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The Effect of COVID-19 Endemicity on the Mental Health of Health Workers

      Abstract

      Objectives

      A major surge in COVID-19 cases despite Singapore's high vaccination has strained the health care system in October 2021. Our aim was to assess and compare Healthcare Worker (HCW) mental well-being in 2021 against a previously published cohort in 2020.

      Design

      Cross-sectional survey study.

      Setting and Participants

      HCWs from 4 public hospitals and a primary health care system over a 4-week duration in 2021 coinciding with a major surge compared with a similar period in 2020.

      Methods

      A survey comprising of the Oldenburg Burnout Inventory (OLBI), Hospital Anxiety and Depression Scale (HADS), and Safety Attitudes Questionnaire (SAQ) was distributed via email. Primary endpoints were the proportion meeting OLBI thresholds for both disengagement and exhaustion and being at risk for both Anxiety and Depression using HADS. Multivariate analysis identified significant predictors among demographic, workplace, and SAQ data. Subgroup analysis of overseas HCWs was performed.

      Results

      We surveyed 1475 HCWs. Significantly more HCWs met primary outcomes using OLBI and HADS than in 2020 (84.1% and 39.6% vs 68.2% and 23.3%, respectively; P < .001). Burnout levels were uniformly high. A HADS score ≥8 in either subscale was significantly associated with meeting burnout thresholds (P < .001). Overseas HCWs (P = .002), South Asian ethnicity (P = .004), preuniversity educational qualifications (P = .026), and longer shift workhours of 8 to <12 (P = .015) and ≥12 (P = .001) were significantly associated with meeting HADS thresholds. Among overseas HCWs (n=407), seeing family more than a year ago was significantly associated with worse OLBI disengagement scores and a greater proportion meeting HADS thresholds vs seeing them within a year or being local HCWs (47.2% vs 37.2% and 35.6%, respectively; P = .001).

      Conclusions and Implications

      HCW mental health has objectively worsened between 2020 and 2021 in the pandemic’s second year. Avoiding prolonged shifts, adopting preventive mental health strategies, improving patient safety, and attention to HCWs of minority ethnicity, from overseas, and with preuniversity education may help.

      Keywords

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      Indeed, mitigating factors, such as altruism, have emerged as themes during this pandemic, although opinions regarding the extent of their protective effects have been conflicting.
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      have contributed to a paradoxical surge in cases since the start of the pandemic from less than 0.7 daily cases per 100,000 population (April to August 2020) to a record high of 58.1 (October 2021) (Figure 1). Although about 98% are asymptomatic or mild,
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      serious cases have risen exponentially from less than 0.04 daily deaths per 1,000,000 population to 1.83 and a previous high of 31 critical care cases to a current peak of 67 over the same time frame.

      Hannah R, Edouard M, Rodés-Guirao L, et al. Coronavirus pandemic (COVID-19). https://ourworldindata.org/coronavirus. Accessed October 11, 2021.

      Figure thumbnail gr1
      Fig. 1Multivariate analysis for predictors of meeting thresholds for (1) OLBI disengagement and exhaustion and (2) HADS anxiety and depression.
      At present, Singapore’s health care system is strained by a high volume of COVID-19 cases comprising individuals who are unvaccinated or have poor response despite home-based recovery being proposed as the standard of care.
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      Ng KG. Longer wait for admission with most public hospitals seeing more A&E patients, Covid-19 cases. The Straits Times. Updated September 20, 2021. https://www.straitstimes.com/singapore/health/most-public-hospitals-saw-more-ae-patients-in-past-week-compared-with-past-month. Accessed October 11, 2021.

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      The chronic, unrelenting volume of cases since the start of the pandemic combined with the continuation of restrictions have likely contributed to an exodus of health care workers from our workforce.
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      As more countries embark on this transition, it will be important to identify contributing factors to HCW mental health, well-being, and burnout in anticipation of possible strains on health care systems. In this follow-up study, we aim to compare the current prevalence of burnout and adverse mental health outcomes in HCWs with that derived from our previous study conducted in 2020 early in Singapore’s COVID-19 experience.
      • Tan B.Y.Q.
      • Kanneganti A.
      • Lim L.J.H.
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      Burnout and associated factors among health care workers in Singapore during the COVID-19 pandemic.
      Additionally, we aim to understand the effects on our HCWs from overseas.

