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. 2022 Oct 18:10.1002/jcop.22953. Online ahead of print. doi: 10.1002/jcop.22953

Race, masks, residency and concern regarding COVID‐19 transmission

Sameena Azhar 1,✉, Rahbel Rahman 1, Laura J Wernick 1, Saumya Tripathi 1, Margaret Cohen 1, Tina Maschi 1
PMCID: PMC9874564  PMID: 36256889

Abstract

To explore sociodemographic predictors for concern regarding COVID‐19 transmission and how these factors interact with the identities of others, we conducted a web‐based survey where we asked 568 respondents in the United States to indicate their level of COVID‐19 concern in response to a series of images with short vignettes of masked and unmasked individuals of different racial/ethnic backgrounds. Using a linear mixed effects model, we found that regardless of the race of the image being presented in the vignette, concern regarding COVID‐19 transmission was associated with respondents' older age (b = 0.029, p < 0.001), residing in NYC (b = 0.556, p = 0.009), being heterosexual (b = 1.075, p < 0.001), having higher levels of education, that is, completion of a Bachelor's degree (b = 1.10, p = 0.033) or graduate degree (b = 1.78, p < 0.001), and the person in the vignette being unmasked (b = 0.822, p < 0.001). Asian respondents were more likely than White respondents to be concerned regarding COVID‐19. Individuals who self‐reported themselves to be at high risk for COVID‐19 were more likely to be concerned about COVID‐19 over those who considered themselves to be low risk. These findings highlight the importance of acknowledging interactions between race, mask status, and residency in predicting COVID‐19 concern.

Keywords: COVID‐19, masks, New York City, race, residency

1. BACKGROUND

Minimizing the risks of the global COVID‐19 pandemic and addressing its racial, social, and economic implications are the greatest public health dilemmas of our era. In the United States (U.S.), mask‐wearing has been highly politicized as social tensions have arisen over mask mandates and social distancing (Stroebe et al., 2021). The politics of pandemics often involves ethnic and racial discrimination against minoritized groups (Azhar et al., 2022). Emerging research calls for an exploration of the implications of mask‐wearing for racially minoritized groups, as well as stigmatization toward people with and without masks (Betsch et al., 2020). To explore sociodemographic predictors for concern regarding COVID‐19 transmission and how these factors interact with the identities of others, we conducted a web‐based survey where we asked 568 respondents in the US to indicate their level of COVID‐19 concern in response to a series of images with short vignettes of masked and unmasked individuals of different racial/ethnic backgrounds. We hypothesized that race and residency of the subject, as well as race and mask status of the presented image, would predict COVID‐19 concern.

1.1. Impacts of COVID‐19 on racial/ethnic and religious minority communities

As of May 5, 2022, there have been 81,492,170 documented cases of COVID‐19 infections and 994,187 deaths in the US (Centers for Disease Control and Prevention [CDC], 2022a). As of May 5, 2022, New York City (NYC) had an estimated 2,387,450 COVID‐19 infections and 40,227 deaths (NYC DOH, 2020). NYC was the epicenter of the COVID‐19 pandemic during the first wave of infections in the US, from roughly March to June 2020. Over the summer of 2020, stay‐at‐home orders and restrictions on businesses were first being lifted in many states, including NYC. While a notable decrease in positivity rates was reported in NYC, New England, the mid‐Atlantic, and the Midwest during the summer of 2020, COVID‐19 rates concurrently increased in rural areas in the Southeast, South central, and South/West Coast of the US by more than 10% (CDC, 2020a). As such, COVID‐19 concern may vary depending on where people resided in the US and the concurrent incidence of the virus in that region at that time.

COVID‐19 has disproportionately impacted racial and ethnic minority populations in the US (CDC, 2022a). Although only 12.8% of people in the US identify as Black/African American (U.S. Census Bureau, 2019), they were 1.1 times more likely than White people to be infected with COVID‐19, 2.2 times more likely to be hospitalized, and 1.7 times more likely to die of COVID‐19 fatalities (CDC, 2022b). Similarly, although 18.4% of people in the US identify as Hispanic/Latinx (U.S. Census Bureau, 2019), Hispanic/Latinx people were 1.5 times more likely to be infected with COVID‐19 than White people, 2.1 times more likely to be hospitalized, and 1.8 times more likely to die of COVID‐19 fatalities (CDC, 2022b).

COVID‐19 fatality rates for Black and Latinx/Hispanic communities were also disproportionately higher in NYC. While NYC residents are 32.1% White, 29.1% Hispanic/Latinx, 24.3% Black, 13.9% Asian, and 3.5% biracial/multiracial (U.S. Census Bureau, 2019). Black and Hispanic/Latinx New Yorkers were significantly more likely to be infected with or to die from COVID‐19 over other racial groups (Laurencin & McClinton, 2020; NYC DOH, 2020; Selden & Berdahl, 2020). Racial/ethnic and religious minorities who experienced higher rates of COVID‐19 incidence were also more likely to experience poverty, live in crowded spaces, and work in lower‐paid positions as essential workers (Brown, 2020). Given the concentration of COVID‐19 outbreaks in the NYC metropolitan area at this point in the pandemic (Summer 2020) and the racialization of the pandemic across the US, residency and race were key factors of interest in the present study.

