Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Sep 23.
Published in final edited form as: J Affect Disord. 2025 Sep 16;393(Pt A):120342. doi: 10.1016/j.jad.2025.120342

Mental health outcomes among U.S. healthcare workers before, during, and after the 2019 global respiratory pandemic: A population-based study

Saanie Sulley a,#, David Adzrago b,#, Cameron K Ormiston b,c, Faustine Williams b
PMCID: PMC12453623  NIHMSID: NIHMS2111995  PMID: 40967410

Abstract

Background

Limited evidence exists on the persistence of anxiety and depression in the post-2019 global respiratory pandemic period among healthcare workers (HCWs). This study aims to assess anxiety and depression symptoms among HCWs during the pre-pandemic, pandemic, and post-pandemic periods—and to examine moderating effects of race and/or ethnicity, nativity, and sexual orientation.

Methods

This study analyzed data from National Health Interview Survey on a nationally representative sample of adults during pre-pandemic (N= 38,109), pandemic (N= 89,693), and post-pandemic (N= 13,895) periods in 2019–2023. The sample included HCWs in the U.S., with direct patient HCW status as the primary independent variable. The primary outcomes were self-reported anxiety and depression, measured using the Washington Group on Disability Statistics Extended Set on Functioning. Weighted logistic regression models were used to assess the associations.

Results

Direct HCWs had higher odds of anxiety and depression compared to non-direct HCWs during the pandemic, but there were no significant differences between them before or after the pandemic. Non-Hispanic White (versus racial and/or ethnic minority), sexual minority (versus heterosexual), and U.S.-born (versus foreign-born) individuals had higher odds of anxiety and depression across the three pandemic phases. Nativity was the only significant moderator, with U.S.-born HCWs having higher odds of anxiety and depression compared to foreign-born HCWs during the pandemic.

Conclusions

U.S.-born HCWs, non-Hispanic White individuals, and sexual minority remain at heightened risk for anxiety and depression, highlighting the need for targeted, long-term mental health interventions to support these vulnerable groups in the post-pandemic era.

Keywords: Healthcare workers, 2019 global respiratory pandemic, Immigration, Mental health

1. Introduction

The 2019 global respiratory pandemic has exacted a significant toll on healthcare systems and healthcare workers (HCWs) in the United States (U.S.) and worldwide (Blumenthal et al., 2020; Gupta et al., 2021; Mehta et al., 2021). The unprecedented demands of the pandemic, including overworking, burnout, shortages of personal protective equipment (PPE), and ethical dilemmas, have placed immense strain on healthcare systems that were largely unprepared for such a crisis (Rosenbaum, 2020; Wu et al., 2020). Healthcare workers were subjected to countless stressors, including poor training in the proper use of PPE, long working hours, staff shortages, lack of support, emotional burden, trauma, isolation, and fear of transmitting the virus to family and friends (Muller et al., 2020; Salazar de Pablo et al., 2020; Umbetkulova et al., 2024). These factors, coupled with unrelenting rotation schedules, have led to poor rest and sleep problems, which are known exacerbators of psychological distress (Diaz et al., 2022; Pappa et al., 2022; Pataka et al., 2022; Umbetkulova et al., 2024). The lack of preparedness of healthcare systems further contributed to the anxieties and stress faced by HCWs (Afulani et al., 2021; Chirico et al., 2020; Rink et al., 2023).

Past research highlights that the mental health impacts on HCWs were influenced by social and structural factors, which varied across sociodemographic groups (Artiga & Mattew, 2020; Salerno et al., 2020; Serafini et al., 2021). Specific vulnerabilities were reported among racial and/or ethnic minorities, sexual minorities, and non-citizen HCWs, who faced intersecting stressors such as discrimination, reduced access to mental health resources, and societal stigma (Nguyen et al., 2022; Salerno et al., 2020). Research has shown that, even before the pandemic, HCWs experienced high levels of stress and anxiety due to workplace demands, which were further exacerbated by pandemic-related challenges (Artiga & Mattew, 2020; Greenberg et al., 2020; Salerno et al., 2020; Serafini et al., 2021). While the immediate mental health impacts of the pandemic on HCWs are well-documented (Biber et al., 2022; Doukas et al., 2023; Huang et al., 2024; Padmanathan et al., 2023; Starkweather et al., 2023; Umbetkulova et al., 2024), few studies have utilized a nationally representative sample of U.S. HCWs and examined mental health disparities within specific sociodemographic groups particularly across the pandemic phases.

In this study, we assessed whether direct patient HCWs experienced pronounced anxiety and depression relative to non-direct patient HCWs. Furthermore, we examined whether factors such as race and/or ethnicity, citizenship status, nativity (U.S.-born vs. foreign-born), and sexual orientation moderated the relationship between HCW status and mental health outcomes. Additionally, we stratified the analysis by pandemic phase and HCW status to provide a comprehensive view of how HCWs’ mental health changed over time. There is an urgent need to identify which groups were most affected by pandemic stressors to inform the development of targeted mental health interventions that can better support HCWs in future public health crises.

2. Methods

2.1. Study design and study population

We combined the 2019–2023 National Health Interview Survey (NHIS) public-use datasets, which are cross-sectional survey datasets, to perform secondary data analysis. The National Center for Health Statistics at the Centers for Disease Control and Prevention (CDC) sponsors the NHIS. The U.S. Census Bureau conducts the NHIS annually among a nationally representative sample of civilian, noninstitutionalized U.S. children aged 17 years or younger and adults aged 18 years or older living in the U.S. (Keralis et al., 2023; NCHS, 2022). The NHIS collects and monitors the general health information (e.g., mental health outcomes) of the U.S. population. It uses a stratified, complex survey design. Sequentially, houses are systematically selected from counties within state boundaries, and a child and an adult are randomly selected from each household (Keralis et al., 2023; NCHS, 2022). We conducted the analysis using only the adult sample from the 2019–2023 surveys (N= 150,250). The 2023 NHIS data comprise 29,552 adults with 47.0% response rate. The 2022 NHIS data include 27,651 adults with 47.7% response rate. The 2021 NHIS data consist of 29,482 adults with 50.9% response rate. The 2020 NHIS data consist of 31,568 adults with 48.9% response rate. The 2019 NHIS data include 31,997 adults with 59.1% response rate. We categorized the surveys into pre-pandemic (2019 [N= 31,997] and quarter 1 of 2020 [N= 8,063]; total sample = 40,060), during the pandemic (quarters 2–4 of 2020 [N= 23,505], 2021 [N= 29,482], 2022 [N= 27,651], and quarters 1–2 of 2023 [N= 14,728]; combined total sample = 95,366), and post-pandemic (quarters 3–4 of 2023 [N= 14,794]) to evaluate mental health before, during, and after the pandemic. We performed a complete case analysis (pre-pandemic [N= 38,109], during the pandemic [N= 89,693], and post-pandemic [N= 13,895]) to address missing data. We used the de-identified and publicly available data and therefore no Institutional Review Board approval was required. This study followed Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines (Von Elm et al., 2007).

