues around and being able to work alongside the people or be bouncing ideas off each other as we’re working” (#46, W, 31). As such, some participants noted that it was difficult to achieve work goals as they were unable to receive continuous feedback: the virtual team dynamic did not create a suitable environment to truly work with their colleagues thus interfering with goal completion.

Handling unpredictable situations

A total of four sub-themes ( future orientation , self-care and wellbeing , productivity , time management ) were identified within this theme. This theme was noted by the majority of participants and highlighted the impact of participants’ feelings on their work goals. Many participants identified an increase in negative feelings due to the unpredictable nature of the pandemic, such as feeling demotivated, stressed, frustrated, and in some cases “feeling like everything was beyond [their] control” (#18, W, 32). Conversely, this unpredictability had been positive for a few participants as they noted feeling more at ease and less pressured as the pandemic had allowed them to “carry on living in the moment and not worry too much about the future or the past” (#43, W, 75).

Behaviorally, positive feelings toward unpredictability led to goal changes in terms of self-care and wellbeing , productivity , and time management . An increase in motivation and focus led some participants to consider self-care and wellbeing as the pandemic had emphasized the importance of health. For example, one participant stated “A lot more prioritization of sort of self-care, don’t completely lose it, goals” (#5, W, 36) had become important. This reprioritization was not limited to self-care and wellbeing but also included participants starting new businesses or courses. For example, one participant said “I have time [to do] lots of things that I didn’t have time for. For example, I started to learn the guitar. The online courses also I’ve been wanting to do for a long time and I’m quite happy I have the time to spend on it now.” (#20, W, 29). Furthermore, participants additionally noted they were more productive as they felt less pressured to complete and pursue tasks; this was caused by a reduction in work interactions and generally feeling more relaxed at home. As such, participants often did not create new goals but the pandemic had allowed participants to refocus and dedicate time to pursuing goals they had previously been unable to.

Conversely, many participants identified negative feelings such as demotivation due to the unpredictable nature of the pandemic which practically impacted productivity and the way in which they handled work stress. Many participants struggled to self-motivate and noted an increase in distractions that made it difficult to focus on goals. For example, one participant said that “I think not having a reason to, like get changed and do the little things makes it a lot more difficult for me mentally to be motivated to do anything.” (#37, W, 19). As such, many participants noted they were less productive on work goals than they had previously been.

While most participants focused on the here and now, some participants had become more future oriented : this was evident for participants who identified both positive and negative feelings toward unpredictability. For example, some participants noted they felt that “thinking about what the future is gonna look like is more relevant” (#4, W, 46). Participants thus had to be somewhat flexible with their goals and make them bigger or smaller to cope with the circumstances and prepare for the future. Indeed, goals that had once been placed on the backburner were at times placed at a forefront to allow participants to better prepare for the future. As such, participants began to consider the financial and emotional implications of the pandemic. For example, one participant stated, “So financially, I might have to change a couple of things around until I’m back into work full-time” (#28, M, 28). A change in perspective from the present to the future was particularly notable in the follow-up interviews as participants noted a variety of changes such as pregnancy and job allocation and security. Indeed, some participants noted they had been unable to secure a new job as “there’s less jobs out there and people are less willing to hire” (#12, W, 26). Therefore, many participants were having to reconsider their future job prospects in light of the pandemic. Some participants additionally noted within the follow-up interviews that they considered the future alongside their partner and their partner’s goals. For example, one participant noted the pandemic had “made us think about goals a little bit, kind of future-orientated, both individually and together” (#11, W, 36).

Two subthemes ( physically oriented adaptability and learning new tasks and technologies ) were identified within logistics. Many participants mentioned they had to make new practical arrangements in order to complete their tasks and goals. A new reliance on online formats or balancing homeschooling and work were logistical changes commonly mentioned. Many participants thought these new arrangements to be necessary in pursuing goals, thus they rarely appeared fazed but noted it to be an adjustment as they were “getting used to it and kind of figuring it out” (#5, W, 36). Some participants demonstrated physically oriented adaptability regarding work-space and creating a suitable work environment. For example, one participant stated, “What I went ahead and did with the help of my partner was set up. Like I had a desk at home, we didn’t really use it. So, I went ahead and set it up for more effective […] productive use so it’s similar to how my office is.” (#3, W, 26) Indeed, rearranging or creating work-spaces was mentioned by a few participants as being necessary in achieving work tasks and goals. Therefore, many participants commonly mentioned that they were able to continue pursuing goals through practically adapting to their new circumstances. Nonetheless, some participants additionally noted how the implications of working from home slowed down goal achievement. Many participants mentioned they felt frustrated and challenged by inadequate practical arrangements such as “quite slow internet” (#40, M, 33). As such, it was noted to be harder to efficiently complete goals than it had been prior to the pandemic. In such instances, some participants were able to overcome these difficulties and continue completing tasks and work goals whereas for other participants this was not possible, leading to goal postponement .