1.2. Politicization and racialization of mask‐wearing

Social distancing and mask‐wearing were recommended as public health guidelines to combat the transmission of COVID‐19 (CDC, 2020b). Wearing masks or facial coverings has been shown to reduce the spread of droplets and infectious aerosols that can transmit COVID‐19 and other respiratory infections (Leung et al., 2020). In June 2020, the World Health Organization (WHO, 2020) recommended that all individuals wear nonmedical masks in settings where physical distancing could not be achieved, including public spaces, like grocery stores.

On March 13, 2020, the President declared a national emergency under Proclamation 9994 (Executive Office of the President of the United States of America, 2020). Nonetheless, there was never a unified, national containment strategy for COVID‐19 in the US. Policy responses to COVID‐19 across the country have been disparate and sometimes conflicting, leaving space for the dismissal of epidemiological information. Public health guidelines and mandates within the US ranged from strict shelter‐in‐place or stay‐at‐home orders, such as in New York; to minimal regulations, such as in South Carolina, which was the first state to end their lockdown after only 13 days; to no regulations at all in South Dakota (Zhang & Warner, 2020). Inconsistent local and state public health mandates and the lack of a robust federal response have left racial/ethnic minority communities vulnerable to the impacts of stigmatizing policies (Mooney et al., 2020).

Xenophobia compounds experiences of stigma and discrimination associated with infectious diseases (Colson et al., 2014). Epidemics are characterized and racialized through language. Immigrants are frequently the scapegoats for contagious diseases as stigmatization plays into the identity dichotomy of “us” and “them,” notions that are predicated on the fear of the Other (Roberto et al., 2020). Stigma threatens the ability of minoritized communities to access care and can be used as a political catalyst for xenophobia (Villa et al., 2020). Immigrants have also been shown to have higher rates of both internalized shame and externalized blame regarding infectious diseases (Marks et al., 2008).

Mask‐wearing for Asian people during COVID‐19 also primes historical stereotypes of foreignness and disease. Previous research has documented how Asian immigrants experienced stigma related to H1N1 and SARS (Ali, 2008; Ding, 2014). During the SARS epidemic, the Chinese Canadian community was heavily stigmatized as community members actively avoided neighborhoods in Chinatown to avoid potential infection (Ali, 2008). During the SARS pandemic, people of Chinese ethnicity were stigmatized for wearing masks as this behavior was associated with danger and contagion (Ali, 2008). Similarly, stigma associated with both TB and HIV was racialized against Haitians (Colson et al., 2014; Coreil et al., 2010). Previous research regarding H1N1 suggests that concerns regarding contagion may be catalyzed by a desire for physical distance from individuals perceived to be potentially infected (Earnshaw & Quinn, 2013). During the H1N1 pandemic, increased prejudice toward those infected with the virus was associated with increased physical distance (Earnshaw & Quinn, 2013). These same trends of racializing epidemics have recurred with the spread of COVID‐19 (Roberto et al., 2020). Asian American communities in the US have experienced increased discrimination following media framing that has primarily associated COVID‐19 with people of Asian ethnicity (Kambhampaty, 2020).

COVID‐19 has also disproportionately impacted the Orthodox and Hasidic Jewish communities (Bellafonte, 2020). NYC also has a large Hasidic Jewish population and initial COVID‐19 outbreaks had been concentrated in this group, leading to escalated stigmatization against members of this community (Stack & Goldstein, 2020). Local media and elected officials targeted racial/ethnic and religious minority communities for noncompliance with public health mandates, blaming these communities for spiking COVID‐19 incidence, particularly in the NYC metropolitan area (Carmody et al., 2021; Stack & Goldstein, 2020; Weinberger‐Litman et al., 2020). In NYC Orthodox and Hasidic Jews have been attacked on the street as they may be more easily identifiable by their appearance or dress (Gilman, 2021).

