Literature DB >> 35587476

Coping with COVID-19: Differences in hope, resilience, and mental well-being across U.S. racial groups.

Carol Graham1,2, Yung Chun3, Bartram Hamilton4, Stephen Roll3,5, Wilbur Ross6, Michal Grinstein-Weiss3,5.   

Abstract

OBJECTIVES: To explore if the COVID-19 pandemic revealed differences across racial groups in coping, resilience, and optimism, all of which have implications for health and mental well-being.
METHODS: We collect data obtained from four rounds of a national sample of 5,000 US survey respondents in each round from April 2020 to February 2021. Using logistic regression and fixed effects models, we estimate the pandemic impacts on COVID-19 related concerns, social distancing behaviors, and mental health/life satisfaction and optimism for racial/income groups.
RESULTS: Despite extreme income and health disparities before and during the COVID-19 outbreak, Blacks and Hispanics remain more resilient and optimistic than their White counterparts. Moreover, the greatest difference in resilience, optimism and better mental health-is found between poor Blacks and poor Whites, a difference that persists through all four rounds.
CONCLUSIONS: These deep differences in resilience have implications for the long-term mental health of different population groups in the face of an unprecedented pandemic. Better understanding these dynamics may provide lessons on how to preserve mental health in the face of public health and other large-scale crises.

Entities:  

Mesh:

Year:  2022        PMID: 35587476      PMCID: PMC9119465          DOI: 10.1371/journal.pone.0267583

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


Introduction

The outbreak of the Coronavirus disease 2019 (COVID-19) in the U.S. exposed deep vulnerabilities in our fragmented health care system as well as the broader consequences of extreme income inequality [1]. African American and Hispanic populations, who had the greatest income and wealth inequality compared with White populations before COVID-19 also suffered disproportionately high incidence and mortality rates from COVID-19 [2-4]. Inequalities in COVID-19 incidence and case mortality rates are well documented: while Black individuals make up just 12.5% of the U.S. population, they have accounted for 23% of COVID-19 deaths nationwide [5, 6]. Similarly, case rates and mortality rates have been higher for Hispanic and Latinx individuals across the country [7, 8]. One area about which less is known, however, is the degree to which the realities of COVID-19 have impacted people’s physical and mental health, concerns and fears, and behaviors in response to COVID-19. There is reason to be concerned that COVID-19 may disproportionately impact these outcomes for racial and ethnic minorities. The disparity in the impact of COVID-19 across racial/ethnic groups occurred for several reasons, principally the longstanding untoward effects of institutional and structural racism. One notable manifestation of systemic racism is the overrepresentation of Black and Hispanic individuals in jobs deemed “essential” (e.g., in health, transportation, and service sectors), where working from home or maintaining social distancing is impossible [9]. Black and Hispanic people in the U.S. also have a higher probability of being low income and having worse access to good health care [10]. Long before the COVID-19 outbreak, these problems were exacerbated by systemic inequities in housing, health, employment, and opportunity [11, 12]. Racial and ethnic minority groups are also more likely to have comorbid conditions such as asthma, heart disease, and diabetes, all of which are risk factors for worse COVID-19 outcomes [10, 13–17]. Given such disparities, one might assume that minority and low-income populations would display greater fear of COVID-19 –potentially reflected in their social distancing and other behaviors, and the greatest losses on measures of health and mental well-being [18]. In this paper, we examine the intersection of social and economic factors that influence people’s COVID-19 health behaviors. We investigate the relationship between how these individuals are coping with the pandemic and their mental well-being, as well as the ways in which the fear of COVID-19 influences health behaviors in non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx individuals (hereafter White, Black, and Hispanic). Our findings are based on four waves of the Socio-Economic Impacts of COVID-19 Survey, fielded by a team of scholars, primarily from Washington University in St. Louis (and including these authors) and seeking to examine these issues in a diverse, national sample of U.S. adults. They reveal some surprises which include better reported mental health and well-being among racial/ethnic minorities throughout the pandemic, and complex patterns in the relationship between race/ethnicity and behavioral responses to it.

Methods

Data and sample

Data for are from the Socio-Economic Impacts of COVID-19 Survey. It is based on nationally representative survey samples from four waves of the survey, administered in late April—early May (Wave 1), late August (Wave 2), and November (Wave 3) in 2020, and March through April in 2021 (Wave 4) to approximately 5,000 nationally representative respondents in each wave, approximately half of which have repeated observations, forming a sub-set of respondents that are a panel (Fig 1). The survey relied on Qualtrics online panels developed using quota sampling techniques to ensure that the sample approximated United States demographic characteristics in terms of age, gender, race/ethnicity, and income. (Online, non-probability samples using Qualtrics panels typically generate samples that closely approximate those of the General Social Survey, which is considered the gold standard in survey administration [19]).
Fig 1

Source: New York Times (COVID-19 case), Oxford University (Vaccinations).