2.2. Measures

2.2.1. Anxiety and depression

Anxiety/depression symptoms were examined as the dependent variable. Anxiety symptoms question asks how often the participants feel worried, nervous, or anxious. Depression symptoms were also determined based on how often the participants feel depressed. The two questions were derived from the Washington Group on Disability Statistics Extended Set on Functioning (NCHS, 2022). The response options for the anxiety and depression questions included whether the participants experienced the symptoms daily, weekly, monthly, a few times a year, or never. We dichotomized the response options based on previous literature (Adzrago, Thapa, et al., 2024; Zablotsky et al., 2022). Participants experienced anxiety, depression, or anxiety/depression symptoms if they responded with daily, weekly, or monthly. Otherwise, they were considered not to have experienced the symptoms (i.e., if reported a few times a year or never). Our analysis focused on anxiety/depression symptoms, as they are the most common co-occurring mental health disorders and are often measured together to evaluate psychological distress or overall mental health (Adzrago, Walker, et al., 2024; Kalin, 2020; WHO, 2017).

2.2.2. Direct patient healthcare worker status

The main independent variable was direct patient healthcare worker (HCW) status. Direct patient HCWs include doctors, nurses, dentists, therapists, home health care workers, or emergency responders who provide direct medical care to patients. Otherwise, the participants were categorized as non-direct patient HCWs (e.g., healthcare administration, medical billers, medical record managers, IT professionals, researchers, patient advocates, or the general population).

2.2.3. Other independent variables

Other independent variables included race and/or ethnicity (Hispanic/Latino, non-Hispanic Asian, non-Hispanic Black, non-Hispanic other [Non-Hispanic Native American/Alaska Native and Native Hawaiian, or other single races] and multiple races, non-Hispanic White); citizenship status (citizen or non-citizen); nativity (born outside the U.S. or U.S.-born); and sexual orientation (gay/lesbian, bisexual, heterosexual, other [something else or don’t know]).

2.2.4. Covariates

Covariates included the contextual factors such as age, sex (female or male), marital status, level of education completed, and ratio of family income to poverty threshold (ratios greater than 1 imply higher than the poverty level). We also included the survey years in the analysis.

2.3. Statistical analysis

We examined subgroup differences in the prevalence of anxiety/depression across the independent variables, stratified by pre-pandemic, during-pandemic, and post-pandemic survey years, using chi-squared tests (Table 1). We also examined the association between anxiety/depression status and the independent variables using multivariable logistic regression analysis, stratified by pre-pandemic, during pandemic, and post-pandemic survey years (Table 2). We further assessed the moderating effects of each independent variable on the association between anxiety/depression status and direct patient healthcare worker status and presented statistically significant results as average predicted probabilities using graphs with marginsplots (Fig. 1). We adjusted for the covariates (age, sex, education, marital status, and poverty ratio) in all the models. The adjusted odds ratios (AORs) with their corresponding 95% confidence intervals (CIs) were estimated. Statistical significance was determined at p<0.05 for all the analyses. The strata and survey weights provided in NHIS data were used to account for clustering and unequal probabilities in the complex survey design (NCHS, 2022). The application of the weights also helps produce nationally representative estimations with statistical accuracy (NCHS, 2022). We also adjusted the survey weights (i.e., survey weight divided by the survey years) for the combined surveys to account for the survey year effects and produce average population estimates. All the analyses were conducted with Stata version 18.0.

Table 1.

Descriptive and bivariate analysis of anxiety/depression prevalence by pre-pandemic, pandemic, and post-pandemic