Further, mask‐wearing during the COVID‐19 pandemic has become heavily politicized and at times stigmatized, both for those who wear masks and for those who do not (Yoshioka & Maeda, 2020). Anti‐mask protests erupted in the summer of 2020 as protestors believed that state and local mask mandates were stripping citizens of their autonomy (Rahman et al., 2022). During the early months of the pandemic, people with stronger beliefs in faith over science were more likely to report higher degrees of concern regarding COVID‐19 transmission (Johnson et al., 2021). People with conservative views were more likely to resist mask‐wearing whereas Black people reported experiencing mistreatment when masked (Christiani et al., 2022). Black and Hispanic/Latinx Americans may also have been fearful of mask‐wearing due to a legacy of policing Black and Brown bodies prejudicially because of their clothing and appearance (Lowe, 2020). Between March 16 and May 10, 2020, 93% of coronavirus‐related arrests made by the New York City Police Department were of people of color (Duggan, 2020). The concept of “mask tipping,” which pressures Black men to show shopkeepers their faces when entering stores, was used as a means to perpetuate anti‐Black racism by requiring racialized bodies to reveal themselves as “safe” to avoid biases and endangerment from store owners (Jan, 2020). The arrests of people for breaching COVID‐19 public health measures and subsequent labeling of “superspreaders” also signals the creation of a deviant, immoral—and racialized—other (Bhanot et al., 2021). Mask‐wearing can create a paradox for Black and Latinx people who may be racially profiled for mask‐wearing while conversely also being admonished for not wearing a mask. Ultimately, mask‐wearing is an individual‐level behavioral intervention that leaves primary responsibility for disease prevention on the onus of individuals. The politicization of mask‐wearing helped to mold a narrative where individuals were at fault for the spread of the disease through particular deviant behaviors, namely not wearing a mask, not engaging in social distancing, or not being vaccinated.

1.3. Study objective

From the extant research, predictors for concern regarding COVID‐19 transmission, particularly as this concern is affected by mask status, race, and residency, remain unclear, particularly in the sociocultural context of the US. To explore sociodemographic predictors for concern regarding COVID‐19 transmission and how these factors interact with the identities of others, we conducted a web‐based survey where we asked 568 respondents in the US to indicate their level of COVID‐19 concern in response to a series of images with short vignettes of masked and unmasked individuals of different racial/ethnic backgrounds.

2. METHODS

We surveyed 568 individuals on the online survey platform, Qualtrics XM, between August and November 2020. In consultation with Qualtrics administrators, the incentive amount for participants was set at a range from $2.50 to $4, depending on the timing of the survey and sampling quotas within the data collection period. Eligibility criteria were: (1) participants were residents of the US; (2) were over the age of 18 years, and (3) were able to complete the online survey using the Qualtrics platform.

2.1. Recruitment

Qualtrics administrators sent out the survey link to various national panels and respondents completed the online survey on their own, without any assistance from the research team. Using stratified random sampling to analyze differences across race, we recruited roughly equal numbers of Asian (N = 181), Black (N = 195), and White (N = 192) participants, both within (N = 308) and outside of NYC (N = 260). Equal numbers were obtained by setting up quotas on the Qualtrics study recruitment parameters. Once the quota for equal representation of each racial group was met on the Qualtrics platform, respondents from that group were no longer eligible for participation in the study. Race was determined by a self‐report question, following the five categories for race utilized by the US Census Bureau, namely American Indian/Alaska Native, Asian, Black/African American, Native Hawaiian/Pacific Islander, and White. Participants were also able to indicate if they had a biracial or multiracial background. Ethnicity was measured in dichotomous terms, as it is currently defined by the US Census Bureau: Latinx/Hispanic or not Latinx/Hispanic.

2.2. Measures

The measures used in the present study were adapted in response to the context of COVID‐19 in the US at the height of the pandemic. One of the novel contributions of our study is the utilization of images to attempt to capture racialized attitudes. All measures, manipulations, and exclusions and reported here. Sample size was determined before any data analysis was performed.

2.2.1. Images

Emerging research suggests that images used in surveys can affect survey responses (Toepoel & Couper, 2011), likely in relation to the vagueness of the associated verbal or textual information (Couper et al., 2004). An important feature of image significance is the assimilation effect in which respondents react to questions based on the images, potentially functioning as primers for survey responses (Toepoel & Couper, 2011).

After answering sociodemographic questions, participants were asked to indicate their level of concern about COVID‐19 transmission in response to a series of eight short vignettes that were accompanied by images. In the first four images, the person was wearing a mask, and in the second four images, the person was not wearing a mask. To avoid biases by gender, the presentation of the people in the images matched the clothing and gender expression typically associated with males. Further, the racial/ethnic or religious identity of the mask wearer varied to include an Asian person, a Black person, a Hasidic person, and a White person. A graphic designer was enlisted to create these images. The sequence of the first four images of a masked person were randomized on the Qualtrics platform; similarly, the second four images of an unmasked person were also randomized. However, all images were presented to all participants (see Figures 1, 2, 3, 4, 5, 6, 7, 8).

Figure 1.

Figure 1

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Asian man, masked

Figure 2.

Figure 2

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Asian man, unmasked

Figure 3.

Figure 3

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Black man, masked

Figure 4.

Figure 4

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Black man, unmasked

Figure 5.

Figure 5

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Hasidic man, masked

Figure 6.

Figure 6

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Hasidic man, unmasked

Figure 7.

Figure 7

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White man, masked

Figure 8.