Furthermore, for instances in which participants were able to overcome logistical difficulties this was also achieved through learning new tasks and technologies including online exams, podcasts and virtual team software with many commonly noting this adjustment to be “challenging” (#11, W, 36). For example, one participant stated “I’ve had to move my courses online. […] I can’t deliver exams in class settings, so I’ve spent a lot of time trying to develop online, multiple choice tests, which I wouldn’t have used […] that’s been challenging” (#23, W, 49). Furthermore participants additionally noted that the new formats had been challenging and caused disruptions due to external factors such as “a lot of professors [struggled] with the online format” (#37, W, 19). Some participants who were currently studying noted that as they relied on their professor to deliver the material, it made the completion of tasks more difficult when their professor was struggling with the technology. Therefore, learning new tasks and technologies was noted to be disrupting to work goals as the participants themselves struggled or had been impacted by those who struggled.

Solving problems creatively

A few participants noted that although the pandemic had created challenges, they had been able to creatively address these and adapt their goals accordingly. This allowed them to ‘think out of the box’ and achieve their work goals in a new manner. For example, one participant noted they “quite like[d] the challenge and use[d] it as an opportunity” (#11, W, 36). Some participants thus put a positive spin on the pandemic and the new opportunities it could create. Few participants explicitly noted they had foreseen and solved potential work-related issues. Nonetheless, one participant stated, “I think the focus of my work has changed quite a lot. Most patients are not wanting therapy, most people are wanting to put on hold. So actually, my focus has been a lot more kind of strategic and planning and preparing for what’s to come. Because I think, in community mental health, we’re getting a calm before the storm” (#18, W, 32). However, preventing the occurrence of problems was at times implicitly mentioned by participants in teaching professions who noted that they had to switch to online formats for learning and exams. In this regard, an overlap was present between solving problems creatively and learning new tasks and technologies.

Goal postponement

About half the participants mentioned that their goals had to be postponed or cancelled. Most noted this was due to factors outside of their control such as being unable to go on holiday, an inability to pursue work goals, or because of uncertainty about how long the pandemic is going to last and what the world will look like post-pandemic. As such, this theme somewhat overlapped with logistics as some participants noted where it was not possible to complete goals from home, goals were postponed. Some participants were unable to find jobs with one participant noting, “there aren’t many vacancies right now… I’ve received emails saying that they’ve closed so they’re no longer considering applicants or that they’re closing the vacancy” (#12, W, 26). Some participants found this postponement led to changes at work and found that “work is a lot less busy” (#13, M, 31) and they were unable to complete particular tasks and goals.

While almost all participants described that their goal pursuit had changed in some form, a few participants noted no change to goal pursuit regarding the ease of completing goals or creation of goals. For example, one participant said “I think it’s the same it’s just a strange feeling working from home but it’s not harder” (#10, M, 42) and another stated that “nothing much has changed” (#30, W, 39).

