Table 1: Study Characteristics
|
Author
|
Design
|
Country
|
Participants
|
Selection method
|
Measures
|
1
|
Ahmed et al., (2020) (1)
|
Cross-sectional
|
Global
(30 countries)
|
n=650
|
Online questionnaire distributed via email and social media to dental professionals worldwide.
|
Validated questionnaire: 22 closed-ended questions divided into two sections. (Fear & Clinical practices)
|
2
|
Balakumar et al., (2020)
(2)
|
Uncontrolled before and after study.
|
UK
|
n=27
(Surgeons)
|
Pre‐ and post‐training surveys distributed to a surgical team.
|
Pre- and post-training surveys
|
3
|
H.Cai et al., (2020)
(3)
|
Cross-sectional
|
China
Hunan
|
n=534
(Frontline medical workers)
|
Questionnaires sent to frontline medical staff in Hunan province between January and March 2020.
|
Five-section questionnaire
|
4
|
W.Cai et al., (2020) (4)
|
Cross-sectional
|
China
Jiangsu Province
|
n=1521
(147 experienced in public health emergencies (PHE))
|
Health care workers recruited but method unclear.
|
SCL-90
CD-RISC
SSRS
|
5
|
Cao et al., (2020)
(5)
|
Mixed methods
|
China
Beijing
|
n=37
(16 Doctors, 19 Nurses, and
2 Technicians within a COVID-19 clinic)
|
Qualitative and Quantitative evaluations of staff in a fever clinic. Staff had been handpicked based on their ‘experience, adaptability and tenacity under pressure in past works’
|
PHQ-9
MBI
Qualitative interviews
|
6
|
Chew et al., (2020) (6)
|
Cross- sectional
|
Singapore & India
|
n=906
(480 HCW’s from a Singapore
Hospital)
|
HCWs from 5 major hospitals invited to participated in a questionnaire between Feb 2019 – April 2020.
|
DASS-21,
IES-R
Symptom questionnaire
|
7
|
Chung & Yeung, (2020) (7)
|
Cross-sectional
|
China
Hong Kong
|
n=69
(HCWs: 69/8418 full-time hospital staff)
|
Online mental health self-assessment questionnaire distributed to all hospital staff in the Hong Kong East Cluster.
|
PHQ-9
|
8
|
Huang & Zhao, (2020)
(8)
|
Cross- sectional
|
China
Nationwide
|
n=603
(31.1% HCWs)
|
Web-based survey of general population, invited via social media, random recruitment – all Chinese people using WeChat may have seen it.
|
Web-based survey.
PSQI, GAD, CES-D
|
9
|
Kang et al., (2020) (9)
|
Cross-sectional
|
China
Wuhan
|
n=994
(Doctors and Nurses)
|
Questionnaire distributed online to doctors or nurses working in Wuhan.
|
PHQ-9
GAD-7
ISI
IES-R
|
10
|
Lai et al., (2020) (10)
|
Cross-sectional
|
China
(Nationwide but 60% from
Wuhan)
|
n=1257
(Nurses and Doctors in 34 hospitals/fever clinics)
|
Hospital based survey via region-stratified 2-stage cluster sampling from Jan 29 2020 – Feb 3 2020.
|
PHQ-9
GAD
ISI
IES-R
|
11
|
Li et al., (2020) (11)
|
Cross-sectional
|
China
Wuhan
|
n=740
(214 general population and 526 Nurses)
|
Mobile app-based questionnaire of general public and nurses in Wuhan.
|
Vicarious Trauma Questionnaire (Chinese version)
|
12
|
Liang, Chen, Zheng, & Li, (2020) (12)
|
Cross-sectional
|
China
Guangdong Province
|
n=59
(23 Doctors and 36 Nurses
from COVID-19 department and
21 HCWs from other departments)
|
Questionnaire distributed to medical staff in a hospital. Method of distribution unclear.
|
SDS
SAS
|
13
|
Lu, Wang, Lin & Li, (2020) (13)
|
Cross-sectional
|
China
Fujian
|
n=2299
(2042 Medical and 257 admin staff)
|
Questionnaire survey of medical staff in a provincial hospital in Feb 2020.
|
NRS
HAMA
HAMD
|
14
|
Mo et al., (2020) (14)
|
Cross-sectional
|
China
Wuhan
|
n=180
(Nurses from Guangxi supporting COVID-19 in Wuhan)
|
Convenient sampling of nurses from Guangxi recruited to support COVID-19 work in Wuhan. 85.71% response rate of 180 nurses sampled.