Figure 8

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White man, unmasked

2.2.2. Sociodemographic characteristics

As listed in Table 1, we collected information regarding participants' race (Asian, Black, White); age (in years); ethnicity (Latinx/Hispanic or not Latinx/Hispanic); gender identity (cisgender female, cisgender male, transgender/gender‐nonconforming); sexual orientation (heterosexual or not heterosexual); partnership status (single, married/partnered); employment (employed full‐time, employed part‐time, student, disabled, retired or unemployed); annual income (less than $10k, between $10k–$20k, $20k–$30k, $40k–$50k, $50k–$75k, $75k–$100k, $100k–$150k, $150k–$250k, and more than $250k); education (high school or less, some college, Bachelor's degree, graduate degree); country of birth (born in the US or not); years in the US; primary language spoken at home (English or others); residency (NYC resident or not); household size; living situation (living alone, living with partner, family or roommates, living in shelter or homeless); and disability status (yes/no).

Table 1.

Sociodemographic characteristics (N = 568)

Variables – n (%) Asian (N = 181) Black (N = 195) White (N = 192) Total (N = 568)
Age (Mean/SD) 32.39 (11.31) 29.6 (12.02) 40.33 (16.14) 34.12 (14.11)
Ethnicity
Latinx/Hispanic 22 (3.9) 55 (9.7) 49 (8.6) 126 (22.2)
Non‐Latinx/Hispanic 159 (28) 140 (24.6) 143 (25.2) 442 (77.8)
Gender Identity
Male 71 (12.5) 72 (12.7) 109 (19.2) 252 (44.4)
Female 106 (18.7) 113 (19.9) 75 (13.2) 294 (51.8)
Transgender 4 (0.7) 10 (1.8) 8 (1.4) 22 (3.9)
Sexual orientation
Heterosexual 150 (26.4) 152 (26.8) 154 (27.1) 456 (80.3)
Not heterosexual 31 (5.5) 43 (7.6) 38 (6.7) 112 (19.7)
Partnership status
Single 93 (16.4) 129 (22.7) 64 (11.3) 286 (50.4)
Married or partnered 88 (15.5) 66 (11.6) 128 (22.5) 282 (49.6)
Employment status
Employed full‐time 83 (14.6) 80 (14.1) 113 (19.9) 276 (48.6)
Employed part‐time 36 (6.3) 63 (11.1) 31 (5.5) 130 (22.9)
Student 31 (5.5) 19 (3.3) 12 (2.1) 62 (10.9)
Disabled, retired, or unemployed 31 (5.5) 33 (5.8) 36 (6.3) 100 (17.6)
Variables – n (%) Asian Black White Total
Income
Less than $10,000 34 (6) 28 (4.9) 8 (1.4) 70 (12.3)
Between $10,000 and $20,000 15 (2.6) 29 (5.1) 13 (2.3) 57 (10)
Between $20,000 and $30,000 24 (4.2) 32 (5.6) 9 (1.6) 65 (11.4)
Between $30,000 and $40,000 12 (2.1) 19 (3.3) 15 (2.6) 46 (8.1)
Between $40,000 and $50,000 13 (2.3) 13 (2.3) 11 (1.9) 37 (6.5)
Between $50,000 and $75,000 28 (4.9) 25 (4.4) 29 (5.1) 82 (14.4)
Between $75,000 and $100,000 24 (4.2) 16 (2.8) 30 (5.3) 70 (12.3)
Between $100,000 and $150,000 13 (2.3) 12 (2.1) 38 (6.7) 63 (11.1)
Between $150,000 and $250,000 8 (1.4) 11 (1.9) 24 (4.2) 43 (7.6)
Over $250,000 10 (1.8) 10 (1.8) 15 (2.6) 35 (6.2)
Education
High school or less 31 (5.5) 62 (10.9) 30 (5.3) 123 (21.7)
Some college 38 (6.7) 47 (8.3) 24 (4.2) 109 (19.2)
Bachelor's degree 76 (13.4) 62 (10.9) 55 (9.7) 193 (34)
Graduate degree 36 (6.3) 24 (4.2) 83 (14.6) 143 (25.2)
Country of birth
Born in the US 131 (23.1) 177 (31.2) 168 (29.6) 476 (83.8)
Not born in the US 50 (8.8) 18 (3.2) 24 (4.2) 92 (16.2)
Years in the US (mean/SD) 22.65 (13.54) 23.93 (14.31) 35.02 (20.15) 27.22 (17.17)
Primary language spoken at home
English 155 (27.3) 185 (32.6) 173 (30.5) 513 (90.3)
Others 26 (4.6) 10 (1.8) 19 (3.3) 55 (9.7)
Residency
NYC 103 (18.1) 103 (18.1) 102 (18) 308 (54.2)
Non‐NYC 78 (13.7) 92 (16.2) 90 (15.8) 260 (45.7)
Variables – n (%) Asian Black White Total
Second home outside of NYC (NYC residents only)
Yes 19 (10) 27 (13.7) 25 (11.3) 71 (35)
No 84 (21.8) 76 (20.6) 77 (22.5) 237 (65)
Household size (Mean/SD) 3.26 (3.27) 3.04 (3.68) 3.27 (3.27) 3.19 (3.41)
Living situation
Living alone 38 (6.7) 64 (11.3) 47 (8.3) 149 (26.2)
Living with partner, family, or roommates 138 (24.3) 129 (22.7) 143 (25.2) 410 (72.2)
Living in shelter or homeless 5 (0.9) 2 (0.4) 2 (0.4) 9 (1.6)
Disability
Yes 23 (4) 51 (9) 56 (9.9) 130 (22.9)
No 158 (27.8) 144 (25.4) 136 (23.9) 438 (77.1)
Past frequency of public transportation use
Frequently – Every day 46 (8.1) 56 (9.9) 65 (11.4) 167 (29.4)
Often – Several times a week 44 (7.7) 59 (10.4) 43 (7.6) 146 (25.7)
Sometimes – A few times a month 47 (8.3) 39 (6.9) 46 (8.1) 132 (23.2)
Rarely – A few times a year 22 (3.9) 19 (3.3) 22 (3.9) 63 (11.1)
Never 22 (3.9) 22 (3.9) 16 (2.8) 60 (10.6)
Current frequency of public transportation use
Frequently – Every day 20 (3.5) 40 (7) 44 (7.7) 104 (18.3)
Often – Several times a week 41 (7.2) 43 (7.6) 39 (6.9) 123 (21.7)
Sometimes – A few times a month 44 (7.7) 55 (9.7) 48 (8.5) 147 (25.9)
Rarely – A few times a year 38 (6.7) 29 (5.1) 24 (4.2) 91 (16)
Never 38 (6.7) 28 (4.9) 37 (6.5) 103 (18.1)
COVID‐19 diagnosis
Yes 17 (3) 43 (7.6) 49 (8.6) 109 (19.2)
No 164 (28.9) 152 (26.8) 143 (25.2) 459 (80.8)
Variables – n (%) Asian Black White Total
COVID‐19 Symptoms
Yes 28 (4.9) 49 (8.6) 58 (10.2) 135 (23.8)
No 153 (26.9) 146 (25.7) 134 (23.6) 433 (76.2)
Self‐reported COVID‐19 risk level
Low 76 (13.4) 71 (12.5) 50 (8.8) 197 (34.7)
Medium 74 (13) 85 (15) 80 (14.1) 239 (42.1)
High 31 (5.5) 39 (6.9) 62 (10.9) 132 (23.2)
Know someone who has COVID‐19
Yes 89 (15.7) 104 (18.3) 122 (21.5) 315 (55.5)
No 92 (16.2) 91 (16) 70 (12.3) 253 (44.5)
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Abbreviations: 

