key: cord-1006965-o0g7ydm9 authors: Hill, James Edward; Harris, Catherine; Danielle L., Christian; Boland, Paul; Doherty, Alison J.; Benedetto, Valerio; Gita, Bhutani E.; Clegg, Andrew J. title: The prevalence of mental health conditions in healthcare workers during and after a pandemic: Systematic review and meta‐analysis date: 2022-02-12 journal: J Adv Nurs DOI: 10.1111/jan.15175 sha: 59dacaeb6c4e1eeaf62518f24a0c74e802c88729 doc_id: 1006965 cord_uid: o0g7ydm9 AIMS: This review aims to explore the prevalence and incidence rates of mental health conditions in healthcare workers during and after a pandemic outbreak and which factors influence rates. BACKGROUND: Pandemics place considerable burden on care services, impacting on workers' health and their ability to deliver services. We systematically reviewed the prevalence and incidence of mental health conditions in care workers during pandemics. DESIGN: Systematic review and meta‐analysis. DATA SOURCES: Searches of MEDLINE, Embase, Cochrane Library and PsychINFO for cohort, cross‐sectional and case–control studies were undertaken on the 31 March 2020 (from inception to 31 March 2020). REVIEW METHODS: Only prevalence or incidence rates for mental health conditions from validated tools were included. Study selection, data extraction and quality assessment were carried out by two reviewers. Meta‐analyses and subgroup analyses were produced for pandemic period (pre‐ and post), age, country income, country, clinical setting for major depression disorder (MDD), anxiety disorder and post‐traumatic stress disorder (PTSD). RESULTS: No studies of incidence were found. Prevalence estimates showed that the most common mental health condition was PTSD (21.7%) followed by anxiety disorder (16.1%), MDD (13.4%) and acute stress disorder (7.4%) (low risk of bias). For symptoms of these conditions there was substantial variation in the prevalence estimates for depression (95% confidence interval [CI]:31.8%; 60.5%), anxiety (95% CI:34.2%; 57.7%) and PTSD symptoms (95% CI,21.4%; 65.4%) (moderate risk of bias). Age, level of exposure and type of care professional were identified as important moderating factors. CONCLUSION: Mental disorders affect healthcare workers during and after infectious disease pandemics, with higher proportions experiencing symptoms. IMPACT: This review provides prevalence estimates of mental health conditions during and after a pandemic which could be used to inform service staffing impact and formulation of preventative strategies, by identifying clinical populations who may be at high risk of developing mental health symptoms and conditions. The emergence of the Covid-19 coronavirus during 2019 and its subsequent spread worldwide have, like previous pandemics, placed a considerable burden on healthcare services and the informal care sector World Health Organization, 2020c; Xiong & Peng, 2020) The challenges facing people providing care are many and varied (Krubiner et al., 2020) . A highly contagious virus, Covid-19 has spread rapidly between and in countries, offering little opportunity for healthcare services to prepare appropriately (Hamid et al., 2020) . As the need and demand for healthcare has risen due to the pandemic, the pressures placed on those providing care have grown markedly (Khera et al., 2020; Minder & Peltier, 2020 ; World Health Organization, 2020c). Healthcare workers have faced: increased workloads and responsibility; redeployment away from their specialisms; a changing work environment associated with infection control (e.g. protective clothing); emotional consequences of caring for those people with, and dying from, Covid-19 and for their families; the likelihood that they are at increased risk of acquiring the infection themselves from close contact with those already infected; and, personal impact of their own family becoming infected or dying (Schoonhoven et al., 2020) . It is almost inevitable that the situation faced by healthcare workers puts them at risk of suffering from stress and associated psychological problems, both in the short and long term (Adams & Walls, 2020; Minder & Peltier, 2020; Xiong & Peng, 2020) . These may include trauma/emotional events, sleep deprivation, fatigue, anxiety disorders and depression (Schoonhoven et al., 2020) . Recognizing the nature and extent of the effects of pandemics on the mental health of healthcare workers is important, not only for the individual themselves, but also for the continued delivery of services (Xiong & Peng, 2020) . It allows service providers to develop plans to prevent and/or manage mental health conditions among staff during and following pandemics. Although systematic and rapid reviews have assessed the prevalence of psychological problems associated with different pandemics (Pappa et al., 2020; Thapa et al., 2020) , they have certain shortcomings. Several focus on specific pandemics and exclude more recent evidence (Pappa et al., 2020; Thapa et al., 2020) . Another has used a broad range of criteria for diagnosing mental health conditions, lacking valid and reliable clinical thresholds that may result in inconsistency . Given these limitations, we conducted a systematic review and meta-analysis of the incidence and prevalence of mental health conditions among healthcare workers associated with infectious disease pandemics. In doing so, we focused on studies using recognized diagnostic