|
SOS
SAS
|
15
|
Shacham et al., (2020)
(15)
|
Cross- sectional
|
Israel
|
n=338
(Dental hygienists and Dentists)
|
Dental hygienists and dentists, approached using social media, mailing lists and forums.
|
Demands Scale—Short Version
GSES
Kessler K6
|
16
|
Sun et al., (2020)
(16)
|
Qualitative
|
China
Henan (One hospital)
|
n=20
(Nurses/17 Female)
|
Purposeful sampling of nurses caring for COVID-19 patients in a hospital. Jan/Feb 2020.
|
Semi-structured interviews
|
17
|
Tan et al., (2020)
(17)
|
Cross- sectional
|
Singapore
(Two tertiary hospitals)
|
n=470
(HCWs – medical and non-medical)
|
HCWs from two major tertiary hospitals in Singapore invited to participate, Feb/March 2020
|
DASS-21
IES-R
|
18
|
Urooj et al., (2020)
(18)
|
Mixed Method
|
Pakistan
|
n=222
(134 without COVID-19 patients and
150 female)
|
Purposive sampling of 250 clinicians from a range of specialities and seniority. 222 responded (88.8%)
|
Doctors fears and expectations
|
19
|
Wang et al., (2020)
(19)
|
Cross-sectional
|
China
Wuhan
|
n=123
(HCWs in a Paediatric centre)
|
Questionnaire survey conducted at a paediatric centre in Wuhan. 50% of all HCWs responded & were included.
|
PSQI
SAS
SDS
|
20
|
Wu et al., (2020)
(20)
|
Cross-sectional
|
China
Wuhan
|
n=190
(Hubai cancer hospital – all from oncology
1:1 ratio frontline vs usual wards)
|
220 physicians and nurses from Hubai cancer hospital invited in March 2020. 190 included.
|
MBI
|
21
|
Xiao et al., (2020)
(21)
|
Cross-sectional
|
China
Wuhan
|
n=180
(54% Nurses and 45.6% Doctors from a respiratory medicine/ fever clinic)
|
Unclear how participants were sampled. All were medical staff who treated COVID-19 patients in Jan/Feb 2020.
|
SAS
GSES
SASR
PSQI
SSRS
|
22
|
Xu, Xu, Wang & Wang, (2020)
(22)
|
Longitudinal
|
China
Shanghai
|
n= 120
(Surgical staff. One hospital
split into two groups of 60
Grp 1 – Jan-Feb (outbreak period)
Grp 2 – March (non-outbreak)
|
Surgical medical staff sampled.
|
Anxiety scale
Depression score
Dream anxiety score
SF-36 scale
|
23
|
Yin & Zeng, (2020)
(23)
|
Qualitative – in-depth interviews
|
China
Wuhan
|
n= 10
(Nurses at the front-line; having cared for COVID-19 patients >1 week)
|
Purposive sampling
|
|
24
|
Zhang et al., (2020)
(24)
|
Cross -sectional
|
China
Nationwide
|
n=2182
(927 Medical HCWs; 680 Doctors and 247 Nurses,
1255 non-medical HCWs)
|
Random sampling – anyone in China >16 years were welcome to join using an online platform.
|
ISI
SCL-90-R
PHQ-4
Chinese versions
|
Measures Description
Depression: CES-D: Centre for Epidemiologic Studies Depression Scale, HAM-D: Hamilton Depression Rating Scale, PHQ-9: Patient Health Questionnaire, SCL-20: Symptom checklist depression scale, SDS: Zung Self-Rating Depression Scale,
Anxiety: GAD-7: Generalised Anxiety Disorder Questionnaire, HAM-A: Hamilton Anxiety Rating Scale, SAS: Zung Self-Rating Anxiety Scale
Stress: SOS: Stress Overload Scale
Depression & Anxiety: DASS-21: Depression, Anxiety and Stress Scale, PHQ-4: Patient Health Questionnaire-4,
Sleep: PSQI: Pittsburgh Sleep Quality Index, ISI: Insomnia Severity Index
Others: CD-RISC: Connor-Davidson Resilience Scale, Demands Scale—Short Version, Dream anxiety score, GSES: Generalised self-efficacy scale, IES-R: Impact of Event Scale, Kessler K6 Distress Scale, MBI: Maslach Burnout Inventory, SASR: the Stanford Acute Stress Reaction questionnaire, SCL-90: The Symptom Checklist-90-R, SF-36: Short Form Health Survey, SSRS: Social Support Rating Scale, Vicarious Trauma Questionnaire
1. Ahmed MA, Jouhar R, Ahmed N, Adnan S, Aftab M, Zafar MS, et al. Fear and Practice Modifications among Dentists to Combat Novel Coronavirus Disease (COVID-19) Outbreak. International Journal of Environmental Research and Public Health. 2020;17(8):2821.