The survey was submitted to the Washington University at St. Louis IRB (ID: 202004100) and was approved. This was not a requirement as it is an on-line internet survey with voluntary participation, but we sought the additional approval. We received written consent. Even though it was exempt, we still got written (online) consent from all research participants before they entered the survey. The survey was also limited to adults. A copy of the most relevant questions from the 4 waves of the survey, utilized here, are in included in the supplementary materials. The data, variables, and codes can be found at this link: (https://github.com/SocialPolicyInstitute/SEICS/tree/main/PLoS-ONE). The overall response rate across four waves of the survey was 10.1%, and ranged from a low of 6.8% in Wave 4 to a high of 13.5% in Wave 3. (Response rates were calculated using the American Association of Public Opinion Research’s RR2 measure [20]). After exclusions due to quota restrictions and quality checks embedded in the survey, 22,444 respondents remained in the sample. (For the comparison between the survey sample and the ACS 2019 estimate [21], see Table 1). Additional checks on the characteristics of this sample revealed that it also approximated the U.S. population in terms of state of residence, in addition to the quotas specified above. Finally, we excluded respondents who did not provide a response to the items used in this analysis or who did not identify as White, Black, or Hispanic—the racial/ethnic populations of interest in this study—resulting in a final analytical sample of 16,680.
Table 1

Survey sample and ACS 2019 sample comparison.

Characteristic2019 ACS* (1-Year Estimates)Study sample (Wave 1 only)Study sample (Wave 1 to 4)
Age50.446.643.1
Race/Ethnicity
    White, Non-Hispanic (%)60.761.762.0
    Black, Non-Hispanic (%)12.312.212.5
    Asian, Non-Hispanic (%)5.55.35.5
    Hispanic (%)18.017.417.4
    Other (%)4.32.42.7
Male (%)48.549.647.2
Gross Annual Household Income
    Less than $25,000 (%)18.016.321.0
    $25,001 - $50,000 (%)20.422.721.7
    $50,001 to $75,000 (%)17.416.518.6
    $75,001 to $100,000 (%)12.814.413.1
    More than $100,000 (%)31.430.225.6

Notes: * We limit the sample to 18 or older.

Notes: * We limit the sample to 18 or older.

Measures

To measure life-satisfaction, optimism, and mental health, we utilized two sets of questions. The first was a standard life satisfaction question (the Cantril ladder), which asks: “Please imagine a ladder, with steps numbered from 0 at the bottom to 10 at the top. The top of the ladder represents the best possible life for you, and the bottom of the ladder represents the worst possible life for you. On which step of the ladder would you say you personally feel you stand at this time [22]?” A subsequent question asks the respondent where they think they will be on the same ladder in five years. The second question is designed to capture optimism/hope for the future in both the near-term and the long-term (for detail, see Graham et al. [23]). The second measure of well-being asks respondents two questions assessing their mental health on a five-point response scale ranging from poor to excellent. The first question asks respondents to assess their mental health three months ago. The second asks them to rank their mental health currently (i.e. at the time of each wave). To measure COVID-19 related fears among survey respondents, the survey asked “how afraid are you of the COVID-19 pandemic?” where respondents could indicate their level of fear on a scale of 0 (not afraid) to 100 (very afraid). To explore social distancing behaviors during the pandemic we asked respondents to report the degree to which three statements about social distancing practices described their own behaviors. These statements concerned wearing a mask, avoiding social gatherings, and notifying the people around them if they exhibited COVID-19 symptoms. Each response ranged from 0 (“does not describe me”) to 100 (“describes me very well”). These measures were adapted from the “Measuring Worldwide COVID-19 Attitudes and Beliefs” projects [24]. We examined each of the above outcomes by respondents’ race/ethnicity and income level. For the purposes of this study, we only present estimates for White, Black, and Hispanic respondents, as it is between these groups that the largest reported well-being disparities have been observed in other research [25, 26]. We constructed the income groups in this study as a function of self-reported annual household income in 2019, household size, and the U.S. Department of Housing and Urban Development’ measure of area median income (AMI) at the county level. Based on HUD’s methodology for determining the eligibility of applicants for assisted housing programs [27], we defined three income cohorts based upon the AMI at the country level, adjusting for family size: low income: [0, 80% AMI); moderate income: [80, 120% AMI); and middle and high income: [120% AMI,.). In addition to the two key explanatory variables of race/ethnicity and income, we controlled for a set of covariates including demographic characteristics, health insurance status, the self-reported experience of COVID-19 symptoms, the prevalence of COVID-19 cases in the county in which the respondent lived as of the date of survey response, the population density of the respondent’s county of residence, and the respondent’s Census division. Demographic characteristics included gender, age, marital status, the number of children in the household, and educational attainment. In later waves, we also added in questions about likelihood of vaccination, financial shocks due to COVID-19, and other questions related to change in employment and health status due to the virus.