Content analysis of survey responses

We used the themes from the qualitative interviews to guide coding of the open-ended responses. There was not much variation between the codes across the five weeks. Therefore, instead of presenting the responses for each week, we report the aggregate scores across the five weeks (A breakdown of results by week can be found as supplemental material on the OSF project page). The sample of 200 participants provided responses up to five times over the study period. This resulted in a total of 948 responses that were coded into the main codes, with a minority of the responses not being codable (n = 47, 5.0%). The codes were first divided into three categories based on whether goals had become more difficult ( n = 880, 78.64%), easier ( n = 142, 12.69%), or had not changed ( n = 97, 8.67%). The responses were further divided into five specific codes. Many participants reported that goals had become more difficult due to logistics ( n = 276, 29.27%), decline in productivity ( n = 243, 25.77%), and difficulties with time management ( n = 60, 6.36%). Some participants reported that they had adapted their goals in some way ( n = 170, 18.03%) or they had had to postpone or stop their goal pursuit ( n = 80, 8.48%). The only way in which participants reported their goals had become easier was due to having more time to pursue goals ( n = 114, 12.09%). Similar themes were found within the specific codes as in the qualitative interviews. Adapting goals included elements from interpersonal adaptability, handling unpredictable situations, and solving problems creatively but these were difficult to differentiate in the open-ended responses.

The COVID-19 pandemic has affected people’s working and personal lives across the world with millions of people losing their jobs and many more facing significant challenges [ 22 ]. In the present study, our aim was to understand how the pandemic had affected individuals’ work and personal goals and how individuals have adapted their goal pursuit to match the challenging circumstances over time. We examined our research questions using two different methods: semi-structured interviews and open-ended survey responses over five weeks. Using multiple methods allowed us to gather in-depth information into how individuals had adapted their goal pursuit and to quantify any changes over time. With the pandemic being an unprecedented event, a more nuanced understanding of the participants’ experiences was especially important, and since prior research into COVID-19 and goal pursuit [ 17 ] has only employed the use of survey responses, the inclusion of semi-structured interviews allowed for a more in-depth exploration of the phenomenon.

Previous research has stated that in order to cope with new circumstances, individuals and organizations must be able to adapt quickly to respond to changes in demands [ 23 , 24 ]. Nearly 80% of the survey participants and the majority of interview participants reported that their goal pursuit had become more difficult. For example, in line with early research into the pandemic [ 8 , 9 ], a quarter of the participants noted changes in motivation that caused them to become less productive, including having more distractions and a lack of motivation. However, many participants had been able to successfully adapt some of their goals.

We found that logistical challenges were the most commonly reported issue affecting goals during the pandemic. Most participants noted that they had been adapting to these challenges through physically creating workspaces or learning new technologies. A few participants noted technology such as poor internet had made goal progress harder with some additionally identifying their company technology was not sufficient. Many participants also identified perception of social support to have changed, as they were more understanding and supportive of their colleagues and had such feelings reciprocated. Participants who were unable to receive sufficient contact with their colleagues noted they felt lonely and found it practically difficult to complete work without feedback from others. This evidence reinforces the importance of social support in pursuing goals [ 25 , 26 ]. Problem solving creatively was rarely mentioned: it was however identified by those in teaching professions who were required to quickly adapt to provide sufficient resources to students.

While most participants reported that goal pursuit had become more difficult, around 13% of the survey participants as well as some interview participants reported that goal pursuit had become easier, usually because they had more time to work on goals. Some participants had also altered their focus from work-related tasks to pursuit of self-care and hobbies. A minority of the participants said that there was no change in goal pursuit, which may reflect the fact that some participants already worked from home before lockdown or that they engaged in goal pursuits that were possible to do even during lockdown (e.g., going on walks, eating healthily). Furthermore, we did not find evidence of change over time. Instead, most participants reported that they experienced similar challenges to goals over the course of the five weeks. Some participants did mention a shift to more future-related goals in the second interviews than at the start of lockdown.

The themes identified within this study are broadly similar to those reported in Ritchie et al.’s [ 17 ] study. In particular, awareness of the importance of social support, future-oriented planning, and an enhanced focus on self-care were found in both papers to be features associated with continued goal pursuit during the pandemic. This suggests that these strategies have been important during the pandemic for enabling continued goal pursuit. Our findings build on Ritchie et al.’s [ 17 ] in that we identified themes, problems, and strategies specific to the pursuit of work-related goals and work-life interactions in addition to solely personal goals. For example, physical logistics was identified as a major barrier to effectively working from home, and the role of partners and colleagues was emphasized in supporting participants to adapt to new ways of working during the pandemic.

Regarding personal goals, the lockdown saw many individuals create new goals surrounding self-care and wellbeing, perhaps due to an increased awareness of health from the pandemic. Meanwhile, other pre-existing personal goals, which had previously been superseded in priority by work goals, were now able to be pursued during an increased amount of free time. The exploration of both work and personal goals during the lockdown showed that the line between the two types of goals became blurred: new personal goals such as homeschooling and childcare became prerequisites for being able to complete work goals, and reduced time spent on pursuing work goals meant increased time available to pursue new personal goals.