2. Balakumar C, Rait J, Montauban P, Zarsadias P, Iqbal S, Fernandes R. COVID‐19: are frontline surgical staff ready for this? British Journal of Surgery. 2020.
3. Cai H, Tu B, Ma J, Chen L, Fu L, Jiang Y, et al. Psychological Impact and Coping Strategies of Frontline Medical Staff in Hunan Between January and March 2020 During the Outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei, China. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2020;26:e924171-1.
4. Cai W, Lian B, Song X, Hou T, Deng G, Li H. A cross-sectional study on mental health among health care workers during the outbreak of Corona Virus Disease 2019. Asian Journal of Psychiatry. 2020;51:102111.
5. Cao J, Wei J, Zhu H, Duan Y, Geng W, Hong X, et al. A study of basic needs and psychological wellbeing of medical workers in the fever clinic of a tertiary general hospital in Beijing during the COVID-19 outbreak. Psychotherapy and Psychosomatics. 2020:1.
6. Chew NWS, Lee GKH, Tan BYQ, Jing M, Goh Y, Ngiam NJH, et al. A multinational, multicentre study on the psychological outcomes and associated physical symptoms amongst healthcare workers during COVID-19 outbreak. Brain, Behavior, and Immunity. 2020.
7. Chung JPY, Yeung WS. Staff Mental Health Self-Assessment During the COVID-19 Outbreak. East Asian Archives of Psychiatry: Official Journal of the Hong Kong College of Psychiatrists= Dong Ya Jing Shen ke xue zhi: Xianggang Jing Shen ke yi xue Yuan qi kan. 2020;30(1):34-.
8. Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 epidemic in China: a web-based cross-sectional survey. medRxiv. 2020.
9. Kang L, Ma S, Chen M, Yang J, Wang Y, Li R, et al. Impact on mental health and perceptions of psychological care among medical and nursing staff in Wuhan during the 2019 novel coronavirus disease outbreak: A cross-sectional study. Brain, behavior, and immunity. 2020.
10. Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N, et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA network open. 2020;3(3):e203976-e.
11. Li Z, Ge J, Yang M, Feng J, Qiao M, Jiang R, et al. Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control. Brain, behavior, and immunity. 2020.
12. Liang Y, Chen M, Zheng X, Liu J. Screening for Chinese medical staff mental health by SDS and SAS during the outbreak of COVID-19. Journal of Psychosomatic Research. 2020;133:110102.
13. Lu W, Wang H, Lin Y, Li L. Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study. Psychiatry Research. 2020:112936.
14. Mo Y, Deng L, Zhang L, Lang Q, Liao C, Wang N, et al. Work stress among Chinese nurses to support Wuhan for fighting against the COVID‐19 epidemic. Journal of nursing management. 2020.
15. Shacham M, Hamama-Raz Y, Kolerman R, Mijiritsky O, Ben-Ezra M, Mijiritsky E. COVID-19 Factors and Psychological Factors Associated with Elevated Psychological Distress among Dentists and Dental Hygienists in Israel. International Journal of Environmental Research and Public Health. 2020;17(8):2900.
16. Sun N, Shi S, Jiao D, Song R, Ma L, Wang H, et al. A Qualitative Study on the Psychological Experience of Caregivers of COVID-19 Patients. American Journal of Infection Control. 2020.
17. Tan BYQ, Chew NWS, Lee GKH, Jing M, Goh Y, Yeo LLL, et al. Psychological Impact of the COVID-19 Pandemic on Health Care Workers in Singapore. Annals of Internal Medicine. 2020.
18. Urooj U, Ansari A, Siraj A, Khan S, Tariq H. Expectations, Fears and Perceptions of doctors during Covid-19 Pandemic. Pakistan Journal of Medical Sciences. 2020;36(COVID19-S4).
19. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. International journal of environmental research and public health. 2020;17(5):1729.
20. Wu Y, Wang J, Luo C, Hu S, Lin X, Anderson AE, et al. A comparison of burnout frequency among oncology physicians and nurses working on the front lines and usual wards during the COVID-19 epidemic in Wuhan, China. Journal of Pain and Symptom Management. 2020.
21. Xiao H, Zhang Y, Kong D, Li S, Yang N. The effects of social support on sleep quality of medical staff treating patients with coronavirus disease 2019 (COVID-19) in January and February 2020 in China. Medical science monitor: international medical journal of experimental and clinical research. 2020;26:e923549-1.
