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OBSERVATIONS: BRIEF RESEARCH REPORTS

Psychological Impact of the COVID-19 Pandemic on Health Care Workers in Singapore

Background: In response to the coronavirus disease 2019 (COVID-19) pandemic, Singapore raised its Disease Outbreak Response System Condition alert to “orange,” the second highest 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 4 to 11 (5.5%) and no reported deaths in Singapore (1). Under- standing the psychological impact of the COVID-19 outbreak among health care workers is crucial in guiding policies and interventions to maintain their psychological well-being.

Objective: To examine the psychological distress, de- pression, anxiety, and stress experienced by health care workers in Singapore in the midst of the outbreak, and to compare these between medically and non–medically trained hospital personnel.

Methods and Findings: From 19 February to 13 March 2020, health care workers from 2 major tertiary institutions in Singapore who were caring for patients with COVID-19 were invited to participate with a self-administered questionnaire.

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Annals.org Annals of Internal Medicine • Vol. 173 No. 4 • 18 August 2020 317

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In addition to information on demographic characteristics and medical history (Table 1), the questionnaire included the val- idated Depression, Anxiety, and Stress Scales (DASS-21) and the 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, and maintenance workers). The primary outcome was the preva- lence of depression, stress, anxiety, and posttraumatic stress disorder (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 and IES-R scores between medical and nonmedical health care workers. The Pearson �2 test and student t test were used to compare categorical and continuous outcomes, respectively, between the 2 groups. Multivariable regression was used to adjust 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 Table 1. 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 anxiety was 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 for age, sex, ethnicity, marital status, survey completion date, and presence of comorbid conditions. Similarly, higher mean DASS-21 anxiety and stress subscale scores and higher IES-R total and subscale scores were observed in nonmedical health care workers (Table 2).

Discussion: Overall mean DASS-21 and IES-R scores among 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 in Singapore found higher IES scores among physicians and nurses during the SARS outbreak, and an almost 3 times higher prevalence of PTSD, than those in our study (4). This could be attributed to increased mental preparedness and stringent infection control measures after Singapore's SARS experience.

Of note, nonmedical health care workers had higher prevalence of anxiety even after adjustment for possible con- founders. Our findings are consistent with those of a recent COVID-19 study demonstrating that frontline nurses had sig-

Table 1. Participant Characteristics at Baseline

Characteristic Overall (n � 470)

Nonmedical Health Care Personnel (n � 174)

Medical Health Care Personnel (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) 0 Stroke 1 (0.2) 1 (0.6) 0 Preexisting psychiatric illness 0 0 0 Other comorbid conditions 27 (5.7) 11 (6.3) 16 (5.4)

IQR = interquartile range.

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318 Annals of Internal Medicine • Vol. 173 No. 4 • 18 August 2020 Annals.org

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nificantly lower vicarious traumatization scores than non– frontline nurses and the general public (5). Reasons for this may include reduced accessibility to formal psychological support, less first-hand medical information on the outbreak, and less intensive training on personal protective equipment and infection control measures.

As the pandemic continues, important clinical and policy strategies are needed to support health care workers. Our study identified a vulnerable group susceptible to psycholog- ical distress. Educational interventions should target nonmed- ical health care workers to ensure understanding and use of infection 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 outcomes and tailoring specific interventions. Finally, the study was per- formed early in the outbreak and only in Singapore, which may 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 health care personnel are at highest risk for psychological distress during 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 Singapore Singapore

Nicholas W.S. Chew, MD* National University Health System Singapore

Grace K.H. Lee, MD Yong Loo Lin School of Medicine, National University of

Singapore Singapore

Mingxue Jing, MD Yihui Goh, MD National University Health System Singapore

Leonard L.L. Yeo, MD National University Health System and Yong Loo Lin School of

Medicine, National University of Singapore Singapore

Ka Zhang, MD Howe-Keat Chin, MD National University Health System Singapore

Aftab Ahmad, MD Faheem Ahmed Khan, MD Ganesh Napolean Shanmugam, MBBCh Ng Teng Fong General Hospital Singapore

Bernard P.L. Chan, MD Sibi Sunny, MD

Table 2. Prevalence of Depression, Anxiety, Stress, and PTSD and Mean DASS-21 and IES-R Scores in Medical and Nonmedical Health Care Personnel (n = 470)

Outcome Nonmedical Health Care Personnel (n � 174)

Medical Health Care Personnel (n � 296)

Crude Prevalence Ratio (95% CI)

Adjusted Prevalence Ratio (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 Mean Difference (95% CI)

Adjusted Mean Difference (95% CI)†

Mean (SD) DASS-21 and 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-report instrument that measures the subjective distress caused by traumatic events. It has 3 subscales (intrusion, avoidance, and hyperarousal), which are closely 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 was derived from logistic regression models by calculating marginally adjusted prevalence for each group. The 95% CIs were derived by using the delta method. The adjusted mean difference was obtained by using linear regression.

LETTERS

Annals.org Annals of Internal Medicine • Vol. 173 No. 4 • 18 August 2020 319

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Bharatendu Chandra, MD Jonathan J.Y. Ong, MD Prakash R. Paliwal, MD Lily Y.H. Wong, BN Renarebecca Sagayanathan, BSc Jin Tao Chen, BN Alison Ying Ying Ng, Dip Hock Luen Teoh, MD National University Health System Singapore

Cyrus S. Ho, MD National University of Singapore Singapore

Roger C. Ho, MD Institute of Health Innovation and Technology (iHealthtech),

National University of Singapore Singapore

Vijay K. Sharma, MD National University Health System and Yong Loo Lin School of

Medicine, National University of Singapore Singapore

* 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 statistical code: 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 East Kent 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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