criteria for the different mental health conditions and considered the important mediating factors that may influence the occurrence of mental health conditions. Our systematic review addressed two questions. First, what is the prevalence and incidence of mental health conditions in healthcare workers during and after pandemic outbreaks? Second, which factors have an influence on prevalence and incidence rates?' Our systematic review adhered to recognized guidance and is reported in accordance with the PRISMA standards (Moher et al., 2015) , with its methods outlined in a research protocol registered with PROSPERO (Registration number: CRD42020181947). We undertook a multi-database search on MEDLINE, Embase, The Cochrane Library (Cochrane Database of Systematic Reviews) and PsycINFO bibliographic databases on the 31st of March 2020 (from inception to 31 March 2020). The search used terms identified by the review team and a search filter for prevalence studies adapted from Larney et al., 2013 (Larney et al., 2013 ) (see Appendix 1 for the full MEDLINE search strategy). Additional studies were identified through screening of all included studies reference lists and identified systematic reviews, alongside opportunistic searching of the literature. This review provides prevalence estimates of mental health conditions during and after a pandemic which could be used to inform service staffing impact and formulation of preventative strategies, by identifying clinical populations who may be at high risk of developing mental health symptoms and conditions. health and social care workers, mental health, prevalence, incidence, systematic review, nursing, Covid-19, SARS, pandemic We included cohort studies, cross-sectional studies (prevalence only) and case-control studies which used a target population of health- World Health Organization, 2011 , 2020a , 2020b . The primary outcome for the review was either the prevalence or incidence of mental health conditions or the reporting of symptoms of mental health conditions during and after the pandemic. Included studies needed to report a prevalence and/or incidence rate of a psychological condition using cut-off points on a diagnostic scale or a clinical diagnosis (undertaken through clinical interview). For the incidence and prevalence of major depression, anxiety disorders, post-traumatic stress disorder (PTSD), acute stress disorder and psychological distress (see Table 1 study characteristics for full list of validated tools), only studies which were judged to use a valid and reliable data collection tool, based on the Hoy assessment of bias criteria, were included in the meta-analysis (Hoy et al., 2012) . This was based on the tool used having a cut-off threshold which achieved both a sensitivity and specificity above 0.8, test-retest reliability above 0.6 (i.e. rated good) and the values having external validity in terms of the target population (Fleiss, 1986) . In studies which reported multiple cut-off points on a scale, the cut-off point which has been shown to have the greatest diagnostic accuracy was used (Coffey et al., 2006; Dunstan et al., 2017; Foa & Tolin, 2000; Guest et al., 2018; Kim et al., 2019; Kroenke et al., 2001; Lowe et al., 2008; Matza et al., 2010; Mossman et al., 2017; Park, 2012; Spitzer et al., 2006; Yohannes et al., 2019; Zimmerman et al., 2013) . For anxiety disorders the cut-off point included both clinically relevant cut-off points and a specific diagnosis of general anxiety disorder made by a clinician (Bergua et al., 2016; Birmaher et al., 1999; Dunstan & Scott, 2020; Spitzer et al., 2006; Tran et al., 2013) . In contrast, no specific inclusion criteria were set to judge the reliability and validity of the tools used to assess the prevalence of symptoms of these conditions. Instead, this was defined by the author of the paper. Included studies needed to be published in English. Using predefined selection criteria, four reviewers in groups of two independently screened titles and abstracts (J.H., C.H., D.C., P.B.). Full paper screening, data extraction and risk of bias assessment were undertaken by a single reviewer and verified by a second reviewer (J.H., C.H., D.C., P.B.). Any disagreement during screening, data extraction and risk of bias assessment were resolved by discussion; if consensus could not be achieved arbitration was carried out by a third reviewer (A.C.). At each stage, we used pre-piloted processes and forms or tools. The data items which were extracted were pandemic, country, city, staff type, mean age, proportion of females, clinical setting, study type, control group (where applicable), point of observation (day/month/year) and duration of observation (weeks). Countries of study location were coded into high income, upper-middle income, lower-middle income and low-income countries (The World Bank, 2020). Risk of bias assessment used an adapted Hoy quality assessment checklist for prevalence studies (Hoy et al., 2012) and planned to use an adapted Shamliyan checklist for incidence studies (Shamliyan et al., 2011) . The adapted Hoy quality assessment checklist provides a total score (total number of criteria achieved) for each study and a mean quality score (number of studies in the analysis divided by total score of all studies included in the analysis) for all included studies or for studies included in specific sub-group analyses. In contrast