22. Xu J, Xu Q-h, Wang C-m, Wang J. Psychological status of surgical staff during the COVID-19 outbreak. Psychiatry Research. 2020:112955.
23. Yin X, Zeng L. A study on the psychological needs of nurses caring for patients with coronavirus disease 2019 from the perspective of the existence, relatedness, and growth theory. International Journal of Nursing Sciences. 2020.
24. Zhang W-r, Wang K, Yin L, Zhao W-f, Xue Q, Peng M, et al. Mental health and psychosocial problems of medical health workers during the COVID-19 epidemic in China. Psychotherapy and psychosomatics. 2020:1-9.
Table 2: Risk of bias and quality assessment summary
|
Author
|
Participants and setting described in detail, including similarity of controls
|
Criteria for inclusion clearly defined and exposures similarly measured
|
Exposure measured in valid and reliable way
|
Objective, standard criteria used for measurement of condition
|
Confounding factors identified
|
Strategies to deal with confounding factors stated
|
Outcomes measured in valid and reliable way
|
Appropriate statistical analysis used?
|
JBI Score
(1)
|
Risk of Bias
(2)
|
1
|
Ahmed et al., 2020 (3)
|
+
|
+
|
+
|
+
|
+
|
-
|
?
|
+
|
6
|
Low
|
2
|
Balakumar et al., 2020 (4)
|
Risk of bias of uncontrolled before-after studies (assessed with ROBINS – I) (5): Low quality evidence
|
|
3
|
H. Cai et al., 2020 (6)
|
+
|
+
|
+
|
-
|
+
|
-
|
+
|
+
|
6
|
Low
|
4
|
W. Cai et al., 2020 (7)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
5
|
Cao et al., 2020 (8)
|
Mixed methods appraisal tool (MMAT) used (Hong et al., 2018) S1-2 not addressed satisfactory: Low quality evidence
|
|
|
6
|
Chew et al., 2020 (9)
|
+
|
+
|
+
|
+
|
+
|
+
|
+
|
+
|
8
|
Low
|
7
|
Chung & Yeung, 2020 (10)
|
+
|
-
|
+
|
+
|
-
|
-
|
-
|
-
|
3
|
High
|
8
|
Huang & Zhao, 2020 (11)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
9
|
Kang et al., 2020 (12)
|
+
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
7
|
Low
|
10
|
Lai et al., 2020 (13)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
11
|
Li et al., 2020 (14)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
12
|
Liang et al., 2020 (15)
|
-
|
-
|
+
|
+
|
-
|
-
|
+
|
+
|
4
|
High
|
13
|
Lu et al., 2020 (16)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
14
|
Mo et al., 2020 (17)
|
+
|
-
|
+
|
+
|
+
|
-
|
+
|
+
|
6
|
Minor
|
15
|
Shacham et al., 2020 (18)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
16
|
Sun et al., 2020 (19)
|
Joanna Briggs Institute tool to assess qualitative studies used – 10 item tool(20): High quality evidence
|
9
|
|
17
|
Tan et al., 2020 (21)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
18
|
Urooj et al., 2020 (22)
|
Mixed methods appraisal tool (MMAT) (23) S1-2 & all 5 criteria addressed satisfactory: High quality evidence
|
|
19
|
S. Wang et al., 2020 (24)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
20
|
Wu et al., 2020 (25)
|
+
|
-
|
+
|
+
|
+
|
-
|
+
|
+
|
6
|
Minor
|
21
|
Xiao et al., 2020 (26)
|
+
|
-
|
+
|
+
|
+
|
-
|
+
|
+
|
6
|
Minor
|
22
|
Xu et al., 2020 (24)
|
Assessed with Critical Appraisal Skills Programme appraisal tool(27)
|
Minor
|
23
|
Yin & Zeng, 2020 (28)
|
Joanna Briggs Institute tool to assess qualitative studies used – 10 item tool (20): High quality evidence
|
10
|
|
24
|
Zhang et al., 2020 (29)
|
+
|
+
|
+
|
+
|
+
|
-
|
+
|
+
|
7
|
Low
|
1. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, Sfetcu R, et al. Chapter 7: Systematic reviews of etiology and risk. Joanna Briggs Institute Reviewer's Manual The Joanna Briggs Institute. 2017:2019-05.
2. Evidence Partners. Tool to Assess Risk of Bias. Contributed by the CLARITY Group at McMaster University: McMaster University; [Available from: https://www.evidencepartners.com/resources/methodological-resources/.