NYC, New York City; 

SD, standard deviation; 

US, United States.

In terms of behavioral or health‐related factors, we collected information on past and current frequency of public transportation use (frequently/every day, often/several times a week, sometimes/a few times a month), rarely/a few times a year), never); previous COVID‐19 diagnosis (yes/no); previous COVID‐19 symptoms (yes/no); and knowing someone who had COVID‐19 (yes/no). Outside of income, all other sociodemographic and health variables were treated as categorical variables and were not collapsed into larger groups.

2.2.3. Concern regarding COVID‐19 transmission

While the use of face masks to prevent the spread of COVID‐19 or slow the transmission of the disease is considered to be an effective tool (Howard et al., 2021), mask usage has been inconsistent and heavily politicized throughout the pandemic. Given these variations in opinion towards mask usage and concern regarding COVID‐19 transmission, we asked participants to indicate their level of COVID‐19 concern in response to a series of masked and unmasked images. The vignette read: “Imagine the following scenario. Today you walk into a local corner store/bodega, wearing a mask. You notice a customer pictured above.” Following each image, participants were asked, “On a scale of 0 to 10, how concerned would you be about getting close to this person (where 0 indicates completely unconcerned and 10 indicates extremely concerned)?”

2.2.4. Self‐rated COVID‐19 risk

Participants were asked to respond to the question: “What do you consider your risk level for contracting COVID‐19?” with one of three options: high, medium, or low.

2.3. Ethical review

Participant risks and benefits were explained to all participants before data collection. Informed consent was obtained via the Qualtrics platform before initiating the survey questions. The study protocol was approved by the Fordham University Institutional Review Board (IRB) in July 2020; data collection was completed between August and November 2020.

2.4. Data analysis

Statistical analyses were performed on the software package R. Descriptive statistics were performed to characterize the sample. Data were initially cleaned for duplicate or incomplete survey entries, errors or meaningless outliers through a manual review of the data. Missing data were handled using listwise deletion, where any individual in the data set would be deleted from analysis if there was any missing data for any variable included in the analysis. However, given the quality checks for survey completion through the Qualtrics survey platform, there was no missing data for the variables we examined, so no respondents were removed from the final data set for this analysis.