Overall, while COVID-19 has impacted everyone, some participants were better able to effectively adapt their goals to the situation, while others have been forced to postpone and even abandon their goals. These findings are consistent with previous research on self-regulation and goal pursuit, with the processes used by participants to adapt their goals being reflective of Vohs and Baumeister’s [ 13 ] description of dynamic and cyclical self-regulation of goals. For example, goal pursuit was maintained for some by reallocating resources in the form of rearranging the home to become a workspace, while many have sought increased support and feedback on their goals from their partners and colleagues. Where further goals were evaluated as unfeasible due to the changing circumstances, they were often postponed or abandoned. Together this creates a picture of how individuals have effectively regulated their goal pursuit during the pandemic.

Limitations and future research

The present study had several strengths. First, we combined two different methodologies: semi-structured interviews and open-ended survey responses. By combining these methods, the study benefited from the generalizability of a larger and more representative dataset and the nuanced and detailed description of participants’ experiences in the interviews. Participants also began completing the surveys from the beginning of many countries’ stay-at-home orders effectively capturing the first month under lockdown, arguably a time that demanded a great deal of adaptation.

However, the study also had some limitations and results should be interpreted with these in mind. Participants were recruited via Prolific hence we potentially captured data from those who had more time available during the pandemic. Short-term and long-term impact of the pandemic may vary [ 27 ]. However, our study focused on the first five weeks only and did not show change during this period. Moreover, the current study did not address whether successful adaptation in goal pursuit was associated with better outcomes (e.g., higher job performance) long-term. Therefore, future research is needed to investigate the long-term impacts of the pandemic on goal outcomes. Furthermore, while we examined how goals were affected over time, we did not ask how different types of goals (e.g., work or personal goals) may have been affected differently. It is possible that, for example, individuals’ work-related goals have been negatively affected by the pandemic whereas leisure goals may have been positively affected due to having more leisure time. This idea was largely consistent with the qualitative interviews but future research is needed to examine quantitatively whether this is indeed the case on average. It is also possible that some of the changes to goal pursuit were due to factors other than the pandemic (e.g., poor goal-setting skills, job security, mental health issues) even though participants had identified the pandemic as the reason for the changes. Furthermore, due to the speed with which the virus spread in the first few months and its unprecedented nature, it was not possible to gather pre-pandemic data from participants. We began data collection in the first few weeks of most countries’ lockdowns but the reports of how participants’ goals had changed and how they had adapted rely on participants’ retrospective accounts only. There may be ways in which it is possible to investigate how goals have been affected using available data from before, during, and after the pandemic such as work output, student grades, or census data. These possibilities should be explored in future studies to further understand the scale of the impact the pandemic has had on goals.

Practical implications

Many participants in the present study highlighted that they had had to adapt or postpone their goals due to logistical difficulties. Some of these difficulties may have been unavoidable due to widespread business closures and orders to work from home. However, there may be other difficulties that could be mitigated by employers and governments especially as stay-at-home orders ease. More employees are set to continue working from home (37%) once the pandemic is over than they were pre-pandemic (18%; [ 28 ]) As such, it is important companies address the limitations around technology such as through ensuring that their employees have adequate equipment and broadband as well as access to technological support when working from home. Workplaces should also offer guidance and training on how to adapt to the new working conditions. Additionally, as people attempt to look beyond the pandemic and become future-oriented, an increase in long-term funding or resources may be necessary. Many participants also reported that they had less access to social support and colleagues at work which made them feel more isolated. As organizations adapt to social distancing measures, they should also invest in a virtual working environment or smaller work bubbles (i.e., small number of people working together with the same people) that allow for greater connection between team members. While the results are especially useful during the pandemic, the study has implications for other stressful situations (e.g., the evolution of organizational structures and processes, economic and political instability, and technological advances) [ 29 ] that occur more frequently that force individuals to adapt their goal pursuit. Preparing for these eventualities in advance can help mitigate their impact.