Pre-pandemic During pandemic Post-pandemic
Total Anxiety/depression Total Anxiety/depression Total Anxiety/depression
N (%a) n (%b) 95% CI p-value N (%a) n (%b) 95% CI p-value N (%a) n (%b) 95% CI p-value
Total 38,109 14,479 (38.37) (37.53–39.21) 89,693 36,688 (42.17) (41.56–42.78) 13,895 5,861 (43.64) (42.55–44.73)
Direct patient healthcare worker 0.004 p<0.001 p<0.001
No 35,139 (92.10) 13,179 (38.07) (37.21–38.94) 82,928 (92.28) 33,380 (41.50) ([40.89–42.12) 12,780 (91.72) 5,306 (43.07) (41.96–44.18)
Yes 2,970 (7.90) 1,300 (41.88) (39.36–44.45) 6,765 (7.72) 3,308 (50.12) ([48.49–51.74) 1,115 (8.28) 555 (49.96) (46.24–53.69)
Race and/or ethnicity p<0.001 p<0.001 p<0.001
Hispanic 4,955 (16.35) 1,697 (32.40) (30.56–34.29) 11,960 (16.86) 4,388 (35.52) (34.29–36.77) 2,072 (17.37) 829 (39.08) (36.52–41.70)
Non-Hispanic Black 4,088 (11.57) 1,279 (29.89) (27.53–32.37) 9,266 (11.37) 3,096 (35.18) (33.88–36.51) 1,428 (11.38) 476 (35.65) (32.29–39.15)
Non-Hispanic White 26,159 (63.40) 10,594 (42.84) [41.88–43.80) 61,098 (63.16) 26,609 (46.20) (45.50–46.90) 9,290 (62.52) 4,138 (47.28) (46.05–48.51)
Non-Hispanic Asian 1,952 (5.82) 480 (22.32) (19.81–25.06) 5,127 (5.97) 1,498 (28.30) (26.73–29.91) 777 (6.24) 253 (30.62) (27.04–34.45)
Non-Hispanic other/multi- racial 955 (2.86) 429 (40.36) (35.23–45.71) 2,242 (2.64) 1,097 (49.69) (46.87–52.52) 328 (2.50) 165 (53.15) (45.23–60.90)
Citizenship status p<0.001 p<0.001 p<0.001
No 2,395 (8.05) 617 (22.92) (20.69–25.31) 5,536 (7.99) 1,584 (27.74) (26.11–29.43) 960 (8.59) 284 (28.06) (24.88–31.47)
Yes 35,714 (91.95) 13,862 (39.72) (38.85–40.60) 84,157 (92.01) 35,104 (43.42) (42.82–44.03) 12,935 (91.41) 5,577 (45.10) (43.98–46.22)
Born in U.S. p<0.001 p<0.001 p<0.001
No 5,930 (18.16) 1,622 (25.05) (23.60–26.55) 14,172 (18.22) 4,276 (29.17) (28.11–30.24) 2,297 (18.84) 724 (30.99) (28.75–33.32)
Yes 32,179 (81.84) 12,857 (41.32) (40.42–42.23) 75,521 (81.78) 32,412 (45.07) (44.44–45.69) 11,598 (81.16) 5,137 (46.57) (45.43–47.72)
Sexual orientation p<0.001 p<0.001 p<0.001
Lesbian or gay 588 (1.58) 298 (57.34) (50.88–63.56) 1,880 (1.97) 1,068 (60.38) (57.45–63.24) 283 (2.01) 174 (65.32) (58.48–71.58)
Heterosexual 36,548 (95.50) 13,530 (37.17) (36.37–37.98) 84,816 (94.19) 33,470 (40.44) (39.84–41.04) 13,143 (93.96) 5,313 (41.47) (40.38–42.57)
Bisexual 507 (1.61) 397 (77.78) (71.12–83.27) 1,705 (2.25) 1,378 (83.78) (81.51–85.82) 304 (2.62) 249 (85.22) (80.23–89.12)
Other (something else/don’t know) 466 (1.31) 254 (54.04) (46.96–60.96) 1,292 (1.59) 772 (63.40) (59.98–66.70) 165 (1.41) 125 (79.88) (71.45–86.30)
Age p<0.001 p<0.001 p<0.001
18–44 14,352 (46.00) 6,690 (45.25) (43.89–46.61) 32,256 (45.78) 16,818 (51.14) (50.21–52.07) 4,967 (45.99) 2,813 (54.93) (53.21–56.63)
45–54 5,747 (15.97) 2,319 (38.31) (36.52–40.13) 12,762 (15.64) 5,419 (40.46) (39.36–41.57) 1,879 (15.22) 764 (39.16) (36.74–41.65)
55–64 6,951 (16.85) 2,466 (34.14) (32.64–35.68) 16,285 (16.52) 6,258 (37.00) (36.03–37.98) 2,397 (15.95) 901 (35.74) (33.65–37.88)
≥65 11,059 (21.18) 3,004 (26.83) (25.61–28.10) 28,390 (22.06) 8,193 (28.64) (27.95–29.33) 4,652 (22.84) 1,383 (29.40) (27.90–30.94)
Sex p<0.001 p<0.001 p<0.001
Female 20,549 (51.73) 8,830 (44.25) (43.17–45.32) 48,639 (51.38) 22,493 (48.21) (47.43–48.99) 7,630 (50.97) 3,594 (49.42) (47.93–50.91)
Male 17,560 (48.27) 5,649 (32.07) (30.96–33.20) 41,054 (48.62) 14,195 (35.78) (35.09–36.48) 6,265 (49.03) 2,267 (37.63) (36.21–39.06)
Education p<0.001 p<0.001 p<0.001
High school graduate or less 13,239 (39.62) 4,796 (35.67) (34.35–37.00) 29,225 (37.99) 10,734 (38.03) (37.15–38.91) 4,748 (37.23) 1,791 (39.17) (37.53–40.84)
Technical or some college 11,247 (31.20) 4,442 (40.72) (39.18–42.28) 25,341 (29.05) 10,642 (44.63) (43.71–45.56) 3,881 (29.46) 1,680 (46.28) (44.30–48.26)
College/master’s degree 12,276 (26.35) 4,734 (39.63) (38.34–40.94) 31,611 (29.84) 13,767 (44.69) (43.88–45.51) 4,723 (30.03) 2,154 (46.32) (44.57–48.08)
Professional/doctorate degree 1,347 (2.82) 507 (38.49) (34.75–42.38) 3,516 (3.12) 1,545 (45.53) (43.47–47.60) 543 (3.29) 236 (46.08) (41.19–51.04)
Marital status p<0.001 p<0.001 p<0.001
Divorced 6,086 (11.54) 2,465 (40.60) (38.69–42.53) 14,046 (10.75) 5,984 (44.09) (42.95–45.24) 2,242 (10.98) 928 (43.27) (40.65–45.94)
Separated 615 (1.35) 277 (45.05) (39.01–51.25) 1,419 (1.39) 610 (40.25) (36.94–43.65) 221 (1.30) 100 (43.55) (36.25–51.13)
Widowed 3,902 (6.23) 1,238 (33.58) (31.35–35.88) 9,295 (6.02) 3,080 (35.85) (34.49–37.24) 1,535 (6.35) 521 (35.92) (32.93–39.03)
Married/living with partner 18,085 (52.29) 6,138 (33.76) (32.72–34.82) 42,521 (52.20) 15,683 (37.22) (36.56–37.89) 6,310 (50.89) 2,385 (37.95) (36.57–39.35)
Single/never married 9,421 (28.60) 4,361 (46.62) (44.90–48.35) 22,412 (29.64) 11,331 (51.56) (50.46–52.65) 3,587 (30.48) 1,927 (54.87) (52.79–56.92)
Poverty ratio (Mean ± standard deviation) 4.02 ± 2.24 3.83 ± 2.0 (3.74–3.92) p<0.001 4.18 ± 2.65 4.10 ± 2.61 (4.03–4.17) p<0.001 4.17 ± 2.10 4.04 ± 2.03 (3.93–4.14) p<0.001
Survey year 0.989 p<0.001 0.657
2019 30,429 (49.77) 11,576 (38.37) (37.57–39.18) NA NA NA NA NA NA
2020 quarter 1 7,680 (50.23) 2,903 (38.36) (37.00–39.74) NA NA NA NA NA NA
NA NA NA
2020 quarters 2–4 NA NA NA 22,208 (24.82) 8,714 (40.03) (39.02–41.04) NA NA NA
2021 NA NA NA 27,839 (25.01) 11,420 (41.69) (40.83–42.57) NA NA NA
2022 NA NA NA 25,875 (24.93) 10,758 (43.45) (42.61–44.29) NA NA NA
NA NA NA NA NA NA
2023 quarters 1–2 NA NA NA 13,771 (25.25) 5,796 (43.48) (42.41–44.56) NA NA NA
2023 quarter 3 NA NA NA NA NA NA 6,966 (49.87) 2,941 (43.41) (41.97–44.87)
2023 quarter 4 NA NA NA NA NA NA 6,929 (50.13) 2,920 (43.86) (42.37–45.36)
Open in a new tab

Total N (%a) = column percent, n (%b) = row percent.

Pre-pandemic (unweighted n= 38,109 and weighted N= 238,476,722).

During pandemic (unweighted n= 89,693 and weighted N= 238,663,263).

Post-pandemic (unweighted n= 13,895 and weighted N= 242,311,718).

NA = not applicable.

Table 2.

