Search Results
The 677 records of interest were found from the two searches (429 in search 1 and 529 in search 2). After 148 duplicates were removed, 529 records were screened. Of these, 82 full texts of potentially relevant studies were assessed for eligibility (see figure 1). Twenty-four published studies met the inclusion criteria for the rapid review.
Study Characteristics
The 24 studies included in this review consisted of 18 cross-sectional, 2 mixed methods, 2 qualitative, 1 longitudinal and 1 uncontrolled before-after study. The total number of participants in these studies was 13731. In the cross-sectional studies, participant numbers ranged between 59 and 2299. Eighteen of the studies were from China, of which 8 were based in Wuhan, where the COVID-19 outbreak began. The rest were from America (1), Israel (1), UK (1), Singapore (1), Pakistan (1), multicentre - Singapore & India (1), Global (1). Several validated measures were used to assess anxiety, depression, insomnia, stress and burnout. Table 1 provides an overview of the included studies.
Risk of bias assessment
The quality of the cross-sectional studies was fair, with 16 studies scoring 6 or higher on the JBI appraisal tool and eleven scoring 7 or higher (a score of 7 and above is an indicator of study quality). The majority of the studies indicated a low risk of bias when assessed with the Evidence Partners’ appraisal tool. The uncontrolled before-after study indicated a high risk of bias. The qualitative studies indicated a good level of quality (JBI scores of 9 & 10 respectively) while mixed methods studies showed varied quality. In the cross sectional studies, the most common problem affecting study quality was failure to deal with confounding factors. Failure to locate the researcher culturally or theoretically affected the qualitative papers, whilst the two mixed methods papers’ study quality was affected by lack of explicitly articulated research questions. A summary of the risk of bias and quality assessments are provided in Table 2.
Psychological Toll on Healthcare Workers
Of the 24 studies included, 22 directly assessed the psychological toll on healthcare workers and all found levels of anxiety, depression, insomnia, distress or Obsessive Compulsive Disorder (OCD) symptoms.[22-43]
Psychological symptoms were assessed using various validated measures as outlined in Table 3 – the summary of included studies. The most common outcomes assessed were sleep, anxiety and depression. The prevalence of depressive symptoms varied greatly, ranging between 8.9% [36] to 50.4%.[30] These findings indicate marked differences in the presentation of psychological symptoms according to country. The prevalence of anxiety in cross-sectional studies ranged between 14.5%[36] to 44.6%.[30] Sleep was also assessed in several studies. Lai et al[30] found the prevalence of sleep disturbances to be 34%, whilst another, nationwide survey in China found that HCWs had significantly worse sleep than the general population.[28]
Risk factors associated with adverse mental health outcomes
Table 3 provides the GRADE evidence profile of the certainty of evidence for the risk factors associated with adverse MH outcomes during the COVID-19 pandemic identified through the review. These risk factors can be grouped into the four thematic areas of i) occupational, ii) psychosocial, iii) occupational and iv) environmental.
Occupational factors
Medical HCWs: Two studies showed that medical HCWs (nurses and doctors) had significantly higher levels of MH risk in comparison to non-medical HCWs.[32, 43] Zhang et al[43] found that medical HCWs had significantly higher levels of insomnia, anxiety, depression, somatization and OCD symptoms in comparison to non-medical HCWs. This was also reflected in a large study in Fujian province, China, in which medical staff had significantly higher anxiety than admin staff.[32] In contrast, Tan et al[36] found that in a population of 470 HCWs in Singapore, the prevalence of anxiety was significantly higher among non-medical HCWs than medical.
Healthcare groups: In three studies nurses were found to be at risk of worse MH outcomes than doctors [23, 25, 30]. One large study in China found nurses were at significant risk of more severe depression and anxiety than doctors.[30] Another found that nurses had significantly higher financial concerns than doctors and felt significantly more anxious on the ward when compared with other groups. There was no significant difference between professionals regarding stopping work or work overload.[23] A mixed method paper also showed that nurses had a higher rate of depressive symptoms than doctors. Whilst this was a small sample size, it echoes the findings from larger studies.[25]
With regard to other HCWs, there were two studies which assessed dentists and other dental workers and found them to be at risk of anxiety and elevated distress. Neither study found any difference based on gender or educational level.[22, 34] There were no studies comparing dental workers to other HCWs. We did not find any studies that focussed on the primary care workforce or that assessed social care workers.
With regard to seniority, one paper found that having an intermediate technical title was associated with more severe MH symptoms.[30]
Frontline staff/Direct contact with COVID-19: Four high-quality studies found being in a ‘frontline’ position or having direct contact with COVID-19 patients was associated with higher levels of psychological distress.[29, 30, 32, 38]
Increased direct exposure to COVID-19 patients increased the mental health risks in health care workers in one study in Wuhan.[29] This finding is backed by Lai et al[30], who found that being a frontline worker was independently associated with more severe depression, anxiety and insomnia scores. In addition, a cross sectional survey of staff in a paediatric centre found that contact with COVID-19 patients was independently associated with increased risk of sleep disturbance.[38] Lu et al[32] found that medical HCWs in direct contact with COVID-19 patients had almost twice the risk of anxiety and depression than non-medical staff with low risk of contact with COVID-19.
There were conflicting results found in two studies. A study in a cancer hospital in Wuhan found burnout frequency to be lower in frontline staff.[39] The authors identified confounding factors which may have led to this result, but it is of interest as it is one of the only studies that assessed HCWs outside of the acute general medicine setting. Li et al[44], also found that frontline nurses had significantly lower levels of vicarious trauma scores than non-frontline workers and the general population.