We found that most individuals experienced their goals as more difficult and had had to adapt or postpone many work and personal goals. For many participants, difficulty in goal pursuit was due to logistics and lack of social support. These difficulties could be addressed through further support by employers which would alleviate the additional stress and frustration participants noted. Thus, businesses and governments should do more to help individuals adapt their goals to the new circumstances.

Funding Statement

L.M.V. Jubilee Scholarship, University of Southampton, https://www.southampton.ac.uk/ . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder provided support in the form of salaries for L. M. V., but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.

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Change in traffic stop volume in major cities

Traffic stops declined

Philadelphia

Kansas City

New Orleans

San Francisco

–100%

Data covers the municipal police department in each city.

Traffic Enforcement Dwindled in the Pandemic. In Many Places, It Hasn’t Come Back.

The retreat has happened as road deaths have risen.

By Emily Badger and Ben Blatt

Ben Blatt and Emily Badger spent months compiling police data and interviewing police officials, safety advocates and other experts.

In the early days of the pandemic in 2020, traffic stops by the police plummeted around the country, as fewer cars were on the road and as agencies instructed officers to avoid nonessential contact with the public.

But in the months and years that followed, a distinct pattern formed in many cities: The cars came back in full force, but the traffic enforcement didn’t.

By the end of 2023, the police in Baltimore, New Orleans and San Francisco were making fewer than half the traffic stops they did prepandemic. In other police departments that don’t publicly track stops, like in Seattle and New York, the citations given during stops dropped off, too. The downturn appears even among some state agencies that monitor road safety on highways, like the Texas Highway Patrol and Connecticut State Police.

This decline, seen in an Upshot analysis of local law enforcement data, accelerated a shift that began in many places before the pandemic, suggesting that the police have pulled back from a part of their job that has drawn especially sharp criticism. To many communities, traffic stops have led to racial discrimination, burdensome fines and deadly encounters — not road safety.

But the retreat of law enforcement from American roadways has also occurred against the backdrop of a rise in road fatalities.

It’s hard to draw a straight line from the decline of enforcement to the rise of road deaths, but their likely connection has unsettled researchers, safety advocates and police officials.

“I cannot ignore that,” said Charles T. Brown, whose firm Equitable Cities has worked with communities on police reform and road safety. “That does not mean, however, that the traditional form of enforcement is necessary to reverse that trend.”

If traffic stops and road fatalities were falling in tandem — because roads were becoming safer overall, or because officers were giving fewer equipment citations while pursuing dangerous drivers instead — that would be a very different scenario.

Today’s picture suggests, rather, that as the police have responded to both the pandemic and cries for reform after the 2020 murder of George Floyd, they have also withdrawn from their role pulling over speeding cars and reckless drivers.

“When I talk to police, I say, ‘Fine, don’t focus on the paperwork issues,’” like giving tickets for expired registrations, said Ken Barone, who manages the Connecticut Racial Profiling Prohibition Project . “But that should free you up to have more time to focus on the things that are killing people. And I’m not seeing that.”

This decline isn’t universal. But it recurs across communities that differ in notable ways. Police work on traffic safety is down in Denver, which has a camera enforcement program, but also in Austin, Texas, where traffic cameras are banned by state law . It’s down in Seattle, where a severe police staffing shortage lingers, but also in Nashville, where staffing levels have been more stable.

It’s down in Los Angeles and Philadelphia, where new policies have curtailed the kinds of stops officers can make . But it’s also down in Kansas City, Mo., where there’s been no change in policy.

As American roads have grown more deadly, many people interviewed for this article blamed a breakdown in the social contract — the basic expectation that drivers will follow the rules. But reversing that will be difficult when the chief enforcement mechanism of road safety for decades in America — the traffic stop — has been a recurring scene of police misconduct.

“There’s been a lot of injustice. But there’s also an injustice when people die because of speeding drivers,” said Damian Kevitt, who founded Streets Are for Everyone , a Los Angeles road safety advocacy group, after he was pinned under a speeding car while biking in 2013. His right leg was ripped off. The driver was never caught.

Damian Kevitt blames the retreat of law enforcement for rising road deaths in Los Angeles: “It’s not like we suddenly designed more dangerous roads. Like, what changed?”

Montinique Monroe for The New York Times

Today, he is certain of this: “People are dying because there is at this point relatively no enforcement of traffic laws in the city of Los Angeles.”