      Methods

      We conducted a multicenter, cross-sectional study and disseminated a survey to all HCWs across 4 public hospitals and a network of primary health care centers (polyclinics) between September 19 and October 19, 2021 (Supplementary Table 1). This time frame coincided with the start of a surge in cases despite reaching milestone community vaccination levels. Health care workers surveyed comprised doctors, nurses, allied health care professionals (AHPs), administrative or managerial staff, and support staff. Support staff referred to nonclinical employees involved in hospital operations (eg, porters, housekeeping, and security staff). As cross-sectional studies are unable to assess temporal relationships between exposure and outcome, we sought to mitigate this by comparing results in an earlier study
      • Tan B.Y.Q.
      • Kanneganti A.
      • Lim L.J.H.
      • et al.
      Burnout and associated factors among health care workers in Singapore during the COVID-19 pandemic.
      collected over a similar duration from May 29 to June 24, 2020, which coincided with the tail end of the first major surge. The survey was distributed to HCWs in the same health care institutions and via the same methods as the earlier study, that is, through a link to a questionnaire platform (FormSG; GovTech, Singapore) which was disseminated via corporate email and snowball sampling by word of mouth. An email reminder was disseminated twice at the middle and toward the end of each study period. This questionnaire was worded in English, which is Singapore’s lingua franca. The first page declared the questionnaire’s aim, its voluntary and anonymous nature, and that implied consent was associated with proceeding with the survey.
      We collected basic demographic and workplace environment information data and organized respondents by categories such as (1) HCW roles, (2) gender, (3) ethnicity, (4) redeployment outside primary roles, (5) being tested for COVID-19, (6) primary site of work, (7) if work-from-home or working in offsite facilities was part of their job scope, (8) highest educational qualification, (9) number of workdays and average duration of shifts, (10) vaccination status, and (11) if they were HCWs from overseas. For redeployed HCWs, we further categorized them into (1) redeployed onsite (low risk), that is, not in direct contact with known COVID-19 cases; (2) redeployed onsite (high risk), that is, highly likely to be in direct contact with known COVID-19 cases (eg, emergency department, critical care unit); and (3) redeployed offsite to high-risk areas (eg, foreign work dormitory, community care facility, swab isolation facility).
      Responses to three validated questionnaires, that is, Oldenburg Burnout Inventory (OLBI), Safety Attitudes Questionnaire (SAQ), and Hospital Anxiety and Depression Scale (HADS) were collated. These tools have been described in our prior study.
      • Tan B.Y.Q.
      • Kanneganti A.
      • Lim L.J.H.
      • et al.
      Burnout and associated factors among health care workers in Singapore during the COVID-19 pandemic.
      The OLBI
      • Demerouti E.
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      • Kantas A.
      The convergent validity of two burnout instruments: a multitrait-multimethod analysis.
      comprises 16 positively and negatively framed questions rated on a 4-point Likert-type scale that are equally divided into 2 dimensions—exhaustion (which refers to feelings of emptiness, overwork, physical exhaustion, and a strong need for rest) and disengagement (which refers to distancing from the objects and content of one’s work) (Supplementary Table 2). An HCW was deemed to be burnt out if the mean score of both domains exceeded thresholds of ≥2.25 for exhaustion and ≥2.10 for disengagement, which have been correlated with physical symptoms.
      • Demerouti E.
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      The HADS
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      The Hospital Anxiety and Depression Scale.
      is a widely validated,
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      ,
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      self-reported questionnaire evaluating Depression and Anxiety with 7 items for each domain (Supplementary Table 3) rated on a 4-point Likert scale scored as 0, 1, 2, and 3. A score of ≤7 is normal, 8-10 is borderline abnormal, and ≥11 is abnormal. An HCW with a score ≥8 in both domains is deemed to be at risk of both depression and anxiety. The SAQ
      • Sexton J.B.
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      (Supplementary Table 4) covers 6 patient safety domains (ie, teamwork climate, safety climate, perceptions of management, job satisfaction, working conditions, and stress recognition) rated on a 5-point Likert-type scale comprising 30 core questions common to all versions of the SAQ and some additional relevant questions from the full SAQ bank. Nonclinical HCWs had the option to omit domains that were not relevant. A Safety Culture Score
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      ,
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      for each domain was calculated by the formula (Mean value of item scores within a domain – 1) × 25.
      A score of 1 is transformed to 0, 2 to 25, 3 to 50, 4 to 75, and 5 to 100. A score of ≥75 is a percentage “agree” for that domain, and a percentage agree rate (PAR) is the proportion of respondents with a percentage agree.
      Subgroup analysis was performed on HCWs from overseas as these comprised about 20% of the health care workforce in Singapore.

      National Population and Talent Division; Prime Minister's Office (Government of Singapore). Projection of Foreign Manpower Demand for Healthcare Sector, Construction Workers and Foreign Domestic Workers. Prime Minister's Office, Government of Singapore. Updated Novermber 1, 2012, https://www.strategygroup.gov.sg/images/Press%20Release%20images/PDFs/occasional-paper-projection-of-foreign-manpower-demand-healthcare-construction-foreign-domestic-workers.pdf. Accessed October 11, 2021.

      As overseas travel would mandate prolonged quarantining on return, this was disallowed unless special permission was given to preserve manpower for surge capacity, expansion of COVID treatment facilities, and higher operational tempo. We hypothesized that prolonged separation from family would have adverse mental health effects in this subgroup. We stratified HCWs from overseas based on whether they had seen their families within the last 1 year.

      Outcomes

      Our primary outcome measures were the proportions of HCWs meeting thresholds for both OLBI exhaustion and disengagement as well as HADS Anxiety and Depression. This recognizes that HCWs meeting thresholds for both domains in each scale likely demonstrated the highest burnout and adverse mental health risks. Secondary outcomes measured included mean HADS and OLBI scores for each domain as well as SAQ PARs overall and for each domain.

