PsychologicalImpactoftheCOVID-19PandemiconHealthCareWorkersinSingapore.pdf

OBSERVATIONS: BRIEF RESEARCH REPORTS
Psychological Impact of the COVID-19 Pandemic on HealthCare Workers in Singapore
Background: In response to the coronavirus disease 2019(COVID-19) pandemic, Singapore raised its Disease OutbreakResponse System Condition alert to “orange,” the secondhighest level. Between 19 February and 13 March 2020, con-firmed cases rose from 84 to 200 (34.2 per 1 000 000 popu-lation), with an increase in patients in critical condition from 4to 11 (5.5%) and no reported deaths in Singapore (1). Under-standing the psychological impact of the COVID-19 outbreakamong health care workers is crucial in guiding policies andinterventions to maintain their psychological well-being.
Objective: To examine the psychological distress, de-pression, anxiety, and stress experienced by health careworkers in Singapore in the midst of the outbreak, and tocompare these between medically and non–medicallytrained hospital personnel.
Methods and Findings: From 19 February to 13 March2020, health care workers from 2 major tertiary institutions inSingapore who were caring for patients with COVID-19 wereinvited to participate with a self-administered questionnaire.
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In addition to information on demographic characteristics andmedical history (Table 1), the questionnaire included the val-idated Depression, Anxiety, and Stress Scales (DASS-21) andthe Impact of Events Scale–Revised (IES-R) instrument (2, 3).Health care workers included “medical” (physicians, nurses)and “nonmedical” personnel (allied health professionals,pharmacists, technicians, administrators, clerical staff, andmaintenance workers). The primary outcome was the preva-lence of depression, stress, anxiety, and posttraumatic stressdisorder (PTSD) among all health care workers (Table 2). Sec-ondary outcomes were comparison of the prevalence of de-pression, anxiety, stress, and PTSD, and mean DASS-21 andIES-R scores between medical and nonmedical health careworkers. The Pearson �2 test and student t test were used tocompare categorical and continuous outcomes, respectively,between the 2 groups. Multivariable regression was used toadjust for the a priori defined confounders of age, sex, ethnic-ity, marital status, presence of comorbid conditions, and sur-vey completion date.
Of 500 invited health care workers, 470 (94%) partici-pated in the study; baseline characteristics are shown in Table1. Sixty-eight (14.5%) participants screened positive for anxi-ety, 42 (8.9%) for depression, 31 (6.6%) for stress, and 36
(7.7%) for clinical concern of PTSD. The prevalence of anxietywas higher among nonmedical health care workers than med-ical personnel (20.7% versus 10.8%; adjusted prevalence ra-tio, 1.85 [95% CI, 1.15 to 2.99]; P = 0.011), after adjustment forage, sex, ethnicity, marital status, survey completion date, andpresence of comorbid conditions. Similarly, higher meanDASS-21 anxiety and stress subscale scores and higher IES-Rtotal and subscale scores were observed in nonmedical healthcare workers (Table 2).
Discussion: Overall mean DASS-21 and IES-R scoresamong health care workers were lower than those in the pub-lished literature from previous disease outbreaks, such as se-vere acute respiratory syndrome (SARS). A previous study inSingapore found higher IES scores among physicians andnurses during the SARS outbreak, and an almost 3 timeshigher prevalence of PTSD, than those in our study (4). Thiscould be attributed to increased mental preparedness andstringent infection control measures after Singapore’s SARSexperience.