Statistical analysis

We estimated the relationships between race/ethnicity, income, and the array of outcome measures specified above using Ordinary Least Squares (OLS) regression models, with heteroscedasticity-robust standard errors. In addition to controlling for all the variables outlined above, we also included interaction terms for race/ethnicity and income, which allowed us to estimate the joint relationships between these variables and the outcomes of interest. For the sake of simplicity, we primarily focused on disparities between the lower- and middle/high-income cohorts. The data analysis in this study was conducted using Stata (version 16) and we used a statistical significance threshold of p < .10.

Results

Sample description

Overall, the sample well represents the U.S. population with respect to gender, age and marital status, and racial/ethnic composition. However, compared to the U.S. population, our sample is more highly educated; 57% of our respondents held Bachelor’s degree or higher, which is much higher than the U.S. population (32%) [28]. The proportion of respondents without dependents under 18 years old is 74%, which is slightly higher than the U.S. population (69%) [28]. About three in five of our respondents were considered to be low- and moderate-income, whose annual income was less than 120% AMI in 2019 at the country level. Table 2 reports the demographic characteristics of our sample.
Table 2

Analytic sample characteristics.

Percent
Gender:
    Non-Female49.1%
    Female50.9%
Age*:
    18–2411.0%
    25–3419.3%
    35–4416.4%
    45–5417.8%
    55+35.6%
Marital Status:
    Single **39.1%
    Married or living with a partner60.9%
Number of Dependents:
    No child72.1%
    1 Child13.5%
    2 Children10.6%
    3 Children or More3.8%
Education
    High School or Lower14.9%
    Some College/Associate’s Degree30.8%
    Bachelor’s degree29.6%
    Graduate/professional degree24.7%
Health insurance
    Have a health insurance91.3%
    Not have a health insurance8.7%
Race/Ethnicity
    White, non-Hispanic67.4%
    Black, non-Hispanic14.2%
    Hispanic18.4%
Income
    Low Income [0, 80% AMI)44.3%
    Moderate [80%, 120% AMI)20.1%
    Middle, and High Income [120% AMI,.)35.7%
Total  16,680

Notes: Reference categories are underlined

In the analytic model, we use age and age squared as continuous variables

Single includes never married, separated, divorced, and widowed.

Notes: Reference categories are underlined In the analytic model, we use age and age squared as continuous variables Single includes never married, separated, divorced, and widowed.

Life satisfaction, optimism, and mental health

We explore our respondents’ life satisfaction, mental health, and optimism during the pandemic. Figs 2 and 3 plot the changes in respondents’ current life satisfaction and their expected life satisfaction 5 years in the future—a proxy for optimism—by race/ethnicity and income. Fig 4 plots the change in respondents’ mental health throughout the pandemic by race/ethnicity and income.
Fig 2

Changes in life-satisfaction by race and income.

Fig 3

Changes in optimism by race and income.

Fig 4

Changes in mental health by race and income.

Higher incomes were associated with higher levels of life satisfaction, optimism, and mental health during the pandemic. In addition, we observe higher/better levels of these metrics among Black respondents, and smaller but still significant differences in life satisfaction and optimism among Hispanic respondents, with a slight temporary uptick in August of 2020 among rich Hispanics which we cannot fully explain. The differences in reported life satisfaction and optimism for the future between Black and White respondents were roughly as large as the differences between higher and lower income groups, and the gaps in optimism between the two groups were largest at low-income levels. Black respondents also reported better mental health than Whites. We did not observe any significant interactions between income level and race/ethnicity. What is most remarkable is that these trends remained remarkably stable throughout the pandemic. While there were modest drops in optimism and in mental health status at a few peaks, such as November 2020, the overall trends and the gaps across races remained similar, with Blacks in general and low income Blacks in particular retaining higher levels of optimism and lower levels of stress throughout the pandemic. New questions about feeling anxious, nervous, and weary were added to the survey in the final three waves. The patterns in these responses are again consistent with lower levels of anxiety for Blacks and in particular low-income blacks, than for other races and particularly compared to Whites. We ran an additional model, based on the PHQ-4 index (Fig 5), which sums up four indicators gauging depression (i.e., anxiety, worrying, weariness, and hopelessness), and is widely used in the clinical mental health field as a tracking tool (not a clinical diagnostic one). This is appropriate for our purposes, meanwhile, as we are following trends in reported depression and anxiety, not clinical diagnoses.
Fig 5

Changes in PHQ4 by race and income.