Given that we had multiple observations provided by the same subjects, we utilized a linear mixed‐effects model to control for both random and fixed effects within hierarchical models. Bivariate correlations were performed on all predictor variables as preliminary indicators of associations with concern regarding COVID‐19 transmission. All sociodemographic variables, except for income, were treated as categorical variables in the linear mixed effects models; income was treated as a continuous variable. Variables that had a Pearson bivariate correlation with COVID‐19 concern with a p value of <0.10 were tested in subsequent linear mixed effects models. Interaction effects between race and participants' sociodemographic characteristics, as well as interactions between sexual orientation and gender identity, were also tested.

3. RESULTS

3.1. Sociodemographic characteristics

Table 1 reviews the sociodemographic characteristics of the sample of 568 respondents, with cross‐tabulations by race. Of the sample, 22.2% identified as Latinx/Hispanic. The mean age of respondents was 34.12 years (SD = 14.11). By sexual orientation, 19.7% identified as not heterosexual and by gender identity, 3.9% identified as transgender or gender‐nonconforming. The sample was almost equally divided between single (50.4%) and partnered (49.6%) individuals. Most respondents were employed full‐time (48.6%), were born in the US (83.8%), and had spent on average 27.22 years (SD = 17.17) years in the US. Of those not born in the US, the largest proportions were born in China (3.2%), the Philippines (1.4%), the Dominican Republic (1.2%), South Korea (1.1%), and El Salvador (1.1%). In terms of disability status, 22.9% reported having a disability. Income and education were fairly normally distributed across categories. A little over half the sample (54.2%) resided in NYC; 45.7% resided outside of NYC. Of those residing outside of NYC, there was a fairly national representation of respondents, but the largest proportions of respondents were residents of the Northeastern/Mid‐Atlantic region, or the West/Midwest region of the US, namely the states of: California (n = 39); other parts of New York State, outside of NYC (n = 35); Illinois (n = 12); Arizona (n = 7); Texas (n = 7); Washington, DC (n = 6); Maryland (n = 6); Wisconsin (n = 6) and Pennsylvania (n = 4). Mean household size across the sample was 3.19 individuals (SD = 3.41) and the majority of respondents (72.2%) reported that they resided with a partner, family, or roommates.

3.2. Predictors of concern regarding COVID‐19 transmission

The race of the person in the vignette image was not found to be significantly associated with COVID‐19 concern in bivariate correlations or in linear mixed effects models when controlling for other sociodemographic characteristics. As such, the race of the person in the vignette image was not included in the final regression model. As presented in Table 2, we found that regardless of the race of the image being presented in the vignette, concern regarding COVID‐19 transmission was associated with respondents' older age (b = 0.029, p < 0.001), residing in NYC (b = 0.556, p = 0.009), being heterosexual (b = 1.075, p < 0.001), having higher levels of education, that is, completion of a Bachelor's degree (b = 1.10, p = 0.033) or graduate degree (b = 1.78, p < 0.001), and the person in the vignette being unmasked (b = 0.822, p < 0.001). As shown in Table 2, the strongest predictor amongst all variables was mask status; encountering an unmasked individual in the vignette was associated with significantly higher levels of concern regarding COVID‐19 transmission (b = 0.556, p = 0.009). Other sociodemographic variables that did not have a statistically significant bivariate correlation with concern regarding COVID‐19 transmission were not included in the final linear mixed effects model.

Table 2.

Predictors of COVID‐19 concern (N = 567)

Variable Unstandardized coefficient (b) Standard error p Value
Constant 6.722 0.604 0.000
Race of participant
White Ref – –
Black 0.491 0.521 0.346
Asian 1.272 0.594 0.032
Unmasked image 0.556 0.212 0.009
Sociodemographics
NYC residency 0.822 0.054 <0.001
Age 0.029 0.008 <0.001
Partnered 0.401 0.211 0.058
Heterosexual 1.075 0.252 <0.001
Self‐rated COVID‐19 risk
Low risk −0.488 0.253 0.004
Medium risk −0.795 −0.269 0.055
High risk Ref – –
Education
High school degree or less Ref – –
Some college 0.268 0.629 0.670
Bachelor's degree 1.109 0.519 0.033
Graduate degree 1.775 0.497 <0.001
Race*Education
White*High school degree or less Ref ‐ ‐
Black*Some college −0.037 0.770 0.962
Black*Bachelor's degree −0.693 0.663 0.295
Black*Graduate degree −1.184 0.746 0.113
White*High school degree or less Ref – –
Asian*Some college −0.867 0.841 0.304
Asian*Bachelor's degree −1.582 0.663 0.027
Asian*Graduate degree −1.507 0.747 0.044
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Asian respondents were more likely than White respondents to be concerned regarding COVID‐19 (b = 1.27, p = 0.032). Individuals who self‐reported themselves to be at low risk (b = −0.488, p = 0.004) for COVID‐19 were less likely to be concerned about COVID‐19 over those who considered themselves to be high risk. We also tested for interactions between race and various sociodemographic variables. As indicated in Table 2, a statistically significant interaction was found between race and education for the Asian*Bachelor's degree coefficient (b = −1.582, p = 0.027), indicating that the difference in COVID‐19 concern between those with a Bachelor's degree and a high school degree is significantly lower for Asian respondents than for White respondents. Similarly, the Asian*Graduate degree coefficient (b = −1.507, p = 0.044) was also significant, indicating that the difference in concern scores between those with a graduate degree and a high school degree was significantly lower for Asian respondents than for White respondents. Finally, we also tested for interactions between sexual orientation and gender identity. Because none of the interaction terms were significant in controlled models predicting COVID‐19 concern, we did not ultimately include interaction terms for sexual orientation*gender identity in the final regression model.