Of note, nonmedical health care workers had higherprevalence of anxiety even after adjustment for possible con-founders. Our findings are consistent with those of a recentCOVID-19 study demonstrating that frontline nurses had sig-
Table 1. Participant Characteristics at Baseline
Characteristic Overall(n � 470)
Nonmedical Health CarePersonnel (n � 174)
Medical Health CarePersonnel (n � 296)
Sex, n (%)Female 321 (68.3) 119 (68.4) 202 (68.2)Male 149 (31.7) 55 (31.6) 94 (31.8)
Median age (IQR), y 31 (28–36) 33 (28–39) 30 (28–35)
Ethnicity, n (%)Chinese 292 (62.1) 100 (57.5) 192 (64.9)Indian 78 (16.6) 39 (22.4) 39 (13.2)Malay 42 (8.9) 20 (11.5) 22 (7.4)Other 58 (12.4) 15 (8.6) 43 (14.5)
Marital status, n (%)Single 228 (48.5) 83 (47.7) 145 (49.0)Married 232 (49.4) 85 (48.9) 147 (49.7)Divorced, separated, or widowed 10 (2.1) 6 (3.4) 4 (1.3)
Occupation, n (%)Physician 135 (28.7) — 135 (45.6)Nurse 161 (34.3) — 161 (54.4)Allied health care professional 65 (13.8) 65 (37.4) —Technician 10 (2.1) 10 (5.7) —Clerical staff 30 (6.4) 30 (17.2) —Administrator 33 (7.0) 33 (19.0) —Maintenance worker 36 (7.7) 36 (20.7) —
Medical history, n (%)Hypertension 20 (4.3) 13 (7.5) 7 (2.4)Hyperlipidemia 19 (4.0) 11 (6.3) 8 (2.7)Diabetes mellitus 5 (1.1) 1 (0.6) 4 (1.4)Asthma 26 (5.5) 10 (5.7) 16 (5.4)Eczema 35 (7.4) 10 (5.7) 25 (8.4)Migraine 58 (12.3) 27 (15.5) 31 (10.5)Cigarette smoking 17 (3.6) 16 (9.2) 1 (0.3)Ischemic heart disease 3 (0.6) 3 (1.7) 0Stroke 1 (0.2) 1 (0.6) 0Preexisting psychiatric illness 0 0 0Other comorbid conditions 27 (5.7) 11 (6.3) 16 (5.4)
IQR = interquartile range.
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nificantly lower vicarious traumatization scores than non–frontline nurses and the general public (5). Reasons for thismay include reduced accessibility to formal psychologicalsupport, less first-hand medical information on the outbreak,and less intensive training on personal protective equipmentand infection control measures.
As the pandemic continues, important clinical and policystrategies are needed to support health care workers. Ourstudy identified a vulnerable group susceptible to psycholog-ical distress. Educational interventions should target nonmed-ical health care workers to ensure understanding and use ofinfection control measures. Psychological support could in-clude counseling services and development of support sys-tems among colleagues.
Our study has limitations. First, data obtained from self-reported questionnaires were not verified with medical re-cords. Second, the study did not assess socioeconomic status,which may be helpful in evaluating associations of outcomesand tailoring specific interventions. Finally, the study was per-formed early in the outbreak and only in Singapore, whichmay limit the generalizability of the findings. Follow-up stud-ies could help assess for progression or even a potential re-bound effect of psychological manifestations once the immi-nent threat of COVID-19 subsides.
In conclusion, our study highlights that nonmedical healthcare personnel are at highest risk for psychological distressduring the COVID-19 outbreak. Early psychological interven-tions targeting this vulnerable group may be beneficial.