We first find that patterns in overall depression/anxiety are relatively constant over the course of the pandemic. Comparing across incomes, meanwhile, we find that higher income respondents exhibited lower anxiety and depression levels in general than the others through the pandemic, with levels in the “normal” range. Lower income respondents had mild levels of anxiety and depression, meanwhile. Across race/income groups, low-income Blacks again exhibit significantly lower levels of anxiety and depression than either low-incomes Whites or Hispanics, and these differences are large enough to drive the average overall trend in which Blacks have lower levels of anxiety and depression.

COVID-19 related fears/concerns

Overall, White respondents exhibited lower levels of COVID-19 fear than Black and Hispanic respondents and reported lower expected probabilities of COVID-19 infection and death than Hispanic respondents. This pattern remained quite consistent throughout the four survey waves. Fig 6 plots the predicted change in COVID-19 fear scores. Throughout the pandemic, the levels of COVID-19 related fears have not drastically changed except for White respondents—both lower- and higher income White respondents reported lower fear levels in comparison with those in the early period. Notably, the fear level of Black respondents with lower income was drastically increased during the summer in 2020, which might associated with the Black Lives Matter movements in the same period. With respect to variations by income, White respondents reported significant and negative associations between COVID-19 fear and income levels over the course of the pandemic. However, higher-income Black respondents reported significantly higher levels of COVID-19 fear than those with lower incomes, perhaps because of higher health literacy, better information, and more awareness than their lower income counterparts [29].
Fig 6

Changes in COVID-19 related fears by race and income.

It is possible that fear reports are influenced by traits such as optimism and pessimism and, as noted above, low income Blacks are more optimistic than most other groups. We explored the correlation between life satisfaction and COVID-19 fears. It is modestly negative, at 0.554, with a P-value of .003. This is intuitive but not large enough to drive the findings in a substantial way.

Social distancing behaviors

Finally we explored the changes in social distancing behaviors by respondents’ race/ethnicity and income. These were assessed by wearing a mask (Fig 7), avoiding social gatherings (Fig 8) and informing one’s COVID-19 related symptoms (Fig 9). White respondents were less likely to wear masks than Hispanic respondents regardless of income level, though White and Black households were similarly likely to wear masks. Self-reported mask-wearing scores stay flat as income increases for White and Hispanic respondents. While the score for mask wearing for Black respondents increases as their income level rises, this difference is not statistically significant. Over the course of the four waves, meanwhile, the difference in mask wearing across races narrowed quite a bit.
Fig 7

Changes in social distancing behaviors by race and income–wearing a mask.

Fig 8

Changes in social distancing behaviors by race and income–avoiding social gathering.

Fig 9

Changes in social distancing behaviors by race and income–informing one’s COVID-19 related symptoms.

Overall, Black respondents reported a significantly lower propensity to avoid social gatherings than White and Hispanic respondents. This difference appears to be driven by income, however, since higher-income Black households were as likely as those in the other two high income groups to report avoiding social gatherings. The lower reported rates of avoiding social gatherings for the low- and moderate-income (LMI) Black respondents might be associated with their employment status; 76% of Black LMI respondents reported that they were required to be physically present at their primary place of employment, which was significantly higher than the proportion of White (70%) and Hispanic (68%) LMI respondents. Their propensity to avoid gatherings increased slightly though in later waves of the survey, meanwhile. The narrowing of gaps across race/income groups likely reflects more acceptance of protective behaviors as the virus spread quite dramatically across the country (with, of course, some groups still resisting the restrictions). Higher-income respondents were more likely than lower-income respondents to report that they would inform others of any COVID-19 symptoms they exhibited, and low income Black households were the least likely to report that they would inform others of their symptoms than those in other groups, perhaps because of fear of job loss and/or greater mistrust of a health system that has systematically discriminated against them.