Prepandemic, the Los Angeles police were making more than 500,000 traffic stops a year. In 2023, they made fewer than 220,000 .

A broad retreat

The downward pressure on traffic enforcement has come from every direction — the public and the police themselves, reformers and critics of reform.

“There is a kind of Right narrative and a Left narrative, and they actually converge, which is that there’s just less political support for traffic enforcement,” said Greg Shill, a law professor at the University of Iowa. “You can see that as: ‘Cops need to get home safe, and they’re afraid of being wrongly labeled as abusive or racist.’ Or you can see it as: ‘Civilians have asserted more control over police departments.’”

This dynamic has roots well before the pandemic.

The police have become less visible on roads in many cities.

Stella Kalinina for The New York Times

Public data tracking traffic stops, often mandated locally by laws meant to identify racial bias, covers only recent years in many places. And many cities and states publish no information.

But a longer-term decline of enforcement appears elsewhere, too. Since about 2010, D.U.I. arrests have fallen in F.B.I. crime data (with no comparable decline in alcohol-related fatalities). And the share of Americans who say they have been pulled over has fallen since at least the late 1990s in a periodic federal survey tracking contacts between the police and the public. That share has dropped in particular since 2015, after the police shooting death the prior year of Michael Brown in Ferguson, Mo.

“The decline in traffic enforcement predates Ferguson by probably 10 years or more — that’s an important thing,” said Jeff Michael, a former longtime official at the National Highway Traffic Safety Administration who now studies road safety at Johns Hopkins University. “But Ferguson certainly had an effect. That’s without a doubt. Ferguson, and everything after.”

That is apparent in Ferguson itself, among some other cities.

That downturn comes from two sources — orders from on high and individual officers on the street — that can be hard to untangle.

First, some police departments shifted guidance after Ferguson, directing officers to pursue fewer vehicle searches or nonmoving violations. Racial disparities are widest among drivers stopped for those reasons. Equipment and registration issues are also seldom associated with crashes , while stops for such infractions have been more likely to involve the use of police force .

The second force is more diffuse, as officers retreat from interactions with the public that are essentially discretionary.

“Why subject yourself to potential discipline or problems?” said Tom Saggau, spokesman for the Los Angeles Police Protective League union. “Why subject yourself to the inherent danger of engaging? Many times, officers are questioning: ‘Why am I even doing this?’”

These decisions by officers and police leaders intensified three months into the pandemic, when George Floyd was killed by a Minneapolis officer who knelt on his neck in a scene viewed around the world. Protesters rallied in hundreds of communities against discrimination and the deadly use of force. A 2021 New York Times investigation found that American police in five years had killed more than 400 drivers or passengers who were neither wielding weapons nor under pursuit for a violent crime.

In Los Angeles, the police department responded by requiring officers to record their rationale for pretextual stops — when officers use a minor violation as an opening to search for more serious crimes. Philadelphia enacted a law limiting stops for reasons like a broken taillight.

In data from this era, it’s hard to separate the effects of the pandemic from the demands for reform, or to know if policing patterns might have bounced back from the first shock had the second never happened.

“We had two great forces coming together at once,” said Scott Sophier, a commander in the Evanston, Ill., police department.

The police across several cities described the resulting period as one of “police withdrawal,” “cooling off” and confusion over what the public wanted.

“When you hear your community tell you, ‘Where are you? I need you here,’ and you hear the elected leaders say, ‘We’re going to try everything we can to protect you from the police department’ — that’s this conflicting messaging,” said Don Graham, a deputy chief of the Los Angeles Police Department.

The pandemic, the protests and calls to cut police funding also contributed to a police staffing shortage that became acute in larger cities.

Source: F.B.I. Uniform Crime Reporting police employee data. Municipal police departments only. Police force percent change adjusted for change in city size.

And when police departments are short-staffed, they cull specialty units like the traffic division to fill patrol roles. Departments described struggling with staffing during a time when 911 calls and crime were rising. Mental health calls, homelessness and illegal street racing were growing more common. So were marches and demonstrations — and traffic officers often handle those, too.