      Statistics

      All analyses were performed using Stata, version 17.0 (StataCorp LLC) with statistical significance set as 2-sided P <.05. Cronbach alphas and confirmatory factor analysis (utilizing root mean square error of approximation, comparative fit indices, and standardized root mean square residual
      • Vandenberg R.J.
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      ) demonstrated very good reliability and good model fit for most subscales (Supplementary Table 5).
      Multivariate logistic regressions and generalized linear models were used to evaluate for differences in binary and numerical outcomes, respectively, between the 2021 and 2020 cohorts.
      Predictors (demographic, workplace characteristics, and SAQ domain scores) for meeting thresholds for both OLBI exhaustion and disengagement domains as well as both HADS anxiety and depression were investigated using generalized linear mixed model with institution as a random effect and presented as adjusted odds ratios (ORs) with 95% CIs. As respondents comprised random samples from each institution, “Institution” was considered as a random factor (clustering effect) to account for the interinstitutional variance contribution and its impact on the P values. Forest plots are shown for the multivariate analyses (Figure 1). A subgroup analysis on HCWs from overseas has been performed (Table 1).
      Table 1Comparison of OLBI, HADS, and SAQ Among Overseas HCWs
      Local HCWs (n = 1068)Overseas HCWs
      Last Seen Family Within Last Year (n = 45; 11.1%)Last Seen Family Beyond a Year Ago (n = 362; 88.9%)
      Meeting Threshold (%)Mean (SD)Meeting Threshold (%)Mean (SD)Meeting Threshold (%)Mean (SD)
      OLBI Score
       Disengagement89.92.64 (0.51)
      P < .05.
      82.22.50 (0.46)
      P < .05.
      92.32.70 (0.50)
      P < .05.
       Exhaustion88.02.77 (0.49)91.12.71 (0.43)91.22.83 (0.48)
       Disengagement and exhaustion83.380.086.7
      HADS
       Depression44.3
      P < .05.
      7.06 (4.23)46.7
      P < .05.
      7.00 (3.58)52.8
      P < .05.
      7.65 (3.72)
       Anxiety54.9
      P < .001.
      8.50 (4.43)64.4
      P < .001.
      8.58 (3.35)66.3
      P < .001.
      9.11 (3.98)
       Depression and anxiety37.2
      P < .05.
      35.6
      P < .05.
      47.2
      P < .05.
      SAQPercentage Agree Rate (%)
      Teamwork climate43.739.544.6
      Safety climate40.236.646.9
      Stress recognition2.20.03.9
      Job satisfaction39.046.541.0
      Perceptions of management27.121.421.5
      Working conditions24.027.526.6
      Total15.117.620.6
      P < .05.
      P < .001.

      Ethics

      Ethics approval with waiver of individual participant consent was obtained from the National Healthcare Group’s Domain Specific Review Board (reference number 2020/00598).