Multivariable logistic regression analysis of anxiety/depression symptoms by pre-pandemic, pandemic, and post-pandemic

Pre-pandemic During pandemic Post-pandemic
AOR (95% CI) AOR (95% CI) AOR (95% CI)
Direct patient healthcare worker
No 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Yes 0.92 (0.82–1.03) 1.07* (1.01–1.15) 1.02 (0.87–1.20)
Race and/or ethnicity
Hispanic 0.64*** (0.58–0.72) 0.62*** (0.58–0.66) 0.71*** (0.62–0.83)
Non-Hispanic Black 0.44*** (0.39–0.50) 0.51*** (0.48–0.55) 0.50*** (0.43–0.59)
Non-Hispanic White 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Non-Hispanic Asian 0.45*** (0.38–0.54) 0.51*** (0.46–0.56) 0.52*** (0.42–0.64)
Non-Hispanic other/multiracial 0.72* (0.55–0.95) 0.86* (0.76–0.98) 0.85 (0.58–1.25)
Citizenship status
No 0.66*** (0.55–0.80) 0.74*** (0.68–0.82) 0.58*** (0.46–0.73)
Yes 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Born in U.S.
No 0.71*** (0.63–0.80) 0.76*** (0.71–0.81) 0.83* (0.71–0.99)
Yes 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Sexual orientation
Lesbian or gay 1.88*** (1.46–2.41) 1.89*** (1.67–2.14) 2.12*** (1.57–2.87)
Heterosexual 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Bisexual 3.62*** (2.55–5.15) 4.44*** (3.77–5.24) 4.25*** (2.98–6.06)
Other (something else/don’t know) 1.67** (1.25–2.24) 2.13*** (1.85–2.45) 3.48*** (2.18–5.55)
Survey year
2019 1.00 [Reference] NA NA
2020 quarter 1 1.00 (0.94–1.07) NA NA
2020 quarters 2–4 NA 1.00 [Reference] NA
2021 NA 1.06* (1.01–1.11) NA
2022 NA 1.15*** (1.09–1.22) NA
2023 quarters 1–2 NA 1.16*** (1.10–1.23) NA
NA
2023 quarter 3 NA NA 1.00 [Reference]
2023 quarter 4 NA NA 1.02 (0.94–1.11)
Open in a new tab
*

p<0.05,

**

p<0.01,

***

p<0.001.

AOR= adjusted odds ratio.

Adjusted for all other factors, including age, sex, education, marital status, and poverty ratio across each model stratified by the three phases of the pandemic.

NA = not applicable.

Fig. 1.

Fig. 1.

Open in a new tab

Association between direct patient healthcare worker status and anxiety/depression during the pandemic by us-born status.

The association was adjusted for all other factors, including race/ethnicity, sexual orientation, age, sex, education, marital status, and poverty ratio. Pr, probability; US, United States. Circles represent observed average predicted probabilities; red line indicates the estimated average predicted probabilities among foreign-born group; blue line shows the observed average predicted probabilities among US-born group.

3. Results

3.1. Sample characteristics

Table 1 presents population characteristics stratified by pre-pandemic, pandemic, and post-pandemic survey years. There were similar population distributions across the pre-pandemic, during pandemic, and post-pandemic survey years. The majority of them were non-direct patient HCWs, non-Hispanic White, female, identified as heterosexual, citizen, or U.S.-born individuals. A higher proportion were 18–44 years old and had a high school diploma or less. Before the pandemic, about 1.61% identified as bisexual and 1.58% as gay/lesbian; during the pandemic, 2.25% identified as bisexual and 1.97% as gay/lesbian; and post-pandemic, 2.62% identified as bisexual and 2.01% as gay/lesbian. The prevalence of anxiety/depression was higher during the pandemic (42.17%) and post-pandemic (43.64%) than pre-pandemic (38.37%). The distributions of the covariates are provided in Supplemental Table 1.

3.2. Subgroup differences in anxiety/depression prevalence, stratified by pandemic phases

Overall, the proportion of the population subgroups with anxiety/depression was higher during the pandemic than before and after the pandemic (Table 1). In the pre-pandemic survey, higher anxiety/depression prevalence was reported among direct patient HCWs (41.88%), non-Hispanic White (42.84%), citizens (39.72%), U.S.-born (41.32%), and those who identified as bisexual (77.78%). The prevalence of anxiety/depression was not statistically different between 2019 (38.37%) and quarter 1 of 2020 (38.36%).

During the pandemic, the prevalence was higher among direct patient HCWs (50.12%), non-Hispanic other/multi race (49.69%), citizens (43.42%), U.S.-born (45.07%), and identified as bisexual (83.78%). The prevalence was similarly higher in 2022 (43.45%) and quarters 1–2 of 2023 (43.48%) than in 2021 (41.69%) and quarters 2–4 of 2020 (40.03%).

In the post-pandemic survey, those who were direct patient HCWs (49.96%), non-Hispanic other/multi race (53.15%), citizens (45.10%), U.S.-born (46.57%), and identified as bisexual (85.22%) had higher anxiety/depression prevalence. The prevalence was not different between 2023 quarter 3 (43.41%) and 2023 quarter 4 (43.86%).

3.3. Odds of anxiety/depression associated with direct patient HCWs status and sociodemographics, stratified by pandemic phases

While direct patient HCWs (vs. non-direct patient HCWs) had higher odds of experiencing anxiety/depression (AOR= 1.07, 95% CI= 1.01, 1.15) during the pandemic, there were no significant differences before and after the pandemic (Table 2). Hispanic (pre-pandemic: AOR= 0.64, 95% CI= 0.58, 0.72; during pandemic: AOR= 0.62, 95% CI= 0.58, 0.66; post-pandemic: AOR= 0.71, 95% CI= 0.62, 0.83), non-Hispanic Black (pre-pandemic: AOR= 0.44, 95% CI= 0.39, 0.50; during pandemic: AOR= 0.51, 95% CI= 0.48, 0.55; post-pandemic: AOR= 0.50, 95% CI= 0.43, 0.59), non-Hispanic Asian (pre-pandemic: AOR= 0.45, 95% CI= 0.38, 0.54; during pandemic: AOR= 0.51, 95% CI= 0.46, 0.56; post-pandemic: AOR= 0.52, 95% CI= 0.42, 0.64), and non-Hispanic other/multiracial (pre-pandemic: AOR= 0.72, 95% CI= 0.55, 0.95; during pandemic: AOR= 0.86, 95% CI= 0.76, 0.98; post-pandemic: not significant) individuals had lower odds of anxiety/depression compared to non-Hispanic White individuals.