3. Ahmed MA, Jouhar R, Ahmed N, Adnan S, Aftab M, Zafar MS, et al. Fear and Practice Modifications among Dentists to Combat Novel Coronavirus Disease (COVID-19) Outbreak. International Journal of Environmental Research and Public Health. 2020;17(8):2821.
4. Balakumar C, Rait J, Montauban P, Zarsadias P, Iqbal S, Fernandes R. COVID‐19: are frontline surgical staff ready for this? British Journal of Surgery. 2020.
5. Jüni P, Loke Y, Pigott T, Ramsay C, Regidor D, Rothstein H, et al. Risk of bias in non-randomized studies of interventions (ROBINS-I): detailed guidance. 2016.
6. Cai H, Tu B, Ma J, Chen L, Fu L, Jiang Y, et al. Psychological Impact and Coping Strategies of Frontline Medical Staff in Hunan Between January and March 2020 During the Outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei, China. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2020;26:e924171-1.
7. Cai W, Lian B, Song X, Hou T, Deng G, Li H. A cross-sectional study on mental health among health care workers during the outbreak of Corona Virus Disease 2019. Asian Journal of Psychiatry. 2020;51:102111.
8. Cao J, Wei J, Zhu H, Duan Y, Geng W, Hong X, et al. A study of basic needs and psychological wellbeing of medical workers in the fever clinic of a tertiary general hospital in Beijing during the COVID-19 outbreak. Psychotherapy and Psychosomatics. 2020:1.
9. Chew NWS, Lee GKH, Tan BYQ, Jing M, Goh Y, Ngiam NJH, et al. A multinational, multicentre study on the psychological outcomes and associated physical symptoms amongst healthcare workers during COVID-19 outbreak. Brain, Behavior, and Immunity. 2020.
10. Chung JPY, Yeung WS. Staff Mental Health Self-Assessment During the COVID-19 Outbreak. East Asian Archives of Psychiatry: Official Journal of the Hong Kong College of Psychiatrists= Dong Ya Jing Shen ke xue zhi: Xianggang Jing Shen ke yi xue Yuan qi kan. 2020;30(1):34-.
11. Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 epidemic in China: a web-based cross-sectional survey. medRxiv. 2020.
12. Kang L, Ma S, Chen M, Yang J, Wang Y, Li R, et al. Impact on mental health and perceptions of psychological care among medical and nursing staff in Wuhan during the 2019 novel coronavirus disease outbreak: A cross-sectional study. Brain, behavior, and immunity. 2020.
13. Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N, et al. Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019. JAMA Network Open. 2020;3(3):e203976-e.
14. Li Z, Ge J, Yang M, Feng J, Qiao M, Jiang R, et al. Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control. Brain, behavior, and immunity. 2020.
15. Liang Y, Chen M, Zheng X, Liu J. Screening for Chinese medical staff mental health by SDS and SAS during the outbreak of COVID-19. Journal of Psychosomatic Research. 2020;133:110102.
16. Lu W, Wang H, Lin Y, Li L. Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study. Psychiatry Research. 2020:112936.
17. Mo Y, Deng L, Zhang L, Lang Q, Liao C, Wang N, et al. Work stress among Chinese nurses to support Wuhan for fighting against the COVID‐19 epidemic. Journal of nursing management. 2020.
18. Shacham M, Hamama-Raz Y, Kolerman R, Mijiritsky O, Ben-Ezra M, Mijiritsky E. COVID-19 Factors and Psychological Factors Associated with Elevated Psychological Distress among Dentists and Dental Hygienists in Israel. International Journal of Environmental Research and Public Health. 2020;17(8):2900.
19. Sun N, Shi S, Jiao D, Song R, Ma L, Wang H, et al. A Qualitative Study on the Psychological Experience of Caregivers of COVID-19 Patients. American Journal of Infection Control. 2020.
20. Lockwood C, Munn Z, Porritt K. Qualitative research synthesis: methodological guidance for systematic reviewers utilizing meta-aggregation. International journal of evidence-based healthcare. 2015;13(3):179-87.
21. Tan BYQ, Chew NWS, Lee GKH, Jing M, Goh Y, Yeo LLL, et al. Psychological Impact of the COVID-19 Pandemic on Health Care Workers in Singapore. Annals of Internal Medicine. 2020.
22. Urooj U, Ansari A, Siraj A, Khan S, Tariq H. Expectations, Fears and Perceptions of doctors during Covid-19 Pandemic. Pakistan Journal of Medical Sciences. 2020;36(COVID19-S4).