Discussion

The COVID-19 pandemic has exposed deep vulnerabilities across our fragmented health care system and across the income distribution. At the same time, it presents an urgent opportunity to better understand—and ultimately address—the factors driving health behaviors and persistent health inequities. While it may be tempting to blame differences in COVID-19 infection rates on individuals’ health behaviors, the answer to resolving COVID-19 disparities is more nuanced. Although personal compliance with guidelines such as handwashing, wearing a mask, and social distancing is critically important to reducing the spread of COVID-19, the pandemic has highlighted structural factors—who is designated an essential worker, the types of work they do, and whether they get sick days—and their profound influence on the health of individuals and the health of subgroups within the U.S. population. As such, the intersection of structural racism, social and economic factors influence people’s COVID-19 health behaviors. We explored this intersection by looking specifically at the ways in which the fear of COVID-19 influenced health behaviors as well as the impact of coping with the pandemic on mental well-being.

Role of fear in shaping health behaviors

Since the outbreak of the COVID-19 pandemic, the public has been bombarded by nearly continuous media updates of the threat of coronavirus, increasing infection rates, and new milestones in death counts. Living with this constant threat can increase anxiety and have immediate negative effects on mental health. Although the fear of infection could be expected to manifest itself in cautious, careful behavior aimed to prevent acquiring the illness, such fear can be overridden by other factors such as the messaging people receive about the disease, perception of personal infection risk, and economic factors such as income and whether a worker has paid sick days. With other widespread infections or epidemics such as the 2013–2016 West Africa Ebola virus outbreak, the public’s fear of infection led to behaviors that followed expected patterns of being conformist and less accepting of individualistic behavior [30]. COVID-19 has certainly elicited such behaviors in the U.S. population. However, in contrast to fear-driven behavior observed in other epidemics, coping with COVID-19 has brought about unexpected behavioral patterns ranging from harsh social attitudes, more conservative attitudes toward immigration, and even swaying political opinion and affiliations in which strong individualistic attitudes jeopardized the effectiveness of medically proven guide-lines–such as mask wearing–for containing the spread of the disease.

Role of fear in COVID-19 related health behaviors

Given standard patterns of health behaviors and the social determinants of health in which higher levels of income are associated with better access to care and better health outcomes, we were not surprised to find similar results in our sample. Across the intersection of three racial groups and income levels, White respondents with high levels of income reported the lowest levels of fear of COVID-19. However, we did not expect to find that Black respondents with high income levels would be more likely than low-and middle-income Black respondents to report experiencing high levels of fear related to COVID-19. What factors cause affluent White respondents to be insulated from COVID-19 fear whereas their affluent Black counterparts appear to experience high levels of COVID-19 fear? While racial and ethnic background does not protect anyone from COVID-19, the responses of affluent White respondents may reflect greater confidence in their ability to access medical care when needed as well as higher trust in the health care system [18]. The attitudes of more affluent Black respondents may reflect a greater sensitivity to the disproportionate rates of COVID-19 deaths among the Black population in general. Further, for affluent Black respondents, the COVID-19 disparity likely underscored historic health disparities and the ways in which Black patients are often marginalized within the health care system, no matter their wealth levels. Wealthy Blacks may be more aware of these glass ceiling effects than poorer ones. Assari [31], for example, finds that while increasing levels of education have a protective effect on mental health on average, that effect is lower for Blacks than for other races. Additionally, COVID-19 fear among low-income Blacks may be masked by an avoidance strategy that accepts realities that would normally induce toxic, traumatic stress. Acceptance of one’s fate, and in this case, denial of fear, has been documented to offer a long-term survival advantage [32]. However, in the context of COVID-19 related illness, acceptance does not connote an acceptance of racist constructs that consigned Blacks and other people of color to suffer higher morbidity and mortality from COVID-19. While adaptive in the short term, acceptance and avoidance is inherently counter-productive. Wilson and Murrell [33] describe the ways that both avoidance of our emotions and avoidance of meaningful contexts contribute to the maintenance of stress and anxiety. Fear of infection is likely hardwired in the human race to drive behaviors that benefit the species. If so, the fear driver should result in behaviors that are cautious and aim to limit personal and group risk of infection. However, we did not find fear of COVID-19 was consistently associated with better compliance with health guidelines such as wearing a mask in public or limiting social contacts. Indeed, our findings seem puzzling at first because Black respondents, some of whom reported the highest levels of COVID-19 fear, initially reported a much low propensity to avoid social gatherings. Yet a closer look at the intersection of race and income reveals that higher-income Black respondents were equally likely as their White counterparts to avoid social gatherings, whereas lower income Blacks were significantly less likely to. The differences in avoiding social gatherings between low income Blacks and other racial groups also narrowed quite a bit across the survey waves and the virus began to subside in many places by early in 2021, and people of all races began to socialize more. These differences are likely based in the economics of racial inequity, with Black individuals overrepresented in low-wage jobs that require them to be physically present in their workplace and less able to avoid social gatherings [34]. Although deemed essential workers, these workers are often paid minimum wage and do not receive benefits such as paid sick leave. Frequently, the combination of low pay and no benefits means they do not have the choice to practice social distancing, as few can afford to forgo a paycheck and stay at home. The preference for social gatherings among lower income Blacks also a cultural phenomenon, which emphasizes humanity as communal rather than individualistic [35, 36]. Further, whereas affluent respondents indicated a greater likelihood to self-report if they have symptoms consistent with COVID-19, lower-income Black respondents were significantly less likely to self-report their COVID-19 symptoms than other low-income groups. Again, this difference in health behavior is likely explained by the opportunities and choice afforded to affluent respondents. Those with higher incomes are more likely to work in jobs that allow some or all of their work to be done remotely [37]. In contrast, those at the other end of the economic spectrum are often living paycheck-to-paycheck and often report feeling they do not have a choice in continuing to work when feeling ill because their household is dependent on their paycheck. Low-income Blacks may also be less trusting than other cohorts of accessing good quality health care [38]. Again, though, the gaps narrowed significantly across races towards the final wave of the survey, with Hispanics less likely to report symptoms than Blacks (likely for similar reasons, particularly if they were undocumented immigrants).