Lower odds were also observed for non-citizens (pre-pandemic: AOR= 0.66, 95% CI= 0.55, 0.80; during pandemic: AOR= 0.74, 95% CI= 0.68, 0.82; post-pandemic: AOR= 0.58, 95% CI= 0.46, 0.73) compared to citizens, and for foreign-born persons (pre-pandemic: AOR= 0.71, 95% CI= 0.63, 0.80; during pandemic: AOR= 0.76, 95% CI= 0.71, 0.81; post-pandemic: AOR= 0.83, 95% CI= 0.71, 0.99) compared to U.S.-born persons. Bisexual (pre-pandemic: AOR= 3.62, 95% CI= 2.55, 5.15; during pandemic: AOR= 4.44, 95% CI= 3.77, 5.24; post-pandemic: AOR= 4.25, 95% CI= 2.98, 6.06) or lesbian/gay (pre-pandemic: AOR= 1.88, 95% CI= 1.46, 2.41; during pandemic: AOR= 1.89, 95% CI= 1.67, 2.14; post-pandemic: AOR= 2.12, 95% CI= 1.57, 2.87) individuals and those who reported their sexual orientation as something else/don’t know (pre-pandemic: AOR= 1.67, 95% CI= 1.25, 2.24; during pandemic: AOR= 2.13, 95% CI= 1.85, 2.45; post-pandemic: AOR= 3.48, 95% CI= 2.18, 5.55) had higher odds of anxiety/depression compared to heterosexual individuals (Table 2). While anxiety/depression was not significantly associated with pre-pandemic survey years or post-pandemic survey years, it was associated with survey years during the pandemic. During the pandemic, the odds of anxiety/depression were higher in the years 2021 (AOR= 1.06, 95% CI= 1.01, 1.11), 2022 (AOR= 1.15, 95% CI= 1.09, 1.22), and 2023 quarters 1–2 (AOR= 1.16, 95% CI= 1.10, 1.23) compared to 2020 quarters 2–4. The adjusted factors—including age, sex, education, marital status, and poverty ratio—were also associated with anxiety/depression across the three phases of the pandemic (Supplemental Table 2).

Nativity moderated the association between direct patient HCW status and anxiety/depression only during the pandemic (F [1, 662] = 5.12, p= 0.024). The probability of experiencing anxiety/depression was highest for U.S.-born direct patient HCWs while the lowest probability was observed for foreign-born direct patient HCWs, compared to their non-direct patient HCW counterparts (Fig. 1). Race and/or ethnicity, citizenship, and sexual orientation did not significantly moderate the association between direct patient HCW status and anxiety/depression before, during, and after the pandemic.

We stratified the analysis by direct patient HCW status within pre, during, and after the pandemic (Table 3). Racial and/or ethnic minority individuals (vs. non-Hispanic White individuals) had lower odds of anxiety/depression among non-direct patient HCWs and direct patient HCWs before, during, and after the pandemic. However, the difference was not statistically significant between non-Hispanic White individuals and Hispanic individuals within direct patient HCWs before and after the pandemic. Similarly, the difference between non-Hispanic White individuals and non-Hispanic other/multiracial groups was not significant within the direct patient HCWs before, during, and after the pandemic, nor within the non-direct patient HCWs after the pandemic. While the odds were lower for non-citizens (vs. citizens) within non-direct patient HCWs across all periods (i.e., before, during, and after the pandemic), no significant difference was observed for the direct patient HCWs. Foreign-born individuals (vs. U.S.-born) had lower odds of anxiety/depression only within the non-direct patient HCWs before and during the pandemic, and within the direct patient HCWs only during the pandemic. All sexual minority groups (vs. heterosexual individuals) had higher odds of anxiety/depression within both direct and non-direct patient HCWs during and after the pandemic but were not significantly different between lesbian/gay and heterosexual persons post-pandemic. No significant association was found between sexual orientation and anxiety/depression among direct patient HCWs before the pandemic. Anxiety/depression was not associated with pre- and post-pandemic survey years within non- and direct patient HCWs, but during the pandemic, the survey year was a significant factor. Higher odds were observed in 2021 (not significant within non-direct patient HCWs), 2022, and 1–2 quarters of 2023 compared to quarters 2–4 of 2020 during the pandemic within both non- and direct patient HCWs. Across the direct patient HCW status within the three phases of the pandemic, the covariates (age, sex, education, marital status, and poverty ratio) were also associated with anxiety/depression (Supplemental Table 3).

Table 3.

Multivariable logistic regression analysis of anxiety/depression, stratified by healthcare worker status and pandemic phases

Pre-pandemic During pandemic Post-pandemic
Non-direct patient healthcare worker Direct patient healthcare worker Non-direct patient healthcare worker Direct patient healthcare worker Non-direct patient healthcare worker Direct patient healthcare worker
AOR (95% CI) AOR (95% CI) AOR (95% CI) AOR (95% CI) AOR (95% CI) AOR (95% CI)
Race and/or ethnicity
Hispanic 0.64*** (0.57–0.72) 0.70 (0.49–1.01) 0.62*** (0.58–0.67) 0.59*** (0.47–0.73) 0.71*** (0.61–0.82) 0.70 (0.42–1.18)
Non-Hispanic Black 0.43*** (0.38–0.50) 0.53** (0.36–0.78) 0.52*** (0.48–0.55) 0.48*** (0.39–0.60) 0.51*** (0.43–0.61) 0.45** (0.28–0.73)
Non-Hispanic White 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Non-Hispanic Asian 0.47*** (0.39–0.56) 0.33** (0.17–0.64) 0.51*** (0.46–0.57) 0.45*** (0.34–0.60) 0.52*** (0.42–0.65) 0.43* (0.20–0.91)
Non-Hispanic other/multi- racial 0.72* (0.54–0.94) 0.76 (0.42–1.36) 0.87* (0.76–0.99) 0.85 (0.58–1.23) 0.89 (0.62–1.27) 0.60 (0.20–1.82)
Citizenship status
No 0.68*** (0.56–0.82) 0.43 (0.18–1.02) 0.73*** (0.66–0.81) 0.83 (0.57–1.21) 0.58*** (0.45–0.74) 0.59 (0.23–1.54)
Yes 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Born in U.S.
No 0.71*** (0.62–0.80) 0.78 (0.52–1.19) 0.77*** (0.72–0.83) 0.62*** (0.50–0.78) 0.85 (0.71–1.01) 0.80 (0.45–1.42)
Yes 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Sexual orientation
Lesbian or gay 1.95*** (1.50–2.55) 1.16 (0.52–2.58) 1.89*** (1.67–2.15) 1.82** (1.21–2.75) 2.10*** (1.53–2.88) 2.26 (0.86–5.95)
Heterosexual 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference] 1.00 [Reference]
Bisexual 3.97*** (2.72–5.81) 2.01 (0.88–4.59) 4.54*** (3.80–5.41) 3.52*** (2.16–5.73) 3.87*** (2.65–5.66) 10.49*** (3.74–29.40)
Other (something else/don’t know) 1.74*** (1.29–2.37) 0.97 (0.39–2.41) 2.13*** (1.85–2.46) 2.13** (1.24–3.63) 3.30*** (2.04–5.35) 9.54* (1.59–57.14)
Survey year
2019 1.00 [Reference] 1.00 [Reference] NA NA NA NA NA
2020 quarter 1 1.02 (0.95–1.09) 0.87 (0.70–1.07) NA NA NA NA NA
NA NA NA NA NA
2020 quarters 2–4 NA NA 1.00 [Reference] 1.00 [Reference] NA NA
2021 NA NA 1.05 (0.99–1.11) 1.19* (1.01–1.40) NA NA
2022 NA NA 1.15*** (1.09–1.21) 1.28* (1.06–1.54) NA NA
2023 quarters 1–2 NA NA 1.13*** (1.07–1.21) 1.54*** (1.26–1.88) NA NA
2023 quarter 3 NA NA NA NA NA 1.00 [Reference] 1.00 [Reference]
2023 quarter 4 NA NA NA NA NA 1.03 (0.94–1.12) 0.97 (0.72–1.29)
Open in a new tab
*

p<0.05,

**

p<0.01,

***

p<0.001.