the adapted Shamliyan checklist provides an assessment of quality for each component considered important (see Table 1 study characteristics for a full list of included studies). No studies were excluded based on their level of bias. We meta-analysed the prevalence of the different mental health conditions for both our research questions, presenting overall estimates and 95% confidence intervals. Random effects models were estimated (DerSimonian-Laird) due to the likelihood of substantial heterogeneity (DerSimonian & Laird, 1986) . In subgroup analyses where there were only two studies assessing the factors affecting prevalence, we used fixed-effect models, as the number of parameters to be estimated exceeded the number of observations. All studies reported mental health conditions and symptoms as a dichotomous variable (presence/absence). The heterogeneity of pooled estimates collected from the studies was assessed using the I-squared statistic (I 2 ) (Higgins, 2021) . To pool data, we used the jamovi software, employing the Project R Metafor package (R Core Team, 2018; The jamovi project, 2019; Viechtbauer, 2010) . A descriptive analysis was undertaken of possible statistically significant (p < .05) moderators/ confounding factors reported in two or more studies on the prevalence or incidence of mental health conditions or symptoms. The subgroup analyses pre-identified in our registered protocol were performed to address our second research question, which assessed the factors that may influence prevalence rates. These factors, which were identified from previous systematic reviews, were: pandemic period (pre-and post-); age; country income; country; and, clinical setting for major depression disorder (MDD), anxiety disorders and PTSD (Pappa et al., 2020; Thapa et al., 2020) . We did not carry out a subgroup analysis for See Figure 1 for PRISMA flow diagram. The number of participants in the included studies varied, ranging from 26 to 10,511. Across the included studies five different pandemics were studied with the most studies examining SARS (n = 30); Covid-19 (n = 6); Influenza A subtype H1N1 (H1N1) (n = 2) and Ebola (n = 1). The majority of these studies (n = 27) took place in high-income countries, specifically Taiwan (n = 7), Canada (n = 7), Singapore (n = 4), Hong Kong (n = 2), both Hong Kong and Canada (n = 1), Saudi Arabia (n = 2), South Korea (n = 2), Greece (n = 1) and the Netherlands (n = 1). The remaining 16 studies took place in low to upper-middle income countries. These were China (n = 14), Sierra Leone (n = 1) and Malaysia (n = 1). The majority of studies used a cross-sectional design (n = 35) and the remaining eight used either a case-control (n = 6) or cohort study (n = 2) design (see Table 1 for characteristics full of included studies). Using the Hoy quality assessment checklist (Hoy et al., 2012) , the overall risk of bias of the included studies was judged to be of moderate risk (mean score 3.5), in that the studies were susceptible to some bias but not enough to invalidate the results (see Table 2 for full list of assessment of bias criteria and corresponding studies Table 3 The prevalence of four main mental health conditions were reported (including clinically diagnosed and reported symptoms) (see Table 4 and Figures 2-9 for prevalence estimates and corresponding forest plots), specifically PTSD (10 studies; n = 2729), anxiety disorders (eight studies; n = 6003), MDD (seven studies; n = 5747) and acute stress disorder (three studies; n = 582). Also, we report on the prevalence of psychological distress (six studies, n = 2662), which provides an indication of possible clinically diagnosed issues related to MDD and anxiety disorders classified through GHQ-28 (De Almeida Vieira Monteiro, 2011; Lobo et al., 1986) . In interpreting the results presented, it should be noted that all comparisons and sub-group analyses were affected by substantial heterogeneity (I 2 range: 51.5%-99.6%). and Canada (6.1%). The effects of other factors on prevalence were less clear. All studies were in either high-(n = 7, prevalence 23%) or upper-middle income countries (n = 2, 7.6%). All studies were in the secondary care setting (23.6%), except one in tertiary care (5.7%). PTSD appeared more prevalent in staff aged 20-29 (28.4%) and 30-39 (26.7%) years, although there were limited studies conducted among other age groups or studies did not report age. Only one statistically significant moderating factor of level of exposure was identified in two or more studies, with highly exposed healthcare workers being associated with increased prevalence of PTSD symptoms compared with healthcare workers who were less exposed healthcare worker type Lai et al., 2020) . Females, nurses and higher exposed healthcare workers (healthcare workers who are more likely to come in contact with patients with the disease) were associated with increased prevalence of anxiety disorders. Covid-19 14.6%) or clinical settings (secondary 13.3%; secondary and tertiary 14.8%). Although there were differences in prevalence between age groups and the countries affected, these may reflect the limited evidence available. There were signs that age and country of location may be important moderating factors, but there were limited studies in both comparisons. The other statistically significant moderating factor which was identified in two or more studies was exposure