As an effect size measure, we compared three models: the null model, random slope model, and random intercept model for goodness of fit, using the likelihood ratio test. As presented in Table 3, both the random slope model (log‐likelihood ratio = 319.60; p < 0.0001) and the random intercept model (log‐likelihood ratio = 1419.26; p < 0.0001) had a statistically significantly better fit than the null model. We next compared the random slope model and the random intercept model to each other. The results from the likelihood ratio test showed that the random slope model had a significantly better fit compared to the random intercept model. This means that the effect of mask status on concern scores had different slopes among subjects when controlling for other variables (log‐likelihood ratio = 1099.97; p < 0.0001). Given that this was a linear mixed effects model, we followed guidelines for statistical analysis that were based on methods developed by Rights and Sterba (2019). In summary, 13% of the total concern score variance in the final model was explained by all predictors via fixed slopes. Predictors explained 12.79% via random slope variation/co‐variation. Subject means (i.e., cluster‐specific means) via random intercept variation explained 53.42% of the outcome variance.

Table 3.

Comparing goodness of fit of null model, random intercept model, and random slope model

Model comparison Model AIC BIC Log likelihood Likelihood ratio p Value
Random intercept model versus random slope model Random intercept model 19,693.26 19,827.99 −9825.63
Random slope model 18,597.29 18,744.85 −9275.65 1099.97 <0.0001
Null model versus random slope model Null model 19,915.79 19,935.04 −9954.90
Random slope model 19,632.19 19,766.85 −9795.10 319.60 <0.0001
Null model versus random intercept model Null model 19,915.79 19,935.04 −9954.90
Random Intercept model 18,536.53 18,684.01 −9245.27 1419.26 <0.0001
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4. DISCUSSION

Contrary to our hypotheses, the race of the person in the presented image was not found to be statistically significantly associated with COVID‐19 concern. This could be because the questions within the vignette inquired about multiple aspects of participants' perceptions, including mask status and the social context of encountering a customer at a local corner store/bodega, potentially conflating the direct effects of race. The context of the vignette may also have had an impact on the responses we received. Previous research has shown that visiting a grocery store was a context that was most likely to prompt mask use (Darling et al., 2021), so respondents may have been primed for expectations to wear a mask within such a setting. Respondents in our study were most concerned about COVID‐19 transmission when in contact with an individual who was unmasked. This finding is consistent with Krishna et al. (2021) study in which respondents reported their preference in spending time with mask‐wearing individuals and consequentially responded more positively toward them. It is also possible that respondents reacted differently to an animated figure versus a photo of a real person or an interaction in real life.

Older adults were more at risk for being severely affected by COVID‐19 as indicated by their greater risk for COVID‐19 infection. Identifying as heterosexual was associated with a higher concern of COVID‐19 in our study, contrary to emerging research that indicates that sexual minority participants have been more fearful of COVID‐19 and had higher risk perceptions and anxiety about potentially spreading COVID‐19 over heterosexual participants (Baumel et al., 2021; Price et al., 2022; Solomon et al., 2021). Our findings may be skewed by the smaller proportion of respondents who did not identify as heterosexual in our sample. Further longitudinal or qualitative research is needed to fully explore the association between sexual orientation and COVID‐19 concern.

Our findings are consistent with prior research indicating increased COVID‐19 concern amongst Asian Americans. Previous research suggests that Asian Americans perceived a higher level of fear regarding COVID‐19 (Chen et al., 2021; Niño et al., 2021) and were more likely to support mask mandates over Black respondents (Rahman et al., 2022). Their concerns may be driven by perceived experiences of racial discrimination and higher degrees of COVID‐related stress among Asian Americans (Azhar et al., 2021; Exner‐Cortens et al., 2022).