Benjamin Y.Q. Tan, MD*National University Health System and Yong Loo Lin School of
Medicine, National University of SingaporeSingapore
Nicholas W.S. Chew, MD*National University Health SystemSingapore
Grace K.H. Lee, MDYong Loo Lin School of Medicine, National University of
SingaporeSingapore
Mingxue Jing, MDYihui Goh, MDNational University Health SystemSingapore
Leonard L.L. Yeo, MDNational University Health System and Yong Loo Lin School of
Medicine, National University of SingaporeSingapore
Ka Zhang, MDHowe-Keat Chin, MDNational University Health SystemSingapore
Aftab Ahmad, MDFaheem Ahmed Khan, MDGanesh Napolean Shanmugam, MBBChNg Teng Fong General HospitalSingapore
Bernard P.L. Chan, MDSibi Sunny, MD
Table 2. Prevalence of Depression, Anxiety, Stress, and PTSD and Mean DASS-21 and IES-R Scores in Medical andNonmedical Health Care Personnel (n = 470)
Outcome Nonmedical Health CarePersonnel (n � 174)
Medical Health CarePersonnel (n � 296)
Crude PrevalenceRatio (95% CI)
Adjusted PrevalenceRatio (95% CI)*
Prevalence, n (%)*Depression 18 (10.3) 24 (8.1) 1.28 (0.71 to 2.28) 1.12 (0.57 to 2.19)Anxiety 36 (20.7) 32 (10.8) 1.91 (1.23 to 2.97) 1.85 (1.15 to 2.99)Stress 12 (6.9) 19 (6.4) 1.07 (0.53 to 2.16) 1.01 (0.47 to 2.19)PTSD 19 (10.9) 17 (5.7) 1.90 (1.02 to 3.56) 1.47 (0.71 to 3.04)
Crude MeanDifference (95% CI)
Adjusted MeanDifference (95% CI)†
Mean (SD) DASS-21and IES-R scores
DASS depression 3.24 (5.07) 2.54 (5.23) 0.70 (–0.27 to 1.67) 0.46 (–0.62 to 1.54)DASS anxiety 3.57 (3.91) 2.45 (4.28) 1.13 (0.35 to 1.91) 1.04 (0.15 to 1.94)DASS stress 6.10 (5.95) 3.82 (5.74) 2.29 (1.19 to 3.38) 2.15 (0.88 to 3.41)Total IES-R 9.40 (10.08) 5.85 (9.24) 3.55 (1.75 to 5.34) 3.35 (1.34 to 5.36)IES-R Intrusion 0.47 (0.51) 0.31 (0.49) 0.16 (0.07 to 0.25) 0.15 (0.04 to 0.25)IES-R Avoidance 0.46 (0.53) 0.27 (0.46) 0.19 (0.10 to 0.28) 0.18 (0.08 to 0.29)IES-R Hyperarousal 0.35 (0.45) 0.22 (0.40) 0.13 (0.05 to 0.21) 0.12 (0.04 to 0.21)
DASS-21 = Depression, Anxiety, and Stress Scales; IES-R = Impact of Events Scale–Revised; PTSD = posttraumatic stress disorder.* The DASS-21 is a 21-item system that provides independent measures of depression, stress, and anxiety with recommended severity thresholds.Cutoff scores >9, >7, and >14 indicate a positive screen for depression, anxiety, and stress, respectively. The IES-R is a 22-item self-reportinstrument that measures the subjective distress caused by traumatic events. It has 3 subscales (intrusion, avoidance, and hyperarousal), which areclosely affiliated with PTSD symptoms. A total IES-R cutoff score of 24 is used to classify PTSD as a clinical concern.† Adjusted for age, sex, ethnicity, marital status, presence of comorbid conditions, and survey completion date. The adjusted prevalence ratio wasderived from logistic regression models by calculating marginally adjusted prevalence for each group. The 95% CIs were derived by using the deltamethod. The adjusted mean difference was obtained by using linear regression.
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Bharatendu Chandra, MDJonathan J.Y. Ong, MDPrakash R. Paliwal, MDLily Y.H. Wong, BNRenarebecca Sagayanathan, BScJin Tao Chen, BNAlison Ying Ying Ng, DipHock Luen Teoh, MDNational University Health SystemSingapore
Cyrus S. Ho, MDNational University of SingaporeSingapore
Roger C. Ho, MDInstitute of Health Innovation and Technology (iHealthtech),
National University of SingaporeSingapore
Vijay K. Sharma, MDNational University Health System and Yong Loo Lin School of
Medicine, National University of SingaporeSingapore
* Drs. Tan and Chew contributed equally to this work.
Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M20-1083.
Reproducible Research Statement: Study protocol and statisticalcode: Available from Dr. Sharma (e-mail, vijay_kumar_sharma@nuhs.edu.sg). Data set: Not available.
Corresponding Author: Vijay K. Sharma, MD, Division of Neurology,National University Health System, NUHS Tower Block, Level 10, 1 EastKent Ridge Road, Singapore 119228; e-mail, vijay_kumar_sharma@nuhs.edu.sg.
This article was published at Annals.org on 6 April 2020.
doi:10.7326/M20-1083
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