Participants self-identified their race with the option to specify their origin (e.g., if a participant identified as American Indian, they were able to specify Navajo Nation) although national origin categories were collapsed by race for analyses (e.g., if participant identified as Japanese, they were coded as Asian). Participants were also asked to specify whether or not they identified as Hispanic/Latinx and, if so, specify their origin (e.g., Puerto Rican). Individuals who identified with multiple racial identities were coded in accordance with the algorithm developed by the Census Bureau and used by the National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) for coding multiracial individuals with the exception of the coding of Hispanic/Latinx individuals [73]. White and Black participants were separated by Hispanic/Latinx ethnic identity, but other racial groups were not due to low frequencies, and participants who identified with another race and Hispanic/Latinx identity were coded only as the race they reported for the purposes of this study (e.g., Asian and Hispanic/Latinx were coded as Asian).

Socioeconomic status was assessed with three items. First, participants reported their annual household income on a scale from “Less than $10,000” to “$100,000” in $10,000 increments (e.g., $30,000–$39,999). For analyses, income was dichotomized such that 0 = less than $50,000 and 1 = $50,000 or higher. Participants also reported their highest level of completed education, ranging from “Did not complete high school” to “Professional degree (MD, DDS., JD, etc.) or doctoral degree (PhD).” For analyses, education was dichotomized such that 0 = less than bachelor’s degree and 1 = bachelor’s degree or higher. Finally, participants reported their subjective social status on a scale from 1 to 10 using the MacArthur Scale of Subjective Social Status [74]. Each indicator of socioeconomic status was included separately as a covariate in the full path model analysis.

Participants’ experiences of everyday discrimination were assessed using the Everyday Discrimination Scale (EDS) [61], which assesses the frequency of 9 common experiences of discrimination (e.g., threatened or harassed, treated with less respect than other people) on a scale ranging from 1 = never to 6 = almost every day. Scores across the 9 items were averaged such that higher scores indicate a greater frequency of discrimination (alpha = 0.95). For participants who reported any discrimination experiences, a tenth item assessed their primary attribution for their experiences, such as “ancestry or national origin,” “race,” and “skin color.”

Participants’ experiences of structural discrimination were assessed using the Major Experiences of Discrimination Scale (MEDS) [61], which assesses the frequency of 9 common experiences of discrimination reflective of structural racism, e.g., denial of a promotion and discouragement from continuing education. To be consistent with the EDS, participants reported the frequency of each experience on a scale ranging from 1 = never to 6 = almost every day. Scores across the 9 items were averaged such that higher scores indicate a greater frequency of discrimination (alpha = 0.96). For participants who reported any discrimination experiences, a tenth item assessed their primary attribution for their experiences, such as “ancestry or national origin,” “race,” and “skin color.”

Healthcare discrimination attributed to race and ethnicity, and income and education level was assessed with four items: (1) How often have you experienced discrimination in ability to obtain healthcare because of your race or ethnicity? (2) How often have you experienced discrimination in ability to obtain healthcare because or your income or education level? (3) How often have you experienced discrimination in how you were treated when you got care because of your race or ethnicity? (4) How often have you experienced discrimination in how you were treated when you got care because of income or education level? Race/ethnicity items are taken from the NESARC-III [73]. Items were assessed on a 5-point scale with response options ranging from 1 = never to 5 = very often and were averaged with higher scores indicating more frequent race-/ethnicity-based healthcare discrimination (alpha = 0.90).

Medical mistrust was assessed with the 7-item Medical Mistrust Index (MMI) in which participants rated their agreement with statements (e.g., “You’d better be cautious when dealing with healthcare organizations”) reflecting mistrust in medical organizations on a scale from 1 = strongly disagree to 5 = strongly agree [39]. Scores across the 7 items were averaged such that higher scores are indicative of more medical mistrust (alpha = 0.85).

Participants’ endorsement of COVID-19 conspiracy theories was assessed with an adapted version of a measure previously used to assess conspiracy beliefs related to the HIV and Ebola pandemics [31, 75]. Participants rated their agreement with four statements (e.g., “There is a cure for COVID-19, but the government isn’t telling us.”) on a scale from 1 = strongly disagree to 5 = strongly agree. Scores across the items were averaged such that higher scores are indicative of higher endorsement of COVID-19 conspiracy theories (alpha = 0.90).

Participants’ use of COVID-19 protective behaviors was assessed with a checklist of eight behavioral strategies, seven of which were provided based on the recommendations given by the CDC at the time [12] (e.g., “Avoid crowded places,” “Wear protective gear such as a face mask or gloves,” “Isolate yourself if you have symptoms,” “stay at home/avoid going out in public,” “Keep your distance from others (at least 6 feet),” “Quarantine yourself even if you don’t have symptoms,” and “Change school or work arrangements”) and an eighth option for participants to identify additional strategies used. Given that one strategy, “Isolate yourself if you have symptoms,” was only possible if participants had experienced symptoms, only endorsement of either this item or “Quarantine yourself even if you don’t have symptoms” (but not both) was included in participants’ total count score. In other words, if participants selected neither of these two options, it counted as zero checks, and if they chose either or both options, it counted as one—such that scores for COVID-19 protective behaviors could range from 0 to 7.

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