23. Hong QN, Fàbregues S, Bartlett G, Boardman F, Cargo M, Dagenais P, et al. The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers. Education for Information. 2018;34(4):285-91.
24. Wang S, Xie L, Xu Y, Yu S, Yao B, Xiang D. Sleep disturbances among medical workers during the outbreak of COVID-2019. Occupational Medicine. 2020.
25. Wu Y, Wang J, Luo C, Hu S, Lin X, Anderson AE, et al. A comparison of burnout frequency among oncology physicians and nurses working on the front lines and usual wards during the COVID-19 epidemic in Wuhan, China. Journal of Pain and Symptom Management. 2020.
26. Xiao H, Zhang Y, Kong D, Li S, Yang N. The effects of social support on sleep quality of medical staff treating patients with coronavirus disease 2019 (COVID-19) in January and February 2020 in China. Medical science monitor: international medical journal of experimental and clinical research. 2020;26:e923549-1.
27. Critical Appraisal Skills Programme. Cohort Study Checklist: Critical Appraisal Skills Programme (CASP); [Available from: https://casp-uk.net/casp-tools-checklists/.
28. Yin X, Zeng L. A study on the psychological needs of nurses caring for patients with coronavirus disease 2019 from the perspective of the existence, relatedness, and growth theory. International Journal of Nursing Sciences. 2020.
29. Zhang W-r, Wang K, Yin L, Zhao W-f, Xue Q, Peng M, et al. Mental health and psychosocial problems of medical health workers during the COVID-19 epidemic in China. Psychotherapy and psychosomatics. 2020:1-9.
Table 3: Certainty of evidence for the risk factors associated with adverse mental health outcomes on health and care staff during the COVID-19 pandemic
No of studies
|
Design
|
Risk of bias
|
Additional considerations
|
Certainty
(overall score)[1]
|
Factor: Frontline staff/Close contact with COVID-19 patients (1-4)
|
4
|
2
|
2
|
Inconsistency: Higher burnout reported in non-frontline staff (Cancer hospital, Wuhan). (5)
Frontline nurses reported lower vicarious trauma scores. (6)
No difference between frontline and non-frontline staff reported (This finding was not statistically significant). (7)
|
Moderate
|
Factor: Nurse (2, 8, 9)
|
3
|
2
|
2
|
Inconsistency: Doctors were found to have more sleep disturbances than nurses (This finding was not statistically significant). (4)
Not all confounding factors were dealt with in the three studies reporting nurses to be at a higher risk for adverse psychological outcomes. No studies compared nurses to primary care or social staff.
|
Moderate
|
Factor: Clinical healthcare workers (3, 10)
|
2
|
2
|
2
|
Inconsistency in these findings. (11)
|
Moderate
|
Factor: Heavy workload (9, 12, 13)
|
3
|
2
|
2
|
No serious inconsistencies.
|
High
|
Factor: Lack of personal protective equipment (PPE) (8, 14-16)
|
4
|
2
|
2
|
No serious inconsistencies.
|
High
|
Factor: Point of outbreak (13, 17)
|
2
|
2
|
1
|
Only two studies - one was limited to the sample of a surgical department where confounding factors were not dealt with and one was a qualitative study.
|
Low
|
Factor: Rural location (10)
|
1
|
2
|
0
|
Only one study reported findings on effect of rurality.
|
Very low
|
Factor: Fear of infection (9, 14, 18)
|
3
|
2
|
2
|
No serious inconsistencies.
|
High
|
Factor: Concern about family (8, 9, 13, 15)
|
4
|
2
|
1
|
This theme was predominantly raised in qualitative literature.
|
Moderate
|
Factor: Younger age (7, 8, 19)
|
3
|
2
|
2
|
Age was found to be a complex risk factor where the focus of anxiety depended on the age group assessed. (8)
|
Low
|
Factor: Gender – Female (2, 10)
|
2
|
2
|
1
|
Inconsistencies were found – for example: a large global survey of dentists found no differences based on gender. (18) Furthermore, confounding factors assessing gender in both included studies were not satisfactorily dealt with.
|
Low
|
Factor: Organic illness (10, 20)
|
2
|
2
|
1
|
No serious inconsistencies.
|
Moderate
|
Factor: Being an only child (4, 12)
|
2
|
2
|
0
|
No serious inconsistencies.
|
Low
|
1. Kang L, Ma S, Chen M, Yang J, Wang Y, Li R, et al. Impact on mental health and perceptions of psychological care among medical and nursing staff in Wuhan during the 2019 novel coronavirus disease outbreak: A cross-sectional study. Brain, behavior, and immunity. 2020.
2. Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N, et al. Factors associated with mental health outcomes among health care workers exposed to coronavirus disease 2019. JAMA network open. 2020;3(3):e203976-e.
3. Lu W, Wang H, Lin Y, Li L. Psychological status of medical workforce during the COVID-19 pandemic: A cross-sectional study. Psychiatry Research. 2020:112936.
4. Wang S, Xie L, Xu Y, Yu S, Yao B, Xiang D. Sleep disturbances among medical workers during the outbreak of COVID-2019. Occupational Medicine. 2020.
5. Wu Y, Wang J, Luo C, Hu S, Lin X, Anderson AE, et al. A comparison of burnout frequency among oncology physicians and nurses working on the front lines and usual wards during the COVID-19 epidemic in Wuhan, China. Journal of Pain and Symptom Management. 2020.
6. Li Z, Ge J, Yang M, Feng J, Qiao M, Jiang R, et al. Vicarious traumatization in the general public, members, and non-members of medical teams aiding in COVID-19 control. Brain, behavior, and immunity. 2020.
7. Liang Y, Chen M, Zheng X, Liu J. Screening for Chinese medical staff mental health by SDS and SAS during the outbreak of COVID-19. Journal of Psychosomatic Research. 2020;133:110102.
8. Cai H, Tu B, Ma J, Chen L, Fu L, Jiang Y, et al. Psychological Impact and Coping Strategies of Frontline Medical Staff in Hunan Between January and March 2020 During the Outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei, China. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2020;26:e924171-1.
9. Cao J, Wei J, Zhu H, Duan Y, Geng W, Hong X, et al. A study of basic needs and psychological wellbeing of medical workers in the fever clinic of a tertiary general hospital in Beijing during the COVID-19 outbreak. Psychotherapy and Psychosomatics. 2020:1.
10. Zhang W-r, Wang K, Yin L, Zhao W-f, Xue Q, Peng M, et al. Mental health and psychosocial problems of medical health workers during the COVID-19 epidemic in China. Psychotherapy and psychosomatics. 2020:1-9.
11. Tan BYQ, Chew NWS, Lee GKH, Jing M, Goh Y, Yeo LLL, et al. Psychological Impact of the COVID-19 Pandemic on Health Care Workers in Singapore. Annals of Internal Medicine. 2020.
12. Mo Y, Deng L, Zhang L, Lang Q, Liao C, Wang N, et al. Work stress among Chinese nurses to support Wuhan for fighting against the COVID‐19 epidemic. Journal of nursing management. 2020.
13. Sun N, Shi S, Jiao D, Song R, Ma L, Wang H, et al. A Qualitative Study on the Psychological Experience of Caregivers of COVID-19 Patients. American Journal of Infection Control. 2020.
14. Chung JPY, Yeung WS. Staff Mental Health Self-Assessment During the COVID-19 Outbreak. East Asian Archives of Psychiatry: Official Journal of the Hong Kong College of Psychiatrists= Dong Ya Jing Shen ke xue zhi: Xianggang Jing Shen ke yi xue Yuan qi kan. 2020;30(1):34-.
15. Urooj U, Ansari A, Siraj A, Khan S, Tariq H. Expectations, Fears and Perceptions of doctors during Covid-19 Pandemic. Pakistan Journal of Medical Sciences. 2020;36(COVID19-S4).
16. Yin X, Zeng L. A study on the psychological needs of nurses caring for patients with coronavirus disease 2019 from the perspective of the existence, relatedness, and growth theory. International Journal of Nursing Sciences. 2020.
17. Xu J, Xu Q-h, Wang C-m, Wang J. Psychological status of surgical staff during the COVID-19 outbreak. Psychiatry Research. 2020:112955.
18. Ahmed MA, Jouhar R, Ahmed N, Adnan S, Aftab M, Zafar MS, et al. Fear and Practice Modifications among Dentists to Combat Novel Coronavirus Disease (COVID-19) Outbreak. International Journal of Environmental Research and Public Health. 2020;17(8):2821.
19. Huang Y, Zhao N. Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 epidemic in China: a web-based cross-sectional survey. medRxiv. 2020.
20. Shacham M, Hamama-Raz Y, Kolerman R, Mijiritsky O, Ben-Ezra M, Mijiritsky E. COVID-19 Factors and Psychological Factors Associated with Elevated Psychological Distress among Dentists and Dental Hygienists in Israel. International Journal of Environmental Research and Public Health. 2020;17(8):2900.