“We were in kind of a weird situation, because traffic deaths were going up,” said Adrian Diaz, who led the Seattle police department from 2020 until earlier this spring . “And then our staffing is going down. And finally crime was also going up. How do you prioritize just the violent crime, but then also recognize that traffic deaths are a huge issue?”

In 2022, he instructed officers not to stop drivers solely for minor violations like a missing front license plate. Today, in a Seattle traffic division that had about 60 officers prepandemic, there are 12 left.

The number of traffic infractions issued in Seattle over the same time fell by more than 80 percent.

Roads or racetracks?

Since the pandemic, another set of headlines has emerged. Hit-and-runs surged in Philadelphia . Washington had its highest road fatality count since the mid-2000s. In Los Angeles last year, car crashes killed more people than homicides — more than half of them pedestrians.

Patricia Strong-Fargas, a pastor in South Los Angeles who has served on a city task force reconsidering road safety, described drivers treating the roads like racetracks, the stop lights like suggestions. She has three young-adult grandsons whom she prays for daily.

“I pray they will not get involved in any officer entanglement. I pray that no gang member will attack them,” she said. “I pray that nobody runs a red light.”

Two of those three threats are intertwined because the U.S. relies, to a far greater degree than other high-income countries, on police enforcement to produce road safety.

Patricia Strong-Fargas believes reckless driving has worsened in Los Angeles since the pandemic. “Running red lights means nothing,” she said.

Many peer European and Asian countries have reduced fatalities by designing roads that discourage speeding and protect pedestrians and cyclists, while deploying cameras more widely.

The U.S. in essence uses the police to make up for not doing those things. And over time, that enforcement has become increasingly inseparable from fighting crime, with many stops serving no road safety outcome.

The degree to which that’s true varies. In Connecticut, at least 70 percent of stops are categorized as moving violations in nearly every jurisdiction in the state.

By contrast, in Chicago only about 30 percent of traffic stops in 202 3 were for moving violations. Stops there have soared in recent years, contrary to the pattern nationwide. And they started to rise after a 2015 agreement to reform the department’s stop-and-frisk practices, suggesting that the police shifted their crime-fighting stops from pedestrians to drivers.

This overall road safety strategy — beyond its costs in over-policed communities — has proved insufficient to reduce fatalities. In 2023, about 41,000 Americans died in road crashes. Those deaths also disproportionately affect Black Americans, Hispanic Americans and Native Americans, a pattern that reflects in part disparities in who lives along dangerous roads and who must walk or bike there.

For police enforcement to improve road safety, it must shift driver behavior broadly, not just the particular behavior of drivers caught with a ticket, researchers said. And they disagree over how effective the police are at doing that.

Recent history offers some evidence: The motor vehicle death rate in the U.S. dropped in the 1980s and 1990s as states adopted seatbelt laws, and as Mothers Against Drunk Driving lobbied for stricter drunken driving laws. Crucially, those laws were accompanied by aggressive police enforcement, often in the form of highly visible sobriety checkpoints and “click it or ticket” seatbelt campaigns.

Some studies have also suggested police enforcement can affect road safety . But it’s less clear that the benefits last after the police drive away . And while enforcement may have helped shift norms around seatbelts and alcohol, speeding is another challenge entirely.

To address it, other evidence suggests that enforcement and road engineering ought to work together.

Transportation planners say better road infrastructure, not just more police enforcement, will help reduce fatalities.

In the years preceding the pandemic in Burlington, Vt., traffic stops and serious crashes were declining together. That’s because while the police scaled back minor stops and vehicle searches, the city also redesigned speed humps and crosswalks, said the city’s police chief, Jon Murad.

“I believe there’s an elastic bottom to that, at which point things snapped back,” he said. And indeed during the pandemic, serious crashes rose again. “Absent enforcement, the engineering methods don’t do the job by themselves.”

Vision Zero programs , embraced by many U.S. cities to reduce road fatalities, have tried to pair police enforcement with redesigned roads and public education campaigns.

In New York, Vision Zero helped reduce road injury rates in the years leading up the pandemic. But during the pandemic, New York lost those gains , according to a study tracking injuries in Medicaid claims data. One major difference? Police enforcement plummeted, the researchers point out.

“So much of traffic safety hinges on making sure people follow the rules we’ve made for the road,” said Kacie Dragan, one of the study’s authors. “My gut feeling, from that public health perspective, is it’s a bad thing to see that decline. But that’s not the only perspective that matters.”