      Results

      Survey Responses

      We had 1475 respondents (response rate 14.5%) (Table 2), with an average age of 36.4 years. Among these, 74.6% were female (1.91% were pregnant) and 67.9% were of Chinese ethnicity (the remainder were of Malay, South Asian, and Other ethnicities in roughly equal proportions). Doctors, nurses, AHPs, support staff, and administrative staff comprised 21.6%, 41.6%, 18.2%, 9.4%, and 9.1% of respondents, respectively. Further, 89.4% worked in a hospital, with the remainder working in a primary care setting. Redeployed HCWs accounted for 14.8% of respondents whereas HCWs from overseas comprised 27.6% of respondents. For highest educational qualification, degree holders and above, preuniversity (ie, associate degrees, diploma, A levels, technical college), and high school and below comprised 80.7%, 15.3%, and 4.0%, respectively. We received valid OLBI and HADS scores for all 1475 respondents, whereas 979 (66.3%) HCWs completed all 6 domains of the SAQ.
      Table 2Respondent Demographic, Work Environment Characteristics, and Baseline Measures of Emotional Well-Being
      2021, n (%)2020, n (%)P
      Total14753075
      Age, y, mean (SD)36.37 (10.04)36.94 (9.95).29
      Gender.004
       Male321 (21.8)794 (25.8)
       Female1100 (74.6)2199 (71.5)
       Not stated54 (3.7)82 (2.7)
      Ethnicity<.001
       Chinese1001 (67.9)1608 (52.3)
       Malay120 (8.1)401 (13.0)
       South Asian128 (8.7)410 (13.3)
       Others, eg, Filipino, Burmese or from Myanmar, Eurasian, Caucasian, Vietnamese158 (10.7)506 (16.5)
       Not stated68 (4.6)159 (4.9)
      Current primary place of work
       Hospital1318 (89.4)2841 (92.4)<.001
       Polyclinic or general practice157 (10.6)228 (7.41)
       Not stated0 (0)6 (0.20)
      Role<.001
       Doctor318 (21.6)458 (14.9)
       Nurse614 (41.6)1394 (45.3)
       Allied health professional269 (18.2)483 (15.7)
       Support staff, ie, cleaners, porters, technicians, security138 (9.4)491 (16.0)
       Administrative and managerial134 (9.1)247 (8.0)
       Not stated2 (0.1)2 (0.1)
      Highest education qualification<.001
       Degree and above1190 (80.7)2132 (69.3)
       Preuniversity (ie, associate degrees, diploma, A levels, technical college)226 (15.3)699 (22.7)
       High school or below59 (4.0)244 (8.0)
      Redeployment to other areas<.001
       Not redeployed1257 (85.2)2534 (82.4)
       Redeployed218 (14.8)541 (17.6)
      Within hospital, low risk81 (37.2)140 (25.9)
      Within hospital, high risk78 (35.8)245 (45.3)
      Outside of hospital43 (19.7)156 (28.8)
      Not specified2 (0.92)0 (0)
      Have you ever been infected with COVID-19?N/A
       Yes17 (1.2)Not Surveyed
       No1458 (98.8)
      COVID-19 status in the last 1 wk<.001
       Negative1400 (94.9)506 (16.5)
       Positive9 (0.6)21 (0.7)
       Do not know or not tested66 (4.5)254 (82.9)
      Vaccination statusNot ApplicableN/A
       Completed 2 doses at least1456 (98.7)
       Completed only 1 dose9 (0.61)
       Not vaccinated10 (0.68)
      Have you treated a COVID-19–positive patient in the past week?<.001
       Yes332 (22.5)462 (15.0)
       No1059 (71.8)2449 (79.6)
       Don’t know84 (5.7)164 (5.3)
      Average duration of your shift or daily work hours?<.001
       <8 h69 (4.7)299 (9.7)
       8-12 h1248 (84.6)2462 (80.1)
       ≥12 h158 (10.7)314 (10.2)
      ScalesMean (SD)Meeting Threshold, n (%)Mean (SD)Meeting Threshold, n (%)
      OLBI (n = 1475)
      Thresholds for deeming burnout for (1) OLBI disengagement ≥2.10 and (2) OLBI exhaustion ≥2.25.
       Disengagement2.65 (0.51)1331 (90.2)2.38 (0.46)2452 (79.7)<.001
       Exhaustion2.78 (0.46)1311 (88.9)2.502315 (75.3)<.001
       Meeting threshold for both disengagement and exhaustion1240 (84.1)2097 (68.2)<.001
      HADS (n = 1475)
      Thresholds for deeming risk of anxiety or depression for HADS was ≥8 in either subscale.
       Depression7.2 (4.1)685 (46.4)5.7 (3.9)979 (31.9)<.001
       Anxiety6.7 (3.2)855 (57.9)6.9 (4.0)1253 (40.7)<.001
       Meeting threshold for both depression and anxiety584 (39.6)716 (23.3)<.001
      SAQ
      PAR refers to the proportion of respondents who scored 75% or above for the Safety Culture Score in each domain.
      nMean (SD)PAR
      PAR refers to the proportion of respondents who scored 75% or above for the Safety Culture Score in each domain.
      , n (%)
      nMean (SD)PAR
      PAR refers to the proportion of respondents who scored 75% or above for the Safety Culture Score in each domain.
      , n (%)
      Total mean (n=979)97958.6 (15.8)165 (16.9)193164.0 (15.3)501 (25.9)<.001
      Teamwork climate (n=1224)122467.8 (20.6)536 (36.3)247974.4 (18.8)1386 (55.9)<.001
      Safety climate (n=1299)129967.5 (19.1)544 (36.9)252572.3 (18.1)1329 (52.7)<.001
      Stress recognition (n=1238)123820.2 (20.9)32 (2.2)250131.5 (25.7)205 (8.2)<.001
      Job satisfaction (n=1363)136364.1 (24.0)542 (36.7)272574.6 (22.3)1613 (59.2)<.001
      Perceptions of management (n=1341)134157.8 (21.0)342 (23.2)263364.1 (20.0)932 (35.4)<.001
      Working conditions (n=1232)123255.6 (21.3)306 (20.7)242866.2 (20.8)1030 (42.4)<.001
      Thresholds for deeming burnout for (1) OLBI disengagement ≥2.10 and (2) OLBI exhaustion ≥2.25.
      Thresholds for deeming risk of anxiety or depression for HADS was ≥8 in either subscale.
      PAR refers to the proportion of respondents who scored 75% or above for the Safety Culture Score in each domain.

      Comparison Between 2021 and 2020 Cohorts

      Compared to the previous study in 2020 (3075 respondents, response rate 27.2%) (Table 2), there was no significant difference in age (mean age 36.37 vs 36.94, P = .29). However, the 2021 cohort had a slightly higher proportion of females (74.6% vs 71.5%, P = .004). Additionally, there were significant differences observed in ethnic composition, primary place of work, HCW role, highest education qualification, redeployment status, latest COVID-19 testing status, recently treating a COVID-19 patient and shift duration (all P <.001).
      In the current 2021 study, the average OLBI disengagement and exhaustion scores were 2.65 and 2.78, respectively, with 90.2% and 88.9% reaching threshold in each domain and 84.1% reaching thresholds in both domains. This was significantly higher than in the 2020 cohort, where 68.2% met burnout threshold in both domains (P <.001). The HADS scores also showed a significantly higher proportion of respondents at risk of mental health issues in 2021, with 39.6% meeting thresholds for risks of both anxiety and depression vs 23.3% in 2020 (P <.001). Finally, SAQ scores also showed a significantly poorer PAR in each domain in 2021, with only 16.9% reaching PAR for the total score compared with 25.9% in 2020 (P <.001).

      Multivariate Analysis

      In the multivariate analysis (Figure 1), we identified having a HADS score of 8 or more for either the anxiety (OR 4.85, 95% CI 2.72-8.65; P = .001) or depression domains (OR 4.85, 95% CI 2.35-10.0; P <.001) to be independently associated with meeting the thresholds for both OLBI disengagement and exhaustion. Furthermore, reaching a percentage agree in the SAQ domains for job satisfaction (OR 0.13, 95% CI 0.07-0.25; P < .001) and stress recognition (OR 0.25, 95% CI 0.09-0.75; P = .014) was negatively associated with meeting burnout thresholds.
      For being at risk of both anxiety and depression, independent predictors included being HCWs of South Asian ethnicity (OR 2.13, 95% CI 1.28-3.55; P = .004), having a preuniversity educational certificate as the highest qualification (eg, diploma, A levels, technical college) (OR 3.53, 95% CI 1.16-10.7; P = .026), being an HCW from overseas (OR 1.74, 95% CI 1.23-2.45; P = .002), and working longer workhours per shift (8 to <12 hours: OR 3.21, 95% CI 1.26-8.18; P = .015; and ≥12 hours: OR 7.40, 95% CI 2.65-20.63; P = .001). In the SAQ, having a percentage agree for safety climate (OR 0.68, 95% CI 0.47-0.98; P = .041), job satisfaction (OR 0.41, 95% CI 0.28-0.59; P <.001), stress recognition (OR 0.17, 95% CI 0.04-0.79; P = .024), and working conditions (OR 0.55, 95% CI 0.36-0.84; P = .006) were negatively associated.