Effects of coping with COVID-19 on mental well-being

Given the disproportionate effects of COVID-19 on the Black population, it would be logical to expect Blacks to exhibit the greatest losses in mental health and other dimensions of well-being. Yet, that is not what we found; Black respondents–and particularly low income ones—maintained higher levels of resilience–more optimism and better mental health–than White respondents throughout the course of the survey. While this result is in line with those of pre-COVID-19 studies that find high levels of optimism and resilience among Blacks compared to those of other races, is it remarkable that it held throughout the pandemic [26]. We would normally anticipate a negative association between COVID-19 related concerns and well-being during the pandemic–that is, the higher COVID-19 related concerns, the lower life satisfaction/optimism, and the lower mental health. Yet they are remarkably consistent with patterns that we have previously found in the well-being of different race and income cohorts in the face of deaths of despair. Using over 1 million responses over five years in Gallup data for the U.S., one of us (Graham, with Sergio Pinto) found large gaps in optimism and reported stress across poor Black and White individuals, with the former almost three times as likely to be a point higher on the 11-point optimism scale and 50 percent less likely to report experiencing stress the previous day than poor Whites (poor Hispanics again fall in between the two groups on the same markers). This finding is a lasting one, holding from 2010 until the present and now throughout the course of the pandemic [26]. While Black respondents are more optimistic than Whites in both sets of data, the largest differences are between poor Blacks and poor Whites. These patterns are reflected in those in C.D.C. data on deaths of despair, in which Blacks and Hispanics are much less likely to die from these deaths than are Whites. The reasons for this resilience are complex. They include a historical trajectory of overcoming adversity, strong community ties, and continued belief in the promise of education at a time that it has faded among low-income Whites. As a result, Blacks and Hispanics are gradually narrowing gaps in education and in life expectancy with Whites. Poor Whites, meanwhile, have fallen behind in absolute terms compared to wealthy Whites and in relative terms compared to minorities; losses that are reflected in their high levels of despair. Historically, meanwhile, optimism among Blacks began to increase in the 1970s, when civil rights improved, and began to fall among less than college-educated White men around the same time (coinciding with the first declines in manufacturing) [39]. It seems that the same traits that drive minority resilience may also be protective of well-being and mental health in the context of the pandemic. Deaths of despair are, at least at some level, preventable because they are desperation-related behaviors. In contrast, COVID-19 is an exogenous shock–largely unrelated to individual behavior–that has disproportionately affected the Black population. Despite such disparities, in both of our studies the Black respondents have displayed high levels of hope and resilience. It appears that the same traits that drive minority resilience might also be protective of well-being and mental health in the context of the pandemic. While that is the hope, we still do not know what the long-run effects of the COVID-19 pandemic will be. Excess deaths in 2020 (both due to COVID-19 and to many other conditions, including pre-existing conditions and increases in drug overdoses) were highest among Blacks, and there are many reports of increased anxiety, depression, and related outcomes, particularly among the young, with minority teens and young adults in particular experiencing increases from past (relatively lower) levels [40, 41]. These deep differences in resilience have implications for the long-term mental health effects of different population groups in the face of the unprecedented challenge that COVID-19 presents to the health and well-being of our society. Better understanding these differences–and the lessons that stem from those population cohorts with the most resilience–can, in the end, lead to lessons that may help bolster the mental health and coping skills and behavioral responses of vulnerable groups during uncertain times.