AOR= adjusted odds ratio.

Adjusted for all other factors, including age, sex, education, marital status, and poverty ratio across each model stratified by healthcare worker status the three phases of the pandemic.

NA = not applicable.

4. Discussion

This study provides essential insights into the mental health of a nationally representative sample of HCWs across pre-pandemic, pandemic, and post-pandemic periods. Our findings show that the pandemic significantly increased anxiety/depression among direct patient HCWs, with these challenges persisting into the post-pandemic era. Frontline or direct patient HCWs were particularly susceptible to psychological distress due to prolonged exposure to 2019 global respiratory patients, longer working hours, and the emotional impact of witnessing high patient mortality (Diaz et al., 2022; Mehta et al., 2021). Other studies have similarly reported higher rates of anxiety and depression among nurses, emergency department staff, and other frontline workers compared to non-direct patient care workers (Alhouri et al., 2023; Biber et al., 2022; Burrowes et al., 2023; Muller et al., 2020; Wu et al., 2020). Although this study observed a slight decrease in anxiety/depression rates among direct patient HCWs in the post-pandemic period, their mental health challenges remained elevated, highlighting the need for sustained attention to their long-term psychological well-being.

Our analysis also reveals significant sociodemographic disparities in mental health outcomes, beyond overall trends. Contrary to the findings of other studies (Abrahim & Holman, 2023; Nguyen et al., 2022), we observed that non-Hispanic White direct patient HCWs reported higher rates of anxiety/depression than their racial and/or ethnic minority counterparts. While several studies have reported poorer mental health among racial and/or ethnic minority groups due to systemic racism, reduced access to mental health services, and economic disparities (Nguyen et al., 2022; Thomeer et al., 2023), our study further indicates that non-Hispanic White direct patient HCWs, especially those in direct care roles, might have experienced unique stressors. These included heightened emotional exhaustion and substantial professional pressure. Furthermore, other research shows that racial and/or ethnic minorities demonstrate increased resilience during crises, which may explain their lower self-reported levels of anxiety/depression in recent studies (Cénat et al., 2020; Nguyen et al., 2022).

Our findings further show that direct patient HCWs had higher prevalence and odds of anxiety/depression throughout all periods, with the biggest disparities occurring during the pandemic (Alhouri et al., 2023). The literature indicates that the intensity of patient care and fear of infection increase psychological distress among direct patient HCWs (Muller et al., 2020). Post-pandemic mental health outcomes showed slight improvement, but direct patient HCWs still faced higher risks, highlighting the necessity of long-term interventions and support. Our findings stress the importance of ongoing mental health surveillance and tailored interventions, especially for at-risk HCW populations.

Foreign-born direct patient HCWs had lower levels of anxiety/depression than U.S.-born direct patient HCWs, suggesting that nativity significantly moderates the relationship between HCW status and mental health outcomes. This finding aligns with existing literature that suggests U.S.-born individuals are more susceptible to societal stressors, such as pandemic-related media panic and racialized discrimination (Haro-Ramos et al., 2023). In contrast, foreign-born HCWs may exhibit greater resilience due to previous experiences of adversity, which can buffer the psychological impact of the pandemic (Nguyen et al., 2022). Studies have also highlighted that foreign-born individuals often benefit from strong community ties, which can provide emotional and practical support during crises (Cénat et al., 2020). Another potential explanation is the “healthy immigrant paradox,” a phenomenon observed in several studies (Elshahat et al., 2022; Salas-Wright et al., 2018). This finding raises questions about the potential influence of socioeconomic, cultural, or contextual factors on mental health outcomes among HCWs compared to the general U.S. immigrant population.

Sexual minority individuals, particularly bisexual persons, reported the highest rates and odds of anxiety/depression across all phases of the pandemic compared to their heterosexual peers. The societal stigma, discrimination, and social isolation experienced by sexual minorities worsened during the pandemic, consistent with minority stress theory (Meyer, 2003; Salerno et al., 2020). Studies have shown that sexual minorities, especially bisexual individuals, are at a greater risk of mental health disorders, including anxiety/depression, due to the combined impact of identity-related stress and inadequate support systems (Graham et al., 2011; Salerno et al., 2020; Velasco et al., 2024). The post-pandemic period saw the continuation of mental health disparities among sexual minority healthcare workers, as observed in this study, further emphasizing the importance of tailored interventions to support this vulnerable population of HCWs.

4.1. Limitations and future directions

Even though our study provides valuable insights into the mental health of HCWs during the 2019 global respiratory pandemic and highlights the need for targeted interventions to support this critical workforce, it has some limitations. The cross-sectional nature of our study limits our ability to establish causality between the identified factors and anxiety/depression symptoms. The self-reported nature of the data makes it susceptible to recall bias with potential under- or overestimation of health behaviors or outcomes. Also, the findings may not be generalizable to HCWs in other countries or regions with different healthcare systems and cultural contexts. Another limitation is that we combined all direct patient HCWs into one group, which obscures heterogeneity. Moreover, the non-direct HCWs in this study included HCWs and the general population who do not provide direct medical care to patients. Finally, anxiety and depression are complex, multifaceted states or constructs and therefore the single item measure may not have captured the full scope of these constructs. Thus, the single item could have low construct validity, reduced sensitivity, and inability to measure internal consistency. Longitudinal studies are needed to better understand the temporal relationship between these factors and mental health outcomes. Future studies could benefit from incorporating objective measures or clinical assessments of mental health.

5. Conclusions

This study contributes to a deeper understanding of the mental health impacts of the 2019 global respiratory pandemic on U.S. HCWs by examining anxiety/depression rates across key pandemic phases and identifying differences among sociodemographic subgroups. The findings emphasize the importance of demographic-specific and role-specific interventions to support direct patient HCWs’ mental health and well-being. Future research should continue to examine sociodemographic moderators and validate these findings in diverse healthcare settings to expand our understanding of the factors contributing to psychological resilience among HCWs.

Supplementary Material

Supplementary material

Highlights.