      Health Care Workers From Overseas

      Among 407 HCWs from overseas (Table 1), 362 (88.9%) had last seen their families more than a year ago. OLBI disengagement scores for this group were significantly higher (2.70) compared with local HCWs and HCWs from overseas who had seen their families within a year ago (2.64 and 2.50, respectively) (P = .023), whereas the percentage meeting thresholds for being at risk of depression and anxiety was higher at 47.2% vs 37.2% and 35.6%, respectively (P = .0013). There was no significant difference, however, in SAQ PARs, mean HADS scores, or the proportion meeting OLBI thresholds for both domains.

      Discussion

      Our study uniquely addresses the longitudinal impacts of a prolonged pandemic posture on HCW mental well-being by comparing outcomes in 2020 and 2021, in the face of a spike of new cases despite high population vaccination rates. We demonstrated that OLBI and HADS mean scores and proportion of HCWs meeting thresholds for burnout and being at risk of both anxiety and depression has increased significantly between 2020 and 2021. The absolute percentage of HCWs meeting these thresholds in 2021 is at a worrying level of 84.1% and 39.6% respectively as opposed to 68.2% and 23.3% in 2020. Additionally, attitudes toward patient safety have also deteriorated, with a significantly lower PAR for the total score (16.9% vs 25.9% in 2020). This is despite increased awareness and the institution of several protective policies
      • Nanda A.
      More doctors in Singapore face burnout, anxiety amid the pandemic. Straits Times.
      ,
      • Sharifi M.
      • Asadi-Pooya A.A.
      • Mousavi-Roknabadi R.S.
      Burnout among healthcare providers of COVID-19; a systematic review of epidemiology and recommendations.
      • Fessell D.
      • Cherniss C.
      Coronavirus Disease 2019 (COVID-19) and beyond: micropractices for burnout prevention and emotional wellness.
      • Blake H.
      • Bermingham F.
      • Johnson G.
      • Tabner A.
      Mitigating the psychological impact of COVID-19 on healthcare workers: a digital learning package.
      • Appelbom S.
      • Bujacz A.
      • Finnes A.
      • et al.
      The rapid implementation of a psychological support model for frontline healthcare workers during the COVID-19 pandemic: a case study and process evaluation.
      • Amanullah S.
      • Ramesh Shankar R.
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      over the last 2 years.
      When comparing independent predictors for burnout between our 2020 and 2021 cohort, only reaching threshold HADS scores for being at risk of depression and/or anxiety was common. Other predictors identified in 2020, such as being redeployed, and longer working hours per shift were no longer seen as independent predictors in our present cohort although this is likely due to uniformly high levels of burnout among different subgroups of our study population, limiting the power to detect significant differences.
      Regarding adverse mental health outcomes, South Asian ethnicity (a minority ethnic group in Singapore), longer workhours per shift, holding a preuniversity certificate as the highest education qualification, and being an HCW from overseas were independently associated with risk of anxiety and depression. Although some studies have identified people of minority ethnicity as being at risk for mental health issues,
      • Schilgen B.
      • Nienhaus A.
      • Handtke O.
      • Schulz H.
      • Mösko M.
      Health situation of migrant and minority nurses: A systematic review.
      ,
      • Gilleen J.
      • Santaolalla A.
      • Valdearenas L.
      • Salice C.
      • Fusté M.
      Impact of the COVID-19 pandemic on the mental health and well-being of UK healthcare workers.
      there is conflicting evidence
      • Prasad K.
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      • Stillman M.
      • et al.
      Prevalence and correlates of stress and burnout among U.S. healthcare workers during the COVID-19 pandemic: a national cross-sectional survey study.
      owing to poorly understood religio-cultural aspects, the role of community support, varied minority experiences in different countries, and significant intraethnic heterogeneity. Indeed, in Singapore’s multiethnic context, minorities in non-HCW populations have frequently demonstrated better self-reported mental health.
      • Lim W.Y.
      • Ma S.
      • Heng D.
      • Bhalla V.
      • Chew S.K.
      Gender, ethnicity, health behaviour & self-rated health in Singapore.
      ,
      • Vaingankar J.A.
      • Subramaniam M.
      • Abdin E.
      • et al.
      Socio-demographic correlates of positive mental health and differences by depression and anxiety in an Asian community sample.
      This has been postulated to be due to stronger family, religious, and community networks
      • Lim W.Y.
      • Ma S.
      • Heng D.
      • Bhalla V.
      • Chew S.K.
      Gender, ethnicity, health behaviour & self-rated health in Singapore.
      and contrasts against collectivist cultures with Confucian roots among those of Chinese ethnicity that prioritize social and familial harmony over open displays of emotions.
      • Vaingankar J.A.
      • Subramaniam M.
      • Abdin E.
      • et al.
      Socio-demographic correlates of positive mental health and differences by depression and anxiety in an Asian community sample.
      This reversal of trends may be due to negative impacts of the pandemic on important supportive community, religious, familial, and social networks. This is an area that warrants further study.
      Achieving a percentage agree in several SAQ domains had a statistically significant negative association with the primary outcomes. Although the causal relationship between perceptions of patient safety and burnout, depression, or anxiety is unclear, institutional focus on improving patient safety in deficient domains of the SAQ may be protective.