Survey items used in the analysis.

(DOCX) Click here for additional data file. 11 Nov 2021
PONE-D-21-27864
Coping with COVID-19: Differences in Hope, Resilience, and Mental Well-being across U.S. Racial Groups
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For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Sanjay Kumar Singh Patel, Ph.D. Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please provide additional details regarding participant consent. In the Methods section, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information. 3. Thank you for stating the following financial disclosure: There was not a specific funding source for this article. The survey was funded by the School of Social Policy at Washington University in St. Louis. Please state what role the funders took in the study.  If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf. 4. Thank you for stating the following in your Competing Interests section: The authors have no competing interests. Please complete your Competing Interests on the online submission form to state any Competing Interests. If you have no competing interests, please state "The authors have declared that no competing interests exist.", as detailed online in our guide for authors at http://journals.plos.org/plosone/s/submit-now This information should be included in your cover letter; we will change the online submission form on your behalf. 5. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For more information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. In your revised cover letter, please address the following prompts: a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. We will update your Data Availability statement on your behalf to reflect the information you provide. 6. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide. 7. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well. 8. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: No ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: In this paper entitled "Coping with COVID-19: Difference in hope, resilience and mental well-being across U.S. racial groups", the author examines how the COVID-19 pandemic impacts health and mental well-being across different racial groups. The studies have used advanced statistical techniques like logistic regression and fixed effect modeling to estimate COVID-19 impact on health and mental well-being. The study found that Black and Hispanics remain more resilient and optimistic than their white counterparts despite extreme income and health disparities before and during the COVID-19 outbreak. The most significant difference in resilience, optimism, and better mental health is between poor black and white poor. These results help to understand the factors involved to preserve mental health in the face of public health and other large cities crises. The present manuscript is well written and easy to understand. This manuscript is an excellent study that draws attention to adverse mental health and well-being during the COVID-19 pandemic. It also allowed understanding how to reduce the social and economic consequences of adverse mental health, which improves health and well-being during the pandemic. There are no technical flaws in the manuscript to reject it. Therefore, it should be considered for the publication. Reviewer #2: This is an excellent paper by Graham and colleagues that could not be more timely and relevant to the current discourse surrounding health inequities in the COVID-19 era. The methodology is sound and the results are well presented. Additionally, the principal findings of increased resilience among and optimism among Blacks and Hispanics could certainly shape the provision of mental health and support services for these groups going forward. I would recommend this paper for publication following minor revisions. I have very few comments (please see below). General • Authors should maintain consistency in the use of “COVID-19” or “COVID” throughout the paper Abstract • Line 30 – the word “if” is missing from after the word “explore” Introduction • Line 71 – these comorbidities are risk factors for poorer COVID-19 outcomes (not for COVID-19 acquisition) Methods • Authors could consider including the survey as an appendix/supplementary material to complement the description of the tool in the methods section Results • Figure 6 appears to be the same graph twice (both low-income results). The mid/high-income graph is missing Discussion • Did the authors identify any limitations of their study? [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.
1 Feb 2022 On behalf of myself and co-authors, we thank you for the attention to our manuscript entitled “Coping with COVID-19: Differences in Hope, Resilience, and Mental Well-being across U.S. Racial Groups”, the positive and helpful comments of both reviewers, and the opportunity to re-submit the paper. First, we have adapted the formatting to meet the PLOS ONE standards. Second, in terms of data, we have created a GitHub access link, which provides the raw data files and variables that we used for our analysis in this paper, as well as the codes (https://github.com/SocialPolicyInstitute/SEICS/tree/main/PLoS-ONE). Third, although this paper did not receive any direct funding from any source, the collection of the data used in this paper was funded by grants to the SPI at Wash U from the Mastercard Foundation, the JPMorgan Chase Foundation, the Annie E. Casey Foundation, and Centene Corporation. These funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Fourth, the authors have declared that no competing interests exist. Fifth, we have adapted the methods statement to include that the survey was submitted to the Washington University at St. Louis IRB (ID: 202004100) and was approved. This was not a requirement as it is an on-line internet survey with voluntary participation, but we sought the additional approval. We received written consent. Even though it was exempt, we still got written (online) consent from all research participants before they entered the survey. The survey was also limited to adults. Fifth, as required we have checked the reference section to ensure that all references in the list are referenced in the text. We have also uploaded the figures to the PACE tool as recommended. In terms of responses to Reviewer 2’s more detailed comments, we have: standardized our reference to COVID-19 throughout the manuscript; fixed the missing panel in Figure 6; fixed the typo on line 30; and made the point on line 71 that the co-morbidities we refer to are risk factors for poor COVID-19 outcomes, not for COVID-19 acquisition. Finally, we have included the survey questionnaire as supplementary material and reference that in the methods section. Again, we much appreciate the chance to submit a revised manuscript and hope that we have fully addressed the questions above. We are pleased to have the opportunity to publish in PLOS ONE. 12 Apr 2022 Coping with COVID-19: Differences in Hope, Resilience, and Mental Well-being across U.S. Racial Groups PONE-D-21-27864R1 Dear Dr. Graham, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Giuseppe Carrà, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: In this paper entitled "Coping with COVID-19: Differences in Hope, Resilience, and Mental Well-being across U.S. Racial Groups", the authors have addressed all the comments and have no technical deficiency for rejection. The paper is eligible for acceptance in the journal. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: Yes: Aditya Kumar Sharma 29 Apr 2022 PONE-D-21-27864R1 Coping with COVID-19: Differences in hope, resilience, and mental well-being across U.S. racial groups Dear Dr. Graham: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Giuseppe Carrà Academic Editor PLOS ONE
  22 in total