rates, with higher exposed healthcare (defined by geographical location or place of work) workers being associated with increased prevalence of MDD (Lai et al., 2020; Liu et al., 2012; Su et al., 2007) . The least common mental health condition was acute stress disorder, where the estimated prevalence was 7.4% (95% CI: 4.3%, 10.6%). No study reported a statistically significant moderator for prevalence of acute stress for healthcare workers. The prevalence of psychological distress (using GHQ-28) was estimated at 25.5% (95% CI: 10.1%, 40.9%). Was the response rate for the study ≥75% (or a sub-analysis was performed that showed no difference in characteristics between responders and non-responders) Yes 0 0 0 0 0 No or NR 1 1 1 1 1 1 1 Were data collected directly from the subjects (as opposed to a proxy-a representative person)? Yes Was an acceptable case definition used in the study? Was the study instrument that measured prevalence/incidence shown to have reliability and validity (if necessary)? healthcare workers necessitates that healthcare services take responsibility for preventing and managing the effects on the physical and mental health of staff (Spoorthy et al., 2020) . Understanding the likelihood that staff will experience physical and mental health conditions provides an important initial step in developing and implementing services to manage their short-and long-term effects. Our systematic review identified and assessed the evidence on the incidence and prevalence of mental health conditions among healthcare workers during and after infectious disease pandemics. Importantly, our estimates are based on studies using only valid and reliable diagnostic criteria to improve accuracy. Although no studies were identified that looked at incidence, 43 studies reported the prevalence of mental health conditions in healthcare workers from infectious disease pandemics. When pooled through metaanalyses, we found that PTSD (21.7%), anxiety disorders (16.1%), MDD (13.4%) and acute stress disorder (7.4%) were frequently reported. These prevalence rates were not unusual. Previous reviews have reported comparable rates for anxiety disorders and MDD among healthcare workers during earlier phases of the current Covid-19 pandemic (Pappa et al., 2020) . We identified that preva- Was the sample a true or close representation of the target population? Yes 0 0 0 0 0 0 No or NR 1 1 1 1 1 1 Was some form of random selection used to select the sample or, was a census undertaken? Yes 0 0 No or NR 1 1 1 1 1 1 1 1 1 1 Was the response rate for the study ≥75% (or a sub-analysis was performed that showed no difference in characteristics between responders and non-responders) Yes 0 0 0 0 0 No or NR 1 1 1 1 1 1 1 Were data collected directly from the subjects (as opposed to a proxy-a representative person)? Yes Was an acceptable case definition used in the study? Was the study instrument that measured prevalence/incidence shown to have reliability and validity (if necessary)? Importantly, we identified moderating factors that may help to identify specific healthcare workers that are at risk from PTSD, anxiety disorders and MDD. Frontline staff, particularly nurses, who are likely to be highly exposed to the pandemic conditions were found to be at increased risk of having psychological problems than other healthcare workers. Similar findings have been previously reported for healthcare workers during other infectious disease outbreaks (Brooks et al., 2018; Kisely et al., 2020; Ricci-Cabello et al., 2020) . F I G U R E 2 Forest plot PTSD (combined after/before pandemic) providers before, during and after the pandemics (Kisely et al., 2020; Pappa et al., 2020; Ricci-Cabello et al., 2020; Schoonhoven et al., 2020) . This should be a priority given the importance of healthcare workers in tackling pandemics and their effects, the daily hazards that they face and the possible consequences for the health service and its patients if staff experience psychological problems (e.g. medical errors, patient safety). As pandemics can spread rapidly, consideration should be given to ongoing education and training of workers to ensure an understanding of the conditions and actions required to identify, protect themselves and others, and to control infectious spread. Staff should be aware and understand the possible psychological challenges that a pandemic can present in terms of a changing work environment and work patterns, the burden of an increasing workload, the effects of managing patients with distressing conditions and their own increased risks (Schoonhoven et al., 2020) . Although healthcare providers should have sufficient staff and resources to limit the impact F I G U R E 3 Forest plot prevalence posttraumatic (PTSD) symptoms (combined after/before pandemic) F I G U R E 5 Forest plot anxiety symptoms (combined after/before pandemic) on staff, this is increasingly challenging due to the imbalance between funding and increasing demands on services (Robertson et al., 2017) . Despite this, service providers should have plans in place for handling pandemics to limit the consequences for healthcare workers, communicating these effectively throughout (Schoonhoven et al., 2020) . These plans should encompass early detection and screening for symptoms of depression, anxiety and PTSD among workers, as this may reduce those developing more severe symptoms (Halfin, 2007 (Greenberg et al., 2008) or similar adapted approaches for healthcare (Hughes et al., 2012) . Our systematic review has certain strengths, including: it was produced following a research protocol registered on PROSPERO; used a robust multi-database search with the addition of reference checks; study selection, data extraction and assessment of study quality were undertaken using pre-piloted forms and processes; only studies using valid and reliable data collection tools with recognized threshold levels for diagnosing conditions were included; specific definitions for pandemics and for pre-and post-pandemic periods were used to ensure standardization of comparisons (Coffey et al., 2006; Dunstan et al., 2017; Foa & Tolin, 2000; Guest et al., 2018; Hoy et al., 2012; Kim et al., 2019; Kroenke et al., 2001; Lowe et al., 2008; Matza et al., 2010; Mossman et al., 2017; Park, 2012; Spitzer et al., 2006; Yohannes et al., 2019; Zimmerman et al., 2013) ; and, a public advisor was involved during the review. However, this systematic review also had certain limitations, such as: the evidence base is rapidly changing as the Covid-19 pandemic progresses, meaning that it is likely that some evidence will have emerged subsequent to our searches; only studies published in English language were included; screening of studies, data extraction and quality assessment were undertaken by a single reviewer, although decisions were checked by a second reviewer; and, where study details were lacking, further evidence was not obtained from study authors. The evidence-base was also affected by certain limitations. Studies tend to diagnose the prevalence of a single condition, when people may fulfil the diagnostic criteria for several conditions. Given that many mental health conditions are characterized by the same symptoms (e.g. symptom of arousal is common to PTSD and anxiety), it is inevitable that the prevalence of some conditions maybe be underestimated. The accuracy of prevalence estimates may be affected by the approach to diagnosing the condition, specifically whether a cut-off point on a scale or a clinical diagnosis by a physician was used. Importantly, we endeavoured to limit the impact of different diagnostic approaches by using only highly sensitive and specific tools for the prevalence estimates of conditions. As pooled prevalence rates were assessed through a visual inspection of confidence intervals rather than through calculating the difference between the confidence intervals, it is possible that borderline differences were considered statistically significant (i.e. type II error) (Payton et al., 2003) . Additionally, due to the multiple comparison there is also the risk of type I error occurring as no adjustments were made . We were unable to assess the effects of publication bias due to the substantial between-study heterogeneity and limited number of studies (Higgins, 2021) . Although prevalence studies provide an opportunity to estimate the need for mental health services, the proportion of people that will F I G U R E 9 Forest plot psychological distress actually use the services remains uncertain. A consistent approach to stratifying those who may demand mental health services is necessary and remains a challenge for future research. Healthcare workers remain a central part of any strategy responding to the Covid-19 pandemic, with policies focusing on managing the effects of the pandemic on already under pressure healthcare services. Despite their importance, many healthcare workers are experiencing psychological problems during Covid-19 (e.g. PTSD, anxiety disorders and MDD), which are similar to previous pandemics. This places the onus on providers of healthcare to ensure they have adequate plans in place for preventing, diagnosing and managing any mental health conditions arising in the short-and longer term. Although it is evident that certain healthcare workers may be at higher risk, further research would help to clarify who they are, and which interventions should be used to prevent and manage the different mental health conditions. The authors declare that there is no conflict of interest. The peer review history for this article is available at https://publo ns.com/publo n/10.1111/jan.15175. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. James Edward Hill https://orcid.org/0000-0003-1430-6927 Alison J. 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(traumatic stress or traumatic disorder* or stress disorder* or stress syndrome* or ptsd or posttraumatic or post traumatic or traumati* or stress reaction* or burnout or burn out).tw. 9 (depression or anxiety or depressive disorder*).tw.10 or/4-9 11 incidence/ or prevalence/ 12 (incidence or prevalence or survey or rapid assessment or situational assessment or cohort or cross sectional or surveillance or screening or level or presence or rate).tw. (longitudinal or follow-up or prospective or retrospective or observational or case control or epidemiological stud* or occurrence The Journal of Advanced Nursing (JAN) is an international, peer-reviewed, scientific journal. JAN contributes to the advancement of evidence-based nursing, midwifery and health care by disseminating high quality research and scholarship of contemporary relevance and with potential to advance knowledge for practice, education, management or policy. 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