      • de Sire A.
      • Marotta N.
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      • et al.
      Psychological distress and work environment perception by physical therapists from southern Italy during COVID-19 pandemic: the C.A.L.A.B.R.I.A study.
      The relationship between long working hours and adverse mental health outcomes is well understood.
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      Like our previous study, shifts lasting less than 8 hours may be protective against burnout, highlighting the importance of proper work-rest cycles and prevention of prolonged shift lengths as a potential way to prevent burnout.
      Subgroup analysis of HCWs from overseas demonstrated a significant association between prolonged separation from families for longer than a year and higher HADS anxiety and depression mean scores. This supplements the scarce data pertaining to this important and vulnerable group that comprises a significant component of several countries’ HCW workforces.
      • Sidhu K.
      • Bamrah J.
      • Akhtar I.
      • John T.
      • Sood U.
      Covid-19 has added strain on overseas doctors unable to see their families.
      ,,
      • Schilgen B.
      • Nienhaus A.
      • Handtke O.
      • Schulz H.
      • Mösko M.
      Health situation of migrant and minority nurses: A systematic review.
      Finding ways to allow HCWs from overseas to travel by facilitating and prioritizing leave to return home, enabling more efficient quarantining processes (if required), ensuring completion of vaccination, and expanding psychological support may be beneficial.
      A very large proportion of our sample was fully vaccinated (98.7%) or undergoing regular SARS-CoV-2 testing (95.5%). This may be attributed to both of these being mandatory workplace requirements in the absence of valid contraindications,
      • Sokol D.
      Covid-19 vaccination should be mandatory for healthcare workers.
      high levels of vaccine acceptance in Singapore,
      • Lazarus J.V.
      • Ratzan S.C.
      • Palayew A.
      • et al.
      A global survey of potential acceptance of a COVID-19 vaccine.
      as well as a precedent for mandatory hepatitis B vaccinations
      • Wise J.
      Covid-19: is the UK heading towards mandatory vaccination of healthcare workers?.
      and opt-out semiannual influenza vaccination exercises
      • Kyaw W.M.
      • Chow A.
      • Hein A.A.
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      • Leo Y.S.
      • Ho H.J.
      Factors influencing seasonal influenza vaccination uptake among health care workers in an adult tertiary care hospital in Singapore: a cross-sectional survey.
      among HCWs. Nevertheless, this reduced the power of our study to determine the effects of these variables on our primary outcomes. The effects of these potentially protective factors should be further evaluated in settings with less HCW vaccination coverage or testing uptake either due to a lack of availability or personal preferences.
      Despite an abundance of recommendations on how to combat burnout and adverse mental health outcomes among HCWs, there is limited evidence on their efficacy in this pandemic.
      • Sharifi M.
      • Asadi-Pooya A.A.
      • Mousavi-Roknabadi R.S.
      Burnout among healthcare providers of COVID-19; a systematic review of epidemiology and recommendations.
      ,
      • Amanullah S.
      • Ramesh Shankar R.
      The impact of COVID-19 on physician burnout globally: a review.
      The objective worsening of these outcomes highlights the need for renewed efforts to combat this. This may be through the formal creation of well-resourced internal mental well-being departments dedicated to HCWs at an institutional level with appointed welfare champions spread across departments and health care roles. Our study identified HCWs from overseas and of minority ethnicity as groups vulnerable to adverse mental health outcomes, which we postulate may be due to effects of the pandemic on community support structures. As poorer HADS scores was significantly associated with higher risks of burnout, ensuring good HCW mental health may be protective
      • Farì G.
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      • Giorgio V.
      • et al.
      Impact of COVID-19 on the mental health in a cohort of Italian rehabilitation healthcare workers.
      and this can be done by increasing access to trained counseling services, encouraging regular mental well-being breaks, disseminating reminders about self-care with emphasis on adequate rest, sleep, recreation, and maintaining connections with loved ones amid hectic schedules.
      • Tng X.J.J.
      • Chew Q.H.
      • Sim K.
      Psychological sequelae within different populations during the COVID-19 pandemic: a rapid review of extant evidence.
      ,
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      Psychological and coping responses of health care workers toward emerging infectious disease outbreaks: a rapid review and practical implications for the COVID-19 pandemic.
      Policies should be enacted or reinforced at the institutional, state, and national level to guarantee the protection of rest cycles, leave taking, child and family care aspects, and manpower allocations. Factors contributory or indicative of work stress such as shift durations, patient numbers, leave taken, days off, and sick leaves should be tabulated with regular mental health surveys. Redline thresholds for escalation to senior management should be assigned. Finally, targeting deficient patient safety domains as guided by SAQ may complement the above recommendations.