1.  Race and trust in the health care system.

Authors:  L Ebony Boulware; Lisa A Cooper; Lloyd E Ratner; Thomas A LaVeist; Neil R Powe
Journal:  Public Health Rep       Date:  2003 Jul-Aug       Impact factor: 2.792

2.  Racial differences in trust in health care providers.

Authors:  Chanita Hughes Halbert; Katrina Armstrong; Oscar H Gandy; Lee Shaker
Journal:  Arch Intern Med       Date:  2006-04-24

Review 3.  African Americans with asthma: genetic insights.

Authors:  Kathleen C Barnes; Audrey V Grant; Nadia N Hansel; Peisong Gao; Georgia M Dunston
Journal:  Proc Am Thorac Soc       Date:  2007-01

4.  Well-being in metrics and policy.

Authors:  Carol Graham; Kate Laffan; Sergio Pinto
Journal:  Science       Date:  2018-10-18       Impact factor: 47.728

5.  Variation in COVID-19 Hospitalizations and Deaths Across New York City Boroughs.

Authors:  Rishi K Wadhera; Priya Wadhera; Prakriti Gaba; Jose F Figueroa; Karen E Joynt Maddox; Robert W Yeh; Changyu Shen
Journal:  JAMA       Date:  2020-06-02       Impact factor: 56.272

6.  Stroke in a biracial population: the excess burden of stroke among blacks.

Authors:  Brett Kissela; Alexander Schneider; Dawn Kleindorfer; Jane Khoury; Rosemary Miller; Kathleen Alwell; Daniel Woo; Jerzy Szaflarski; James Gebel; Charles Moomaw; Arthur Pancioli; Edward Jauch; Rakesh Shukla; Joseph Broderick
Journal:  Stroke       Date:  2004-02       Impact factor: 7.914

Review 7.  Kidney Disease Among African Americans: A Population Perspective.

Authors:  Marciana Laster; Jenny I Shen; Keith C Norris
Journal:  Am J Kidney Dis       Date:  2018-11       Impact factor: 8.860

8.  Assessment of Community-Level Disparities in Coronavirus Disease 2019 (COVID-19) Infections and Deaths in Large US Metropolitan Areas.

Authors:  Samrachana Adhikari; Nicholas P Pantaleo; Justin M Feldman; Olugbenga Ogedegbe; Lorna Thorpe; Andrea B Troxel
Journal:  JAMA Netw Open       Date:  2020-07-01

9.  The Association between Future Anxiety, Health Literacy and the Perception of the COVID-19 Pandemic: A Cross-Sectional Study.

Authors:  Mariusz Duplaga; Marcin Grysztar
Journal:  Healthcare (Basel)       Date:  2021-01-05

10.  Are There Advantages to Believing in Fate? The Belief in Negotiating With Fate When Faced With Constraints.

Authors:  Evelyn W M Au; Krishna Savani
Journal:  Front Psychol       Date:  2019-11-08
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