[1] 4 High = This research provides a very good indication of the likely effect. The likelihood that the effect will be substantially different** is low.
3 Moderate = This research provides a good indication of the likely effect. The likelihood that the effect will be substantially different** is moderate.
2 Low = This research provides some indication of the likely effect. However, the likelihood that it will be substantially different** is high.
1 Very low = This research does not provide a reliable indication of the likely effect. The likelihood that the effect will be substantially different** is very high.
** Substantially different = a large enough difference that it might affect a decision
Table 4: Certainty of evidence for the protective factors associated with mitigating adverse mental health outcomes on health and care staff during the COVID-19 pandemic.
No of studies
|
Design
|
Risk of bias
|
Additional considerations
|
Certainty
(overall score)[1]
|
Factor: Support (Community, social, team, government)
(1-4)
|
4
|
2
|
2
|
No serious inconsistencies.
|
High
|
Factor: Adequate personal protective equipment (PPE) (1, 4)
|
2
|
2
|
0
|
Few studies assessed PPE directly as a protective factor. Many found it to be a risk factor when inadequate.
|
Low
|
Factor: Being in a committed relationship (5)
|
1
|
2
|
0
|
Only one study assessed this factor.
|
Very low
|
Factor: Prior outbreak experience/COVID-19 Knowledge (1, 4, 6, 7)
|
4
|
2
|
1
|
No serious inconsistencies, but the data also included one low quality uncontrolled pre and post exposure study, as well as a qualitative study.
|
Moderate
|
Factor: Resilience (3, 5, 7)
|
3
|
2
|
1
|
Resilience was empirically measured with validated scores
|
High
|
Factor: Altruistic acts (2)
|
1
|
2
|
1
|
Only one qualitative study assessed this factor.
|
Low
|
Factor: Personal growth (2)
|
1
|
2
|
1
|
Only one qualitative study assessed this factor.
|
Low
|
Factor: Gratitude, Positive self-attitude (1, 2)
|
2
|
2
|
1
|
This factor was not empirically measured.
|
Low
|
Factor: Sense of purpose (2)
|
1
|
2
|
1
|
Only one qualitative study assessed this factor.
|
Low
|
Factor: Safety of family (1)
|
1
|
2
|
0
|
Only one study assessed this factor.
|
Very low
|
1. Cai H, Tu B, Ma J, Chen L, Fu L, Jiang Y, et al. Psychological Impact and Coping Strategies of Frontline Medical Staff in Hunan Between January and March 2020 During the Outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei, China. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research. 2020;26:e924171-1.
2. Sun N, Shi S, Jiao D, Song R, Ma L, Wang H, et al. A Qualitative Study on the Psychological Experience of Caregivers of COVID-19 Patients. American Journal of Infection Control. 2020.
3. Xiao H, Zhang Y, Kong D, Li S, Yang N. The effects of social support on sleep quality of medical staff treating patients with coronavirus disease 2019 (COVID-19) in January and February 2020 in China. Medical science monitor: international medical journal of experimental and clinical research. 2020;26:e923549-1.
4. Yin X, Zeng L. A study on the psychological needs of nurses caring for patients with coronavirus disease 2019 from the perspective of the existence, relatedness, and growth theory. International Journal of Nursing Sciences. 2020.
5. Shacham M, Hamama-Raz Y, Kolerman R, Mijiritsky O, Ben-Ezra M, Mijiritsky E. COVID-19 Factors and Psychological Factors Associated with Elevated Psychological Distress among Dentists and Dental Hygienists in Israel. International Journal of Environmental Research and Public Health. 2020;17(8):2900.
6. Balakumar C, Rait J, Montauban P, Zarsadias P, Iqbal S, Fernandes R. COVID‐19: are frontline surgical staff ready for this? British Journal of Surgery. 2020.
7. Cai W, Lian B, Song X, Hou T, Deng G, Li H. A cross-sectional study on mental health among health care workers during the outbreak of Corona Virus Disease 2019. Asian Journal of Psychiatry. 2020;51:102111.
[1] 4 High = This research provides a very good indication of the likely effect. The likelihood that the effect will be substantially different** is low.
3 Moderate = This research provides a good indication of the likely effect. The likelihood that the effect will be substantially different** is moderate.
2 Low = This research provides some indication of the likely effect. However, the likelihood that it will be substantially different** is high.
1 Very low = This research does not provide a reliable indication of the likely effect. The likelihood that the effect will be substantially different** is very high.
** Substantially different = a large enough difference that it might affect a decision