Personal protective equipment (PPE): PPE concerns were the most common theme brought up voluntarily in free-text feedback in a study by Chung & Yeung[27], and a survey in Pakistan revealed that 80% of participants expected provision of PPE.[37] H.Cai et al[23] also found that PPE was protective when adequate, but a risk factor for stress when inadequate. This finding appears to be bolstered by a qualitative study of frontline nurses in Wuhan, which found that physical health and safety was one of their primary needs. This study also reported PPE as a protective factor.[42]
Heavy Workload: Longer working time per week was found to be a risk factor in a study by Mo et al.[33] This, together with increased work intensity or patient load per hour, were themes in a mixed methods study of 37 staff of a clinic in Beijing[25] and a qualitative study of nurses in China[35], also suggesting heavy workload as a risk factor.
Psychosocial Factors
Fear of infection: A fear of infection was a highlighted in a qualitative study by Cao et al., (2020)[25], and brought up as a theme in free-text feedback in a cross sectional survey by Chung & Yeung.[27] Ahmed et al[22] found that 87% of dentists surveyed described a fear of being infected with COVID-19 from either a patient or a co-worker.
Concern about family: This was brought up as one of the main stress factors in a study by H.Cai et al[23], particularly amongst staff in the 31-40 year age-group. Knowing that their family was safe was also the greatest stress reliever[23], whilst fear of infecting family was identified in 79.7% of 222 participants in a study in Pakistan.[37] It was also a theme highlighted in the qualitative data.[25, 35]
Being an only child: This was independently associated with sleep disturbance in paediatric HCWs in Wuhan.[38] Being an only child was also found to be significantly associated with stress by Mo et al.[33]
Sociodemographic Factors
Younger Age: One Chinese web-based survey which included the general population and HCWs, showed that younger people had significantly higher anxiety and depression scores.[28]
H. Cai et al[23] suggested that age was more complex. They found that all age groups had concerns, but that the focus of their anxieties were different (for example: older staff were more likely to be anxious due to exhaustion from long hours and lack of PPE while younger staff were more likely to worry about their families).
Gender: Women were found to be at higher risk for depression, anxiety and insomnia by Lai et al.[30] This was also found to be an independent risk factor for anxiety in another large nationwide Chinese study.[43] However, a global survey of dentists found no differences based on gender.[22]
Underlying illness: We found two studies which identified that having an underlying organic illness as an independent risk factor for poor psychological outcomes. A study of dentists in Israel found an increase in psychological distress in those with background illnesses as well as an increased fear of contracting COVID-19 and higher subjective overload.[34] In medical HCWs in China, organic illness was found to be an independent risk factor for insomnia, anxiety, OCD, somatising symptoms and depression in medical HCWs.[43]
There was also a significant association between physical symptoms and poor psychological outcomes in a large multicentre study based in India and Singapore. It is unclear if this represented somatization or organic illness and the authors suggest the relationship between physical symptoms and psychological aspects was bi-directional.[26]
Environmental Factors
Point in pandemic curve: One longitudinal study carried out in China in a surgical department, found that anxiety and depression scores during the ‘outbreak’ period were significantly higher when compared to a similar group assessed after the outbreak period.[41] This was a small sample of 120 and only assessed surgical staff, but this longitudinal data was supported by a qualitative study in China which suggested that anxiety peaks at the start of the outbreak and reduces with time.[35]
Geography: Living in a rural area was only assessed by one study which showed that it was an independent risk factor for insomnia and anxiety in medical HCWs.[43] This may reflect a need to further investigate the effect of rurality on psychological wellbeing during this pandemic.
Protective factors against adverse mental health outcomes
The review identified protective factors against adverse mental health outcomes during COVID-19. Table 4 provides the GRADE evidence profile of the certainty of evidence for this. The protective factors can be grouped into the three thematic areas of: i) occupational, ii) psychosocial and iii) environmental.
Occupational Factors
Experience: W. Cai et al[24] found that previous experience in a public health emergency (PHE) was protective against adverse mental health outcomes. Staff that had no previous experience were also more likely to have low rates of resilience, and social support.
Training: A small cohort study of 27 surgeons, who were given pre and post training surveys, suggested that training alleviates psychological stress.[45] Good hospital guidance was identified to relief stress in a study by H.Cai et al[23], and increasing self-knowledge was a coping strategy deployed by staff. Dissemination of knowledge was also mentioned in a qualitative study by Yin & Zeng[42]; participants described subjective stress reduction after their seniors explained relevant knowledge to them.
Adequate PPE: As mentioned above, PPE was found to be a protective factor when adequate and a risk factor for poor mental health outcomes when deemed to be inadequate.[23, 42]
Psychosocial Factors
Resilience: One study assessed self-efficacy in dental staff and found that it was a protective factor.[34] Self-efficacy was also found to improve sleep quality by Xiao et al[40], whilst W.Cai et al[24] measured resilience using a validated measure and found it to be a protective factor against adverse MH outcomes.
Being in a committed relationship: This was found to be protective by Shacham et al.[34] This was not directly assessed in other studies.
Safety of family: This had the biggest impact in reducing stress in a cross-sectional study by H. Cai et al.[23] This was also not assessed in other studies.
Environmental Factors
Support: Support and recognition from the health care team, government and community was identified as a protective theme in several studies. Social support, measured using the Social Support Rate Scale (SSRS) was found to indirectly affect sleep by directly reducing anxiety and stress and increasing self-efficacy.[40]
Team support was identified as a protective factor in a qualitative study by Sun et al.[35] Good hospital guidance was also identified as a stress reliever by H. Cai et al[23], who found that HCWs expected recognition from the hospital authorities. This was echoed in a qualitative study of nurses in Wuhan where the desire for community concern was a strong need and tightly linked to the need for PPE and knowledge:[42]
‘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’[42]