Background
Aim of the review
Methods
Search strategy
Data sources and searches
Search criteria
Types of participants
Types of studies included
Screening and selection of studies
Data extraction and quality assessment
Data synthesis and analysis
Patient and public involvement
Results
Search results
Study characteristics
Author | Design | Country | Participants | Selection method | Measures | |
---|---|---|---|---|---|---|
1 | Ahmed et al., (2020) [21] | 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) [22] | 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) [24] | 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) [25] | 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) [55] | 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) [27] | 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) [28] | 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) [29] | 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) [30] | 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) [31] | 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 292,020 – Feb 32,020. | PHQ-9, GAD-7, ISI, IES-R |
11 | Li et al., (2020) [32] | 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) [56] | 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) [34] | 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) [35] | 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. | SO, SAS |
15 | Shacham et al., (2020) [36] | 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) [37] | 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) [39] | 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) [40] | 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) [57] | 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) [43] | 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) [44] | 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) [58] | 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) [46] | 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) [47] | 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 |
Risk of bias assessment
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 [19] | Risk of Bias [20] | |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Ahmed et al., 2020 [21] | + | + | + | + | + | – | ? | + | 6 | Low |
2 | Balakumar et al., 2020 [22] | Risk of bias of uncontrolled before-after studies (assessed with ROBINS – I) [23]: Low quality evidence | |||||||||
3 | H. Cai et al., 2020 [24] | + | + | + | – | + | – | + | + | 6 | Low |
4 | W. Cai et al., 2020 [25] | + | + | + | + | + | – | + | + | 7 | Low |
5 | Cao et al., 2020 [26] | Mixed methods appraisal tool (MMAT) used (Hong et al., 2018) S1–2 not addressed satisfactory: Low quality evidence | |||||||||
6 | Chew et al., 2020 [27] | + | + | + | + | + | + | + | + | 8 | Low |
7 | Chung & Yeung, 2020 [28] | + | – | + | + | – | – | – | – | 3 | High |
8 | Huang & Zhao, 2020 [29] | + | + | + | + | + | – | + | + | 7 | Low |
9 | Kang et al., 2020 [30] | + | + | + | + | + | + | – | + | 7 | Low |
10 | Lai et al., 2020 [31] | + | + | + | + | + | – | + | + | 7 | Low |
11 | Li et al., 2020 [32] | + | + | + | + | + | – | + | + | 7 | Low |
12 | Liang et al., 2020 [33] | – | – | + | + | – | – | + | + | 4 | High |
13 | Lu et al., 2020 [34] | + | + | + | + | + | – | + | + | 7 | Low |
14 | Mo et al., 2020 [35] | + | – | + | + | + | – | + | + | 6 | Minor |
15 | Shacham et al., 2020 [36] | + | + | + | + | + | – | + | + | 7 | Low |
16 | Sun et al., 2020 [37] | Joanna Briggs Institute tool to assess qualitative studies used – 10 item tool [38]: High quality evidence | 9 | ||||||||
17 | Tan et al., 2020 [39] | + | + | + | + | + | – | + | + | 7 | Low |
18 | Urooj et al., 2020 [40] | Mixed methods appraisal tool (MMAT) [41] S1–2 & all 5 criteria addressed satisfactory: High quality evidence | |||||||||
19 | S. Wang et al., 2020 [42] | + | + | + | + | + | – | + | + | 7 | Low |
20 | Wu et al., 2020 [43] | + | – | + | + | + | – | + | + | 6 | Minor |
21 | Xiao et al., 2020 [44] | + | – | + | + | + | – | + | + | 6 | Minor |
22 | Xu et al., 2020 [42] | Assessed with Critical Appraisal Skills Programme appraisal tool [45] | Minor | ||||||||
23 | Yin & Zeng, 2020 [46] | Joanna Briggs Institute tool to assess qualitative studies used – 10 item tool [38]: High quality evidence | 10 | ||||||||
24 | Zhang et al., 2020 [47] | + | + | + | + | + | – | + | + | 7 | Low |
Psychological toll on healthcare workers
No of studies | Design | Risk of bias | Additional considerations | Certainty (overall score)a |
---|---|---|---|---|
4 | 2 | 2 | Inconsistency: Higher burnout reported in non-frontline staff (Cancer hospital, Wuhan) [43]. Frontline nurses reported lower vicarious trauma scores [32]. No difference between frontline and non-frontline staff reported (This finding was not statistically significant) [33]. |
Moderate |
3 | 2 | 2 | Inconsistency: Doctors were found to have more sleep disturbances than nurses (This finding was not statistically significant) [42]. 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 |
2 | 2 | 2 | Inconsistency in these findings [39]. |
Moderate |
3 | 2 | 2 | No serious inconsistencies. |
High |
4 | 2 | 2 | No serious inconsistencies. |
High |
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 [47] | ||||
1 | 2 | 0 | Only one study reported findings on effect of rurality. |
Very low |
3 | 2 | 2 | No serious inconsistencies. |
High |
4 | 2 | 1 | This theme was predominantly raised in qualitative literature. |
Moderate |
3 | 2 | 2 | Age was found to be a complex risk factor where the focus of anxiety depended on the age group assessed [24]. |
Low |
2 | 2 | 1 | Inconsistencies were found – for example: a large global survey of dentists found no differences based on gender [21]. Furthermore, confounding factors assessing gender in both included studies were not satisfactorily dealt with. |
Low |
2 | 2 | 1 | No serious inconsistencies. |
Moderate |
2 | 2 | 0 | No serious inconsistencies. |
Low |
Risk factors associated with adverse mental health outcomes
Occupational factors
Medical HCWs
Healthcare groups
Frontline staff/direct contact with COVID-19
Personal protective equipment (PPE)
Heavy workload
Psychosocial factors
Fear of infection
Concern about family
Sociodemographic factors
Younger age
Gender
Underlying illness
Being an only child
Environmental factors
Point in pandemic curve
Geography
Protective factors against adverse mental health outcomes
No of studies | Design | Risk of bias | Additional considerations | Certainty (overall score)a |
---|---|---|---|---|
4 | 2 | 2 | No serious inconsistencies. |
High |
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 [36] | ||||
1 | 2 | 0 | Only one study assessed this factor. |
Very low |
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 |
3 | 2 | 1 | Resilience was empirically measured with validated scores |
High |
Factor: Altruistic acts [37] | ||||
1 | 2 | 1 | Only one qualitative study assessed this factor. |
Low |
Factor: Personal growth [37] | ||||
1 | 2 | 1 | Only one qualitative study assessed this factor. |
Low |
2 | 2 | 1 | This factor was not empirically measured. |
Low |
Factor: Sense of purpose [37] | ||||
1 | 2 | 1 | Only one qualitative study assessed this factor. |
Low |
Factor: Safety of family [24] | ||||
1 | 2 | 0 | Only one study assessed this factor. |
Very low |
Occupational factors
Experience
Training
Psychosocial factors
Resilience
Being in a committed relationship
Safety of family
Environmental factors
Support
‘To be honest, I was very apprehensive before coming to the infectious department as support staff, but on the first day here, the head nurse personally explained relevant knowledge such as disinfection and quarantine, and that helped me calm down a lot.”
“I hope that our society and government pay more attention to lack of personal protective equipment’ [46].