  • Direct patient healthcare workers had higher anxiety/depression prevalence before, during, and post-pandemic than non-direct patient healthcare workers

  • US citizens had higher anxiety/depression prevalence before, during, and post-pandemic than non-citizens

  • US-born individuals had higher anxiety/depression prevalence before, during, and post-pandemic than foreign-born individuals

  • US-born direct and non-direct patient healthcare workers had higher probabilities of experiencing anxiety/depression during the pandemic than their foreign-born counterparts

Acknowledgments

This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.

Funding

This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) are considered Works of the United States Government. The findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.

Footnotes

Declaration of competing interests

The authors declare that they have nothing to declare.

Availability of data and materials

All data in this study are publicly available online at https://www.cdc.gov/nchs/nhis/index.html.

References

  1. Abrahim HL, & Holman EA (2023). A scoping review of the literature addressing psychological well-being of racial and ethnic minority nurses during the COVID-19 pandemic. Nursing Outlook, 71(1), 101899. 10.1016/j.outlook.2022.11.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Adzrago D, Thapa K, Rajbhandari-Thapa J, Sulley S, & Williams F (2024). Influence of biopsychosocial factors on self-reported anxiety/depression symptoms among first-generation immigrant population in the U.S. BMC Public Health, 24(1), 819. 10.1186/s12889-024-18336-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Adzrago D, Walker TJ, & Williams F (2024). Reliability and validity of the Patient Health Questionnaire-4 scale and its subscales of depression and anxiety among US adults based on nativity. BMC Psychiatry, 24(1), 213. 10.1186/s12888-024-05665-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Afulani PA, Gyamerah AO, Nutor JJ, Laar A, Aborigo RA, Malechi H, Sterling M, & Awoonor-Williams JK (2021). Inadequate preparedness for response to COVID-19 is associated with stress and burnout among healthcare workers in Ghana. PLoS One, 16(4), e0250294. 10.1371/journal.pone.0250294 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Alhouri A, Abu Shokor M, Marwa K, Sharabi A, Mohammad Nazir Arrouk D, Al Houri FN, & Al Houri H (2023). COVID-19 and Its Impact on Healthcare Workers: Understanding Stigma, Stress, and Quality of Life. Cureus, 15(4), e37846. 10.7759/cureus.37846 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Artiga S, & Mattew R (2020). Health and Financial Risks for Noncitizen Immigrants due to the COVID-19 Pandemic. https://www.kff.org/report-section/health-and-financial-risks-for-noncitizen-immigrants-due-to-the-covid-19-pandemic-summary/
  7. Biber J, Ranes B, Lawrence S, Malpani V, Trinh TT, Cyders A, English S, Staub CL, McCausland KL, Kosinski M, Baranwal N, Berg D, & Pop R (2022). Mental health impact on healthcare workers due to the COVID-19 pandemic: a U.S. cross-sectional survey study. J Patient Rep Outcomes, 6(1), 63. 10.1186/s41687-022-00467-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Blumenthal D, Fowler EJ, Abrams M, & Collins SR (2020). Covid-19 — Implications for the Health Care System. New England Journal of Medicine, 383(15), 1483–1488. 10.1056/NEJMsb2021088 [DOI] [PubMed] [Google Scholar]
  9. Burrowes SAB, Casey SM, Pierre-Joseph N, Talbot SG, Hall T, Christian-Brathwaite N, Del-Carmen M, Garofalo C, Lundberg B, Mehta PK, Mottl-Santiago J, Schechter-Perkins EM, Weber A, Yarrington CD, & Perkins RB (2023). COVID-19 pandemic impacts on mental health, burnout, and longevity in the workplace among healthcare workers: A mixed methods study. Journal of Interprofessional Education & Practice, 32, 100661. 10.1016/j.xjep.2023.100661 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Cénat JM, Mukunzi JN, Noorishad PG, Rousseau C, Derivois D, & Bukaka J (2020). A systematic review of mental health programs among populations affected by the Ebola virus disease. J Psychosom Res, 131, 109966. 10.1016/j.jpsychores.2020.109966 [DOI] [PubMed] [Google Scholar]
  11. Chirico F, Nucera G, & Magnavita N (2020). Protecting the mental health of healthcare workers during the COVID-19 emergency. In BJPsych Int (pp. 1–2). © The Author(s) 2020. 10.1192/bji.2020.39 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Diaz F, Cornelius T, Bramley S, Venner H, Shaw K, Dong M, Pham P, McMurry CL, Cannone DE, Sullivan AM, Lee SAJ, Schwartz JE, Shechter A, & Abdalla M (2022). The association between sleep and psychological distress among New York City healthcare workers during the COVID-19 pandemic. Journal of Affective Disorders, 298, 618–624. 10.1016/j.jad.2021.10.033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Doukas A, DePierro J, Starkweather S, Sharma V, Marin DB, & Charney DS (2023). Symptom characteristics of health care workers seeking outpatient psychiatric care during the COVID-19 pandemic. Am J Ind Med, 66(6), 500–509. 10.1002/ajim.23478 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Elshahat S, Moffat T, & Newbold KB (2022). Understanding the Healthy Immigrant Effect in the Context of Mental Health Challenges: A Systematic Critical Review. J Immigr Minor Health, 24(6), 1564–1579. 10.1007/s10903-021-01313-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Graham LF, Aronson RE, Nichols T, Stephens CF, & Rhodes SD (2011). Factors Influencing Depression and Anxiety among Black Sexual Minority Men. Depress Res Treat, 2011, 587984. 10.1155/2011/587984 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Greenberg N, Docherty M, Gnanapragasam S, & Wessely S (2020). Managing mental health challenges faced by healthcare workers during covid-19 pandemic. Bmj, 368, m1211. 10.1136/bmj.m1211 [DOI] [PubMed] [Google Scholar]
  17. Gupta N, Dhamija S, Patil J, & Chaudhari B (2021). Impact of COVID-19 pandemic on healthcare workers. Ind Psychiatry J, 30(Suppl 1), S282–s284. 10.4103/0972-6748.328830 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Haro-Ramos AY, Brown TT, Deardorff J, Aguilera A, Pollack Porter KM, & Rodriguez HP (2023). Frontline work and racial disparities in social and economic pandemic stressors during the first COVID-19 surge. Health Serv Res, 58 Suppl 2(Suppl 2), 186–197. 10.1111/1475-6773.14136 [DOI] [Google Scholar]
  19. Huang J, Huang ZT, Sun XC, Chen TT, & Wu XT (2024). Mental health status and related factors influencing healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis. PLoS One, 19(1), e0289454. 10.1371/journal.pone.0289454 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kalin NH (2020). The critical relationship between anxiety and depression. In (Vol. 177, pp. 365–367): American Psychiatric Association; Washington, DC. [Google Scholar]