Two competing harms

The question before communities today is in part whether enforcement can return, stripped of the harms that have long been a part of it.

In a country with about 18,000 local police agencies — where the department culture and rate of stops vary widely — each will need an answer.

The most common policy response has been to reduce the stops that are least connected to dangerous driving — “to make certain the traffic work that is done is about traffic safety,” as Mr. Murad put it in Burlington.

But that is not uncontroversial. Police unions and Republican officials have balked at changes that would restrict pretextual stops. That has left some departments at odds with their unions , and put some more liberal cities in conflict with conservative state legislatures .

The Vision Zero movement in the U.S. has meanwhile backed away from emphasizing enforcement.

“Really long-term, design has to be the solution,” said Shawn Garcia, director of advocacy for the safe-streets organization Transportation Alternatives in New York. “Policing is not the direction we want to go in.”

Even among safety advocates, there’s no agreement on automated cameras as an alternative to the police. Studies in the U.S. and overseas show that speed cameras are effective at reducing speeds and injuries . But civil libertarians oppose the surveillance. And officials worry that cameras targeted in high-crash corridors may disproportionately ticket low-income and minority drivers , because decades of racially biased urban planning have left their communities with the most dangerous roads.

Studies have shown that automated cameras, like this one in Philadelphia, can reduce speeding and injuries. But several states ban them.

Caroline Gutman for The New York Times

Communities should also reconsider if they really need someone with a gun and a background in detecting crime to fill out speeding tickets, said Scarlet Neath, the policy director at the Center for Policing Equity .

Critics have many retorts: It’s unrealistic to redesign every dangerous road. Without pretextual stops, police will miss weapons and crime leads. And while better-designed roads or civilian responders may shape the behavior of typical drivers, they’re no match for the most reckless and distracted ones.

“There’s a whole laundry list of other things we support unarmed responses to, 100 percent,” said Mr. Saggau with the Los Angeles police union. “Mental-health calls — we’re on board. But when it comes to traffic — bad idea all the way around.”

Vulnerable cyclists and pedestrians have borne the brunt of rising road fatalities in many cities.

We also don’t know today the full consequences of reforming traffic enforcement, including for crime trends and general police behavior, said Robin Engel, an Ohio State researcher who has long studied policing.

There are other factors at play, too.

“When you have that lived experience,” said Isaiah Thomas, a Philadelphia City Council member who led the city’s reform bill, “you know how demoralizing it can be to be a participant in a traffic stop.”

Particularly a traffic stop that feels racially targeted and unrelated to safety.

At its most raw, this debate pits two harms against each other, with communities searching for a path to lessen both.

Stephanie Evans, whose son died in a hit-and-run, laments that road violence doesn’t receive the attention of gun violence. “The vehicle is a bullet,” she said of the driver who killed her son. “And when he put that vehicle in drive, he pulled the trigger.”

In Philadelphia, the Rev. Stephanie Evans lost her 37-year-old son Robert in January 2020. He was stepping out of his pickup truck when he was struck by a driver who sped away. In her grief, she has become an advocate for hit-and-run victims. To her, that means demanding more cameras — but also more of the police.

“I’m not conflicted over that,” she said, even acknowledging the damage that has come from pulling over more drivers.

“I want them stopped,” she said. “I’m sorry. It’s the lesser of two evils.”

See all cities in our data set

Methodology

All stop and citation data shown here is publicly reported by individual municipal police departments, city governments, state police agencies or state road safety organizations. Because the timeline of available data varies by place, the changes in traffic stops are calculated from the earliest to the most recent data point.

There is no national reporting standard for traffic stops, and some locales include certain criminal or investigative stops that others may exclude. We removed pedestrian and cyclist stops from the data. Some states report traffic stops as “ vehicle stops ” or “ stops ,” but we referred to them all as “traffic stops.”

There is also no national reporting standard for traffic citations. Language to describe them also varies, with some cities publishing data on “ tickets ” or “ infractions .” In our graphics, we have used the word “citation.”

Pandemic-era fatality data comes from the National Highway Traffic Safety Administration’s Fatality Analysis Reporting System . Deaths were counted for each city based on the location of crashes.