Additionally, we found that New Yorkers were more likely to be more concerned over COVID‐19 over those not living in NYC. This finding is consistent with the elevated risks for infection associated with living in cities with heightened prevalence and crowded living situations (Hamidi & Hamidi, 2021). Transmission concerns and social distancing were associated with greater odds of psychological distress for New Yorkers during the pandemic (Cornelius et al., 2021). The respondents outside of NYC were distributed across the country, but were most concentrated in other parts of New York State, California, and Illinois—regions that had outbreaks of COVID‐19 that peaked significantly later than the initial NYC outbreaks in Summer 2020 when we had collected this data. The urgency, proximity, and gravity of the COVID‐19 pandemic in NYC at that time are likely to have been associated with higher levels of concern regarding COVID‐19 transmission than in other geographic areas of the country. Similarly, during the stay‐at‐home orders in Italy, another location that had experienced high COVID‐19 incidence very early in the global pandemic, previous psychopathology predicted severe COVID‐19 concern, anxiety, and PTSD symptoms in pregnant women (Ravaldi et al., 2020). Parents, and especially mothers, were found to be one of the most concerned groups in regard to concern regarding COVID‐19 transmission, regardless of age (Korajlija & Jokic‐Begic, 2020). Similar to our own findings regarding elevated concern among those who considered themselves to be high risk, those with chronic health conditions expressed greater concern and safety behavior than healthy participants (Korajlija & Jokic‐Begic, 2020).

In summary, requiring face masks in public spaces has been an important tool in slowing the spread of COVID‐19 within the US and globally (Howard et al., 2021) and should remain an important area for research inquiry. Given the continued relevance of controlling the COVID‐19 pandemic, understanding predictors of concern regarding COVID‐19 transmission can help public health policymakers to better prepare for future emerging infectious disease outbreaks, especially as mask mandates have largely been retracted in the US. Clinicians and public health practitioners may utilize these findings to be more cognizant of varying concerns regarding COVID‐19 transmission among the public without reinforcing racialized stigma. Our study ultimately sought to inform the need for sensitive health messaging regarding COVID‐19 that does not perpetuate discrimination and xenophobia against racial/ethnic and sexual/gender minorities.

4.1. Limitations

One of the most salient limitations to our data analysis is the fact that we used repeated measures across the same subjects. When repeated measures are used on the same subjects, care must be taken in choosing the indices which are to be used to summarize the measurements or erroneous conclusions may be reached (Bland & Altman, 1994; Oldham, 1962). This is because the variability of measurements based on different subjects is usually greater than the variability of measurements based on the same subject, leading to strong correlations between findings. We did correct this effect in our statistical analyses. However, as participants reviewed and responded to each of the eight images, they may have started to indicate the same response to each image, as a result of repetition, boredom, or a desire to complete the survey quickly. This may be why we did not find statistically significant differences for COVID‐19 concern by image race in our study. In retrospect, having random assignment to view only one of the images to participants would have been a better strategy to identify differences in response by race/ethnicity. Given these methodological limitations, we caution against interpreting our results to mean that the race/ethnicity of the person being encountered in the vignette/image is irrelevant to subjects' concern regarding COVID‐19 transmission.

Another confounder to our study findings is social desirability bias. Due to self‐presentation concerns, respondents are likely to underreport socially undesirable activities and overreport socially desirable ones (Krumpal, 2013), including attitudes that may be interpreted to be racist or prejudicial towards racial/ethnic or religious minority communities. In terms of external validity, our sample included respondents from all over the US. However, we did not stratify sampling to ensure proportionate representation across states. Given this, the generalizability of our findings as a nationally representative sample may be somewhat limited.

Lastly, there may now be stronger measures for concerns regarding COVID‐19 transmission. At the time of data collection, validated measures for COVID‐19 concern were not available. A recent, three‐item measure of COVID‐19 concern relies on notion of compulsive checking and perceived danger regarding the COVID‐19 pandemic (Johnson et al., 2021). However, this measure appears to rely more heavily on notions of obsessiveness or compulsiveness over heightened vulnerability, based on health or other risk factors. Future research regarding concern for COVID‐19 concern or other infectious disease outbreaks, may incorporate or adapt these measures.

5. CONCLUSION

Our findings underscore the importance of sociodemographic factors in predicting concern regarding COVID‐19 transmission. Being unmasked was the strongest predictor for increased concern regarding COVID‐19. Older people, those who resided in NYC, people with higher levels of education, and those with a higher degree of self‐reported COVID‐19 risk were more likely to be concerned regarding COVID‐19 transmission. Asian respondents were found to be more likely than White respondents to be concerned regarding COVID‐19 transmission. The race of the person being encountered in the vignette image was not significantly associated with concern regarding COVID‐19 transmission although these findings may be the result of social desirability bias or methodological limitations. Taken together, these results highlight the importance of acknowledging interactions between race, mask status, and residency in predicting the degree of concern regarding COVID‐19 transmission. These findings may be useful in the design of future public health policies and programs for emerging outbreaks in infectious disease.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

PEER REVIEW

The peer review history for this article is available at https://publons.com/publon/10.1002/jcop.22953

ACKNOWLEDGMENT

This study was supported by funds through the Fordham University Graduate School of Social Service.

Azhar, S. , Rahman, R. , Wernick, L. J. , Tripathi, S. , Cohen, M. , & Maschi, T. (2022). Race, masks, residency and concern regarding COVID‐19 transmission. Journal of Community Psychology, 1–20. 10.1002/jcop.22953

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available on request from the corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author.

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