  21. Keralis JM, Zhang C, Cox CS, & Mirel LB (2023). A Comparison of the Mortality Experience of US Adults Estimated With the 2006–2018 National Health Interview Survey Linked Mortality Files and the Annual US Life Tables. National Health Statistics Reports(186), 1–29. [Google Scholar]
  22. Mehta S, Machado F, Kwizera A, Papazian L, Moss M, Azoulay É, & Herridge M (2021). COVID-19: a heavy toll on health-care workers. Lancet Respir Med, 9(3), 226–228. 10.1016/s2213-2600(21)00068-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Meyer IH (2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: conceptual issues and research evidence. Psychol Bull, 129(5), 674–697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Muller AE, Hafstad EV, Himmels JPW, Smedslund G, Flottorp S, Stensland SØ, Stroobants S, Van de Velde S, & Vist GE (2020). The mental health impact of the covid-19 pandemic on healthcare workers, and interventions to help them: A rapid systematic review. Psychiatry Research, 293, 113441. 10.1016/j.psychres.2020.113441 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. NCHS. (2022). National Health Interview Survey, 2021. Public-use data file and documentation. https://www.cdc.gov/nchs/nhis/data-questionnaires-documentation.htm
  26. Nguyen LH, Anyane-Yeboa A, Klaser K, Merino J, Drew DA, Ma W, Mehta RS, Kim DY, Warner ET, Joshi AD, Graham MS, Sudre CH, Thompson EJ, May A, Hu C, Jørgensen S, Selvachandran S, Berry SE, David SP,…Chan AT (2022). The mental health burden of racial and ethnic minorities during the COVID-19 pandemic. PloS one, 17(8), e0271661. 10.1371/journal.pone.0271661 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Padmanathan P, Lamb D, Scott H, Stevelink S, Greenberg N, Hotopf M, Morriss R, Raine R, Rafferty AM, Madan I, Dorrington S, Wessely S, & Moran P (2023). Suicidal thoughts and behaviour among healthcare workers in England during the COVID-19 pandemic: A longitudinal study. PLoS One, 18(6), e0286207. 10.1371/journal.pone.0286207 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Pappa S, Sakkas N, & Sakka E (2022). A year in review: sleep dysfunction and psychological distress in healthcare workers during the COVID-19 pandemic. Sleep Med, 91, 237–245. 10.1016/j.sleep.2021.07.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Pataka A, Kotoulas S, Tzinas A, Kasnaki N, Sourla E, Chatzopoulos E, Grigoriou I, & Argyropoulou P (2022). Sleep Disorders and Mental Stress of Healthcare Workers during the Two First Waves of COVID-19 Pandemic: Separate Analysis for Primary Care. Healthcare (Basel), 10(8). 10.3390/healthcare10081395 [DOI] [Google Scholar]
  30. Rink LC, Oyesanya TO, Adair KC, Humphreys JC, Silva SG, & Sexton JB (2023). Stressors Among Healthcare Workers: A Summative Content Analysis. Glob Qual Nurs Res, 10, 23333936231161127. 10.1177/23333936231161127 [DOI] [Google Scholar]
  31. Rosenbaum L (2020). The Untold Toll — The Pandemic’s Effects on Patients without Covid-19. New England Journal of Medicine, 382(24), 2368–2371. 10.1056/NEJMms2009984 [DOI] [PubMed] [Google Scholar]
  32. Salas-Wright CP, Vaughn MG, Goings TC, Miller DP, & Schwartz SJ (2018). Immigrants and mental disorders in the united states: New evidence on the healthy migrant hypothesis. Psychiatry research, 267, 438–445. 10.1016/j.psychres.2018.06.039 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Salazar de Pablo G, Vaquerizo-Serrano J, Catalan A, Arango C, Moreno C, Ferre F, Shin JI, Sullivan S, Brondino N, Solmi M, & Fusar-Poli P (2020). Impact of coronavirus syndromes on physical and mental health of health care workers: Systematic review and meta-analysis. J Affect Disord, 275, 48–57. 10.1016/j.jad.2020.06.022 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Salerno JP, Devadas J, Pease M, Nketia B, & Fish JN (2020). Sexual and Gender Minority Stress Amid the COVID-19 Pandemic: Implications for LGBTQ Young Persons’ Mental Health and Well-Being. Public Health Reports, 135(6), 721–727. 10.1177/0033354920954511 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Serafini RA, Powell SK, Frere JJ, Saali A, Krystal HL, Kumar V, Yashaswini C, Hernandez J, Moody K, Aronson A, Meah Y, & Katz CL (2021). Psychological distress in the face of a pandemic: An observational study characterizing the impact of COVID-19 on immigrant outpatient mental health. Psychiatry Research, 295, 113595. 10.1016/j.psychres.2020.113595 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Starkweather S, DePierro JM, Akhtar S, de Guillebon E, Kaplan C, Kaplan S, Ripp J, Peccoralo L, Feingold J, Feder A, Murrough JW, & Pietrzak RH (2023). Predictors of Mental Health Service Utilization among Frontline Healthcare Workers during the COVID-19 Pandemic. Int J Environ Res Public Health, 20(7). 10.3390/ijerph20075326 [DOI] [Google Scholar]
  37. Thomeer MB, Moody MD, & Yahirun J (2023). Racial and Ethnic Disparities in Mental Health and Mental Health Care During The COVID-19 Pandemic. Journal of Racial and Ethnic Health Disparities, 10(2), 961–976. 10.1007/s40615-022-01284-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Umbetkulova S, Kanderzhanova A, Foster F, Stolyarova V, & Cobb-Zygadlo D (2024). Mental Health Changes in Healthcare Workers During COVID-19 Pandemic: A Systematic Review of Longitudinal Studies. Eval Health Prof, 47(1), 11–20. 10.1177/01632787231165076 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Velasco J, Miranda-Tena A, & Sanmartín FJ (2024). Bisexual Discrimination, Internalized Binegativity and their Impact on Mental Health. Sexuality Research and Social Policy, 21(3), 1100–1111. 10.1007/s13178-024-00990-9 [DOI] [Google Scholar]
  40. Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, & Vandenbroucke JP (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. The lancet, 370(9596), 1453–1457. [Google Scholar]
  41. WHO. (2017). Depression and other common mental disorders: global health estimates.
  42. Wu D, Jiang C, He C, Li C, Yang L, & Yue Y (2020). Stressors of nurses in psychiatric hospitals during the COVID-19 outbreak. Psychiatry Research, 288, 112956. 10.1016/j.psychres.2020.112956 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Zablotsky B, Weeks JD, Terlizzi EP, Madans JH, & Blumberg SJ (2022). Assessing Anxiety and Depression: A Comparison of National Health Interview Survey Measures. Natl Health Stat Report(172), 1–17. [Google Scholar]

Associated Data

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

Supplementary Materials

Supplementary material
NIHMS2111995-supplement-Supplementary_material.docx (71KB, docx)

Data Availability Statement

All data in this study are publicly available online at https://www.cdc.gov/nchs/nhis/index.html.

RESOURCES