      Limitations and Strengths

      Although the 2021 study adopted the same methodology and recruitment strategy as the 2020 study over a similar study duration, we unexpectedly had fewer respondents (1475 vs 3075). This may have led to a sampling bias with some differences in baseline characteristics of the respondents. Nonetheless, the distribution of respondents’ age was similar, and these differences were adjusted for when performing multivariate analysis to study the primary outcomes. Furthermore, we sampled the same population that would have faced similar changes in workplace conditions and policies between the 2 study periods. Thus, although a similar response rate with equivalent demographic factors would have been ideal, we feel that our findings remain valid. Various factors may have contributed to our reduced response rate. We postulate that HCWs had reduced ability to respond to survey invitation as workloads in 2021 were significantly higher because of a large surge in COVID-19 cases coupled with a return to prepandemic levels of non-COVID cases.
      • Iacobucci G.
      How is the pandemic affecting non-covid services?.
      ,
      • Birkmeyer J.D.
      • Barnato A.
      • Birkmeyer N.
      • Bessler R.
      • Skinner J.
      The impact of the COVID-19 pandemic on hospital admissions in the United States.
      Significantly more HCWs treated COVID-19–positive patients in our present study (22.5% vs 15.0%). Additionally, because of difficulties with predicting case trajectories, the 2020 study coincided with the tail end of the initial surge whereas the 2021 one coincided with the peak of a much larger one (Figure 2).
      Figure thumbnail gr2
      Fig. 2Daily new cases and percentage of population fully vaccinated in Singapore.
      The majority of studies in the current literature that evaluate mental health outcomes in HCWs during the COVID-19 pandemic are cross-sectional in nature, hence limiting their interpretation of causality. We believe a significant strength in our study is that we attempted to mitigate this by comparing the outcomes with our 2020 cohort. Nevertheless, longitudinal follow-up with individual subjects as part of a prospective cohort study design would have improved our understanding of how this relationship has changed with time. Additionally, mixed methods analysis can be employed to qualitatively understand other relevant factors contributing to these worrying trends.

      Conclusions and Implications

      Singapore’s paradoxical peak in COVID-19 cases despite high population vaccination rates is a cautionary message to all countries aiming to open their economies and accept COVID-19 endemicity. Furthermore, until global vaccine equality is achieved,
      • Smith A.
      Covid omicron variant linked to vaccine inequality, experts say.
      the risk of future SARS-CoV-2 variants, such as omicron, exists and guarantees that COVID-19 will remain a long-term public health concern.
      • Dyer O.
      Covid-19: Delta infections threaten herd immunity vaccine strategy.
      ,
      Scientific Advisory Group for Emergencies (Government of UK)
      Long term evolution of SARS-CoV-2, 26 July 2021. gov.uk.
      Although HCW burnout and mental health issues have been a perennial problem, it has worsened over this pandemic despite increased awareness and support. Thus, as we transit to a state of COVID endemicity, we may face a second mental health epidemic among HCWs. We urge health care systems to comprehensively audit the state of mental health among their HCWs and to continually evaluate for contributory factors to guide formal steps toward protecting them and keeping health care delivery sustainable.

      Acknowledgments

      The authors would like to acknowledge and thank Ms Dawn Sim for her assistance in the dissemination of the survey.

      Supplementary Data

      Supplementary Table 1Health Care Institutions Included in This Study
      Health InstitutionAddressBed CapacityCOVID Cases at Time of Study
      National University Hospital5 Lower Kent Ridge Rd, Singapore 119074

      6779 5555
      1239 bedsMore than 100
      Ng Teng Fong General Hospital1 Jurong East Street 21, Singapore 609606

      6716 2000
      700 bedsMore than 100
      Alexandra Hospital378 Alexandra Rd, Singapore 159964

      6472 2000
      300 beds50-100
      Institute of Mental health10 Buangkok View,

      Buangkok Green Medical Park, Singapore 539747

      6389 2000
      2010 beds24-49
      National University PolyclinicsBukit Batok Polyclinic

      50 Bukit Batok West Avenue 3

      Singapore 659164

      Choa Chu Kang Polyclinic

      2 Teck Whye Crescent

      Singapore 688846

      Clementi Polyclinic

      Blk 451 Clementi Avenue 3 #02-307

      Singapore 120451

      Jurong Polyclinic

      190 Jurong East Avenue 1

      Singapore 609788

      Pioneer Polyclinic

      26 Jurong West Street 61

      Singapore 648201

      Queenstown Polyclinic

      580 Stirling Road

      Singapore 148958
      Outpatient services
      Supplementary Table 2Oldenburg Burnout Inventory (4-Point Likert Scale)
      QuestionDomainReversed Questions
      1.I always find new and interesting aspects of my work.D
      2.There are days when I feel tired before I arrive at work.E
      3.It happens more and more often that I talk about my work in a negative way.D
      4.After work, I tend to need more time than in the past in order to relax and feel betterE
      5.I can tolerate the pressure of my work very well.E
      6.Lately, I tend to think less at work and do my job almost mechanically.D
      7.I find my work to be a positive challenge.D
      8.During my work, I often feel emotionally drained.E
      9.Over time, one can become disconnected from this type of work.D
      10.After working, I have enough energy for my leisure activities.E
      11.Sometimes I feel sickened by my work tasks.D
      12.After my work, I usually feel worn out and weary.E
      13.This is the only type of work that I can imagine myself doing.D
      14.Usually, I can manage the amount of my work well.E
      15.I feel more and more engaged in my work.D
      16.When I work, I usually feel energized.E
      D, Disengagement; E, Exhaustion.
      Supplementary Table 3Hospital Anxiety and Depression Scale
      QuestionDomainResponses & Score
      1.I feel tense or ‘wound up’AMost of the timeA lot of the timeFrom time to time, occasionallyNot at all
      3210
      2.I still enjoy the things I used to enjoyDDefinitely as muchNot quite so muchOnly a littleHardly at all
      0123
      3.I get a sort of frightened feeling as if something awful is about to happenAVery definitely and quite badlyYes, but not too badlyA little, but it doesn’t worry meNot at all
      3210
      4.I can laugh and see the funny side of thingsDAs much as I always couldNot quite so much nowDefinitely not so much nowNot at all
      0123
      5.Worrying thoughts go through my mindAA great deal of the timeA lot of the timeFrom time to time, but not too oftenOnly occasionally
      3210
      6.I feel cheerfulDNot at allNot oftenSometimesMost of the time
      0123
      7.I can sit at ease & feel relaxedADefinitelyUsuallyNot oftenNot at all
      0123
      8.I feel as if I am slowed downDNearly all the timeVery oftenSometimesNot at all
      3210
      9.I get a sort of frightened feeling like ‘butterflies’ in the stomachANot at allOccasionallyQuite oftenVery often
      0123
      10.I have lost interest in my appearanceDDefinitelyI don’t take as much care as I shouldI may not take quite as much careI take just as much care ever
      3210
      11.I feel restless as I have to be on the moveAVery much indeedQuite a lotNot very muchNot at all
      3210
      12.I look forward with enjoyment to thingsDAs much as I ever didRather less than I used toDefinitely less than I used toHardly at all
      0123
      13.I get sudden feelings of panicAVery often indeedQuite oftenNot very oftenNot at all
      3210
      14.I can enjoy a good book or radio or TV programDOftenSometimesNot oftenVery seldom
      0123
      D: Depression, A: Anxiety.
      0-7: Normal, 8-10: Borderline abnormal, 11-21: Abnormal.
      Supplementary Table 4Safety Attitudes Questionnaire (5-Point Likert Scale)
      QuestionDomainReversed Questions
      1.Nurse input is well received in this clinical area.TW
      2.In this clinical area, it is difficult to speak up if I perceive a problem with patient care.
      3.Disagreements in this clinical area are resolved appropriately (i.e., not who is right, but what is best for the patient).
      4.I have the support I need from other personnel to care for patients.
      5.It is easy for personnel here to ask questions when there is something that they do not understand.
      6.The physicians and nurses here work together as a well-coordinated team.
      7.I would feel safe being treated here as a patient.SC
      8.Medical errors are handled appropriately in this clinical area.
      9.I know the proper channels to direct questions regarding patient safety in this clinical area.
      10.I receive appropriate feedback about my performance.
      11.In this clinical area, it is difficult to discuss errors.
      12.I am encouraged by my colleagues to report any patient safety concerns I may have.
      13.The culture in this clinical area makes it easy to learn from the errors of others.
      14.I like my job.JS
      15.Working here is like being part of a large family.
      16.This is a good place to work.
      17.I am proud to work in this clinical area.
      18.Morale in this clinical area is high.
      19.When my workload becomes excessive, my performance is impaired.SR
      20.I am less effective at work when fatigued.
      21.I am more likely to make errors in tense or hostile situations.
      22.Fatigue impairs my performance during emergency situations (e.g. emergency resuscitation, seizure).
      23.Management supports my daily efforts.PM
      24.Management doesn’t knowingly compromise patient safety.
      25.Management is doing a good job.
      26.Problem personnel are dealt with constructively by our management.
      27.I get adequate, timely info about events that might affect my work, from management.
      28.The levels of staffing in this clinical area are sufficient to handle the number of patients.WC
      29.This hospital does a good job of training new personnel.
      30.All the necessary information for diagnostic and therapeutic decisions is routinely available to me.
      31.Trainees in my discipline are adequately supervised.
      32.I experience good collaboration with nurses in this clinical area.No domain
      33.I experience good collaboration with staff physicians in this clinical area.
      34.I experience good collaboration with pharmacists in this clinical area.
      35.Communication breakdowns that lead to delays in delivery of care are common.
      36.My suggestions about safety would be acted upon if I expressed them to management.
      JS, Job satisfaction; PM, Perceptions of management; SC, Safety culture; SR, Stress recognition; TW, Teamwork; WC, Working conditions.
      Supplementary Table 5Cronbach’s Alpha and Goodness-of-Fit Confirmatory Factor Analysis
      SubscaleCronbach Alpha (>0.7)Confirmatory Factor Analysis Model-Fit Indices
      CFI (>0.9)RMSEA (<0.06)SRMSR (<0.08)
      HADS
       Depression0.8300.9760.0610.029
       Anxiety0.8650.9820.0590.024
      OLBI
       Disengagement0.8250.9060.1110.055
       Exhaustion0.8330.9290.0970.057
      SAQ
       Teamwork0.8590.9940.0380.016
       Safety climate0.8120.9880.0470.021
       Job satisfaction0.8920.9810.1050.025
       Stress recognition0.8430.9760.1390.028
       Perception of management0.8010.9950.0430.015
       Working condition0.7680.9900.0780.019
      CFI, comparative fit indices; HADS, Hospital Anxiety and Depression Scale; OLBI, Oldenburg Burnout Inventory; RMSEA, root mean square error of approximation; SAQ, Safety Attitudes Questionnaire; SRMSR, standardized root mean square residual.

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